| Literature DB >> 35074756 |
Igor Odintsov1,2, Michael V Ortiz3, Inna Khodos4, Marissa S Mattar4, Allan J W Lui1, Shinji Kohsaka1,2, Elisa de Stanchina4, Julia L Glade Bender3, Marc Ladanyi1,2, Romel Somwar1,2.
Abstract
Kinase fusions have been identified in a growing subset of sarcomas, but a lack of preclinical models has impeded their functional analysis as therapeutic targets in the sarcoma setting. In this study, we generated models of sarcomas bearing kinase fusions and assessed their response to molecularly targeted therapy. Immortalized, untransformed human mesenchymal stem cells (HMSC), a putative cell of origin of sarcomas, were modified using CRISPR-Cas9 to harbor a RET chromosomal translocation (HMSC-RET). In parallel, patient-derived models of RET- and NTRK-rearranged sarcomas were generated. Expression of a RET fusion activated common proliferation and survival pathways and transformed HMSC cells. The HMSC-RET models displayed similar behavior and response to therapy as the patient-derived counterparts in vitro and in vivo. Capicua (CIC)-mediated suppression of negative MAPK pathway regulators was identified as a potential mechanism by which these sarcomas compensate for RET or NTRK inhibition. This CIC-mediated feedback reactivation was blocked by coinhibition of the MAPK pathway and RET or NTRK in the respective models. Importantly, the combination of RET and ERK inhibitors was more effective than single agents at blocking tumor growth in vivo. This work offers new tools and insights to improve targeted therapy approaches in kinase-addicted sarcomas and supports upfront combination therapy to prolong responses. SIGNIFICANCE: Novel models of kinase-rearranged sarcomas show that MAPK pathway feedback activation dampens responses to tyrosine kinase inhibitors, revealing the potential of combinatorial therapies to combat these tumors. ©2022 The Authors; Published by the American Association for Cancer Research.Entities:
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Year: 2022 PMID: 35074756 PMCID: PMC8930606 DOI: 10.1158/0008-5472.CAN-21-1397
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 13.312