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Pan-Cancer Landscape and Analysis of ERBB2 Mutations Identifies Poziotinib as a Clinically Active Inhibitor and Enhancer of T-DM1 Activity
Open accessAbstract
We characterized the landscape and drug sensitivity of ERBB2 (HER2) mutations in cancers. In 11 datasets (n = 211,726), ERBB2 mutational hotspots varied across 25 tumor types. Common HER2 mutants yielded differential sensitivities to eleven EGFR/HER2 tyrosine kinase inhibitors (TKIs) in vitro, and molecular dynamics simulations revealed that mutants with a reduced drug-binding pocket volume were associated with decreased affinity for larger TKIs. Overall, poziotinib was the most potent HER2 mutant-selective TKI tested. Phase II clinical testing in ERBB2 exon 20-mutant non-small cell lung cancer resulted in a confirmed objective response rate of 42% in the first 12 evaluable patients. In pre-clinical models, poziotinib upregulated HER2 cell-surface expression and potentiated the activity of T-DM1, resulting in complete tumor regression with combination treatment.
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“Clinically, second-generation TKIs have been associated with inhibition of wild-type EGFR and related adverse events15,35,36; however, most second-generation TKIs are dosed at the maximum tolerated doses, resulting in plasma concentrations 10–100 fold greater than concentrations necessary for inhibiting PACC mutations.”
From Structure-based classification predicts drug response in EGFR-mutant NSCLC (2021) · cites this paper as [36]
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Metadata
- Authors
- Robichaux, J. P., Elamin, Y. Y., Vijayan, R. S. K., Nilsson, M. B., Hu, L., He, J., Zhang, F., Pisegna, M., Poteete, A., Sun, H., Li, S., Chen, T., Han, H., Negrao, M. V., Ahnert, J. R., Diao, L., Wang, J., Le, X., Meric-Bernstam, F., Routbort, M., Roeck, B., Yang, Z., Raymond, V. M., Lanman, R. B., Frampton, G. M., Miller, V. A., Schrock, A. B., Albacker, L. A., Wong, K.-K., Cross, J. B., & Heymach, J. V.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- NYU Langone Health (US)
- Spectrum Pharmaceuticals (United States) (US)
- Guardant (United States) (US)
- Foundation Medicine (United States) (US)
- Corresponding author
- Heymach, John V.
- ORCID
- Robichaux, Jacqulyne P.
- Elamin, Yasir Y.
- Vijayan, R.S.K.
- Nilsson, Monique B.
- He, Junqin
- Zhang, Fahao
- Poteete, Alissa
- Sun, Huiying
- Li, Shuai
- Chen, Ting
- Han, Han
- Negrao, Marcelo Vailati
- Diao, Lixia
- Wang, Jing
- Le, Xiuning
- Raymond, Victoria M.
- Lanman, Richard B.
- Frampton, Garrett M.
- Miller, Vincent A.
- Schrock, Alexa B.
- Albacker, Lee A.
- Wong, Kwok-kin
- Cross, Jason B.
- Heymach, John V.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 36
- Issue
- 4
- Pages
- 444-457.e7
- ISSN
- 1535-6108 (ISSN-L)
- PMC
- PMC6944069
- OpenAlex
- W2977889895
- Cited by
- 242
- References
- 66
- Citations by year
- 2026: 21 · 2025: 34 · 2024: 33 · 2023: 40 · 2022: 43 · 2021: 43 · 2020: 28
- FWCI
- 12.00
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-03-16)
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute
- Topics
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- ERBB2 mutations, HER2, poziotinib, tyrosine kinase inhibitors, trastuzumab emtansine, non-small cell lung cancer, drug sensitivity, molecular dynamics simulation, drug-binding pocket, combination therapy
- MeSH terms
- Antineoplastic Agents, Immunological, Progression-Free Survival, Ado-Trastuzumab Emtansine, Adult, Animals, Antineoplastic Combined Chemotherapy Protocols, Disease Models, Animal, DNA Mutational Analysis, Drug Synergism, Female, Humans, Male, Mice, Transgenic, Mutation, Neoplasms, Quinazolines, Erb-b2 Receptor Tyrosine Kinases, Drug Resistance, Neoplasm, Protein Kinase Inhibitors, Mice, Datasets as Topic
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