Abstract 1840: Whole-exome somatic mutation analysis of mouse cancer models and implications for preclinical immunomodulatory drug development
Authors: Zeitouni Bruno , Tschuch Cordula , Davis Jason M. , Peille Anne-Lise , Raeva Yana , Landesfeind Manuel , Barnes Sheri , Schüler Julia B. 
Published: July 2017

Abstract
Experimental tumors raised in rodents represent an important preclinical tool to develop innovative anticancer compounds before clinical testing. Amongst others such models include solid tumors raised in syngeneic fully immunocompetent hosts and tumors spontaneously growing in genetically engineered mice (GEM) and derivate thereof. These model platforms have gained additional value since the manipulation of the immune system to fight cancer has led to tangible benefits for cancer patients. In the current study, we analyzed somatic mutation profiles from whole-exome sequencing (WES) data in a panel of 14 different mouse models covering 6 major cancer types. 4 models were GEM-derived, all other lines were developed by injection of established cell lines into the corresponding mouse strain. In parallel, these models were evaluated for their sensitivity towards checkpoint inhibitors (α-CTLA-4, α-PD-1 or α-PDL-1) in mono- or combined therapy with cytostatic and/or targeted agents.WES achieved an average-of-coverage of 165X in tumor models and normal DNA. A median mutation rate of 34 somatic mutations (m)/MB was detected, ranging from 7 m/MB (GEM derived NSCLC model KP) to 328 m/MB (syngeneic NSCLC line Lewis Lung) in exons. Mutation rates were markedly lower in GEM-derived models as in syngeneic lines (median of 9 vs 43 m/MB). This reflects very well the different underlying carcinogenic mechanism of these two types of models. The cross-comparison of tissue-transplants vs cell lines from GEM-derived model KP revealed that 75% of the mutations found in the primary KP could also be detected in the corresponding cell lines KP1 and KP4. Of note, the mutation count increased 1.3- (KP4) and 2.9-fold (KP1) during cell line establishment. Every model depicted a distinct profile against modulators of the immune system dividing the panel in responders and non-responders. In our hands no significant correlation could be determined between mutational load and sensitivity towards checkpoint inhibition in vivo. This might be related to the fact that the dataset was not broad enough and the number of models per entity was too small, rendering the subtype analysis within the panel not feasible. However, a strong tendency was observed when investigating the colon lines Colon26, CT26 and MC38 showing best response to the combination of PD-1+CTLA-4 inhibitors and in parallel the highest mutation rates (52, 64 and 59 m/MB, respectively) compared to non-responders B16-F10, CloudmanS91, 4T1 and KP1 (23 m/MB on average). Mouse models of cancer are a relevant tool for preclinical studies specifically for immuno-oncology. The molecular characterization of these models will help to optimize their use in drug discovery. They will support the development of innovative drugs and indentification of biomarkers to classify the patient cohort profiting the most from these new compounds.
Citation Format: Bruno Zeitouni, Cordula Tschuch, Jason M. Davis, Anne-Lise Peille, Yana Raeva, Manuel Landesfeind, Sheri Barnes, Julia B. Schüler. Whole-exome somatic mutation analysis of mouse cancer models and implications for preclinical immunomodulatory drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1840. doi:10.1158/1538-7445.AM2017-1840