Inhibiting Pathways Predicted From a Steroid Hormone Gene Signature Yields Synergistic Antitumor Effects in NSCLC

Abdulaziz A. Almotlak, Mariya Farooqui, Jill M. Siegfried

Research output: Contribution to journalArticle

4 Scopus citations

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. 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. 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. 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.

Original languageEnglish (US)
Pages (from-to)62-79
Number of pages18
JournalJournal of Thoracic Oncology
Volume15
Issue number1
DOIs
StatePublished - Jan 2020

Keywords

  • Estrogen signaling
  • Human EGFRs
  • NSCLC
  • Prediction Analysis of Microarray 50 signature
  • Targeted therapy

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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