Abstract 1172: Oncogenic context shapes the fitness landscape of tumor suppression

Abstract

Abstract Cancer progression is a quintessential example of a walk on an adaptive fitness landscape, with tumor growth depending on the cooperation of multiple driver mutations. While sequencing of tens of thousands of clinical samples has revealed a vast set of cancer drivers, far less is known about the interactions of oncogene-tumor suppressor pairs. Due to patient-level selection bias, confounding biological factors and limited sample sizes, a map of these interactions cannot be generated from human data alone and, instead, requires direct perturbational experiments and functional genomics approaches. Here, we model and quantify tumors using an autochthonous mouse platform and Tubaseq, which integrates barcoded lentiviral-sgRNA/Cre vectors and high-throughput barcode sequencing to uncover the number of neoplastic cells in each tumor of each genotype. Across four oncogenic contexts—KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R—we analyzed >10,000,000 tumors to estimate the tumorigenesis potential of the oncogene alone as well as the effect of inactivating 28 tumor suppressor genes. We discovered that despite KRAS G12D producing >10x the tumors as G12C, tumor suppressor inactivations provide similar growth effects on both backgrounds. In contrast, although the intrinsic abilities of BRAF V600E and EGFR L858R to drive tumor development fall within the range of the KRAS variants, tumor suppressive effects are categorically different in the context of each oncogene. Many tumor suppressors show clear sign epistasis with the oncogenes, whereby inactivation is advantageous in one context and neutral or deleterious in another. Inactivation of some of the strongest tumor suppressors (e.g., Lkb1, Setd2, and Kmt2d) in KRAS-driven tumors strongly decreases tumor growth in the presence of oncogenic EGFR. While some of these epistatic effects are consistent with a textbook understanding of the RAS pathway, most cannot be predicted based on the linear oncogenic EGFR → KRAS → BRAF pathway model. Analyses of clinical genomics data from AACR Project GENIE confirm that high rates of passenger mutations in KRAS- and BRAF-driven lung tumors, among other factors, prevent the discovery of these interactions from human data alone. However, for EGFR-mutant lung cancers, which are less confounded by high mutational burden, the rates of coincident tumor suppressor mutation are highly correlated with tumor growth effects in our in vivo model. Thus, we find via causal experiments that the landscape of tumor suppression is highly dependent on oncogenic context, with a minority of tumor suppressive effects robust to changes in the oncogene. These findings suggest that the utility of a specific cancer mutation as a prognostic or predictive biomarker of patient outcomes will be dependent on coincident mutations in the tumor and highlight the utility of high-throughput, quantitative autochthonous mouse models in advancing our understanding of cancer biology. Citation Format: Lily M. Blair, Joseph M. Juan, Lafia Sebastian, Vy B. Tran, Wensheng Nie, Gregory D. Wall, Mehmet Gerceker, Ian K. Lai, Edwin A. Apilado, Gabriel Grenot, David Amar, Giorgia Foggetti, Mariana Do Carmo, Zeynep Ugur, Debbie Deng, Alex Chenchik, Maria Paz Zafra, Lukas E. Dow, Katerina Politi, Jonathan J. MacQuitty, Dmitri A. Petrov, Monte M. Winslow, Michael J. Rosen, Ian P. Winters. Oncogenic context shapes the fitness landscape of tumor suppression [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 1172.