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BIM expression in treatment-naive cancers predicts responsiveness to kinase inhibitors
Open accessPublished version of a preprint
Abstract
Cancers with specific genetic mutations are susceptible to selective kinase inhibitors. However, there is a wide spectrum of benefit among cancers harboring the same sensitizing genetic mutations. Herein, we measured apoptotic rates among cell lines sharing the same driver oncogene following treatment with the corresponding kinase inhibitor. There was a wide range of kinase inhibitor-induced apoptosis despite comparable inhibition of the target and associated downstream signaling pathways. Surprisingly, pretreatment RNA levels of the BH3-only pro-apoptotic BIM strongly predicted the capacity of EGFR, HER2, and PI3K inhibitors to induce apoptosis in EGFR-mutant, HER2-amplified, and PIK3CA-mutant cancers, respectively, but BIM levels did not predict responsiveness to standard chemotherapies. Furthermore, BIM RNA levels in EGFR-mutant lung cancer specimens predicted response and duration of clinical benefit from EGFR inhibitors. These findings suggest assessment of BIM levels in treatment-naïve tumor biopsies may indicate the degree of benefit from single-agent kinase inhibitors in multiple oncogene-addiction paradigms. Significance: In several oncogene-addiction paradigms, assessment of BIM RNA levels identifies those cancers that fail to have substantial apoptotic responses to kinase inhibitors. BIM RNA levels may be assessed in diagnostic cancer specimens to predict which patients will receive less benefit from single-agent kinase inhibitors. Cancer Discovery: 1(4); 352–65. ©2011 AACR. Read the Commentary on this article by Yoshida and Haura, p. 289 This article is highlighted in the In This Issue feature, p. 275
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“Previous studies have shown that high levels of pretreatment BIM can predict the apoptotic response of oncogene-addicted cancers to their cognate kinase inhibitors (Faber et al., 2011).”
From A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution (2017) · cites this paper as Faber et al., 2011
In the citing paper
“Patients harbouring BIM deletion polymorphisms23 or patients with low-to-intermediate levels of BIM mRNA18 are associated with reduced clinical efficacy when treated with EGFR-TKIs.25”
From Mechanisms of resistance to EGFR-targeted drugs: lung cancer (2016) · cites this paper as [25]
In the citing paper
“Indeed, we observed that levels of the pro-apoptotic BH3-only Bcl2 family member, BIM, are predictive of response to targeted therapy in EGFR mutant lung cancers, HER2-amplified breast cancers and PIK3CA mutant cancers (Faber et al., 2011).”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
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“In this study, although erlotinib or lapatinib inhibited EGFR and HER2 and downstream signaling in EGFR mutant and HER2-amplified cancers, respectively, only those cell lines with high levels of BIM underwent marked apoptosis.”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
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“BIM protein normally is induced following inhibition of EGFR and HER2 in these cancers.”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
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Apoptosis Initiated When BH3 Ligands Engage Multiple Bcl-2 Homologs, Not Bax or Bak
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Metadata
- Authors
- Faber, A. C., Corcoran, R. B., Ebi, H., Sequist, L. V., Waltman, B. A., Chung, E., Incio, J., Digumarthy, S. R., Pollack, S. F., Song, Y., Muzikansky, A., Lifshits, E., Roberge, S., Coffman, E. J., Benes, C. H., Gómez, H. L., Baselga, J., Arteaga, C. L., Rivera, M. N., Dias-Santagata, D., Jain, R. K., & Engelman, J. A.
- Affiliations
- Harvard University (US)
- Authors' Affiliations: 1Pathology and 2Radiology, Massachusetts General Hospital, Boston; 3Massachusetts General Hospital Cancer Center, Boston; 4Department of Medicine, Harvard Medical School, Boston; 5Radiation Oncology, Steele Lab for Tumor Biology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts; 6Department of Medicine, 7Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee; 8Instituto Nacional de Enfermedades Neoplásicas, Lima, Perú
- Corresponding author
- Engelman, Jeffrey A.
- ORCID
- Venue
- Cancer Discovery
- Published
- 2011-09-01
- Volume
- 1
- Issue
- 4
- Pages
- 352-365
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC3229203
- OpenAlex
- W2117986690
- Cited by
- 283
- References
- 50
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 4 · 2023: 11 · 2022: 13 · 2021: 15 · 2020: 15 · 2019: 8 · 2018: 27 · 2017: 26 · 2016: 27 · 2015: 31 · 2014: 34 · 2013: 33 · 2012: 22
- FWCI
- 24.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Vanderbilt University
- Vanderbilt-Ingram Cancer Center
- National Cancer Institute (P50CA127003, R01CA080195, R01CA140594, P50CA090578, P01CA080124, P20CA090578, R01CA135257, K08CA120060, P50CA098131, R01CA137008)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Cell death mechanisms and regulation
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Keywords
- building information modeling, BH3-only proteins, kinase inhibitors, predictive biomarkers, apoptosis, EGFR inhibitors, HER2 inhibitors, PI3K inhibitors, oncogene addiction, EGFR-mutant lung cancer, PIK3CA mutation, treatment-naive tumors, drug response prediction
- MeSH terms
- Bcl-2-Like Protein 11, Phosphoinositide-3 Kinase Inhibitors, Animals, Female, Humans, Lung Neoplasms, Membrane Proteins, Mice, Nude, Oncogenes, Proto-Oncogene Proteins, Retrospective Studies, Cohort Studies, Signal Transduction, Apoptosis, Receptor, ErbB-2, Erb-b2 Receptor Tyrosine Kinases, Phosphatidylinositol 3-Kinases, Cell Line, Tumor, Protein Kinase Inhibitors, Apoptosis Regulatory Proteins, BH3 Interacting Domain Death Agonist Protein, Mice, ErbB Receptors
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