Study On Risk Prediction Model Of Lung Cancer In Chinese Population Based On Genome - Wide Association Study

Lung, cancer is the leading cause of cancer deaths worldwide. Although cigarette smoke plays an important role in lung cancer development, only10-15%of smokers develop lung cancer, suggesting possible involvement of genetic factors.Recent genome-wide association studies (GWAS) have identified multiple susceptibility regions for lung cancer, including5p15.33,6p21.33and15q25regions, but most of these variants have not been validated in a Chinese population. In this study, we investigate whether the single nucleotide polymorphisms (SNPs) identified by GWAS associate with risk of lung cancer in Chinese population, and estimate the discriminatory capability of genetic risk score combining multiple genetic loci.Seventeen SNPs identified in previous GWA and large cohort studies were genotyped in2283incident lung cancer cases and2785controls. The genetic risk score (GRS) based on these SNPs was estimated by two approaches:a simple risk alleles count (cGRS) and a weighted (wGRS) method. The area under the receiver operating characteristic (ROC) curve (AUC) in combination with the bootstrap resample method was used to assess the predictive performance of the genetic risk score for lung cancer.Four independent SNPs (rs2736100, rs402710, rs4488809and rs4083914), were found to be associated with a risk of lung cancer. The wGRS based on these four SNPs was a better predictor than cGRS, cGRS:odds ratio for persons in the highest risk group vs those in the lowest=2.12(95%CI:1.57-2.86), P<0.001; wGRS:odds ratio for persons in the highest quintile of weight genetic risk score vs those in the lowest=2.01(95%CI:1.59-2.54), P<0.001. Using a liability threshold model, we estimated that these four SNPs accounted for only4.02%of genetic variance in lung cancer. Smoking history contributed significantly to lung cancer risk, and incorporated with wGRS gave a c statistic of0.637after adjustment for over-fitting. This model shows promise for assessing lung cancer risk in a Chinese population. Our results indicate that genetic variants related to lung cancer (3q28,5p15.33and6q25regions) may be useful for lung cancer prediction in a Chinese population.