Abstract B17: Modeling genomic complexity of colorectal cancer using multigenic Drosophila models

Abstract

Abstract Colorectal cancer (CRC) is a leading cause of cancer related death worldwide, with an estimated 53,000 deaths in 2019 in the US alone. Despite significant progress made in elucidating mechanisms of tumor initiation and progression, targeted therapies have shown limited efficacy for inoperable or metastatic CRC tumors, especially KRAS or BRAF mutant tumors, which account for more than half (~55%) of CRC tumors. Several targeted inhibitors have failed clinical trials for CRC despite proving effective in preclinical CRC studies and other cancer types. A potential reason for this resistance is the presence of several other mutations in the tumors. CRC patient tumors present significant genetic heterogeneity with mutations in genes in several other major signaling pathways. We address the challenge of genetic complexity by constructing a population of multigenic Drosophila CRC models incorporating 7-15 gene alterations in each line. This population of CRC fly lines models the genetic heterogeneity of CRC by basing the genotype of each fly line on an individual patient’s tumor genotype, with a focus on Ras mutant tumors. Our work has identified multiple combinations of FDA-approved compounds that have shown efficacy in some complex multigenic models and not others. Bangi et al. (2019) discuss the results from the first human CRC patient to be treated with the recommended combination identified from screening the patient-matched fly model. My work aims to uncover the mechanisms of response and resistance presented by the population of heterogeneous CRC genotypes. My results show that there is variability in therapeutic response between different patient genotypes, even when they contain the same known CRC cancer drivers (such as Ras, p53, APC, etc.). I am investigating the downstream transcriptional and signaling networks activated by these genotypes to assess their contribution to resistance or response to specific therapeutic agents. Citation Format: Sindhura Gopinath, Ross Cagan, Eric Schadt. Modeling genomic complexity of colorectal cancer using multigenic Drosophila models [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B17.