Abstract 11: Analysis of 30 million tumor time course reveals that inactivating tumor suppressors produces complex gene-specific, time-dependent growth dynamics
Authors: Severson Alissa L. , Juan Joseph , Sebastian Lafia , Tran Vy , Nie Wensheng , Lai Ian , Wall Gregory D. , Winslow Monte M. , Petrov Dmitri A. , Winters Ian P. , Rosen Michael J. 
Published: April 2023

Abstract
Aberrant growth driven by genomic alterations is the defining feature of cancer, yet the temporal dynamics of this process are poorly understood. Previous efforts to model tumor growth relied on patient data or in vivo transplantation models. However, low sample sizes and sparse time points constrained these studies to simple, deterministic models that were underpowered to quantify the effect of different genotypes on tumor growth. We previously combined CRISPR/Cas9-mediated gene editing, tumor barcoding, and ultra-deep barcode sequencing with genetically engineered mouse models of human lung cancer to enable precise, high-throughput quantification of tumor sizes across many tumor genotypes in parallel. Here, we leverage this platform to systematically assay the effect of inactivating 30 known and putative tumor suppressor genes on the growth of KRASG12D_ driven lung tumors. Analyzing nearly 30 million clonal tumors within 200 mice across 19 time points between 3 and 37 weeks post-tumor initiation provided an unprecedented level of granularity and unique opportunity to evaluate the effect of tumor suppressor genotype on early lung tumor growth over time. For all tumors, we find the relative overall growth rate of tumor burden decreases monotonically with time, or alternatively the doubling time increases. Excluding the first two time points, tumor burden is approximately linear on a log-log scale, suggesting that growth scales as a power of time. For tumors driven only by oncogenic KRAS, tumor burden is approximately quadric in time. When compared to KRAS-only tumors, tumor suppressors modify tumor burden with a variety of strategies, either altering tumor number, tumor size, or a combination of both. Of the 30 tumor suppressors assayed, 8 produced a striking phenotype wherein growth during the first 10 weeks is rapid, resulting in as much as 10-fold greater tumor burden than KRAS-only tumors, but subsequently slows. Remarkably, these 8 genes included every tumor suppressor in our panel that is predicted to activate RAS signaling and downstream effector pathways (KRASWT, NF1, PTEN, STK11, and TSC1). This suggests that signaling through these key pathways limits cancer growth initially, but that this advantage lessens over time. Interestingly, inactivation of 2 tumor suppressor genes that are frequently mutated in human lung adenocarcinoma, CDKN2A and TP53, provides a sustained advantage through later time points, up to 20 weeks after tumor initiation, despite a more limited early advantage relative to other genes. Beyond characterizing the dynamics of tumor burden, the full distributions of tumor sizes of each genotype at each time point allows for quantitative stochastic modeling of the growth process. Together these results provide a detailed description of the effects of tumor suppressor genotype on the complex dynamics of early lung tumor growth.
Citation Format: Alissa L. Severson, Joseph Juan, Lafia Sebastian, Vy Tran, Wensheng Nie, Ian Lai, Gregory D. Wall, Monte M. Winslow, Dmitri A. Petrov, Ian P. Winters, Michael J. Rosen. Analysis of 30 million tumor time course reveals that inactivating tumor suppressors produces complex gene-specific, time-dependent growth dynamics [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 11.