Abstract LB-326: Elucidating significant genetic associations between genes and lung cancer

Abstract

Abstract Introduction: To further understand and elucidate the genetic risk factors for Lung Cancer (LC) will substantially improve cancer prevention, screening programs, and treatment options for this insidious disease. However, our previous attempts to increase the discriminatory power in an existing risk model with the inclusion of SNPs identified via GWAS have not been very successful. In this analysis, we reassess the increase in discriminatory power by including haplotypes based on existing GWAS-identified SNPs and additional single SNPs. Methods: Cases included 1154 histological-confirmed Caucasian lung cases from MD Anderson Cancer Center in Houston, Texas, and controls included 1137 individuals recruited through the Kelsey-Seybold Clinics in Houston, Texas. Genetic information from both populations was selected for 157 SNPs that exist in the Texas GWAS and were part of the top 200 SNPs as determined by a previously published meta-analysis of 10 different lung cancer GWAS datasets (Landi et al. 2009). Plink and Haploview were used to determine the top SNPs and top haplotype blocks respectively. Then, univariate logistic regression was used to determine the best genetic model for the top SNPs. Joint logistic risk model regression was used to determine haplotype risk for each individual haplotype block. Finally, multivariate logistic regression was used to develop the final extended model that included the original set of risk factors from the Spitz model plus additional haplotypes and SNPs. We evaluated increase in discriminatory power by evaluated change in the area under the receiver-operating characteristic curve and the net reclassification index. Results: The discriminatory power for the original Spitz model was 66.1% (95% CI = 0.638-0.683). With the inclusion of only single SNPs in to the model, the discriminatory power increased by 4.5% to 70.6% (95% CI = 0.684-0.727, p-value = <0.0001). Adding the top 6 haplotypes further increased the discriminatory power to 71.9% (95% CI = 0.697-0.739). The net reclassification index results show that this increase in discriminatory power is evident for both cases (23.47%) and controls (23.43%). Conclusions: Inclusion of genetic variants into an established epidemiologic risk model can substantially increase the discriminatory power; however, selection and modeling of these variants needs to be carefully done. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-326. doi:1538-7445.AM2012-LB-326