Abstract LB146: Multi Omics analyses identified novel loci and genes for lung cancer risk among European Descendants
Authors: Xu Shuai , Yang Yaohua , Zhao Tianying , Shi Jiajun , Ping Jie , Wen Wanqing , Cai Hui , Guo Xingyi , Tao Ran , Shu Xiao-Ou , Zheng Wei , Long Jirong , Cai Qiuyin 
Published: April 2024

Abstract
Introduction Genome-wide association studies (GWAS) have identified &gt;60 genomic loci for lung cancer risk. However, causal genes and the underlying biological mechanisms for most of these loci remain unknown. Therefore, we conducted a multi-omics study to identify lung cancer susceptibility genes.
Method We first conducted a transcriptome-wide association study (TWAS) using S-PrediXcan framework. Whole transcriptome data from adjacent-normal lung tissue samples and genomic data from 304 European-ancestry lung cancer patients were used to build genetic prediction models for expression levels of protein-coding genes and lincRNAs. The prediction models were then applied to GWAS meta-analysis results for lung cancer with 39,363 cases and 621,480 controls of European descents from TRICL-ILCCO, the UK Biobank, and FinnGen. COJO was used to assess whether those significant genes were independent of proximal (±1.5 Mb) GWAS-identified risk variants. To replicate our TWAS-identified genes, we used data from GTEx version 8 normal lung tissue (N=444) to build imputation models and then run association analyses. We acquired gene (N=107) and protein expression data (N=111) from tumor and matched adjacent-normal lung tissues from European-ancestry participants in the Clinical Proteomic Tumor Analysis Consortium. Paired Wilcoxon rank sum tests were then conducted to assess whether identified genes and their corresponding proteins were expressed differentially.
Results Out of 18,850 genes (read count &gt;6 and TPM &gt;0.1 in at least 20% samples), 6,754 protein-coding genes and 802 lincRNAs were predicted reliably using genetic variants (R&gt;0.1 and P&lt;0.05). Among them, genetically proxied expression levels of 24 genes located at 15 loci were significantly associated with lung cancer risk at a Bonferroni adjusted P &lt;0.05. Four genes were located at four novel loci, including SERF1A at 5q13.2, SMIM33 at 5q31.2, MUC5B at 11p15.5, and RASSF10 at 11p15.2. Six putative candidate genes, namely H4C13, HCP5B, STN1, COPS2, SKIV2L, and LINC00243 resided in previously GWAS-identified lung cancer loci but have not been reported. Of these six genes, SKIV2L (Padjust=1.49e-5) and LINC00243 (Padjust=3.47e-5) were independently associated with lung cancer risk even after adjusting for GWAS-identified variants. Among 24 identified genes, 16 showed a consistent significant association with lung cancer risk (p&lt;0.05) based on the prediction models built using GTEx data. Of ten unreported or novel genes, MUC5B, SMIM33, SERF1A, STN1, COPS2, and LINC00243 showed differential gene expression at P &lt;0.05 and consistent association direction with TWAS results. Three proteins, STN1, COPS2, and SKIV2L, showed differential expression in tumor and adjacent-normal tissue at P&lt;0.05, which is consistent with our TWAS direction.
Conclusion Our findings offer novel insights into lung cancer carcinogenesis by uncovering new genes and loci.
Citation Format: Shuai Xu, Yaohua Yang, Tianying Zhao, Jiajun Shi, Jie Ping, Wanqing Wen, Hui Cai, Xingyi Guo, Ran Tao, Xiao-Ou Shu, Wei Zheng, Jirong Long, Qiuyin Cai. Multi Omics analyses identified novel loci and genes for lung cancer risk among European Descendants [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB146.