| Literature DB >> 34171264 |
Ariella B Hanker1, Benjamin P Brown2, Jens Meiler3, Arnaldo Marín4, Harikrishna S Jayanthan5, Dan Ye6, Chang-Ching Lin6, Hiroaki Akamatsu6, Kyung-Min Lee7, Sumanta Chatterjee6, Dhivya R Sudhan6, Alberto Servetto6, Monica Red Brewer5, James P Koch8, Jonathan H Sheehan9, Jie He10, Alshad S Lalani11, Carlos L Arteaga12.
Abstract
Activating mutations in HER2 (ERBB2) drive the growth of a subset of breast and other cancers and tend to co-occur with HER3 (ERBB3) missense mutations. The HER2 tyrosine kinase inhibitor neratinib has shown clinical activity against HER2-mutant tumors. To characterize the role of HER3 mutations in HER2-mutant tumors, we integrate computational structural modeling with biochemical and cell biological analyses. Computational modeling predicts that the frequent HER3E928G kinase domain mutation enhances the affinity of HER2/HER3 and reduces binding of HER2 to its inhibitor neratinib. Co-expression of mutant HER2/HER3 enhances HER2/HER3 co-immunoprecipitation and ligand-independent activation of HER2/HER3 and PI3K/AKT, resulting in enhanced growth, invasiveness, and resistance to HER2-targeted therapies, which can be reversed by combined treatment with PI3Kα inhibitors. Our results provide a mechanistic rationale for the evolutionary selection of co-occurring HER2/HER3 mutations and the recent clinical observations that HER3 mutations are associated with a poor response to neratinib in HER2-mutant cancers.Entities:
Keywords: HER2; HER3; PI3K; Rosetta; breast cancer; molecular dynamics; neratinib; personalized structural biology; precision oncology
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Year: 2021 PMID: 34171264 PMCID: PMC8355076 DOI: 10.1016/j.ccell.2021.06.001
Source DB: PubMed Journal: Cancer Cell ISSN: 1535-6108 Impact factor: 38.585