Abstract 291: Functionalizing novel modulators in lung cancer

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Abstract Lung cancer is the leading cause of cancer mortality globally, with lung adenocarcinoma being the most prevalent subtype. The discovery of driver mutations has paved the way for the use of targeted therapy, notably EGFR inhibitors, in the management of advanced disease. However, the effectiveness of targeted therapy is limited firstly by the eventual development of treatment resistance, and secondly by the sizeable percentage of cases in which the driver mutations remain unknown. Furthermore, lung adenocarcinoma (LUAD) in Asians is known to exhibit a molecular profile distinct from that in Caucasians, yet the majority of existing cohort studies have been focused on the latter. To address this gap, we and our collaborators have spearheaded the largest Asian LUAD cohort study, comprising genomic and transcriptomic data from 305 patients. The MutSigCV and 20/20+ driver prediction algorithms were applied to whole exome sequencing data from our cohort and yielded seven novel candidate drivers that had not been previously implicated in LUAD. We proceeded to functionally validate these drivers by overexpressing or knocking them down in patient-derived transformed lung cell lines and observing their effects on tumorigenicity via a number of in vitro and in vivo tumorigenicity assays. We have identified a poly (ADP-ribose) polymerase (PARP) gene, which was mutated at a relatively high frequency within our cohort, and show that PARP is crucial for modulating the tumorigenicity of lung cancer cells. In LUAD patients, reduced PARP expression levels were correlated with poorer prognosis, suggesting a putative tumor suppressor role. We further observed a loss of PARP copy number both within our cohort as well as the Caucasian The Cancer Genome Atlas (TCGA) LUAD cohort. We are now working to dissect the underlying mechanisms and explore PARP's clinical utility. This work illustrates the use of a platform to systematically model genetics in patient-derived models to study novel driver functions. Citation Format: Yi Fei Lee, Ju Yuan, Edwin Lim, Jianbin Chen, Weiwei Zhai, Nguan Soon Tan, Wai Leong Tam. Functionalizing novel modulators in lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 291.