Survival outcomes for lung cancer, the leading cause of cancer-related mortality in the United States, remainpoor. Improving lung cancer survival requires a multi-pronged approach, including smoking cessation andbetter elucidation of gene-environment interactions in risk, identification of new promising drug targets, aswell as identification of potential prognostic and predictive markers that can help optimize treatment forpatients. Our molecular epidemiology research group has investigated lung cancer risk and geneenvironmentinteractions in the first SPORE cycle,.and supported by R01 funding. Other proposed SPOREprojects are directly addressing new potential targets for drug interventions. In SPORE Project 1, we willfocus on identifying prognostic and predictive markers of survival in lung cancer. The ultimate goal ofidentifying such markers is to find ways to select the best treatment course for each patient. Recent studiesby our group have demonstrated the importance of germline polymorphic variants as prognostic andpredictive factors, but these studies have investigated only a few candidate polymorphisms relative tosurvival outcomes. In this SPORE renewal, we have adopted a high-density pathway approach toinvestigate more extensively and efficiently the role of entire pathways in survival outcomes. We selectedpathways with biologic evidence for a role in tumor aggressiveness or treatment response. Although theeventual goal will be to evaluate germline DNA, serology, tumor-based tissue, and clinical factors in onecohesive model, at present we will focus on germline DNA to identify critical pathway markers. To achievethis goal, we will utilize a large'(n=1,000), mature NSCLC case series, early and late stages, with annotatedDNA and clinical data to assess genetic variation in selected pathways as prognostic and predictive markersin NSCLC.
In Aim 1 (gene discovery), we will use the Illumina Bead Station GoldenGate assay system forgenotyping of single nucleotide polymorphisms (SNPs), which allows large-scale genotyping for up to 1,536customized SNPs, to systematically assess the effects of genetic variation in these pathways on survivaloutcomes in 60% of our large sample size (discovery phase). For polymorphisms that cannot be assayedwith this system and for candidate genes to be used in a validation phase (Aim 2) on the whole population,we will utilize other in-house techniques in the Genomics Core, including Sequenom and ABI 7900 Taqman.Though our primary endpoint will be overall survival (OS), we will also assess disease-free survival (DPS)and progression-free survival (PFS), where appropriate.
Aims 3 -4 will include assessing the role of genderand other factors in the genetic predictors of survival among lung cancer patients, using both stratified andinteraction analyses; and assessing additional candidate genes (e.g. EGFR) and pathways identified fromcompanion basic and translational science studies (Projects 2-5) in lung cancer outcomes. The detailed .clinical annotation of our case series is a unique resource with which to investigate prognostic and predictivemarkers, as well as for gene-environment interactions, in lung cancer survival.
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