# Patent

## Title
Salivary biomarkers for lung cancer detection

## Abstract

Presented herein are biomarkers related to lung cancer. The presently identified salivary biomarkers create the basis for a lung cancer detection bioassay with sensitivity and specificity. Means and methods for evaluating the data generated using multiple biomarkers in order to validate findings and further use of the multiplexed lung cancer assay in clinical, diagnostic and therapeutic uses is also included.

## Background
CROSS-REFERENCES TO RELATED APPLICATIONS
The present application claims priority to provisional application U.S. Ser. No. 61/303,205, filed Feb. 10, 2010, herein incorporated by reference in its entirety.


STATEMENT AS TO RIGHTS TO INVENTIONS MADE UNDER FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
This invention was made with Government support under Grant No. DE016275, awarded by the National Institutes of Health. The Government has certain rights in this invention.


BACKGROUND
According to the National Cancer Institute, lung cancer is the leading cause of cancer death (hypertext transfer protocol://www.cancer.gov/cancertopics/types/lung). In 2008, approximately 215,000 new lung cancer patients were diagnosed in the United States alone. Roughly 87% of these patients will have on-small cell lung cancer (NSCLC).
Smoking, particularly of cigarettes, is by far the main contributor to lung cancer. In the U.S., it is estimated that there are 45 million current and 45 million former smokers at risk for developing lung carcinoma. Lung cancer is estimated to remain a major health problem for at least the next 50 years.
Over 75% of lung cancer cases are diagnosed in late stages because there remains no practical way to screen the large numbers of people at risk. Early detection offers the promise of improved cure rates.
Attempts have been made to identify and stratify individuals at high risk for developing lung cancer and early detection. Initially spectum cytology and chest X-ray were used as screening tools. Unfortunately these procedures failed to increase the number of curable cases.
These procedures were supplanted by computerized tomography (CT) scans, which are more sensitive than chest X-ray. Unfortunately, broad application of CT screening of the at risk population has several drawbacks including high false positives (detection of benign lung nodules) and poor ability to identify central tumors. Because of the high false positive rate, approaching 50%, it is estimated that for every lung cancer death prevented by CT screening, two unnecessary invasive procedures will be conducted.
As such, a need exists for methods useful for detecting lung cancer, and in particular biomarkers that can detect early stages of the disease and are largely non-invasive.
BRIEF SUMMARY OF THE INVENTION
In accordance with some embodiments of the invention, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided. The disclosed method includes analyzing a saliva sample from the subject with an assay that specifically detects a biomarker in the saliva sample, the biomarker selected from the group of: CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:9), Zinc Alpha2-Glycoprotein (SEQ ID NO: 10), Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, and Granulicatella adiacens 16S rRNA. The relative occurrence of the biomarkers is determined and compared to a control, thereby allowing the lung cancer status of the test subject to be determined.
In some embodiments, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided, the method entailing the detection of at least two biomarkers in a saliva sample. In other embodiments, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided, the method entailing the detection of Porphyromonas catoniae 16S rRNA and Camplylobacter showae 16S rRNA. The relative occurrence of these biomarkers or these biomakers and others in these instances is determined and compared to a control, for example, thereby allowing the lung cancer status of the test subject to be determined.
In some embodiments, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided, the method entailing the detection of at least three biomarkers in a saliva sample. In other embodiments, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided, the method entailing the detection of GREB1, CCNI and FRS. In other embodiments, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided, the method entailing the detection of. The relative occurrence of these biomarkers or these biomakers and others in these instances is determined and compared to a control, for example, thereby allowing the lung cancer status of the test subject to be determined.
In other embodiments, the method of determining the likelihood of the presence or occurrence of lung cancer in a test subject includes an assay in which a nucleic acid encoding at least one biomarker is detected. The nucleic acid can be detected by, for example, mass spectroscopy, polymerase chain reaction (PCR), microarray hybridization, thermal sequencing, capillary array sequencing, or solid phase sequencing.
In other embodiments, the method of determining the likelihood of the presence or occurrence of lung cancer in a test subject includes an assay in which a polypeptide encoding at least one biomarker is detected. The polypeptide can be detected by, for example, enzyme-linked immunosorbent assay (ELISA), Western blot, flow cytometry, immunofluorescence, immunohistochemistry, or mass spectroscopy.
In accordance with other embodiments of the invention, a method for assessing the efficacy of a therapy is disclosed. This method includes analyzing a first saliva sample from the subject with an assay that specifically detects a biomarker, the biomarker selected from the group consisting of CCNI, EGFR, FGF9, GREB1 protein, LZTS, BRAF, FRS2, ANXA1, Hp2, Zinc Alpha2-Glycoprotein, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oxalis 16S rRNA, and Granulicatella adiacens 16S rRNA. This first analysis provides a first expression profile. A therapy is applied to a subject. An analysis of a second saliva sample from the subject is undertaken with an assay that specifically detects at least two biomarkers selected from the group consisting of CCNI, EGFR, FGF9, GREB1 protein, LZTS, BRAF, FRS2, ANXA1, Hp2, Zinc Alpha2-Glycoprotein, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oxalis 16S rRNA, and Granulicatella adiacens 16S rRNA thereby providing a second expression profile. The first and second expression profiles are compared in order to assess the efficacy of a therapy.
In another embodiment, a solid support is provided, wherein the solid support includes a capture binding probe selective for at least two biomarkers selected from the group of CCNI, EGFR, FGF9, GREB1 protein, LZTS, BRAF, FRS2, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, and Granulicatella adiacens 16S rRNA. In some embodiments, a first and a second solid support are provided, wherein the first solid support includes a capture binding probe selective for a biomarker selected from the group consisting of CCNI, EGFR, FGF9, GREB1 protein, LZTS, BRAF, FRS2, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, and Granulicatella adiacens 16S rRNA and wherein the second solid support includes a capture binding ligand selective for a biomarker selected from ANXA1, Hp2, Zinc Alpha2-Glycoprotein, and Calprotectin.
In some embodiments, the capture binding ligand of the kit is an antibody. In another embodiment the kit provides one or more primers for the selective amplification of a biomarker, wherein the biomarker is selected from the group of: CCNI, EGFR, FGF9, GREB1 protein, LZTS, BRAF, FRS2, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, and Granulicatella adiacens 16S rRNA. In some embodiments one or more of the primers possess a detectable label.
In accordance with some embodiments of the invention, a method of determining the likelihood of the presence or occurrence of lung cancer in a test subject is provided. The disclosed method includes analyzing a saliva sample from the subject with an assay that specifically detects at least seventeen biomarkers in the saliva sample. The biomarkers are selected from the group of: CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:9), Zinc Alpha2-Glycoprotein (SEQ ID NO: 10), Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oxalis 16S rRNA, and Granulicatella adiacens 16S rRNA. The relative occurrence of at least seventeen biomarkers is determined and compared to a control, thereby allowing the lung cancer status of the test subject to be determined.
In any of the embodiments above, wherein a method for determining the likelihood of the presence or occurrence of lung cancer in a test subject, the number of biomarkers used can be 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 or more.
These and other embodiments, features and potential advantages will become apparent with reference to the following description and drawings.



BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic representation of the protocol for saliva collection.



DETAILED DESCRIPTION OF THE INVENTION
Introduction
Early detection of lung cancer offers the promise of easier treatment (smaller surgeries, less radiation or chemotherapy) and improved survival. Conventional screening (CT, X-ray, sputum cytology) has a less-than desirable sensitivity and specificity. A sensitive assay to identify biomarkers using non-invasively collected specimens is therefore ideal for lung cancer detection.
Biomarkers, whether produced by healthy individuals or by individuals affected by specific systemic disease, can be used as tell-tale molecules for monitoring health status, disease onset, treatment responsiveness, and outcome.
Saliva is a readily accessible source of biomarkers. As a clinical diagnostic biofluid, saliva offers many advantages; sample collection is simple, non-invasive, and causes less anxiety on the part of patients. The use of saliva also offers a cost-effective approach for large-scale screens.
The present invention discloses the diagnostic/prognostic significance of seventeen salivary biomarkers, including detection of the 16S rRNA indicative of seven bacteria strains. These biomarkers include CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:9), Zinc Alpha2-Glycoprotein (SEQ ID NO:10), Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, Granulicatella adiacens 16S rRNA, and combinations thereof, in lung cancer detection. Detection of these and other biomarkers in saliva are useful for diagnosis and prognosis of lung cancer.
Methods for detecting salivary biomarkers (proteins and nucleic acids) include techniques such as ELISA, PCR, for example, RT-PCR or mass spectroscopy, alone or in combination with other markers. Any specific probe can be used for detection, such as an antibody, a receptor, a ligand, RT-PCR etc. Mass spectroscopy can also be used for protein detection. Thus, the present invention can be used alone or as a complement to traditional antigen analysis to enhance the diagnosis of lung and other cancers.
DEFINITIONS
CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:8), Zinc Alpha2-Glycoprotein (SEQ ID NO:9), Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA, Granulicatella adiacens 16S rRNA refer to nucleic acids, e.g., gene, DNA, pre-mRNA, mRNA, and polypeptides, polymorphic variants, alleles, mutants, and interspecies homologs that have an amino acid sequence that has greater than about 60% amino acid sequence identity, 65%, 70%, 75%, 80%, 85%, 90%, preferably 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% or greater amino acid sequence identity, preferably over a region of over a region of at least about 25, 50, 100, 200, 500, 1000, or more amino acids, to a polypeptide encoded by a referenced nucleic acid or an amino acid sequence described herein. The nucleic acids and proteins of the invention include both naturally occurring or recombinant molecules. The nucleic acid or protein sequence is provided, for example, in SEQ ID NOs: 1-9.
Porphyromonas catoniae, Campylobacter showae, Streptocococcus salivaris, Campylobacter rectus, Veillonella parvula, Kigella oralis, Granulicatella adiacens refer to bacterial strains. These strains and others can be detected in a sample using any number of methods, including, for example, the detection of 16S rRNA (ribonucleic acid or deoxyribonucleic acid), the detection of chromosomal DNA, mRNA or by culturing bacteria from a sample in an appropriate growth medium under appropriate growth conditions.
“Cancer” refers to human cancers and carcinomas, sarcomas, adenocarcinomas, lymphomas, leukemias, etc., including solid and lymphoid cancers, kidney, breast, lung, kidney, bladder, colon, ovarian, prostate, pancreas, stomach, brain, head and neck, skin, uterine, testicular, esophagus, and liver cancer, including hepatocarcinoma, lymphoma, including non-Hodgkin's lymphomas (e.g., Burkitt's, Small Cell, and Large Cell lymphomas) and Hodgkin's lymphoma, leukemia, and multiple myeloma.
“Therapeutic treatment” and “cancer therapies” refers to chemotherapy, hormonal therapy, radiotherapy, and immunotherapy.
The terms “overexpress,” “overexpression” or “overexpressed” interchangeably refer to a protein that is transcribed or translated at a detectably greater level, usually in a cancer cell, in comparison to a normal cell. The term includes overexpression due to transcription, post transcriptional processing, translation, post-translational processing, cellular localization (e.g, organelle, cytoplasm, nucleus, cell surface), and RNA and protein stability, as compared to a normal cell. Overexpression can be detected using conventional techniques for detecting mRNA (i.e., RT-PCR, PCR, hybridization) or proteins (i.e., ELISA, immunohistochemical techniques, mass spectroscopy). Overexpression can be 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or more in comparison to a normal cell. In certain instances, overexpression is 1-fold, 2-fold, 3-fold, 4-fold or more higher levels of transcription or translation in comparison to a normal cell.
The terms “cancer-associated antigen” or “tumor-specific marker” or “tumor marker” interchangeably refers to a molecule (typically protein or nucleic acid such as RNA) that is expressed in the cell, expressed on the surface of a cancer cell or secreted by a cancer cell in comparison to a normal cell, and which is useful for the diagnosis of cancer, for providing a prognosis, and for preferential targeting of a pharmacological agent to the cancer cell. Oftentimes, a cancer-associated antigen is overexpressed in a cancer cell in comparison to a normal cell, for instance, about 1.2-fold over expression, about 2-fold overexpression, about 3-fold overexpression or more in comparison to a normal cell. Oftentimes, a cancer-associated antigen is a cell surface molecule that is inappropriately synthesized in the cancer cell, for instance, a molecule that contains deletions, additions or mutations in comparison to the molecule expressed on a normal cell. Oftentimes, a cancer-associated antigen will be expressed exclusively on the cell surface of a cancer cell and not synthesized or expressed on the surface of a normal cell. Exemplified cell surface tumor markers include the proteins c-erbB-2 and human epidermal growth factor receptor (HER) for breast cancer, PSMA for prostate cancer, and carbohydrate mucins in numerous cancers, including breast, ovarian and colorectal.
It will be understood by the skilled artisan that markers may be used singly or in combination with other markers for any of the uses, e.g., diagnosis or prognosis of lung cancer, disclosed herein.
The terms “identical” or percent “identity,” in the context of two or more nucleic acids or polypeptide sequences, refer to two or more sequences or subsequences that are the same or have a specified percentage of amino acid residues or nucleotides that are the same (i.e., about 60% identity, preferably 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or higher identity over a specified region, when compared and aligned for maximum correspondence over a comparison window or designated region) as measured using a BLAST or BLAST 2.0 sequence comparison algorithms with default parameters described below, or by manual alignment and visual inspection (see, e.g., NCBI web site hypertext transfer protocol://www.ncbi.nlm.nih.gov/BLAST/ or the like). Such sequences are then said to be “substantially identical.” This definition also refers to, or may be applied to, the compliment of a test sequence. The definition also includes sequences that have deletions and/or additions, as well as those that have substitutions. As described below, the preferred algorithms can account for gaps and the like. Preferably, identity exists over a region that is at least about 25 amino acids or nucleotides in length, or more preferably over a region that is 50-100 amino acids or nucleotides in length.
For sequence comparison, typically one sequence acts as a reference sequence, to which test sequences are compared. When using a sequence comparison algorithm, test and reference sequences are entered into a computer, subsequence coordinates are designated, if necessary, and sequence algorithm program parameters are designated. Preferably, default program parameters can be used, or alternative parameters can be designated. The sequence comparison algorithm then calculates the percent sequence identities for the test sequences relative to the reference sequence, based on the program parameters.
A “comparison window”, as used herein, includes reference to a segment of any one of the number of contiguous positions selected from the group consisting of from 20 to 600, usually about 50 to about 200, more usually about 100 to about 150 in which a sequence may be compared to a reference sequence of the same number of contiguous positions after the two sequences are optimally aligned. Methods of alignment of sequences for comparison are well-known in the art. Optimal alignment of sequences for comparison can be conducted, e.g., by the local homology algorithm of Smith & Waterman, Adv. Appl. Math. 2:482 (1981), by the homology alignment algorithm of Needleman & Wunsch, J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson & Lipman, Proc. Nat'l. Acad. Sci. USA 85:2444 (1988), by computerized implementations of these algorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group, 575 Science Dr., Madison, Wis.), or by manual alignment and visual inspection (see, e.g., Current Protocols in Molecular Biology (Ausubel et al., eds. 1987-2005, Wiley Interscience)).
An example of algorithm that is suitable for determining percent sequence identity and sequence similarity are the BLAST and BLAST 2.0 algorithms, which are described in Altschul et al., Nuc. Acids Res. 25:3389-3402 (1977) and Altschul et al., J. Mol. Biol. 215:403-410 (1990), respectively. BLAST and BLAST 2.0 are used, with the parameters described herein, to determine percent sequence identity for the nucleic acids and proteins of the invention. Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information (hypertext transfer protocol://www.ncbi.nlm.nih.gov/). This algorithm involves first identifying high scoring sequence pairs (HSPs) by identifying short words of length W in the query sequence, which either match or satisfy some positive-valued threshold score T when aligned with a word of the same length in a database sequence. T is referred to as the neighborhood word score threshold (Altschul et al., supra). These initial neighborhood word hits act as seeds for initiating searches to find longer HSPs containing them. The word hits are extended in both directions along each sequence for as far as the cumulative alignment score can be increased. Cumulative scores are calculated using, for nucleotide sequences, the parameters M (reward score for a pair of matching residues; always >0) and N (penalty score for mismatching residues; always <0). For amino acid sequences, a scoring matrix is used to calculate the cumulative score. Extension of the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached. The BLAST algorithm parameters W, T, and X determine the sensitivity and speed of the alignment. The BLASTN program (for nucleotide sequences) uses as defaults a wordlength (W) of 11, an expectation (E) of 10, M=5, N=−4 and a comparison of both strands. For amino acid sequences, the BLASTP program uses as defaults a wordlength of 3, and expectation (E) of 10, and the BLOSUM62 scoring matrix (see Henikoff & Henikoff, Proc. Natl. Acad. Sci. USA 89:10915 (1989)) alignments (B) of 50, expectation (E) of 10, M=5, N=−4, and a comparison of both strands.
“Nucleic acid” refers to deoxyribonucleotides or ribonucleotides and polymers thereof in either single or double-stranded form, and complements thereof.
Specifically refers to ability of a ligand to bind to a target with an affinity at least 1.2, 1.5, 2, 3, 5, 8, 10, 20, 50, 100, 150, 200, 500, 1000, or more fold greater than a ligand not specific for the target.
Unless otherwise indicated, a particular nucleic acid sequence also implicitly encompasses conservatively modified variants thereof (for example, degenerate codon substitutions) and complementary sequences, as well as the sequence explicitly indicated. Specifically, degenerate codon substitutions may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and/or deoxyinosine residues (Batzer et al., Nucleic Acid Res. 19:5081 (1991); Ohtsuka et al., J. Biol. Chem. 260:2605-2608 (1985); Rossolini et al., Mol. Cell. Probes 8:91-98 (1994)). The term nucleic acid is used interchangeably with gene, cDNA, mRNA, oligonucleotide, and polynucleotide.
A particular nucleic acid sequence also implicitly encompasses “splice variants” and nucleic acid sequences encoding truncated forms of cancer antigens. Similarly, a particular protein encoded by a nucleic acid implicitly encompasses any protein encoded by a splice variant or truncated form of that nucleic acid. “Splice variants,” as the name suggests, are products of alternative splicing of a gene. After transcription, an initial nucleic acid transcript may be spliced such that different (alternate) nucleic acid splice products encode different polypeptides. Mechanisms for the production of splice variants vary, but include alternate splicing of exons. Alternate polypeptides derived from the same nucleic acid by read-through transcription are also encompassed by this definition. Any products of a splicing reaction, including recombinant forms of the splice products, are included in this definition. Nucleic acids can be truncated at the 5′ end or at the 3′ end. Polypeptides can be truncated at the N-terminal end or the C-terminal end. Truncated versions of nucleic acid or polypeptide sequences can be naturally occurring or recombinantly created.
The term “amino acid” refers to naturally occurring and synthetic amino acids, as well as amino acid analogs and amino acid mimetics that function in a manner similar to the naturally occurring amino acids. Naturally occurring amino acids are those encoded by the genetic code, as well as those amino acids that are later modified, e.g., hydroxyproline, .gamma.-carboxyglutamate, and O-phosphoserine. Amino acid analogs refers to compounds that have the same basic chemical structure as a naturally occurring amino acid, i.e., an .alpha. carbon that is bound to a hydrogen, a carboxyl group, an amino group, and an R group, e.g., homoserine, norleucine, methionine sulfoxide, methionine methyl sulfonium. Such analogs have modified R groups (e.g., norleucine) or modified peptide backbones, but retain the same basic chemical structure as a naturally occurring amino acid. Amino acid mimetics refers to chemical compounds that have a structure that is different from the general chemical structure of an amino acid, but that functions in a manner similar to a naturally occurring amino acid.
Amino acids may be referred to herein by either their commonly known three letter symbols or by the one-letter symbols recommended by the IUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise, may be referred to by their commonly accepted single-letter codes.
“Conservatively modified variants” applies to both amino acid and nucleic acid sequences. With respect to particular nucleic acid sequences, conservatively modified variants refers to those nucleic acids which encode identical or essentially identical amino acid sequences, or where the nucleic acid does not encode an amino acid sequence, to essentially identical sequences. Because of the degeneracy of the genetic code, a large number of functionally identical nucleic acids encode any given protein. For instance, the codons GCA, GCC, GCG and GCU all encode the amino acid alanine Thus, at every position where an alanine is specified by a codon, the codon can be altered to any of the corresponding codons described without altering the encoded polypeptide. Such nucleic acid variations are “silent variations,” which are one species of conservatively modified variations. Every nucleic acid sequence herein which encodes a polypeptide also describes every possible silent variation of the nucleic acid. One of skill will recognize that each codon in a nucleic acid (except AUG, which is ordinarily the only codon for methionine, and TGG, which is ordinarily the only codon for tryptophan) can be modified to yield a functionally identical molecule. Accordingly, each silent variation of a nucleic acid which encodes a polypeptide is implicit in each described sequence with respect to the expression product, but not with respect to actual probe sequences.
As to amino acid sequences, one of skill will recognize that individual substitutions, deletions or additions to a nucleic acid, peptide, polypeptide, or protein sequence which alters, adds or deletes a single amino acid or a small percentage of amino acids in the encoded sequence is a “conservatively modified variant” where the alteration results in the substitution of an amino acid with a chemically similar amino acid. Conservative substitution tables providing functionally similar amino acids are well known in the art. Such conservatively modified variants are in addition to and do not exclude polymorphic variants, interspecies homologs, and alleles of the invention.
The following eight groups each contain amino acids that are conservative substitutions for one another: 1) Alanine (A), Glycine (G); 2) Aspartic acid (D), Glutamic acid (E); 3) Asparagine (N), Glutamine (Q); 4) Arginine (R), Lysine (K); 5) Isoleucine (I), Leucine (L), Methionine (M), Valine (V); 6) Phenylalanine (F), Tyrosine (Y), Tryptophan (W); 7) Serine (S), Threonine (T); and 8) Cysteine (C), Methionine (M) (see, e.g., Creighton, Proteins (1984)).
A “label” or a “detectable moiety” is a composition detectable by spectroscopic, photochemical, biochemical, immunochemical, chemical, or other physical means. For example, useful labels include fluorescent dyes, electron-dense reagents, enzymes (for example, as commonly used in an ELISA), biotin, digoxigenin, or haptens and proteins which can be made detectable, e.g., by incorporating a radiolabel into the peptide or used to detect antibodies specifically reactive with the peptide.
The term “recombinant” when used with reference, e.g., to a cell, or nucleic acid, protein, or vector, indicates that the cell, nucleic acid, protein or vector, has been modified by the introduction of a heterologous nucleic acid or protein or the alteration of a native nucleic acid or protein, or that the cell is derived from a cell so modified. Thus, for example, recombinant cells express genes that are not found within the native (non-recombinant) form of the cell or express native genes that are otherwise abnormally expressed, under expressed or not expressed at all.
The phrase “stringent hybridization conditions” refers to conditions under which a probe will hybridize to its target subsequence, typically in a complex mixture of nucleic acids, but to no other sequences. Stringent conditions are sequence-dependent and will be different in different circumstances. Longer sequences hybridize specifically at higher temperatures. An extensive guide to the hybridization of nucleic acids is found in Tijssen, Techniques in Biochemistry and Molecular Biology—Hybridization with Nucleic Probes, “Overview of principles of hybridization and the strategy of nucleic acid assays” (1993). Generally, stringent conditions are selected to be about 5-10° C. lower than the thermal melting point (Tm) for the specific sequence at a defined ionic strength pH. The Tm is the temperature (under defined ionic strength, pH, and nucleic concentration) at which 50% of the probes complementary to the target hybridize to the target sequence at equilibrium (as the target sequences are present in excess, at Tm, 50% of the probes are occupied at equilibrium). Stringent conditions may also be achieved with the addition of destabilizing agents such as formamide. For selective or specific hybridization, a positive signal is at least two times background, preferably 10 times background hybridization. Exemplary stringent hybridization conditions can be as following: 50% formamide, 5×SSC, and 1% SDS, incubating at 42° C., or, 5×SSC, 1% SDS, incubating at 65° C., with wash in 0.2×SSC, and 0.1% SDS at 65° C.
Nucleic acids that do not hybridize to each other under stringent conditions are still substantially identical if the polypeptides which they encode are substantially identical. This occurs, for example, when a copy of a nucleic acid is created using the maximum codon degeneracy permitted by the genetic code. In such cases, the nucleic acids typically hybridize under moderately stringent hybridization conditions. Exemplary “moderately stringent hybridization conditions” include a hybridization in a buffer of 40% formamide, 1 M NaCl, 1% SDS at 37° C., and a wash in 1×SSC at 45° C. A positive hybridization is at least twice background. Those of ordinary skill will readily recognize that alternative hybridization and wash conditions can be utilized to provide conditions of similar stringency. Additional guidelines for determining hybridization parameters are provided in numerous reference, e.g., and Current Protocols in Molecular Biology, ed. Ausubel, et al., supra.
For PCR, a temperature of about 36° C. is typical for low stringency amplification, although annealing temperatures may vary between about 32° C. and 48° C. depending on primer length. For high stringency PCR amplification, a temperature of about 62° C. is typical, although high stringency annealing temperatures can range from about 50° C. to about 65° C., depending on the primer length and specificity. Typical cycle conditions for both high and low stringency amplifications include a denaturation phase of 90° C.-95° C. for 30 sec-2 min., an annealing phase lasting 30 sec.-2 min., and an extension phase of about 72° C. for 1-2 min. Protocols and guidelines for low and high stringency amplification reactions are provided, e.g., in Innis et al. (1990) PCR Protocols, A Guide to Methods and Applications, Academic Press, Inc. N.Y.).
“Antibody” means a protein comprising one or more polypeptides substantially encoded by all or part of the recognized immunoglobulin genes. The recognized immunoglobulin genes, for example in humans, include the kappa (κ), lambda (λ) and heavy chain genetic loci, which together compose the myriad variable region genes, and the constant region genes mu (μ), delta (δ), gamma (γ), epsilon (ε) and alpha (α), which encode the IgM, IgD, IgG, IgE, and IgA isotypes respectively. Antibody herein is meant to include full length antibodies and antibody fragments, and may refer to a natural antibody from any organism, an engineered antibody or an antibody generated recombinantly for experimental, therapeutic or other purposes as further defined below. Antibody fragments include Fab, Fab′, F(ab′)2, Fv, scFv or other antigen-binding subsequences of antibodies and can include those produced by the modification of whole antibodies or those synthesized de novo using recombinant DNA technologies. The term “antibody” refers to both monoclonal and polyclonal antibodies. Antibodies can be antagonists, agonists, neutralizing, inhibitory or stimulatory.
Biomarkers
Biomarkers may originate from epidemiological studies, animal studies, pathophysiological considerations and end-organ experiments. Ideally, a biomarker will have a high predictive value for a meaningful outcome measure, can be or is validated in appropriately designed prospective trials, reflects therapeutic success by corresponding changes in the surrogate marker results, and should be easy to assess in clinical practice.
Biomarkers can be used in conjunction with other diagnostic tools or used alone.
The term “surrogate marker,” “biomolecular marker,” “biomarker” or “marker” (also sometimes referred to herein as a “target analyte,” “target species” or “target sequence”) refers to a molecule whose measurement provides information as to the state of a subject. In various exemplary embodiments, the biomarker is used to assess a pathological state. Measurements of the biomarker may be used alone or combined with other data obtained regarding a subject in order to determine the state of the subject. In one embodiment, the biomarker is “differentially present” in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease). In one embodiment, the biomarker is “differentially present” in a sample taken from a subject undergoing no therapy or one type of therapy as compared with another type of therapy. Alternatively, the biomarker may be “differentially present” even if there is no phenotypic difference, e.g. the biomarkers may allow the detection of asymptomatic risk.
A biomarker may be over-expressed (over-abundant) or under-expressed (under abundant) relative to a control. The biomarker can be an allelic variant, truncated or mutated form of a wild-type nucelic acid or protein. The biomarker can be a splice variant.
A biomarker may be determined to be “differentially present” in a variety of ways, for example, between different phenotypic statuses if the mean or median level (particularly the expression level of the associated mRNAs as described below) of the biomarker in the different groups is calculated to be statistically significant. Common tests for statistical significance include, among others, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and odds ratio.
As described herein, a biomarker may be, for example, a small molecule, an analyte or target analyte, a nucleic acid, a protein, a metabolite or any derivative thereof or any and all combinations of these molecules, with proteins and nucleic acids finding particular use in the invention. As will be appreciated by those in the art, a large number of analytes may be detected using the present methods; basically, any biomarker for which a binding ligand, described below, may be made may be detected using the methods of the invention.
In various embodiments, the biomarkers used in the panels of the invention can be detected either as proteins or as nucleic acids (e.g. mRNA or cDNA transcripts) in any combination. In various embodiments, the protein form of a biomarker is measured. As will be appreciated by those in the art, protein assays may be done using standard techniques such as ELISA assays. In various embodiments, the nucleic acid form of a biomarker (e.g., the corresponding mRNA) is measured. In various exemplary embodiments, one or more biomarkers from a particular panel are measured using a protein assay and one or more biomarkers from the same panel are measured using a nucleic acid assay.
As will be appreciated by those in the art, there are a large number of possible proteinaceous target analytes and target species that may be detected using the present invention. The term “protein,” “polypeptide” or “oligopeptide” refers to at least two or more peptides or amino acids joined by one or more peptide bonds. A protein or an amino acid may be naturally or nonnaturally occurring and may be also be an analog, a derivative or a peptidomimetic structure. The term “protein” refers to wild-type sequences, variants of wild-type sequences and either of these containing analogs or derivatized amino acids. In various embodiments, variants of the sequences described herein, including proteins and nucleic acids based on e.g. splice variants, variants comprising a deletion, addition, substitution, fragments, preproprotein, processed preproprotein (e.g. without a signaling peptide), processed proprotein (e.g. resulting in an active form), nonhuman sequences and variant nonhuman sequences may be used as biomarkers.
In various embodiments, the biomarker is a nucleic acid. The term “nucleic acid” or “oligonucleotide” or grammatical equivalents herein means at least two nucleotides covalently linked together. A nucleic acid of the present invention will generally contain phosphodiester bonds, although in some cases, as outlined below, for example in the use of binding ligand probes, nucleic acid analogs are included that may have alternate backbones.
Biomarkers can also be bacterial nucleic acids or proteins. The oral cavity is a large reservoir of bacteria, with more than 700 species or phylotypes, of which over 50% have not been cultivated. In some embodiments, assessing bacterial flora composition and dynamic changes are biomarkers for lung cancer.
A recently developed 16S rRNA-based oligonucleotide microarray (Human Oral Microbe Identification Microarray) made it possible to profile the oral bacterial flora in patients with and without lung cancer. In some embodiments, the presence, absence, or level of 16S rRNA from bacteria in a sample may correlate with a disease or condition. “Bacteria” refers to small prokaryotic organisms (linear dimensions of around 1 μm) with non-compartmentalized circular DNA and ribosomes of about 70 S. “16S RNA” refers to a nucleic acid component of the 30S subunit of prokaryotic ribosomes; the gene that encodes the 16S rRNA or the 16S rRNA itself. Bacterial strains of species or phylotypes have less than about a 2% difference in 16S rRNA. Closely related species or phylotypes generally have between about a 2% and about a 4% difference in 16S rRNA, whereas a genus often has between about a 5% and about a 10% difference in 16S rRNA.
To resolve the identity of bacterial populations, probes on a microarray can be designed, for example, to take advantage of conserved features of the 16S rRNA gene. For example, probes complementary to the more conserved features regions identify species in a large phylogenetic group, each group corresponding to a higher taxon (for example, domain, phylum, class, order, or family). Probes complementary to more variable regions distinguish genera and species.
Biomarkers can also include micro RNAs. “MicroRNAs” (miRs) refers to a class of small naturally occurring non-coding RNAs (18-24 nucleotides) that regulate gene expression. Many microRNAs are well conserved across species and they are present in a broad range of species: plants, nematodes, fruit flies and humans. MicroRNAs have partially or perfect complementary sequence to one or more messenger RNA molecules (mRNAs) and their main function is to negatively regulate the expression of genes. In particular, microRNAs bind to the 3′ untranslated regions of mRNAs (3-UTR) thus leading to down regulation of mRNAs in a variety of ways such as mRNA cleavage, translational repression and deadenylation.
A variety of experimental approaches and different techniques have been used to identify new microRNAs, as well as to study their expression pattern in the different biological processes. The cloning and identification of new microRNAs have been successfully done from size fractioned RNA samples using small RNA cloning approaches. Other approaches is as putative microRNAs homologues to microRNAs that already have been described in other species or using computational approaches alone or in combination with microarray analysis and sequence-directed cloning.
One of the first techniques used for detection and profiling of microRNAs was Northern Blotting, where hybridization is done with a complementary 32P, digoxigenin-labeled oligo or modified Locked-nucleic-acid (LNA) oligonucleotides after gel separation.
Other techniques that have been developed to specifically detect microRNAs are a modified invader assay (a synthetic oligonucleotide, the probe, which is in an appropriate overlap-flap structure is enzymatically cleavage by a structure-specific 5* nuclease) and in situ hybridization (using fluorescent-labeled complementary probes containing chemically modified nucleotides e.g. LNAs). Another widely used technique for detection and profiling of microRNAs is the use of oligonucleotide micro-array based detection platforms either with DNA capture probes or using modified Locked-nucleic-acid (LNA) oligonucleotides in which the ribose moiety is modified with an extra bridge that connects the 2′-0 and 4′-C atoms.
In addition, quantitative real-time PCR (reverse transcriptase/polymerase chain reaction using Taqman or SYBR green technology) has been used for detection and profiling of precursor or mature microRNAs. This technique is sensitive and requires low amounts of starting material for the detection of individual mature microRNAs. Taqman microRNA arrays have been developed that provide the sensitivity of the qRT-PCR, while at the same time enables the simultaneously detection of different microRNAs in one sample.
Biomarkers can also include metabolites. “Metabolite” or “small molecule” refers to organic and inorganic molecules which are present in a sample. The term does not include large macromolecules, such as large proteins (e.g., proteins with molecular weights over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), large nucleic acids (e.g., nucleic acids with molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), or large polysaccharides (e.g., polysaccharides with a molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000).
The metabolites of the cell are generally found free in solution. A “metabolic profile”, or “small molecule profile”, means a complete or partial inventory of small molecules within a targeted cell, tissue, organ, organism, or fraction thereof (e.g., cellular compartment). The inventory may include the quantity and/or type of small molecules present. The “small molecule profile” may be determined using a single technique or multiple different techniques.
A metabolic profile can be developed by analyzing a sample using for example, techniques such as GC-MS (gas chromatography-mass spectrometry) and LC-MS (liquid chromatography-mass spectrometry).
Biomarker Panels
Any combination of the biomarkers described herein is used to assemble a biomarker panel, which is detected or measured as described herein. As is generally understood in the art, a combination may refer to an entire set or any subset or subcombination thereof. The term “biomarker panel,” “biomarker profile,” or “biomarker fingerprint” refers to a set of biomarkers. As used herein, these terms can also refer to any form of the biomarker that is measured. Thus, if CCNI is part of a biomarker panel, then either CCNI mRNA, for example, or protein, for example, could be considered to be part of the panel. While individual biomarkers are useful as diagnostics, combination of biomarkers can sometimes provide greater value in determining a particular status than single biomarkers alone. Specifically, the detection of a plurality of biomarkers in a sample can increase the sensitivity and/or specificity of the test. Thus, in various embodiments, a biomarker panel may include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or more types of biomarkers. In various exemplary embodiments, the biomarker panel consists of a minimum number of biomarkers to generate a maximum amount of information. Thus, in various embodiments, the biomarker panel consists of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or more types of biomarkers. Where a biomarker panel “consists of” a set of biomarkers, no biomarkers other than those of the set are present. In exemplary embodiments, the biomarker panel consists of 1 biomarkers disclosed herein. In various embodiments, the biomarker panel consists of 2 biomarkers disclosed herein. In various embodiments, the biomarker panel consists of 3 biomarkers disclosed herein. In various embodiments, the biomarker panel consists of 4 or more biomarkers disclosed herein.
In various exemplary embodiments, the biomarker panel comprises or consists of a biomarker selected from the group of CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:8), Chain B, Crystal Structure of the Complex formed between MHc-Like Zinc Alpha2-Glycoprotein and Pro1, Porphyromonas catoniae 16S rRNA, Campylobacter showae 16S rRNA, Streptocococcus salivaris 16S rRNA, Campylobacter rectus 16S rRNA, Veillonella parvula 16S rRNA, Kigella oralis 16S rRNA.
A biomarker can also be a clinical parameter. The term “clinical parameter” refers to all non-sample or non-analyte biomarkers of subject health status or other characteristics, such as, without limitation, age, ethnicity, gender, family history, height, and weight.
The biomarkers of the invention show a statistically significant difference in lung cancer diagnosis. In various embodiments, diagnostic tests that use these biomarkers alone or in combination show a sensitivity and specificity of at least about 85%, at least about 90%, at least about 95%, at least about 98% and about 100%.
Measurement and Detection of Biomarkers
Biomarkers generally can be measured and detected through a variety of assays, methods and detection systems known to one of skill in the art. The term “measuring,” “detecting,” or “taking a measurement” refers to a quantitative or qualitative determination of a property of an entity, for example, quantifying the amount or concentration of a molecule or the activity level of a molecule. The term “concentration” or “level” can refer to an absolute or relative quantity. Measuring a molecule may also include determining the absence or presence of the molecule. Various methods include but are not limited to refractive index spectroscopy (RI), ultra-violet spectroscopy (UV), fluorescence analysis, electrochemical analysis, radiochemical analysis, near-infrared spectroscopy (near-IR), infrared (IR) spectroscopy, nuclear magnetic resonance spectroscopy (NMR), light scattering analysis (LS), mass spectrometry, pyrolysis mass spectrometry, nephelometry, dispersive Raman spectroscopy, gas chromatography, liquid chromatography, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) combined with mass spectrometry, ion spray spectroscopy combined with mass spectrometry, capillary electrophoresis, colorimetry and surface plasmon resonance (such as according to systems provided by Biacore Life Sciences). See also PCT Publications WO/2004/056456 and WO/2004/088309. In this regard, biomarkers can be measured using the above-mentioned detection methods, or other methods known to the skilled artisan. Other biomarkers can be similarly detected using reagents that are specifically designed or tailored to detect them.
Different types of biomarkers and their measurements can be combined in the compositions and methods of the present invention. In various embodiments, the protein form of the biomarkers is measured. In various embodiments, the nucleic acid form of the biomarkers is measured. In exemplary embodiments, the nucleic acid form is mRNA. In various embodiments, measurements of protein biomarkers are used in conjunction with measurements of nucleic acid biomarkers.
Methods for detecting mRNA, such as RT-PCR, real time PCR, branch DNA, NASBA and others, are well known in the art. Using sequence information provided by the database entries for the biomarker sequences, expression of the biomarker sequences can be detected (if present) and measured using techniques well known to one of ordinary skill in the art. For example, sequences in sequence database entries or sequences disclosed herein can be used to construct probes for detecting biomarker RNA sequences in, e.g., Northern blot hybridization analyses or methods which specifically, and, preferably, quantitatively amplify specific nucleic acid sequences. As another example, the sequences can be used to construct primers for specifically amplifying the biomarker sequences in, e.g., amplification-based detection methods such as reverse-transcription based polymerase chain reaction (RT-PCR). When alterations in gene expression are associated with gene amplification, deletion, polymorphisms and mutations, sequence comparisons in test and reference populations can be made by comparing relative amounts of the examined DNA sequences in the test and reference cell populations. In addition to Northern blot and RT-PCR, RNA can also be measured using, for example, other target amplification methods (e.g., TMA, SDA, NASBA), signal amplification methods (e.g., bDNA), nuclease protection assays, in situ hybridization and the like.
In one embodiment in the present invention are biochip assays. By “biochip” or “chip” herein is meant a composition generally comprising a solid support or substrate to which a capture binding ligand (also called an adsorbent, affinity reagent or binding ligand, or when nucleic acid is measured, a capture probe) is attached and can bind either proteins, nucleic acids or both. Generally, where a biochip is used for measurements of protein and nucleic acid biomarkers, the protein biomarkers are measured on a chip separate from that used to measure the nucleic acid biomarkers. For nonlimiting examples of additional platforms and methods useful for measuring nucleic acids, see Publications US/2006/0275782, US/2005/0064469 and DE10201463. In various embodiments, biomarkers are measured on the same platform, such as on one chip. In various embodiments, biomarkers are measured using different platforms and/or different experimental runs.
By “binding ligand,” “capture binding ligand,” “capture binding species,” “capture probe” or grammatical equivalents herein is meant a compound that is used to detect the presence of or to quantify, relatively or absolutely, a target analyte, target species or target sequence (all used interchangeably) and that will bind to the target analyte, target species or target sequence. Generally, the capture binding ligand or capture probe allows the attachment of a target species or target sequence to a solid support for the purposes of detection as further described herein. Attachment of the target species to the capture binding ligand may be direct or indirect. In exemplary embodiments, the target species is a biomarker. As will be appreciated by those in the art, the composition of the binding ligand will depend on the composition of the biomarker. Binding ligands for a wide variety of biomarkers are known or can be readily found using known techniques. For example, when the biomarker is a protein, the binding ligands include proteins (particularly including antibodies or fragments thereof (Fabs, etc.) as discussed further below) or small molecules. The binding ligand may also have cross-reactivity with proteins of other species. Antigen-antibody pairs, receptor-ligands, and carbohydrates and their binding partners are also suitable analyte-binding ligand pairs. In various embodiments, the binding ligand may be nucleic acid. Nucleic acid binding ligands find particular use when proteins are the targets; alternatively, as is generally described in U.S. Pat. Nos. 5,270,163; 5,475,096; 5,567,588; 5,595,877; 5,637,459; 5,683,867; 5,705,337 and related patents, hereby incorporated by reference, nucleic acid “aptamers” can be developed for binding to virtually any biomarker. Nucleic acid binding ligands also find particular use when nucleic acids are binding targets. There is a wide body of literature relating to the development of binding partners based on combinatorial chemistry methods. In these embodiments, when the binding ligand is a nucleic acid, preferred compositions and techniques are outlined in PCT Publication WO/1998/020162, hereby incorporated by reference.
In various exemplary embodiments, the capture binding ligand is an antibody. These embodiments are particularly useful for the detection of the protein form of a biomarker.
Detecting or measuring the level (e.g. the transcription level) of a biomarker involves binding of the biomarker to a capture binding ligand, generally referred to herein as a “capture probe” when the mRNA of the biomarker is to be detected on a solid support. In that sense, the biomarker is a target sequence. The term “target sequence” or “target nucleic acid” or grammatical equivalents herein means a nucleic acid sequence that may be a portion of a gene, a regulatory sequence, genomic DNA, cDNA, RNA including mRNA and rRNA, or others. As is outlined herein, the target sequence may be a target sequence from a sample, or a secondary target such as a product of an amplification reaction such as PCR etc. In some embodiments, measuring a nucleic acid can thus refer to measuring the complement of the nucleic acid. It may be any length, with the understanding that longer sequences are more specific.
The target sequence may also comprise different target domains; for example, a first target domain of the sample target sequence may hybridize to a first capture probe, a second target domain may hybridize to a label probe (e.g. a “sandwich assay” format), etc. The target domains may be adjacent or separated as indicated. Unless specified, the terms “first” and “second” are not meant to confer an orientation of the sequences with respect to the 5′-3′ orientation of the target sequence. For example, assuming a 5′-3′ orientation of the target sequence, the first target domain may be located either 5′ to the second domain, or 3′ to the second domain.
When nucleic acids are used as the target analyte, the assays of the invention can take on a number of embodiments. In one embodiment, the assays are done in solution format, using any number of solution based formats. In one embodiment, end-point or real time PCR formats are used, as are well known in the art. These assays can be done either as a panel, in individual tubes or wells, or as multiplex assays, using sets of primers and different labels within a single tube or well. In addition to PCR-based solution formats, other formats can be utilized, including, but not limited to for example ligation based assays utilizing FRET dye pairs. In this embodiment, only upon ligation of two (or more) probes hybridized to the target sequence is a signal generated.
In many embodiments, the assays are done on a solid support, utilizing a capture probe associated with the surface. As discussed herein, the capture probes (or capture binding ligands, as they are sometimes referred to) can be covalently attached to the surface, for example using capture probes terminally modified with functional groups, for example amino groups, that are attached to modified surfaces such as silanized glass. Alternatively, non-covalent attachment, such as electrostatic, hydrophobic/hydrophilic adhesion can be utilized. As is appreciated by those in the art and discussed herein, a large number of attachments are possible on a wide variety of surfaces.
In this embodiment, the assays can take on a number of formats. In one embodiment, the target sequence comprises a detectable label, as described herein. In this embodiment, the label is generally added to the target sequence during amplification of the target in one of two ways: either labeled primers are utilized during the amplification step or labeled dNTPs are used, both of which are well known in the art. The label can either be a primary or secondary label as discussed herein. For example, in one embodiment, the label on the primer and/or a dNTP is a primary label such as a fluorophore. Alternatively, the label may be a secondary label such as biotin or an enzyme; for example, in one embodiment, the primers or dNTPs are labeled with biotin, and then a streptavidin/label complex is added. In one embodiment, the streptavidin/label complex contains a label such as a fluorophore. In an alternative embodiment, the streptavidin/label complex comprises an enzymatic label. For example, the complex can comprise horseradish peroxidase, and upon addition of TMB, the action of the horseradish peroxidase causes the TMB to precipitate, causing an optically detectable event. This has a particular benefit in that the optics for detection does not require the use of a fluorimeter.
In alternate embodiments, the solid phase assay relies on the use of a labeled soluble capture ligand, sometimes referred to as a “label probe” or “signaling probe” when the target analyte is a nucleic acid. In this format, the assay is a “sandwich” type assay, where the capture probe binds to a first domain of the target sequence and the label probe binds to a second domain. In this embodiment, the label probe can also be either a primary (e.g. a fluorophore) or a secondary (biotin or enzyme) label. In one embodiment, the label probe comprises biotin, and a streptavidin/enzyme complex is used, as discussed herein. As above, for example, the complex can comprise horseradish peroxidase, and upon addition of TMB, the action of the horseradish peroxidase causes the TMB to precipitate, causing an optically detectable event.
Detection of a target species in some embodiments requires a “label” or “detectable marker” (as described below) that can be incorporated in a variety of ways. Thus, in various embodiments, the composition comprises a “label” or a “detectable marker.” In one embodiment, the target species (or target analyte or target sequence) is labeled; binding of the target species thus provides the label at the surface of the solid support.
In embodiments finding particular use herein, a sandwich format is utilized, in which target species are unlabeled. In these embodiments, a “capture” or “anchor” binding ligand is attached to the detection surface as described herein, and a soluble binding ligand (frequently referred to herein as a “signaling probe,” “label probe” or “soluble capture ligand”) binds independently to the target species and either directly or indirectly comprises at least one label or detectable marker.
By “label” or “labeled” herein is meant that a compound has at least one molecule, element, isotope or chemical compound attached to enable the detection of the compound. In general, labels fall into four classes: a) isotopic labels, which may be radioactive or heavy isotopes; b) magnetic, electrical, thermal; c) colored or luminescent dyes; and d) enzymes; although labels include particles such as magnetic particles as well. The dyes may be chromophores or phosphors but are preferably fluorescent dyes, which due to their strong signals provide a good signal-to-noise ratio for decoding. Suitable dyes for use in the invention include, but are not limited to, fluorescent lanthanide complexes, including those of Europium and Terbium, fluorescein, rhodamine, tetramethylrhodamine, eosin, erythrosin, coumarin, methyl-coumarins, pyrene, Malacite green, stilbene, Lucifer Yellow, Cascade Blue, Texas Red, Alexa dyes and others described in the 6th Edition of the Molecular Probes Handbook by Richard P. Haugland, hereby expressly incorporated by reference. Additional labels include nanocrystals or Q-dots as described in U.S. Pat. No. 6,544,732 incorporated by reference.
In various embodiments, a secondary detectable label is used. A secondary label is one that is indirectly detected; for example, a secondary label can bind or react with a primary label for detection, can act on an additional product to generate a primary label (e.g. enzymes), or may allow the separation of the compound comprising the secondary label from unlabeled materials, etc. Secondary labels include, but are not limited to, one of a binding partner pair; chemically modifiable moieties; nuclease inhibitors, enzymes such as horseradish peroxidase, alkaline phosphatases, lucifierases, etc. Secondary labels can also include additional labels.
In various embodiments, the secondary label is a binding partner pair. For example, the label may be a hapten or antigen, which will bind its binding partner. For example, suitable binding partner pairs include, but are not limited to: antigens (such as proteins (including peptides)) and antibodies (including fragments thereof (Fabs, etc.)); proteins and small molecules, including biotin/streptavidin; enzymes and substrates or inhibitors; other protein-protein interacting pairs; receptor-ligands; and carbohydrates and their binding partners. Nucleic acid-nucleic acid binding proteins pairs are also useful. In general, the smaller of the pair is attached to the NTP for incorporation into the primer. Preferred binding partner pairs include, but are not limited to, biotin (or imino-biotin) and streptavidin, digeoxinin and Abs, and ProlinxTM reagents.
In the sandwich formats of the invention, an enzyme serves as the secondary label, bound to the soluble capture ligand. Of particular use in some embodiments is the use of horseradish peroxidase, which when combined with 3,3′,5,5′-tetramethylbenzidine (TMB) forms a colored precipitate which is then detected. In some cases, the soluble capture ligand comprises biotin, which is then bound to a enzyme-streptavidin complex and forms a colored precipitate with the addition of TMB.
In various embodiments, the label or detectable marker is a conjugated enzyme (for example, horseradish peroxidase). In various embodiments, the system relies on detecting the precipitation of a reaction product or on a change in, for example, electronic properties for detection. In various embodiments, none of the compounds comprises a label.
As used herein, the term “fluorescent signal generating moiety” or “fluorophore” refers to a molecule or part of a molecule that absorbs energy at one wavelength and re-emits energy at another wavelength. Fluorescent properties that can be measured include fluorescence intensity, fluorescence lifetime, emission spectrum characteristics, energy transfer, and the like.
Signals from single molecules can be generated and detected by a number of detection systems, including, but not limited to, scanning electron microscopy, near field scanning optical microscopy (NSOM), total internal reflection fluorescence microscopy (TIRFM), and the like. Abundant guidance is found in the literature for applying such techniques for analyzing and detecting nanoscale structures on surfaces, as evidenced by the following references that are incorporated by reference: Reimer et al, editors, Scanning Electron Microscopy: Physics of Image Formation and Microanalysis, 2nd Edition (Springer, 1998); Nie et al, Anal. Chem., 78: 1528-1534 (2006); Hecht et al, Journal Chemical Physics, 112: 7761-7774 (2000); Zhu et al, editors, Near-Field Optics: Principles and Applications (World Scientific Publishing, Singapore, 1999); Drmanac, PCT Publication WO/2004/076683; Lehr et al, Anal. Chem., 75: 2414-2420 (2003); Neuschafer et al, Biosensors & Bioelectronics, 18: 489-497 (2003); Neuschafer et al, U.S. Pat. No. 6,289,144; and the like.
Thus, a detection system for fluorophores includes any device that can be used to measure fluorescent properties as discussed above. In various embodiments, the detection system comprises an excitation source, a fluorophore, a wavelength filter to isolate emission photons from excitation photons and a detector that registers emission photons and produces a recordable output, in some embodiments as an electrical signal or a photographic image. Examples of detection devices include without limitation spectrofluorometers and microplate readers, fluorescence microscopes, fluorescence scanners (including e.g. microarray readers) and flow cytometers.
In various exemplary embodiments, the binding of the biomarker to the binding ligand is specific or selective, and the binding ligand is part of a binding pair. By “specifically bind” or “selectively bind” or “selective for” a biomarker herein is meant that the ligand binds the biomarker with specificity sufficient to differentiate between the biomarker and other components or contaminants of the test sample.
The term “solid support” or “substrate” refers to any material that can be modified to contain discrete individual sites appropriate for the attachment or association of a capture binding ligand. Suitable substrates include metal surfaces such as gold, electrodes, glass and modified or functionalized glass, plastics (including acrylics, polystyrene and copolymers of styrene and other materials, polypropylene, polyethylene, polybutylene, polycarbonate, polyurethanes, Teflon, derivatives thereof, etc.), polysaccharides, nylon or nitrocellulose, resins, mica, silica or silica-based materials including silicon and modified silicon, carbon, metals, inorganic glasses, fiberglass, ceramics, GETEK (a blend of polypropylene oxide and fiberglass) and a variety of other polymers. Of particular use in the present invention are the ClonDiag materials described below.
Frequently, the surface of a biochip comprises a plurality of addressable locations, each of which comprises a capture binding ligand. An “array location,” “addressable location,” “pad” or “site” herein means a location on the substrate that comprises a covalently attached capture binding ligand. An “array” herein means a plurality of capture binding ligands in a regular, ordered format, such as a matrix. The size of the array will depend on the composition and end use of the array. Arrays containing from about two or more different capture binding ligands to many thousands can be made. Generally, the array will comprise 3, 4, 5, 6, 7 or more types of capture binding ligands depending on the end use of the array. In the present invention, the array can include controls, replicates of the markers and the like. Exemplary ranges are from about 3 to about 50. In some embodiments, the compositions of the invention may not be in array format; that is, for some embodiments, compositions comprising a single capture ligand may be made as well. In addition, in some arrays, multiple substrates may be used, either of different or identical compositions. Thus for example, large arrays may comprise a plurality of smaller substrates.
Accordingly, in one aspect, the invention provides a composition comprising a solid support comprising a capture binding ligand for each biomarker of a biomarker panel. In various embodiments, the capture ligand is a nucleic acid. In various embodiments, the capture binding ligand is an antibody. In various embodiments, the composition further comprises a soluble binding ligand for each biomarker of a biomarker panel.
A number of different biochip array platforms as known in the art may be used. For example, the compositions and methods of the present invention can be implemented with array platforms such as GeneChip® (Affymetrix), CodeLinkTM Bioarray (Amersham), Expression Array System (Applied Biosystems), SurePrint microarrays (Agilent), Sentrix® LD BeadChip or Sentrix® Array Matrix (Illumina) and Verigene (Nanosphere).
In various exemplary embodiments, detection and measurement of biomarkers utilizes colorimetric methods and systems in order to provide an indication of binding of a target analyte or target species. In colorimetric methods, the presence of a bound target species such as a biomarker will result in a change in the absorbance or transmission of light by a sample or substrate at one or more wavelengths. Detection of the absorbance or transmission of light at such wavelengths thus provides an indication of the presence of the target species.
A detection system for colorimetric methods includes any device that can be used to measure colorimetric properties as discussed above. Generally, the device is a spectrophotometer, a colorimeter or any device that measures absorbance or transmission of light at one or more wavelengths. In various embodiments, the detection system comprises a light source; a wavelength filter or monochromator; a sample container such as a cuvette or a reaction vial; a detector, such as a photoresistor, that registers transmitted light; and a display or imaging element.
In various exemplary embodiments, a ClonDiag chip platform is used for the colorimetric detection of biomarkers. In various embodiments, a ClonDiag ArrayTube (AT) is used. One unique feature of the ArrayTube is the combination of a micro probe array (the biochip) and micro reaction vial. In various embodiments, where a target sequence is a nucleic acid, detection of the target sequence is done by amplifying and biotinylating the target sequence contained in a sample and optionally digesting the amplification products. The amplification product is then allowed to hybridize with probes contained on the ClonDiag chip. A solution of a streptavidin-enzyme conjugate, such as Poly horseradish peroxidase (HRP) conjugate solution, is contacted with the ClonDiag chip. After washing, a dye solution such as o-dianisidine substrate solution is contacted with the chip. Oxidation of the dye results in precipitation that can be detected colorimetrically. Further description of the ClonDiag platform is found in Monecke S, Slickers P, Hotzel H et al., Clin Microbiol Infect 2006, 12: 718-728; Monecke S, Berger-Bächi B, Coombs C et al., Clin Microbiol Infect 2007, 13: 236-249; Monecke S, Leube I and Ehricht R, Genome Lett 2003, 2: 106-118; Monecke S and Ehricht R, Clin Microbiol Infect 2005, 11: 825-833; German Patent DE 10201463; US Publication US/2005/0064469 and ClonDiag, ArrayTube (AT) Experiment Guideline for DNA-Based Applications, version 1.2, 2007, all incorporated by reference in their entirety. One of skill in the art will appreciate that numerous other dyes that react with a peroxidase can be utilized to produce a colorimetric change, such as 3,3′,5,5′-tetramethylbenzidine (TMB). For information on specific assay protocols, see www.clondiag.com/technologies/publications.php.
In various embodiments, where a target species is a protein, the ArrayTube biochip comprises capture binding ligands such as antibodies. A sample is contacted with the biochip, and any target species present in the sample is allowed to bind to the capture binding ligand antibodies. A soluble capture binding ligand or a detection compound such as a horseradish peroxidase conjugated antibody is allowed to bind to the target species. A dye, such as TMB, is then added and allowed to react with the horseradish peroxidase, causing precipitation and a color change that is detected by a suitable detection device. Further description of protein detection using ArrayTube is found in, for example, Huelseweh B, Ehricht R and Marschall H-J, Proteomics, 2006, 6, 2972-2981; and ClonDiag, ArrayTube (AT) Experiment Guideline for Protein-Based Applications, version 1.2, 2007, all incorporated by reference in their entirety.
Transmission detection and analysis is performed with a ClonDiag AT reader instrument. Suitable reader instruments and detection devices include the ArrayTube Workstation ATS and the ATR 03.
In addition to ArrayTube, the ClonDiag ArrayStrip (AS) can be used. The ArrayStrip provides a 96-well format for high volume testing. Each ArrayStrip consists of a standard 8-well strip with a microarray integrated into the bottom of each well. Up to 12 ArrayStrips can be inserted into one microplate frame enabling the parallel multiparameter testing of up to 96 samples. The ArrayStrip can be processed using the ArrayStrip Processor ASP, which performs all liquid handling, incubation, and detection steps required in array based analysis. In various embodiments, where a protein is detected, a method of using the ArrayStrip to detect the protein comprises conditioning the AS array with buffer or blocking solution; loading of up to 96 sample solutions in the AS wells to allow for binding of the protein; 3× washing; conjugating with a secondary antibody linked to HRP; 3× washing; precipitation staining with TMB; and AS array imaging and optional data storage.
Those skilled in the art will be familiar with numerous additional immunoassay formats and variations thereof which may be useful for carrying out the method disclosed herein. See generally E. Maggio, Enzyme-Immunoassay, (CRC Press, Inc., Boca Raton, Fla., 1980); see also U.S. Pat. Nos. 4,727,022; 4,659,678; 4,376,110; 4,275,149; 4,233,402; and 4,230,767.
In general, immunoassays carried out in accordance with the present invention may be homogeneous assays or heterogeneous assays. In a homogeneous assay the immunological reaction usually involves the specific antibody (e.g., anti-biomarker protein antibody), a labeled analyte, and the sample of interest. The signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labeled analyte. Both the immunological reaction and detection of the extent thereof can be carried out in a homogeneous solution. Immunochemical labels which may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
In a heterogeneous assay approach, the reagents are usually the sample, the antibody, and means for producing a detectable signal. Samples as described above may be used. The antibody can be immobilized on a support, such as a bead (such as protein A and protein G agarose beads), plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase. The support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal. The signal is related to the presence of the analyte in the sample. Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels. For example, if the antigen to be detected contains a second binding site, an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step. The presence of the detectable group on the solid support indicates the presence of the antigen in the test sample. Examples of suitable immunoassays include immunoblotting, immunofluorescence methods, immunoprecipitation, chemiluminescence methods, electrochemiluminescence (ECL) or enzyme-linked immunoassays.
Antibodies can be conjugated to a solid support suitable for a diagnostic assay (e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding. Antibodies as described herein may likewise be conjugated to detectable labels or groups such as radiolabels (e.g., 35S, 125I, 131I), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine) in accordance with known techniques.
Using any of the methods and compositions described herein, a sample can be assayed to determine levels of a biomarker panel. Thus, in one aspect, the invention provides a method of assaying a sample from a patient to determine concentrations of a biomarker panel in the sample. In some embodiments, the method comprises contacting the sample with a composition comprising a solid support comprising a capture binding ligand or capture probe for each biomarker of a biomarker panel.
The invention further provides kits for use in determining lung health or lung cancer status for a number of medical (including diagnostic and therapeutic), industrial, forensic and research applications. Kits may comprise a carrier, such as a box, carton, tube or the like, having in close confinement therein one or more containers, such as vials, tubes, ampoules, bottles, pouches, envelopes and the like. In various embodiments, the kits comprise one or more components selected from one or more media or media ingredients and reagents for the measurement of the various biomarkers and biomarker panels disclosed herein. For example, kits of the invention may also comprise, in the same or different containers, one or more DNA polymerases, one or more primers, one or more suitable buffers, one or more nucleotides (such as deoxynucleoside triphosphates (dNTPs) and preferably fluorescently labeled dNTPs) and labeling components. The one or more components may be contained within the same container, or may be in separate containers to be admixed prior to use. The kits of the present invention may also comprise one or more instructions or protocols for carrying out the methods of the present invention. The kits may also comprise a computer or a component of a computer, such as a computer-readable storage medium or device. Examples of storage media include, without limitation, optical disks such as CD, DVD and Blu-ray Discs (BD); magneto-optical disks; magnetic media such as magnetic tape and internal hard disks and removable disks; semi-conductor memory devices such as EPROM, EEPROM and flash memory; and RAM. The computer-readable storage medium may comprise software encoding references to the various therapies and treatment regimens disclosed herein. The software may be interpreted by a computer to provide the practitioner with treatments according to various measured concentrations of biomarkers as provided herein. In various embodiments, the kit comprises a biomarker assay involving a lateral-flow-based point-of-care rapid test with detection of risk thresholds, or a biochip with quantitative assays for the constituent biomarkers.
Methods of Diagnosing and Treating
The compositions and methods of the present invention can be used in the prognosis, diagnosis and treatment of disease in a subject. The invention provides compositions and methods for laboratory and point-of-care tests for measuring biomarkers in a sample from a subject. The invention can be generally applied for a number of different diseases. In exemplary embodiments, the disease is lung cancer.
The biomarkers and biomarker panels disclosed herein can be used in methods to diagnose, identify or screen subjects that have, do not have or are at risk for having disease; to monitor subjects that are undergoing therapies for disease; to determine or suggest a new therapy or a change in therapy; to differentially diagnose disease states associated with the disease from other diseases or within sub-classifications of disease; to evaluate the severity or changes in severity of disease in a patient; to stage a subject with the disease and to select or modify therapies or interventions for use in treating subjects with the disease. In an exemplary embodiment, the methods of the present invention are used to identify and/or diagnose subjects who are asymptomatic or presymptomatic for a disease. In this context, “asymptomatic” or “presymptomatic” means not exhibiting the traditional symptoms or enough abnormality for disease.
In various embodiments, a method of determining a prognosis of a disease in a subject, diagnosing a disease in a subject, or treating a disease in a subject comprises taking a measurement of a biomarker panel in a sample from the subject. In various exemplary embodiments, the biomarker panel consists of two or more of CCNI (Cyclin I)(SEQ ID NO: 1), EGFR (Epidermal growth factor receptor)(SEQ ID NO:2), FGF9 (Fibroblast growth factor 19)(SEQ ID NO: 3), GREB1 protein (SEQ ID NO:4), LZTS (Leucine zipper, putative suppresor I)(SEQ ID NO: 5), BRAF (v-raf murine sarcoma viral oncogene homolog B1 (SEQ ID NO: 6), FRS2 (Fibroblast growth factor receptor substrate 2)(SEQ ID NO: 7), ANXA1 (Annexin A1)(SEQ ID NO: 8), Hp2 (Haptoglobin 2)(SEQ ID NO:8), Chain B, Crystal Structure of the Complex formed between MHc-Like Zinc Alpha2-Glycoprotein and Pro1, Porphyromonas catoniae, Campylobacter showae, Streptocococcus salivaris, Campylobacter rectus, Veillonella parvula, Kigella oralis. 
The term “disease status” includes any distinguishable manifestation of the disease, including non-disease. For example, disease status includes, without limitation, the presence or absence of disease, the risk of developing disease, the stage of the disease, the progression of disease (e.g., progress of disease or remission of disease over time), the severity of disease and the effectiveness or response to treatment of disease.
A “subject” in the context of the present invention is an animal, preferably a mammal. The mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, or cow, but are not limited to these examples. In various exemplary embodiments, a subject is human and may be referred to as a patient. Mammals other than humans can be advantageously used as subjects that represent animal models of a disease or for veterinarian applications. A subject can be one who has been previously diagnosed or identified as having a disease, and optionally has already undergone, or is undergoing, a therapeutic intervention for a disease. Alternatively, a subject can also be one who has not been previously diagnosed as having a disease. For example, a subject can be one who exhibits one or more risk factors for a disease, or one who does not exhibit a disease risk factor, or one who is asymptomatic for a disease. A subject can also be one who is suffering from or at risk of developing a disease. In certain embodiments, the subject can be already undergoing therapy or can be a candidate for therapy.
As will be appreciated by those in the art, the biomarkers may be measured in using several techniques designed to achieve more predictable subject and analytical variability.
The term “sample” refers to a specimen or culture obtained from a subject and includes fluids, gases and solids including for example tissue. In various exemplary embodiments, the sample comprises saliva. As will be appreciated by those in the art, virtually any experimental manipulation or sample preparation steps may have been done on the sample. For example, wash steps and/or fragmentation may be applied to a sample. In various embodiments, a biomarker panel is measured directly in a subject without the need to obtain a separate sample from the patient.
In one aspect, the invention provides a method of diagnosing a subject for a disease comprising taking a measurement of a biomarker panel; and correlating the measurement with the disease. The term “correlating” generally refers to determining a relationship between one type of data with another or with a state. In various embodiments, correlating the measurement with disease comprises comparing the measurement with a reference biomarker profile or some other reference value. In various embodiments, correlating the measurement with disease comprises determining whether the subject is currently in a state of disease.
The quantity or activity measurements of a biomarker panel can be compared to a reference value. Differences in the measurements of biomarkers in the subject sample compared to the reference value are then identified. In exemplary embodiments, the reference value is given by a risk category as described further below.
In various embodiments, the reference value is a baseline value. A baseline value is a composite sample of an effective amount of biomarkers from one or more subjects who do not have a disease, who are asymptomatic for a disease or who have a certain level of a disease. A baseline value can also comprise the amounts of biomarkers in a sample derived from a subject who has shown an improvement in risk factors of a disease as a result of treatments or therapies. In these embodiments, to make comparisons to the subject-derived sample, the amounts of biomarkers are similarly calculated. A reference value can also comprise the amounts of biomarkers derived from subjects who have a disease confirmed by an invasive or non-invasive technique, or are at high risk for developing a disease. Optionally, subjects identified as having a disease, or being at increased risk of developing a disease are chosen to receive a therapeutic regimen to slow the progression of a disease, or decrease or prevent the risk of developing a disease. A disease is considered to be progressive (or, alternatively, the treatment does not prevent progression) if the amount of biomarker changes over time relative to the reference value, whereas a disease is not progressive if the amount of biomarkers remains constant over time (relative to the reference population, or “constant” as used herein). The term “constant” as used in the context of the present invention is construed to include changes over time with respect to the reference value.
The biomarkers of the present invention can be used to generate a “reference biomarker profile” of those subjects who do not have a disease according to a certain threshold, are not at risk of having a disease or would not be expected to develop a disease. The biomarkers disclosed herein can also be used to generate a “subject biomarker profile” taken from subjects who have a disease or are at risk for having a disease. The subject biomarker profiles can be compared to a reference biomarker profile to diagnose or identify subjects at risk for developing a disease, to monitor the progression of disease, as well as the rate of progression of disease, and to monitor the effectiveness of disease treatment modalities. The reference and subject biomarker profiles of the present invention can be contained in a machine-readable medium, such as but not limited to, analog tapes like those readable by a VCR; optical media such as CD-ROM, DVD-ROM and the like; and solid state memory, among others.
Measurements of the biomarker panels of the invention can lead a practitioner to affect a therapy with respect to a subject. Thus, the invention provides methods of treating a disease in a subject comprising taking a measurement of a biomarker panel in a sample from the subject, and affecting a therapy with respect to the subject. The terms “therapy” and “treatment” may be used interchangeably. In certain embodiments, the therapy can be selected from, without limitation, initiating therapy, continuing therapy, modifying therapy or ending therapy. A therapy also includes any prophylactic measures that may be taken to prevent disease.
In certain embodiments, treatment comprises administering a disease-modulating drug to a subject. The drug can be a therapeutic or prophylactic used in subjects diagnosed or identified with a disease or at risk of having the disease. In certain embodiments, modifying therapy refers to altering the duration, frequency or intensity of therapy, for example, altering dosage levels.
In various embodiments, effecting a therapy comprises causing a subject to or communicating to a subject the need to make a change in lifestyle, for example, increasing exercise, changing diet, reducing or eliminating smoking and so on. The therapy can also include surgery, for example, mastectomy.
Measurement of biomarker levels allow for the course of treatment of a disease to be monitored. The effectiveness of a treatment regimen for a disease can be monitored by detecting one or more biomarkers in an effective amount from samples obtained from a subject over time and comparing the amount of biomarkers detected. For example, a first sample can be obtained prior to the subject receiving treatment and one or more subsequent samples are taken after or during treatment of the subject. Changes in biomarker levels across the samples may provide an indication as to the effectiveness of the therapy.
To identify therapeutics or drugs that are appropriate for a specific subject, a test sample from the subject can also be exposed to a therapeutic agent or a drug, and the level of one or more biomarkers can be determined. Biomarker levels can be compared to a sample derived from the subject before and after treatment or exposure to a therapeutic agent or a drug, or can be compared to samples derived from one or more subjects who have shown improvements relative to a disease as a result of such treatment or exposure. Thus, in one aspect, the invention provides a method of assessing the efficacy of a therapy with respect to a subject comprising taking a first measurement of a biomarker panel in a first sample from the subject; effecting the therapy with respect to the subject; taking a second measurement of the biomarker panel in a second sample from the subject and comparing the first and second measurements to assess the efficacy of the therapy.
Additionally, therapeutic or prophylactic agents suitable for administration to a particular subject can be identified by detecting a biomarker (which may be two or more) in an effective amount from a sample obtained from a subject and exposing the subject-derived sample to a test compound that determines the amount of the biomarker(s) in the subject-derived sample. Accordingly, treatments or therapeutic regimens for use in subjects having a disease or subjects at risk for developing a disease can be selected based on the amounts of biomarkers in samples obtained from the subjects and compared to a reference value. Two or more treatments or therapeutic regimens can be evaluated in parallel to determine which treatment or therapeutic regimen would be the most efficacious for use in a subject to delay onset, or slow progression of a disease. In various embodiments, a recommendation is made on whether to initiate or continue treatment of a disease.
Drug Treatments
In various exemplary embodiments, effecting a therapy comprises administering a disease-modulating drug to the subject. The subject may be treated with one or more disease-modulating drugs until altered levels of the measured biomarkers return to a baseline value measured in a population not suffering from the disease, experiencing a less severe stage or form of a disease or showing improvements in disease biomarkers as a result of treatment with a disease-modulating drug. Additionally, improvements related to a changed level of a biomarker or clinical parameter may be the result of treatment with a disease-modulating drug.
A number of compounds such as a disease-modulating drug may be used to treat a subject and to monitor progress using the methods of the invention. In certain embodiments, the disease-modulating drug comprises
The beneficial effects of these and other drugs can be visualized by assessment of clinical and laboratory biomarkers.
Any drug or combination of drugs disclosed herein may be administered to a subject to treat a disease. The drugs herein can be formulated in any number of ways, often according to various known formulations in the art or as disclosed or referenced herein.
In various embodiments, any drug or combination of drugs disclosed herein is not administered to a subject to treat a disease. In these embodiments, the practitioner may refrain from administering the drug or combination of drugs, may recommend that the subject not be administered the drug or combination of drugs or may prevent the subject from being administered the drug or combination of drugs.
In various embodiments, one or more additional drugs may be optionally administered in addition to those that are recommended or have been administered. An additional drug will typically not be any drug that is not recommended or that should be avoided. In exemplary embodiments, one or more additional drugs comprise one or more glucose lowering drugs.
Decision Matrices
The therapy chosen by a practitioner can depend on the concentrations of biomarkers determined in a sample. In various exemplary embodiments, the therapy depends on which category from a range of categories particular to each biomarker the measured concentration of each biomarker falls in. In various exemplary embodiments, the therapy depends on the combination of risk levels for different symptoms or diseases that are indicated by a biomarker panel.
With respect to concentration measurements of a biomarker, the term “category” refers to a subset of a partition of the possible concentrations that a biomarker may have. Each category may be associated with a label or classification chosen by the practitioner. The labels may be refer to, for example, the risk level of an individual for having or being subject to a disease state. The categories and labels may be derived from the current literature or according to the findings of the practitioner.
Each biomarker of a biomarker panel can thus be associated with a discrete set of categories, for example, risk categories. Combining one category from each biomarker forms a “decision point.” In various exemplary embodiments, the complete set of decision points comprises all possible n-tuples of categories, wherein n is the number of biomarkers in the biomarker panel. This complete set will have m1×m2× . . . mn possible decision points, wherein mi is the number of categories for biomarker i.
Every decision point can be associated with a condition or a disease state, which is not necessarily unique. That is, one or more decision points can be associated with the same disease state. The association of every possible decision point with a condition or disease state can be referred to as a “disease classification matrix” or a “disease classification tree.” Thus, by correlating a measurement of a biomarker panel with a decision point, the practitioner can classify the condition or disease state of a patient.
Every decision point can also be associated with a particular therapy, which is not necessarily unique. That is, one or more decision points can be associated with the same therapy. The association of every possible decision point with one or more therapies can be referred to as a “therapy decision matrix” or “therapy decision tree.”
Each decision point can be associated with more than one type of information. For example, both disease state and therapy can be indicated by a decision point.
The articles “a,” “an” and “the” as used herein do not exclude a plural number of the referent, unless context clearly dictates otherwise. The conjunction “or” is not mutually exclusive, unless context clearly dictates otherwise. The term “include” is used to refer to non-limiting examples.
EXAMPLES
The following examples are offered to illustrate, but not to limit the invention.
Example 1
Salivary Transciptomic Profiling and Analysis
Saliva Collection
Unstimulated whole saliva samples were collected with previously established protocols. Subjects were asked to refrain from eating, drinking, smoking, or oral hygiene procedures for at least 30 minutes before the collection. Lipstick was wiped off, and the subject rinsed her mouth once with plain water. Typically, patients donated approximately 5-10 ml of saliva. Samples were then centrifuged at 2,600 g for 15 minutes at 4° C. The supernatant was then stored at −80° C. until use. Of note, protease inhibitors cocktail, containing 1 μl aprotinin, 10 μl PMSF (phenylmethanesulfonyl fluoride) and 3 μl sodium orthovanadate (all from Sigma, St. Louis, Mo.) were added to each 1 ml saliva sample.
mRNA Isolation and Analysis
RNA was isolated from 330 μl of saliva supernatant using MagMaxTM Viral RNA Isolation Kit (Ambion, Austin, Tex.). This process was automated using KingFisher® mL technology (Thermo Fisher Scientific, Waltham, Mass.), followed by TURBOTM DNase treatment (Ambion, Austin, Tex.) to remove contaminating DNA. 90 μl of extracted RNA (out of 100 μl) was concentrated to 11 μl and was linearly amplified using the RiboAmp® RNA Amplification kit (Molecular Devices, Sunnyvale, Calif.). After purification, cDNA was transcribed and biotinylated using GeneChip® Expression 3′-Amplification Reagents for in vitro transcription labeling (Affymetrix, Santa Clara, Calif.). Approximately 20 μg of labeled RNA were subsequently submitted for GeneChip® analysis using an Affymetrix Human Genome U133 Plus 2.0 Array. Chip hybridization and scanning were performed.
Gene Array Statistical Analysis
The CEL files from all databases were imported into the statistical R 2.7.0 (hypertext transfer protocol://www.r-project.org) using Bioconductor 2.2 (hypertext transfer protocol://www.bioconductor.org. The Probe Logarithmic Intensity Error Estimation (PLIER) expression measures were computed after background correction and quantile normalization for each microarray dataset. Probeset-level quantile normalization was performed across all samples to make the effect sizes similar among all datasets. Finally, for every probeset, two-sample t-test was applied to identify differential expression. After obtaining the estimates and the p-values of each probset, p-values of each probeset was corrected for false discovery rate (FDR). Genes were selected at the FDR level of 0.05, and with cancer effect size >2 fold change between cancer and normal samples.
Screening of Biomarker Candidates
The biomarker candidates generated by microarray profiling were subjected to further screening by real-time quantitative RT-PCR (qPCR) on the same set of samples used for the microarray analysis. To accomplish this, total RNA was reverse-transcribed using reverse transcriptase and gene-specific primers using the following thermal cycling conditions: 1 min at 60° C., 30 min at 50° C., 2 min at 95° C., followed by 15 cycles of 15 s at 95° C., 30 s at 50° C., 10 s at 72° C. These steps were followed with a final extension of 5 min. at 72° C. and then cooling to 4° C. The preamplified product was cleaned using ExoSAP-IT (USB Corporation) and diluted 1/40 in water. 2 μl of the cDNA was used for qPCR.
qPCR was carried out in a 96-well plate in a reation volume of 10 μl using power SYBR®-Green Master Mix (Applied Biosystems, Foster City, Calif.) for 15 min at 95° C. for initial denaturing, followed by 40 cycles of 95° C. for 30 s and 60° C. for 30 s in the ABI 7500HT Fast Real Time PCR system (Applied Biosystems, Foster City, Calif.). All qPCRS were performed in duplicate for all candidate mRNA. The specificity of the PCR was confirmed according to the melting curve of each gene, and the average threshold cycle (Ct) was examined.
Amplicon lengths were around 100-130 bp for the outer primer pairs used in preamplification and 60-80 bp for the inner primer pairs used in qPCR. RT-qPCR primers were designed using Primer Express 3.0 software (Applied Biosystems, Foster City, Calif.). All primers were synthesized by Sigma-Genosys (Woodlands, Tex.), and the amplicons were intron spanning whenever possible.
Raw data were normalized by subtracting GAPDH Ct values from the biomarker Ct values to generate ΔCt. The Mann-Whitney rank sum test was used for between-group biomarker comparisons.
The data analysis for qPCR was performed using the 2−Ct method, where GAPDH is used as the reference gene. The qPCR based gene expression values between two groups were compared using the non-parametric Wilcoxon test. To normalize for RNA input, qPCR was also performed for GAPDH. Raw data were normalized by subtracting GAPDH Ct values from the marker Ct values to provide ΔCt and then analyze with the stats, utilities packages from R 2.7.0 (world wide web.r-project.org) and the ROC package from Bioconductor 2.2 (world wide web.bioconductor.org). Statistical comparisons were made with the use of the Mann-Whitney U test with consideration of two different distributions for control and pancreatic cancer groups. Biomarkers that differentiated between groups of subjects (P value <0.05) were identified and compared by Area Under Curve (AUC) value. The AUC is based on constructing a receiver operating characteristic (ROC) curve which plots the sensitivity versus one minus the specificity. The AUC value is computed by numerical integration of the ROC curve. The range of this value can be 0.5 to 1.0. A value of 0.5 indicates that the biomarker is no better that a coin toss, while 1.0 indicates the relatively best diagnostic accuracy.
Seven mRNA biomarkers were identified as differentially expressed between lung cancer subjects and control subjects. The logistic regression model, with the combination of three mRNA biomarkers (GREB1, CCNI, and FRS2) differentiated lung cancer patients from control subjects, yielding a ROC-plot AUC value of approximately 0.91 with approximately 91% sensitivity and approximately 88% specificity.
Example 2
Salivary Proteomic Profiling and Analysis
Protein Isolation and Analysis
Saliva from 10 healthy control subjects and 10 lung cancer subjects were collected and centrifuged at 2600 g at 4° C. for 15 minutes. Saliva supernatant from the 10 health control subjects and 10 lung cancer subjects were pooled to form a control sample and a cancer sample for proteomic profiling. 250 μg of proteins in the pooled saliva samples were precipitated by methanol and then resuspended in 2-D cell lysis buffer (30 mM Tris-HCl, pH 8.8, containing 7M urea, 2M thiourea and 4% CHAPS detergent). The total proteins of each pooled sample, lung cancer and control, were labeled with the cyanine dyes Cy2 and Cy5 respectively. The two labeled sample sets were then combined and subjected to two-dimensional difference gel electrophoresis. After loading the labeled samples, isoelectric focusing (IEF) (pH3-10) was run following the protocol provided by Amersham BioSciences. The IPG strips were rinses in the SDS-gel running buffer before transferring to 13.5% SDS-gels. The SDS-gels were run at 15° C. until the dye front ran out of the gels. Gel images were scanned immediately following the SDS-PAGE using Typhoon TRIOTM (Amersham BioSciences). The fold change of the protein expression levels was obtained from in-gel DeCyderTM analysis.
Spots with fold changes larger than 1.5 on the gel were cut and then were washed multiple times to remove staining dye and other chemicals. Gel spots were dried to absorb maximum volume of digestion buffer. Dried 2D gel spots were rehydrated in digestion buffer containing sequencing grade modified trypsin (Promega, USA). Proteins were digested in-gel at 37° C. overnight. Digested peptides were extracted from the gel with TFA extraction buffer and with shaking. The digested tryptic peptides were desalted using C-18 Zip-tips (Millipore). The desalted peptides were mixed with CHCA matrix (α-cyano-4-hydroxycinnamic acid) and spotted into wells of a MALDI plate for MALDI-TOF MS (ABI4800) identification. Protein identification was based on peptide fingerprint mass mapping (using MS spectra) and peptide fragmentation mapping (using MS/MS spectra). Combined MS and MS/MS spectra were submitted for database search using GPS Explorer software equipped with the MASCOT search engine to identify proteins from primary sequence databases.
Screening of Biomarker Candidates
Four proteins (Annexin A1, Haptoglobin HP2, Interleukin 1 receptor antagonsit, Zinc Alpha2-glycoprotein). Calprotectin was verified by commercial ELISA kit. The distribution of Haptoglobin HP2, Zinc Alpha2-glycoprotein and Calprotectin in the cancer group and control shows significant difference with a p value of 0.00903, 0.05, and 0.048, respectively.
The four proteins identified in the 2-D gel analysis (above) were subjected to Western blot analysis on the original sample set. Reduced protein samples (15 μg total protein per lane) were loaded onto a 10% bis-Tris gel and run at 150V in MES SDS running buffer for one hour. Pre-stained protein standard (Invitrogen) was used to track protein migration. The proteins were transferred to nitrocellulose membrane by using iBlot® (Invitrogen). The membrane was then washed in wash buffer containing 10 mM Tris-HCl, pH 7.6, 150 mM NaCl, and 0.1% (v/v) Tween®-20 (Sigma-Aldrich) before blocking for one hour in wash buffer containing 5% non-fat dry milk. After further washes in wash buffer, the membrane was incubated with primary antibody (mouse anti-Annexin A1 (Abcam), mouse anti-haptoglobin (Lifespan Bioscience), mouse anti-ZAG (Santa Cruz Biotech), mouse anti-actin (Sigma-Aldrich), all according to manufacturers instructions in blocking buffer at room temperature for 2 h. The membrane was then washed before applying the secondary antibody (anti-mouse IgG peroxidase-linked species specific whole antibody from sheep, GE Healthcare) according to manufacturer's instructions for one hour at room temperature. Finally, the membrane was washed and visualized using ECL PlusTM detection kit (GE Healthcare). The signal intensity of the bands was measured using Image J software (NIH, Bethesda, Md., USA). The intensity of a band representing the protein of interest was divided by the intensity of it corresponding β-actin expression on the same blot for normalization.
The ELISA for calprotectin was done according to manufacturers instructions (Cell Sciences). All saliva samples were diluted 100 fold in sample diluent. All samples were loaded in duplicate.
Example 3
Salivary Microbial Biomarkers
Saliva from 10 healthy control subjects and 10 lung cancer subjects were collected and centrifuged at 2600 g at 4° C. for 15 minutes. The supernatant was decanted and the pellet was used for DNA isolation.
DNA was extracted from the pellet using UltraClean® Microbial DNA Isolation Kit (MO Bio Laboratories) following the manufacturer's instructions. Isolated DNA was then submitted to the Forsyth Institute (Cambridge, Mass., USA) for microbe analysis using their Human Oral Microbe Identification Microarray service. Based on the microarray profiles from control and lung cancer subjects, eleven microbes were identified as being differentially present among the two subject groups.
Quantities of bacterial strains in the original DNA samples were determined using real-time PCR. Specific primers were designed for all species and real-time PCR was performed to quantify bacterial quantity between lung cancer samples and control samples. Seven bacteria were identified by real-time PCR as differentially present among the sample groups. Two bacteria, Porphyromonas catoniae and Campylobacter showae, were identified as being more abundant in lung cancer subject relative to controls.
Example 4
Screening Method
A patient undergoing routine dental care is screened during the visit. For example, a 62 year old female patient, and former smoker, prior to oral exam is asked to provide a saliva sample. A saliva sample is collected and analyzed either at the point of care or is submitted for analysis by a reference laboratory. The saliva sample is tested for the biomarkers of the instant invention and optionally other biomarkers. Results from the analysis are provided to the dental professional and the patient is informed as to whether she has lung cancer.









SEQ ID NO: 1



Cyclin I (NM_001237.3)



ccatttcaat agtcgcggga tacttgaact gcaagaacag



 



ccgccgctcc ggcgggctgc tcgctgcatc tctgggcgtc



 



tttggctcgc cacgctgggc agtgcctgcc tgcgcctttc



 



gcaacctcct cggccctgcg tggtctcgag ctgggtgagc



 



gagcgggcgg gctggtaggc tggcctgggc tgcgaccggc



 



ggctacgact attctttggc cgggtcggtg cgagtggtcg



 



gctgggcaga gtgcacgctg cttggcgccg caggctgatc



 



ccgccgtcca ctcccgggag cagtgatgtt gggcaactct



 



gcgccggggc ctgcgacccg cgaggcgggc tcggcgctgc



 



tagcattgca gcagacggcg ctccaagagg accaggagaa



 



tatcaacccg gaaaaggcag cgcccgtcca acaaccgcgg



 



acccgggccg cgctggcggt actgaagtcc gggaacccgc



 



ggggtctagc gcagcagcag aggccgaaga cgagacgggt



 



tgcacccctt aaggatcttc ctgtaaatga tgagcatgtc



 



accgttcctc cttggaaagc aaacagtaaa cagcctgcgt



 



tcaccattca tgtggatgaa gcagaaaaag aagctcagaa



 



gaagccagct gaatctcaaa aaatagagcg tgaagatgcc



 



ctggctttta attcagccat tagtttacct ggacccagaa



 



aaccattggt ccctcttgat tatccaatgg atggtagttt



 



tgagtcacca catactatgg acatgtcaat tgtattagaa



 



gatgaaaagc cagtgagtgt taatgaagta ccagactacc



 



atgaggatat tcacacatac cttagggaaa tggaggttaa



 



atgtaaacct aaagtgggtt acatgaagaa acagccagac



 



atcactaaca gtatgagagc tatcctcgtg gactggttag



 



ttgaagtagg agaagaatat aaactacaga atgagaccct



 



gcatttggct gtgaactaca ttgataggtt cctgtcttcc



 



atgtcagtgc tgagaggaaa acttcagctt gtgggcactg



 



ctgctatgct gttagcctca aagtttgaag aaatataccc



 



cccagaagta gcagagtttg tgtacattac agatgatacc



 



tacaccaaga aacaagttct gagaatggag catctagttt



 



tgaaagtcct tacttttgac ttagctgctc caacagtaaa



 



tcagtttctt acccaatact ttctgcatca gcagcctgca



 



aactgcaaag ttgaaagttt agcaatgttt ttgggagaat



 



taagtttgat agatgctgac ccatacctca agtatttgcc



 



atcagttatt gctggagctg cctttcattt agcactctac



 



acagtcacgg gacaaagctg gcctgaatca ttaatacgaa



 



agactggata taccctggaa agtcttaagc cttgtctcat



 



ggaccttcac cagacctacc tcaaagcacc acagcatgca



 



caacagtcaa taagagaaaa gtacaaaaat tcaaagtatc



 



atggtgtttc tctcctcaac ccaccagaga cactaaatct



 



gtaacaatga aagactgcct ttgttttcta agatgtaaat



 



cactcaaagt atatggtgta cagtttttaa cttaggtttt



 



aattttacaa tcatttctga atacagaagt tgtggccaag



 



tacaaattat ggtatctatt actttttaaa tggttttaat



 



ttgtatatct tttgtatatg tatctgtctt agatatttgg



 



ctaattttaa gtggttttgt taaagtatta atgatgccag



 



ctgtcaggat aataaattga tttggaaaac tttgcaagtc



 



aaatttaact tcttcaggat tttgcttagt aaagaagttt



 



acttggttta ctatataatg ggaagtgaaa agccttcctc



 



taaaattaaa gtaggtttag gaaaacagac cctcaaattc



 



tgacattcat tttcctaagc aactggatca atttgctgac



 



ttgggcataa tctaatctaa gcatatctga atacagtatt



 



cagagataga tacagtagag attccccaga ctttttcgct



 



ctttgtaaaa cctgtttgtt taggttttgc gaggtaaact



 



caacagaggt tgggagtgga agagggtggg aagcttatat



 



gcaaattaac agacgagaaa tgctccagaa ggtttattat



 



tttaaagcac attaaaaaca aaaaactatt tttaaaatcc



 



tgctagattt tataatggat ttgtgaataa aaaataccca



 



gggttctcag aatggaataa atatcccttt taatagttat



 



atatacagat atacaactgt tagctttaat tggcagctct



 



cttctttttt cttcttttca ctggcttttt acttggtgct



 



ttttcttgtt ttgcactggt ggtctgtgtt ctgtgaataa



 



agcaaagtaa gaatttacta agagtatgtt aagttttgga



 



ttattgaaat aagaggcatt tcttagtttt ccagtaggat



 



ctaaaatgtg tcagctatga gtaagactgg catccaagaa



 



gtttatatta tagatttagg tcctaatttt tataaatcac



 



aaggtaaaaa aatcacagaa cagatggatc tctaatgaaa



 



aagggatgtc tttttgttta tagtcatgtg gcaagatgag



 



agtaaaacca gagagcaaac ctctataagt gttgagtata



 



tgtatacatt tgaaataaac cagaaatttg ttaccttaaa



 



aaaaaaaaaa a



 



SEQ ID NO: 2



EGFR(NM_005228.3)



ccccggcgca gcgcgggcgc agcagcctcc gccccccgca



 



cggtgtgagc gcccgacgcg gccgaggcgg ccggagtccc



 



gagctagccc cggcggccgc cgccgcccag accggacgac



 



aggccacctc gtcggcgtcc gcccgagtcc ccgcctcgcc



 



gccaacgcca caaccaccgc gcacggcccc ctgactccgt



 



ccagtattga tcgggagagc cggagcgagc tcttcgggga



 



gcagcgatgc gaccctccgg gacggccggg gcagcgctcc



 



tggcgctgct ggctgcgctc tgcccggcga gtcgggctct



 



ggaggaaaag aaagtttgcc aaggcacgag taacaagctc



 



acgcagttgg gcacttttga agatcatttt ctcagcctcc



 



agaggatgtt caataactgt gaggtggtcc ttgggaattt



 



ggaaattacc tatgtgcaga ggaattatga tctttccttc



 



ttaaagacca tccaggaggt ggctggttat gtcctcattg



 



ccctcaacac agtggagcga attcctttgg aaaacctgca



 



gatcatcaga ggaaatatgt actacgaaaa ttcctatgcc



 



ttagcagtct tatctaacta tgatgcaaat aaaaccggac



 



tgaaggagct gcccatgaga aatttacagg aaatcctgca



 



tggcgccgtg cggttcagca acaaccctgc cctgtgcaac



 



gtggagagca tccagtggcg ggacatagtc agcagtgact



 



ttctcagcaa catgtcgatg gacttccaga accacctggg



 



cagctgccaa aagtgtgatc caagctgtcc caatgggagc



 



tgctggggtg caggagagga gaactgccag aaactgacca



 



aaatcatctg tgcccagcag tgctccgggc gctgccgtgg



 



caagtccccc agtgactgct gccacaacca gtgtgctgca



 



ggctgcacag gcccccggga gagcgactgc ctggtctgcc



 



gcaaattccg agacgaagcc acgtgcaagg acacctgccc



 



cccactcatg ctctacaacc ccaccacgta ccagatggat



 



gtgaaccccg agggcaaata cagctttggt gccacctgcg



 



tgaagaagtg tccccgtaat tatgtggtga cagatcacgg



 



ctcgtgcgtc cgagcctgtg gggccgacag ctatgagatg



 



gaggaagacg gcgtccgcaa gtgtaagaag tgcgaagggc



 



cttgccgcaa agtgtgtaac ggaataggta ttggtgaatt



 



taaagactca ctctccataa atgctacgaa tattaaacac



 



ttcaaaaact gcacctccat cagtggcgat ctccacatcc



 



tgccggtggc atttaggggt gactccttca cacatactcc



 



tcctctggat ccacaggaac tggatattct gaaaaccgta



 



aaggaaatca cagggttttt gctgattcag gcttggcctg



 



aaaacaggac ggacctccat gcctttgaga acctagaaat



 



catacgcggc aggaccaagc aacatggtca gttttctctt



 



gcagtcgtca gcctgaacat aacatccttg ggattacgct



 



ccctcaagga gataagtgat ggagatgtga taatttcagg



 



aaacaaaaat ttgtgctatg caaatacaat aaactggaaa



 



aaactgtttg ggacctccgg tcagaaaacc aaaattataa



 



gcaacagagg tgaaaacagc tgcaaggcca caggccaggt



 



ctgccatgcc ttgtgctccc ccgagggctg ctggggcccg



 



gagcccaggg actgcgtctc ttgccggaat gtcagccgag



 



gcagggaatg cgtggacaag tgcaaccttc tggagggtga



 



gccaagggag tttgtggaga actctgagtg catacagtgc



 



cacccagagt gcctgcctca ggccatgaac atcacctgca



 



caggacgggg accagacaac tgtatccagt gtgcccacta



 



cattgacggc ccccactgcg tcaagacctg cccggcagga



 



gtcatgggag aaaacaacac cctggtctgg aagtacgcag



 



acgccggcca tgtgtgccac ctgtgccatc caaactgcac



 



ctacggatgc actgggccag gtcttgaagg ctgtccaacg



 



aatgggccta agatcccgtc catcgccact gggatggtgg



 



gggccctcct cttgctgctg gtggtggccc tggggatcgg



 



cctcttcatg cgaaggcgcc acatcgttcg gaagcgcacg



 



ctgcggaggc tgctgcagga gagggagctt gtggagcctc



 



ttacacccag tggagaagct cccaaccaag ctctcttgag



 



gatcttgaag gaaactgaat tcaaaaagat caaagtgctg



 



ggctccggtg cgttcggcac ggtgtataag ggactctgga



 



tcccagaagg tgagaaagtt aaaattcccg tcgctatcaa



 



ggaattaaga gaagcaacat ctccgaaagc caacaaggaa



 



atcctcgatg aagcctacgt gatggccagc gtggacaacc



 



cccacgtgtg ccgcctgctg ggcatctgcc tcacctccac



 



cgtgcagctc atcacgcagc tcatgccctt cggctgcctc



 



ctggactatg tccgggaaca caaagacaat attggctccc



 



agtacctgct caactggtgt gtgcagatcg caaagggcat



 



gaactacttg gaggaccgtc gcttggtgca ccgcgacctg



 



gcagccagga acgtactggt gaaaacaccg cagcatgtca



 



agatcacaga ttttgggctg gccaaactgc tgggtgcgga



 



agagaaagaa taccatgcag aaggaggcaa agtgcctatc



 



aagtggatgg cattggaatc aattttacac agaatctata



 



cccaccagag tgatgtctgg agctacgggg tgaccgtttg



 



ggagttgatg acctttggat ccaagccata tgacggaatc



 



cctgccagcg agatctcctc catcctggag aaaggagaac



 



gcctccctca gccacccata tgtaccatcg atgtctacat



 



gatcatggtc aagtgctgga tgatagacgc agatagtcgc



 



ccaaagttcc gtgagttgat catcgaattc tccaaaatgg



 



cccgagaccc ccagcgctac cttgtcattc agggggatga



 



aagaatgcat ttgccaagtc ctacagactc caacttctac



 



cgtgccctga tggatgaaga agacatggac gacgtggtgg



 



atgccgacga gtacctcatc ccacagcagg gcttcttcag



 



cagcccctcc acgtcacgga ctcccctcct gagctctctg



 



agtgcaacca gcaacaattc caccgtggct tgcattgata



 



gaaatgggct gcaaagctgt cccatcaagg aagacagctt



 



cttgcagcga tacagctcag accccacagg cgccttgact



 



gaggacagca tagacgacac cttcctccca gtgcctgaat



 



acataaacca gtccgttccc aaaaggcccg ctggctctgt



 



gcagaatcct gtctatcaca atcagcctct gaaccccgcg



 



cccagcagag acccacacta ccaggacccc cacagcactg



 



cagtgggcaa ccccgagtat ctcaacactg tccagcccac



 



ctgtgtcaac agcacattcg acagccctgc ccactgggcc



 



cagaaaggca gccaccaaat tagcctggac aaccctgact



 



accagcagga cttctttccc aaggaagcca agccaaatgg



 



catctttaag ggctccacag ctgaaaatgc agaataccta



 



agggtcgcgc cacaaagcag tgaatttatt ggagcatgac



 



cacggaggat agtatgagcc ctaaaaatcc agactctttc



 



gatacccagg accaagccac agcaggtcct ccatcccaac



 



agccatgccc gcattagctc ttagacccac agactggttt



 



tgcaacgttt acaccgactagccaggaagt acttccacct



 



cgggcacatt ttgggaagtt gcattccttt



 



gtcttcaaactgtgaagcat ttacagaaac gcatccagca



 



agaatattgt ccctttgagc agaaatttat ctttcaaaga



 



ggtatatttg aaaaaaaaaa aaagtatatg tgaggatttt



 



tattgattgg ggatcttgga gtttttcatt gtcgctattg



 



atttttactt caatgggctc ttccaacaag gaagaagctt



 



gctggtagca cttgctaccc tgagttcatc caggcccaac



 



tgtgagcaag gagcacaagc cacaagtctt ccagaggatg



 



cttgattcca gtggttctgc ttcaaggctt ccactgcaaa



 



acactaaaga tccaagaagg ccttcatggc cccagcaggc



 



cggatcggta ctgtatcaag tcatggcagg tacagtagga



 



taagccactc tgtcccttcc tgggcaaaga agaaacggag



 



gggatggaat tcttccttag acttactttt gtaaaaatgt



 



ccccacggta cttactcccc actgatggac cagtggtttc



 



cagtcatgag cgttagactg acttgtttgt cttccattcc



 



attgttttga aactcagtat gctgcccctg tcttgctgtc



 



atgaaatcag caagagagga tgacacatca aataataact



 



cggattccag cccacattgg attcatcagc atttggacca



 



atagcccaca gctgagaatg tggaatacct aaggatagca



 



ccgcttttgt tctcgcaaaa acgtatctcc taatttgagg



 



ctcagatgaa atgcatcagg tcctttgggg catagatcag



 



aagactacaa aaatgaagct gctctgaaat ctcctttagc



 



catcacccca accccccaaa attagtttgt gttacttatg



 



gaagatagtt ttctcctttt acttcacttc aaaagctttt



 



tactcaaaga gtatatgttc cctccaggtc agctgccccc



 



aaaccccctc cttacgcttt gtcacacaaa aagtgtctct



 



gccttgagtc atctattcaa gcacttacag ctctggccac



 



aacagggcat tttacaggtg cgaatgacag tagcattatg



 



agtagtgtgg aattcaggta gtaaatatga aactagggtt



 



tgaaattgat aatgctttca caacatttgc agatgtttta



 



gaaggaaaaa agttccttcc taaaataatt tctctacaat



 



tggaagattg gaagattcag ctagttagga gcccaccttt



 



tttcctaatc tgtgtgtgcc ctgtaacctg actggttaac



 



agcagtcctt tgtaaacagt gttttaaact ctcctagtca



 



atatccaccc catccaattt atcaaggaag aaatggttca



 



gaaaatattt tcagcctaca gttatgttca gtcacacaca



 



catacaaaat gttccttttg cttttaaagt aatttttgac



 



tcccagatca gtcagagccc ctacagcatt gttaagaaag



 



tatttgattt ttgtctcaat gaaaataaaa ctatattcat



 



ttccactcta aaaaaaaaaa aaaaaa



 



SEQ ID NO: 3



FGF19 (NM_002010.2)



actctgcgcg ccggcggggg ctgcgcagga ggagcgctcc



 



gcccggctac aacgctccgc gagccggcgc ggcaacacct



 



gttcgcggca gcctgggcgg cacgcgagct cccggacgcg



 



gctctcctcg ctcgccgctc gccacccgtt ctaagccaat



 



ggacatctgc cgagcctctg gagaatcctg gatactagct



 



ttggacgcct aaagtttctt cttctttttg ttttattatt



 



attatcattt tttggagggg ggaccgggag gggagatttg



 



tcgccgccac caacgtgaga tttttttttc cccttgaagg



 



attcatgctg atgtctgcag agtcggttag agagtaaaaa



 



cagcgcatgc cttcctggag tcaggatccg taaattctga



 



cgtagcccgt gcatcttaaa aatccctata ataacgccta



 



ggcatttaag ttgctatggt cattctgatc tcaaaccaaa



 



tggagaaact acggattttt tttccttatt acggtcggat



 



gggatgaaga ccttcctgcc tgctaagagc tggggatcta



 



tctatagaga tacatagata tgtttatcaa tatgtcagtg



 



tgtgagtata aagtggtggt ttcttagact atcagtggtt



 



tgaccttgaa cctgtgccag tgaaacagca gattactttt



 



atttatgcat ttaatggatt gaagaaaaga accttttttt



 



tctctctctc tctgcaactg cagtaaggga ggggagttgg



 



atatacctcg cctaatatct cctgggttga caccatcatt



 



attgtttatt cttgtgctcc aaaagccgag tcctctgatg



 



gctcccttag gtgaagttgg gaactatttc ggtgtgcagg



 



atgcggtacc gtttgggaat gtgcccgtgt tgccggtgga



 



cagcccggtt ttgttaagtg accacctggg tcagtccgaa



 



gcaggggggc tccccagggg acccgcagtc acggacttgg



 



atcatttaaa ggggattctc aggcggaggc agctatactg



 



caggactgga tttcacttag aaatcttccc caatggtact



 



atccagggaa ccaggaaaga ccacagccga tttggcattc



 



tggaatttat cagtatagca gtgggcctgg tcagcattcg



 



aggcgtggac agtggactct acctcgggat gaatgagaag



 



ggggagctgt atggatcaga aaaactaacc caagagtgtg



 



tattcagaga acagttcgaa gaaaactggt ataatacgta



 



ctcatcaaac ctatataagc acgtggacac tggaaggcga



 



tactatgttg cattaaataa agatgggacc ccgagagaag



 



ggactaggac taaacggcac cagaaattca cacatttttt



 



acctagacca gtggaccccg acaaagtacc tgaactgtat



 



aaggatattc taagccaaag ttgacaaaga cagtttcttc



 



acttgagccc ttaaaaaagt aaccactata aaggtttcac



 



gcggtgggtt cttattgatt cgctgtgtca tcacatcagc



 



tccactgttg ccaaactttg tcgcatgcat aatgtatgat



 



ggaggcttgg atgggaatat gctgattttg ttctgcactt



 



aaaggcttct cctcctggag ggctgcctag ggccacttgc



 



ttgatttatc atgagagaag aggagagaga gagagactga



 



gcgctaggag tgtgtgtatg tgtgtgtgtg tgtgtgtgtg



 



tgtgtgtgta tgtgtgtagc gggagatgtg ggcggagcga



 



gagcaaaagg actgcggcct gatgcatgct ggaaaaagac



 



acgcttttca tttctgatca gttgtacttc atcctatatc



 



agcacagctg ccatacttcg acttatcagg attctggctg



 



gtggcctgcg cgagggtgca gtcttactta aaagactttc



 



agttaattct cactggtatc atcgcagtga acttaaagca



 



aagacctctt agtaaaaaat aaaaaaaaat aaaaaataaa



 



aataaaaaaa gttaaattta tttatagaaa ttccaaaggc



 



aacattttat ttattttata tatttattta ttatatagag



 



tttattttta atgaaacatg tacaggccag ataggcattt



 



tggaagcttt aggctctgta agcattaaat ggcaaagtcc



 



gctatgaacc tgtggtaaat tcatgcaagt agatataatg



 



gtgcatggat ataagaaatt ctaatgaccc taatgtacta



 



aaggcgacaa tctcttttgt gcccatatta ttgtaaactt



 



atgcacatcg ctcatgacac tgagtattca ctcttcagac



 



tgcttgtttc atagcttatc ccagaggatt aaagataaac



 



tgggtctcaa actttgattc tgtgtctgca atatttcctc



 



tctcataagt gactccacta ttgtaacttc atggttggaa



 



aatatgaggg ttgatatatg tcttacttgt ttaaatctgt



 



cgcagaatat accaaagcta aataataact atgctttcat



 



tttagccgat ctccagaatg acagtattaa catcaaacat



 



tgtattgatt tagaattctc aaaaaaggaa aaaaaagtac



 



atagcacaga ctattttttt taaagacgta agaatcagat



 



taacaggatc atacttgtaa actttttttg gttcacttgg



 



ctatcaaata tgaaattata gaagtatcat aggggtcatt



 



gtaacatctt ttagagaaaa tggctatcag tgtgaactgt



 



cataattacg tggtaatag acccttagta aaacttgcaa



 



aatgaaacta ataaatcgtt atcaataatg acaatgaggg



 



ggaaagtatt atacttgttg actgtgtttt gttttttaaa



 



atggtctcca caagcgctca atttttttag aggggatatt



 



actatataga atatctttta caaggctttt ataacatttt



 



atgctgaaaa gcataagaat acgtatttct ttagtagcaa



 



taattttgga acttgccctt gggcaagcga gactatttct



 



tactatatac taaggagaaa agagccaaat tcttaaagca



 



atatttaaga aaaaaggaat ttataacaaa ttctcatcta



 



catatgacac tttctagcca gttgtgttga gaagtgcaaa



 



gtgacggttt aaacatgtgt tgggatttat tgaactaatt



 



ttaaaattta ctattcaaac tttattttgc tctgatgcac



 



attctctatg aaaaataaaa gtgtgtcact ggtgagtgac



 



agctgttatg agctagaagc gcatgactta ttgtgacgat



 



gtcttgcctt tctgtggtcc aagttggagt acatggcaat



 



gccctcctgc tgatgtgcat taaggaaaat ctaagtctaa



 



tatttggaat taagatatat tttaggggga ggggacagaa



 



gcaatgtaaa atagttgatt tatgataaag ctcagaatgt



 



cctcttcatt tattttcttg ttttattttc ctttctaaac



 



agaaactgca tttaattcca aaaagtagta ttcttattta



 



ttatttaacc ctttgctgct gctaaaatgt gcacatattc



 



aggctttagt ttttccaaaa ggcatttttt ttttggctga



 



aaaatattaa acatttgacc acagggaaga atcaagtttc



 



taggatgtca taggtatact atgtagcact gaaaaaattg



 



attttaggtg acagccaaaa gtagtcttaa agtagcatga



 



gaccttagat aatcgaccta aaagaaagaa aattgtgaaa



 



aagacaaaaa tcttcatgca ttcctataaa acgctacttt



 



aaggtctact tttggagtta attttgtttg gtactttttt



 



tttttttaag acgagcaaat tgttatatgc ttttggcaat



 



tgatacaata aactgtaatg gtctgtaaat aaataaatat



 



tgactcatgc gatttatgta aatagtggaa ctgggagagt



 



ggatggctca gggtttcggt gtgggcattg tctcttgggc



 



agtagagtga gtcatcccca gctcatgggt ttgcatccag



 



ttcttgtctt aagagaccca aagcccagtg aatggcagcc



 



ctgagccact gtggaatggg ggttctggtt tcacaaacag



 



atgcttagat agccaaacca ctgtcttgtt ggtgccaaca



 



cttgcactgt ggtcaaagac ttaccgagca tgggctgaac



 



aaccttccca tctgtcatgt gaatgtcccc aagcagtggt



 



gaaggacatg ctaggtcagt gttggggaac ctgccctgcc



 



aggtcctgtt ttgtagataa acaaatggct gccttctggt



 



gtttttattc tatttcatct cattaacact acaaccttgt



 



gttatttact tgataatctg taattgtatg taaatacata



 



caggattatg taatttgtgt aaatacataa ttacagagtt



 



ttgaaaactg aaaaaaaaaa aaaaa



 



SEQ ID NO: 4



GREBI (NM_033090.2)



gaaagaatca aagcgcacat cttgtacttt gatgcccata



 



ggaagggctc tcctctggcc cctctggctt tgtttggagc



 



agaaaacaac aaactgcagc tgaggacagc caccctttct



 



tcgtctctgc tgagcgaagg ctacacggcc cttcctcctt



 



gcagctgttt caccttctac cttgcgtgga gccaggcttt



 



tgcaccgaat ctgagatgcc attttaaaca gaagactcca



 



tcctcttgaa gatgggaaat tcttacgctg gacagctgaa



 



gacgacacgc tttgaagagg tcttgcacaa ttccatcgag



 



gcatccctgc ggtccaacaa cctggtgccc aggcccatct



 



tttcccagct gtacctggaa gctgagcagc agcttgccgc



 



tctagaaggt ggtagccgag tggacaatga ggaagaggaa



 



gaagagggag aaggagggct ggaaacaaat ggccccccaa



 



accctttcca gctgcaccct ctgcctgaag gatgctgtac



 



cacagacggg ttttgccagg ccgggaagga cctgcgcctt



 



gtctccattt ccaacgagcc catggatgtc cctgcgggct



 



ttctcctcgt gggggtcaag tcccccagcc tgccggacca



 



tctcctggtg tgcgccgttg acaagaggtt cttgccagat



 



gacaatggcc acaatgctct tcttggtttc tctgggaatt



 



gtgttggctg tggaaagaaa ggcttctgtt acttcacgga



 



attctccaat catataaatc tgaaactgac cactcaaccc



 



aagaagcaga aacacttgaa gtattacctg gtccgtaatg



 



cacaagggac tctaaccaaa ggacctttaa tctgttggaa 



 



aggctcagag tttagaagcc ggcagatccc cgccagtact



 



tgttccagtt ccctcttccc agccctggag agcacggct



 



ccttccccag cgagcccgtt cctgggacga accccagcat



 



cctgatggga gctcagcagg caggaccagc ttctgatcac



 



ccctcactaa acgcagcaat gggtccggct gttttcaacg



 



gcaaagattc cccgaagtgc caacaactgg caaagaataa



 



cctgttggcc ctgccgcgac catcggcttt aggtatcttg



 



tcaaactccg ggccccccaa aaaacgccac aaagggtggt



 



ctccagaatc tccatcagct ccagatggtg gctgccccca



 



aggtggtggg aacagagcta agtatgagag cgcaggcatg



 



tcctgcgtgc cgcaggttgg cttggtggga ccagcttcag



 



tcacctttcc agtggtggcc tctggagaac cagtgtctgt



 



tcctgacaac ttgctgaaaa tatgcaaggc caagccagtg



 



atatttaaag gccatgggaa cttcccttac ctctgtggga



 



acctgaatga cgtcgtggtc agccccctct tgtacacgtg



 



ctaccagaat tcccagtctg tctcacgggc atacgagcag



 



tacggcgcct ctgccatcca gcccatctcc gaggagatgc



 



agctcctgct taccgtctac tacctggtcc agctggcaca



 



tcaaatacga aatccggacg tataaaccag acaattcata



 



aaagagaaaa taccagaagg aaacaaatat tgaaaagtat



 



tcagtctcac tcatcatcaa agacatgcaa atcacaaatc



 



aagtcatctt tttctgaatt aataacccaa atgatggtac



 



ccagtggtgc ttaggtgcgg taaaaccagc gcttgtccga



 



tgcaccgttc gcgtggtaaa ctgacgcatt caggctcttg



 



ggaagcaatc tgatgatatg tagtagctgg ttctgtaaat



 



ccacctttga gaatttaggc gaaggaagta acgttctata



 



tgtcaagatg tgcattgcag agggatttat aaaggtgaat



 



atttggaaga aataagagaa tccacaatag agaccttgct



 



aagtaaacgg tggtgctcac gtatgatggg acattatgga



 



cacactaaca gcactcttta tgttggctga aaatggcact



 



gaaactgatg atagggtcat ggttaaggaa agaatgcaag



 



acccaaagtt tatactgaca atcattgcag ctatttgtaa



 



ggacagtttt aatactaatt ccagcaatac atgtttttat



 



tccctgtcct ggagtaggag aaagcctata ttcccaggct



 



gaatgttcta cacatttacc actgtatatg cacataggga



 



cagtgtaacc tgtctatacc accgtagttc cagtcctaac



 



tttctgaatt ctgtttaaag accttct



 



SEQ ID NO: 5



LZTS1 (NM_021020.2)



tgagggcttt gctatgacct cagtcccctc acggagccac



 



gactgcccct tgctgccaca gcctttccaa gaccctgccc



 



ggccctgccc catcctcagc cccgagtcac catgggcagc



 



gtcagtagcc tcatctccgg ccacagcttc cacagcaagc



 



actgccgggc ttcgcagtac aagctgcgca agtcctccca



 



cctcaagaag ctcaaccggt attccgacgg gctgctgagg



 



tttggcttct cccaggactc cggtcacggc aagtccagct



 



ccaaaatggg caagagcgaa gacttcttct acatcaaggt



 



cagccagaaa gcccggggct cccatcaccc agattacacg



 



gcactgtcca gcggggattt agggggccag gctggggtgg



 



actttgaccc gtccacaccc cccaagctca tgcccttctc



 



caatcagcta gaaatgggct ccgagaaggg tgcagtgagg



 



cccacagcct tcaagcctgt gctgccacgg tcaggagcca



 



tcctgcactc ctccccggag agtgccagcc accagctgca



 



ccccgcccct ccagacaagc ccaaggagca ggagctgaag



 



cctggcctgt gctctggggc gctgtcagac tccggccgga



 



actccatgtc cagcctgccc acacacagca ccagcagcag



 



ctaccagctg gacccgctgg tcacacccgt gggacccaca



 



agccgttttg ggggctccgc ccacaacatc acccagggca



 



tcgtcctcca ggacagcaac atgatgagcc tgaaggctct



 



gtccttctcc gacggaggta gcaagctggg ccactcgaac



 



aaggcagaca agggcccctc gtgtgtccgc tcccccatct



 



ccacggacga gtgcagcatc caggagctgg agcagaagct



 



gttggagagg gagggcgccc tccagaagct gcagcgcagc



 



tttgaggaga aggagcttgc ctccagcctg gcctacgagg



 



agcggccgcg gcgctgcagg gacgagctgg agggcccgga



 



gcccaaaggc ggcaacaagc tcaagcaggc ctcgcagaag



 



agccagcgcg cgcagcaggt cctgcacctg caggtactgc



 



agcttcagca ggagaagcgg cagctccggc aggagctcga



 



gagcctcatg aaggagcagg acctgctgga gaccaagctc



 



aggtcctacg agagggagaa gaccagcttc ggccccgcgc



 



tggaggagac ccagtgggag gtgtgccaga agtcaggcga



 



gatctccctc ctgaagcagc agctgaagga gtcccagacg



 



gaggtgaacg ccaaggctag cgagatcctg ggtctcaagg



 



cacagctgaa ggacacgcgg ggcaagctgg agggcctgga



 



gctgaggacc caggacctgg agggcgccct gcgcaccaag



 



ggcctggagc tggaggtctg tgagaatgag ctgcagcgca



 



agaagaacga ggcggagctg ctgcgggaga aggtgaacct



 



gctggagcag gagctgcagg agctgcgggc ccaggccgcc



 



ctggcccgcg acatggggcc gcccaccttc cccgaggacg



 



tccctgccct gcagcggga ctggagcggc tgcgggccga



 



gctgcgggag gagcggcaag gccatgacca gatgtcctcg



 



ggcttccagc atgagcggct cgtgtggaag gaggagaagg



 



agaaggtgat tcagtaccag aaacagctgc agcagagcta



 



cgtggccatg taccagcgga accagcgcct ggagaaggcc



 



ctgcagcagc tggcacgtgg ggacagcgcc ggggagccct



 



tggaggttga cctggaaggg gctgacatcc cctacgagga



 



catcatagcc actgagatct gaggggctgc ctgggaaggc



 



gagtctgggg acctggcact gggaggcagg gctctcccgt



 



gcatcccccc tgctcagcaa ttcagacccc tttgagagac



 



gccactccct gggacacaga cccaggaccc ccgaggggag



 



ggcaggatgg cctttccttc cctctctgat gtcccagtgc



 



tcaccagccc tgcagcccac cagacgtcag gccctgactc



 



ctctggcttt cccaggagat gggtccaggg gtctgtctgc



 



tttggttaag ggctccctaa actttggcct ttgttcgaaa



 



tagatatcct ctccccctcc tccagggaag gtggccacag



 



caagtacagc ggctcccctc tgcttctcat cccaacctct



 



ttttcctcct ggacacattg gaatgccttg gaaatagaaa



 



gaagccatat atgaccagaa gccttggaac cagccccatc



 



agaacctgag ctattttcct ctggccgcag aggtgtagg



 



gtggaatgag ccgcggggaa gctggctttg aaacctcagg



 



gctgtcccag ccccggcaag ccacaggaag gaggggagag



 



acaggcagcc cagcagtgtg gagaccctgc cacagccaga



 



ggagggcaga gggagaatcc aagggttgag agccagtggc



 



gggtgatggc cagcccctgg ggcccagccc ctgtttactg



 



gttcttgcaa atgggagctg agcagcctct ggacagccag



 



tgacctttga cctcggtgac cactcttctt taagccatag



 



accctgaggc cctgggctgg gtgctgggaa gggagggttg



 



aaaccaccgt gaaccagagg gtgtggcttt ccaggcaccc



 



tcagggagcc tccccatctg tccagctggg gccagaggct



 



gggagtccct acctgcttca cgttggccgg cggctactct



 



ggaatgtttt tccctcccca gaatcaagct tttgcttgat



 



ccagaagagc ccatatcact aagatggcat atatgtgatc



 



tgggcatttt cctcctctgc ctacagccag gtttagcggc



 



aaacctttcc cccttagcac cttcagggct gagttctggg



 



tttctagagg tcaggacggc tcctcagagc gccaggaagc



 



cagagcccca agcaggacga aaaagaggca tacacacagc



 



agtgtgaata gcctggccac cagccatcct ccctccacct



 



caagaccccc atttgtccca gactaaagga tccagagagc



 



agctcccttt ctcaggagct tgggcagtgc cccagggagt



 



ccagggtttc tctgcagatg tgcggagcgg gaggcggtgg



 



tagagagaga taaaaggtgg agtttctctg ttgtttggtt



 



cagggatttt atttttaatt ttatgagaca gggtcttgct



 



ctgtccccca ggctggagtg cagtggcatg atcatagctc



 



actgcagcct catactcctg ggctcaagca atcctcctgc



 



ctcagccttc caactagctg ggactacagg tgcgcgccac



 



cgtgcctggc taacttttca ttttttttgt agggacgggg



 



tctcgttttg ttgccaaagc tggtctcaaa cttgtggcct



 



caagcaatcc acctgccttg gcctcccaaa gtgctgagat



 



tgcagatgtg agccaccgtg cctggccaga tttttctttt



 



attcttcttt ctttttcttt tttgctttct tgtcttttca



 



gaagcaagcc agacctagca ggctgttcca tgttctattt



 



ttgactgtag ccacagctgc tgttctcagg acagcatccc



 



ttcccacatg cctgcgcctg ctgcctgctg agatgaggag



 



gggagcgtct gggaacttgc gagtccaagg ccagtcccca



 



tttctgcctc gctcaccgct ggcccttaga gaccccgagg



 



taggggtggg gagatgcttc tctccttgcc ccccgccctc



 



atgggtccta gcccttccct gagtgcgggc tgaggccaga



 



gtcacctttt ctgtggctgg ctctaccttc ctgtccctga



 



ggttaaacgg tgcccatcct gccatcctca aacgacagag



 



gagcttttct ggaatttcaa accattgctc ttagtcccaa



 



gctaggctta aacctggaat ctacaagcca aaagtccctc



 



cctgcctgag ggcagtaccc tccattgggc acagtccaga



 



cccaagtcaa agatgcccca ttccttgcgc ctcagccctc



 



agttccttca tttccaccag gccgtgcctt gtttgagttt



 



ttcctcccag tgagactgcc ccacggagac agaggaaagg



 



gctggctccc cctccccagg ctggagaccc ccccccaact



 



ccaggaaaga gcagtcagag tccagtgctc tgcctcagac



 



gttgcctgag aagaagtggc tgccacaccc aggggaaggc



 



cctgaggcgg aggctgtgct ccgccatggt gtcccggtac



 



cttccataca cagaggagtg cagccttctc catatctcc



 



tggccctgtc ccaggccggc ccagatgtgt cccccccagg



 



ccttgtccta cgtccaaggt ggcagatgtc ttccctgggc



 



tgccaccagc ccccgcccca gagtggccca ccgtggcact



 



agaatgcaag tatcctgcga ccttgcaacc tcaccttcct



 



gtgggtgttc tttcctgccc tgtccaaaag cgccctcact



 



attcttggac catgccagat tctgcctctc tggaaagagg



 



ctctggacag cagaagcctc caagcacaga gcctggcccc



 



aggccccaga cagggtgggc ttcctgccct tccctctggg



 



cacgcctgct ggccgaccca ctgacccact cggatggacc



 



aacctgctct gtccccaaag gacgcctgca ggagagagca



 



gcactccgca tcacctcacc aaggatcgga ctctgcccct



 



ggacctggga acgactggac tgtcacgggg ttccctccta



 



gctctcccag tgaactcctg ccaggcacac acagccccta



 



tagcactgag ctcacatggg actgggatat gggggcatct



 



cttccccaga gaggcactca gtgagcctcc tgtgcctggc



 



cccagcctgg gccatctctt aggtgagaca gttgcccgaa



 



actaagccag gcctggctgg aggagcagca gcttggggag



 



agggatttcc ctgcagacct caagccatca tgcggtgggt



 



gctgccatga cagaggctgc acccctgggc cagcggggct



 



gctcacccac ctcttgtgca aggtggcctt tgtgctgcgc



 



ctgcaggcag agctggagcc cccagcagag gcaggctggg



 



acggaccagc atctggaaga tgtacatagt tatttttctc



 



tttgtggttt cttgtttggt ttggtttgct tttgacagct



 



tcattttatt tttgacgtca ctttttggcc atgtaaacta



 



tttgtggcaa ttttatgttt ttatttatga ataaagaatg



 



ccatttctca cgccctcta



 



SEQ ID NO: 6



BRAF (NM_004333.4)



cgcctccctt ccccctcccc gcccgacagc ggccgctcgg



 



gccccggctc tcggttataa gatggcggcg ctgagcggtg



 



gcggtggtgg cggcgcggag ccgggccagg ctctgttcaa



 



cggggacatg gagcccgagg ccggcgccgg cgccggcgcc



 



gcggcctctt cggctgcgga ccctgccatt ccggaggagg



 



tgtggaatat caaacaaatg attaagttga cacaggaaca



 



tatagaggcc ctattggaca aatttggtgg ggagcataat



 



ccaccatcaa tatatctgga ggcctatgaa gaatacacca



 



gcaagctaga tgcactccaa caaagagaac aacagttatt



 



ggaatctctg gggaacggaa ctgatttttc tgtttctagc



 



tctgcatcaa tggataccgt tacatcttct tcctatcta



 



gcctttcagt gctaccttca tctctttcag tttttcaaaa



 



tcccacagat gtggcacgga gcaaccccaa gtcaccacaa



 



aaacctatcg ttagagtctt cctgcccaac aaacagagga



 



cagtggtacc tgcaaggtgt ggagttacag tccgagacag



 



tctaaagaaa gcactgatga tgagaggtct aatcccagag



 



tgctgtgctg tttacagaat tcaggatgga gagaagaaac



 



caattggttg ggacactgat atttcctggc ttactggaga



 



agaattgcat gtggaagtgt tggagaatgt tccacttaca



 



acacacaact ttgtacgaaa aacgtttttc accttagcat



 



tttgtgactt ttgtcgaaag ctgcttttcc agggtttccg



 



ctgtcaaaca tgtggttata aatttcacca gcgttgtagt



 



acagaagttc cactgatgtg tgttaattat gaccaacttg



 



atttgctgtt tgtctccaag ttctttgaac accacccaa



 



accacaggaa gaggcgtcct tagcagagac tgccctaaca



 



tctggatcat ccccttccgc acccgcctcg gactctattg



 



ggccccaaat tctcaccagt ccgtctcctt caaaatccat



 



tccaattcca cagcccttcc gaccagcaga tgaagatcat



 



cgaaatcaat ttgggcaacg agaccgatcc tcatcagctc



 



ccaatgtgca tataaacaca atagaacctg tcaatattga



 



tgacttgatt agagaccaag gatttcgtgg tgatggagga



 



tcaaccacag gtttgtctgc taccccccct gcctcattac



 



ctggctcact aactaacgtg aaagccttac agaaatctcc



 



aggacctcag cgagaaagga agtcatcttc atcctcagaa



 



gacaggaatc gaatgaaaac acttggtaga cgggactcga



 



gtgatgattg ggagattcct gatgggcaga ttacagtgg



 



acaaagaatt ggatctggat catttggaac agtctacaag



 



ggaaagtggc atggtgatgt ggcagtgaaa atgttgaatg



 



tgacagcacc tacacctcag cagttacaag ccttcaaaaa



 



tgaagtagga gtactcagga aaacacgaca tgtgaatatc



 



ctactcttca tgggctattc cacaaagcca caactggcta



 



ttgttaccca gtggtgtgag ggctccagct tgtatcacca



 



tctccatatc attgagacca aatttgagat gatcaaactt



 



atagatattg cacgacagac tgcacagggc atggattact



 



tacacgccaa gtcaatcatc cacagagacc tcaagagtaa



 



taatatattt cttcatgaag acctcacagt aaaaataggt



 



gattttggtc tagctacagt gaaatctcga tggagtgggt



 



cccatcagtt tgaacagttg tctggatcca ttttgtggat



 



ggcaccagaa gtcatcagaa tgcaagataa aaatccatac



 



agctttcagt cagatgtata tgcatttgga attgttctgt



 



atgaattgat gactggacag ttaccttatt caaacatcaa



 



caacagggac cagataattt ttatggtggg acgaggatac



 



ctgtctccag atctcagtaa ggtacggagt aactgtccaa



 



aagccatgaa gagattaatg gcagagtgcc tcaaaaagaa



 



aagagatgag agaccactct ttccccaaat tctcgcctct



 



attgagctgc tggcccgctc attgccaaaa attcaccgca



 



gtgcatcaga accctccttg aatcgggctg gtttccaaac



 



agaggatttt agtctatatg cttgtgcttc tccaaaaaca



 



cccatccagg cagggggata tggtgcgttt cctgtccact



 



gaaacaaatg agtgagagag ttcaggagag tagcaacaaa



 



aggaaaataa atgaacatat gtttgcttat atgttaaatt



 



gaataaaata ctctcttttt ttttaaggtg aaccaaagaa



 



cacttgtgtg gttaaagact agatataatt tttccccaaa



 



ctaaaattta tacttaacat tggattttta acatccaagg



 



gttaaaatac atagacattg ctaaaaattg gcagagcctc



 



ttctagaggc tttactttct gttccgggtt tgtatcattc



 



acttggttat tttaagtagt aaacttcagt ttctcatgca



 



acttttgttg ccagctatca catgtccact agggactcca



 



gaagaagacc ctacctatgc ctgtgtttgc aggtgagaag



 



ttggcagtcg gttagcctgg gttagataag gcaaactgaa



 



cagatctaat ttaggaagtc agtagaattt aataattcta



 



ttattattct taataatttt tctataacta tttcttttta



 



taacaatttg gaaaatgtgg atgtctttta tttccttgaa



 



gcaataaact aagtttcttt ttataaaaa



 



SEQ ID NO: 7



FRS2 (NM_006654.3)



aaaacccttc cctcccccgc tcccccggaa gtgcttttcc



 



aagattcggg ccggagagag gccttgtagg cacagcggct



 



gagactcgat ctgctccaag taggggctcc agcgcgggtc



 



ggagtctggg ggttcgcgcc cgccgacccg cgccctgctc



 



cctctcagca cctgggcgga cgaaatgacc attaagaagt



 



agatgcccag atgcaaaagt gatgaaacag tccatttgtc



 



ataaagtaag atgcagctgt ggcatgtcaa ccagcttgga



 



acaaaattgt atctgttttt ctcagaagag aattccacaa



 



ggagattttc ttctttctac catcatcaag atcaagcagg



 



caagtttact tgctgtcatc ttctgcaagg ttaaatcagc



 



aaacaaagaa aacatggtat tttgaaatat gattaaactc



 



ctgatgctgc agcagaggct aagaatatta atggccagat



 



ctagtgcaca catggtcttc tgaagaagcc atgggtagct



 



gttgtagctg tccagataaa gacactgtcc cagataacca



 



tcggaacaag tttaaggtca ttaatgtgga tgatgatggg



 



aatgagttag gttctggcat aatggaactt acagacacag



 



aactgatttt atacacccgc aaacgtgact cagtaaaatg



 



gcactacctc tgcctgcgac gctatggcta tgactcgaat



 



ctcttttctt ttgaaagtgg tcgaaggtgt caaactggac



 



aaggaatctt tgcctttaag tgtgcccgtg cagaagaatt



 



atttaacatg ttgcaagaga ttatgcaaaa taatagtata



 



aatgtggtgg aagagccagt tgtagaaaga aataatcatc



 



agacagaatt ggaagtccct agaacacctc gaacacctac



 



aactccagga tttgctgctc agaacttacc taatggatat



 



ccccgatatc cctcatttgg agatgcttca tcccatccgt



 



caagcagaca tccttctgtg ggaagtgctc gcctgccttc



 



agtaggggaa gaatctacac atcctttgct tgtggctgag



 



gaacaagtac atacctatgt caacactaca ggtgtgcaag



 



aagagcggaa aaaccgcaca agtgtgcatg ttccattgga



 



ggcgagggtt tctaacgctg aaagcagcac accaaaagaa



 



gaaccaagta gtattgagga cagggatcct cagattcttc



 



ttgaacctga aggagtcaaa tttgttttag ggccaacccc



 



tgttcaaaag cagttaatgg aaaaagagaa actggagcaa



 



cttggaagag atcaagttag tggaagtgga gcaaataaca



 



cagaatggga cactggctat gacagtgatg aacgaagaga



 



tgcaccctct gttaacaaac tggtgtatga aaatataaat



 



gggctatcta tccctagtgc ctcaggggtc aggagaggtc



 



gtctgacatc caccagtacc tcagataccc agaatatcaa



 



caactcagct cagagaagaa ctgcattatt aaactatgaa



 



aatctaccat ctttgcctcc tgtttgggaa gcccgcaagc



 



taagtaggga tgaagatgac aatttaggac caaagacccc



 



atctctaaat ggctaccata ataatctaga tccaatgcat



 



aactatgtaa atacagagaa tgtaacagtg ccagcaagtg



 



ctcacaaaat agaatattca aggcgtcggg actgtacacc



 



aacagtcttt aactttgata tcagacgccc aagtttagaa



 



cacaggcagc ttaattacat acaggttgac ttggaaggtg



 



gcagtgactc tgacaaccct cagactccaa aaacgcctac



 



aactcccctt ccacaaaccc ctaccaggcg cacagagctg



 



tatgccgtga tagacatcga gagaactgct gctatgtcaa



 



atttgcagaa agcactgcca cgagatgatg gtacatctag



 



gaaaactaga cacaatagta ctgatctgcc catgtgagcc



 



tggaaagcat tgtgttgttt gcacctttgt gaagttttta



 



aaaatgaaga tgcaagtgct tcattttcat ttctaaacac



 



taactccttt tatagactga taaaattttt ttctgaatat



 



ttcatgtgca tctttaacta aagggaatta atgtagagca



 



ggtactcctt aaagaacact aatttcatta tatactactc



 



gttgtacagc agcattcccg ttttcacagt gcctatttaa



 



aatgagagtt gaagtaaatg acatgctggt tgatttttat



 



caatattctg gacttaacgc atacctttca tgtctaagtc



 



atggttggct tttaaaactt tttataaagc ctcttgacaa



 



tgtacattgc taacaggtaa ctataggctt tgaaagtaat



 



gctcgtagat tcagtgttca cagtatgtgg cctccagcat



 



gtaacatgag gaatccttta tttcattaat taatggcttt



 



ttgacttgag ccaaaacata tgtaaaggaa acagaagtac



 



cgcacctcct cttacaccag tcagctcctt tgccttcagt



 



gttactagaa agcggcctgt gtccatgagt gtgctttgct



 



gttggtgcac tgaaaggcag gaaggagaca agattttcta



 



tttactcatc tcatgatgtc atttgaaggg catgtccaga



 



tatcttaaaa ttataatagg ctcaagaatc agtctcaggt



 



cactttaccc aaaaacattt gaaaatctga accacaatct



 



cctgaaagtt tttctcctat agattgttga caacacattg



 



ttttctggag gcatttgtgc cattaggttt ccatttatct



 



tcagtttttt tctttggtgt ttgggatgtc ttattttgtt



 



gccttatgtc cttttcaatttaaaatgttt gagtttgtat



 



atagttttga aattggatta tgtgttcatt gttgtttagt



 



ttgcattttt gtcaaattat ggttttgaag gttcatttgg



 



aacttactgt tagtctgtaa cagggttgcc cttgtccagt



 



atttatttat aagctgttta cttttcaagt tgataaaaac



 



attctccaat tctaaatttg cttgtgtcca taggtgatct



 



ctttagcaaa ctgagaaaaa aaggaagcta cttttaacat



 



gcaaagttcc ctcaaggtgt accgtgttgt ctctgtgggc



 



actcttcccc agcactttag cagtaattcc cccagctaca



 



cgctgcagtt gtactctgcc cactctagtg ttcctcagct



 



ctgctgtcct tttacttgta gctggatctt tgattatcct



 



tcgatttcca tgaaatatta atattgttgc cagcatagca



 



ggtacagtgg aagtcttgt gcagtgagat tgtatcataa



 



tttaggattt aaaatgaatt aaagtttata



 



taaactgaagagtctccata tgtcaaactc ttggaaaatc



 



aaagatgttc caatttccta aacactagag aatacgagag



 



aaggtagagt ggaaaaggtt aggtaacctt gcaaaatatt



 



ttactatttt ctctaaatat gaggaagttt gagattatga



 



tctggatcta ccagatataa ctaaggttaa tttagcatga



 



aaaagtttta gtcatattgg catccaacct attcagtaac



 



cgaatcatag gacaatgatg gattaggaga acaatagagt



 



gggatcatta taaagaaaat aaattattaaaggtgtcttt



 



atcgttttag tgccattttt agtgtcttta ctataaatca



 



atatcagtgtattttatcat tctatgtgca tagcagaatt



 



ttcttttctc ccttttgttc ccctgtgaac ttggtgctta



 



ttaaagtgct cactgttctc ttaaaagaga gcagtggtat



 



aggtgtgcag tttccatgat gcaggttcca tttttaatat



 



attgttccac ttatcctttc ttctgagtaa attgctaatt



 



gtgccaaatt tatgtaatag tttttgtaat gtggaataag



 



aattatgatg gaaccattgc acattttttt ctgaaacagc



 



cagtcaaggc agaacattaa tctccaaatg caagggctga



 



tctatttatt cattttggag gttgggtact ttattctttc



 



tttccgtcat ccttttcatt gtttcccccg gattctaatt



 



agtttttatt ttttttagat aactccaata taatcattac



 



agtttatgct ttaaatacta tgtgctttaa aaaggaaaat



 



gggaccaatt tgtctgctaa gaatttgatt ttaggtacta



 



taagagtatt aggaaaatat atacaactgg tgttaatttc



 



tagatatttt ctagaaatca cttgtgttcc tatttaataa



 



aaggtaattt agaatactac ttgtcctttg cagtagttta



 



gtaatgggca ttaagctgtg tcctcgaagg atgtacctat



 



tactaggtgc attttagaat gaaatattga tattttatta



 



gcatataatt gtggccatat atctcagatt ttctgaggca



 



gatctaattt tagataattc tgttggtaga ccatgtgatc



 



cttctttttg gttttggaaa tataatcatt gttaatgttt



 



tccctccaaa tagaatactg ttttatccat acaaatcata



 



acagcatcta tcccatgcta gggttggaaa ctgatattgg



 



tattacttgt gttttttctt agtgtgtttt atttcccagt



 



ttcatcttct tctaaaaatg aaaatatggt gccttccctc



 



cctccaggaa gactggcaaa tatttccttt tatttactgc



 



tgctgtggag tgatgagata tgcactttac tctttaagat



 



tcagcaaaaa gcttttcact tctcagtata tccagaatac



 



atcatatctg ggacttagga aaatttgcca agcaatcttt



 



gtttttatag atactaatgt tgaccctctc cagcgttcaa



 



tgttataaat agaacaagtc aagctagtgt ttatctcctc



 



cccctcccca aaactgtggc acagcatat aaaatgtacc



 



tcaataatgt tctattaaaa atgggacagg ggccttatgt



 



tttcataatt tcccaacaat gtgccgccat atttttgcct



 



caaggtaaag gttttaacag atgaaaaagt acttcccaat



 



tcccccgtgc tattcctaac ctataatgcc caaatgtttt



 



gtgcaatgtg tagtgtgtgt gtataaatac atatattctt



 



gaaatagaca taccatcaga gacatcattc acaagtaact



 



gatgtattgg catctcattc atatttctga tgtgtgaggt



 



atatggtact aattaccttt tccttgatgt ttgccaaatt



 



tgaataaagg cattggtacg aaattacaga atgtaaagaa



 



aatgtttttg gcttgaaaaa ttaacatatt ttatgacgta



 



ccacagtata ctctgcccaa accagcaccc tatctatctt



 



tcctgttctt tacatccctg ttccccatcc ctacttcctc



 



atttttggta taacacagtt cttttgtagc atcattataa



 



ttgcagttct atggcaattg gacagttata gcatggaaac



 



agactggtat aagtagtaca gtagtcacca gtgtgccaca



 



tttgcattag taatgcaaaa tatacatttt ataaaggaca



 



aactttgtgt tatgttttat tttcattaca ttgtataata



 



ttgtaagact attgtatgtc ctaatttgca ttataaatgt



 



ttttttccta cgtaaaggca taaatatagc aactttgtat



 



aaaggtagct tattagattt ttaatttttt cttttataaa



 



aaattgtcca acagtgggac taccattgcc aaattgtata



 



tgaaatatga attttacccc catggttaat ttcttttata



 



aacattccat atttctctaa taaaaagaca taagtgatac



 



tgtactatgc atacattgta tcttaatgct gtttcagatc



 



agcattttaa attttggttt gcatttttaa tattggcaaa



 



acgtaaccac tgttaattaa aataaaacct tgttgtatat



 



gtaacaacat aattttccct ctatcccttc ccaccctttg



 



ttctctattt ctccctatca gtgccaactt catacatttt



 



gtagcatggc aataaaatat aacttttaca ctgaggccga



 



gtgtggcttt ttggaggaag tggggatggg acgattgccc



 



tctagttgtc ctttgcatat gactgttttt tgccatataa



 



gccatgtcat caggcatgaa aagttttctc atatatgatg



 



taaacttgct tttaaggaca agtgtgaatg tgctttttaa



 



gcttaatttt tgtcatgaca actaattttt tttatctttg



 



gagaagtcag agttctttac aatcaaacgt ttattaactg



 



gagtacttag aataagctag taattgaatt tagttcaagg



 



gctaagcaac acatttttaa atccttattt attgtagagt



 



attagtatac tgtcctacaa attatgtaaa atatggttta



 



atattagatg actttggatt ttgcaatgcc ttactgttgt



 



cattctagca taaatatcca taatgaggta ctcaagttga



 



tactggaagctgagctgatc atacactgac ctgaagcatt



 



catgaaaagc tgctttattg aataaagtct gattggagtt



 



cttttcatgc tcactttccc cttattgctg aaagtagatt



 



gcaataaaaccccaataaaa cgtttggtcg gataaaaaaa



 



aaaaaaaaaa aa






SEQ ID NO: 8 ANXA1 (NP_000691.1) mamvseflkq awfieneeqe yvqtvksskg gpgsayspyp tfnpssdvaa lhkaimvkgvdeatiidilt krnnaqrqqi kaaylqetgk pldetlkkal tghleevvla llktpaqfda delraamkgl gtdedtliei lasrtnkeir dinrvyreel krdlakdits dtsgdfrnal lslakgdrse dfgvnedlad sdaralyeag errkgtdvnv fntilttrsy pqlrrvfqky tkyskhdmnk vldlelkgdi ekcltaivkc atskpaffae klhqamkgvg trhkalirim vsrseidmnd ikafyqkmyg islcqailde tkgdyekilv alcggn
SEQ ID NO: 9 Hp2 (NP_001119574.1) msalgavial llwgqlfavd sgndvtdiad dgcpkppeia hgyvehsvry qcknyyklrt egdgvytlnn ekqwinkavg dklpeceavc gkpknpanpv qrilgghlda kgsfpwqakm vshhnittga tlineqwllt taknlflnhs enatakdiap tltlyvgkkq lveiekvvlh pnysqvdigl iklkqkvsvn ervmpiclps kdyaevgrvg yvsgwgrnan fkftdhlkyv mlpvadqdqc irhyegstvp ekktpkspvg vqpilnehtf cagmskyqed tcygdagsaf avhdleedtw yatgilsfdk scavaeygvy vkvtsiqdwv qktiaen
SEQ ID NO: 10 Zinc alpha2-glycoprotein (Chain B, Crystal structure of the complex formed between Mhc-Like Zinc Alpha2-glycoprotein and Prol) qdntrkiiik nfdipksvrp ndevtavlav qtelkecmvv ktylissipl qgafnykyt cicddnpktf ywdfytnrtv qiaavvdvir elgicpddaa vipiknnrfy tieilkve
SEQ ID NO: 11 (calprotectin) mltelekaln siidvyhkys likgnflhavy rddlkkllet ecpqyirkkg advwfkeldi ntdgavnfqe flilvikmgv aahkkshees hke
All references, publications, patent applications, issued patents, accession records and databases cited herein, including in any appendices, are incorporated by reference in their entirety for all purposes.

## Claims

1. A method for diagnosing the presence of lung cancer in a subject at risk of having lung cancer, the method comprising: a) contacting a saliva sample from the subject with a set of at least three reagents, wherein the set of at least three reagents specifically binds to at least three biomarkers in the saliva sample, wherein the three biomarkers are selected from the group consisting of BRAF, EGFR, FGF19, LZTS1, CCNI, GREB1, and FRS2; b) measuring the level of the at least three biomarkers in the saliva sample; c) detecting that the level of the at least three biomarkers is increased in the saliva sample relative to a control sample from a subject without lung cancer, thereby detecting the presence of lung cancer in the subject; and d) administering a lung cancer therapy to the subject, wherein the lung cancer therapy is selected from the group consisting of chemotherapy, hormonal therapy, radiotherapy, immunotherapy, and surgical removal of lung tissue.

2. The method of claim 1, wherein the assay detects at least three nucleic acids encoding at least three biomarkers, and wherein the at least three nucleic acids are detected by mass spectroscopy, PCR, microarray hybridization, thermal sequencing, capillary array sequencing, or solid phase sequencing.

3. The method of claim 1, wherein the assay that specifically detects at least three biomarkers in the saliva sample, detects at least four biomarkers selected from the group consisting of BRAF, EGFR, FGF19, LZTS1, CCNI, GREB1, and FRS2.

4. The method of claim 1, wherein the assay that specifically detects at least three biomarkers in the saliva sample, detects at least five biomarkers selected from the group consisting of BRAF, EGFR, FGF19, LZTS1, CCNI, GREB1, and FRS2.