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Originally published as JCO Early Release 10.1200/JCO.2005.05.4114 on March 20 2006 © 2006 American Society of Clinical Oncology.
Genetic Susceptibility to Lung CancerMassachusetts General Hospital; Harvard Medical School, Harvard School of Public Health, Boston, MA There are several significant challenges to understanding variation in an individual's or a population's susceptibility to an environmentally induced disease such as lung cancer. Firstly, the genetic landscape of human susceptibility is complex. There are likely to be only rare instances in which mutations within a single gene convey significant sensitivity to typical levels of exposure. More likely, there will be many genes with moderate or small effects, which, in combination, result in disease susceptibility after exposure. Interactions among genetic variants, as well as gene-environment interactions and epigenetic processes, are likely to play a significant role in determining disease susceptibility to an exposure. This etiologic heterogeneity presents methodologic challenges. Secondly, we are only beginning to understand the distribution of single nucleotide polymorphisms (SNPs) in the human genome and to type large numbers of SNPs accurately. Ideally, we would like to handle all known SNPs' measures in epidemiologic, clinical, or in vitro studies, eliminating the puzzle of whether unmeasured genetic variants contribute to observed variation in disease risk or progression. Currently, in population genetics, multistaged research strategies, such as linkage to identify potential genomic regions, followed by positional candidate gene studies or genomic scans using tag SNPs followed by fine mapping, are employed to identify a set of genes and their variants that are most significantly associated with disease susceptibility. These multistaged approaches typically assume that individual mutations have statistically significant and context-independent (ie, some disease association in different populations or other contexts) disease associations. However, true multigenic models of susceptibility to common (ie, complex) disorders have not been achievable to date. Lung cancer remains the leading cause of cancer mortality in the Western world, and its incidence is increasing worldwide. Lung cancer is associated strongly with environmental exposures, with the highest population-attributable risk from cigarette smoking. Although smoking accounts for the majority of lung cancer cases, the fact that only a minority of smokers develop lung cancer in their lifetimes makes this disease an important model for assessing gene-environment interactions. Because of its clinically poor prognosis, which makes it difficult to conduct efficient family-based linkage analysis of pedigrees for polygenic inheritance, the predominant method used to date in lung cancer has been the candidate gene approach in case-control studies.1-4 The most common method to date of selecting candidates consists of what can be considered as forward selection on the basis of existing knowledge of toxicologic and carcinogenic pathways (eg, DNA repair, cell cycle, apoptosis) and from functional genomics. The alternate approach offered in this issue by Spinola et al5 can be regarded as a reverse selection method. In their approach, no prior hypothesis about gene pathways, function, or toxicokinetics are entertained. They undertook a case-control study using two pools of DNA samples from lung cancer patients and controls and employed a whole-genome scan. From the initial scan, 160 SNPs were identified, which differed significantly between cases and controls, and the SNP (rs1862214) most strongly associated with lung cancer was then individually genotyped in the same case-control population, as well as an independent population. Their results showed that the variant form of use of this apoptosis PDCD5 gene was associated with an increased risk of lung cancer in both the German and Italian populations studied. Additionally, the GG homozygous variant was associated with clinical stage and therefore, not surprisingly, poorer survival. The rs1862214 variant allocates in a haplotype block containing the PDCD5 gene that involves in the regulation of apoptosis. Despite other studies showing some cell-specific effects in transfected human lung cancer cell lines, preliminary functional studies in vivo did not show difference of PDCD5 mRNA levels in lung parenchyma between individuals with the common CC genotyped and the GG allele carriers. Although the method used in this study is attractive, some caveats remain. Firstly, estimation of separate contributions of genes and environment (in this case, smoking) to lung cancer, while ignoring their interactions, will incorrectly estimate the proportion of the disease explained by genes, environment, and their joint effects. Hence, the identification of susceptibility in candidate gene studies will provide direct evidence that these genes and their associated pathways are relevant to disease in humans.6 Understanding these pathways will help to determine which agents in a complex mixture cause disease. Secondly, lung cancer itself is a heterogeneous disease. This study included adenocarcinoma from an Italian population, and all cell types (including small-cell lung cancer) from the German population, as well as all lung cancer stages. Larger studies, with detailed information on covariates enabling an examination of different strata, such as cell type, are needed. Additionally, a multivariate survival analysis, adjusting for stage and performance status and other potential confounders, is needed. Showing an association between genotype and clinical stage at presentation is important, but does not add substantially to our prognostic inventory. Finally, there was no difference between tumor and noninvolved tissue in PDCD5 mRNA levels and the rs1862214 polymorphism. Nevertheless, this research provides a cost-efficient approach for candidate gene selection without any prior knowledge using whole-genome scan on pooled samples. Studies such as this contribute significantly to our understanding of lung cancer susceptibility and toward the goal of preventative medicine that will allow us to advise patients on disease prevention and outcomes. Although individual genome-wide sequencing will soon become affordable, its proven widespread use depends on sound research that produces a reliable and credible database on gene-environment interactions. This research requires more accurate assessment of exposure, as part of well-designed epidemiologic studies. Author's Disclosures of Potential Conflicts of Interest The author indicated no potential conflicts of interest. Author Contributions
REFERENCES 1. Su L, Zhou W, Asomaning K, et al: Genotypes and haplotypes of matrix metalloproteinase 1, 3 and 12 genes and the risk of lung cancer. Carcinogenesis 26:November 25, 2005 [epub ahead of print] 2. Zhou W, Liu G, Park S, et al: Gene-smoking interaction associations for the ERCC1 polymorphisms in the risk of lung cancer. Cancer Epidemiol Biomarkers Prev 14:491-496, 2005 3. Wu X, Zhao H, Suk R, et al: Genetic susceptibility to tobacco-related cancer. Oncogene 23:6500-6523, 2004[CrossRef][Medline] 4. Gurubhagavatula S, Liu G, Park S, et al: XPD and XRCC1 genetic polymorphisms are prognostic factors in advanced non–small-cell lung cancer patients treated with platinum chemotherapy. J Clin Oncol 22:2594-2601, 2004 5. Spinola M, Meyer P, Kammerer S, et al: Association of the PDCD5 locus with lung cancer risk and prognosis in smokers. J Clin Oncol 24:10.1200/JCO.2005.04.4339 6. Hunter DJ: Gene-environment interactions in human diseases. Nat Rev Genet 6:287-298, 2005[Medline]
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Copyright © 2006 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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