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Inhibiting Pathways Predicted From a Steroid Hormone Gene Signature Yields Synergistic Antitumor Effects in NSCLC.
- Source :
-
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer [J Thorac Oncol] 2020 Jan; Vol. 15 (1), pp. 62-79. Date of Electronic Publication: 2019 Oct 10. - Publication Year :
- 2020
-
Abstract
- Introduction: Mounting evidence supports a role for estrogen signaling in NSCLC progression. We previously reported a seven-gene signature that predicts prognosis in estrogen receptor β positive (ERβ+) NSCLC. The signature defines a network comprised of ER and human EGFR-2/3 (HER2/HER3) signaling.<br />Methods: We tested the efficacy of combining the pan-HER inhibitor, dacomitinib, with the estrogen antagonist, fulvestrant, in ERβ+ NSCLC models with differing genotypes. We assessed the potency of this combination on xenograft growth and survival of host mice, and the ability to reverse the gene signature associated with poor outcome.<br />Results: Synergy was observed between dacomitinib and fulvestrant in three human ERβ+ NSCLC models: 201T (wild-type EGFR), A549 (KRAS mutant), and HCC827 (EGFR 19 deletion) with combination indices of 0.1-0.6. The combination, but not single agents, completely reversed the gene signature associated with poor prognosis in a mechanism that is largely mediated by activator protein 1 downregulation. In vivo, the combination also induced tumor regression and reversed the gene signature. In HCC827 xenografts treated with the combination, survival of mice was prolonged after therapy discontinuation, tumors that recurred were less aggressive, and two mechanisms of HER inhibitor resistance involving c-Met activation and PTEN loss were blocked.<br />Conclusions: The combination of an ER blocker and a pan-HER inhibitor provides synergistic efficacy in different models of ERβ+ NSCLC. Our data support the use of this combination clinically, considering its ability to induce potent antitumor effects and produce a gene signature that predicts better clinical outcomes.<br /> (Copyright © 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Animals
Cell Line, Tumor
Drug Resistance, Neoplasm
Fulvestrant pharmacology
Mice
Neoplasm Recurrence, Local
Signal Transduction
Xenograft Model Antitumor Assays
Carcinoma, Non-Small-Cell Lung drug therapy
Carcinoma, Non-Small-Cell Lung genetics
Lung Neoplasms drug therapy
Lung Neoplasms genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1556-1380
- Volume :
- 15
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
- Publication Type :
- Academic Journal
- Accession number :
- 31606604
- Full Text :
- https://doi.org/10.1016/j.jtho.2019.09.195