Identification of Genes and DNA Methylation Markers for Lung Cancer Risk by Integrating Multi-omics Data

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Project Summary Lung cancer is the leading cause of cancer death in the United States and many other countries. Genome-wide association studies (GWAS) have identified ~55 genetic loci associated with lung cancer risk. However, causal genes (and their underlying biological mechanisms) for most of these loci remain unknown. Gene expression is an intermediate phenotype between genetic variants and disease. DNA methylation plays a critical role in regulating gene expression. Directly integrating genomic, transcriptomic, and methylomic data with disease risk can uncover novel disease susceptibility genes and potential mechanisms. However, it is extremely difficult, if at all possible, and costly to directly profile the transcriptome and methylome in lung tissues from a large number of cases and controls for evaluating these associations. Herein, we propose a novel approach: transcriptome-wide association study (TWAS) and methylation-wide association study (MeWAS) to identify novel genes and methylation loci related to lung cancer risk using genetic instruments. These novel approaches have been shown to be very powerful in identifying novel genes and methylation sites in both GWAS-reported loci and regions not yet revealed in GWAS in multiple recent studies, including our pilot study in lung cancer. We propose to conduct a well-powered TWAS and MeWAS to discover novel genes and methylation loci (both potential targeted genes/methylation sites in GWAS-identified loci and genes/methylation sites in loci not yet uncovered by GWAS) for lung cancer risk (Aim 1). We will evaluate the differences in the expression levels of TWAS-identified genes and the methylation levels of MeWAS-identified loci between lung cancer tissues and normal tissues to prioritize genes and methylation loci that may contribute to lung cancer risk (Aim 2). We will investigate the regulating effects of methylation sites on the expression of promising genes and evaluate the functions of genes and methylation loci by functional genomics analyses (Aim 3). Finally, we will perform a serial of functional analyses to evaluate the potential functions of identified genes and methylation loci (Aim 4). We anticipate that this proposed study will identify a large number of novel genes and methylation loci for lung cancer risk and provide functional data to improve understanding of biological mechanisms. The proposed study is highly innovative and cost efficient. Our results will help us to better understand the mechanistic relationship between genetic and epigenetic variations and how those variations relate to lung cancer risk, and may lead to the discovery of biomarkers that would facilitate early detection of lung cancer and the development of targeted gene therapies for personalized treatment.