Project 1: Smoking, environmental and genomic factors in lung cancer and managing risk

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Project Summary/Abstract Lung cancer (LC) is a “poster child” for a disease resulting from interactions between genetic and environmental risk factors. Ongoing LC genome wide association studies (GWAS) conducted by us have identified over 40 loci involved in LC susceptibility that have dramatically improved the understanding of the genetic architecture of LC risk. However, there is a significant bias in the conducted GWASs: most studies have involved populations of European descent. Ancestry plays an important role in LC risk through contribution of ancestry- specific germline polymorphisms as well as socio-cultural differences including environmental exposures. We hypothesize that a “one size (ancestry) fits all” model is not applicable to LC and that exploring risk of LC and its translation across ancestries manner will improve the understanding of LC risk and prevention in diverse human populations. Our specific aims include the following. Aim 1. To precisely characterize the contribution of genetic variation to lung cancer etiology. The genetic approach will include genotyping arrays and low pass whole genome sequencing (WGS) and imputation into the large multi-ethnic reference panels to generate the world largest resource for the discovery of lung cancer susceptibility variants influencing lung cancer risk across a range of ethnicities. Aim 2. To perform post- GWAS analysis to identify environmental and host-specific factors influencing lung cancer development. Mendelian randomization will enable the identification of causal molecular factors, such as biomarkers, influencing lung cancer, which facilitates developing screening programs for lung cancer (Projects 2 and 3. In addition, we will also use forward and reverse Mendelian randomization to partition the causal effects of biomarkers on lung cancer risk according to cis-acting genetic components, trans-acting components related to broader host-exposures and external factors. We will develop and use novel annotation methods to identify most likely causal variants to improve polygenic risk score development. Aim 3. To develop population-specific as well as multi-ancestry polygenic risk scores (PRSs) to refine risk estimation of LC for minority populations. In this aim, we will first build and characterize PRSs from genomic analyses to identify subsets of individuals at high risk for lung cancer development1. Second, to date, studies have focused on analysis in European-descent populations. Aim 4. To evaluate the impact of returning genetic risk factors information to motivate behavior change in diverse populations and to scrutinize direct translational implications of the genomic findings from our ancestry-specific and cross-ancestry studies. In this translational aim, we will engage both patients and healthcare providers by adopting a rapid cycle research approach to reduce the time lag from discovery to practice while accommodating evolving genomic evidence base. This project provides data to the other projects and plays a key role in developing translational applications to evaluate interest in communities for biomarker-informed recruitment for screening and risk reduction.