Deciphering the genetic landscape of cancer – from genes to pathways
Authors: Neal G. Copeland, Nancy A. Jenkins
Journal: Trends in Genetics (2009)

Advances in genomic technologies have made it possible to screen the entire cancer genome for mutations, leading to a better understanding of the genetic landscape of cancer. Emerging results suggest that the cancer genome is composed of a few commonly mutated genes and many infrequently mutated genes. Although the number of mutated genes in any one tumor is limited, there is much heterogeneity in the genes mutated in two tumors of even the same class because of the large number of infrequently mutated genes. This could explain the wide variation in tumor behavior to chemotherapeutic intervention. Pathway analysis suggests this large collection of cancer genes functions in a few signaling pathways, providing a simplifying picture of cancer, and indicating the possibility of treating cancer using target-based therapeutics directed against the deregulated signaling pathways themselves rather than the individually mutated genes. Advances in genomic technologies have made it possible to screen the entire cancer genome for mutations, leading to a better understanding of the genetic landscape of cancer. Emerging results suggest that the cancer genome is composed of a few commonly mutated genes and many infrequently mutated genes. Although the number of mutated genes in any one tumor is limited, there is much heterogeneity in the genes mutated in two tumors of even the same class because of the large number of infrequently mutated genes. This could explain the wide variation in tumor behavior to chemotherapeutic intervention. Pathway analysis suggests this large collection of cancer genes functions in a few signaling pathways, providing a simplifying picture of cancer, and indicating the possibility of treating cancer using target-based therapeutics directed against the deregulated signaling pathways themselves rather than the individually mutated genes. Small molecule inhibitors, such as Imatinib (Gleevec) [1Schiffer C.A. BCR-ABL tyrosine kinase inhibitors for chronic myelogenous leukemia.N. Engl. J. Med. 2007; 357: 258-265Crossref PubMed Scopus (156) Google Scholar], that interfere with the activated breakpoint cluster region-Abelson (BCR-ABL) tyrosine kinase found in 95% of cases of chronic myelogenous leukemia, have had great clinical success without inducing the deleterious side effects often associated with conventional cancer therapeutics that target rapidly dividing cells. This has spurred a worldwide effort to identify all the genes that cause cancer, with the hope that some will lead to new drug targets. Although this effort is still in its infancy, the results suggest that it will be a daunting task. Recent studies suggest that number of cancer genes is large and most are infrequently mutated in cancer. There is also great variability in the genes mutated in different cancers of the same type as well as among different cancer types. Validating the large number of candidate cancer (CAN) genes identified by high-throughput genomic methods will, therefore, be difficult and require multiple methods, including the use of model organisms. Finally, because there are few frequently mutated cancer genes it will be challenging to identify new drug targets such as Imatinib. Fortunately, early studies suggest that the large number of infrequently mutated cancer genes function in a relatively small number of signaling pathways that cooperate to induce disease. Therefore, it might be possible to target the signaling pathways themselves rather that the individual mutant proteins such as BCR-ABL. In this article, we review the recent genome-wide screens that aim to identify cancer-causing genes, discuss why there seems to be so many of them and how such candidate genes can be validated. With improvements in DNA sequencing technologies, it became possible in the latter part of the 20th century to contemplate performing systematic genome-wide screens for new cancer genes using exon resequencing. At the time these studies were initiated, sequencing technology had not advanced to the point where it was possible to sequence all coding exons in the human genome. Consequently, early studies prioritized sequencing genes in signaling pathways where at least one gene in the pathway was known to be mutated in cancer, such as the rat sarcoma (RAS) extracellular-signal-regulated kinase (ERK) mitogen-activated protein (MAP) kinase pathway [2Davies H. et al.Mutations of the BRAF gene in human cancer.Nature. 2002; 417: 949-954Crossref PubMed Scopus (8511) Google Scholar]. Coding exons, and their upstream and downstream splice sites, were amplified using PCR from tumor and control DNA from the same patient, and the sequences were compared to find somatic mutations unique to the cancer cell. Among the collection of 15 cancer cell lines and matched lymphoblastoid cell lines screened in these studies, three were identified that had somatic mutations in the v-RAF murine sarcoma viral oncogene homolog B1 (BRAF) serine/threonine kinase domain, which led to follow-up studies in which BRAF coding exons were sequenced in an additional 530 cancer cell lines. BRAF mutations were identified in 66% of malignant melanomas and at a lower frequency in a wide variety of human cancers, including melanomas, colorectal cancers, gliomas, lung cancers, sarcomas, ovarian carcinomas, breast cancers and liver cancers. All mutations were in the kinase domain, elevated kinase activity and were transforming in NIH 3T3 cells. Similar studies performed thereafter identified a high frequency of mutations in the phosphatidylinositol 3-kinase (PI3K), catalytic, alpha-subunit gene (PIK3CA) in colorectal cancer (37%), glioblastomas (27%), gastric cancers (25%) and lung cancers (4%) [3Samuels Y. et al.High frequency of mutations of the PIK3CA gene in human cancers.Science. 2004; 304: 554Crossref PubMed Scopus (2979) Google Scholar]. The mutations clustered in the helical and kinase domains and increased lipid kinase activity consistent with a role in tumorigenesis. These early studies validated the use of large-scale exon resequencing for identifying new CAN genes in human cancers. Further advances in exon sequencing rapidly made it possible to sequence even more genes in a larger number of cancers for mutations. In one study making use of these expanded DNA sequencing capabilities, all the coding exons and associated splice sites for the 138 known protein tyrosine kinases (PTKs) and 87 known protein phosphatases (PTPs) were sequenced in a collection of colorectal cancer lines [4Bardelli A. et al.Mutational analysis of the tyrosine kinome in colorectal cancers.Science. 2003; 300: 949Crossref PubMed Scopus (432) Google Scholar]. Phosphorylation of tyrosine kinase residues is a central feature of many cellular signaling pathways involved in cancer and is coordinately controlled by PTKs and PTPs. Although a variety of PTKs had been linked to tumorigenesis, only a few PTPs had been implicated in cancer (http://www.sanger.ac.uk/genetics/CGP/Census). Among the 138 PTK genes sequenced from 35 colorectal cancer cell lines, 14 contained mutations in their kinase domains. These genes were then reanalyzed for mutations in another 147 colorectal cancers. Seven of the 14 genes were mutated in more than one cancer, and the ratio of nonsynonomous to synonmous mutations (see Glossary) was higher than predicted, supporting the notion that these are driver mutations for cancer. These studies suggested that a minimum of 30% of colorectal cancers contain at least one mutation in a PTK gene. PTKs, as demonstrated for BCR-ABL, provide good drug targets for therapeutic intervention, and these mutant PTKs, therefore, represent many new opportunities for drug development. Among the 87 PTP genes sequenced from 18 colorectal cancers [5Wang Z. et al.Mutational analysis of the tyrosine phosphatome in colorectal cancers.Science. 2004; 304: 1164-1166Crossref PubMed Scopus (435) Google Scholar], six contained mutations and were further analyzed in another 157 colorectal cancers. Altogether, 83 mutations in six PTPs were identified, affecting 26% of colorectal cancers and a smaller fraction of lung, breast and gastric cancers. Fifteen mutations were predicted to produce truncated proteins lacking phosphatase activity, suggesting that these PTPs are tumor suppressor genes. Consistent with this prediction, five mutations in the protein–tyrosine phosphatase receptor type T (PTPRT) gene were examined biochemically and found to reduce phosphatase activity. These two studies greatly expanded on what was known about the role of PTKs and PTPs in colorectal cancer and suggested that both PTKs and PTPs are major players in the disease. In 2006, Sjoblom et al. [6Sjoblom T. et al.The consensus coding sequences of human breast and colorectal cancers.Science. 2006; 314: 268-274Crossref PubMed Scopus (2890) Google Scholar] published their seminal paper reporting the sequencing of all coding exons and splice sites for the majority of protein-coding genes in 11 breast and 11 colorectal cancers. Genes with somatic mutations in at least one cancer were then reanalyzed for mutations in 24 additional cancers of the same type. Genes mutated in two or more cancers were then further analyzed in additional tumors to better define their mutation frequency and aid subsequent bioinformatic analyses. On average, colorectal and breast cancers contained a median of 76 and 84 nonsynonomous mutations, respectively. The great majority were single base substitutions; 81% were missense, 7% were nonsense and 4% were altered splice sites. The remaining 8% were insertions, deletions and duplications. These mutations could have been selected during tumor growth because of their effect on net cell growth (driver mutations) or through the accumulation of nonfunctional alterations that arise spontaneously during repeated rounds of cell division in the tumor or its progenitor stem cell (passenger mutations). Statistical methods were developed to estimate the probability that the number of nonsynonomous mutations in any given gene was greater than predicted by the background mutation rate [6Sjoblom T. et al.The consensus coding sequences of human breast and colorectal cancers.Science. 2006; 314: 268-274Crossref PubMed Scopus (2890) Google Scholar]. This analysis suggested that the majority of nonsynonomous mutations were passenger mutations and that the number of driver genes mutated in an individual colorectal or breast cancer averaged only 15 and 14, respectively. Among the driver genes identified, only a few were mutated in a large proportion of tumors, whereas most were mutated in < 5% of the tumors (Figure 1). Comparison of the driver genes mutated in two tumors of the same type also showed little overlap, which is not surprising given that most driver genes are mutated in only a few percent of the tumors. These differences in the spectrum of driver genes mutated in different tumors of the same type are likely to cause the wide variations in tumor behavior and response to therapy seen in individual tumors. These data support the view that cancer is caused by a large number of driver mutations, each associated with a small fitness advantage, to drive tumor formation. Statistical analysis of the genes mutated in breast cancer suggested that many function in PI3K signaling. This pathway was also overrepresented in the genes mutated in colorectal cancer, in addition to other pathways related to cell adhesion, the cytoskeleton and the extracellular matrix. Exactly how many pathways need to be deregulated to induce cancer remains unknown. Although the fraction of mutations that were single base substitutions was similar in colorectal and breast cancer, the nature of the substitutions was strikingly different. The largest difference occurred at C:G base pairs: 59% of colorectal cancer mutations were C:G to T:A transitions, whereas only 7% were C:G to G:C transversions. By contrast, only 35% of breast cancer mutations were C:G to T:A transitions, whereas 29% were C:G to G:C transversions. A large proportion (44%) of the mutations in colorectal cancers were at 5'-CpG-3' dinucleotide sites, but only 17% of the mutations in breast cancer occurred at such sites. This leads to an excess of nonsynonomous mutations, resulting in changes of arginine residues in colorectal cancer, but not in breast cancer. By contrast, 31% of mutations in breast cancer occurred at 5'-TpC-3' sites, whereas only 11% of mutations in colorectal cancer occurred at dinucleotide sites. This difference is highly significant (p < 0.0001) and consistent with other studies, which suggest that the spectrum of mutations in any given cancer is influenced by previous exposure to environmental and chemical carcinogens (Box 1).Box 1Pattern of somatic mutations in human cancer genomesInsights into the general patterns of somatic mutations in human cancer have been provided by sequencing coding exons and splice sites of 518 protein kinase family genes in 210 different types of human cancers [21Davies H. et al.Somatic mutations of the protein kinase gene family in human lung cancer.Cancer Res. 2005; 65: 7591-7595Crossref PubMed Scopus (393) Google Scholar, 22Greenman C. et al.Patterns of somatic mutation in human cancer genomes.Nature. 2007; 446: 153-158Crossref PubMed Scopus (2442) Google Scholar, 23Stephens P. et al.A screen of the complete protein kinase gene family identifies diverse patterns of somatic mutations in human breast cancer.Nat. Genet. 2005; 37: 590-592Crossref PubMed Scopus (291) Google Scholar]. A total of 1007 somatic mutations were detected. Of these, 921 were nonsynonomous and 219 were synonomous mutations. There was substantial variation in the number and pattern of mutations in individual cancers, reflecting the different exposure to carcinogens, DNA repair defects and cellular origins. The highest mutation rate (∼77 mutations per Mb) was seen in two gliomas that were recurrences after treatment with the anticancer drug temozolomide, a known mutagen. Some melanomas and lung cancers also showed increased mutation rates that might relate to the extent of their past exposure to UV radiation and tobacco smoke, respectively. Another five cancers were identified with defective DNA mismatch repairs, leading to microsatellite instability (MIN) and an increased number of base substitutions (14–40 per Mb), and small insertions/deletions at polynucleotide tracts (5–12 per Mb).Among the primary cancers studied, lung carcinomas showed the greatest number of somatic mutations (4.21 per Mb), followed by gastric (2.10 per Mb), ovarian (1.85 per Mb), colorectal (1.21 per Mb) and renal (0.74 per Mb) cancers. Cancers with the fewest mutations were testicular cancer (0.12 per Mb), lung carcinoids (0 per Mb) and breast cancer (0.19 per Mb). Cancers with the highest mutation rates mainly originated from the high turnover of surface epithelia that are subject to recurrent mutagen exposure. This was not the only factor effecting mutation rates, however, as ovarian cancer had a higher mutation rate than colorectal cancer even though it is thought to arise from a region not normally exposed to carcinogens. Insights into the general patterns of somatic mutations in human cancer have been provided by sequencing coding exons and splice sites of 518 protein kinase family genes in 210 different types of human cancers [21Davies H. et al.Somatic mutations of the protein kinase gene family in human lung cancer.Cancer Res. 2005; 65: 7591-7595Crossref PubMed Scopus (393) Google Scholar, 22Greenman C. et al.Patterns of somatic mutation in human cancer genomes.Nature. 2007; 446: 153-158Crossref PubMed Scopus (2442) Google Scholar, 23Stephens P. et al.A screen of the complete protein kinase gene family identifies diverse patterns of somatic mutations in human breast cancer.Nat. Genet. 2005; 37: 590-592Crossref PubMed Scopus (291) Google Scholar]. A total of 1007 somatic mutations were detected. Of these, 921 were nonsynonomous and 219 were synonomous mutations. There was substantial variation in the number and pattern of mutations in individual cancers, reflecting the different exposure to carcinogens, DNA repair defects and cellular origins. The highest mutation rate (∼77 mutations per Mb) was seen in two gliomas that were recurrences after treatment with the anticancer drug temozolomide, a known mutagen. Some melanomas and lung cancers also showed increased mutation rates that might relate to the extent of their past exposure to UV radiation and tobacco smoke, respectively. Another five cancers were identified with defective DNA mismatch repairs, leading to microsatellite instability (MIN) and an increased number of base substitutions (14–40 per Mb), and small insertions/deletions at polynucleotide tracts (5–12 per Mb). Among the primary cancers studied, lung carcinomas showed the greatest number of somatic mutations (4.21 per Mb), followed by gastric (2.10 per Mb), ovarian (1.85 per Mb), colorectal (1.21 per Mb) and renal (0.74 per Mb) cancers. Cancers with the fewest mutations were testicular cancer (0.12 per Mb), lung carcinoids (0 per Mb) and breast cancer (0.19 per Mb). Cancers with the highest mutation rates mainly originated from the high turnover of surface epithelia that are subject to recurrent mutagen exposure. This was not the only factor effecting mutation rates, however, as ovarian cancer had a higher mutation rate than colorectal cancer even though it is thought to arise from a region not normally exposed to carcinogens. Colorectal and breast cancers were also evaluated with single nucleotide polymorphism (SNP) arrays containing at least 317 000 SNP probes to detect homozygous deletions and amplifications. These data were then integrated with the sequencing data, which made it possible to identify genes and cellular pathways affected by both copy number changes and point mutations. Colorectal and breast tumors had on average seven and 18 copy number alterations, respectively, defined as homozygous deletions or amplifications to at least 12 copies per cell. The average number of protein-coding genes affected by amplification or homozygous deletions were nine and 24 per colorectal and breast cancer, respectively. CAN genes that harbored point mutations were sometimes amplified or deleted in other tumors. Among 19 CAN genes amplified in colorectal and breast cancer, only eight were previously implicated in tumorigenesis. A few genes were also altered in both breast and colorectal cancers. For example, the V-ERB-B2 avian erythroblastic leukemia viral oncogene homolog 2 (ERBB2) was amplified in both breast and colorectal cancer, whereas fibroblast growth factor receptor 2 (FGFR2) was mutated in breast cancer and amplified in colorectal cancer. Otherwise, there was little overlap in the genes amplified in breast and colorectal cancer. The same was true for the 19 CAN genes homozygously deleted in breast and colorectal cancer. Three were inactivated in both breast and colorectal cancer. Others were deleted in other types of cancer but not in breast and colorectal cancer. The rest are not known to be affected by homozygous deletions and are candidates for new tumor suppressor genes. Analysis of copy number changes also provided general insights into the functional effects of point mutations. For example, single nucleotide substitutions in genes that were deleted in other tumors are more likely to be inactivating, whereas substitutions in genes that were amplified in other tumors are more likely to be activating. Genome-wide studies have also been reported for glioblastoma multiforme and pancreatic cancer [7Jones S. et al.Core signaling pathways in human pancreatic cancers revealed by global genomic analyses.Science. 2008; 321: 1801-1806Crossref PubMed Scopus (3197) Google Scholar, 8Parsons D.W. et al.An integrated genomic analysis of human glioblastoma multiforme.Science. 2008; 321: 1807-1812Crossref PubMed Scopus (4703) Google Scholar], with fairly similar results. One major difference was in the total number of nonsynonomous mutations in glioblastoma multiforme, which was substantially smaller than the number in pancreas, breast and colorectal cancer. The mostly likely reason is the reduced number of cell generations in glial cells before the onset of cancer. Pathway analysis showed that many of the signaling pathways deregulated in glioblastoma multiforme were also deregulated in pancreas, colorectal and breast tumors, such as those regulating control of cellular growth, apoptosis and cell adhesion. However, a number of pathways were enriched only in glioblastoma multiforme, including channels involved in the transport of sodium, potassium and calcium ions, as well as nervous system-specific cellular pathways such as synaptic transmission, transmission of nerve impulses and axonal guidance. Thus, many signaling pathways seem to be shared among different cancer types, in addition to cancer type-specific pathways. Serial analysis of gene expression was also performed to analyze the transcriptome of glioblastoma multiforme because this technique can identify epigenetic alterations not detectable by sequencing or copy number changes alone. This helped identify previously uncharacterized target genes from amplified and deleted regions. It also aided in the identification of the best CAN gene lying within large amplified and HD regions. Finally, it helped assess the significance of gene sets implicated in pathways enriched for genetic alterations. Interestingly, the integrated genomic analyses of glioblastoma multiforme led to the discovery of recurrent alterations in the active site of isocitrate dehydrogenase 1 (IDH1) in 12% of glioblastoma multiforme patients. IDH1 mutations occurred in a large proportion of young patients and in most patients with secondary glioblastoma multiforme, and were associated with an increase in overall survival. This illustrates the value of a genome-wide screen because in a more limited screen only analyzing genes deemed to have the highest probability of being involved in cancer, IDH1 would almost certainly have been excluded. Analysis of the genes mutated in pancreatic cancer identified 12 partially overlapping pathways that were genetically altered in the great majority of pancreatic cancers (Table 1). One striking finding was that the pathway components that were altered in individual tumors varied widely. For example, 100% of pancreatic cancers had mutations in genes that are predicted to function in the hedgehog-signaling pathway. However, the number of mutated genes in the pathway was large. In addition, with few exceptions, only one gene in a pathway was mutated in any one cancer (Table 2). This again demonstrates the value of a genome-wide screen because only a small fraction of tumors will contain a mutation in any one gene in a pathway, and only through the analysis of all genes in a pathway will the contribution of the pathway to the cancer become evident.Table 1Core signaling pathways and processes genetically altered in most pancreatic cancersRegulatory process or pathwayNumber of mutated genes in pathwayPercentage of tumors with genetic alterations in pathwayApoptosis9100%DNA damage control983%Regulation of G1/S transition19100%Hedgehog signaling19100%Homophilic cell adhesion3079%Integrin signaling2467%c-Jun N-terminal kinase signaling996%KRAS5100%Regulation of invasion4692%GTPase-dependent signaling3379%TGF-β signaling37100%WNT/Notch signaling29100%Data from 7Jones S. et al.Core signaling pathways in human pancreatic cancers revealed by global genomic analyses.Science. 2008; 321: 1801-1806Crossref PubMed Scopus (3197) Google Scholar, reproduced with permission from AAAS. Open table in a new tab Table 2Mutations of the TP53, PI3K and RB1 pathways in GBM tumorsTP53 pathwayPI3K pathwayRB1 pathwayTumor No.TP53MDM2MDM4PTENPIK3CAPIK3R1IRS1RB1CDK4CDKN2A1DelMutDel2MutMut3MutMutMut4AmpMutDel5Del6MutMutDel7Del8MutAmp9Mut10Mut11MutMut12MutDel13MutDel14Del15Amp16MutDel1718MutDel19MutDel20MutDel21Mut22MutAbbreviations: Mut, mutated; Amp, amplified; Del, deleted. Data from 8Parsons D.W. et al.An integrated genomic analysis of human glioblastoma multiforme.Science. 2008; 321: 1807-1812Crossref PubMed Scopus (4703) Google Scholar, reproduced with permission from AAAS. Open table in a new tab Data from 7Jones S. et al.Core signaling pathways in human pancreatic cancers revealed by global genomic analyses.Science. 2008; 321: 1801-1806Crossref PubMed Scopus (3197) Google Scholar, reproduced with permission from AAAS. Abbreviations: Mut, mutated; Amp, amplified; Del, deleted. Data from 8Parsons D.W. et al.An integrated genomic analysis of human glioblastoma multiforme.Science. 2008; 321: 1807-1812Crossref PubMed Scopus (4703) Google Scholar, reproduced with permission from AAAS. None of the published studies have incorporated approaches designed to detect structural aberrations, such as balanced chromosome translocations, inversions and rearrangements on a genome-wide scale, although this has now become possible (Box 2). Structural aberrations are an important class of cancer-causing mutations (Box 3) and have been detected in every major tumor type, representing at total of more than 56 400 tumors. They can be classified based on characteristic chromosome abnormalities (see the Mitelman Database of Chromosome Aberrations in Cancer; http://cgap.nci.nih.gov/Chromosomes/Mitelman). More than 500 recurrent balanced translocations have been identified, and many show remarkable specificity regarding tumor subtypes. The majority of translocations have been detected in hematological malignancies, which is not surprising given that these tumors are the easiest to karyotype. Solid tumors, such as epithelial tumors, which cause 80% of all cancer deaths, also contain recurrent balanced translocations, although the data on these tumors is much less complete because of the inherent difficulty in karyotyping these tumors, and because they usually have multiple structural aberrations at the time of diagnosis.Box 2Methods for detecting structural aberrations in cancerA number of methods for detecting genomic rearrangements have been reported that are amenable to high-throughput analysis of cancer genomes. One method uses high-throughput sequencing to generate millions of sequence reads from both ends of short DNA fragments derived from tumor cells. By investigating read pairs from two individuals with lung cancer that did not align correctly with respect to each other on the reference genome, Campbell et al. [24Campbell P.J. et al.Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing.Nat. Genet. 2008; 40: 722-729Crossref PubMed Scopus (672) Google Scholar] identified 306 germline structural variants and 103 somatic rearrangements to the base pair level of resolution. Another method uses transcriptome sequencing to detect gene fusions in cancer cells. High-throughput transcriptome sequencing of a single breast cancer cell line HCC1954 identified genomic rearrangements leading to fusions or truncations of genes known to be involved in cancer, in addition to a number of novel genes [25Zhao Q. et al.Transcriptome-guided characterization of genomic rearrangements in a breast cancer cell line.Proc. Natl. Acad. Sci. U. S. A. 2009; 106: 1886-1891Crossref PubMed Scopus (103) Google Scholar]. Transcriptome sequencing also successfully rediscovered the BCR-ABL gene fusion in a CML cell line and the TMPRSS2-ERG gene fusion in a prostate cancer cell line [26Maher C.A. et al.Transcriptome sequencing to detect gene fusions in cancer.Nature. 2009; 458: 97-101Crossref PubMed Scopus (705) Google Scholar]. These studies open up an important class of cancer-related mutations for comprehensive characterization.Box 3Chromosome aberrations in cancerTranslocationsA chromosome abnormality can be caused by the reciprocal exchange of genetic material between nonhomologous chromosomes. A fusion gene can be created when the translocation joins two separate genes, which is a common event in cancer. Translocations are referred to as balanced, when genetic material is neither lost or gained, or unbalanced.Amplifications and deletionsChromosome duplications can result from an error in homologous recombination, a retrotransposition event or duplication of an entire chromosome. Duplications resulting from errors in homologous recombination arise from unequal crossing over during meiosis or mitosis, and are facilitated by the sharing of repetitive DNA between chromosomes. The product of the recombination is a duplication at the site of exchange and a reciprocal deletion. Deletions can become homozygous following mitotic recombination involving non-sister chromatids, whereas the process of amplification can continue until multicopy amplicons are formed. Duplications and amplification can be intragenic or span large amounts of DNA.InversionsAn inversion is a chromosome rearrangement in which a segment of a chromosome is reversed end-to-end. Paracentric inversions are inversions where both breaks occur in one arm of a chromosome and do not involve the centromere, whereas pericentric inversions include the centromere and are caused by chromosome breaks in both chromosome arms. Inversions can be balanced or unbalanced and can create fusion genes of the type produced following chromosome translocation. A number of methods for detecting genomic rearrangements have been reported that are amenable to high-throughput analysis of cancer genomes. One method uses high-throughput sequencing to generate millions of sequence reads from both ends of short DNA fragments derived from tumor cells. By investigating read pairs from two individuals with lung cancer that did not align correct