克拉斯
癌症研究
胰腺癌
生物
抗性(生态学)
癌症
生物信息学
结直肠癌
生态学
遗传学
作者
Julien Dilly,Megan T. Hoffman,Laleh Abbassi,Ziyue Li,Francesca Paradiso,Brendan D. Parent,Connor J. Hennessey,Alexander C. Jordan,Micaela Morgado,Shatavisha Dasgupta,Giselle A. Uribe,An-Dao Yang,Kevin S. Kapner,Felix P. Hambitzer,Qiang Li,Hanrong Feng,Jacob Geisberg,Junning Wang,Kyle E. Evans,Hengyu Lyu
出处
期刊:Cancer Discovery
[American Association for Cancer Research]
日期:2024-07-05
卷期号:14 (11): 2135-2161
被引量:128
标识
DOI:10.1158/2159-8290.cd-24-0177
摘要
Abstract KRAS inhibitors demonstrate clinical efficacy in pancreatic ductal adenocarcinoma (PDAC); however, resistance is common. Among patients with KRASG12C-mutant PDAC treated with adagrasib or sotorasib, mutations in PIK3CA and KRAS, and amplifications of KRASG12C, MYC, MET, EGFR, and CDK6 emerged at acquired resistance. In PDAC cell lines and organoid models treated with the KRASG12D inhibitor MRTX1133, epithelial-to-mesenchymal transition and PI3K-AKT-mTOR signaling associate with resistance to therapy. MRTX1133 treatment of the KrasLSL-G12D/+; Trp53LSL-R172H/+; p48-Cre (KPC) mouse model yielded deep tumor regressions, but drug resistance ultimately emerged, accompanied by amplifications of Kras, Yap1, Myc, Cdk6, and Abcb1a/b, and co-evolution of drug-resistant transcriptional programs. Moreover, in KPC and PDX models, mesenchymal and basal-like cell states displayed increased response to KRAS inhibition compared to the classical state. Combination treatment with KRASG12D inhibition and chemotherapy significantly improved tumor control in PDAC mouse models. Collectively, these data elucidate co-evolving resistance mechanisms to KRAS inhibition and support multiple combination therapy strategies. Significance: Acquired resistance may limit the impact of KRAS inhibition in patients with PDAC. Using clinical samples and multiple preclinical models, we define heterogeneous genetic and non-genetic mechanisms of resistance to KRAS inhibition that may guide combination therapy approaches to improve the efficacy and durability of these promising therapies for patients. See related commentary by Marasco and Misale, p. 2018
科研通智能强力驱动
Strongly Powered by AbleSci AI