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• W2014967187 abstract "Understanding the molecular events underlying the initiation and progression of colorectal cancer (CRC) is essential for implementing appropriate screening strategies for early detection and treatment regimes for improved outcome. Highly penetrant, inherited gene mutations account for only 3–5% of CRC cases, whilst a family history is reported by approximately one-third of all patients. The environment has been the presumed culprit in the remaining ‘sporadic’ cases and indeed associations have been observed between multiple environmental risk factors and increased disease incidence.1 However, despite intense efforts to prove causality, many associations with environmental factors are modest and remain controversial. The reason for this may in part be due to the genetic heterogeneity of sample populations, whereby subtle molecular differences may alter the magnitude of risk conferred by an environmental insult. In recent years, attention has turned to low-penetrance, common genetic variants (single nucleotide polymorphisms, SNPs) as modifiers of cancer risk and disease course. It is conceivable that low-penetrance variants will influence the disease onset and phenotype of a significant proportion of ‘sporadic’ CRCs. Furthermore, the impact of such variants could be substantial since multiple alleles are likely to act in an additive or multiplicative fashion.2, 3 This effect is unlikely to be linear due to interaction with other SNPs and the environment, both of which may increase risk or be protective. Variant alleles may be causally associated with disease risk or phenotype, or may be in linkage disequilibrium with the causative allele variant. Identifying SNPs associated with disease is currently the subject of intense investigation. For this field to transition from scientific interest to clinical utility, we will need to determine which SNPs contribute to CRC risk and phenotype, better understand gene–gene and gene–environment interactions and collaborate with bioinformaticians to devise the complex algorithm necessary to translate this genetic information into clinical recommendations for screening and disease management. Two major approaches for identifying and validating clinically relevant SNPs are genome-wide scans and hypothesis-driven candidate SNP studies, the latter based on physical location near a gene or region of potential importance in carcinogenesis. In recent months, a number of major discoveries have highlighted the advantages of large scale, genome-wide approaches for identifying low-penetrance alleles. A SNP on chromosome 8q24.21 (rs6983267) was identified in two independent studies4, 5 as conferring between 1.17- and 1.27-fold increased risk of CRC. These odds ratios were highly statistically significant and reproducible in multiple validation cohorts consisting of many thousands of patients and control subjects, including a third independent study of the SNP.6 A variant lying within the third intron of the SMAD7 gene (rs4939827) was also identified as a CRC susceptibility locus using a microarray SNP chip containing over 550 000 loci, and was estimated to contribute to approximately 15% of CRC cases.7 An alternative to genome-wide association is the candidate gene approach. For example, based on initial linkage data to families with hereditary mixed polyposis syndrome, the CRAC1 locus on chromosome 15q13.3 was investigated as a susceptibility locus for sporadic CRC.8 This revealed statistically significant risk estimates of 1.23 (heterozygotes) and 1.70 (homozygotes) for the rs4779584 SNP, and is estimated to account for approximately 15% of CRC cases. It may also be necessary to examine associations in defined CRC subgroups. For example, an MLH1 promoter SNP (rs1800734) was not associated with increased risk of CRC in an unselected cohort. However, when case patients were stratified for level of microsatellite instability (MSI), there was a highly significant association observed between the minor allele and a high level of MSI.9 Large-scale candidate gene approaches have also been successful, and may involve the construction of a ‘hypothesis-driven SNP chip’. A recent study using this approach resulted in the identification of 44 SNPs associated with CRC.10 An important consideration when designing association studies is adequate powering based on allele frequencies. It is estimated that for low-penetrance variants, where an odds ratio of 1.1–1.5 would be expected, a cohort of over 1000 subjects would be necessary to achieve statistical significance.11 When assessing multiple SNPs, stringent statistical tests must be applied to correct for multiple comparisons, which further necessitates large numbers of subjects. Cohort ethnicity is also an important factor as SNP frequencies may vary widely in different populations. Meta-analyses have been performed in an effort to achieve sufficient cohort numbers; however, ethnic heterogeneity must be avoided unless allele frequencies are known to be stable. Control populations must also be matched to case samples for age, gender, and ethnicity. Validation studies in secondary cohorts are also essential to confirm initial findings. In addition to estimation of disease risk, SNP profiling may also provide insights into the expected clinical course of a tumor. Ultimately this may be important for determining treatment modalities and predicting outcome. In the present issue of the Journal, Yoshiya and colleagues have adopted a candidate gene approach to investigate whether defined clinicopathologic features co-segregate with any of five common SNPs (CCND1, p21cip1, DCC, MTHFR, and Exo1).12 These were chosen based on their genomic location either within or near the coding regions of genes with putative roles in carcinogenesis. The study cohort consisted of 114 patients with colorectal cancer. This is a relatively small cohort for an association study, and the authors emphasize that the data is preliminary and requires further validation. Associations were observed between DCC and depth of invasion (P = 0.04), and MTHFR and tumor size (P = 0.02). After correction for multiple comparisons, these associations would lose statistical significance and should therefore be interpreted as intriguing correlations which require validation in a larger cohort. The Exo1 SNP examined is an example of a variant which may impact disease outcome. In this study the rare TT genotype segregated with a significantly reduced patient survival (P = 0.002). The variant T allele results in a proline to leucine amino acid change and may alter the ability of the gene to facilitate DNA repair. Exo1 has been implicated as a predisposition gene for hereditary non-polyposis colorectal cancer,13 but this conclusion has been controversial.14, 15 The present study should kindle further interest in the role Exo1 may play in CRC initiation and progression, which should now be tested in larger association and functional studies. Genomic medicine for the management of highly penetrant, hereditary colorectal syndromes is becoming routine in clinical practice. The utility of low-penetrance SNPs is still being evaluated in the research setting; however, preliminary findings certainly look promising. Whilst individual variants may confer only slightly altered risk, certain combinations of SNPs may synergize to significantly increase an individual's lifetime risk. Assuming a multiplicative affect, Broderick and colleagues proposed that five susceptibility loci would be sufficient to warrant regular colonoscopic surveillance.7 An immediate goal is to identify SNPs which may modify CRC susceptibility, pathology, clinical course, and response to therapy. The greater challenges will be deciphering the mechanisms through which the SNPs impact disease progression, and formulating the complex algorithm necessary to calculate risk based on multiple low-penetrance variants which are also modulated by environmental influences. Whilst intelligent selection of patients requiring surveillance remains an economic necessity, we are now in an era where generation of a simple ‘SNP-Chip’ for routine presymptomatic patient evaluation seems a realistic and cost-effective goal. Ultimately, such a test will not only be utilized for risk assessment, but will be an invaluable routine tool for individualized patient therapy." @default.
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• W2014967187 date "2008-06-01" @default.
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• W2014967187 title "Genomic medicine: SNPs on chips?" @default.
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• W2014967187 doi "https://doi.org/10.1111/j.1440-1746.2008.05422.x" @default.
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