# Patent

## Title
Assessment of risk for colorectal cancer

## Abstract

Disclosed is a method for identifying an individual who has an altered risk for developing colorectal cancer comprising detecting a single nucleotide polymorphism (SNP).

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a §371 National Stage of International Application No. PCT/CA2007/000993 filed on Jun. 5, 2007, which designates the United States, and which claims the priority of Canadian Application No. 2,547,824 filed on Jun. 5, 2006, and Canadian Application No. 2,548,375 filed on Jun. 13, 2006, and Canadian Application No. 2,579,588 filed on Feb. 21, 2007, the entire contents of which are incorporated herein by reference.
FIELD OF THE INVENTION
This invention relates to prediction of the susceptibility of an individual to colorectal cancer. Basis for the prediction lies in relating an individual's genetic makeup, as through molecular analysis, to the genetic makeup of a population of individuals.
BACKGROUND
During the course of evolution, spontaneous mutations arise in the genomes of organisms. Variations in genomic DNA sequences are created continuously at a rate of about 100 new base changes per individual (Kondrashov, 1995; Crow, 1995). These germ-line changes may produce an evolutionary advantage and be retained in the population, or they may be deleterious and ultimately eliminated. In many cases, equilibrium between multiple germline forms of a sequence is established within a population if reproductive ability of individuals containing either polymorphism is not affected. Over time, significant numbers of mutations have accumulated within the human population that may be observed to varying extents in geographically separated groups based upon the presence of common ancestors.
Colorectal cancer is the third most common cancer and the third most common cause of death from cancer for both men and women. Colorectal cancer is responsible for more deaths that are not due primarily to tobacco use than any other type of cancer and inflicts a huge financial burden. Early detection of some human tumors such as uterine cervical cancer has dramatically reduced mortality from this condition (Herzog, 2003). Early detection of colorectal cancer can reasonably be expected to prevent death from this condition by identifying patients at risk for the disease, or those with the disease in an early stage and allow life saving intervention. A validated genetic test for colorectal cancer predisposition will have clinical utility, allowing prevention of cancer mortality through targeted screening programs. There are good reasons to expect that at least some of the genetic risks of common disease is due to common variants—for example, based on evolutionary arguments, and the fact that most human genetic variation is common. Although approximately 20% of colorectal cancers have a familial component with relatives exhibiting a doubling of risk (Carstensen et al., 1996), less than 5% of colorectal cancer is explained by rare, highly penetrant genetic syndromes such as APC and HNPCC (de Leon et al., 1999). Familial colorectal cancer occurring in patterns inconsistent with classical inherited syndromes suggests that variation in genome sequence plays a major role in determining individual risk to colorectal cancer. These genetic causes appear complex due to a variety of reasons such as genetic heterogeneity, incomplete penetrance, phenocopies and variation in exposures to environmental co-factors etc. There is little insight into the genetic or environmental determinants of almost 90% of cases of human colorectal carcinoma (Lynch and de La, 2003).
Although common human genetic variation is limited compared to other species, it remains impractical to discover and test every one of the estimated 10,000,000 common genotype variants (Sachidanandam et al., 2001) as predictors of disease risk. Genotypic complexity is reduced through linkage disequilibrium that exists across long segments of the human genome with restriction in the diversity of haplotypes observed (Daly et al., 2001; Rioux et al., 2001; Liu et al., 2004). That is, single nucleotide polymorphisms found at specific locations within the human genome are inherited in conjunction with nucleotides that can be polymorphic that are physically located near by. In European genomes, allelic association between pairs of markers typically extends over 10-50k, although there is tremendous variability in the magnitude of association observed at any given distance (Clark et al., 1998; Kikuchi et al., 2003; Dunning et al., 2000; Abecasis et al., 2001). Genome-wide data (Gabriel et al., 2002; Reich et al., 2001; Dawson et al., 2002) supports the generality of this description as well as its application across populations. This confirms that measurement of single nucleotide polymotphisms at sites in tight linkage disequilibrium with adjacent genomic regions can provide information about the presence of diversity not just at sites actually measured, but also about large areas of the adjacent genome.
Numerous types of polymorphisms exist and are created when DNA sequences are either inserted or deleted from the genome. Another source of sequence variation results from the presence of repeated sequences in the genome variously termed short tandem repeats (STR), variable number of tandem repeats (VNTR), short sequence repeats (SSR) or microsatellites. These repeats commonly are comprised of 1 to 5 base pairs. Polymorphism occurs due to variation in the number of repeated sequences found at a particular locus.
The most common form of genomic variability are single nucleotide polymorphisms or SNPs. SNPs account for as much as 90% of human DNA polymorphism (Collins et al., 1998). SNPs are single base pair positions in genomic DNA at which different sequence alternatives (genotypes) exist in a population. By common definition, the least frequent allele occurs at least 1% of the time. These nucleotide substitutions may be a transition, which is the substitution of one purine by another purine or the substitution of one pyrimidine by another, or they may be transversions in which a purine is replaced by a pyrimidine or vice versa.
Typically SNPs are observed in about 1 in 1000 base pairs (Wang et al., 1998; Taillon-Miller et al., 1999). The frequency of SNPs varies with the type and location of the change. Specifically, two-thirds of the substitutions involve the CT (GA) type, which may occur due to 5-methylcytosine deamination reactions that occur commonly. SNPs occur at a much higher frequency in non-coding regions than they do in coding regions.
Known environmental risk factors for the development of colorectal cancer include obesity, absence of a vegetable-rich diet and a sedentary life style. Estrogen use in post menopausal women is associated with reduced individual risk for the development of colorectal cancer. The mechanism of risk reduction through the chronic administration of estrogen is unknown and a way of quantifying altered risk associated with estrogen use is not obvious. It is known that expression of the estrogen receptor beta on colorectal tumors is reduced compared to undiseased adjacent tissue. It is not known if this observation has any relevance to the reduced incidence of colorectal cancer in women taking postmenopausal estrogen, nor is it useful in predicting individual risk for the development of colorectal cancer. It is not known if single nucleotide polymorphisms within the estrogen receptor beta can modify the risk of developing colorectal cancer conferred by certain polymorphisms in other risk genes.
SUMMARY OF THE INVENTION
It has been discovered that polymorphic variations in a number of loci in human genomic DNA are associated with susceptibility to colorectal cancer. This invention thus includes methods for identifying a subject at risk of colorectal and/or determining risk of colorectal cancer in a subject, which comprise detecting the presence or absence of one or more polymorphic variations associated with colorectal cancer in a nucleic acid sample from the subject. In a specific embodiment, this invention relates to identifying an individual who is at altered risk for developing colorectal cancer based on the presence of specific genotypes defined by 85 single nucleotide polymorphism (SNPs), observed alone or in combination. Through large scale genotyping studies on 2,373 blood samples from patients with colorectal cancer and 2,296 control samples from unaffected individuals we have identified 85 polymorphic markers found in 32 genes which are found more frequently in patients with colorectal cancer than in those without this disease. These markers, or those in close linkage disequilibrium, may change the composition, function or abundance of the elements of cellular constituents resulting in a predisposition to colorectal cancer. Measuring these markers in individuals who do not ostensibly have colorectal cancer will identify those at heightened risk for the subsequent development of colorectal cancer, providing benefit for, but not limited to, individuals, insurers, care givers and employers. Genes containing colorectal cancer-associated polymorphic markers that we have identified and genes found in linkage disequilibrium with these that we have identified are valuable targets for the development of therapeutics that inhibit or augment the activity of the gene products of these genes for therapeutic use in, but not restricted to, colorectal cancer. Information obtained from the detection of SNPs associated with colorectal cancer is of great value in the treatment and prevention of this condition.
Accordingly, one aspect of the present invention provides a method for diagnosing a genetic predisposition to colorectal cancer in a subject, comprising obtaining a sample containing at least one polynucleotide from the subject and analyzing the polynucleotide to detect the genetic polymorphism wherein the presence or absence of the polymorphism is associated with an altered susceptibility to developing colorectal cancer. In one embodiment, one or more of the 85 polymorphisms found distributed among 32 genes that we have identified may be used.
Another aspect of the present invention provides an isolated nucleic acid sequence comprising at least 16 contiguous nucleotides or their complements found in the genomic sequences of the 32 genes adjacent to and including the 85 polymorphic sites the inventors have identified to be associated with colorectal cancer.
Yet another aspect of the invention provides a method for treating colorectal cancer comprising obtaining a sample of biological material containing at least one polynucleotide from the subject, analyzing the polynucleotides to detect the presence of at least one polymorphism associated with colorectal cancer and treating the subject in such a way as to counteract the effect of any such polymorphism detected.
Still another aspect of the invention provides a method for the prophylactic treatment of a subject identified with a genetic predisposition to colorectal cancer identified through the measurement of all or some of the 85 polymorphic SNP markers described in Tables 1 to 85.
Through large scale genotyping studies on 1231 blood samples from patients with colorectal cancer and 1240 control samples from unaffected individuals we have identified polymorphic sites within the estrogen receptor beta gene that act as a further risk predictor for colorectal cancer when considered along with colorectal cancer risk-predicting markers on chromosome 8q24. While polymorphic sites within the estrogen receptor beta gene, which is located at chromosome 14q23, are not predictors of colorectal cancer independent of other markers, they strongly modify the predictive power of markers at chromosome 8q24.
Accordingly, one or more of the polymorphic sites within 8q24 may be used in conjunction with one or more polymorphisms within the estrogen beta receptor locus which is found at chromosome 14q23 to more accurately predict risk of colorectal cancer as described in Table 86.
Further scope of the applicability of the present invention will become apparent from the detailed description provided below. It should be understood however, that the following detailed description and examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modification within the spirit and scope of the invention will become apparent to those skilled in the art from the following detailed description.
Tables 1 to 85 report the result of a genotyping analysis of 4,669 samples by measuring 99,632 single nucleotide polymorphisms in peripheral blood DNA from 2,475 subjects (1,234 cases with colorectal cancer and 1,241 age matched individuals undiseased at the time of testing), and validating the identified CRC-associated alleles by using peripheral blood DNA from a second, different, group of 2,194 subjects (1,139 cases with colorectal cancer and 1,055 age matched individuals undiseased at the time of testing).


DETAILED DESCRIPTION OF THE INVENTION
It has been discovered that polymorphic variants in a number of sequences, SEQ ID NOs:1 to 1760 are associated with an altered risk of developing colorectal cancer in subjects. The present invention thus provides SNPs associated with colorectal cancer, nucleic acid molecules containing SNPs, methods and reagents for the detection of the SNPs disclosed herein, uses of these SNPs for the development of detection reagents, and assays or kits that utilize such reagents. The colorectal cancer-associated SNPs disclosed herein are useful for diagnosing, screening for, and evaluating predisposition to colorectal cancer and related pathologies in humans. Furthermore, such SNPs and their encoded products are useful targets for the development of therapeutic agents.
A large number of colorectal cancer-associated SNPs have been identified by genotyping DNA from 4,669 individuals, 2,373 of these individuals having been previously diagnosed with colorectal cancer and 2,296 being “control” or individuals thought to be free of colorectal cancer.
The present invention thus provides individual SNPs associated with colorectal cancer, genomic sequences (SEQ ID NOs:1761 to 1790) containing SNPs, and transcript sequences amino acid sequences. The invention includes methods of detecting these polymorphisms in a test sample, methods of determining the risk of an individual of having or developing colorectal cancer, methods of screening for compounds useful for treating disorders associated with a variant gene/protein such as colorectal cancer, compounds identified by these screening methods, methods of using the disclosed SNPs to select a treatment strategy, methods of treating a disorder associated with a variant gene/protein (i.e., therapeutic methods), and methods of using the SNPs of the present invention for human identification.
When the presence in the genome of an individual of a particular base, e.g., adenine, at a particular location in the genome correlates with an increased probability of that individual contracting colorectal cancer vis-à-vis a population not having that base at that location in the genome, that individual is said to be at “increased risk” of contracting colorectal cancer, i.e., to have an increased susceptibility. In certain cases, this effect can be a “dominant” effect in which case such increased probability exists when the base is present in one or the other or both alleles of the individual. In certain cases, the effect can be said to be “recessive”, in which case such increased probability exists only when the base is present in both alleles of the individual.
When the presence in the genome of an individual of a particular base, e.g., adenine, at a particular location in the genome decreases the probability of that individual contracting colorectal cancer vis-à-vis a population not having that base at that location in the genome, that individual is said to be at “decreased risk” of contracting colorectal cancer, i.e., to have a decreased susceptibility. Such an allele is sometimes referred to in the art as being “protective”. As with increased risk, it is also possible for a decreased risk to be characterized as dominant or recessive.
An “altered risk” means either an increased or a decreased risk.
The genetic analysis detailed below linked colorectal cancer with SNPs in the human genome. A SNP is a particular type of polymorphic site, a polymorphic site being a region in a nucleic acid sequence at which two or more alternative nucleotides are observed in a significant number of individuals from a population. A polymorphic site may be a nucleotide sequence of two or more nucleotides, an inserted nucleotide or nucleotide sequence, a deleted nucleotide or nucleotide sequence, or a microsatellite, for example. A polymorphic site that is two or more nucleotides in length may be 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or more, 20 or more, 30 or more, 50 or more, 75 or more, 100 or more, 500 or more, or about 1000 nucleotides in length, where all or some of the nucleotide sequences differ within the region. Each of the specific polymorphic sites found in SEQ ID NOs:1761 to 1790 is a “single nucleotide polymorphism” or a “SNP.”
Where there are two, three, or four alternative nucleotide sequences at a polymorphic site, each nucleotide sequence is referred to as a “polymorphic variant” or “nucleic acid variant.” Where two polymorphic variants exist, for example, the polymorphic variant represented in a majority of samples from a population is sometimes referred to as a “prevalent allele” and the polymorphic variant that is less prevalently represented is sometimes referred to as an “uncommon allele.” An individual who possesses two prevalent alleles or two uncommon alleles is “homozygous” with respect to the polymorphism, and an individual who possesses one prevalent allele and one uncommon allele is “heterozygous” with respect to the polymorphism. Individuals who are homozygous with respect to one allele are sometimes predisposed to a different phenotype as compared to individuals who are heterozygous or homozygous with respect to another allele.
A genotype or polymorphic variant may also be expressed in terms of a “haplotype,” which refers to the identity of two or more polymorphic variants occurring within genomic DNA on the same strand of DNA. For example, two SNPs may exist within a gene where each SNP position may include a cytosine variation or an adenine variation. Certain individuals in a population may carry an allele (heterozygous) or two alleles (homozygous) having the gene with a cytosine at each SNP position. As the two cytosines corresponding to each SNP in the gene travel together on one or both alleles in these individuals, the individuals can be characterized as having a cytosine/cytosine haplotype with respect to the two SNPs in the gene.
A “phenotype” is a trait which can be compared between individuals, such as presence or absence of a condition, for example, occurrence of colorectal cancer.
Polymorphic variants are often reported without any determination of whether the variant is represented in a significant fraction of a population. Some reported variants are sequencing errors and/or not biologically relevant. Thus, it is often not known whether a reported polymorphic variant is statistically significant or biologically relevant until the presence of the variant is detected in a population of individuals and the frequency of the variant is determined.
A polymorphic variant may be detected on either or both strands of a double-stranded nucleic acid. Also, a polymorphic variant may be located within an intron or exon of a gene or within a portion of a regulatory region such as a promoter, a 5′ untranslated region (UTR), a 3′ UTR, and in DNA (e.g., genomic DNA (gDNA) and complementary DNA (cDNA)), RNA (e.g., mRNA, tRNA, and rRNA), or a polypeptide. Polymorphic variations may or may not result in detectable differences in gene expression, polypeptide structure, or polypeptide function.
In our genetic analysis associating colorectal cancer with the polymorphic variants set forth in the tables, samples from individuals having been diagnosed with colorectal cancer and individuals not having cancer were allelotyped and genotyped. The allele frequency for each polymorphic variant among cases and controls was determined. These allele frequencies were compared in cases and controls, or combinations. Particular SNPs were thus found to be associated with colorectal cancer when genotype and haplotype frequency differences calculated between case and control pools were established to be statistically significant.
As mentioned above, polymorphic variants can travel together. Such variants are said to be in “linkage disequilibrium” so that heritable elements e.g., alleles that have a tendency to be inherited together instead of being inherited independently by random assortment are in linkage disequilibrium. Alleles are randomly assorted or inherited independently of each other if the frequency of the two alleles together is the product of the frequencies of the two alleles individually. For example, if two alleles at different polymorphic sites are present in 50% of the chromosomes in a population, then they would be said to assort randomly if the two alleles are present together on 25% of the chromosomes in the population. A higher percentage would mean that the two alleles are linked. For example, a first polymorphic site P1 having two alleles, e.g. A and C—each appearing in 50% of the individuals in a given population, is said to be in linkage disequilibrium with a second polymorphic site P2 having two alleles e.g. G and T—each appearing in 50% of the individuals in a given population, if particular combinations of alleles are observed in individuals at a frequency greater than 25% (if the polymorphic sites are not linked, then one would expect a 50% chance of an individual having A at P1 and a 50% chance of having G at P2 thus leading to a 25% chance of having the combination of A at P1 and G at P2 together). Heritable elements that are in linkage disequilibrium are said to be “linked” or “genetically linked” to each other.
One can see that in the case of a group of SNPs that are in linkage disequilibrium with each other, knowledge of the existence of all such SNPs in a particular individual generally provides redundant information. Thus, when identifying an individual who has an altered risk for developing colorectal cancer according to this invention, it is necessary to detect only one SNP of such a group of SNPs associated with an altered risk of developing colorectal cancer.
It has been shown that each SNP in the genomic sequences identified as SEQ ID NOs:1761 to 1790 is associated with the occurrence of colorectal cancer. Thus, featured herein are methods for identifying a risk of colorectal cancer in a subject, which includes detecting the presence or absence of one or more of the SNPs described herein in a human nucleic acid sample.
Three different analyses were performed for each marker: (a) a test of trend across the 3 genotypes (Sasieni et al. 1997); (b) a dominant model where the homozygous genotype for allele “B” is combined with the prevalent heterozygote genotype; and (c) a recessive model where the homozygous genotype for allele “A” is combined with the heterozygous genotype. Using permutation analysis, the empirical p-value for the maximum of these three test statistics was calculated. Odds ratios measuring the strength of the association are also reported for the model corresponding to the largest of the three test statistics.
Pertinent results for each SNP are summarized in the tables: Chromosomal number and position-using the International Human Genome Sequencing Consortium build 35 (http://www.ncbi.nlm.nih.gov/genome/seq/) as made available by the National Center for Biotechnology Information (NCBI), National Library of Medicine, Building 38A, Bethesda, Md. 20894 U.S.A., gene marker name-using the nomenclature of the NCBI dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) and gene name-using the unigene naming convention. Under the “Case Flag” the number 1 designates Cases and the number 0 designates Controls. The identity of the base designated “A” in the analysis is indicated where 1=A (adenine), 2=C (cytosine), 3=G (guanine) and 4=T (thymidine). “B” indicates the polymorphic allele. AA, AB, BB are the counts of the number of individuals with the given genotype, by cases/controls. For dominant models, an odds ratio measuring the increase in risk associated with one or two copies of allele B is calculated. For recessive models, an odds ratio associated with exactly two copies of allele B is calculated. For the trend models, the Mantel-Haenszel odds ratio showing the increase in risk with each additional copy of allele B is calculated.
It has been discovered that each polymorphic variation in the genomic sequences identified as SEQ ID NOs:1761 to 1790 is associated with the occurrence of colorectal cancer. Thus, featured herein are methods for identifying a risk of colorectal cancer in a subject, which comprises detecting the presence or absence of one or more of the polymorphic variations described herein in a human nucleic acid sample. The polymorphic variation, SNP, are detailed in the tables.
Methods for determining whether a subject is susceptible to, i.e., at risk of colorectal cancer are provided herein. These methods include detecting the presence or absence of one or more polymorphic variations, i.e., SNPs, associated with colorectal cancer in a sample from a subject.
SNPs can be associated with a disease state in humans or in animals. The association can be direct, as in conditions where the substitution of a base results in alteration of the protein coding sequence of a gene which contributes directly to the pathophysiology of the condition. Common examples of this include diseases such as sickle cell anemia and cystic fibrosis. The association can be indirect when the SNP plays no role in the disease, but is located close to the defective gene such that there is a strong association between the presence of the SNP and the disease state. Because of the high frequency of SNPs within the genome, there is a greater probability that a SNP will be linked to a genetic locus of interest than other types of genetic markers.
Disease-associated SNPs can occur in coding and non-coding regions of the genome. When located in the coding region altered function of the ensuing protein sequence may occur. If it occurs in the regulatory region of a gene it may affect expression of the protein. If the protein is involved in protecting the body against pathological conditions this can result in disease susceptibility.
Numerous methods exist for the measurement of specific SNP genotypes. Individuals carrying mutations in one or more SNPs of the present invention may be detected at the DNA level by a variety of techniques. Nucleic acids for diagnosis may be obtained from a patient's cells, such as from blood, urine, saliva, tissue biopsy and autopsy material.
The genomic DNA may be used directly for detection or may be amplified enzymatically by using PCR prior to analysis (Saiki et al., 1986). RNA or cDNA may also be used in the same ways. As an example, PCR primers complementary to the nucleic acid of one or more SNPs of the present invention can be used to identify and analyze the presence or absence of the SNP. For example, deletions and insertions can be detected by a change in size of the amplified product in comparison to the normal genotype. Point mutations can be identified by hybridizing amplified DNA to radiolabeled SNP RNA of the present invention or alternatively, radiolabeled SNP antisense DNA sequences of the present invention. Perfectly matched sequences can be distinguished from mismatched duplexes by RNase A digestion or by differences in melting temperatures.
Sequence differences between a reference gene and genes having mutations also may be revealed by direct DNA sequencing. In addition, cloned DNA segments may be employed as probes to detect specific DNA segments. The sensitivity of such methods can be greatly enhanced by appropriate use of PCR or another amplification method. For example, a sequencing primer is used with double-stranded PCR product or a single-stranded template molecule generated by a modified PCR. The sequence determination is performed by conventional procedures with radiolabeled nucleotide or by automatic sequencing procedures with fluorescent-tags.
Genetic testing based on DNA sequence differences may be achieved by detection of alteration in electrophoretic mobility of DNA fragments in gels, with or without denaturing agents. Small sequence deletions and insertions can be visualized by high resolution gel electrophoresis. DNA fragments of different sequences may be distinguished on denaturing formamide gradient gels in which the mobilities of different DNA fragments are retarded in the gel at different positions according to their specific melting or partial melting temperatures (Myers et al., 1985).
Sequence changes at specific locations also may be revealed by nuclease protection assays, such as RNase and S1 protection or the chemical cleavage method (Cotton et al., 1988).
Thus, the detection of a specific DNA sequence may be achieved by methods which include, but are not limited to, hybridization, RNase protection, chemical cleavage, direct DNA sequencing or the use of restriction enzymes, (e.g., restriction fragment length polymorphisms (“RFLP”) and Southern blotting of genomic DNA).
In addition to more conventional gel-electrophoresis and DNA sequencing, mutations also can be detected by in situ analysis.
Genetic mutations can be identified by hybridizing a sample and control nucleic acids, e.g., DNA or RNA, to high density arrays containing hundreds or thousands of oligonucleotide probes (Cronin et al., 1996; Kozal et al., 1996). For example, genetic mutations can be identified in two-dimensional arrays containing light-generated DNA probes as described in Cronin et al., supra. Briefly, a first hybridization array of probes can be used to scan through long stretches of DNA in a sample and control to identify base changes between the sequences by making linear arrays of sequential overlapping probes. This step allows the identification of point mutations. This step is followed by a second hybridization array that allows the characterization of specific mutations by using smaller, specialized probe arrays complementary to all variants or mutations detected. Each mutation array is composed of parallel probe sets, one complementary to the wild-type gene and the other complementary to the mutant gene. Specific mutations can also be determined through direct sequencing of one or both strands of DNA using dideoxy nucleotide chain termination chemistry, electrophoresis through a semi-solid matrix and fluorescent or radioactive chain length detection techniques. Further mutation detection techniques may involve differential susceptibility of the polymorphic double strand to restriction endonuclease digestion, or altered electrophoretic gel mobility of single or double stranded gene fragments containing one polymorphic form. Other techniques to detect specific DNA polymorphisms or mutation may involve evaluation of the structural characteristics at the site of polymorphism using nuclear magnetic resonance or x-ray diffraction techniques.
These genetic tests are useful for prognosing and/or diagnosing colorectal cancer and often are useful for determining whether an individual is at an increased or decreased risk of developing or having colorectal cancer.
Thus, the invention includes a method for identifying a subject at risk of colorectal cancer, which includes detecting in a nucleic acid sample from the subject the presence or absence of a SNP associated with colorectal cancer at a polymorphic site in a nucleotide sequence identified as SEQ ID NOs:1 to 1790.
Results from prognostic tests may be combined with other test results to diagnose colorectal cancer. For example, prognostic results may be gathered, a patient sample may be ordered based on a determined predisposition to colorectal cancer, the patient sample analyzed, and the results of the analysis may be utilized to diagnose colorectal cancer. Also colorectal cancer diagnostic methods can be developed from studies used to generate prognostic/diagnostic methods in which populations are stratified into subpopulations having different progressions of colorectal cancer. In another embodiment, prognostic results may be gathered; a patient's risk factors for developing colorectal cancer analyzed (e.g., age, family history); and a patient sample may be ordered based on a determined predisposition to colorectal cancer. In an alternative embodiment, the results from predisposition analyses may be combined with other test results indicative of colorectal cancer, which were previously, concurrently, or subsequently gathered with respect to the predisposition testing. In these embodiments, the combination of the prognostic test results with other test results can be probative of colorectal cancer, and the combination can be utilized as a colorectal cancer diagnostic.
Risk of colorectal cancer sometimes is expressed as a probability, such as an odds ratio, percentage, or risk factor. The risk is based upon the presence or absence of one or more of the SNP variants described herein, and also may be based in part upon phenotypic traits of the individual being tested. Methods for calculating risk based upon patient data are well known (Agresti, 2001). Allelotyping and genotyping analyses may be carried out in populations other than those exemplified herein to enhance the predictive power of the prognostic method. These further analyses are executed in view of the exemplified procedures described herein, and may be based upon the same polymorphic variations or additional polymorphic variations. Risk determinations for colorectal cancer are useful in a variety of applications. In one embodiment, colorectal cancer risk determinations are used by clinicians to direct appropriate detection, preventative and treatment procedures to subjects who most require these. In another embodiment, colorectal cancer risk determinations are used by health insurers for preparing actuarial tables and for calculating insurance premiums.
The nucleic acid sample typically is isolated from a biological sample obtained from a subject. For example, nucleic acid can be isolated from blood, saliva, sputum, urine, cell scrapings, and biopsy tissue. The nucleic acid sample can be isolated from a biological sample using standard techniques. The nucleic acid sample may be isolated from the subject and then directly utilized in a method for determining the presence of a polymorphic variant, or alternatively, the sample may be isolated and then stored (e.g., frozen) for a period of time before being subjected to analysis.
The presence or absence of a polymorphic variant is determined using one or both chromosomal complements represented in the nucleic acid sample. Determining the presence or absence of a polymorphic variant in both chromosomal complements represented in a nucleic acid sample is useful for determining the zygosity of an individual for the polymorphic variant (i.e., whether the individual is homozygous or heterozygous for the polymorphic variant). Any oligonucleotide-based diagnostic may be utilized to determine whether a sample includes the presence or absence of a polymorphic variant in a sample. For example, primer extension methods, ligase sequence determination methods (e.g., U.S. Pat. Nos. 5,679,524 and 5,952,174, and WO 01/27326), mismatch sequence determination methods (e.g., U.S. Pat. Nos. 5,851,770; 5,958,692; 6,110,684; and 6,183,958), microarray sequence determination methods, restriction fragment length polymorphism (RFLP), single strand conformation polymorphism detection (SSCP) (e.g., U.S. Pat. Nos. 5,891,625 and 6,013,499), PCR-based assays (e.g., TAQMANTM PCR System (Applied Biosystems)), and nucleotide sequencing methods may be used.
Oligonucleotide extension methods typically involve providing a pair of oligonucleotide primers in a polymerase chain reaction (PCR) or in other nucleic acid amplification methods for the purpose of amplifying a region from the nucleic acid sample that comprises the polymorphic variation. One oligonucleotide primer is complementary to a region 3′ of the polymorphism and the other is complementary to a region 5′ of the polymorphism. A PCR primer pair may be used in methods disclosed in U.S. Pat. Nos. 4,683,195; 4,683,202, 4,965,188; 5,656,493; 5,998,143; 6,140,054; WO 01/27327; and WO 01/27329 for example. PCR primer pairs may also be used in any commercially available machines that perform PCR, such as any of the GENEAMPTM, systems available from Applied Biosystems. Also, those of ordinary skill in the art will be able to design oligonucleotide primers based upon the nucleotide sequences set forth in SEQ ID NOs:1 to 1790.
Also provided is an extension oligonucleotide that hybridizes to the amplified fragment adjacent to the polymorphic variation. An adjacent fragment refers to the 3′ end of the extension oligonucleotide being often 1 nucleotide from the 5′ end of the polymorphic site, and sometimes 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides from the 5′ end of the polymorphic site, in the nucleic acid when the extension oligonucleotide is hybridized to the nucleic acid. The extension oligonucleotide then is extended by one or more nucleotides, and the number and/or type of nucleotides that are added to the extension oligonucleotide determine whether the polymorphic variant is present. Oligonucleotide extension methods are disclosed, for example, in U.S. Pat. Nos. 4,656,127; 4,851,331; 5,679,524; 5,834,189; 5,876,934; 5,908,755; 5,912,118; 5,976,802; 5,981,186; 6,004,744; 6,013,431; 6,017,702; 6,046,005; 6,087,095; 6,210,891; and WO 01/20039. Oligonucleotide extension methods using mass spectrometry are described, for example, in U.S. Pat. Nos. 5,547,835; 5,605,798; 5,691,141; 5,849,542; 5,869,242; 5,928,906; 6,043,031; and 6,194,144. Multiple extension oligonucleotides may be utilized in one reaction, which is referred to as multiplexing.
A microarray can be utilized for determining whether a SNP is present or absent in a nucleic acid sample. A microarray may include any oligonucleotides described herein, and methods for making and using oligonucleotide microarrays suitable for diagnostic use are disclosed in U.S. Pat. Nos. 5,492,806; 5,525,464; 5,589,330; 5,695,940; 5,849,483; 6,018,041; 6,045,996; 6,136,541; 6,142,681; 6,156,501; 6,197,506; 6,223,127; 6,225,625; 6,229,911; 6,239,273; WO 00/52625; WO 01/25485; and WO 01/29259. The microarray typically comprises a solid support and the oligonucleotides may be linked to this solid support by covalent bonds or by non-covalent interactions. The oligonucleotides may also be linked to the solid support directly or by a spacer molecule. A microarray may comprise one or more oligonucleotides complementary to a SNP set forth in the tables.
A kit also may be utilized for determining whether a polymorphic variant is present or absent in a nucleic acid sample. A kit can include one or more pairs of oligonucleotide primers useful for amplifying a fragment of a nucleotide sequence of interest, where the fragment includes a polymorphic site. The kit sometimes comprises a polymerizing agent, for example, a thermo-stable nucleic acid polymerase such as one disclosed in U.S. Pat. No. 4,889,818 or 6,077,664. Also, the kit often comprises an elongation oligonucleotide that hybridizes to the nucleotide sequence in a nucleic acid sample adjacent to the polymorphic site. Where the kit includes an elongation oligonucleotide, it can also include chain elongating nucleotides, such as dATP, dTTP, dGTP, dCTP, and dITP, including analogs of dATP, dTTP, dGTP, dCTP and dITP, provided that such analogs are substrates for a thermo-stable nucleic acid polymerase and can be incorporated into a nucleic acid chain elongated from the extension oligonucleotide. Along with chain elongating nucleotides would be one or more chain terminating nucleotides such as ddATP, ddTTP, ddGTP, ddCTP. The kit can include one or more oligonucleotide primer pairs, a polymerizing agent, chain elongating nucleotides, at least one elongation oligonucleotide, and one or more chain terminating nucleotides. Kits optionally include buffers, vials, microtiter plates, and instructions for use.
An individual identified as being susceptible to colorectal cancer may be heterozygous or homozygous with respect to the allele associated with an increased risk of colorectal cancer, as indicated in the tables. A subject homozygous for an allele associated with an increased risk of colorectal cancer is at a comparatively high risk of colorectal cancer as far as that SNP is concerned whether or not the allelic effect has been determined to be dominant or recessive. A subject who is heterozygous for an allele associated with an increased risk of colorectal cancer, in which the allelic effect is recessive would likely be at a comparatively reduced risk of colorectal cancer predicted by that SNP.
Individuals carrying mutations in one or more SNP of the present invention may be detected at the protein level by a variety of techniques. Cells suitable for diagnosis may be obtained from a patient's blood, urine, saliva, tissue biopsy and autopsy material.
Also featured are methods for determining risk of colorectal cancer and/or identifying a subject at risk of colorectal cancer by contacting a polypeptide or protein encoded by a nucleotide sequence from a subject with an antibody that specifically binds to an epitope associated with an altered, usually increased risk of colorectal cancer in the polypeptide.
Isolated Nucleic Acids
Oligonucleotides can be linked to a second moiety, which can be another nucleic acid molecule to provide, for example, a tail sequence (e.g., a polyadenosine tail), an adapter sequence (e.g., phage M13 universal tail sequence), etc. Alternatively, the moiety might be one that facilitates linkage to a solid support or a detectable label, e.g., a radioactive label, a fluorescent label, a chemiluminescent label, a paramagnetic label, etc.
Nucleic acid sequences shown in the tables can be used for diagnostic purposes for detection and control of polypeptide expression. Also, oligonucleotide sequences such as antisense RNA, small-interfering RNA (siRNA) and DNA molecules and ribozymes that function to inhibit translation of a polypeptide are part of this invention.
Antisense RNA and DNA molecules, siRNA and ribozymes can be prepared by known methods. These include techniques for chemically synthesizing oligodeoxyribonucleotides such as solid phase phosphoramidite chemical synthesis. Alternatively, RNA molecules may be generated by in vitro and in vivo transcription of DNA sequences encoding the antisense RNA molecule. Such DNA sequences can be incorporated into vectors which incorporate suitable RNA polymerase promoters such as the T7 or SP6 polymerase promoters, or antisense cDNA constructs that synthesize antisense RNA constitutively or inducibly, depending on the promoter used, can be introduced stably into cell lines.
DNA encoding a polypeptide can also be used in the diagnosis of colorectal cancer, resulting from aberrant expression of a target gene. For example, the nucleic acid sequence can be used in hybridization assays of biopsies or autopsies to diagnose abnormalities of expression or function (e.g., Southern or Northern blot analysis, in situ hybridization assays).
Expression of a polypeptide during embryonic development can also be determined using nucleic acid encoding the polypeptide, particularly production of a functionally impaired polypeptide that is the cause of colorectal cancer. In situ hybridizations using a polypeptide as a probe can be employed to predict problems related to colorectal cancer. Administration of human active polypeptide, recombinantly produced can be used to treat disease states related to functionally impaired polypeptide. Alternatively, gene therapy approaches may be employed to remedy deficiencies of functional polypeptide or to replace or compete with a dysfunctional polypeptide.
Included as part of this invention are nucleic acid vectors, often expression vectors, which contain a nucleotide sequence set forth in the tables. A vector is a nucleic acid molecule capable of transporting another nucleic acid to which it has been linked and can include a plasmid, cosmid, or viral vector. The vector can be capable of autonomous replication or it can integrate into a host DNA. Viral vectors may include replication defective retroviruses, adenoviruses and adeno-associated viruses for example.
A vector can include a nucleotide sequence from the tables in a form suitable for expression of an encoded protein or nucleic acid in a host cell. The recombinant expression vector generally includes one or more regulatory sequences operatively linked to the nucleic acid sequence to be expressed. A regulatory sequence includes promoters, enhancers and other expression control elements (e.g., polyadenylation signals). Regulatory sequences include those that direct constitutive expression of a nucleotide sequence, as well as tissue-specific regulatory and/or inducible sequences. The design of the expression vector can depend on such factors as the choice of the host cell to be transformed, the level of expression of polypeptide desired, etc. Expression vectors can be introduced into host cells to produce the desired polypeptides, including fusion polypeptides.
Recombinant expression vectors can be designed for expression of polypeptides in prokaryotic or eukaryotic cells. For example, the polypeptides can be expressed in E. coli, insect cells (e.g., using baculovirus expression vectors), yeast cells, or mammalian cells. Suitable host cells are discussed further by Goeddel (Goeddel, 1990). A recombinant expression vector can also be transcribed and translated in vitro, for example using T7 promoter regulatory sequences and T7 polymerase.
Expression of polypeptides in prokaryotes can be carried out in E. coli with vectors containing constitutive or inducible promoters directing the expression of either fusion or non-fusion polypeptides. Fusion vectors add a number of amino acids to a polypeptide. Such fusion vectors typically serve to increase expression of recombinant polypeptide, to increase the solubility of the recombinant polypeptide and/or to aid in the purification of the recombinant polypeptide by acting as a ligand during purification. Often, a proteolytic cleavage site is introduced at the junction of the fusion moiety and the recombinant polypeptide to enable separation of the recombinant polypeptide from the fusion moiety after purification of the fusion polypeptide. Such enzymes, and their cognate recognition sequences, include Factor Xa, thrombin and enterokinase. Typical fusion expression vectors include pGEX (Pharmacia Biotech Inc; (Smith & Johnson, 1988)), pMAL (New England Biolabs, Beverly, Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuse glutathione S-transferase (GST), maltose E binding polypeptide, or polypeptide A, respectively, to the target recombinant polypeptide.
Purified fusion polypeptides can be used in screening assays and to generate antibodies specific for polypeptides. In a therapeutic embodiment, fusion polypeptide expressed in a retroviral expression vector can be used to infect bone marrow cells that are subsequently transplanted into irradiated recipients. The pathology of the subject recipient is then examined after sufficient time has passed.
Expressing a polypeptide in host bacteria with an impaired capacity to proteolytically cleave the recombinant polypeptide can be used to maximize recombinant polypeptide expression (Gottesman, 1990). The nucleotide sequence of the nucleic acid to be inserted into an expression vector can be changed so that the individual codons for each amino acid are those preferentially utilized in E. coli (Wada et al., 1992).
When used in mammalian cells, the expression vector's control functions are often provided by viral regulatory elements. For example, commonly used promoters are derived from polyoma, Adenovirus 2, cytomegalovirus and Simian Virus 40. Recombinant mammalian expression vectors can be capable of directing expression of the nucleic acid in a particular cell type (e.g., tissue-specific regulatory elements are used to express the nucleic acid). Examples of suitable tissue-specific promoters include an albumin promoter (Pinkert et al., 1987), lymphoid-specific promoters (Calame and Eaton, 1988), promoters of immunoglobulins (Banerji et al., 1983; Queen and Baltimore, 1983), neuron-specific promoters (Byrne and Ruddle, 1989), pancreas-specific promoters (Edlund et al., 1985), and mammary gland-specific promoters (e.g., milk whey promoter; U.S. Pat. No. 4,873,316 and European Application Publication No. 264,166). Developmentally-regulated promoters are sometimes utilized, for example, the murine hox promoters (Kessel and Gruss, 1990) and the .alpha.-fetopolypeptide promoter (Camper and Tilghman, 1989).
A nucleic acid from one of the tables might be cloned into an expression vector in an antisense orientation. Regulatory sequences (e.g., viral promoters and/or enhancers) operatively linked to a nucleic acid cloned in the antisense orientation can be chosen for directing constitutive, tissue specific or cell type specific expression of antisense RNA in a variety of cell types. Antisense expression vectors can be in the form of a recombinant plasmid, phagemid or attenuated virus.
The invention includes host cells having a nucleotide sequence from the tables within a recombinant expression vector or a fragment of such a sequence, which facilitate homologous recombination into a specific site of the host cell genome. Terms such as host cell and recombinant host cell refer not only to the particular subject cell but also to the progeny of a cell. Because certain modifications may occur in succeeding generations due to either mutation or environmental influences, such progeny may not, in fact, be identical to the parent cell. A host cell can be any prokaryotic or eukaryotic cell. For example, a polypeptide can be expressed in bacterial cells such as E. coli, insect cells, yeast or mammalian cells (such as Chinese hamster ovary cells (CHO) or COS cells).
Vectors can be introduced into host cells via conventional transformation or transfection techniques. The terms transformation and transfection refer to a variety of techniques known for introducing foreign nucleic acid (e.g., DNA) into a host cell, including calcium phosphate or calcium chloride co-precipitation, transduction/infection, DEAE-dextran-mediated transfection, lipofection, or electroporation.
A host cell can be used to produce a polypeptide. Accordingly, methods for producing a polypeptide using the host cells are included as part of this invention. Such a method can include culturing host cells into which a recombinant expression vector encoding a polypeptide has been introduced in a suitable medium such that the polypeptide is produced. The method can further include isolating the polypeptide from the medium or the host cell.
The invention also includes cells or purified preparations of cells which include a transgene from the tables, or which otherwise mis-express a polypeptide. Cell preparations can consist of human or non-human cells, e.g., rodent cells, e.g., mouse or rat cells, rabbit cells, or pig cells. The transgene can be mis-expressed, e.g., over-expressed or under-expressed. In other embodiments, the cell or cells include a gene which misexpresses an endogenous polypeptide (e.g., expression of a gene is disrupted, also known as a knockout). Such cells can serve as a model for studying disorders which are related to mutated or mis-expressed alleles or for use in drug screening. Also provided are human cells (e.g., hematopoietic stem cells) transformed with a nucleic acid from the tables.
The invention includes cells or a purified preparation thereof (e.g., human cells) in which an endogenous nucleic acid from the tables is under the control of a regulatory sequence that does not normally control the expression of the endogenous gene corresponding to the sequence. The expression characteristics of an endogenous gene within a cell (e.g., a cell line or microorganism) can be modified by inserting a heterologous DNA regulatory element into the genome of the cell such that the inserted regulatory element is operably linked to the corresponding endogenous gene. For example, an endogenous corresponding gene (e.g., a gene which is transcriptionally silent, not normally expressed, or expressed only at very low levels) may be activated by inserting a regulatory element which is capable of promoting the expression of a normally expressed gene product in that cell. Techniques such as targeted homologous recombinations, can be used to insert the heterologous DNA as described in, e.g., Chappel, U.S. Pat. No. 5,272,071; WO 91/06667, published on May 16, 1991.
Non-human transgenic animals that express a heterologous polypeptide (e.g., expressed from a nucleic acid from the tables) can be generated. Such animals are useful for studying the function and/or activity of a polypeptide and for identifying and/or evaluating modulators of the activity of the nucleic acids and encoded polypeptides. A transgenic animal is a non-human animal such as a mammal (e.g., a non-human primate such as chimpanzee, baboon, or macaque; an ungulate such as an equine, bovine, or caprine; or a rodent such as a rat, a mouse, or an Israeli sand rat), a bird (e.g., a chicken or a turkey), an amphibian (e.g., a frog, salamander, or newt), or an insect (e.g., Drosophila melanogaster), in which one or more of the cells of the animal includes a transgene. A transgene is exogenous DNA or a rearrangement (e.g., a deletion of endogenous chromosomal DNA) that is often integrated into or occurs in the genome of cells in a transgenic animal. A transgene can direct expression of an encoded gene product in one or more cell types or tissues of the transgenic animal. Thus, a transgenic animal can be one in which an endogenous nucleic acid homologous to a nucleic acid from the tables has been altered by homologous recombination between the endogenous gene and an exogenous DNA molecule introduced into a cell of the animal (e.g., an embryonic cell of the animal) prior to development of the animal.
Intronic sequences and polyadenylation signals can also be included in the transgene to increase expression efficiency of the transgene. One or more tissue-specific regulatory sequences can be operably linked to a nucleotide sequence from the tables to direct expression of an encoded polypeptide to particular cells. A transgenic founder animal can be identified based upon the presence of the nucleotide sequence in its genome and/or expression of encoded mRNA in tissues or cells of the animals. A transgenic founder animal can then be used to breed additional animals carrying the transgene. Moreover, transgenic animals carrying a nucleotide sequence can further be bred to other transgenic animals carrying other transgenes.
Polypeptides can be expressed in transgenic animals or plants by introducing a nucleic acid encoding the polypeptide into the genome of an animal. In certain embodiments the nucleic acid is placed under the control of a tissue specific promoter, e.g., a milk or egg specific promoter, and recovered from the milk or eggs produced by the animal. Also included is a population of cells from a transgenic animal.
Isolated polypeptides encoded by a nucleotide sequence from the tables can be synthesized. Isolated polypeptides include both the full-length polypeptide and the mature polypeptide (i.e., the polypeptide minus the signal sequence or propeptide domain). An isolated, or purified, polypeptide or protein is substantially free of cellular material or other contaminating proteins from the cell or tissue source from which the protein is derived, or is substantially free from chemical precursors or other chemicals when chemically synthesized. Substantially free means a preparation of a polypeptide having less than about 5% (by dry weight) of contaminating protein, or of chemical precursors or non-target chemicals. When the desired polypeptide is recombinantly produced, it is typically substantially free of culture medium, specifically, where culture medium represents less than about 10% of the polypeptide preparation.
Also, polypeptides may exist as chimeric or fusion polypeptides. As used herein, a “target chimeric polypeptide” or “target fusion polypeptide” includes a target polypeptide linked to a different polypeptide. The target polypeptide in the fusion polypeptide can correspond to an entire or nearly entire polypeptide as it exists in nature or a fragment thereof. The other polypeptide can be fused to the N-terminus or C-terminus of the target polypeptide.
Fusion polypeptides can include a moiety having high affinity for a ligand. For example, the fusion polypeptide can be a GST-target fusion polypeptide in which the target sequences are fused to the C-terminus of the GST sequences, or a polyhistidine-target fusion polypeptide in which the target polypeptide is fused at the N- or C-terminus to a string of histidine residues. Such fusion polypeptides can facilitate purification of recombinant target polypeptide. Expression vectors are commercially available that already encode a fusion moiety (e.g., a GST polypeptide), and a nucleotide sequence from the tables, or a substantially identical nucleotide sequence thereof, can be cloned into an expression vector such that the fusion moiety is linked in-frame to the target polypeptide. Further, the fusion polypeptide can be a target polypeptide containing a heterologous signal sequence at its N-terminus. In certain host cells (e.g., mammalian host cells), expression, secretion, cellular internalization, and cellular localization of a target polypeptide can be increased through use of a heterologous signal sequence. Fusion polypeptides can also include all or a part of a serum polypeptide (e.g., an IgG constant region or human serum albumin).
Target polypeptides can be incorporated into pharmaceutical compositions and administered to a subject in vivo. Administration of these polypeptides can be used to affect the bioavailability of a substrate of the polypeptide and may effectively increase polypeptide biological activity in a cell. Target fusion polypeptides may be useful therapeutically for the treatment of disorders caused by, for example, (i) aberrant modification or mutation of a gene encoding a polypeptide; (ii) mis-regulation of the gene encoding the polypeptide; and (iii) aberrant post-translational modification of a polypeptide. Also, target polypeptides can be used as immunogens to produce anti-target antibodies in a subject, to purify the polypeptide ligands or binding partners, and in screening assays to identify molecules which inhibit or enhance the interaction of a polypeptide with a substrate.
Polypeptides can be differentially modified during or after translation, e.g., by glycosylation, acetylation, phosphorylation, amidation, derivatization by known protecting/blocking groups, proteolytic cleavage, linkage to an antibody molecule or other cellular ligand, etc. Any known modification including specific chemical cleavage by cyanogen bromide, trypsin, chymotrypsin, papain, V8 protease, NaBH4; acetylation, formylation, oxidation, reduction; metabolic synthesis in the presence of tunicamycin; etc. may be used. Additional post-translational modifications include, for example, N-linked or O-linked carbohydrate chains, processing of N-terminal or C-terminal ends), attachment of chemical moieties to the amino acid backbone, chemical modifications of N-linked or O-linked carbohydrate chains, and addition or deletion of an N-terminal methionine residue as a result of prokaryotic host cell expression. The polypeptide fragments may also be modified with a detectable label, such as an enzymatic, fluorescent, isotopic or affinity label to allow for detection and isolation of the polypeptide.
Chemically modified derivatives of polypeptides that can provide additional advantages such as increased solubility, stability and circulating time of the polypeptide, or decreased immunogenicity (see e.g., U.S. Pat. No. 4,179,337) are also part of this invention. The chemical moieties for derivitization may be selected from water soluble polymers such as polyethylene glycol, ethylene glycol/propylene glycol copolymers, carboxymethylcellulose, dextran, polyvinyl alcohol and the like. The polypeptides may be modified at random positions within the molecule, or at predetermined positions within the molecule and may include one, two, three or more attached chemical moieties.
The polymer may be of any molecular weight, and may be branched or unbranched. For polyethylene glycol, the molecular weight often is between about 1 kDa and about 100 kDa for ease in handling and manufacturing. Other sizes may be used, depending on the desired therapeutic profile (e.g., the duration of sustained release desired, the effects, if any on biological activity, the ease in handling, the degree or lack of antigenicity and other known effects of the polyethylene glycol to a therapeutic protein or analog).
The polymers can be attached to the polypeptide with consideration of effects on functional or antigenic domains of the polypeptide. There are a number of attachment methods available to those skilled in the art (e.g., EP 0 401 384 (coupling PEG to G-CSF) and Malik et al. (Malik et al., 1992) For example, polyethylene glycol may be covalently bound through amino acid residues via a reactive group, such as a free amino or carboxyl group. Reactive groups are those to which an activated polyethylene glycol molecule may be bound. The amino acid residues having a free amino group may include lysine residues and the N-terminal amino acid residues; those having a free carboxyl group may include aspartic acid residues, glutamic acid residues and the C-terminal amino acid residue. Sulfhydryl groups may also be used as a reactive group for attaching the polyethylene glycol molecules. For therapeutic purposes, the attachment sometimes is at an amino group, such as attachment at the N-terminus or lysine group.
Proteins can be chemically modified at the N-terminus. Using polyethylene glycol, for example, one may select from a variety of polyethylene glycol molecules (by molecular weight, branching, and the like), the proportion of polyethylene glycol molecules to protein (polypeptide) molecules in the reaction mix, the type of pegylation reaction to be performed, and the method of obtaining the selected N-terminally pegylated protein. The method of obtaining the N-terminally pegylated preparation (i.e., separating this moiety from other monopegylated moieties if necessary) may be by purification of the N-terminally pegylated material from a population of pegylated protein molecules. Selective proteins chemically modified at the N-terminus may be accomplished by reductive alkylation, which exploits differential reactivity of different types of primary amino groups (lysine versus the N-terminal) available for derivatization in a particular protein. Under the appropriate reaction conditions, substantially selective derivatization of the protein at the N-terminus with a carbonyl group containing polymer is achievable.
Applications of Prognostic and Diagnostic Results to Pharmacogenomic Methods
Pharmacogenomics is a discipline that involves tailoring a treatment for a subject according to the subject's genotype. For example, based upon the outcome of a prognostic test, a clinician or physician may target pertinent information and preventative or therapeutic treatments to a subject who would be benefited by the information or treatment and avoid directing such information and treatments to a subject who would not be benefited (e.g., the treatment has no therapeutic effect and/or the subject experiences adverse side effects). As therapeutic approaches for colorectal cancer continue to evolve and improve, the goal of treatments for colorectal cancer related disorders is to intervene even before clinical signs manifest themselves. Thus, genetic markers associated with susceptibility to colorectal cancer prove useful for early diagnosis, prevention and treatment of colorectal cancer.
The following is an example of a pharmacogenomic embodiment. A particular treatment regimen can exert a differential effect depending upon the subject's genotype. Where a candidate therapeutic exhibits a significant beneficial interaction with a prevalent allele and a comparatively weak interaction with an uncommon allele (e.g., an order of magnitude or greater difference in the interaction), such a therapeutic typically would not be administered to a subject genotyped as being homozygous for the uncommon allele, and sometimes not administered to a subject genotyped as being heterozygous for the uncommon allele. In another example, where a candidate therapeutic is not significantly toxic when administered to subjects who are homozygous for a prevalent allele but is comparatively toxic when administered to subjects heterozygous or homozygous for an uncommon allele, the candidate therapeutic is not typically administered to subjects who are genotyped as being heterozygous or homozygous with respect to the uncommon allele.
Methods of the invention are applicable to pharmacogenomic methods for detecting, preventing, alleviating and/or treating colorectal cancer. For example, a nucleic acid sample from an individual may be subjected to a genetic test. Where one or more SNPs associated with increased risk of colorectal cancer are identified in a subject, information for detecting, preventing or treating colorectal cancer and/or one or more colorectal cancer detection, prevention and/or treatment regimens then may be directed to and/or prescribed to that subject.
In certain embodiments, a detection, preventative and/or treatment regimen is specifically prescribed and/or administered to individuals who will most benefit from it based upon their risk of developing colorectal cancer assessed by the methods described herein. Methods are thus provided for identifying a subject at risk of colorectal cancer and then prescribing a detection, therapeutic or preventative regimen to individuals identified as being at increased risk of colorectal cancer. Thus, certain embodiments are directed to methods for treating colorectal cancer in a subject, reducing risk of colorectal cancer in a subject, or early detection of colorectal cancer in a subject, which comprise: detecting the presence or absence of a SNP associated with colorectal cancer in a nucleotide sequence set forth in SEQ ID NOs:1 to 1790, and prescribing or administering a colorectal cancer treatment regimen, preventative regimen and/or detection regimen to a subject from whom the sample originated where the presence of one or more SNPs associated with colorectal cancer are detected in the nucleotide sequence. In these methods, genetic results may be utilized in combination with other test results to diagnose colorectal cancer as described above.
The use of certain colorectal cancer treatments are known in the art, and include surgery, chemotherapy and/or radiation therapy. Any of the treatments may be used in combination to treat or prevent colorectal cancer (e.g., surgery followed by radiation therapy or chemotherapy).
Pharmacogenomic methods also may be used to analyze and predict a response to a colorectal cancer treatment or a drug. For example, if pharmacogenomic analysis indicates a likelihood that an individual will respond positively to a colorectal cancer treatment with a particular drug, the drug may be administered to the individual. Conversely, if the analysis indicates that an individual is likely to respond negatively to treatment with a particular drug, an alternative course of treatment may be prescribed. A negative response may be defined as either the absence of an efficacious response or the presence of toxic side effects. The response to a therapeutic treatment can be predicted in a background study in which subjects in any of the following populations are genotyped: a population that responds favorably to a treatment regimen, a population that does not respond significantly to a treatment regimen, and a population that responds adversely to a treatment regiment (e.g., exhibits one or more side effects). These populations are provided as examples and other populations and subpopulations may be analyzed. Based upon the results of these analyses, a subject is genotyped to predict whether he or she will respond favorably to a treatment regimen, not respond significantly to a treatment regimen, or respond adversely to a treatment regimen.
The methods described herein also are applicable to clinical drug trials. One or more SNPs indicative of response to an agent for treating colorectal cancer or to side effects to an agent for treating colorectal cancer may be identified. Thereafter, potential participants in clinical trials of such an agent may be screened to identify those individuals most likely to respond favorably to the drug and exclude those likely to experience side effects. In that way, the effectiveness of drug treatment may be measured in individuals who respond positively to the drug, without lowering the measurement as a result of the inclusion of individuals who are unlikely to respond positively in the study and without risking undesirable safety problems. Thus, another embodiment is a method of selecting an individual for inclusion in a clinical trial of a treatment or drug comprising the steps of: (a) obtaining a nucleic acid sample from an individual; (b) determining the identity of a polymorphic variant, e.g., SNP which is associated with a positive response to the treatment or the drug, or at least one SNP which is associated with a negative response to the treatment or the drug in the nucleic acid sample, and (c) including the individual in the clinical trial if the nucleic acid sample contains the SNP associated with a positive response to the treatment or the drug or if the nucleic acid sample lacks said SNP associated with a negative response to the treatment or the drug. The SNP may be in a sequence selected individually or in any combination from those disclosed in the tables. Step (c) can also include administering the drug or the treatment to the individual if the nucleic acid sample contains the SNP associated with a positive response to the treatment or the drug and the nucleic acid sample lacks the SNP associated with a negative response to the treatment or the drug.
Compositions Comprising Colorectal Cancer-Directed Molecules
The invention includes a composition made up of a colorectal cancer cell and one or more molecules specifically directed and targeted to a nucleic acid comprising a nucleotide sequence shown in the tables, or a polypeptide encoded thereby. Such directed molecules include, but are not limited to, a compound that binds to a nucleic acid or a polypeptide; a RNAi or siRNA molecule having a strand complementary to a nucleotide sequence; an antisense nucleic acid complementary to an RNA encoded by a DNA sequence; a ribozyme that hybridizes to a nucleotide sequence; a nucleic acid aptamer that specifically binds a polypeptide; and an antibody that specifically binds to a polypeptide or binds to a nucleic acid. In specific embodiments, the colorectal cancer directed molecule interacts with a nucleic acid or polypeptide variant associated with colorectal cancer.
Compounds
Compounds can be obtained using any of numerous approaches in combinatorial library methods known in the art, including: biological libraries; peptoid libraries (libraries of molecules having the functionalities of peptides, but with a novel, non-peptide backbone which are resistant to enzymatic degradation but which nevertheless remain bioactive (Zuckermann et al., 1994). Biological library and peptoid library approaches are typically limited to peptide libraries, while the other approaches are applicable to peptide, non-peptide oligomer or small molecule libraries of compounds (Lam, 1997). Examples of methods for synthesizing molecular libraries are described, for example, in DeWitt et al. (DeWitt et al., 1993), Erb et al. (Erb et al., 1994), Zuckermann et al. (Zuckermann et al., 1994), Cho et al. (Cho et al., 1993) and Gallop et al. (Gallop et al., 1994).
Libraries of compounds may be presented in solution (Houghten et al., 1992), or on beads (Lam et al., 1991), chips (Fodor et al., 1993), bacteria or spores (Ladner, U.S. Pat. No. 5,223,409), plasmids (Cull et al., 1992) or on phage (Scott and Smith, 1990; Devlin et al., 1990; Cwirla et al., 1990; Felici et al., 1991).
A compound sometimes alters expression and sometimes alters activity of a target polypeptide and may be a small molecule. Small molecules include peptides, peptidomimetics (e.g., peptoids), amino acids, amino acid analogs, polynucleotides, polynucleotide analogs, nucleotides, nucleotide analogs, organic or inorganic compounds (i.e., including heteroorganic and organometallic compounds) having a molecular weight less than about 10,000 grams per mole, organic or inorganic compounds having a molecular weight less than about 5,000 grams per mole, organic or inorganic compounds having a molecular weight less than about 1,000 grams per mole, organic or inorganic compounds having a molecular weight less than about 500 grams per mole, and salts, esters, and other pharmaceutically acceptable forms of such compounds.
An antisense nucleic acid refers to a nucleotide sequence complementary to a sense nucleic acid encoding a polypeptide, e.g., complementary to the, coding strand of a double-stranded cDNA molecule or complementary to an mRNA sequence. The antisense nucleic acid can be complementary to an entire coding strand in a nucleic acid molecule having a sequence of one of SEQ ID NOs:1761 to 1790, or to a portion thereof. In another embodiment, the antisense nucleic acid molecule is antisense to a non-coding region of the coding strand of a nucleotide sequence, e.g., 5′ and 3′ untranslated regions.
An antisense nucleic acid can be designed such that it is complementary to the entire coding region of an mRNA encoded by a nucleotide sequence of interest, and often the antisense nucleic acid is an oligonucleotide antisense to only a portion of a coding or non-coding region of the mRNA. For example, the antisense oligonucleotide can be complementary to the region surrounding the translation start site of the mRNA, e.g., between the −10 and +10 regions of the target gene nucleotide (SNP) sequence of interest. An antisense oligonucleotide can be, for example, about 7, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, or more nucleotides in length. The antisense nucleic acids, which include the ribozymes described below, can be designed to target a nucleotide sequence in any of SEQ ID NOs:1761 to 1790. Uncommon alleles and prevalent alleles can be targeted, and those associated with an increased risk of colorectal cancer are often designed, tested, and administered to subjects.
An antisense nucleic acid can be constructed using chemical synthesis and enzymatic ligation reactions using standard procedures. For example, an antisense nucleic acid molecule can be chemically synthesized using naturally occurring nucleotides or variously modified nucleotides designed to increase the biological stability of the molecules or to increase the physical stability of the duplex formed between the antisense and sense nucleic acids, e.g., phosphorothioate derivatives and acridine substituted nucleotides can be used. Antisense nucleic acid also can be produced biologically using an expression vector into which a nucleic acid has been subcloned in an antisense orientation (i.e., RNA transcribed from the inserted nucleic acid will be of an antisense orientation to a target nucleic acid of interest.
When utilized as therapeutics, antisense nucleic acids typically are administered to a subject (e.g., by direct injection at a tissue site) or generated in situ such that they hybridize with or bind to cellular mRNA and/or genomic DNA encoding a polypeptide and thereby inhibit expression of the polypeptide, for example, by inhibiting transcription and/or translation. Alternatively, antisense nucleic acid molecules can be modified to target selected cells and then are administered systemically. For systemic administration, antisense molecules can be modified such that they specifically bind to receptors or antigens expressed on a selected cell surface, for example, by linking antisense nucleic acid molecules to peptides or antibodies which bind to cell surface receptors or antigens. Antisense nucleic acid molecules can also be delivered to cells using vectors. Sufficient intracellular concentrations of antisense molecules are achieved by incorporating a strong promoter, such as a pol II or pol III promoter, in the vector construct.
Antisense nucleic acid molecules sometimes are anomeric nucleic acid molecules (Gautier et al., 1987). Antisense nucleic acid molecules can also comprise a 2′-o-methylribonucleotide (Inoue et al., 1987a) or a chimeric RNA-DNA analogue (Inoue et al., 1987b). Antisense nucleic acids sometimes are composed of DNA or peptide nucleic acid (PNA).
In another embodiment, an antisense nucleic acid is a ribozyme. A ribozyme having specificity for a target nucleotide sequence can include one or more sequences complementary to such a nucleotide sequence, and a sequence having a known catalytic region responsible for mRNA cleavage (see e.g., U.S. Pat. No. 5,093,246 or Haselhoff and Gerlach (Haseloff and Gerlach, 1988). For example, a derivative of a Tetrahymena L-19 IVS RNA is sometimes utilized in which the nucleotide sequence of the active site is complementary to the nucleotide sequence to be cleaved in a mRNA (see e.g., Cech et al., U.S. Pat. No. 4,987,071; and Cech et al., U.S. Pat. No. 5,116,742). Also, target mRNA sequences can be used to select a catalytic RNA having a specific ribonuclease activity from a pool of RNA molecules (Bartel and Szostak, 1993).
Colorectal cancer directed molecules include in certain embodiments nucleic acids that can form triple helix structures with a target nucleotide sequence, especially one that includes a regulatory region that controls expression of a polypeptide. Gene expression can be inhibited by targeting nucleotide sequences complementary to the regulatory region of a target nucleotide sequence (e.g., promoter and/or enhancers) to form triple helical structures that prevent transcription of a gene in target cells (Helene, 1991; Helene et al., 1992; Maher, III, 1992). Potential sequences that can be targeted for triple helix formation can be increased by creating a switchback nucleic acid molecule. Switchback molecules are synthesized in an alternating 5′-3′,3′-5′ manner, such that they base pair with first one strand of a duplex and then the other, eliminating the necessity for a sizeable stretch of either purines or pyrimidines to be present on one strand of a duplex.
Colorectal cancer directed molecules include RNAi and siRNA nucleic acids. Gene expression may be inhibited by the introduction of double-stranded RNA (dsRNA), which induces potent and specific gene silencing, a phenomenon called RNA interference or RNAi. See, e.g., Fire et al., U.S. Pat. No. 6,506,559; Tuschl et al., PCT International Publication No. WO 01/75164; Kay et al., PCT International Publication No. WO 03/010180A1; or Bosher J M, Labouesse (Bosher and Labouesse, 2000). This process has been improved by decreasing the size of the double-stranded RNA to 20-24 base pairs (to create small-interfering RNAs or siRNAs) that switched off genes in mammalian cells without initiating an acute phase response, i.e., a host defense mechanism that often results in cell death (Caplen et al., 2001a; Elbashir et al., 2002). There is increasing evidence of post-transcriptional gene silencing by RNA interference (RNAi) for inhibiting targeted expression in mammalian cells at the mRNA level, in human cells. There is additional evidence of effective methods for inhibiting the proliferation and migration of tumor cells in human patients, and for inhibiting metastatic cancer development (see, e.g., U.S. patent application No. US2001000993183; Caplen et al. (Caplen et al., 2001b), Abderrahman et al. (Abderrahmani et al., 2001).
An siRNA or RNAi is a nucleic acid that forms a double stranded RNA and has the ability to reduce or inhibit expression of a gene or target gene when the siRNA is delivered to or expressed in the same cell as the gene or target gene. siRNA is short double-stranded RNA formed by the complementary strands. Complementary portions of the siRNA that hybridize to form the double stranded molecule often have substantial or complete identity to the target molecule sequence. In one embodiment, an siRNA is a nucleic acid that has substantial or complete identity to a target gene and forms a double stranded siRNA.
When designing the siRNA molecules, the targeted region often is selected from a given DNA sequence beginning 50 to 100 nucleotides downstream of the start codon. See, e.g., Elbashir et al. (Elbashir et al., 2002). Initially, 5′ or 3′ UTRs and regions nearby the start codon were avoided assuming that UTR-binding proteins and/or translation initiation complexes may interfere with binding of the siRNP or RISC endonuclease complex. Sometimes regions of the target 23 nucleotides in length conforming to the sequence motif AA (N19)TT (N, an nucleotide), and regions with approximately 30% to 70% G/C-content (often about 50% G/C-content) often are selected. If no suitable sequences are found, the search often is extended using the motif NA (N2 1). The sequence of the sense siRNA sometimes corresponds to (N19) TT or N21 (position 3 to 23 of the 23-nt motif), respectively. In the latter case, the 3′ end of the sense siRNA often is converted to TT. The rationale for this sequence conversion is to generate a symmetric duplex with respect to the sequence composition of the sense and antisense 3′ overhangs. The antisense siRNA is synthesized as the complement to position 1 to 21 of the 23-nt motif. Because position 1 of the 23-nt motif is not recognized sequence-specifically by the antisense siRNA, the 3′-most nucleotide residue of the antisense siRNA can be chosen deliberately. However, the penultimate nucleotide of the antisense siRNA (complementary to position 2 of the 23-nt motif) often is complementary to the targeted sequence. For simplifying chemical synthesis, TT often is utilized. siRNAs corresponding to the target motif NAR (N17)YNN, where R is purine (A,G) and Y is pyrimidine (C,U), often are selected. Respective 21 nucleotide sense and antisense siRNAs often begin with a purine nucleotide and can also be expressed from pol III expression vectors without a change in targeting site. Expression of RNAs from pol III promoters can be more efficient when the first transcribed nucleotide is a purine.
The sequence of the siRNA can correspond to the full length target gene, or a subsequence thereof. Often, the siRNA is about 15 to about 50 nucleotides in length (e.g., each complementary sequence of the double stranded siRNA is 15 to 50 nucleotides in length, and the double stranded siRNA is about 15 to 50 base pairs in length, sometimes about 20 to 30 nucleotides in length or about 20 to 25 nucleotides in length, e.g., 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides in length. The siRNA sometimes is about 21 nucleotides in length. Methods of using siRNA are known in the art, and specific siRNA molecules may be purchased from a number of companies including Dharmacon Research, Inc.
Antisense, ribozyme, RNAi and siRNA nucleic acids can be altered to form modified nucleic acid molecules. The nucleic acids can be altered at base moieties, sugar moieties or phosphate backbone moieties to improve stability, hybridization, or solubility of the molecule. For example, the deoxyribose phosphate backbone of nucleic acid molecules can be modified to generate peptide nucleic acids (see Hyrup et al., Bioorganic & Medicinal Chemistry 4 (1): 5-23 (1996)). A peptide nucleic acid, or PNA, refers to a nucleic acid mimic such as a DNA mimic, in which the deoxyribose phosphate backbone is replaced by a pseudopeptide backbone and only the four natural nucleobases are retained. The neutral backbone of a PNA can allow for specific hybridization to DNA and RNA under conditions of low ionic strength. Synthesis of PNA oligomers can be performed using standard solid phase peptide synthesis protocols as described, for example, in Hyrup et al. (Hyrup and Nielsen, 1996), and Perry-O'Keefe et al. (Abderrahmani et al., 2001).
PNA nucleic acids can be used in prognostic, diagnostic, and therapeutic applications. For example, PNAs can be used as anti-sense or anti-gene agents for sequence-specific modulation of gene expression by, for example, inducing transcription or translation arrest or inhibiting replication. PNA nucleic acid molecules can also be used in the analysis of SNPs in a gene, (e.g., by PNA-directed PCR clamping); as artificial restriction enzymes when used in combination with other enzymes, (e.g., S1 nucleases (Hyrup and Nielsen, 1996) or as probes or primers for DNA sequencing or hybridization (Hyrup and Nielsen, 1996; Perry-O'Keefe et al., 1996).
In other embodiments, oligonucleotides may include other appended groups such as peptides (e.g., for targeting host cell receptors in vivo), or agents facilitating transport across cell membranes (see e.g., Letsinger et al. (Letsinger et al., 1989); Lemaitre et al. (Lemaitre et al., 1987) and PCT Publication No. WO88/09810) or the blood-brain barrier (see, e.g., PCT Publication No. WO89/10134). In addition, oligonucleotides can be modified with hybridization-triggered cleavage agents (van der Krol et al., 1988) or intercalating agents (Zon, 1988). To this end, the oligonucleotide may be conjugated to another molecule, (e.g., a peptide, hybridization triggered cross-linking agent, transport agent, or hybridization-triggered cleavage agent).
Also included as part of this invention are molecular beacon oligonucleotide primer and probe molecules having one or more regions complementary to a target nucleotide sequence, two complementary regions one having a fluorophore and one a quencher such that the molecular beacon is useful for quantifying the presence of the nucleic acid in a sample. Molecular beacon nucleic acids are described, for example, in Lizardi et al., U.S. Pat. No. 5,854,033; Nazarenko et al., U.S. Pat. No. 5,866,336, and Livak et al., U.S. Pat. No. 5,876,930.
Antibodies
An immunogen typically is used to prepare antibodies by immunizing a suitable subject, (e.g., rabbit, goat, mouse or other mammal). An appropriate immunogenic preparation can contain, for example, recombinantly expressed chemically synthesized polypeptide. The preparation can further include an adjuvant, such as Freund's complete or incomplete adjuvant, or a similar immunostimulatory agent. Amino acid polymorphisms can be detected using antibodies specific for the altered epitope by western analysis after the electrophoresis of denatured proteins. Protein polymorphism can also be detected using fluorescently identified antibodies which bind to specific polymorphic epitopes and detected in whole cells using fluorescence activated cell sorting techniques (FACS). Polymorphic protein sequence may also be determined by NMR spectroscopy or by x-ray diffraction studies. Further, determination of polymorphic sites in proteins may be accomplished by observing differential cleavage by specific or non specific proteases.
An antibody is an immunoglobulin molecule or immunologically active portion thereof, i.e., an antigen-binding portion. Examples of immunologically active portions of immunoglobulin molecules include F(ab) and F(ab′)2 fragments which can be generated by treating the antibody with an enzyme such as pepsin. An antibody can be polyclonal, monoclonal, or recombinant (e.g., a chimeric or humanized), fully human, non-human (e.g., murine), or a single chain antibody. An antibody may have effector function and can fix complement, and is sometimes coupled to a toxin or imaging agent.
A full-length polypeptide or antigenic peptide fragment encoded by a target nucleotide sequence can be used as an immunogen or can be used to identify antibodies made with other immunogens, e.g., cells, membrane preparations, and the like. An antigenic peptide often includes at least 8 amino acid residues of the amino acid sequences encoded by a nucleotide sequence of one of SEQ ID NOs:1761 to 1790, and encompasses an epitope. Antigenic peptides sometimes include 10 or more amino acids, 15 or more amino acids, 20 or more amino acids, or 30 or more amino acids. Hydrophilic and hydrophobic fragments of polypeptides sometimes are used as immunogens.
Epitopes encompassed by the antigenic peptide are regions located on the surface of the polypeptide (e.g., hydrophilic regions) as well as regions with high antigenicity. For example, an Emini surface probability analysis of the human polypeptide sequence can be used to indicate the regions that have a particularly high probability of being localized to the surface of the polypeptide and are thus likely to constitute surface residues useful for targeting antibody production. The antibody may bind an epitope on any domain or region on polypeptides for use in the invention.
Also, chimeric, humanized, and completely human antibodies are useful for applications which include repeated administration to subjects. Chimeric and humanized monoclonal antibodies, comprising both human and non-human portions, can be made using standard recombinant DNA techniques. Such chimeric and humanized monoclonal antibodies can be produced by recombinant DNA techniques, for example using methods described in Robinson et al., International Application No. PCT/US86/02269; Akira, et al., European Patent Application 184,187; Taniguchi, M., European Patent Application 171,496; Morrison et al., European Patent Application 173,494; Neuberger et al., PCT International Publication No. WO 86/01533; Cabilly et al., U.S. Pat. No. 4,816,567; Cabilly et al., European Patent Application 125,023; (Better et al., 1988; Liu et al., 1987a; Liu et al., 1987b; Sun et al., 1987; Nishimura et al., 1987; Wood et al., 1985; Shaw et al., 1988; Morrison, 1985; Verhoeyen et al., 1988; Beidler et al., 1988) and Winter, U.S. Pat. No. 5,225,539.
Completely human antibodies can be particularly desirable for therapeutic treatment of human patients. Such antibodies can be produced using transgenic mice that are incapable of expressing endogenous immunoglobulin heavy and light chains genes, but which can express human heavy and light chain genes. See, for example, Lonberg and Huszar (Lonberg and Huszar, 1995) and U.S. Pat. Nos. 5,625,126; 5,633,425; 5,569,825; 5,661,016; and 5,545,806. In addition, companies such as Abgenix, Inc. (Fremont, Calif.) and Medarex, Inc. (Princeton, N.J.), can be engaged to provide human antibodies directed against a selected antigen. Completely human antibodies that recognize a selected epitope also can be generated using guided selection. In this approach a selected non-human monoclonal antibody (e.g., a murine antibody) is used to guide the selection of a completely human antibody recognizing the same epitope. This technology is described for example by Jespers et al. (Jespers et al., 1994).
An antibody can be a single chain antibody. A single chain antibody (scFV) can be engineered (see, e.g., Colcher et al. (Colcher et al., 1999) and Reiter (Reiter and Pastan, 1996). Single chain antibodies can be dimerized or multimerized to generate multivalent antibodies having specificities for different epitopes of the same target polypeptide.
Antibodies also may be selected or modified so that they exhibit reduced or no ability to bind an Fc receptor. For example, an antibody may be an isotype or subtype, fragment or other mutant, which does not support binding to an Fc receptor (e.g., it has a mutagenized or deleted Fc receptor binding region).
Also, an antibody (or fragment thereof) may be conjugated to a therapeutic moiety such as a cytotoxin, a therapeutic agent or a radioactive metal ion. A cytotoxin or cytotoxic agent includes any agent that is detrimental to cells. Examples include taxol, cytochalasin B, gramicidin D, ethidium bromide, emetine, mitomycin, etoposide, tenoposide, vincristine, vinblastine, colchicin, doxorubicin, daunorubicin, dihydroxy anthracin dione, mitoxantrone, mithramycin, actinomycin D, 1 dehydrotestosterone, glucocorticoids, procaine, tetracaine, lidocaine, propranolol, and puromycin and analogs or homologs thereof. Therapeutic agents include antimetabolites (e.g., methotrexate, 6-mercaptopurine, 6-thioguanine, cytarabine, 5-fluorouracil decarbazine), alkylating agents (e.g., mechlorethamine, thiotepa chlorambucil, melphalan, carmustine (BCNU) and lomustine (CCNU), cyclophosphamide, busulfan, dibromomannitol, streptozotocin, mitomycin C, and cis-dichlorodiamine platinum (II) (DDP) cisplatin), anthracyclines (e.g., daunorubicin (formerly daunomycin) and doxorubicin), antibiotics (e.g., dactinomycin (formerly actinomycin), bleomycin, mithramycin, and anthramycin (AMC)), and anti-mitotic agents (e.g., vincristine and vinblastine).
Antibody conjugates can be used for modifying a given biological response. For example, the drug moiety may be a protein or polypeptide possessing a desired biological activity. Such proteins may include, for example, a toxin such as abrin, ricin A, pseudomonas exotoxin, or diphtheria toxin; a polypeptide such as tumor necrosis factor, γ-interferon, α-interferon, nerve growth factor, platelet derived growth factor, tissue plasminogen activator; or, biological response modifiers such as, for example, lymphokines, interleukin-1 (“IL-1”), interleukin-2 (“IL-2”), interleukin-6 (“IL-6”), granulocyte macrophage colony stimulating factor (“GM-CSF”), granulocyte colony stimulating factor (“G-CSF”), or other growth factors. Also, an antibody can be conjugated to a second antibody to form an antibody heteroconjugate as described by Segal in U.S. Pat. No. 4,676,980, for example.
An antibody (e.g., monoclonal antibody) can be used to isolate target polypeptides by standard techniques, such as affinity chromatography or immunoprecipitation. Moreover, an antibody can be used to detect a target polypeptide (e.g., in a cellular lysate or cell supernatant) in order to evaluate the abundance and pattern of expression of the polypeptide. Antibodies can be used diagnostically to monitor polypeptide levels in tissue as part of a clinical testing procedure, e.g., to determine the efficacy of a given treatment regimen. Detection can be facilitated by coupling (i.e., physically linking) the antibody to a detectable substance. Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, β-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include 125I, 131I, 35S or 3H. Also, an antibody can be utilized as a test molecule for determining whether it can treat colorectal cancer, and as a therapeutic for administration to a subject for treating colorectal cancer.
An antibody can be made by immunizing with a purified antigen, or a fragment thereof, a membrane associated antigen, tissues, e.g., crude tissue preparations, whole cells, preferably living cells, lysed cells, or cell fractions.
Included as part of this invention are antibodies which bind only a native polypeptide, only denatured or otherwise non-native polypeptide, or which bind both, as well as those having linear or conformational epitopes. Conformational epitopes sometimes can be identified by selecting antibodies that bind to native but not denatured polypeptide. Also featured are antibodies that specifically bind to a polypeptide variant associated with colorectal cancer.
Screening Assays
The invention includes methods for identifying a candidate therapeutic for treating colorectal cancer. The methods include contacting a test molecule with a target molecule in a system. A target molecule is a nucleic acid molecule having a sequence of any of SEQ ID NOs:1 to 1790, or a fragment thereof, or an encoded polypeptide of SEQ ID NOs:1761 to 1790. The method also includes determining the presence or absence of an interaction between the test molecule and the target molecule, where the presence of an interaction between the test molecule and the nucleic acid or polypeptide identifies the test molecule as a candidate colorectal cancer therapeutic. The interaction between the test molecule and the target molecule may be quantified.
Test molecules and candidate therapeutics include compounds, antisense nucleic acids, siRNA molecules, ribozymes, polypeptides or proteins encoded by target nucleic acids, and immunotherapeutics (e.g., antibodies and HLA-presented polypeptide fragments). A test molecule or candidate therapeutic may act as a modulator of target molecule concentration or target molecule function in a system. A modulator may agonize (i.e., up-regulates) or antagonize (i.e., down-regulates) a target molecule concentration partially or completely in a system by affecting such cellular functions as DNA replication and/or DNA processing (e.g., DNA methylation or DNA repair), RNA transcription and/or RNA processing (e.g., removal of intronic sequences and/or translocation of spliced mRNA from the nucleus), polypeptide production (e.g., translation of the polypeptide from mRNA), and/or polypeptide post-translational modification (e.g., glycosylation, phosphorylation, and proteolysis of pro-polypeptides). A modulator may also agonize or antagonize a biological function of a target molecule partially or completely, where the function may include adopting a certain structural conformation, interacting with one or more binding partners, ligand binding, catalysis (e.g., phosphorylation, dephosphorylation, hydrolysis, methylation, and isomerization), and an effect upon a cellular event (e.g., effecting progression of colorectal cancer).
According to an aspect of this invention a system, i.e., a cell free in vitro environment and a cell-based environment such as a collection of cells, a tissue, an organ, or an organism, is contacted with a test molecule in a variety of manners, including adding molecules in solution and allowing them to interact with one another by diffusion, cell injection, and any administration routes in an animal. An interaction refers to an effect of a test molecule on test molecule, where the effect sometimes is binding between the test molecule and the target molecule, and sometimes is an observable change in cells, tissue, or organism.
There are known methods for detecting the presence or absence of interaction between a test molecule and a target molecule. For example, titrametric, acidimetric, radiometric, NMR, monolayer, polarographic, spectrophotometric, fluorescent, and ESR assays probative of a target molecule interaction may be utilized.
Test molecule/target molecule interactions can be detected and/or quantified using known assays. For example, an interaction can be determined by labeling the test molecule and/or the target molecule, where the label is covalently or non-covalently attached to the test molecule or target molecule. The label is sometimes a radioactive molecule such as 125I, 131I, 35S or 3H, which can be detected by direct counting of radio-emission or by scintillation counting. Also, enzymatic labels such as horseradish peroxidase, alkaline phosphatase, or luciferase may be utilized where the enzymatic label can be detected by determining conversion of an appropriate substrate to product. In addition, presence or absence of an interaction can be determined without labeling. For example, a microphysiometer (e.g., Cytosensor) is an analytical instrument that measures the rate at which a cell acidifies its environment using a light-addressable potentiometric sensor (LAPS). Changes in this acidification rate can be used as an indication of an interaction between a test molecule and target molecule (McConnell et al., 1992).
In cell-based systems, cells typically include a nucleic acid from SEQ ID NOs:1 to 1790 or an encoded polypeptide from SEQ ID NOs:1761 to 1790, and are often of mammalian origin, although the cell can be of any origin. Whole cells, cell homogenates, and cell fractions (e.g., cell membrane fractions) can be subjected to analysis. Where interactions between a test molecule with a target polypeptide are monitored, soluble and/or membrane bound forms of the polypeptide may be utilized. Where membrane-bound forms of the polypeptide are used, it may be desirable to utilize a solubilizing agent. Examples of such solubilizing agents include non-ionic detergents such as n-octylglucoside, n-dodecylglucoside, n-dodecylmaltoside, octanoyl-N-methylglucamide, decanoyl-N-methylglucamide, TritonTMX-100, TritonTM X-114, etc.
An interaction between a test molecule and target molecule also can be detected by monitoring fluorescence energy transfer (FET) (see, e.g., Lakowicz et al., U.S. Pat. No. 5,631,169; Stavrianopoulos et al., U.S. Pat. No. 4,868,103). A fluorophore label on a first, donor molecule is selected such that its emitted fluorescent energy will be absorbed by a fluorescent label on a second, acceptor molecule, which in turn is able to fluoresce due to the absorbed energy. Alternately, the donor polypeptide molecule may simply utilize the natural fluorescent energy of tryptophan residues. Labels are chosen that emit different wavelengths of light, such that the acceptor molecule label may be differentiated from that of the donor. Since the efficiency of energy transfer between the labels is related to the distance separating the molecules, the spatial relationship between the molecules can be assessed. In a situation in which binding occurs between the molecules, the fluorescent emission of the acceptor molecule label in the assay should be maximal. An FET binding event can be conveniently measured through standard fluorometric detection means well known in the art (e.g., using a fluorimeter).
In another embodiment, determining the presence or absence of an interaction between a test molecule and a target molecule can be effected by monitoring surface plasmon resonance (Sjolander and Urbaniczky, 1991; Szabo et al., 1995). Surface plasmon resonance (SPR) or biomolecular interaction analysis (BIA) can be utilized to detect biospecific interactions in real time, without labeling any of the interactants (e.g., BIAcore). Changes in the mass at the binding surface (indicative of a binding event) result in alterations of the refractive index of light near the surface (the optical phenomenon of surface plasmon resonance, resulting in a detectable signal which can be used as an indication of real-time reactions between biological molecules.
In another embodiment, the target molecule or test molecules are anchored to a solid phase, facilitating the detection of target molecule/test molecule complexes and separation of the complexes from free, uncomplexed molecules. The target molecule or test molecule is immobilized to the solid support. In one embodiment, the target molecule is anchored to a solid surface, and the test molecule, which is not anchored, can be labeled, either directly or indirectly, with detectable labels.
It may be desirable to immobilize a target molecule, an anti-target molecule antibody, and/or test molecules to facilitate separation of target molecule/test molecule complexes from uncomplexed forms, as well as to accommodate automation of the assay. The attachment between a test molecule and/or target molecule and the solid support may be covalent or non-covalent (see, e.g., U.S. Pat. No. 6,022,688 for non-covalent attachments). The solid support may be one or more surfaces of the system, such as one or more surfaces in each well of a microtiter plate, a surface of a silicon wafer, a surface of a bead (Lam et al., 1991) that is optionally linked to another solid support, or a channel in a microfluidic device, for example. Types of solid supports, linker molecules for covalent and non-covalent attachments to solid supports, and methods for immobilizing nucleic acids and other molecules to solid supports are known (see, e.g., U.S. Pat. Nos. 6,261,776; 5,900,481; 6,133,436; and 6,022,688; and WIPO publication WO 01/18234).
In one embodiment, a target molecule may be immobilized to surfaces via biotin and streptavidin. For example, a biotinylated polypeptide can be prepared from biotin-NHS (N-hydroxysuccinimide, e.g., biotinylation kit, Pierce Chemicals, Rockford, Ill.), and immobilized in the wells of streptavidin-coated 96 well plates (Pierce Chemical). In another embodiment, a target polypeptide can be prepared as a fusion polypeptide. For example, glutathione-S-transferase/-polypeptide fusion can be adsorbed onto glutathione sepharose beads (Sigma Chemical, St. Louis, Mo.) or glutathione derivatized microtiter plates, which are then combined with a test molecule under conditions conducive to complex formation (e.g., at physiological conditions for salt and pH). Following incubation, the beads or microtiter plate wells are washed to remove any unbound components, or the matrix is immobilized in the case of beads, and complex formation is determined directly or indirectly as described above. Alternatively, the complexes can be dissociated from the matrix, and the level of target molecule binding or activity is determined using standard techniques.
In one embodiment, the non-immobilized component is added to the coated surface containing the anchored component. After the reaction is complete, unreacted components are removed (e.g., by washing) under conditions such that a significant percentage of complexes formed will remain immobilized to the solid surface. The detection of complexes anchored on the solid surface can be accomplished in a number of manners. Where the previously non-immobilized component is pre-labeled, the detection of label immobilized on the surface indicates that complexes were formed. Where the previously non-immobilized component is not pre-labeled, an indirect label can be used to detect complexes anchored on the surface, e.g., by adding a labeled antibody specific for the immobilized component, where the antibody, in turn, can be directly labeled or indirectly labeled with, e.g., a labeled anti-Ig antibody.
In another embodiment, an assay is performed utilizing antibodies that specifically bind a target molecule or test molecule but do not interfere with binding of the target molecule to the test molecule. Such antibodies can be linked to a solid support, and unbound target molecule may be immobilized by antibody conjugation. Methods for detecting such complexes, in addition to those described above for the GST-immobilized complexes, include immunodetection of complexes using antibodies reactive with the target molecule, as well as enzyme-linked assays which rely on detecting an enzymatic activity associated with the target molecule.
Cell free assays also can be conducted in a liquid phase. In such an assay, reaction products are separated from unreacted components, by known techniques, including: differential centrifugation (Rivas and Minton, 1993); electrophoresis (1999) and immunoprecipitation (1999). Media and chromatographic techniques are known (Heegaard, 1998; Hage and Tweed, 1997). Further, fluorescence energy transfer may also be conveniently utilized to detect binding without further purification of the complex from solution.
In another embodiment, modulators of target molecule expression are identified. For example, a cell or cell free mixture is contacted with a candidate compound and the expression of target mRNA or polypeptide is evaluated relative to the level of expression of target mRNA or polypeptide in the absence of the candidate compound. When expression of target mRNA or polypeptide is greater in the presence of the candidate compound than in its absence, the candidate compound is identified as an agonist of target mRNA or polypeptide expression. Alternatively, when expression of target mRNA or polypeptide is less (e.g., less with statistical significance) in the presence of the candidate compound than in its absence, the candidate compound is identified as an antagonist or inhibitor of target mRNA or polypeptide expression. The level of target mRNA or polypeptide expression can be determined by methods described herein.
In another embodiment, binding partners that interact with a target molecule are detected. The target molecules can interact with one or more cellular or extra-cellular macromolecules, such as polypeptides in vivo, and these interacting molecules or binding partners. Binding partners can agonize or antagonize target molecule biological activity. Also, test molecules that agonize or antagonize interactions between target molecules and binding partners can be useful as therapeutic molecules as they can up-regulate or down-regulated target molecule activity in vivo and thereby treat colorectal cancer.
Binding partners of target molecules can be identified by known methods. For example, binding partners may be identified by lysing cells and analyzing cell lysates by electrophoretic techniques. Alternatively, a two-hybrid assay or three-hybrid assay can be utilized (Zervos et al., 1993; Madura et al., 1993; Bartel et al., 1993; Iwabuchi et al., 1993): see also, e.g., U.S. Pat. No. 5,283,317 and Brent WO94/10300. A two-hybrid system is based on the modular nature of most transcription factors, which consist of separable DNA-binding and activation domains. The assay often utilizes two different DNA constructs. In one construct, a nucleic acid from one of SEQ ID NOs:1761 to 1790, sometimes referred to as the bait, is fused to a gene encoding the DNA binding domain of a known transcription factor (e.g., GAL-4). In another construct, a DNA sequence from a library of DNA sequences that encodes a potential binding partner, sometimes referred to as the prey, is fused to a gene that encodes an activation domain of the known transcription factor. Sometimes, a target nucleic acid can be fused to the activation domain. If the bait and the prey molecules interact in vivo, the DNA-binding and activation domains of the transcription factor are brought into close proximity. This proximity allows transcription of a reporter gene (e.g., lacZ) which is operably linked to a transcriptional regulatory site responsive to the transcription factor. Expression of the reporter gene can be detected and cell colonies containing the functional transcription factor can be isolated and used to identify the potential binding partner.
In an embodiment for identifying test molecules that antagonize or agonize complex formation between target molecules and binding partners, a reaction mixture containing the target molecule and the binding partner is prepared, under conditions and for a time sufficient to allow complex formation. The reaction mixture often is provided in the presence or absence of the test molecule. The test molecule can be included initially in the reaction mixture, or can be added at a time subsequent to the addition of the target molecule and its binding partner. Control reaction mixtures are incubated without the test molecule or with a placebo. Formation of any complexes between the target molecule and the binding partner then is detected. Decreased formation of a complex in the reaction mixture containing test molecule as compared to in a control reaction mixture indicates that the molecule antagonizes target molecule/binding partner complex formation. Alternatively, increased formation of a complex in the reaction mixture containing test molecule as compared to in a control reaction mixture, indicates that the molecule agonizes target molecule/binding partner complex formation. In another embodiment, complex formation of target molecule/binding partner can be compared to complex formation of mutant target molecule/binding partner (e.g., amino acid modifications in a target polypeptide). Such a comparison can be important in those cases where it is desirable to identify test molecules that modulate interactions of mutant but not non-mutated target gene products.
The assays can be conducted in a heterogeneous or homogeneous format. In heterogeneous assays, a target molecule and/or the binding partner are immobilized to a solid phase, and complexes are detected on the solid phase at the end of the reaction. In homogeneous assays, the entire reaction is carried out in a liquid phase. In either approach, the order of addition of reactants can be varied to obtain different information about the molecules being tested. For example, test compounds that agonize target molecule/binding partner interactions can be identified by conducting the reaction in the presence of the test molecule in a competition format. Alternatively, test molecules that agonize preformed complexes, e.g., molecules with higher binding constants that displace one of the components from the complex, can be tested by adding the test compound to the reaction mixture after complexes have been formed.
In a heterogeneous assay, the target molecule or the binding partner is anchored onto a solid surface (e.g., a microtiter plate), while the non-anchored species is labeled, either directly or indirectly. The anchored molecule can be immobilized by non-covalent or covalent attachments. Alternatively, an immobilized antibody specific for the molecule to be anchored can be used to anchor the molecule to the solid surface. The partner of the immobilized species is exposed to the coated surface with or without the test molecule. After the reaction is complete, unreacted components are removed (e.g., by washing) such that a significant portion of any complexes formed will remain immobilized on the solid surface. Where the non-immobilized species is pre-labeled, the detection of label immobilized on the surface is indicative of complex. Where the non-immobilized species is not pre-labeled, an indirect label can be used to detect complexes anchored to the surface; e.g., by using a labeled antibody specific for the initially non-immobilized species. Depending upon the order of addition of reaction components, test compounds that inhibit complex formation or that disrupt preformed complexes can be detected.
The reaction can be conducted in a liquid phase in the presence or absence of test molecule, where the reaction products are separated from unreacted components, and the complexes are detected (e.g., using an immobilized antibody specific for one of the binding components to anchor any complexes formed in solution, and a labeled antibody specific for the other partner to detect anchored complexes). Again, depending upon the order of addition of reactants to the liquid phase, test compounds that inhibit complex or that disrupt preformed complexes can be identified.
In an alternate embodiment, a homogeneous assay can be utilized. For example, a preformed complex of the target gene product and the interactive cellular or extra-cellular binding partner-product is prepared. One or both of the target molecule or binding partner is labeled, and the signal generated by the label(s) is quenched upon complex formation (e.g., U.S. Pat. No. 4,109,496 that-utilizes this approach for immunoassays). Addition of a test molecule that competes with and displaces one of the species from the preformed complex will result in the generation of a signal above background. In this way, test substances that disrupt target molecule/binding partner complexes can be identified.
Identification of Candidate Therapeutics
Candidate therapeutics for treating colorectal cancer are identified from a group of test molecules that interact with a target molecule. Test molecules are normally ranked according to the degree with which they modulate (e.g., agonize or antagonize) a function associated with the target molecule (e.g., DNA replication and/or processing, RNA transcription and/or processing, polypeptide production and/or processing, and/or biological function/activity), and then top ranking modulators are selected. Also, pharmacogenomic information can determine the rank of a modulator. The top 10% of ranked test molecules often are selected for further testing as candidate therapeutics, and sometimes the top 15%, 20%, or 25% of ranked test molecules are selected for further testing as candidate therapeutics. Candidate therapeutics typically are formulated for administration to a subject.
Therapeutic Formulations
Formulations and pharmaceutical compositions typically include in combination with a pharmaceutically acceptable carrier one or more target molecule modulators. The modulator often is a test molecule identified as having an interaction with a target molecule by a screening method. The modulator may be a compound, an antisense nucleic acid, a ribozyme, an antibody, or a binding partner. Also, formulations may include a polypeptide combination with a pharmaceutically acceptable carrier.
A pharmaceutically acceptable carrier includes solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like, compatible with pharmaceutical administration. See for example, Remington's Pharmaceutical Sciences (2005). Supplementary active compounds can also be incorporated into the compositions. Pharmaceutical compositions can be included in a container, pack, or dispenser together with instructions for administration.
A pharmaceutical composition typically is formulated to be compatible with its intended route of administration. Examples of routes of administration include parenteral, e.g., intravenous, intradermal, subcutaneous, oral (e.g., inhalation), transdermal (topical), transmucosal, and rectal administrations Solutions or suspensions used for parenteral, intradermal, or subcutaneous application can include the following components: a sterile diluent such as water for injection, saline solution, fixed oils, polyethylene glycols, glycerin, propylene glycol or other synthetic solvents; antibacterial agents such as benzyl alcohol or methyl parabens; antioxidants such as ascorbic acid or sodium bisulfite; chelating agents such as ethylenediaminetetraacetic acid; buffers such as acetates, citrates or phosphates and agents for the adjustment of tonicity such as sodium chloride or dextrose. pH can be adjusted with acids or bases, such as hydrochloric acid or sodium hydroxide. The parenteral preparation can be enclosed in ampoules, disposable syringes or multiple dose vials made of glass or plastic.
Oral compositions generally include an inert diluent or an edible carrier. For the purpose of oral therapeutic administration, the active compound can be incorporated with excipients and used in the form of tablets, troches, or capsules, e.g., gelatin capsules. Oral compositions can also be prepared using a fluid carrier for use as a mouthwash. Pharmaceutically compatible binding agents, and/or adjuvant materials can be included as part of the composition. The tablets, pills, capsules, troches and the like can contain any of the following ingredients, or compounds of a similar nature: a binder such as microcrystalline cellulose, gum tragacanth or gelatin; an excipient such as starch or lactose, a disintegrating agent such as alginic acid, Primogel, or corn starch; a lubricant such as magnesium stearate; a glidant such as colloidal silicon dioxide; a sweetening agent such as sucrose or saccharin; or a flavoring agent such as peppermint, methyl salicylate, or orange flavoring.
Pharmaceutical compositions suitable for injectable use include sterile aqueous solutions (where water soluble) or dispersions and sterile powders for the extemporaneous preparation of sterile injectable solutions or dispersion. For intravenous administration, suitable carriers include physiological saline, bacteriostatic water, Cremophor ELTM (BASF, Parsippany, N.J.) or phosphate buffered saline (PBS). The composition must be sterile and should be fluid to the extent that easy syringability exists. It should be stable under the conditions of manufacture and storage and must be preserved against the contaminating action of microorganisms such as bacteria and fungi. The carrier can be a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), and suitable mixtures thereof. The proper fluidity can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. Prevention of the action of microorganisms can be achieved by various antibacterial and antifungal agents, for example, parabens, chlorobutanol, phenol, ascorbic acid, thimerosal, and the like. In many cases, it will be preferable to include isotonic agents, for example, sugars, polyalcohols such as mannitol or sorbitol, and/or sodium chloride in the composition. Prolonged absorption of the injectable compositions can be brought about by including in the composition an agent which delays absorption, for example, aluminum monostearate and gelatin.
Sterile injectable solutions can be prepared by incorporating the active compound in the required amount in an appropriate solvent with one or a combination of ingredients enumerated above, as required, followed by filtered sterilization. Generally, dispersions are prepared by incorporating the active compound into a sterile vehicle which contains a basic dispersion medium and the required other ingredients from those enumerated above. In the case of sterile powders for the preparation of sterile injectable solutions, the methods of preparation often utilized are vacuum drying and freeze-drying which yields a powder of the active ingredient plus any additional desired ingredient from a previously sterile-filtered solution thereof.
Systemic administration might be by transmucosal or transdermal means. For transmucosal or transdermal administration, penetrants appropriate to the barrier to be permeated are used in the formulation. Such penetrants are generally known in the art, and include, for example, for transmucosal administration, detergents, bile salts, and fusidic acid derivatives. Transmucosal administration can be accomplished through the use of nasal sprays or suppositories. For transdermal administration, the active compounds are formulated into ointments, salves, gels, or creams as generally known in the art. Molecules can also be prepared in the form of suppositories (e.g., with conventional suppository bases such as cocoa butter and other glycerides) or retention enemas for rectal delivery.
In one embodiment, active molecules are prepared with carriers that will protect the compound against rapid elimination from the body, such as a controlled release formulation, including implants and microencapsulated delivery systems. Biodegradable, biocompatible polymers can be used, such as ethylene vinyl acetate, polyanhydrides, polyglycolic acid, collagen, polyorthoesters, and polylactic acid. Methods for preparation of such formulations will be apparent to those skilled in the art. Materials can also be obtained commercially from Alza Corporation and Nova Pharmaceuticals, Inc. Liposomal suspensions (including liposomes targeted to infected cells with monoclonal antibodies to viral antigens) can also be used as pharmaceutically acceptable carriers. These can be prepared according to methods known to those skilled in the art, for example, as described in U.S. Pat. No. 4,522,811.
It is advantageous to formulate oral or parenteral compositions in dosage unit form for ease of administration and uniformity of dosage. Each unit containing a predetermined quantity of active compound is calculated to produce the desired therapeutic effect in association with the required pharmaceutical carrier.
Toxicity and therapeutic efficacy of such compounds can be determined by standard pharmaceutical procedures in cell cultures or experimental animals, e.g., for determining the LD50 (the dose lethal to 50% of the population) and the ED.sub.50 (the dose therapeutically effective in 50% of the population). The dose ratio between toxic and therapeutic effects is the therapeutic index and it can be expressed as the ratio LD50/ED50. Molecules which exhibit high therapeutic indices often are utilized. While molecules that exhibit toxic side effects may be used, care should be taken to design a delivery system that targets such compounds to the site of affected tissue in order to minimize potential damage to uninfected cells and, thereby, reduce side effects.
The data obtained from the cell culture assays and animal studies can be used in formulating a range of dosage for use in humans. The dosage of such molecules typically lies within a range of circulating concentrations that include the ED50 with little or no toxicity. The dosage may vary within this range depending upon the dosage form employed and the route of administration utilized. For any molecules used in methods described herein, the therapeutically effective dose can be estimated initially from cell culture assays. A dose may be formulated in animal models to achieve a circulating plasma concentration range that includes the IC.sub.50 (i.e., the concentration of the test compound which achieves a half-maximal inhibition of symptoms) as determined in cell culture. Such information can be used to more accurately determine useful doses in humans. Levels in plasma may be measured, for example, by high performance liquid chromatography.
As defined herein, a therapeutically effective amount of protein or polypeptide (i.e., an effective dosage) ranges from about 0.001 to 30 mg/kg body weight, sometimes about 0.01 to 25 mg/kg body weight, often about 0.1 to 20 mg/kg body weight, and more often about 1 to 10 mg/kg, 2 to 9 mg/kg, 3 to 8 mg/kg, 4 to 7 mg/kg, or 5 to 6 mg/kg body weight. The protein or polypeptide can be administered one time per week for between about 1 to 10 weeks, sometimes between 2 to 8 weeks, often between about 3 to 7 weeks, and more often for about 4, 5, or 6 weeks. The skilled artisan will appreciate that certain factors may influence the dosage and timing required to effectively treat a subject, including but not limited to the severity of the disease or disorder, previous treatments, the general health and/or age of the subject, and other diseases present. Moreover, treatment of a subject with a therapeutically effective amount of a protein, polypeptide, or antibody can include a single treatment or, can include a series of treatments.
For antibodies, a dosage of 0.1 mg/kg of body weight (generally 10 mg/kg to 20 mg/kg) is often utilized. If the antibody is to act in the brain, a dosage of 50 mg/kg to 100 mg/kg is often appropriate. Generally, partially human antibodies and fully human antibodies have a longer half-life within the human body than other antibodies. Accordingly, lower dosage and less frequent administration is often possible. Modifications such as lipidation can be used to stabilize antibodies and to enhance uptake and tissue penetration (e.g., into the brain). A method for lipidation of antibodies is described by Cruikshank et al. (Cruikshank et al., 1997).
Antibody conjugates can be used for modifying a given biological response, the drug moiety is not to be construed as limited to classical chemical therapeutic agents. For example, the drug moiety may be a protein or polypeptide possessing a desired biological activity. Such proteins may include, for example, a toxin such as abrin, ricin A, pseudomonas exotoxin, or diphtheria toxin; a polypeptide such as tumor necrosis factor, alpha-interferon, beta-interferon, nerve growth factor, platelet derived growth factor, tissue plasminogen activator; or, biological response modifiers such as, for example, lymphokines, interleukin-1 (“IL-1”), interleukin-2 (“IL-2”), interleukin-6 (“IL-6”), granulocyte macrophage colony stimulating factor (“GM-CSF”), granulocyte colony stimulating factor (“G-CSF”), or other growth factors. Alternatively, an antibody can be conjugated to a second antibody to form an antibody heteroconjugate as described by Segal in U.S. Pat. No. 4,676,980.
For compounds, exemplary doses include milligram or microgram amounts of the compound per kilogram of subject or sample weight, for example, about 1 microgram per kilogram to about 500 milligrams per kilogram, about 100 micrograms per kilogram to about 5 milligrams per kilogram, or about 1 microgram per kilogram to about 50 micrograms per kilogram. It is understood that appropriate doses of a small molecule depend upon the potency of the small molecule with respect to the expression or activity to be modulated. When one or more of these small molecules is to be administered to an animal (e.g., a human) in order to modulate expression or activity of a polypeptide or nucleic acid described herein, a physician, veterinarian, or researcher may, for example, prescribe a relatively low dose at first, subsequently increasing the dose until an appropriate response is obtained. In addition, it is understood that the specific dose level for any particular animal subject will depend upon a variety of factors including the activity of the specific compound employed, the age, body weight, general health, gender, and diet of the subject, the time of administration, the route of administration, the rate of excretion, any drug combination, and the degree of expression or activity to be modulated.
With regard to nucleic acid formulations, gene therapy vectors can be delivered to a subject by, for example, intravenous injection, local administration (see, e.g., U.S. Pat. No. 5,328,470) or by stereotactic injection (Chen et al., 1994). Pharmaceutical preparations of gene therapy vectors can include a gene therapy vector in an acceptable diluent, or can comprise a slow release matrix in which the gene delivery vehicle is imbedded. Alternatively, where the complete gene delivery vector can be produced intact from recombinant cells (e.g., retroviral vectors) the pharmaceutical preparation can include one or more cells which produce the gene delivery system. Examples of gene delivery vectors are described herein.
Therapeutic Methods
A therapeutic formulation described above can be administered to a subject in need of a therapeutic for treating colorectal cancer. Therapeutic formulations can be administered by any of the paths described herein. With regard to both prophylactic and therapeutic methods of treatment, such treatments may be specifically tailored or modified, based on knowledge obtained from pharmacogenomic analyses described herein.
A treatment is the application or administration of a therapeutic formulation to a subject, or application or administration of a therapeutic agent to an isolated tissue or cell line from a subject with the purpose to cure, heal, alleviate, relieve, alter, remedy, ameliorate, improve or affect colorectal cancer, symptoms of colorectal cancer or a predisposition towards colorectal cancer. A therapeutic formulation includes small molecules, peptides, antibodies, ribozymes and antisense oligonucleotides. Administration of a therapeutic formulation can occur prior to the manifestation of symptoms characteristic of colorectal cancer, such that the cancer is prevented or delayed in its progression. The appropriate therapeutic composition can be determined based on screening assays described herein.
As discussed, successful treatment of colorectal cancer can be brought about by techniques that serve to agonize target molecule expression or function, or alternatively, antagonize target molecule expression or function. These techniques include administration of modulators that include, but are not limited to, small organic or inorganic molecules; antibodies (including, for example, polyclonal, monoclonal, humanized, anti-idiotypic, chimeric or single chain antibodies, and FAb, F(ab′)2 and FAb expression library fragments, scFV molecules, and epitope-binding fragments thereof); and peptides, phosphopeptides, or polypeptides.
Further, antisense and ribozyme molecules that inhibit expression of the target gene can also be used to reduce the level of target gene expression, thus effectively reducing the level of target gene activity. Still further, triple helix molecules can be utilized in reducing the level of target gene activity. Antisense, ribozyme and triple helix molecules are discussed above. It is possible that the use of antisense, ribozyme, and/or triple helix molecules to reduce or inhibit mutant gene expression can also reduce or inhibit the transcription (triple helix) and/or translation (antisense, ribozyme) of mRNA produced by normal target gene alleles, such that the concentration of normal target gene product present can be lower than is necessary for a normal phenotype. In such cases, nucleic acid molecules that encode and express target gene polypeptides exhibiting normal target gene activity can be introduced into cells via gene therapy method. Alternatively, in instances in that the target gene encodes an extra-cellular polypeptide, it can be preferable to co-administer normal target gene polypeptide into the cell or tissue in order to maintain the requisite level of cellular or tissue target gene activity.
Another method by which nucleic acid molecules may be utilized in treating or preventing colorectal cancer is use of aptamer molecules specific for target molecules. Aptamers are nucleic acid molecules having a tertiary structure which permits them to specifically bind to ligands (Osborne et al., 1997; Patel, 1997).
Yet another method of utilizing nucleic acid molecules for colorectal cancer treatment is gene therapy, which can also be referred to as allele therapy. The invention thus includes a gene therapy method for treating colorectal cancer in a subject, which includes contacting one or more cells in the subject or from the subject with a nucleic acid having a first nucleotide sequence. Genomic DNA in the subject includes a second nucleotide sequence having one or more SNPs associated with colorectal cancer. The first and second nucleotide sequences typically are substantially identical to one another, and the first nucleotide sequence comprises fewer SNPs associated with colorectal cancer than the second nucleotide sequence. The first nucleotide sequence may comprise a gene sequence that encodes a full-length polypeptide or a fragment thereof. The subject is often a human. Allele therapy methods often are utilized in conjunction with a method of first determining whether a subject has genomic DNA that includes SNPs associated with colorectal cancer.
Another allele therapy is a method which comprises contacting one or more cells in the subject or from the subject with a polypeptide encoded by a nucleic acid having a first nucleotide sequence. Genomic DNA in the subject includes a second nucleotide sequence having one or more SNPs associated with colorectal cancer. The first and second nucleotide sequences typically are substantially identical to one another, and the first nucleotide sequence includes fewer SNPs associated with colorectal cancer than the second nucleotide sequence. The first nucleotide sequence may include a gene sequence that encodes a full-length polypeptide or a fragment thereof. The subject is usually a human.
For antibody-based therapies, antibodies can be generated that are both specific for target molecules and that reduce target molecule activity. Such antibodies may be administered in instances where antagonizing a target molecule function is appropriate for the treatment of colorectal cancer.
In circumstances where stimulating antibody production in an animal or a human subject by injection with a target molecule is harmful to the subject, it is possible to generate an immune response against the target molecule by use of anti-idiotypic antibodies (Herlyn and Birebent, 1999; Bhattacharya-Chatterjee and Foon, 1998). Introducing an anti-idiotypic antibody to a mammal or human subject often stimulates production of anti-anti-idiotypic antibodies, which typically are specific to the target molecule. Vaccines directed to colorectal cancer also may be generated in this fashion.
In instances where the target molecule is intracellular and whole antibodies are used, internalizing antibodies often are utilized. Lipofectin or liposomes can be used to deliver the antibody or a fragment of the Fab region that binds to the target antigen into cells. Where fragments of the antibody are used, the smallest inhibitory fragment that binds to the target antigen often is utilized. For example, peptides having an amino acid sequence corresponding to the Fv region of the antibody can be used. Alternatively, single chain neutralizing antibodies that bind to intracellular target antigens can also be administered. Such single chain antibodies can be administered, for example, by expressing nucleotide sequences encoding single-chain antibodies within the target cell population (Marasco et al., 1993).
Modulators can be administered to a patient at therapeutically effective doses to treat colorectal cancer. A therapeutically effective dose refers to an amount of the modulator sufficient to result in amelioration of symptoms of colorectal cancer. Toxicity and therapeutic efficacy of modulators can be determined by standard pharmaceutical procedures in cell cultures or experimental animals, e.g., for determining the LD50 (the dose lethal to 50% of the population) and the ED50 (the dose therapeutically effective in 50% of the population). The dose ratio between toxic and therapeutic effects is the therapeutic index and it can be expressed as the ratio LD50/ED50. Modulators that exhibit large therapeutic indices often are utilized. While modulators that exhibit toxic side effects can be used, care should be taken to design a delivery system that targets such molecules to the site of affected tissue in order to minimize potential damage to uninfected cells, thereby reducing side effects.
Data obtained from cell culture assays and animal studies can be used in formulating a range of dosages for use in humans. The dosage of such compounds typically lies within a range of circulating concentrations that include the ED50 with little or no toxicity. The dosage can vary within this range depending upon the dosage form employed and the route of administration utilized. The therapeutically effective dose can be estimated initially from cell culture assays. A dose can be formulated in animal models to achieve a circulating plasma concentration range that includes the IC50 (i.e., the concentration of the test compound that achieves a half-maximal inhibition of symptoms) as determined in cell culture. Such information can be used to more accurately determine useful doses in humans. Levels in plasma can be measured, for example, by high performance liquid chromatography.
Another example of effective dose determination for an individual is the ability to directly assay levels of “free” and “bound” compound in the serum of the test subject. Such assays may utilize antibody mimics and/or “biosensors” that have been created through molecular imprinting techniques. Molecules that modulate target molecule activity are used as a template, or “imprinting molecule”, to spatially organize polymerizable monomers prior to their polymerization with catalytic reagents. The subsequent removal of the imprinted molecule leaves a polymer matrix which contains a repeated “negative image” of the compound and is able to selectively rebind the molecule under biological assay conditions. A detailed review of this technique can be seen in Ansell et al. (Ansell et al., 1996). Such “imprinted” affinity matrixes are amenable to ligand-binding assays, whereby the immobilized monoclonal antibody component is replaced by an appropriately imprinted matrix. An example of the use of such matrixes in this way can be seen in Vlatakis, et al. (Vlatakis et al., 1993). Through the use of isotope-labeling, the “free” concentration of compound which modulates target molecule expression or activity readily can be monitored and used in calculations of IC50. Such “imprinted” affinity matrixes can also be designed to include fluorescent groups whose photon-emitting properties measurably change upon local and selective binding of target compound. These changes readily can be assayed in real time using appropriate fiberoptic devices, in turn allowing the dose in a test subject to be quickly optimized based on its individual IC50.
The examples set forth below are intended to illustrate but not limit the invention.
Genomic DNA samples from patients aged 25-74 and patients with both familial and sporadic CRC with family and unrelated ethnically matched controls were studied. We identified CRC-associated alleles by measuring 99,632 single nucleotide polymorphisms in peripheral blood DNA from 2,475 subjects (1,234 cases with colorectal cancer and 1,241 age matched individuals undiseased at the time of testing), and validating the identified CRC-associated alleles by using peripheral blood DNA from a second, different, group of 2,194 subjects (1,139 cases with colorectal cancer and 1,055 age matched individuals undiseased at the time of testing). Patients with clinically documented well characterized inherited colorectal cancer syndromes such as Familial Adenomatous Polyposis (FAP) or Hereditary Non Polyposis Colorectal Cancer were excluded from our analysis. Single nucleotide polymorphisms were selected to maximize measurement of genomic variability by choosing these markers that were in the greatest degree of linkage disequilibrium with neighboring SNPs. This was determined by calculating correlation coefficients (r2) with successive neighboring SNPs at each site of polymorphism until an arbitrary cut off of 0.8 was observed. Marker SNPs selected for measurement were in linkage disequilibrium with a maximal number of adjacent SNPs, thus providing an economical method for measuring diversity over a large portion of the genome.
Single Nucleotide Polymorphisms selected for study were derived from the International Haplotype Mapping Project (http://www.hapmap.org) August 2004 release, information about which is available from the National Institutes of Health, National Institutes of Health (NIH; http://www.nih.gov/), 9000 Rockville Pike, Bethesda, Md. 20892. The SNPs were analyzed on DNA from our control and study population using either the Illumina Bead Array system (http://www.illumina.com; Illumina, Inc., 9885 Towne Centre Drive, San Diego, Calif. 92121-1975), the MIP platform (http://www.affymetrix.com, Affymetrix, Inc., 3380 Central Expressway, Santa Clara, Calif. 95051), the Affymetrix GeneChip® Human Mapping 100K Set platform (http://www.affymetrix.com, Affymetrix, Inc., 3380 Central Expressway, Santa Clara, Calif. 95051), or the Affymetrix GeneChip® Human Mapping 500K Array Set platform (http://www.affymetrix.com, Affymetrix, Inc., 3380 Central Expressway, Santa Clara, Calif. 95051). The SNPs for the Illumina Bead Array system were selected on the basis of being associated with genes involved in DNA repair, chromosomal stability or signal transduction and expressed in human colon epithelium. The SNPs for the MIP platform were selected to include most SNPs that would alter the coding sequence of a protein product. The SNPs for the Affymetrix GeneChip® Human Mapping 100K Set platform were selected as to cover the entire genome, but the SNPs were preferentially selected in genic regions present on XbaI or HindIII restriction fragments varying in length from about 250 base pairs to about 2000 base pairs. The SNPs for the Affymetrix GeneChip® Human Mapping 500K Array Set platforms were selected as to cover the entire genome, but the SNPs were preferentially selected in genic regions present on NspI and Styl restriction fragments varying in length from about 200 base pairs to about 1100 base pairs. Data was stored and organized using the Nanuq informatics environment of the McGill University and Genome Quebec Innovation Centre (http://www.genomequebec.mcgill.ca/; McGill University and Genome Quebec Innovation Centre, 740, Docteur Penfield Avenue, Montreal, Quebec H3A 1A4). Allele frequencies found within DNA from patients with colorectal cancer and those without this disease were compared using the univariate Mantel-Haenszel Chi-Square statistic.
The inventors of the present invention have discovered single base pair polymorphisms that are present in a highly significant percentage of the genetic DNA of individuals affected with colorectal cancer while only present in a smaller percentage of individuals who are not known to be affected by the disease.
EXAMPLE 1
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 20900501 of chromosome 1, found within the EIF4G3 gene, was different from those without colorectal cancer (Table 1). The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.008235 based on permutation analysis, and the corresponding recessive odds ratio is 1.353 (Table 1). These data further suggest that this marker, located within the EIF4G3 gene, is associated with colorectal cancer risk and that the C allele at position 20900501 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 1









rs no.
2320590



Chromosome; Position
1; 20900501



Gene Name
EIF4G3



SEQ ID NO; Position
1761; 222293



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.07125

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
307
520
173
Recessive
0.008235
1.353


1
C
295
486
221









Table 1A indicates SNPs found to be in strong linkage disequilibrium with rs2320590. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 1A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs951805
0.627
20805662
1



rs710311
0.702
20807307
2



rs12123092
0.697
20812307
3



rs12121807
0.702
20814435
4



rs10916859
0.702
20833262
5



rs7548269
0.627
20834778
6



rs7548649
0.702
20835387
7



rs3736880
0.702
20843033
8



rs651085
0.871
20843089
9



rs651538
0.902
20843172
10



rs589755
0.896
20845152
11



rs1021077
0.702
20851322
12



rs12123093
0.603
20859722
13



rs3856173
0.676
20860139
14



rs4233274
0.966
20866984
15



rs1152999
0.57
20868329
16



rs1152998
0.752
20869596
17



rs3125161
0.729
20871652
18



rs3121071
0.551
20873726
19



rs7520481
0.724
20885691
20



rs935918
0.649
20890966
21



rs10753507
0.867
20897686
22



rs4654873
0.603
20897690
23



rs10799665
0.676
20897946
24



rs2320590
—
20900501
25



rs4654874
0.933
20901973
26



rs11805169
0.697
20902168
27



rs4654875
0.555
20910482
28



rs935917
0.729
20912408
29



rs4654724
0.651
20922516
30



rs2305463
0.868
20925487
31



rs7543140
0.605
20925556
32



rs1530946
0.651
20927846
33



rs4654880
0.745
20931914
34



rs10916885
0.925
20934009
35



rs6695218
0.539
20935818
36



rs7519685
0.651
20937929
37



rs2167811
0.646
20939816
38



rs3890762
0.899
20943571
39



rs10737452
0.651
20945070
40



rs10916891
0.551
20945280
41



rs4654725
0.651
20945717
42



rs4654726
0.729
20949204
43



rs17449966
0.629
20949302
44



rs7545133
0.729
20951449
45



rs4654881
0.934
20955075
46



rs2290381
0.651
20958577
47



rs4654883
0.895
20959014
48



rs4654727
0.729
20960041
49



rs2275468
0.729
20965681
50



rs6704421
0.902
20965980
51



rs17410008
0.651
20966007
52



rs4654729
0.934
20969559
53



rs3767247
0.651
20972644
54



rs4654887
0.729
20980229
55



rs10916900
0.934
20984365
56



rs6699704
0.551
20986738
57



rs10916903
0.651
20993250
58



rs11805006
0.934
20994909
59



rs6692677
0.934
20997023
60



rs17450586
0.565
20999899
61



rs12407731
0.934
21000095
62



rs10916906
0.643
21000981
63



rs6698440
0.9
21004018
64



rs10916907
0.9
21006394
65



rs10442633
0.9
21010403
66



rs12133780
0.694
21016114
67



rs3767248
0.694
21022160
68



rs6700459
0.617
21024702
69



rs12137408
0.9
21028251
70



rs6697555
0.694
21033244
71



rs10916911
0.9
21035367
72



rs6669077
0.894
21035826
73



rs6697284
0.9
21040905
74



rs2271115
0.694
21041170
75



rs6700718
0.687
21044669
76



rs4654893
0.551
21050902
77



rs12021529
0.551
21051467
78



rs7540023
0.571
21055398
79



rs10916919
0.566
21062830
80



rs10799677
0.517
21063762
81



rs10799678
0.9
21068091
82



rs12123300
0.575
21068874
83



rs2874367
0.9
21069797
84



rs11302414
0.664
21072609
85



rs12130664
0.617
21078118
86



rs6661116
0.694
21082461
87



rs12070677
0.898
21082628
88



rs6681064
0.694
21084950
89



rs6659152
0.662
21101147
90



rs6426658
0.617
21106482
91



rs6685914
0.545
21107684
92



rs6684976
0.694
21112807
93



rs6668370
0.9
21114874
94



rs6703227
0.694
21120116
95



rs964466
0.565
21120469
96



rs10493006
0.617
21121210
97



rs6426665
0.9
21127511
98



rs10916927
0.617
21131101
99



rs6658526
0.541
21136620
100



rs1354792
0.9
21137181
101



rs12567861
0.551
21140439
102



rs10916930
0.559
21140663
103



rs6426667
0.897
21141522
104



rs6426668
0.694
21141902
105



rs6692244
0.694
21142192
106



rs7521711
0.9
21145524
107



rs1567128
0.512
21149959
108










EXAMPLE 2
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 54538208 of chromosome 1, found within the SSBP3 gene, was different from those without colorectal cancer (Table 2). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.002647, and the corresponding dominant odds ratio is 1.348 (Table 2). These data further suggest that this marker, located within the SSBP3 gene, is associated with colorectal cancer risk and that the C allele at position 54538208 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 2









rs no.
10489565



Chromosome; Position
1; 54538208



Gene Name
SSBP3



SEQ ID NO; Position
1762; 45710



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.89558


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
C
740
240
20
Dominant
0.002647
1.348


1
C
680
295
27









Table 2A indicates SNPs found to be in strong linkage disequilibrium with rs10489565. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 2A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO







rs4601533
0.929
54531998
109



rs10489565
—
54538208
110



rs12024740
0.586
54548927
111



rs2073108
0.656
54551090
112



rs17101278
0.656
54552517
113



rs12029610
0.639
54556623
114



rs3795357
0.656
54557621
115



rs12022116
0.635
54561302
116



rs12043222
0.656
54561394
117



rs2297573
0.656
54562638
118



rs4141420
0.591
54563585
119



rs12045400
0.656
54563831
120










EXAMPLE 3
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 97159204 of chromosome 1 was different from those without colorectal cancer (Table 3). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.004716, and the corresponding dominant odds ratio is 1.428 (Table 3). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 97159204 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 3









rs no.
10493889



Chromosome; Position
1; 97159204



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.80154


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
C
841
124
5
Dominant
0.004716
1.428


1
C
817
173
6









Table 3A indicates SNPs found to be in strong linkage disequilibrium with rs10493889. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 3A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs17525524
0.667
96911594
121



rs2391782
0.667
96938696
122



rs17115733
0.647
96961817
123



rs12024594
0.73
97005044
124



rs11165746
1.0
97141267
125



rs10493889
—
97159204
126










EXAMPLE 4
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 97657313 of chromosome 1, found within the DPYD gene, was different from those without colorectal cancer (Table 4). The dominant test for risk associated with carrying the A allele had an empirical p-value based on permutation analysis of 0.047614, and the corresponding dominant odds ratio is 1.236 (Table 4). These data further suggest that this marker, located within the DPYD gene, is associated with colorectal cancer risk and that the A allele at position 97657313 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 4









rs no.
945881



Chromosome; Position
1; 97657313



Gene Name
DPYD



SEQ ID NO; Position
1763; 441288



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.17718

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
236
569
403
Dominant
0.047614
1.236


1
A
202
609
419









Table 4A indicates SNPs found to be in strong linkage disequilibrium with rs945881. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 4A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs11165879
0.699
97653506
127



rs945881
—
97657313
128



rs11165881
1.0
97659904
129










EXAMPLE 5
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 107056364 of chromosome 1 was different from those without colorectal cancer (Table 5). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.0856 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.171 (Table 5). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 107056364 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 5









rs no.
2049064



Chromosome; Position
1; 107056364



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.77232


















Case Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
761
222
14
Trend
0.0856
1.171


1
A
729
247
20









Table 5A indicates SNPs found to be in strong linkage disequilibrium with rs2049064. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 5A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs11184922
0.502
106818235
130



rs7530540
0.61
106828844
131



rs4914979
0.61
106830088
132



rs4409683
0.631
106833215
133



rs10430081
0.568
106891798
134



rs7527883
0.688
106912949
135



rs12066688
0.688
106928115
136



rs7545951
0.574
106930964
137



rs4311915
0.688
106937218
138



rs17017475
0.688
106971827
139



rs17017532
0.935
106998017
140



rs17017567
0.932
107004258
141



rs12085613
0.932
107006719
142



rs12078403
0.935
107010986
143



rs12409858
0.935
107011275
144



rs11184981
0.873
107011305
145



rs12407314
0.935
107011409
146



rs12406199
0.932
107011554
147



rs12407335
0.935
107011627
148



rs12410591
0.932
107012941
149



rs10494050
0.935
107014445
150



rs12079669
0.928
107017707
151



rs10494052
0.935
107021830
152



rs17017658
0.935
107024684
153



rs17492154
0.63
107025142
154



rs2139462
0.935
107033827
155



rs17017694
0.932
107034845
156



rs17017723
1.0
107044596
157



rs17017736
1.0
107047341
158



rs12097821
1.0
107048343
159



rs955988
1.0
107052637
160



rs1519889
1.0
107054139
161



rs1519887
1.0
107056341
162



rs2049064
—
107056364
163



rs1607634
0.734
107079348
164



rs1519874
0.688
107080550
165



rs2030341
0.688
107081508
166



rs908953
0.734
107086826
167



rs10881449
0.688
107088101
168



rs1607635
0.63
107091984
169



rs1156426
0.688
107092704
170



rs7530116
0.688
107093768
171



rs12094371
0.688
107095587
172



rs1519875
0.688
107096669
173



rs1519876
0.672
107098220
174



rs10881450
0.688
107100885
175



rs2102909
0.688
107103052
176



rs7511900
0.688
107112872
177



rs10465780
0.672
107115313
178



rs11184996
0.688
107115334
179










EXAMPLE 6
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 114975727 of chromosome 1, found within the D1S155E gene, was different from those without colorectal cancer (Table 6). The dominant test for risk associated with carrying the G allele had an empirical p-value based on permutation analysis of 0.002032, and the corresponding dominant odds ratio is 1.638 (Table 6). These data further suggest that this marker, located within the D1S155E gene, is associated with colorectal cancer risk and that the G allele at position 114975727 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 6









rs no.
10489525



Chromosome; Position
1; 114975727



Gene Name
D1S155E



SEQ ID NO; Position
1764; 36894



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.04271

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
107
388
476
Dominant
0.002032
1.638


1
G
 70
394
532









Table 6A indicates SNPs found to be in strong linkage disequilibrium with rs10489525. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 6A







Linked SNPs












SNP
r2
Position on chr1
SEQ ID NO







rs10489525
—
114975727
183










EXAMPLE 7
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 115166656 of chromosome 1, found within the SYCP1 gene, was different from those without colorectal cancer (Table 7). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.002586 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.187 (Table 7). These data further suggest that this marker, located within the SYCP1 gene, is associated with colorectal cancer risk and that the A allele at position 115166656 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 7









rs no.
360659



Chromosome; Position
1; 115166656



Gene Name
SYCP1



SEQ ID NO; Position
1765; 57160



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.43217


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
414
552
202
Trend
0.002586
1.187


1
A
378
575
264









Table 7A indicates SNPs found to be in strong linkage disequilibrium with rs360659. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 7A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs2010899
0.518
114947052
180



rs969273
0.522
114968711
181



rs6671984
0.522
114969563
182



rs2007231
0.522
114978348
184



rs2144428
0.569
114981253
185



rs6663115
0.522
114984296
186



rs4140445
0.522
115004020
187



rs3121503
0.966
115071842
188



rs1286555
0.542
115073938
189



rs3121506
0.599
115075249
190



rs3121507
0.964
115077252
191



rs6689326
0.583
115081154
192



rs3126216
0.966
115084567
193



rs1286560
0.583
115087972
194



rs869990
0.583
115091656
195



rs360599
0.815
115100040
196



rs360603
0.966
115101751
197



rs360606
0.583
115103811
198



rs360607
0.599
115104443
199



rs360614
1.0
115111982
200



rs360617
0.603
115116141
201



rs360622
1.0
115119103
202



rs360627
1.0
115125087
203



rs360630
0.564
115127174
204



rs360634
1.0
115132157
205



rs360635
0.564
115132560
206



rs360636
1.0
115132947
207



rs360643
1.0
115139005
208



rs360645
0.564
115139260
209



rs360647
1.0
115141772
210



rs360655
0.564
115159909
211



rs360659
—
115166656
212



rs360661
0.62
115167322
213



rs360576
0.546
115171216
214



rs360586
0.564
115179531
215



rs360588
1.0
115180386
216



rs360590
0.504
115182953
217



rs360591
0.809
115183282
218



rs360596
0.815
115185601
219



rs360668
0.815
115193640
220



rs506934
0.51
115200356
221



rs360675
0.583
115202960
222



rs360682
0.815
115209101
223



rs12135023
0.815
115217819
224



rs1591899
0.805
115226640
225



rs12125190
0.815
115234779
226



rs12026343
0.815
115236258
227



rs7416955
0.812
115242333
228



rs4839017
0.815
115242502
229



rs11102859
0.806
115242740
230



rs6698174
0.815
115244057
231



rs7536888
0.815
115261728
232



rs4839399
0.815
115268188
233



rs11102872
0.815
115277042
234



rs7515454
0.815
115278233
235



rs7517739
0.815
115278345
236



rs7541251
0.815
115278448
237



rs6537849
0.815
115278686
238



rs1575070
0.674
115279927
239



rs1575069
0.689
115280070
240



rs12136420
0.689
115281663
241



rs7530810
0.689
115282510
242



rs7523360
0.689
115282884
243



rs1321108
0.689
115284407
244



rs11102874
0.749
115285912
245



rs3754363
0.686
115287160
246



rs1321107
0.583
115287345
247



rs7514765
0.612
115289952
248



rs1998008
0.703
115292582
249



rs4611011
0.633
115298443
250



rs7413646
0.638
115298798
251



rs11102878
0.55
115303040
252










EXAMPLE 8
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 143040559 of chromosome 1, found within the FLJ25124 gene, was different from those without colorectal cancer (Table 8). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.000396 based on permutation analysis, and the corresponding recessive odds ratio is 1.653 (Table 8). These data further suggest that this marker, located within the FLJ25124 gene, is associated with colorectal cancer risk and that the G allele at position 143040559 of chromosome 1 is associated with an increased risk of developing colorectal cancer.










TABLE 8









rs no.
10494240



Chromosome; Position
1; 143040559



Gene Name
FLJ25124



SEQ ID NO; Position
1766; 2272



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.10646

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
433
447
 90
Recessive
0.000396
1.653


1
G
433
419
144









Table 8A indicates SNPs found to be in strong linkage disequilibrium with rs10494240. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 8A







Linked SNPs














Position




SNP
r2
on chr1
SEQ ID NO
















rs4636400
0.611
142933600
253



rs6688400
0.71
142994415
254



rs872786
0.71
142996870
255



rs2274617
0.898
143024965
256



rs12410298
0.501
143037007
257



rs720899
1.0
143039966
258



rs10494240
—
143040559
259



rs12125340
0.965
143043494
260










EXAMPLE 9
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 20254115 of chromosome 2 was different from those without colorectal cancer (Table 9). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.028471, and the corresponding dominant odds ratio is 1.265 (Table 9). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 20254115 of chromosome 2 is associated with an increased risk of developing colorectal cancer.










TABLE 9









rs no.
973128



Chromosome; Position
2; 20254115



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.56307

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
249
475
245
Dominant
0.028471
1.265


1
C
213
513
266









Table 9A indicates SNPs found to be in strong linkage disequilibrium with rs973128. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 9A







Linked SNPs














Position




SNP
r2
on chr2
SEQ ID NO
















rs17697743
0.755
20250764
261



rs6753830
1.0
20250981
262



rs975951
1.0
20252966
263



rs973128
—
20254115
264



rs875411
1.0
20254650
265



rs875412
1.0
20255588
266



rs6744463
1.0
20256013
267



rs2881879
0.534
20257476
268



rs4666362
0.522
20258973
269



rs6531212
0.522
20259648
270



rs46663641
0.513
20260227
271










EXAMPLE 10
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 49189474 of chromosome 2, found within the FSHR gene, was different from those without colorectal cancer (Table 10). The trend test for risk associated with carrying the G allele had an empirical p-value of 0.005443 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.193 (Table 10). These data further suggest that this marker, located within the FSHR gene, is associated with colorectal cancer risk and that the G allele at position 49189474 of chromosome 2 is associated with an increased risk of developing colorectal cancer.










TABLE 10









rs no.
1504175



Chromosome; Position
2; 49189474



Gene Name
FSHR



SEQ ID NO; Position
1767; 103808



Genotype; Phenotype
n = G; increased risk



Hard-Weinberg
0.43804


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
G
323
501
175
Trend
0.005443
1.193


1
G
281
498
220









Table 10A indicates SNPs found to be in strong linkage disequilibrium with rs1504175. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 10A







Linked SNPs














Position




SNP
r2
on chr2
SEQ ID NO
















rs3788981
0.506
49157212
272



rs9807991
0.693
49163446
273



rs10171892
0.579
49169518
274



rs10865238
0.626
49180455
275



rs12614817
0.776
49183068
276



rs3850344
0.731
49184463
277



rs6716567
1.0
49185265
278



rs11125197
1.0
49186995
279



rs13004879
0.688
49187513
280



rs3913665
0.757
49187893
281



rs1504175
—
49189474
282



rs1504177
0.737
49189694
283



rs2134811
0.757
49190619
284



rs13032266
1.0
49191171
285



rs1504188
0.74
49191484
286



rs1504190
0.737
49192006
287



rs2091786
0.565
49195881
288



rs1394207
0.572
49199434
289



rs4420736
0.565
49199611
290



rs11686474
0.565
49199634
291



rs11680730
0.565
49199711
292



rs11676909
0.581
49203878
293



rs12473815
0.579
49204013
294



rs11125206
0.598
49204336
295



rs1882560
0.565
49205020
296



rs12620805
0.598
49205539
297



rs11903014
0.786
49205989
298



rs6716923
0.552
49227109
299



rs976230
0.552
49239677
300



rs11898430
0.539
49239769
301



rs974896
0.568
49242500
302



rs974897
0.552
49242583
303



rs4510264
0.552
49244528
304



rs9309159
0.502
49253703
305



rs1032838
0.556
49311997
306



rs11125217
0.556
49319087
307



rs11685850
0.556
49329514
308



rs9309160
0.556
49329682
309



rs6720857
0.506
49332061
310



rs4564810
0.53
49332761
311



rs11125222
0.524
49335916
312










EXAMPLE 11
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 186869364 of chromosome 2 was different from those without colorectal cancer (Table 11). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.002126 based on permutation analysis, and the corresponding recessive odds ratio is 3.892 (Table 11). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 186869364 of chromosome 2 is associated with an increased risk of developing colorectal cancer.










TABLE 11









rs no.
10497667



Chromosome; Position
2; 186869364



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.12585


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
G
797
197
6
Recessive
0.002126
3.892


1
G
791
188
23









Table 11A indicates SNPs found to be in strong linkage disequilibrium with rs10497667. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 11A







Linked SNPs














Position




SNP
r2
on chr2
SEQ ID NO
















rs7582258
0.611
186729521
313



rs12615770
0.611
186748482
314



rs12998383
0.635
186752544
315



rs16827480
0.63
186753368
316



rs12614513
0.726
186759677
317



rs10931222
0.63
186771130
318



rs991084
0.63
186774634
319



rs13005466
0.63
186783677
320



rs6750636
0.61
186788675
321



rs13003934
0.612
186795981
322



rs12999989
0.629
186797056
323



rs13028175
0.59
186797101
324



rs12999474
0.627
186804008
325



rs12373738
0.63
186822924
326



rs10186498
0.63
186841731
327



rs6725283
0.891
186849447
328



rs13419562
0.63
186854278
329



rs13394207
0.63
186854406
330



rs13421172
0.63
186856196
331



rs4284795
1.0
186866149
332



rs2887816
0.63
186869233
333



rs10497667
—
186869364
334



rs13388196
0.629
186870116
335



rs2370681
0.63
186873391
336



rs12233005
0.63
186873805
337



rs8179713
1.0
186874321
338



rs13416578
0.63
186876760
339



rs12614595
1.0
186877596
340



rs2370677
1.0
186878043
341



rs4500906
0.908
186883056
342



rs16827554
1.0
186887466
343



rs2370672
1.0
186891840
344



rs2370671
1.0
186892009
345



rs7584724
1.0
186895423
346



rs4461230
1.0
186897281
347



rs16827602
1.0
186898014
348



rs6434164
1.0
186899824
349



rs2370670
1.0
186903194
350



rs16827614
1.0
186905158
351



rs3107174
0.915
186910195
352



rs3107423
0.908
186918596
353



rs2887818
0.915
186918660
354



rs3112312
0.901
186933341
355



rs1878754
0.915
186935034
356



rs3112315
0.915
186937617
357



rs2370659
0.915
186938372
358



rs3112316
0.915
186938761
359



rs3107410
0.915
186940537
360



rs3112317
0.915
186942136
361



rs10195099
0.591
186944471
362



rs2370662
0.915
186945120
363



rs10931232
0.915
186950816
364



rs2029085
0.915
187032899
365



rs10497669
0.643
187050892
366










EXAMPLE 12
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 218776751 of chromosome 2, found within the FLJ46536 gene, was different from those without colorectal cancer (Table 12). The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.005832 based on permutation analysis, and the corresponding recessive odds ratio is 1.335 (Table 12). These data further suggest that this marker, located within the FLJ46536 gene, is associated with colorectal cancer risk and that the C allele at position 218776751 of chromosome 2 is associated with an increased risk of developing colorectal cancer.










TABLE 12









rs no.
4133195



Chromosome; Position
2; 218776751



Gene Name
FLJ46536



SEQ ID NO; Position
1768; 51535



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.79932


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
288
493
219
Recessive
0.005832
1.335


1
C
279
450
273









Table 12A indicates SNPs found to be in strong linkage disequilibrium with rs4133195. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 12A







Linked SNPs














Position




SNP
r2
on chr2
SEQ ID NO
















rs4672870
0.647
218767422
367



rs12694425
0.647
218767819
368



rs12694426
0.637
218767857
369



rs10932745
0.669
218768482
370



rs11687200
0.665
218770121
371



rs11676275
0.669
218770314
372



rs12694427
0.669
218770551
373



rs6737563
0.934
218771180
374



rs13013361
0.933
218773021
375



rs4133195
—
218776751
376



rs6726126
1.0
218777739
377



rs10804264
0.819
218781315
378



rs12694428
0.63
218784326
379



rs13035513
0.935
218786186
380



rs13007992
0.792
218789557
381



rs7426289
0.935
218791821
382



rs6436029
0.785
218803037
383



rs4674257
0.935
218814280
384



rs4674259
0.935
218816511
385



rs6723449
0.934
218823086
386



rs1126579
0.967
218826240
387



rs4674261
0.625
218830515
388



rs11677534
0.935
218832566
389



rs13009946
0.935
218833258
390



rs7594532
0.918
218833506
391



rs7607437
0.935
218833898
392



rs11676348
0.74
218835652
393



rs13027120
0.935
218846420
394



rs1008563
0.625
218852394
395



rs1008562
0.935
218852478
396



rs4674267
0.625
218871943
397



rs13397673
0.641
218873288
398










EXAMPLE 13
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 230825727 of chromosome 2 was different from those without colorectal cancer (Table 13). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.022599 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.160 (Table 13). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 230825727 of chromosome 2 is associated with an increased risk of developing colorectal cancer.










TABLE 13









rs no.
10498243



Chromosome; Position
2; 230825727



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.12363


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
467
424
75
Trend
0.022599
1.160


1
C
444
443
107









Table 13A indicates SNPs found to be in strong linkage disequilibrium with rs10498243. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 13A







Linked SNPs














Position




SNP
r2
on chr2
SEQ ID NO
















rs12694839
0.527
230822818
399



rs12694840
0.523
230822908
400



rs6706782
1.0
230823742
401



rs6707129
1.0
230824051
402



rs10933323
1.0
230824308
403



rs10933324
1.0
230824428
404



rs1529377
1.0
230825316
405



rs12694841
1.0
230825613
406



rs10498243
—
230825727
407



rs6715536
1.0
230825877
408



rs1549567
1.0
230827852
409



rs6721137
1.0
230828862
410



rs1365775
1.0
230829298
411



rs10933326
1.0
230830081
412



rs2396713
0.961
230830316
413



rs13004807
1.0
230830886
414



rs10048686
1.0
230832540
415



rs2894694
0.501
230838320
416



rs11677105
0.527
230842525
417










EXAMPLE 14
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 25062781 of chromosome 3 was different from those without colorectal cancer (Table 14). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.009697 based on permutation analysis, and the corresponding recessive odds ratio is 1.298 (Table 14). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 25062781 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 14









rs no.
4484159



Chromosome; Position
3; 25062781



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.29815


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
22
278
667
Recessive
0.009697
1.298


1
A
22
231
730









Table 14A indicates SNPs found to be in strong linkage disequilibrium with rs4484159. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 14A







Linked SNPs














Position




SNP
r2
on chr3
SEQ ID NO
















rs13067187
0.583
25052936
418



rs6777624
0.854
25054402
419



rs9866836
0.877
25056885
420



rs17015670
1.0
25061156
421



rs4484159
—
25062781
422



rs1604007
0.817
25068060
423



rs988268
0.808
25076452
424



rs6550943
0.778
25084253
425



rs6777955
0.932
25084806
426



rs6766372
0.757
25086476
427



rs994267
0.825
25090198
428



rs1574901
0.825
25090417
429



rs6775433
0.824
25091862
430



rs4858698
0.825
25093457
431



rs7430038
0.825
25099388
432



rs1587430
0.825
25100369
433



rs4858700
0.517
25102693
434



rs11294076
0.788
25105990
435



rs4858703
0.825
25108277
436



rs2036270
0.825
25112900
437



rs972016
0.825
25114656
438



rs1603987
0.825
25115540
439



rs6807196
0.696
25117575
440



rs4858704
0.517
25118394
441



rs1580817
0.825
25121605
442










EXAMPLE 15
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 25244762 of chromosome 3, found within the LOC442077 gene, was different from those without colorectal cancer (Table 15). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.005641 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.300 (Table 15). These data further suggest that this marker, located within the LOC442077 gene, is associated with colorectal cancer risk and that the A allele at position 25244762 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 15









rs no.
10510558



Chromosome; Position
3; 25244762



Gene Name
LOC442077



SEQ ID NO; Position
1769; 53870



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.80066


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
20
253
724
Trend
0.005641
1.300


1
A
13
209
779









Table 15A indicates SNPs found to be in strong linkage disequilibrium with rs10510558. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 15A







Linked SNPs














Position




SNP
r2
on chr3
SEQ ID NO
















rs13060347
0.929
25169305
443



rs17517792
0.929
25170688
444



rs17517931
0.914
25184366
445



rs13068891
0.853
25188663
446



rs13061437
0.924
25194200
447



rs17578042
0.929
25205423
448



rs17578259
0.929
25207827
449



rs13100362
0.872
25211158
450



rs2068130
0.818
25211837
451



rs1561115
0.932
25235457
452



rs17015971
0.932
25238040
453



rs13096074
0.844
25239011
454



rs17015978
1.0
25239845
455



rs7432016
1.0
25243914
456



rs10510558
—
25244762
457



rs10510559
1.0
25244932
458



rs10510560
1.0
25245547
459



rs13092896
0.799
25250478
460



rs7427426
1.0
25264520
461



rs1601161
1.0
25265009
462



rs1992060
0.919
25269521
463



rs1992059
0.932
25273091
464



rs13082318
0.932
25273425
465



rs13087573
0.932
25274083
466



rs17016060
0.932
25275052
467



rs13074533
0.932
25277488
468



rs10510561
0.932
25279386
469



rs17016078
0.932
25280012
470



rs13093059
0.932
25280571
471



rs13068143
0.932
25283486
472



rs13091754
0.932
25283965
473



rs17016117
0.932
25284812
474



rs17016120
0.932
25285067
475



rs13059799
0.932
25287098
476



rs13082440
0.928
25287161
477



rs17016133
0.932
25288171
478



rs13084418
0.932
25291318
479



rs13084608
0.932
25291410
480



rs17016141
0.861
25295964
481



rs1436239
0.861
25300483
482










EXAMPLE 16
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 62952892 of chromosome 3 was different from those without colorectal cancer (Table 16). The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.001158 based on permutation analysis, and the corresponding recessive odds ratio is 2.127 (Table 16). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 62952892 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 16









rs no.
4404442



Chromosome; Position
3; 62952892



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.06369


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
C
623
321
27
Recessive
0.001158
2.127


1
C
627
310
57









Table 16A indicates SNPs found to be in strong linkage disequilibrium with rs4404442. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 16A







Linked SNPs














Position




SNP
r2
on chr3
SEQ ID NO
















rs9828340
0.528
62937809
483



rs12631618
1.0
62941462
484



rs6807315
1.0
62943033
485



rs4312654
1.0
62943151
486



rs4583651
1.0
62943547
487



rs13072243
1.0
62945427
488



rs4613448
0.948
62949979
489



rs4404442
—
62952892
490



rs13091015
1.0
62955440
491



rs9814898
1.0
62957942
492



rs17067503
1.0
62958060
493



rs10510890
0.948
62959133
494



rs9821058
1.0
62959399
495



rs10510891
1.0
62960430
496



rs13084396
1.0
62961266
497



rs4147406
0.95
62962215
498



rs2367590
1.0
62964393
499



rs17067527
0.898
62965607
500



rs12488885
0.948
62966446
501



rs17361212
0.752
62966549
502



rs11130909
0.947
62968123
503



rs13099709
0.948
62968779
504



rs13079904
0.948
62968976
505



rs2367591
0.898
62969677
506



rs9850740
0.947
62970029
507



rs10510892
0.948
62970190
508



rs2367592
0.852
62970589
509



rs11130910
0.887
62971291
510



rs7372226
0.947
62972138
511



rs13061838
0.898
62975188
512



rs6770985
0.528
62981633
513



rs1447443
0.528
62982901
514



rs12637433
0.528
62983787
515



rs4688357
0.555
62985367
516










EXAMPLE 17
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 120037273 of chromosome 3 was different from those without colorectal cancer (Table 17). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.000464 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.407 (Table 17). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 120037273 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 17









rs no.
1402582



Chromosome; Position
3; 120037273



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.00386


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
776
202
3
Trend
0.000464
1.407


1
A
710
254
11









Table 17A indicates SNPs found to be in strong linkage disequilibrium with rs1402582. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 17A







Linked SNPs












SNP
r2
Position on chr3
SEQ ID NO







rs1081903
0.549
120036240
519



rs1402582
—
120037273
520



rs812824
0.608
120037336
521



rs2936727
0.608
120037804
522



rs1521289
0.608
120039183
523



rs2684320
0.608
120039851
524



rs2649882
0.608
120044441
525










EXAMPLE 18
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 120037336 of chromosome 3 was different from those without colorectal cancer (Table 18). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.001767 based on permutation analysis, and the corresponding recessive odds ratio is 1.986 (Table 18). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 120037336 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 18









rs no.
812824



Chromosome; Position
3; 120037336



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.01053


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
G
582
357
32
Recessive
0.001767
1.986


1
G
575
356
63









Table 18A indicates SNPs found to be in strong linkage disequilibrium with rs812824. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 18A







Linked SNPs












SNP
r2
Position on chr3
SEQ ID NO
















rs881603
0.705
120013362
517



rs881604
0.711
120013382
518



rs1081903
0.953
120036240
519



rs1402582
0.608
120037273
520



rs812824
—
120037336
521



rs2936727
1.0
120037804
522



rs1521289
1.0
120039183
523



rs2684320
1.0
120039851
524



rs2649882
1.0
120044441
525










EXAMPLE 19
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 186033203 of chromosome 3, found within the KIAA0804 gene, was different from those without colorectal cancer (Table 19). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.009969 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.193 (Table 19). These data further suggest that this marker, located within the KIAA0804 gene, is associated with colorectal cancer risk and that the A allele at position 186033203 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 19









rs no.
9830734



Chromosome; Position
3; 186033203



Gene Name
KIAA0804



SEQ ID NO; Position
1770; 8081



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.08380


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
98
512
520
Trend
0.009969
1.193


1
A
81
472
583









Table 19A indicates SNPs found to be in strong linkage disequilibrium with rs9830734. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 19A







Linked SNPs














Position




SNP
r2
on chr3
SEQ ID NO
















rs4686769
0.765
186008653
526



rs2377115
0.71
186008673
527



rs725656
0.636
186008910
528



rs7640976
1.0
186012692
529



rs13079793
0.619
186027445
530



rs10513799
0.636
186032241
531



rs9830734
—
186033203
532



rs4432622
0.617
186038166
533



rs11710551
0.643
186041770
534



rs16859344
0.636
186043671
535



rs2305240
0.636
186049741
536



rs11720538
0.623
186052729
537



rs6443999
0.6
186056257
538



rs16859357
0.593
186058136
539



rs724273
0.597
186058533
540



rs6809079
0.597
186059022
541



rs7340698
0.636
186060619
542



rs3733165
0.553
186063619
543



rs2377107
0.593
186070576
544



rs7619460
0.597
186070838
545



rs9757458
0.615
186072802
546



rs7628188
0.553
186073295
547



rs7638317
0.557
186076934
548



rs11717139
0.593
186079782
549



rs11714752
0.588
186081364
550



rs9881074
0.593
186083378
551



rs1000270
0.593
186090182
552



rs6762984
0.529
186099834
553



rs4324453
0.593
186104572
554



rs7618180
0.557
186112996
555



rs9821657
0.557
186113805
556



rs4686879
0.556
186115949
557



rs7611263
0.597
186117351
558



rs9825856
0.604
186119962
559



rs9290804
0.557
186126928
560



rs10446349
0.597
186131728
561



rs13066369
0.518
186142625
562



rs9870352
0.576
186146360
563



rs4422281
0.518
186148006
564



rs9820111
0.518
186149057
565



rs6784179
0.518
186152026
566



rs7623170
0.512
186156901
567



rs6765821
0.524
186244971
568



rs6783157
0.521
186252104
569



rs12636670
0.526
186267820
570










EXAMPLE 20
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 187873329 of chromosome 3, found within the HRG gene, was different from those without colorectal cancer (Table 20). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.003172, and the corresponding dominant odds ratio is 1.456 (Table 20). These data further suggest that this marker, located within the HRG gene, is associated with colorectal cancer risk and that the C allele at position 187873329 of chromosome 3 is associated with an increased risk of developing colorectal cancer.










TABLE 20









rs no.
9898



Chromosome; Position
3; 187873329



Gene Name
HRG



SEQ ID NO; Position
1771; 6830



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.00984


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
167
481
483
Dominant
0.003172
1.456


1
C
121
514
503









Table 20A indicates SNPs found to be in strong linkage disequilibrium with rs9898. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 20A







Linked SNPs














Position




SNP
r2
on chr3
SEQ ID NO
















rs3733159
0.8
187843111
571



rs1868154
0.574
187857373
572



rs11720187
0.654
187860431
573



rs9898
—
187873329
574



rs1042464
0.547
187878274
575










EXAMPLE 21
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 4862109 of chromosome 4 was different from those without colorectal cancer (Table 21). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.000489 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.464 (Table 21). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 4862109 of chromosome 4 is associated with an increased risk of developing colorectal cancer.










TABLE 21









rs no.
10516168



Chromosome; Position
4; 4862109



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.83766


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
837
157
6
Trend
0.000489
1.464


1
A
776
215
10









Table 21A indicates SNPs found to be in strong linkage disequilibrium with rs10516168. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 21A







Linked SNPs














Position




SNP
r2
on chr4
SEQ ID NO
















rs6814552
0.667
4846426
576



rs2089781
1.0
4857130
577



rs13149006
0.848
4857759
578



rs10516168
—
4862109
579



rs767564
0.79
4867970
580










EXAMPLE 22
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 73418955 of chromosome 4 was different from those without colorectal cancer (Table 22). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.003466 based on permutation analysis, and the corresponding recessive odds ratio is 1.478 (Table 22). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 73418955 of chromosome 4 is associated with an increased risk of developing colorectal cancer.










TABLE 22









rs no.
10518098



Chromosome; Position
4; 73418955



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.20305


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
404
459
108
Recessive
0.003466
1.478


1
G
401
437
155









Table 22A indicates SNPs found to be in strong linkage disequilibrium with rs10518098. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 22A







Linked SNPs














Position




SNP
r2
on chr4
SEQ ID NO
















rs11726886
0.533
73187634
581



rs10518093
0.621
73200067
582



rs4129733
0.749
73328055
583



rs4337703
0.749
73346262
584



rs11733404
0.73
73346848
585



rs11737827
0.749
73348223
586



rs12651098
0.738
73357454
587



rs11734943
0.675
73363372
588



rs9790741
0.676
73365920
589



rs11940196
0.925
73368604
590



rs10755169
0.963
73376981
591



rs11729989
0.884
73386336
592



rs4333153
0.963
73387894
593



rs17775363
0.888
73401936
594



rs17718934
0.889
73402263
595



rs885521
0.889
73403367
596



rs2137735
0.889
73409745
597



rs7675397
1.0
73418036
598



rs10518098
—
73418955
599



rs1554016
1.0
73419931
600



rs10938007
0.91
73420592
601



rs4444797
1.0
73420874
602



rs4502651
1.0
73420904
603



rs4301078
1.0
73420954
604



rs7700096
1.0
73421198
605



rs7654146
1.0
73421361
606



rs2056022
1.0
73421626
607



rs2056023
1.0
73421636
608



rs2365795
1.0
73424191
609



rs6840004
0.926
73426574
610



rs1121770
1.0
73428206
611



rs11940139
1.0
73428609
612



rs868028
1.0
73429022
613



rs868026
1.0
73429166
614



rs7673208
1.0
73429961
615



rs4694467
1.0
73430864
616



rs4694468
0.924
73432371
617



rs1398982
1.0
73432662
618



rs10938009
0.926
73433172
619



rs996154
1.0
73435810
620



rs996153
1.0
73435851
621



rs2365797
1.0
73437550
622



rs1018283
1.0
73437882
623



rs10805048
0.926
73438096
624



rs957047
1.0
73440758
625



rs957046
1.0
73441001
626



rs957045
1.0
73441029
627



rs10008822
1.0
73442206
628



rs4547769
1.0
73445194
629



rs7674709
0.835
73446950
630



rs10938010
0.888
73448534
631



rs4694469
0.926
73451047
632



rs7662481
1.0
73453617
633



rs884511
0.89
73454336
634



rs9685357
1.0
73455010
635



rs10029245
0.924
73456969
636



rs10938012
0.925
73461427
637



rs4694120
0.926
73468266
638



rs10518099
0.926
73468802
639



rs10518100
0.89
73469693
640



rs9985540
0.889
73472897
641



rs985302
0.921
73473510
642



rs2117380
0.855
73474331
643



rs1865383
0.816
73475459
644



rs984406
0.842
73476824
645



rs2175830
0.603
73481968
646



rs1554017
0.603
73482388
647



rs10006866
0.603
73484550
648



rs1513894
0.661
73489468
649



rs11729217
0.593
73491229
650



rs6857543
0.662
73491598
651



rs1398980
0.574
73492707
652



rs7681169
0.574
73493192
653



rs10433664
0.574
73493907
654



rs10050160
0.574
73496343
655



rs6446823
0.662
73496916
656



rs7679388
0.574
73501955
657










EXAMPLE 23
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 156010845 of chromosome 4 was different from those without colorectal cancer (Table 23). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.011861, and the corresponding dominant odds ratio is 1.359 (Table 23). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 156010845 of chromosome 4 is associated with an increased risk of developing colorectal cancer.










TABLE 23









rs no.
10517602



Chromosome; Position
4; 156010845



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.04835


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
T
825
134
11
Dominant
0.011861
1.359


1
T
804
180
12









Table 23A indicates SNPs found to be in strong linkage disequilibrium with rs10517602. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 23A







Linked SNPs












SNP
r2
Position on chr4
SEQ ID NO







rs17031951
1.0
156007562
658



rs17031954
1.0
156008015
659



rs17031957
1.0
156009501
660



rs10517602
—
156010845
661



rs12501328
1.0
156019936
662



rs1876031
1.0
156020341
663



rs3775785
1.0
156027459
664



rs12507608
1.0
156029231
665



rs17032000
1.0
156030563
666



rs1392546
1.0
156032538
667



rs1500372
1.0
156033905
668










EXAMPLE 24
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 114720973 of chromosome 5 was different from those without colorectal cancer (Table 24). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.000444 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.252 (Table 24). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 114720973 of chromosome 5 is associated with an increased risk of developing colorectal cancer.










TABLE 24









rs no.
2963765



Chromosome; Position
5; 114720973



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.65318


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
254
478
239
Trend
0.000444
1.252


1
A
207
484
305









Table 24A indicates SNPs found to be in strong linkage disequilibrium with rs2963765. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 24A







Linked SNPs














Position




SNP
r2
on chr5
SEQ ID NO
















rs269511
0.677
114716570
669



rs12654556
0.74
114718052
670



rs10519405
0.525
114719100
671



rs10519406
0.525
114719186
672



rs2963765
—
114720973
673



rs2964560
1.0
114721020
674



rs269503
0.525
114724952
675



rs10463669
0.544
114727927
676



rs12657417
0.525
114728598
677



rs2925172
0.935
114729688
678



rs17383755
0.559
114730035
679



rs11241322
0.9
114730402
680



rs11241323
0.501
114731087
681



rs2963749
0.934
114734391
682



rs17383865
0.932
114735264
683



rs2963747
0.934
114735588
684



rs17137667
0.902
114735981
685



rs2925170
0.934
114736503
686



rs2591258
0.501
114737036
687



rs11740600
0.902
114737354
688



rs7715232
0.505
114739954
689



rs2198712
0.935
114741070
690



rs10477531
0.841
114742706
691



rs7703997
0.615
114743558
692



rs17137708
0.9
114743576
693



rs13162208
0.933
114744950
694



rs751485
0.934
114747047
695



rs897478
0.933
114747337
696



rs2016888
0.902
114747490
697










EXAMPLE 25
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 121110284 of chromosome 5 was different from those without colorectal cancer (Table 25). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.003657 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.303 (Table 25). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 121110284 of chromosome 5 is associated with an increased risk of developing colorectal cancer.










TABLE 25









rs no.
1988515



Chromosome; Position
5; 121110284



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.71224


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
21
257
700
Trend
0.003657
1.303


1
A
11
216
754









Table 25A indicates SNPs found to be in strong linkage disequilibrium with rs1988515. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 25A







Linked SNPs












SNP
r2
Position on chr5
SEQ ID NO







rs1988515
—
121110284
698










EXAMPLE 26
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128145987 of chromosome 5 was different from those without colorectal cancer (Table 26). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.000992 based on permutation analysis, and the corresponding recessive odds ratio is 1.771 (Table 26). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 128145987 of chromosome 5 is associated with an increased risk of developing colorectal cancer.










TABLE 26









rs no.
10491268



Chromosome; Position
5; 128145987



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.24247

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
547
394
57
Recessive
0.000992
1.771


1
A
522
382
97









Table 26A indicates SNPs found to be in strong linkage disequilibrium with rs10491268. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 26A







Linked SNPs












SNP
r2
Position on chr5
SEQ ID NO
















rs247184
0.545
128103463
699



rs247195
0.545
128108152
700



rs247210
0.583
128113997
701



rs247094
0.583
128120050
702



rs10074635
0.503
128134369
703



rs10061806
1.0
128135572
704



rs7449021
1.0
128139763
705



rs17163935
0.56
128141175
706



rs10491268
—
128145987
707



rs17790915
0.512
128146786
708



rs1496344
0.576
128156553
709



rs1019137
0.545
128157693
710



rs7735162
0.961
128160641
711



rs7707454
0.926
128164258
712



rs2310808
0.545
128170372
713



rs10066082
0.816
128197696
714



rs10058629
0.778
128206257
715



rs17678073
0.778
128220969
716



rs2214369
0.816
128223084
717



rs6860974
0.778
128227979
718



rs10050439
0.778
128228401
719



rs7723679
0.767
128232311
720



rs7723683
0.777
128232320
721



rs10079808
0.778
128233576
722



rs1363170
0.769
128233727
723



rs13360809
0.778
128234493
724



rs13356389
0.778
128234617
725



rs17678190
0.778
128234806
726



rs17616306
0.778
128235438
727



rs7712212
0.778
128235745
728



rs7712497
0.778
128235767
729



rs7716412
0.778
128236078
730



rs13362019
0.778
128236528
731



rs9327496
0.523
128238639
732



rs13358000
0.778
128240119
733



rs4469239
0.776
128241301
734



rs13360401
0.583
128258653
735



rs6595867
0.578
128260778
736



rs6873372
0.552
128260800
737



rs6880855
0.558
128263313
738



rs1421889
0.61
128265259
739



rs9285913
0.558
128269933
740



rs10478827
0.544
128271956
741



rs9327500
0.591
128273703
742



rs13436689
0.549
128279649
743



rs13156417
0.558
128280539
744



rs10477690
0.555
128287628
745



rs6867677
0.554
128289750
746



rs6861915
0.558
128316551
747



rs10042256
0.567
128327389
748



rs11740497
0.556
128340511
749



rs10038006
0.54
128341528
750



rs17617241
0.516
128345166
751



rs10065480
0.516
128346380
752



rs11743701
0.525
128348967
753



rs3886286
0.525
128351543
754



rs7735034
0.524
128352581
755



rs7730969
0.525
128352924
756



rs11749027
0.558
128353107
757



rs17679250
0.525
128355391
758



rs17617329
0.525
128355483
759



rs3851463
0.525
128356081
760



rs6859805
0.642
128358774
761










EXAMPLE 27
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 1032946 of chromosome 6, found within the LOC285768 gene, was different from those without colorectal cancer (Table 27). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.015463 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.199 (Table 27). These data further suggest that this marker, located within the LOC285768 gene, is associated with colorectal cancer risk and that the A allele at position 1032946 of chromosome 6 is associated with an increased risk of developing colorectal cancer.










TABLE 27









rs no.
9328033



Chromosome; Position
6; 1032946



Gene Name
LOC285768



SEQ ID NO; Position
1772; 13622



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
1

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
59
370
571
Trend
0.015463
1.199


1
A
42
340
620









Table 27A indicates SNPs found to be in strong linkage disequilibrium with rs9328033. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 27A







Linked SNPs














Position




SNP
r2
on chr6
SEQ ID NO
















rs9405439
0.795
1026731
762



rs9391899
0.837
1032864
763



rs9328033
—
1032946
764



rs7756730
0.756
1033885
765



rs7770094
0.756
1033964
766



rs10900904
0.75
1034131
767



rs10458112
0.756
1034217
768



rs6596783
0.744
1035056
769



rs6914197
0.72
1035451
770



rs9405441
0.753
1037138
771



rs6911992
0.72
1037761
772










EXAMPLE 28
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 69521107 of chromosome 6, found within the BAI3 gene, was different from those without colorectal cancer (Table 28). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.00332, and the corresponding dominant odds ratio is 1.378 (Table 28). These data further suggest that this marker, located within the BAI3 gene, is associated with colorectal cancer risk and that the T allele at position 69521107 of chromosome 6 is associated with an increased risk of developing colorectal cancer.










TABLE 28









rs no.
10484791



Chromosome; Position
6; 69521107



Gene Name
BAI3



SEQ ID NO; Position
1773; 116950



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.01334

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
245
459
295
Dominant
0.00332
1.378


1
T
191
485
325









Table 28A indicates SNPs found to be in strong linkage disequilibrium with rs10484791. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 28A







Linked SNPs












SNP
r2
Position on chr6
SEQ ID NO
















rs9354792
0.628
69363616
773



rs2585614
0.595
69379328
774



rs2246104
0.656
69411039
775



rs2585627
0.656
69414352
776



rs2585626
0.656
69414862
777



rs2802694
0.807
69416925
778



rs2253759
0.868
69428738
779



rs2253866
0.746
69429357
780



rs2802689
0.865
69429728
781



rs2585622
0.709
69435338
782



rs2585621
0.716
69435377
783



rs2254654
0.837
69435704
784



rs3121775
0.69
69436412
785



rs6931872
0.743
69437088
786



rs2585592
0.656
69437132
787



rs7754835
0.69
69437929
788



rs2746125
0.746
69439747
789



rs2746127
0.746
69440936
790



rs2585597
0.715
69445347
791



rs2746141
0.837
69447873
792



rs2585598
0.69
69449271
793



rs2802684
0.742
69454318
794



rs2802683
0.868
69455343
795



rs2585599
0.733
69461590
796



rs2802680
0.776
69462851
797



rs2585600
0.718
69463179
798



rs2585604
0.776
69469800
799



rs2746132
0.718
69471343
800



rs715294
0.744
69483117
801



rs2802676
0.901
69483590
802



rs12206222
0.717
69486083
803



rs12210045
0.776
69490498
804



rs10945138
0.901
69496298
805



rs7768591
0.901
69497479
806



rs11752837
0.776
69504298
807



rs11752398
0.718
69504487
808



rs10945139
0.775
69511710
809



rs12154008
0.776
69513299
810



rs7745837
0.813
69517615
811



rs12201488
0.813
69518419
812



rs10484791
—
69521107
813










EXAMPLE 29
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 83088471 of chromosome 6 was different from those without colorectal cancer (Table 29). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.001403, and the corresponding dominant odds ratio is 1.335 (Table 29). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 83088471 of chromosome 6 is associated with an increased risk of developing colorectal cancer.










TABLE 29









rs no.
508106



Chromosome; Position
6; 83088471



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.64887

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
496
409
90
Dominant
0.001403
1.335


1
T
425
460
111









Table 29A indicates SNPs found to be in strong linkage disequilibrium with rs508106. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 29A







Linked SNPs












SNP
r2
Position on chr6
SEQ ID NO
















rs2323642
0.644
82950808
814



rs540814
0.544
83037702
815



rs2753211
0.692
83052756
816



rs2753212
0.69
83052893
817



rs9344267
0.792
83059529
818



rs62953
0.763
83059811
819



rs529833
0.748
83063355
820



rs544734
0.958
83065585
821



rs554594
0.958
83065715
822



rs511002
1.0
83066965
823



rs507500
0.919
83067321
824



rs532219
1.0
83079412
825



rs577767
0.958
83086171
826



rs526833
0.957
83086772
827



rs7756828
1.0
83087733
828



rs508106
—
83088471
829



rs555844
0.919
83089659
830



rs1923137
1.0
83092525
831



rs1923138
0.957
83092537
832



rs723142
1.0
83094274
833



rs2180742
1.0
83094499
834



rs1547614
0.958
83094576
835



rs2145368
1.0
83095347
836



rs2180743
1.0
83095565
837



rs7762072
0.955
83095939
838



rs13191698
0.919
83096974
839



rs13207433
0.958
83097004
840



rs1321622
0.876
83097222
841



rs9353066
0.919
83098262
842



rs6907015
0.958
83098329
843



rs6930014
0.958
83098352
844



rs9353067
0.876
83100260
845



rs9353068
1.0
83101000
846



rs2024996
0.876
83103870
847



rs12527551
0.877
83104741
848



rs9344270
0.919
83105428
849



rs796398
0.958
83113039
850



rs770904
0.913
83114887
851



rs770897
0.782
83120523
852



rs770898
0.75
83122607
853



rs770894
0.773
83126442
854



rs770895
0.773
83127291
855



rs1570140
0.754
83129590
856



rs770911
0.754
83131084
857



rs1275806
0.658
83137358
858



rs770906
0.517
83140060
859



rs932614
0.517
83146661
860



rs9344274
0.508
83147795
861



rs1951006
0.52
83150543
862



rs9449462
0.507
83153296
863



rs9361914
0.505
83155501
864



rs714133
0.52
83162032
865



rs1998204
0.508
83163350
866



rs1853143
0.508
83165082
867



rs4706945
0.52
83165771
868



rs9449469
0.52
83167427
869



rs9449470
0.544
83167802
870



rs4706948
0.505
83168404
871



rs2875128
0.532
83169297
872



rs6912008
0.508
83169493
873



rs9449475
0.556
83170215
874



rs967730
0.553
83170490
875



rs967731
0.544
83170598
876



rs9361923
0.508
83172329
877










EXAMPLE 30
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 83094274 of chromosome 6 was different from those without colorectal cancer (Table 30). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.001298, and the corresponding dominant odds ratio is 1.337 (Table 30). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 83094274 of chromosome 6 is associated with an increased risk of developing colorectal cancer.










TABLE 30









rs no.
723142



Chromosome; Position
6; 83094274



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.49209

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
501
404
91
Dominant
0.001298
1.337


1
T
430
458
110









Table 30A indicates SNPs found to be in strong linkage disequilibrium with rs723142. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 30A







Linked SNPs












SNP
r2
Position on chr6
SEQ ID NO
















rs2323642
0.621
82950808
814



rs540814
0.553
83037702
815



rs2753211
0.698
83052756
816



rs2753212
0.696
83052893
817



rs9344267
0.797
83059529
818



rs62953
0.768
83059811
819



rs529833
0.754
83063355
820



rs544734
0.959
83065585
821



rs554594
0.959
83065715
822



rs511002
1.0
83066965
823



rs507500
0.921
83067321
824



rs532219
1.0
83079412
825



rs577767
0.959
83086171
826



rs526833
0.958
83086772
827



rs7756828
1.0
83087733
828



rs508106
1.0
83088471
829



rs555844
0.921
83089659
830



rs1923137
1.0
83092525
831



rs1923138
0.958
83092537
832



rs723142
—
83094274
833



rs2180742
1.0
83094499
834



rs1547614
0.959
83094576
835



rs2145368
1.0
83095347
836



rs2180743
1.0
83095565
837



rs7762072
0.956
83095939
838



rs13191698
0.921
83096974
839



rs13207433
0.959
83097004
840



rs1321622
0.879
83097222
841



rs9353066
0.921
83098262
842



rs6907015
0.959
83098329
843



rs6930014
0.959
83098352
844



rs9353067
0.879
83100260
845



rs9353068
1.0
83101000
846



rs2024996
0.879
83103870
847



rs12527551
0.88
83104741
848



rs9344270
0.921
83105428
849



rs796398
0.959
83113039
850



rs770904
0.916
83114887
851



rs770897
0.786
83120523
852



rs770898
0.755
83122607
853



rs770894
0.778
83126442
854



rs770895
0.778
83127291
855



rs1570140
0.759
83129590
856



rs770911
0.759
83131084
857



rs1275806
0.664
83137358
858



rs770906
0.525
83140060
859



rs932614
0.525
83146661
860



rs9344274
0.517
83147795
861



rs1951006
0.528
83150543
862



rs9449462
0.515
83153296
863



rs9361914
0.514
83155501
864



rs714133
0.528
83162032
865



rs1998204
0.517
83163350
866



rs1853143
0.517
83165082
867



rs4706945
0.528
83165771
868



rs9449469
0.528
83167427
869



rs9449470
0.552
83167802
870



rs4706948
0.514
83168404
871



rs2875128
0.541
83169297
872



rs6912008
0.517
83169493
873



rs9449475
0.565
83170215
874



rs967730
0.562
83170490
875



rs967731
0.552
83170598
876



rs9361923
0.517
83172329
877










EXAMPLE 31
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 129960703 of chromosome 6, found within the ARHGAP18 gene, was different from those without colorectal cancer (Table 31). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.000525 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.358 (Table 31). These data further suggest that this marker, located within the ARHGAP18 gene, is associated with colorectal cancer risk and that the C allele at position 129960703 of chromosome 6 is associated with an increased risk of developing colorectal cancer.










TABLE 31









rs no.
10499162



Chromosome; Position
6; 129960703



Gene Name
ARHGAP18



SEQ ID NO; Position
1774; 112361



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.16957

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
746
215
9
Trend
0.000525
1.358


1
C
704
266
24









Table 31A indicates SNPs found to be in strong linkage disequilibrium with rs10499162. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 31A







Linked SNPs












SNP
r2
Position on chr6
SEQ ID NO







rs9385502
0.928
129960436
878



rs10499162
—
129960703
879



rs9402145
1.0 
129962477
880



rs9375636
0.635
129970245
881










EXAMPLE 32
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 11585877 of chromosome 7, found within the KIAA0960 gene, was different from those without colorectal cancer (Table 32). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.008011 based on permutation analysis, and the corresponding recessive odds ratio is 1.596 (Table 32). These data further suggest that this marker, located within the KIAA0960 gene, is associated with colorectal cancer risk and that the G allele at position 11585877 of chromosome 7 is associated with an increased risk of developing colorectal cancer.










TABLE 32









rs no.
2355084



Chromosome; Position
7; 11585877



Gene Name
KIAA0960



SEQ ID NO; Position
1775; 339055



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.27870

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
545
393
58
Recessive
0.008011
1.596


1
G
526
386
90









Table 32A indicates SNPs found to be in strong linkage disequilibrium with rs2355084. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 32A







Linked SNPs












SNP
r2
Position on chr7
SEQ ID NO







rs2355084
—
11585877
882










EXAMPLE 33
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 81559837 of chromosome 7, found within the CACNA2D1 gene, was different from those without colorectal cancer (Table 33). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.008433, and the corresponding dominant odds ratio is 1.455 (Table 33). These data further suggest that this marker, located within the CACNA2D1 gene, is associated with colorectal cancer risk and that the C allele at position 81559837 of chromosome 7 is associated with an increased risk of developing colorectal cancer.










TABLE 33









rs no.
10280428



Chromosome; Position
7; 81559837



Gene Name
CACNA2D1



SEQ ID NO; Position
1776; 157620



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.01828

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
872
91
7
Dominant
0.008433
1.455


1
C
856
138
2









Table 33A indicates SNPs found to be in strong linkage disequilibrium with rs10280428. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 33A







Linked SNPs












SNP
r2
Position on chr7
SEQ ID NO
















rs11768310
0.88
81554149
883



rs10279911
0.915
81559478
884



rs10280428
—
81559837
885



rs11763784
1.0
81641687
886



rs11768220
0.901
81648931
887



rs11770457
0.88
81654315
888










EXAMPLE 34
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 144767960 of chromosome 7 was different from those without colorectal cancer (Table 34). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.006242, and the corresponding dominant odds ratio is 1.590 (Table 34). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 144767960 of chromosome 7 is associated with an increased risk of developing colorectal cancer.










TABLE 34









rs no.
850470



Chromosome; Position
7; 144767960



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.07590

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
95
386
517
Dominant
0.006242
1.590


1
T
62
422
515









Table 34A indicates SNPs found to be in strong linkage disequilibrium with rs850470. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 34A







Linked SNPs












SNP
r2
Position on chr7
SEQ ID NO
















rs12532655
0.538
144628286
889



rs12534416
0.538
144628318
890



rs7805406
0.546
144628632
891



rs12533991
0.538
144629754
892



rs12533483
0.538
144629965
893



rs6968614
0.574
144630098
894



rs12374872
0.574
144635813
895



rs6968911
0.582
144643683
896



rs7784182
0.574
144645286
897



rs10280300
0.574
144646697
898



rs6964491
0.7
144669590
899



rs6951319
0.695
144669600
900



rs1357620
0.701
144671926
901



rs12531013
0.748
144672558
902



rs6952652
0.701
144674138
903



rs16882782
0.701
144676045
904



rs17169751
0.698
144676393
905



rs1357624
0.701
144678594
906



rs1357623
0.701
144678612
907



rs17169752
0.701
144680315
908



rs17169763
0.885
144718311
909



rs17169765
0.913
144720727
910



rs6960519
0.513
144733732
911



rs850456
0.72
144733992
912



rs850455
0.884
144734180
913



rs850454
0.884
144734239
914



rs850452
0.885
144734742
915



rs850450
0.885
144738529
916



rs850505
0.85
144744457
917



rs850502
0.885
144745645
918



rs850500
0.956
144745774
919



rs850499
0.885
144745875
920



rs850493
0.957
144751586
921



rs850492
0.958
144752182
922



rs850491
0.961
144752705
923



rs850490
0.957
144753415
924



rs850489
0.961
144753565
925



rs850488
0.961
144754173
926



rs850487
0.957
144755233
927



rs850486
0.961
144755604
928



rs850485
0.961
144755775
929



rs850483
0.961
144756961
930



rs850482
0.961
144757255
931



rs850480
1.0
144759437
932



rs850478
0.961
144760563
933



rs850476
0.961
144761726
934



rs850474
0.96
144766026
935



rs850472
0.961
144766794
936



rs850470
—
144767960
937



rs850468
0.693
144768118
938



rs850467
1.0
144768579
939



rs850466
1.0
144768715
940



rs850462
0.857
144770877
941



rs850461
0.85
144770905
942



rs850458
0.844
144771574
943



rs850457
0.854
144771653
944



rs860333
0.854
144771867
945



rs10246840
0.854
144774486
946



rs6952320
0.847
144774883
947



rs1079789
0.852
144776678
948



rs10952623
0.857
144777538
949



rs1468582
0.857
144778707
950



rs2372057
0.851
144781332
951



rs10952624
0.857
144781771
952



rs733171
0.857
144782495
953



rs10952625
0.857
144783026
954



rs12667814
0.618
144783666
955



rs6976909
0.857
144784599
956



rs2079830
0.849
144785299
957



rs12154287
0.533
144788902
958



rs1990347
0.857
144791211
959



rs10267840
0.857
144793063
960



rs10808035
0.857
144796105
961



rs11763425
0.857
144799583
962



rs2191275
0.887
144799675
963



rs12535408
0.856
144800213
964



rs6961951
0.857
144800438
965



rs6962101
0.857
144800519
966



rs6979892
0.805
144800830
967



rs12703731
0.58
144801300
968



rs6951436
0.857
144802085
969



rs11761238
0.821
144802576
970



rs10228710
0.857
144803188
971



rs7810370
0.857
144803650
972



rs6464691
0.857
144804012
973



rs6962254
0.857
144804167
974



rs2888244
0.854
144805193
975



rs4285408
0.857
144805467
976



rs11764219
0.857
144806025
977



rs6944748
0.857
144806327
978



rs6969500
0.809
144806354
979



rs10952627
0.857
144808010
980



rs6966867
0.857
144810732
981



rs10237200
0.849
144814121
982



rs10266218
0.846
144814527
983



rs850571
0.852
144818301
984



rs850570
0.857
144819907
985










EXAMPLE 35
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 149242026 of chromosome 7 was different from those without colorectal cancer (Table 35). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.001661 based on permutation analysis, and the corresponding recessive odds ratio is 1.418 (Table 35). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 149242026 of chromosome 7 is associated with an increased risk of developing colorectal cancer.










TABLE 35









rs no.
3864498



Chromosome; Position
7; 149242026



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.48562

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
20
215
704
Recessive
0.001661
1.418


1
G
17
168
786









Table 35A indicates SNPs found to be in strong linkage disequilibrium with rs3864498. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 35A







Linked SNPs












SNP
r2
Position on chr7
SEQ ID NO







rs4015699
0.699
149201414
986



rs4725865
0.779
149210939
987



rs13227764
0.687
149213761
988



rs4367449
0.543
149214960
989



rs6947979
0.844
149219765
990



rs3864498
—
149242026
991



rs4406321
0.907
149242664
992



rs17173853
0.92 
149243724
993










EXAMPLE 36
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 4257764 of chromosome 8, found within the CSMD1 gene, was different from those without colorectal cancer (Table 36). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.025004 based on permutation analysis, and the corresponding recessive odds ratio is 1.228 (Table 36). These data further suggest that this marker, located within the CSMD1 gene, is associated with colorectal cancer risk and that the A allele at position 4257764 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 36









rs no.
10503262



Chromosome; Position
8; 4257764



Gene Name
CSMD1



SEQ ID NO; Position
1777; 581973



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.27772

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
72
360
539
Recessive
0.025004
1.228


1
A
63
330
602









Table 36A indicates SNPs found to be in strong linkage disequilibrium with rs10503262. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 36A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO







rs10089026
0.958
4252805
994



rs10092807
1.0 
4257185
995



rs10503262
—
4257764
996










EXAMPLE 37
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 9440613 of chromosome 8 was different from those without colorectal cancer (Table 37). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.049874 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.144 (Table 37). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 9440613 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 37









rs no.
6601328



Chromosome; Position
8; 9440613



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.08727

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
26
252
931
Trend
0.049874
1.144


1
A
8
248
974









Table 37A indicates SNPs found to be in strong linkage disequilibrium with rs6601328. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 37A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO
















rs17150201
0.88
9426711
997



rs1471203
0.803
9431741
998



rs7009486
0.891
9436057
999



rs13261395
1.0
9436101
1000



rs4841169
0.891
9436786
1001



rs4840423
1.0
9437029
1002



rs4841171
1.0
9437099
1003



rs11785485
1.0
9439838
1004



rs7388554
0.88
9440072
1005



rs6601328
—
9440613
1006



rs11781665
1.0
9444872
1007



rs7013834
1.0
9452052
1008



rs13274310
1.0
9458679
1009



rs13265363
0.891
9460336
1010



rs11784858
0.785
9463104
1011



rs13270240
0.847
9468129
1012



rs11775432
1.0
9480306
1013



rs4551359
1.0
9503674
1014



rs11774818
1.0
9523873
1015



rs4841186
1.0
9526021
1016



rs4840432
1.0
9526193
1017



rs4535743
0.891
9529470
1018



rs11994018
1.0
9531111
1019



rs11991547
1.0
9538857
1020



rs7839648
0.891
9541393
1021



rs4128324
1.0
9546289
1022



rs1393
1.0
9549119
1023



rs11780274
1.0
9558649
1024



rs13250838
1.0
9563755
1025



rs13264510
1.0
9568067
1026



rs13261385
1.0
9568084
1027



rs4570159
1.0
9568712
1028



rs13259379
0.891
9640154
1029



rs4289816
0.88
9645506
1030



rs17734024
0.891
9673180
1031










EXAMPLE 38
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 55701610 of chromosome 8, found within the RP1 gene, was different from those without colorectal cancer (Table 38). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.003739 based on permutation analysis, and the corresponding recessive odds ratio is 1.279 (Table 38). These data further suggest that this marker, located within the RP1 gene, is associated with colorectal cancer risk and that the G allele at position 55701610 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 38









rs no.
444772



Chromosome; Position
8; 55701610



Gene Name
RP1



SEQ ID NO; Position
1778; 10431



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.88723

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
102
471
554
Recessive
0.003739
1.279


1
G
87
421
628









Table 38A indicates SNPs found to be in strong linkage disequilibrium with rs444772. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 38A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO
















rs421844
0.95
55688038
1032



rs435326
0.952
55688723
1033



rs396881
0.954
55688788
1034



rs446102
0.954
55689106
1035



rs702761
1.0
55691506
1036



rs145290
1.0
55692165
1037



rs428854
1.0
55698923
1038



rs429668
1.0
55699691
1039



rs444772
—
55701610
1040



rs446227
1.0
55704003
1041



rs414352
1.0
55704066
1042



rs441800
1.0
55704170
1043



rs388912
1.0
55714151
1044



rs376055
1.0
55718398
1045



rs448744
1.0
55720864
1046



rs433265
1.0
55724371
1047



rs421469
1.0
55724624
1048



rs383666
1.0
55725409
1049



rs509273
1.0
55729655
1050



rs428630
1.0
55732233
1051



rs369565
1.0
55734727
1052



rs858428
1.0
55734972
1053



rs499324
1.0
55735628
1054



rs409429
1.0
55735791
1055



rs426380
0.909
55736905
1056



rs439539
1.0
55738068
1057



rs433881
1.0
55740834
1058



rs437439
1.0
55741606
1059



rs450496
1.0
55742554
1060



rs446153
1.0
55747804
1061



rs453186
1.0
55748460
1062



rs371043
1.0
55752508
1063



rs394020
1.0
55760756
1064



rs395862
1.0
55761309
1065



rs858396
1.0
55776456
1066



rs893361
1.0
55783865
1067



rs6473950
0.955
55801936
1068



rs1437785
0.955
55811566
1069



rs2043774
0.955
55819136
1070



rs7000259
0.955
55821626
1071



rs4737673
0.955
55823685
1072



rs1509678
0.955
55825618
1073



rs2375220
0.955
55845129
1074



rs1553764
0.955
55858095
1075



rs1498181
0.955
55861650
1076



rs1498182
0.866
55870126
1077



rs1039842
0.955
55880446
1078



rs9298510
0.955
55883850
1079



rs1498189
0.802
55886453
1080










EXAMPLE 39
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 105447572 of chromosome 8 was different from those without colorectal cancer (Table 39). The dominant test for risk associated with carrying the G allele had an empirical p-value based on permutation analysis of 0.0698, and the corresponding dominant odds ratio is 1.184 (Table 39). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 105447572 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 39









rs no.
2853129



Chromosome; Position
8; 105447572



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.13044

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
917
264
27
Dominant
0.0698
1.184


1
G
894
312
24









Table 39A indicates SNPs found to be in strong linkage disequilibrium with rs2853129. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 39A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO







rs2853129
—
105447572
1081










EXAMPLE 40
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128476287 of chromosome 8 was different from those without colorectal cancer (Table 40). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.021659 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.305 (Table 40). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 128476287 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 40









rs no.
16902149



Chromosome; Position
8; 128476287



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.04399

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
959
124
0
Trend
0.021659
1.305


1
C
824
134
5









Table 40A indicates SNPs found to be in strong linkage disequilibrium with rs16902149. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 40A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO







rs16902149
—
128476287
1082



rs17467139
1.0
128481192
1089










EXAMPLE 41
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128476625 of chromosome 8 was different from those without colorectal cancer (Table 41). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.000282 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.264 (Table 41). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 128476625 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 41









rs no.
10505477



Chromosome; Position
8; 128476625



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
1


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
251
486
234
Trend
0.000282
1.264


1
A
209
478
309









Table 41A indicates SNPs found to be in strong linkage disequilibrium with rs10505477. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 41A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO







rs10505477
—
128476625
1084



rs10808556
0.627
128482329
1090



rs6983267
0.935
128482487
1091



rs3847137
0.598
128483680
1092



rs10505474
0.632
128486686
1094



rs2060776
0.609
128489299
1096



rs4871788
0.609
128490967
1097



rs7837328
0.609
128492309
1098



rs7837626
0.609
128492523
1099



rs7837644
0.609
128492580
1100



rs10956368
0.586
128492832
1101



rs10956369
0.609
128492999
1102



rs871135
0.609
128495575
1104










EXAMPLE 42
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128477298 of chromosome 8 was different from those without colorectal cancer (Table 42). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.001921, and the corresponding dominant odds ratio is 1.337 (Table 42). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 128477298 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 42









rs no.
10505476



Chromosome; Position
8; 128477298



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.19082


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
480
357
52
Dominant
0.001921
1.337


1
T
439
434
66









Table 42A indicates SNPs found to be in strong linkage disequilibrium with rs10505476. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 42A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO







rs10505476
—
128477298
1086



rs10808556
0.602
128482329
1090



rs3847137
0.557
128483680
1092



rs10505474
0.579
128486686
1094



rs2060776
0.601
128489299
1096



rs4871788
0.601
128490967
1097



rs7837328
0.601
128492309
1098



rs7837626
0.601
128492523
1099



rs7837644
0.601
128492580
1100



rs10956368
0.557
128492832
1101



rs10956369
0.601
128492999
1102



rs871135
0.601
128495575
1104










EXAMPLE 43
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128483680 of chromosome 8 was different from those without colorectal cancer (Table 43). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.004512 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.193 (Table 43). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 128483680 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 43









rs no.
3847137



Chromosome; Position
8; 128483680



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.40673


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
359
521
169
Trend
0.004512
1.193


1
C
313
518
214









Table 43A indicates SNPs found to be in strong linkage disequilibrium with rs3847137. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 43A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO







rs3847136
0.581
128476372
1083



rs10505477
0.598
128476625
1084



rs10505476
0.557
128477298
1086



rs11985829
0.524
128478414
1087



rs10808556
0.956
128482329
1090



rs6983267
0.556
128482487
1091



rs3847137
—
128483680
1092



rs7013278
0.663
128484074
1093



rs10505474
0.963
128486686
1094



rs2060776
0.928
128489299
1096



rs4871788
0.928
128490967
1097



rs7837328
0.928
128492309
1098



rs7837626
0.928
128492523
1099



rs7837644
0.928
128492580
1100



rs10956368
0.893
128492832
1101



rs10956369
0.928
128492999
1102



rs7014346
0.701
128493974
1103



rs871135
0.928
128495575
1104










EXAMPLE 44
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128486686 of chromosome 8 was different from those without colorectal cancer (Table 44). The trend test for risk associated with carrying the T allele had an empirical p-value of 0.004329 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.199 (Table 44). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 128486686 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 44









rs no.
10505474



Chromosome; Position
8; 128486686



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.64397


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
355
485
155
Trend
0.004329
1.199


1
T
308
482
198









Table 44A indicates SNPs found to be in strong linkage disequilibrium with rs10505474. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 44A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs3847136
0.608
128476372
1083



rs10505477
0.632
128476625
1084



rs10505476
0.579
128477298
1086



rs11985829
0.545
128478414
1087



rs10808556
1.0
128482329
1090



rs6983267
0.591
128482487
1091



rs3847137
0.963
128483680
1092



rs7013278
0.695
128484074
1093



rs10505474
—
128486686
1094



rs2060776
0.963
128489299
1096



rs4871788
0.963
128490967
1097



rs7837328
0.963
128492309
1098



rs7837626
0.963
128492523
1099



rs7837644
0.963
128492580
1100



rs10956368
0.927
128492832
1101



rs10956369
0.963
128492999
1102



rs7014346
0.727
128493974
1103



rs871135
0.963
128495575
1104










EXAMPLE 45
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128487118 of chromosome 8 was different from those without colorectal cancer (Table 45). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.008718, and the corresponding dominant odds ratio is 1.293 (Table 45). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 128487118 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 45









rs no.
10505473



Chromosome; Position
8; 128487118



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.20587


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
722
262
16
Dominant
0.008718
1.293


1
T
669
312
21









Table 45A indicates SNPs found to be in strong linkage disequilibrium with rs10505473. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 45A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs12334317
1.0
128477246
1085



rs10505473
—
128487118
1095



rs9297756
0.841
128509349
1106



rs7357368
1.0
128512569
1107



rs7831606
0.69
128524876
1108










EXAMPLE 46
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128492832 of chromosome 8 was different from those without colorectal cancer (Table 46). The trend test for risk associated with carrying the T allele had an empirical p-value of 0.006508 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.180 (Table 46). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 128492832 of chromosome 8 is associated with an increased risk of developing colorectal cancer.








TABLE 46







rs no.
10956368


Chromosome; Position
8; 128492832


Gene Name


SEQ ID NO; Position
;


Genotype; Phenotype
n = T; increased risk


Hardy-Weinberg
0.60762

















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
393
519
159
Trend
0.006508
1.180


1
T
347
509
203









Table 46A indicates SNPs found to be in strong linkage disequilibrium with rs10956368. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 46A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO







rs10505477
0.586
128476625
1084



rs10505476
0.557
128477298
1086



rs10808556
0.911
128482329
1090



rs6983267
0.548
128482487
1091



rs3847137
0.893
128483680
1092



rs7013278
0.586
128484074
1093



rs10505474
0.927
128486686
1094



rs2060776
0.962
128489299
1096



rs4871788
0.962
128490967
1097



rs7837328
0.962
128492309
1098



rs7837626
0.962
128492523
1099



rs7837644
0.962
128492580
1100



rs10956368
—
128492832
1101



rs10956369
0.962
128492999
1102



rs7014346
0.713
128493974
1103



rs871135
0.962
128495575
1104










EXAMPLE 47
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128492999 of chromosome 8 was different from those without colorectal cancer (Table 47). The trend test for risk associated with carrying the T allele had an empirical p-value of 0.002283 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.208 (Table 47). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 128492999 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 47









rs no.
10956369



Chromosome; Position
8; 128492999



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.56463


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
375
518
165
Trend
0.002283
1.208


1
T
322
516
211









Table 47A indicates SNPs found to be in strong linkage disequilibrium with rs10956369. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 47A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs3847136
0.553
128476372
1083



rs10505477
0.609
128476625
1084



rs10505476
0.601
128477298
1086



rs10808556
0.955
128482329
1090



rs6983267
0.569
128482487
1091



rs3847137
0.928
128483680
1092



rs7013278
0.64
128484074
1093



rs10505474
0.963
128486686
1094



rs2060776
1.0
128489299
1096



rs4871788
1.0
128490967
1097



rs7837328
1.0
128492309
1098



rs7837626
1.0
128492523
1099



rs7837644
1.0
128492580
1100



rs10956368
0.962
128492832
1101



rs10956369
—
128492999
1102



rs7014346
0.755
128493974
1103



rs871135
1.0
128495575
1104










EXAMPLE 48
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128493974 of chromosome 8 was different from those without colorectal cancer (Table 48). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.000759 based on permutation analysis, and the corresponding recessive odds ratio is 1.529 (Table 48). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 128493974 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 48









rs no.
7014346



Chromosome; Position
8; 128493974



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.09641


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
429
517
124
Recessive
0.000759
1.529


1
A
378
505
177









Table 48A indicates SNPs found to be in strong linkage disequilibrium with rs7014346. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 48A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO







rs3847136
0.714
128476372
1083



rs11985829
0.644
128478414
1087



rs10808555
0.505
128478693
1088



rs10808556
0.748
128482329
1090



rs3847137
0.701
128483680
1092



rs7013278
0.944
128484074
1093



rs10505474
0.727
128486686
1094



rs2060776
0.755
128489299
1096



rs4871788
0.755
128490967
1097



rs7837328
0.755
128492309
1098



rs7837626
0.755
128492523
1099



rs7837644
0.755
128492580
1100



rs10956368
0.713
128492832
1101



rs10956369
0.755
128492999
1102



rs7014346
—
128493974
1103



rs871135
0.755
128495575
1104



rs7842552
0.642
128500876
1105










EXAMPLE 49
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 128500876 of chromosome 8 was different from those without colorectal cancer (Table 49).
The trend test for risk associated with carrying the G allele had an empirical p-value of 0.002018 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.240 (Table 49). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 128500876 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 49









rs no.
7842552



Chromosome; Position
8; 128500876



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.87942


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
510
424
85
Trend
0.002018
1.240


1
G
430
450
107









Table 49A indicates SNPs found to be in strong linkage disequilibrium with rs7842552. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 49A







Linked SNPs












SNP
r2
Position on chr8
SEQ ID NO
















rs7013278
0.53
128484074
1093



rs7014346
0.642
128493974
1103



rs7842552
—
128500876
1105










EXAMPLE 50
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 138583352 of chromosome 8 was different from those without colorectal cancer (Table 50).
The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.000829 based on permutation analysis, and the corresponding recessive odds ratio is 2.664 (Table 50). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 138583352 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 50









rs no.
1399176



Chromosome; Position
8; 138583352



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.04904


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
686
269
15
Recessive
0.000829
2.664


1
C
666
290
40









Table 50A indicates SNPs found to be in strong linkage disequilibrium with rs1399176. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 50A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs4909649
0.835
138448609
1109



rs4909652
0.835
138448978
1110



rs7000235
0.835
138450507
1111



rs7833216
0.835
138450935
1112



rs6986763
0.835
138451287
1113



rs4265216
0.821
138452272
1114



rs4391470
0.835
138452507
1115



rs13249389
0.834
138452835
1116



rs10102751
0.835
138453471
1117



rs4532628
0.835
138454113
1118



rs4279630
0.829
138454197
1119



rs4474054
0.835
138454235
1120



rs4909654
0.835
138454833
1121



rs4292724
0.835
138455486
1122



rs12541665
0.835
138455728
1123



rs4909657
0.82
138456184
1124



rs4909367
0.652
138456296
1125



rs7820493
0.835
138456395
1126



rs7837229
0.835
138457265
1127



rs13253269
0.83
138458205
1128



rs7014387
0.835
138458287
1129



rs7826913
0.835
138458607
1130



rs6577786
0.835
138459228
1131



rs7835685
0.835
138459736
1132



rs4909658
0.833
138460258
1133



rs4909659
0.835
138460320
1134



rs4909660
0.835
138460491
1135



rs6577788
0.835
138461455
1136



rs6577789
0.835
138461471
1137



rs7845225
0.835
138461926
1138



rs7827162
0.835
138462319
1139



rs4131207
0.796
138467267
1140



rs4131208
0.835
138467277
1141



rs7016247
0.835
138467539
1142



rs7007938
0.835
138469853
1143



rs10875404
0.835
138469883
1144



rs6577790
0.835
138472916
1145



rs4909665
0.835
138473941
1146



rs6577792
0.828
138477490
1147



rs4582597
0.681
138481482
1148



rs10098545
0.819
138482393
1149



rs2943199
0.86
138490184
1150



rs2960100
0.835
138498734
1151



rs11166725
0.958
138545196
1152



rs17629911
0.958
138546484
1153



rs10505682
0.837
138551497
1154



rs17632067
1.0
138576626
1155



rs11786383
1.0
138578139
1156



rs11773949
0.628
138580074
1157



rs1399176
—
138583352
1158



rs10505684
0.628
138585809
1159



rs7816962
0.628
138585968
1160



rs6577803
0.606
138586498
1161



rs6996799
0.606
138588282
1162



rs17683816
0.959
138590203
1163



rs12677749
0.959
138590751
1164



rs6981747
0.957
138594903
1165



rs6998164
0.959
138598108
1166



rs4384013
0.958
138601596
1167



rs4625065
0.959
138601771
1168



rs11786764
0.959
138603600
1169



rs11786786
0.959
138603658
1170



rs11776612
0.959
138603708
1171



rs1913453
0.959
138604408
1172



rs17684894
0.959
138604979
1173



rs17633888
0.959
138607006
1174



rs17633935
0.959
138607169
1175



rs17685141
0.956
138607178
1176



rs12677813
0.959
138608732
1177



rs11780534
0.959
138610100
1178



rs11777429
0.958
138610110
1179



rs17634044
0.959
138610517
1180



rs11166729
0.959
138611185
1181



rs1514199
0.959
138611655
1182



rs1514200
0.954
138611699
1183



rs1514201
0.953
138611757
1184



rs11780105
0.954
138612308
1185



rs12375358
0.959
138614096
1186



rs10505685
0.958
138614490
1187



rs17685382
0.959
138614687
1188



rs17634252
0.959
138615037
1189



rs17634276
0.957
138615093
1190



rs11778762
0.959
138615852
1191



rs1514202
0.954
138616621
1192



rs1514203
0.959
138616711
1193



rs1514204
0.959
138616778
1194










EXAMPLE 51
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 138614490 of chromosome 8 was different from those without colorectal cancer (Table 51). The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.002867 based on permutation analysis, and the corresponding recessive odds ratio is 2.258 (Table 51). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 138614490 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 51









rs no.
10505685



Chromosome; Position
8; 138614490



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.12615


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
673
278
19
Recessive
0.002867
2.258


1
C
654
299
43









Table 51A indicates SNPs found to be in strong linkage disequilibrium with rs10505685. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 51A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs4909649
0.794
138448609
1109



rs4909652
0.794
138448978
1110



rs7000235
0.794
138450507
1111



rs7833216
0.794
138450935
1112



rs6986763
0.794
138451287
1113



rs4265216
0.777
138452272
1114



rs4391470
0.794
138452507
1115



rs13249389
0.793
138452835
1116



rs10102751
0.794
138453471
1117



rs4532628
0.794
138454113
1118



rs4279630
0.788
138454197
1119



rs4474054
0.794
138454235
1120



rs4909654
0.794
138454833
1121



rs4292724
0.794
138455486
1122



rs12541665
0.794
138455728
1123



rs4909657
0.776
138456184
1124



rs4909367
0.641
138456296
1125



rs7820493
0.794
138456395
1126



rs7837229
0.794
138457265
1127



rs13253269
0.789
138458205
1128



rs7014387
0.794
138458287
1129



rs7826913
0.794
138458607
1130



rs6577786
0.794
138459228
1131



rs7835685
0.794
138459736
1132



rs4909658
0.792
138460258
1133



rs4909659
0.794
138460320
1134



rs4909660
0.794
138460491
1135



rs6577788
0.794
138461455
1136



rs6577789
0.794
138461471
1137



rs7845225
0.794
138461926
1138



rs7827162
0.794
138462319
1139



rs4131207
0.755
138467267
1140



rs4131208
0.794
138467277
1141



rs7016247
0.794
138467539
1142



rs7007938
0.794
138469853
1143



rs10875404
0.794
138469883
1144



rs6577790
0.794
138472916
1145



rs4909665
0.794
138473941
1146



rs6577792
0.786
138477490
1147



rs4582597
0.643
138481482
1148



rs10098545
0.774
138482393
1149



rs2943199
0.815
138490184
1150



rs2960100
0.794
138498734
1151



rs11166725
0.916
138545196
1152



rs17629911
0.916
138546484
1153



rs10505682
0.797
138551497
1154



rs17632067
0.957
138576626
1155



rs11786383
0.958
138578139
1156



rs11773949
0.585
138580074
1157



rs1399176
0.958
138583352
1158



rs10505684
0.585
138585809
1159



rs7816962
0.585
138585968
1160



rs6577803
0.626
138586498
1161



rs6996799
0.626
138588282
1162



rs17683816
1.0
138590203
1163



rs12677749
1.0
138590751
1164



rs6981747
1.0
138594903
1165



rs6998164
1.0
138598108
1166



rs4384013
0.957
138601596
1167



rs4625065
1.0
138601771
1168



rs11786764
1.0
138603600
1169



rs11786786
1.0
138603658
1170



rs11776612
1.0
138603708
1171



rs1913453
1.0
138604408
1172



rs17684894
1.0
138604979
1173



rs17633888
1.0
138607006
1174



rs17633935
1.0
138607169
1175



rs17685141
1.0
138607178
1176



rs12677813
1.0
138608732
1177



rs11780534
1.0
138610100
1178



rs11777429
1.0
138610110
1179



rs17634044
1.0
138610517
1180



rs11166729
1.0
138611185
1181



rs1514199
1.0
138611655
1182



rs1514200
1.0
138611699
1183



rs1514201
1.0
138611757
1184



rs11780105
1.0
138612308
1185



rs12375358
1.0
138614096
1186



rs10505685
—
138614490
1187



rs17685382
1.0
138614687
1188



rs17634252
1.0
138615037
1189



rs17634276
1.0
138615093
1190



rs11778762
1.0
138615852
1191



rs1514202
1.0
138616621
1192



rs1514203
1.0
138616711
1193



rs1514204
1.0
138616778
1194










EXAMPLE 52
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 141587219 of chromosome 8 was different from those without colorectal cancer (Table 52). The dominant test for risk associated with carrying the A allele had an empirical p-value based on permutation analysis of 0.0772, and the corresponding dominant odds ratio is 1.172 (Table 52). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 141587219 of chromosome 8 is associated with an increased risk of developing colorectal cancer.










TABLE 52









rs no.
1057083



Chromosome; Position
8; 141587219



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.04921


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
892
283
34
Dominant
0.0772
1.172


1
A
867
337
24









Table 52A indicates SNPs found to be in strong linkage disequilibrium with rs1057083. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 52A







Linked SNPs














Position




SNP
r2
on chr8
SEQ ID NO
















rs12676904
0.806
141567935
1195



rs4961309
1.0
141583366
1196



rs1057083
—
141587219
1197



rs6578111
1.0
141589763
1198



rs4246131
0.752
141595220
1199



rs4961323
1.0
141595413
1200



rs10216653
1.0
141596167
1201



rs4610723
0.951
141596488
1202



rs7388327
0.521
141597272
1203










EXAMPLE 53
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 6355683 of chromosome 9 was different from those without colorectal cancer (Table 53). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.005611 based on permutation analysis, and the corresponding recessive odds ratio is 1.289 (Table 53). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 6355683 of chromosome 9 is associated with an increased risk of developing colorectal cancer.










TABLE 53









rs no.
719725



Chromosome; Position
9; 6355683



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.50139


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
138
479
378
Recessive
0.005611
1.289


1
A
121
435
439









Table 53A indicates SNPs found to be in strong linkage disequilibrium with rs719725. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 53A







Linked SNPs














Position




SNP
r2
on chr9
SEQ ID NO
















rs744567
0.509
6282602
1204



rs17756142
0.553
6291578
1205



rs1322166
0.57
6299862
1206



rs17705436
0.553
6300908
1207



rs4742179
0.518
6314376
1208



rs10758764
0.511
6316825
1209



rs10491836
0.649
6321421
1210



rs16924356
0.615
6321610
1211



rs721352
0.518
6322901
1212



rs7850988
0.649
6325760
1213



rs731585
0.546
6332328
1214



rs2169282
0.717
6340235
1215



rs16924428
0.624
6341111
1216



rs10975552
0.966
6341834
1217



rs10975553
1.0
6342819
1218



rs7022186
1.0
6349144
1219



rs7851246
0.649
6352365
1220



rs10975558
0.649
6354449
1221



rs7875812
1.0
6354533
1222



rs719724
0.84
6355614
1223



rs719725
—
6355683
1224



rs7860427
0.74
6375637
1225



rs7025295
0.965
6385247
1226



rs7850497
0.782
6385540
1227



rs10217561
0.782
6386245
1228



rs10815428
0.686
6390030
1229



rs7045097
0.816
6392856
1230



rs10758783
0.816
6397799
1231



rs10739097
0.834
6397843
1232



rs7865955
0.84
6398247
1233



rs7857628
0.966
6399874
1234










EXAMPLE 54
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 73642109 of chromosome 9 was different from those without colorectal cancer (Table 54). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.005462 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.489 (Table 54). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 73642109 of chromosome 9 is associated with an increased risk of developing colorectal cancer.










TABLE 54









rs no.
10512028



Chromosome; Position
9; 73642109



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.28078


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
6
113
852
Trend
0.005462
1.489


1
A
3
81
911









Table 54A indicates SNPs found to be in strong linkage disequilibrium with rs10512028. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 54A







Linked SNPs












SNP
r2
Position on chr9
SEQ ID NO







rs4288438
1.0
73606988
1235



rs6560355
1.0
73607164
1236



rs1585251
1.0
73607569
1237



rs4745250
1.0
73612124
1238



rs7044457
1.0
73613027
1239



rs2061399
1.0
73614943
1240



rs2061398
1.0
73615076
1241



rs2061396
1.0
73615232
1242



rs2061395
1.0
73616781
1243



rs10781152
1.0
73617303
1244



rs4745254
1.0
73618675
1245



rs2168884
1.0
73619146
1246



rs4745255
1.0
73622095
1247



rs4745256
1.0
73622395
1248



rs4745257
1.0
73622439
1249



rs4745258
1.0
73625852
1250



rs4745259
1.0
73626601
1251



rs4745260
1.0
73626706
1252



rs7389572
1.0
73627824
1253



rs10746927
1.0
73628740
1254



rs7048840
1.0
73629704
1255



rs4744695
1.0
73633747
1256



rs981197
1.0
73634385
1257



rs1458489
1.0
73635467
1258



rs1379909
1.0
73635691
1259



rs1379910
1.0
73635782
1260



rs1902976
1.0
73636447
1261



rs1902978
1.0
73636612
1262



rs7026566
1.0
73636831
1263



rs1379911
1.0
73638980
1264



rs7027893
1.0
73639771
1265



rs7039655
1.0
73639895
1266



rs4468001
1.0
73640222
1267



rs10512028
—
73642109
1268



rs999791
1.0
73642315
1269



rs17059425
1.0
73643177
1270










EXAMPLE 55
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 79353007 of chromosome 9 was different from those without colorectal cancer (Table 55). The recessive test for risk associated with carrying the T allele had an empirical p-value of 0.016576 based on permutation analysis, and the corresponding recessive odds ratio is 1.573 (Table 55). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 79353007 of chromosome 9 is associated with an increased risk of developing colorectal cancer.










TABLE 55









rs no.
946807



Chromosome; Position
9; 79353007



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.39477


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
0
76
895
Recessive
0.016576
1.573


1
T
1
50
945









Table 55A indicates SNPs found to be in strong linkage disequilibrium with rs946807. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 55A







Linked SNPs














Position




SNP
r2
on chr9
SEQ ID NO







rs946807
—
79353007
1271



rs7040700
0.59
79353924
1272



rs12005727
1.0
79356465
1273



rs12347524
1.0
79356737
1274



rs10867398
0.536
79359981
1275










EXAMPLE 56
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 110115339 of chromosome 9 was different from those without colorectal cancer (Table 56). The recessive test for risk associated with carrying the A allele had an empirical p-value of 0.009423 based on permutation analysis, and the corresponding recessive odds ratio is 1.294 (Table 56). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 110115339 of chromosome 9 is associated with an increased risk of developing colorectal cancer.










TABLE 56









rs no.
10512404



Chromosome; Position
9; 110115339



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.04658


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
44
278
649
Recessive
0.009423
1.294


1
A
37
239
720









Table 56A indicates SNPs found to be in strong linkage disequilibrium with rs10512404. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 56A







Linked SNPs












SNP
r2
Position on chr9
SEQ ID NO







rs10512404
—
110115339
1276



rs10980301
1.0
110130428
1277










EXAMPLE 57
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 4453422 of chromosome 11, found within the OR52K3P gene, was different from those without colorectal cancer (Table 57). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.002811, and the corresponding dominant odds ratio is 1.290 (Table 57). These data further suggest that this marker, located within the OR52K3P gene, is associated with colorectal cancer risk and that the T allele at position 4453422 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 57









rs no.
2278170



Chromosome; Position
11; 4453422



Gene Name
OR52K3P



SEQ ID NO; Position
1779; 808



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.05835


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
570
431
107
Dominant
0.002811
1.290


1
T
497
497
108









Table 57A indicates SNPs found to be in strong linkage disequilibrium with rs2278170. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 57A







Linked SNPs














Position




SNP
r2
on chr11
SEQ ID NO
















rs167948
0.593
4430296
1278



rs10836079
0.835
4430392
1279



rs191761
0.573
4430569
1280



rs7395324
1.0
4434860
1281



rs11032345
1.0
4440254
1282



rs10836102
1.0
4442501
1283



rs11032351
1.0
4443277
1284



rs11032354
0.928
4443753
1285



rs11032359
0.925
4444427
1286



rs11032361
0.929
4444806
1287



rs10768026
1.0
4446686
1288



rs331502
1.0
4448408
1289



rs11032378
0.929
4449042
1290



rs11032381
0.929
4449105
1291



rs890416
0.929
4449910
1292



rs890417
0.927
4450407
1293



rs890418
0.929
4450528
1294



rs331503
1.0
4451604
1295



rs9633905
1.0
4453189
1296



rs2278170
—
4453422
1297



rs2278171
1.0
4453492
1298



rs2278172
0.964
4453537
1299



rs2278173
1.0
4453673
1300



rs11032407
1.0
4454017
1301



rs9633900
1.0
4454894
1302



rs2641405
0.658
4532655
1303



rs11032827
0.577
4543829
1304










EXAMPLE 58
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 5766249 of chromosome 11, found within the OR52N1 gene, was different from those without colorectal cancer (Table 58). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.002453, and the corresponding dominant odds ratio is 1.584 (Table 58). These data further suggest that this marker, located within the OR52N1 gene, is associated with colorectal cancer risk and that the C allele at position 5766249 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 58









rs no.
10769224



Chromosome; Position
11; 5766249



Gene Name
OR52N1



SEQ ID NO; Position
1780; 374



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.07909


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
C
117
453
559
Dominant
0.002453
1.584


1
C
77
502
553









Table 58A indicates SNPs found to be in strong linkage disequilibrium with rs10769224. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 58A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs7948009
0.819
5766124
1305



rs10769224
—
5766249
1306



rs10742787
1.0
5766322
1307



rs7924824
1.0
5768065
1308



rs10838648
0.698
5772861
1309



rs10769232
1.0
5774897
1310



rs7949986
1.0
5775192
1311



rs1377512
1.0
5776193
1312



rs7940926
1.0
5778275
1313



rs10769235
1.0
5779169
1314



rs10769236
1.0
5779183
1315



rs4758099
1.0
5779725
1316



rs4758100
0.804
5779774
1317



rs4758101
1.0
5779871
1318



rs7484069
0.826
5780048
1319



rs11039085
0.524
5780227
1320



rs7937133
1.0
5781044
1321



rs1453419
1.0
5781459
1322



rs1453418
1.0
5781526
1323



rs1453417
0.688
5781557
1324



rs11039096
0.845
5781753
1325



rs10742793
0.672
5782739
1326



rs11039102
0.704
5783829
1327



rs12279684
0.524
5783893
1328



rs11607346
0.634
5784028
1329



rs6578689
0.71
5784528
1330



rs1453415
0.67
5785595
1331



rs1840175
0.67
5786072
1332



rs4372479
0.655
5792979
1333



rs10734554
0.861
5799485
1334



rs7938541
1.0
5800361
1335



rs4758444
0.524
5802527
1336



rs1979197
0.51
5802898
1337










EXAMPLE 59
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 43156746 of chromosome 11 was different from those without colorectal cancer (Table 59). The recessive test for risk associated with carrying the T allele had an empirical p-value of 0.062 based on permutation analysis, and the corresponding recessive odds ratio is 1.698 (Table 59). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 43156746 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 59









rs no.
890248



Chromosome; Position
11; 43156746



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
1


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
T
720
252
22
Recessive
0.062
1.698


1
T
699
264
37









Table 59A indicates SNPs found to be in strong linkage disequilibrium with rs890248. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 59A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs11601828
0.646
43124098
1338



rs11037302
0.704
43145953
1339



rs7940185
0.669
43149399
1340



rs6485403
0.715
43151108
1341



rs2114089
0.688
43153254
1342



rs7931762
1.0
43154329
1343



rs1559763
1.0
43154718
1344



rs1025168
1.0
43155303
1345



rs1353463
1.0
43156052
1346



rs890249
0.715
43156514
1347



rs890248
—
43156746
1348



rs890246
0.857
43156937
1349



rs7935140
0.715
43158142
1350



rs7938445
1.0
43158508
1351



rs977439
1.0
43159402
1352



rs977438
1.0
43159607
1353



rs7943295
1.0
43160243
1354



rs2068405
1.0
43160762
1355



rs7933421
0.715
43160895
1356



rs959648
1.0
43160975
1357



rs959647
0.715
43161066
1358



rs10838055
0.715
43161471
1359



rs10838056
1.0
43161777
1360



rs7129867
1.0
43161927
1361



rs7950242
1.0
43167395
1362



rs7950144
0.715
43167433
1363



rs1318986
1.0
43169005
1364



rs1025166
1.0
43169462
1365



rs1425857
1.0
43170570
1366



rs10768938
1.0
43171231
1367










EXAMPLE 60
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 73972614 of chromosome 11 was different from those without colorectal cancer (Table 60). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.007216 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.169 (Table 60). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 73972614 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 60









rs no.
11236164



Chromosome; Position
11; 73972614



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.45469


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
305
618
286
Trend
0.007216
1.169


1
A
267
621
342









Table 60A indicates SNPs found to be in strong linkage disequilibrium with rs11236164. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 60A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs10899009
1.0
73953815
1368



rs10793092
1.0
73956355
1369



rs10793093
0.832
73968600
1370



rs11236164
—
73972614
1371



rs7940880
0.966
73995062
1376



rs10219203
0.96
74002571
1377



rs10793094
1.0
74013473
1383



rs2155935
0.966
74017225
1385



rs2298792
0.966
74017844
1386



rs11236178
0.966
74018984
1387



rs3824999
0.966
74023198
1388



rs10899024
0.705
74036330
1393



rs7932922
0.68
74037678
1396



rs1944933
0.923
74039262
1397



rs11236185
0.928
74040179
1398



rs4145954
0.669
74040814
1399



rs11236187
0.966
74042214
1400



rs11236188
0.966
74042378
1401



rs6421715
0.966
74052598
1402



rs11236203
0.966
74055648
1403



rs11825804
0.964
74056519
1404



rs6592590
0.649
74058677
1405



rs11822234
0.631
74062794
1406



rs11602237
0.604
74063339
1407



rs7104802
0.572
74064448
1408



rs17244949
0.632
74067429
1410










EXAMPLE 61
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 73982157 of chromosome 11, found within the POLD3 gene, was different from those without colorectal cancer (Table 61). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.038785 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.177 (Table 61). These data further suggest that this marker, located within the POLD3 gene, is associated with colorectal cancer risk and that the C allele at position 73982157 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 61









rs no.
7939226



Chromosome; Position
11; 73982157



Gene Name
POLD3



SEQ ID NO; Position
1781; 881



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.59483


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
C
34
322
853
Trend
0.038785
1.177


1
C
25
294
911









Table 61A indicates SNPs found to be in strong linkage disequilibrium with rs7939226. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 61A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs7944514
0.516
73978840
1372



rs7939226
—
73982157
1373



rs10899013
0.543
73987190
1374



rs6592573
0.543
73990610
1375



rs4944051
0.673
74002983
1378



rs4145953
0.66
74009527
1381



rs1433970
0.673
74016841
1384



rs3741127
1.0
74024581
1389



rs1051058
0.673
74029849
1390



rs7123887
0.636
74033737
1391



rs4944922
0.635
74034353
1392



rs7106219
0.636
74036714
1394



rs4944925
0.636
74037177
1395



rs12789086
0.747
74067075
1409



rs11236208
0.707
74067969
1411



rs12282262
0.589
74071586
1412










EXAMPLE 62
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 74002983 of chromosome 11, found within the POLD3 gene, was different from those without colorectal cancer (Table 62). The trend test for risk associated with carrying the T allele had an empirical p-value of 0.016198 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.176 (Table 62). These data further suggest that this marker, located within the POLD3 gene, is associated with colorectal cancer risk and that the T allele at position 74002983 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 62









rs no.
4944051



Chromosome; Position
11; 74002983



Gene Name
POLD3



SEQ ID NO; Position
1781; 21707



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.12046


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
T
72
406
731
Trend
0.016198
1.176


1
T
53
382
795









Table 62A indicates SNPs found to be in strong linkage disequilibrium with rs4944051. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 62A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs7939226
0.673
73982157
1373



rs4944051
—
74002983
1378



rs7943085
0.582
74007856
1379



rs10501417
0.582
74008628
1380



rs4145953
1.0
74009527
1381



rs11236173
0.582
74009910
1382



rs1433970
1.0
74016841
1384



rs3741127
0.659
74024581
1389



rs1051058
1.0
74029849
1390



rs7123887
0.945
74033737
1391



rs4944922
0.945
74034353
1392



rs7106219
0.945
74036714
1394



rs4944925
0.945
74037177
1395










EXAMPLE 63
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 83565887 of chromosome 11, found within the DLG2 gene, was different from those without colorectal cancer (Table 63). The recessive test for risk associated with carrying the T allele had an empirical p-value of 0.0749 based on permutation analysis, and the corresponding recessive odds ratio is 1.223 (Table 63). These data further suggest that this marker, located within the DLG2 gene, is associated with colorectal cancer risk and that the T allele at position 83565887 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 63









rs no.
1454027



Chromosome; Position
11; 83565887



Gene Name
DLG2



SEQ ID NO; Position
1782; 746200



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.15576


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
T
8
210
771
Recessive
0.0749
1.223


1
T
13
174
809









Table 63A indicates SNPs found to be in strong linkage disequilibrium with rs1454027. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 63A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs790367
0.536
83325571
1413



rs1599914
0.536
83326348
1414



rs790372
0.536
83331489
1415



rs1471687
0.608
83333982
1416



rs790351
0.536
83338726
1417



rs2449592
0.536
83346857
1418



rs2449594
0.536
83359180
1419



rs2514171
0.536
83378990
1420



rs2449575
0.536
83383578
1421



rs1817515
0.536
83385447
1422



rs7933909
0.535
83386501
1423



rs1483387
0.536
83387013
1424



rs1586143
0.536
83389630
1425



rs1118277
0.509
83389983
1426



rs1304480
0.536
83390829
1427



rs2170707
0.536
83400665
1428



rs1483388
0.536
83402660
1429



rs2514167
0.536
83403491
1430



rs2514166
0.536
83403720
1431



rs10751101
0.536
83404929
1432



rs2853026
0.536
83418135
1433



rs1601094
0.536
83420693
1434



rs1160818
0.536
83430317
1435



rs7114261
0.774
83504794
1436



rs7108582
0.774
83508907
1437



rs1945828
0.774
83513418
1438



rs1945824
0.749
83523059
1439



rs10501555
0.774
83525615
1440



rs1014066
0.774
83527163
1441



rs2000961
0.773
83532440
1442



rs1584854
0.536
83540697
1443



rs1598073
0.536
83542042
1444



rs1454019
0.773
83548041
1445



rs1869472
1.0
83555723
1446



rs1454027
—
83565887
1447



rs970226
1.0
83569470
1448



rs1670685
0.536
83570172
1449



rs7943267
0.891
83572107
1450



rs988322
1.0
83574800
1451



rs1377746
1.0
83576676
1452



rs7941004
0.881
83594342
1453



rs10751106
0.73
83597820
1454



rs7394840
1.0
83598063
1455



rs4944472
0.785
83599752
1456



rs10751109
0.774
83601427
1457










EXAMPLE 64
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 115738853 of chromosome 11 was different from those without colorectal cancer (Table 64). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.006275 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.202 (Table 64). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 115738853 of chromosome 11 is associated with an increased risk of developing colorectal cancer.










TABLE 64









rs no.
572619



Chromosome; Position
11; 115738853



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.94522


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
135
452
384
Trend
0.006275
1.202


1
A
110
437
449









Table 64A indicates SNPs found to be in strong linkage disequilibrium with rs572619. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 64A







Linked SNPs












SNP
r2
Position on chr11
SEQ ID NO
















rs513935
0.507
115737050
1458



rs572619
—
115738853
1459



rs574529
1.0
115739067
1460



rs526151
0.575
115741985
1461



rs571139
0.928
115742227
1462



rs488435
0.575
115742992
1463



rs491111
0.927
115743244
1464



rs567559
0.648
115744952
1465



rs541874
0.615
115745463
1466



rs11215905
0.544
115747903
1467










EXAMPLE 65
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 9814118 of chromosome 12 was different from those without colorectal cancer (Table 65). The dominant test for risk associated with carrying the A allele had an empirical p-value based on permutation analysis of 0.006667, and the corresponding dominant odds ratio is 1.277 (Table 65). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 9814118 of chromosome 12 is associated with an increased risk of developing colorectal cancer.










TABLE 65









rs no.
724667



Chromosome; Position
12; 9814118



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.09590

























Odds


Case Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
A
563
359
75
Dominant
0.006667
1.277


1
A
503
424
71









Table 65A indicates SNPs found to be in strong linkage disequilibrium with rs724667. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 65A







Linked SNPs












SNP
r2
Position on chr12
SEQ ID NO
















rs3176789
0.959
9803997
1468



rs2071647
1.0
9805272
1469



rs3136559
1.0
9807907
1470



rs3176776
0.64
9808088
1471



rs3176775
0.64
9808349
1472



rs3176773
0.597
9809369
1473



rs12422685
0.64
9811239
1474



rs724668
1.0
9814096
1475



rs724667
—
9814118
1476



rs724666
1.0
9814380
1477



rs10772132
1.0
9816179
1478



rs1029992
1.0
9817025
1479



rs1029991
1.0
9817331
1480



rs1029990
1.0
9817664
1481



rs10844749
1.0
9817891
1482



rs1540356
1.0
9818051
1483



rs12582052
1.0
9818837
1484



rs1861090
0.921
9820946
1485










EXAMPLE 66
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 31141128 of chromosome 12, found within the DDX11 gene, was different from those without colorectal cancer (Table 66). The trend test for risk associated with carrying the G allele had an empirical p-value of 0.025417 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.139 (Table 66). These data further suggest that this marker, located within the DDX11 gene, is associated with colorectal cancer risk and that the G allele at position 31141128 of chromosome 12 is associated with an increased risk of developing colorectal cancer.










TABLE 66









rs no.
2075322



Chromosome; Position
12; 31141128



Gene Name
DDX11



SEQ ID NO; Position
1783; 23052



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.48386


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
G
378
582
243
Trend
0.025417
1.139


1
G
336
617
277









Table 66A indicates SNPs found to be in strong linkage disequilibrium with rs2075322. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 66A







Linked SNPs












SNP
r2
Position on chr12
SEQ ID NO







rs2075322
—
31141128
1488










EXAMPLE 67
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 31157554 of chromosome 12 was different from those without colorectal cancer (Table 67). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.027702 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.146 (Table 67). These data further suggest that this marker is associated with colorectal cancer risk and that the A allele at position 31157554 of chromosome 12 is associated with an increased risk of developing colorectal cancer.










TABLE 67









rs no.
4931434



Chromosome; Position
12; 31157554



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.89691


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
538
539
132
Trend
0.027702
1.146


1
A
496
577
157









Table 67A indicates SNPs found to be in strong linkage disequilibrium with rs4931434. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 67A







Linked SNPs












SNP
r2
Position on chr12
SEQ ID NO







rs11051239
0.534
31132974
1486



rs1808348
0.515
31136113
1487



rs4931432
0.588
31144153
1489



rs11219
0.588
31148962
1490



rs1974752
0.588
31149995
1491



rs2111770
0.581
31152638
1492



rs2005900
0.588
31152965
1493



rs1053552
0.588
31156037
1494



rs4931434
—
31157554
1495



rs4244856
0.581
31157580
1496










EXAMPLE 68
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 21875373 of chromosome 13 was different from those without colorectal cancer (Table 68). The dominant test for risk associated with carrying the G allele had an empirical p-value based on permutation analysis of 0.01544, and the corresponding dominant odds ratio is 1.618 (Table 68). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 21875373 of chromosome 13 is associated with an increased risk of developing colorectal cancer.










TABLE 68









rs no.
10507308



Chromosome; Position
13; 21875373



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.41148


















Case Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
G
954
44
1
Dominant
0.01544
1.618


1
G
930
70
1









Table 68A indicates SNPs found to be in strong linkage disequilibrium with rs10507308. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 68A







Linked SNPs












SNP
r2
Position on chr13
SEQ ID NO
















rs9506845
0.66
21846344
1497



rs2038713
1.0
21860220
1498



rs692783
0.59
21868669
1499



rs573671
0.589
21868693
1500



rs1886088
0.59
21870958
1501



rs9316962
0.59
21873258
1502



rs10507308
—
21875373
1503










EXAMPLE 69
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 32659011 of chromosome 13, found within the STARD13 gene, was different from those without colorectal cancer (Table 69). The trend test for risk associated with carrying the A allele had an empirical p-value of 0.005337 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.229 (Table 69). These data further suggest that this marker, located within the STARD13 gene, is associated with colorectal cancer risk and that the A allele at position 32659011 of chromosome 13 is associated with an increased risk of developing colorectal cancer.










TABLE 69









rs no.
797206



Chromosome; Position
13; 32659011



Gene Name
STARD13



SEQ ID NO; Position
1784; 98882



Genotype; Phenotype
n = A; increased risk



Hardy-Weinberg
0.75076


















Case









Flag
Allele B
AA
AB
BB
Model
p-Value
Odds Ratio





0
A
74
396
500
Trend
0.005337
1.229


1
A
58
365
573









Table 69A indicates SNPs found to be in strong linkage disequilibrium with rs797206. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 69A







Linked SNPs












SNP
r2
Position on chr13
SEQ ID NO
















rs797227
0.68
32643593
1504



rs797222
0.68
32647970
1505



rs797211
0.636
32655052
1506



rs797208
0.951
32658737
1507



rs797206
—
32659011
1508



rs797201
0.904
32665137
1509










EXAMPLE 70
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 45440577 of chromosome 13, found within the KIAA0853 gene, was different from those without colorectal cancer (Table 70). The dominant test for risk associated with carrying the G allele had an empirical p-value based on permutation analysis of 0.023626, and the corresponding dominant odds ratio is 1.210 (Table 70). These data further suggest that this marker, located within the KIAA0853 gene, is associated with colorectal cancer risk and that the G allele at position 45440577 of chromosome 13 is associated with an increased risk of developing colorectal cancer.










TABLE 70









rs no.
4941537



Chromosome; Position
13; 45440577



Gene Name
KIAA0853



SEQ ID NO; Position
1785; 84319



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.11382


















Case






Odds


Flag
Allele B
AA
AB
BB
Model
p-Value
Ratio





0
G
473
545
190
Dominant
0.023626
1.210


1
G
427
605
198









Table 70A indicates SNPs found to be in strong linkage disequilibrium with rs4941537. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 70A







Linked SNPs












SNP
r2
Position on chr13
SEQ ID NO
















rs7325308
1.0
45412663
1510



rs2075427
1.0
45413606
1511



rs1080107
0.733
45414960
1512



rs6561274
1.0
45416097
1513



rs9534258
1.0
45418874
1514



rs4460970
1.0
45438294
1515



rs4941537
—
45440577
1516



rs9534265
1.0
45445023
1517



rs4942460
1.0
45448444
1518



rs9316177
0.962
45459812
1519



rs9534272
1.0
45464824
1520



rs4941538
1.0
45484610
1521



rs1409436
0.926
45512651
1522



rs3783200
0.744
45514463
1523



rs1087
0.636
45525440
1524



rs9534304
0.568
45538603
1525



rs9526136
0.642
45539148
1526



rs9316179
0.578
45539467
1527



rs9316180
0.578
45539686
1528



rs9562635
0.591
45540993
1530



rs7988836
0.655
45541374
1531



rs7993537
0.578
45541562
1532



rs9534307
0.578
45542131
1533



rs9526140
0.578
45542153
1534



rs9316181
0.578
45543741
1535



rs1409434
0.578
45544445
1536



rs3742264
0.601
45546095
1537



rs9567613
0.578
45547399
1538



rs11618062
0.578
45547569
1539



rs9534312
0.578
45548220
1540



rs9567615
0.607
45549081
1541



rs9567618
0.578
45549309
1542



rs1326398
0.523
45550691
1543



rs723391
0.555
45553450
1544



rs9534322
0.509
45568003
1545



rs1952187
0.524
45572910
1546










EXAMPLE 71
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 45525440 of chromosome 13, found within the KIAA0853 gene, was different from those without colorectal cancer (Table 71). The trend test for risk associated with carrying the T allele had an empirical p-value of 0.00737 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.181 (Table 71). These data further suggest that this marker, located within the KIAA0853 gene, is associated with colorectal cancer risk and that the T allele at position 45525440 of chromosome 13 is associated with an increased risk of developing colorectal cancer.










TABLE 71









rs no.
1087



Chromosome; Position
13; 45525440



Gene Name
KIAA0853



SEQ ID NO; Position
1785;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.42878


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
T
563
515
131
Trend
0.00737
1.181


1
T
507
564
158









Table 71A indicates SNPs found to be in strong linkage disequilibrium with rs1087. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 71A







Linked SNPs












SNP
r2
Position on chr13
SEQ ID NO
















rs7325308
0.636
45412663
1510



rs2075427
0.636
45413606
1511



rs6561274
0.636
45416097
1513



rs9534258
0.636
45418874
1514



rs4460970
0.666
45438294
1515



rs4941537
0.636
45440577
1516



rs9534265
0.613
45445023
1517



rs4942460
0.636
45448444
1518



rs9316177
0.607
45459812
1519



rs9534272
0.634
45464824
1520



rs4941538
0.636
45484610
1521



rs1409436
0.577
45512651
1522



rs3783200
0.744
45514463
1523



rs1087
—
45525440
1524



rs9534304
0.96
45538603
1525



rs9526136
0.957
45539148
1526



rs9316179
0.961
45539467
1527



rs9316180
0.961
45539686
1528



rs9534305
0.724
45540157
1529



rs9562635
0.958
45540993
1530



rs7988836
0.917
45541374
1531



rs7993537
0.961
45541562
1532



rs9534307
0.961
45542131
1533



rs9526140
0.961
45542153
1534



rs9316181
0.961
45543741
1535



rs1409434
0.961
45544445
1536



rs3742264
0.961
45546095
1537



rs9567613
0.961
45547399
1538



rs11618062
0.961
45547569
1539



rs9534312
0.961
45548220
1540



rs9567615
0.956
45549081
1541



rs9567618
0.961
45549309
1542



rs1326398
0.885
45550691
1543



rs723391
0.85
45553450
1544



rs1952187
0.811
45572910
1546










EXAMPLE 72
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 67187174 of chromosome 14, found within the ARG2 gene, was different from those without colorectal cancer (Table 72). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.005073 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.501 (Table 72). These data further suggest that this marker, located within the ARG2 gene, is associated with colorectal cancer risk and that the C allele at position 67187174 of chromosome 14 is associated with an increased risk of developing colorectal cancer.










TABLE 72









rs no.
10483802



Chromosome; Position
14; 67187174



Gene Name
ARG2



SEQ ID NO; Position
1786; 30766



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
1


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
901
69
1
Trend
0.005073
1.501


1
C
890
99
6









Table 72A indicates SNPs found to be in strong linkage disequilibrium with rs10483802. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 72A







Linked SNPs












SNP
r2
Position on chr14
SEQ ID NO
















rs12436474
1.0
67170429
1547



rs8010798
1.0
67184920
1548



rs10483802
—
67187174
1549



rs15493
1.0
67187885
1550



rs1804799
1.0
67188117
1551



rs17249563
0.743
67194680
1552



rs12435927
1.0
67197723
1553



rs8013234
1.0
67219687
1554



rs3759768
1.0
67233546
1555



rs12434923
1.0
67239521
1556



rs12435352
1.0
67241643
1557



rs2009590
0.744
67257453
1558



rs12431676
0.744
67258104
1559



rs910315
0.743
67258676
1560



rs718213
1.0
67266474
1561



rs17836863
1.0
67276155
1562










EXAMPLE 73
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 46146164 of chromosome 15 was different from those without colorectal cancer (Table 73). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.001698 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.230 (Table 73). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 46146164 of chromosome 15 is associated with an increased risk of developing colorectal cancer.










TABLE 73









rs no.
2469583



Chromosome; Position
15; 46146164



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.60186


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
184
486
297
Trend
0.001698
1.230


1
C
150
476
363









Table 73A indicates SNPs found to be in strong linkage disequilibrium with rs2469583. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 73A







Linked SNPs












SNP
r2
Position on chr15
SEQ ID NO
















rs17423970
0.706
46089356
1563



rs2081619
0.964
46101819
1564



rs17424213
0.965
46103228
1565



rs11070622
0.965
46108382
1566



rs1869453
0.965
46111620
1567



rs1426656
0.965
46114468
1568



rs17340116
0.965
46114858
1569



rs1453857
0.965
46116200
1570



rs1453856
0.965
46116311
1571



rs12324567
0.965
46116717
1572



rs748848
0.965
46118326
1573



rs930016
0.962
46118529
1574



rs930017
0.965
46118841
1575



rs1453855
0.965
46120302
1576



rs1025199
1.0
46126798
1577



rs11070623
1.0
46136739
1578



rs2433363
1.0
46139544
1579



rs1426655
0.964
46145643
1580



rs2469583
—
46146164
1581



rs2469581
0.964
46149357
1582










EXAMPLE 74
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 93233505 of chromosome 15 was different from those without colorectal cancer (Table 74). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.00088 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.280 (Table 74). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 93233505 of chromosome 15 is associated with an increased risk of developing colorectal cancer.










TABLE 74









rs no.
4372639



Chromosome; Position
15; 93233505



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.44578


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
66
364
570
Trend
0.00088
1.280


1
C
43
321
636









Table 74A indicates SNPs found to be in strong linkage disequilibrium with rs4372639. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 74A







Linked SNPs












SNP
r2
Position on chr15
SEQ ID NO
















rs6496053
0.795
93195638
1583



rs12439498
0.681
93202040
1584



rs4984579
1.0
93217814
1585



rs4489958
1.0
93221398
1586



rs6416529
1.0
93222123
1587



rs4247091
0.919
93226669
1588



rs6496059
1.0
93229804
1589



rs6496060
1.0
93231817
1590



rs6496061
1.0
93232312
1591



rs4372639
—
93233505
1592



rs766233
0.742
93238457
1593



rs12440481
1.0
93261273
1594



rs4306453
0.947
93263139
1595



rs4247087
1.0
93264699
1596



rs1562628
1.0
93265029
1597



rs6496067
1.0
93266435
1598



rs6496068
1.0
93266453
1599



rs11630913
1.0
93267466
1600



rs4283178
0.649
93274496
1601



rs9920787
0.649
93277598
1602



rs6416531
0.569
93279847
1603










EXAMPLE 75
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 97282996 of chromosome 15, found within the IGF1R gene, was different from those without colorectal cancer (Table 75). The recessive test for risk associated with carrying the C allele had an empirical p-value of 0.0658 based on permutation analysis, and the corresponding recessive odds ratio is 1.311 (Table 75). These data further suggest that this marker, located within the IGF1R gene, is associated with colorectal cancer risk and that the C allele at position 97282996 of chromosome 15 is associated with an increased risk of developing colorectal cancer.










TABLE 75









rs no.
3743262



Chromosome; Position
15; 97282996



Gene Name
IGF1R



SEQ ID NO; Position
1787; 272709



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
1


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
3
119
1087
Recessive
0.0658
1.311


1
C
6
 91
1133









Table 75A indicates SNPs found to be in strong linkage disequilibrium with rs3743262. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 75A







Linked SNPs












SNP
r2
Position on chr15
SEQ ID NO







rs3743262
—
97282996
1604










EXAMPLE 76
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 99773203 of chromosome 15, found within the PCSK6 gene, was different from those without colorectal cancer (Table 76). The dominant test for risk associated with carrying the T allele had an empirical p-value based on permutation analysis of 0.003898, and the corresponding dominant odds ratio is 1.673 (Table 76). These data further suggest that this marker, located within the PCSK6 gene, is associated with colorectal cancer risk and that the T allele at position 99773203 of chromosome 15 is associated with an increased risk of developing colorectal cancer.










TABLE 76









rs no.
1994967



Chromosome; Position
15; 99773203



Gene Name
PCSK6



SEQ ID NO; Position
1788; 74508



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.24094


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
T
88
383
499
Dominant
0.003898
1.673


1
T
56
391
548









Table 76A indicates SNPs found to be in strong linkage disequilibrium with rs1994967. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 76A







Linked SNPs












SNP
r2
Position on chr15
SEQ ID NO
















rs1532364
0.81
99768367
1605



rs1000914
0.81
99768456
1606



rs1108993
0.81
99768718
1607



rs880452
0.81
99769785
1608



rs7172235
1.0
99772560
1609



rs12437488
1.0
99772834
1610



rs12912500
1.0
99773041
1611



rs1994967
—
99773203
1612



rs1994968
0.554
99773242
1613



rs4965856
1.0
99775105
1614



rs4965857
1.0
99775156
1615



rs12911482
1.0
99775985
1616



rs2277585
0.515
99785607
1617










EXAMPLE 77
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 5830572 of chromosome 16 was different from those without colorectal cancer (Table 77). The trend test for risk associated with carrying the G allele had an empirical p-value of 0.000314 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.332 (Table 77). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 5830572 of chromosome 16 is associated with an increased risk of developing colorectal cancer.










TABLE 77









rs no.
7200548



Chromosome; Position
16; 5830572



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.85932


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
G
53
353
565
Trend
0.000314
1.332


1
G
34
308
654









Table 77A indicates SNPs found to be in strong linkage disequilibrium with rs7200548. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 77A







Linked SNPs












SNP
r2
Position on chr16
SEQ ID NO







rs7187057
0.523
5806139
1618



rs7189118
0.513
5806149
1619



rs1865820
0.509
5806269
1620



rs7189684
0.509
5806460
1621



rs7195375
0.509
5807386
1622



rs11648254
0.573
5807689
1623



rs6500727
0.532
5808267
1624



rs2342743
0.507
5808466
1625



rs2342745
0.509
5808524
1626



rs2342747
0.509
5808701
1627



rs2342748
0.509
5808730
1628



rs7200468
0.509
5809618
1629



rs1550137
0.509
5810450
1630



rs2343252
0.509
5812560
1631



rs9930544
0.509
5813426
1632



rs4296263
0.532
5819886
1633



rs2118014
0.812
5828787
1634



rs7200548
—
5830572
1635










EXAMPLE 78
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 23619426 of chromosome 16, found within the LOC388226 gene, was different from those without colorectal cancer (Table 78). The trend test for risk associated with carrying the G allele had an empirical p-value of 0.005014 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.212 (Table 78). These data further suggest that this marker, located within the LOC388226 gene, is associated with colorectal cancer risk and that the G allele at position 23619426 of chromosome 16 is associated with an increased risk of developing colorectal cancer.










TABLE 78









rs no.
26764



Chromosome; Position
16; 23619426



Gene Name
LOC388226



SEQ ID NO; Position
1789; 12897



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.61714


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
G
635
390
65
Trend
0.005014
1.212


1
G
573
425
87









Table 78A indicates SNPs found to be in strong linkage disequilibrium with rs26764. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 78A







Linked SNPs












SNP
r2
Position on chr16
SEQ ID NO
















rs249856
0.638
23566477
1636



rs249870
0.638
23573679
1637



rs249869
0.566
23574058
1638



rs249867
0.638
23576069
1639



rs34514
0.637
23578098
1640



rs34513
0.551
23579493
1641



rs35586
0.638
23584507
1642



rs35585
0.566
23584612
1643



rs7588
0.638
23588666
1644



rs40076
0.767
23599906
1645



rs35635
0.566
23601271
1646



rs42873
0.637
23602233
1647



rs35634
0.638
23605180
1648



rs26767
0.766
23605958
1649



rs27770
0.638
23609039
1650



rs35633
0.591
23611506
1651



rs26764
—
23619426
1652



rs26763
1.0
23619684
1653



rs26762
1.0
23619949
1654



rs11074570
0.857
23620229
1655










EXAMPLE 79
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 13110425 of chromosome 17 was different from those without colorectal cancer (Table 79). The dominant test for risk associated with carrying the G allele had an empirical p-value based on permutation analysis of 0.022381, and the corresponding dominant odds ratio is 1.481 (Table 79). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 13110425 of chromosome 17 is associated with an increased risk of developing colorectal cancer.










TABLE 79









rs no.
1963296



Chromosome; Position
17; 13110425



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.24539


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
G
89
393
518
Dominant
0.022381
1.481


1
G
62
399
541









Table 79A indicates SNPs found to be in strong linkage disequilibrium with rs1963296. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 79A







Linked SNPs












SNP
r2
Position on chr17
SEQ ID NO







rs1963296
—
13110425
1656



rs3886341
1.0
13112831
1657



rs11869275
0.956
13114370
1658



rs7212267
0.955
13117081
1659



rs2188894
0.831
13117504
1660



rs2214260
0.831
13117537
1661










EXAMPLE 80
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 30908917 of chromosome 17, found within the LOC342618 gene, was different from those without colorectal cancer (Table 80). The trend test for risk associated with carrying the C allele had an empirical p-value of 0.003563 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.251 (Table 80). These data further suggest that this marker, located within the LOC342618 gene, is associated with colorectal cancer risk and that the C allele at position 30908917 of chromosome 17 is associated with an increased risk of developing colorectal cancer.










TABLE 80









rs no.
10512472



Chromosome; Position
17; 30908917



Gene Name
LOC342618



SEQ ID NO; Position
1790; 278



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.07034


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
685
295
20
Trend
0.003563
1.251


1
C
634
328
39









Table 80A indicates SNPs found to be in strong linkage disequilibrium with rs10512472. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 80A







Linked SNPs












SNP
r2
Position on chr17
SEQ ID NO







rs10512472
—
30908917
1662



rs12940584
0.536
30912424
1663



rs11655098
0.536
30918963
1664



rs1037590
1.0
30926748
1665



rs11656872
0.536
30962717
1666



rs17669281
0.536
30967908
1667



rs17606150
0.536
30967921
1668



rs16971217
1.0
30968168
1669



rs9897552
1.0
30998594
1670



rs12943224
0.536
31001651
1671



rs11652390
0.536
31006594
1672



rs3506
0.536
31011147
1673



rs11654542
0.536
31013421
1674



rs17670584
0.536
31023017
1675



rs17670614
0.536
31023480
1676



rs9907772
1.0
31024741
1677



rs17676508
0.536
31044721
1678



rs17608253
0.536
31050583
1679










EXAMPLE 81
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 34299961 of chromosome 18 was different from those without colorectal cancer (Table 81). The recessive test for risk associated with carrying the T allele had an empirical p-value of 0.015541 based on permutation analysis, and the corresponding recessive odds ratio is 1.770 (Table 81). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 34299961 of chromosome 18 is associated with an increased risk of developing colorectal cancer.










TABLE 81









rs no.
10502694



Chromosome; Position
18; 34299961



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.18482


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
T
641
323
30
Recessive
0.015541
1.770


1
T
608
336
52









Table 81A indicates SNPs found to be in strong linkage disequilibrium with rs10502694. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 81A







Linked SNPs












SNP
r2
Position on chr18
SEQ ID NO







rs10502692
1.0
34294350
1680



rs12373278
1.0
34294807
1681



rs9954810
1.0
34297013
1682



rs10502694
—
34299961
1683










EXAMPLE 82
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 64600521 of chromosome 18 was different from those without colorectal cancer (Table 82). The trend test for risk associated with carrying the G allele had an empirical p-value of 0.004534 based on permutation analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.945 (Table 82). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 64600521 of chromosome 18 is associated with an increased risk of developing colorectal cancer.










TABLE 82









rs no.
10503122



Chromosome; Position
18; 64600521



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
1


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
G
0
53
947
Trend
0.004534
1.945


1
G
0
28
973









Table 82A indicates SNPs found to be in strong linkage disequilibrium with rs10503122. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 82A







Linked SNPs












SNP
r2
Position on chr18
SEQ ID NO







rs646985
1.0
64574312
1684



rs17079646
1.0
64575303
1685



rs631470
1.0
64575455
1686



rs1676846
1.0
64577169
1687



rs12458298
1.0
64577779
1688



rs17079657
1.0
64578874
1689



rs679650
1.0
64579596
1690



rs12604145
1.0
64580779
1691



rs17079677
1.0
64584139
1692



rs491835
1.0
64586668
1693



rs12457185
1.0
64588166
1694



rs12454555
1.0
64588368
1695



rs12455204
1.0
64589299
1696



rs12607604
1.0
64591510
1697



rs595015
1.0
64592428
1698



rs607696
1.0
64592919
1699



rs12454311
1.0
64593139
1700



rs11151464
1.0
64595151
1701



rs17079696
1.0
64595371
1702



rs677592
1.0
64596256
1703



rs11151465
1.0
64596392
1704



rs499881
1.0
64596771
1705



rs1676853
1.0
64600350
1706



rs10503122
—
64600521
1707



rs656681
1.0
64601827
1708



rs17079705
1.0
64602989
1709



rs8092610
1.0
64612870
1710



rs17079717
1.0
64618545
1711










EXAMPLE 83
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 59485642 of chromosome 19 was different from those without colorectal cancer (Table 83). The dominant test for risk associated with carrying the C allele had an empirical p-value based on permutation analysis of 0.000472, and the corresponding dominant odds ratio is 1.401 (Table 83). These data further suggest that this marker is associated with colorectal cancer risk and that the C allele at position 59485642 of chromosome 19 is associated with an increased risk of developing colorectal cancer.










TABLE 83









rs no.
798893



Chromosome; Position
19; 59485642



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = C; increased risk



Hardy-Weinberg
0.26927


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
C
628
266
36
Dominant
0.000472
1.401


1
C
567
331
51









Table 83A indicates SNPs found to be in strong linkage disequilibrium with rs798893. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 83A







Linked SNPs












SNP
r2
Position on chr19
SEQ ID NO







rs383369
0.535
59475942
1712



rs431420
0.583
59483891
1713



rs386000
0.875
59484573
1714



rs398217
0.856
59484850
1715



rs798887
0.937
59485000
1716



rs798893
—
59485642
1717



rs416867
0.883
59488442
1718



rs384116
0.891
59488531
1719



rs103294
0.945
59489660
1720



rs410852
0.619
59492183
1721










EXAMPLE 84
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 20272988 of chromosome 21 was different from those without colorectal cancer (Table 84). The recessive test for risk associated with carrying the T allele had an empirical p-value of 0.00021 based on permutation analysis, and the corresponding recessive odds ratio is 1.465 (Table 84). These data further suggest that this marker is associated with colorectal cancer risk and that the T allele at position 20272988 of chromosome 21 is associated with an increased risk of developing colorectal cancer.










TABLE 84









rs no.
377685



Chromosome; Position
21; 20272988



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = T; increased risk



Hardy-Weinberg
0.31086


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
T
264
515
220
Recessive
0.00021
1.465


1
T
256
452
293









Table 84A indicates SNPs found to be in strong linkage disequilibrium with rs377685. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 84A







Linked SNPs












SNP
r2
Position on chr21
SEQ ID NO
















rs2825896
0.564
20218657
1722



rs2825899
0.571
20222308
1723



rs2825905
0.561
20226492
1724



rs2825910
0.591
20228734
1725



rs12482291
0.591
20232506
1726



rs2825922
0.714
20243479
1727



rs13047152
0.714
20257959
1728



rs12482827
0.714
20261725
1729



rs377685
—
20272988
1730



rs7281221
0.51
20274521
1731



rs2825928
0.522
20274865
1732



rs2825930
1.0
20279236
1733



rs12482714
1.0
20282727
1734



rs2825941
0.966
20308050
1735










EXAMPLE 85
For individuals with colorectal cancer, the distribution of polymorphic alleles at position 19773582 of chromosome 22 was different from those without colorectal cancer (Table 85). The recessive test for risk associated with carrying the G allele had an empirical p-value of 0.007571 based on permutation analysis, and the corresponding recessive odds ratio is 1.541 (Table 85). These data further suggest that this marker is associated with colorectal cancer risk and that the G allele at position 19773582 of chromosome 22 is associated with an increased risk of developing colorectal cancer.










TABLE 85









rs no.
431319



Chromosome; Position
22; 19773582



Gene Name



SEQ ID NO; Position
;



Genotype; Phenotype
n = G; increased risk



Hardy-Weinberg
0.74998


















Case
Allele





Odds


Flag
B
AA
AB
BB
Model
p-Value
Ratio





0
G
526
402
 72
Recessive
0.007571
1.541


1
G
486
409
107









Table 85A indicates SNPs found to be in strong linkage disequilibrium with rs431319. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 85A







Linked SNPs












SNP
r2
Position on chr22
SEQ ID NO
















rs727497
0.598
19751933
1736



rs9613607
0.598
19752848
1737



rs6417766
0.64
19756298
1738



rs6519750
0.566
19756323
1739



rs9608684
0.573
19756976
1740



rs9613641
0.565
19764380
1741



rs444763
0.855
19767837
1742



rs415591
0.855
19769591
1743



rs399401
0.851
19769618
1744



rs933582
0.855
19769950
1745



rs11913109
0.519
19771148
1746



rs11912450
0.519
19771633
1747



rs1210599
1.0
19772588
1748



rs444204
1.0
19772956
1749



rs365421
1.0
19772978
1750



rs367594
1.0
19773492
1751



rs431319
—
19773582
1752



rs448041
1.0
19773965
1753



rs6005623
0.623
19774278
1754



rs9306459
0.632
19774574
1755



rs9608693
0.601
19774735
1756



rs6005625
0.625
19774818
1757



rs5997305
0.625
19775246
1758



rs1210606
0.885
19776791
1759



rs406160
0.963
19778477
1760

















TABLE 86





Modifying effect of the estrogen receptor beta rs1256033 polymorphism on the


colorectal risk predicting properties of rs10505477 overall (“OR”).







Samples from the Ontario Familial Colorectal Cancer Registry


Multiplicative effect of each “A” allele in rs10505477 (OR = 1.22, p = 0.00044)


Modifying effects of estrogen receptor beta rs1256033


Gene Name: estrogen receptor beta; SEQ ID NO: 1836











C/C
C/T or T/T


OR = 1.09 p = 0.42; N = 664
OR = 1.31; p = 0.00015; N = 1568










Samples from the Ontario Familial Colorectal Cancer Registry


Multiplicative effect of each “A” allele in rs10505477 by gender alone and in


combination with the estrogen receptor beta SNP rs1256033











Male
Female


OR = 1.27; p = 0.005
OR = 1.18; p = 0.044


estrogen receptor beta: rs1256033
estrogen receptor beta: rs1256033










C/C (N = 344)
C/T or T/T (N = 772)
C/C (N = 303)
C/T or T/T (N = 755)


OR = 1.16 p = 0.35
OR = 1.33 p = 0.006
OR = 0.97 p = 0.86
OR = 1.29 p = 0.012









Table 86A indicates SNPs found to be in strong linkage disequilibrium with rs1256033. To generate this list, correlation coefficients (r2) were calculated between the index SNP and all neighboring SNPs cited in the January 2007 HapMap data set release. An r2 cut off of 0.50 was selected for inclusion as evidence for strong genetic linkage, i.e., a “strong linkage disequilibrium”.







TABLE 86A







Linked SNPs












SNP
r2
Position on chr14
SEQ ID NO
















rs1152591
0.523
63750601
1791



rs1152589
0.582
63753679
1792



rs915057
0.743
63755960
1793



rs1152588
0.803
63757928
1794



rs1152582
0.773
63762383
1795



rs928554
0.735
63763948
1796



rs1152579
0.73
63764840
1797



rs1152578
0.761
63766790
1798



rs1256065
0.752
63768685
1799



rs1256061
0.646
63773346
1800



rs1256059
0.796
63780170
1801



rs1256056
0.803
63782379
1802



rs4365213
0.583
63790017
1803



rs6573549
0.584
63791402
1804



rs12435857
0.579
63793278
1805



rs1256048
0.87
63798033
1806



rs1256045
0.87
63799513
1807



rs1256044
0.87
63803780
1808



rs1256043
0.845
63804035
1809



rs10148269
0.87
63806677
1810



rs1271573
0.868
63807224
1811



rs1256040
1.0
63808147
1812



rs11158536
0.873
63809928
1813



rs1256038
0.867
63810492
1814



rs1256037
0.869
63813054
1815



rs1256036
0.87
63813085
1816



rs1269056
0.87
63813643
1817



rs960069
0.845
63814755
1818



rs960070
0.873
63814932
1819



rs1256033
—
63815152
1820



rs1256031
1.0
63815932
1821



rs1256030
1.0
63816923
1822



rs3783736
0.528
63821125
1823



rs6573553
0.844
63824114
1824



rs1271572
0.93
63831670
1825



rs3020445
0.775
63858397
1826



rs2357479
0.684
63862517
1827



rs1256112
0.595
63884064
1828



rs1256111
0.547
63886152
1829



rs1256110
0.595
63886610
1830



rs10146204
0.52
63888522
1831



rs1256108
0.547
63891973
1832



rs1256107
0.547
63893134
1833



rs1256101
0.547
63899770
1834



rs1256093
0.518
63912505
1835










Another aspect of the invention is a method of diagnosing colorectal cancer in an individual, or determining whether the individual is at altered risk for colorectal cancer, by detecting polymorphism in a subject by treating a tissue sample from the subject with an antibody to a polymorphic genetic variant of the present invention and detecting binding of said antibody. A person of skill in the art would know how to produce such an antibody (see, for instance, Harlow, E. and Lane, eds., 1988, “Antibodies: A Laboratory Manual”, Cold Spring Harbor Press, Cold Spring Harbor). Such antibodies may include, but are not limited to polyclonal antibodies, monoclonal antibodies (mAbs), humanized or chimeric antibodies, single chain antibodies, Fab fragments, F(ab′)2 fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies, and epitope-binding fragments of any of the above. The present invention also provides an animal model to study colorectal cancer and susceptibility to colorectal cancer. Such studies can be performed using transgenic animals. For example, one can produce transgenic mice, which contain a specific allelic variant of a containing any of the SNPs disclosed herein. These mice can be created, e.g., by replacing their wild-type gene with an allele containing a SNP disclosed herein, or of the corresponding human gene containing such a SNP.
In a preferred embodiment, the present invention provides a transgenic mammalian animal, said animal having cells incorporating a recombinant expression system adapted to express a gene containing a SNP disclosed herein (preferably the human gene containing a SNP disclosed herein). Generally, the recombinant expression system will be stably integrated into the genome of the transgenic animal and will thus be heritable so that the offspring of such a transgenic animal may themselves contain the transgene. Transgenic animals can be engineered by introducing the a nucleic acid molecule containing only the coding portion of the gene into the genome of animals of interest, using standard techniques for producing transgenic animals. Animals that can serve as a target for transgenic manipulation include, without limitation, mice, rats, rabbits, guinea pigs, sheep, goats, pigs, and non-human primates, e.g. baboons, chimpanzees and monkeys. Techniques known in the art to introduce a transgene into such animals include pronucleic microinjection (U.S. Pat. No. 4,873,191); retrovirus-mediated gene transfer into germ lines (e.g. Van der Putten et al. 1985, Proc. Natl. Acad. Sci. USA 82: 6148-6152); gene targeting in embryonic stem cells (Thompson et al., Cell 56 (1989), 313-321); electroporation of embryos and sperm-mediated gene transfer (for a review, see for example, U.S. Pat. No. 4,736,866). For the purpose of the present invention, transgenic animals include those that carry the recombinant molecule only in part of their cells (“mosaic animals”). The molecule can be integrated either as a single transgene, or in concatamers. Selective introduction of a nucleic acid molecule into a particular cell type is also possible by following, for example, the technique of Lasko et al., Proc. Natl. Acad. Sci. USA 89 (1992): 6232-6236. Particular cells could also be targeted for molecular incorporation with tissue-specific enhancers. The expression of the integrated molecule can be monitored by standard techniques such as in situ hybridization, Northern Blot analysis, PCR or immunocytochemistry. Transgenic animals that include a copy of such a nucleic acid molecule introduced into the germ line of the animal at an embryonic stage can be used to examine the effect of increased expression of DNA encoding the corresponding protein. In accordance with this facet of the invention, an animal is treated with the reagent and a reduced incidence of the pathological condition, compared to untreated animals bearing the transgene, would indicate a potential therapeutic intervention for the pathological condition.
The present invention has been described in detail by way of illustration and example in order to acquaint others skilled in the art with the invention, its principles and its practical application. Particular formulations and processes of the present invention are not limited to the descriptions of the specific embodiments presented, but rather the descriptions and examples should be viewed in terms of the claims that follow and their equivalents. While some of the examples and descriptions above include some conclusions about the way the invention may function, the inventors do not intend to be bound by those conclusions and functions, but put them forth only as possible explanations.
It is to be further understood that the specific embodiments of the present invention as set forth are not intended as being exhaustive or limiting of the invention, and that many alternatives, modifications and variations will be apparent to those of ordinary skill in the art in light of the foregoing examples and detailed description. Accordingly, this invention is intended to embrace all such alternatives, modifications and variations that fall within the spirit and scope of the following claims.
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## Claims

1. A method of identifying a human subject as having an increased risk of developing colorectal cancer, the method comprising detecting the presence of an allele corresponding to position 331 of SEQ ID NO:1084 from a sample obtained from the subject wherein presence of an A allele at position 331 of SEQ ID NO:1084 and/or a T allele at the corresponding position in the complementary strand of SEQ ID NO:1084 indicates that the subject has an increased risk of developing colorectal cancer.

2. The method of claim 1, wherein the sample is blood or saliva.

3. A method for identifying for a human subject as having an increased risk of developing colorectal cancer, said method comprising the steps of:
(a) providing a sample containing genetic material from the subject;
(b) amplifying the genetic material in the presence of a pair of primers wherein a first of the primers comprises at least 10 consecutive nucleotides of SEQ ID NO: 1084 or the complement of SEQ ID NO:1084 each located upstream of the base located at position 331 of each of said sequences and a second primer comprising at least 10 consecutive nucleotides selected from within the same sequence and located downstream of the base located at position 331 of each of said sequences; and
(c) determining the identity of the base in the genetic material that corresponds to position 331, wherein the presence of an A allele corresponding to position 331 of SEQ ID NO:1084 and/or a T allele at the corresponding position in the complementary strand of SEQ ID NO:1084 indicates the subject has an increased risk of developing colorectal cancer.

4. The method of claim 1, wherein detecting the presence of the allele having an A corresponding to position 331 of SEQ ID NO:1084 and/or a T allele at the corresponding position in the complementary strand of SEQ ID NO:1084 is conducted with a kit comprising a probe that hybridizes to the allele.

5. The method of claim 3, wherein the sample is blood or saliva.