Abstract

Abstract Objectives: Leveraging whole exome and transcriptome data from large cancer datasets, we sought to develop a computational approach to nominate candidate genomic alterations that are associated with hot or cold tumor. We anticipate this tool will identify candidate novel drug targets and biomarkers for immunotherapy in cancer. Methods: The user selects a gene of interest (GOI) as input for the pipeline. The pipeline searches TCGA (The Cancer Genome Atlas) mutation and structural variant outputs to collect hits in the gene of interest. Each sample with an alteration in the GOI is annotated with the alteration’s predicted biological function (loss-of-function or LOF vs gain-of-function or GOF) using gene set enrichment analysis and pathway analysis from RNA sequencing. After annotating by sample, the alterations themselves are scored and recorded. Next, Quantiseq and Trust4 are employed to estimate features of the immune microenvironment in both the LOF and GOF samples. These results along with cancer type distributions, genomic position maps, and oncoplots are delivered to the user for further investigation. We are creating an online application to provide these results to the public. Simultaneously, a command line tool is being developed for application to any data source. Results: We will present findings for the pipeline using positive controls including genomic alterations in ADAR, MTAP, IDH1, and CD274 (PD-L1). Preliminarily, we identified candidate GOF mutations (n=81) in PD-L1 that have inflamed tumor immune microenvironments like those of samples with known GOF structural variations in PD-L1. These samples have an overall “hot” immune microenvironment with significantly (p<.05) increased M1 macrophages, increased expression of IFN-gamma, and decreased M2 macrophages. Conclusion: Currently there are no systematic approaches to interrogate individual genomic alterations and their association with an altered immune microenvironment. Our approach is pragmatic for any gene of interest, can be applied to any database, and identifies clinically actionable targets. This approach will identify heretofore unstudied connections between genomic alterations and immune microenvironment and support personalized drug development strategies in immuno-oncology. Citation Format: Raven Vella, Emily L. Hoskins, Julie W. Reeser, Michele R. Wing, Eric Samorodnitsky, Anoosha Paruchuri, Amy Smith, Leah Stein, Thuy Dao, Zachary Risch, Sameek Roychowdhury. A systematic approach for detection of tumor genomic alterations which alter the immune microenvironment. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6645.

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