A transcriptionally definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to Hsp90 inhibition

Kevin Shee, Jason D. Wells, Matthew Ung, Riley A. Hampsch, Nicole A. Traphagen, Wei Yang, Stephanie C. Liu, Megan A. Zeldenrust, Liewei Wang, Krishna R. Kalari, Jia Yu, Judy C. Boughey, Eugene Demidenko, Arminja N. Kettenbach, Chao Cheng, Matthew P. Goetz, Todd W. Miller

Research output: Contribution to journalArticle

Abstract

Purpose: We hypothesized that integrated analysis of cancer types from different lineages would reveal novel molecularly defined subgroups with unique therapeutic vulnerabilities. On the basis of the molecular similarities between subgroups of breast and ovarian cancers, we analyzed these cancers as a single cohort to test our hypothesis. Experimental Design: Identification of transcriptional subgroups of cancers and drug sensitivity analyses were performed using mined data. Cell line sensitivity to Hsp90 inhibitors (Hsp90i) was tested in vitro. The ability of a transcriptional signature to predict Hsp90i sensitivity was validated using cell lines, and cell line- and patient-derived xenograft (PDX) models. Mechanisms of Hsp90i sensitivity were uncovered using immunoblot and RNAi. Results: Transcriptomic analyses of breast and ovarian cancer cell lines uncovered two mixed subgroups comprised primarily of triple-negative breast and multiple ovarian cancer subtypes. Drug sensitivity analyses revealed that cells of one mixed subgroup are significantly more sensitive to Hsp90i compared with cells from all other cancer lineages evaluated. A gene expression classifier was generated that predicted Hsp90i sensitivity in vitro, and in cell line- and PDXs. Cells from the Hsp90i-sensitive subgroup underwent apoptosis mediated by Hsp90i-induced upregulation of the proapoptotic proteins Bim and PUMA. Conclusions: Our findings identify Hsp90i as a potential therapeutic strategy for a transcriptionally defined subgroup of ovarian and breast cancers. This study demonstrates that gene expression profiles may be useful to identify therapeutic vulnerabilities in tumor types with limited targetable genetic alterations, and to identify molecularly definable cancer subgroups that transcend lineage.

Original languageEnglish (US)
Pages (from-to)159-170
Number of pages12
JournalClinical Cancer Research
Volume26
Issue number1
DOIs
StatePublished - Jan 1 2020

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Triple Negative Breast Neoplasms
Ovarian Neoplasms
Cell Line
Neoplasms
Breast Neoplasms
RNA Interference
Transcriptome
Heterografts
Pharmaceutical Preparations
Breast
Research Design
Up-Regulation
Therapeutics
Apoptosis
Gene Expression

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

A transcriptionally definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to Hsp90 inhibition. / Shee, Kevin; Wells, Jason D.; Ung, Matthew; Hampsch, Riley A.; Traphagen, Nicole A.; Yang, Wei; Liu, Stephanie C.; Zeldenrust, Megan A.; Wang, Liewei; Kalari, Krishna R.; Yu, Jia; Boughey, Judy C.; Demidenko, Eugene; Kettenbach, Arminja N.; Cheng, Chao; Goetz, Matthew P.; Miller, Todd W.

In: Clinical Cancer Research, Vol. 26, No. 1, 01.01.2020, p. 159-170.

Research output: Contribution to journalArticle

Shee, K, Wells, JD, Ung, M, Hampsch, RA, Traphagen, NA, Yang, W, Liu, SC, Zeldenrust, MA, Wang, L, Kalari, KR, Yu, J, Boughey, JC, Demidenko, E, Kettenbach, AN, Cheng, C, Goetz, MP & Miller, TW 2020, 'A transcriptionally definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to Hsp90 inhibition', Clinical Cancer Research, vol. 26, no. 1, pp. 159-170. https://doi.org/10.1158/1078-0432.CCR-18-2213
Shee, Kevin ; Wells, Jason D. ; Ung, Matthew ; Hampsch, Riley A. ; Traphagen, Nicole A. ; Yang, Wei ; Liu, Stephanie C. ; Zeldenrust, Megan A. ; Wang, Liewei ; Kalari, Krishna R. ; Yu, Jia ; Boughey, Judy C. ; Demidenko, Eugene ; Kettenbach, Arminja N. ; Cheng, Chao ; Goetz, Matthew P. ; Miller, Todd W. / A transcriptionally definable subgroup of triple-negative breast and ovarian cancer samples shows sensitivity to Hsp90 inhibition. In: Clinical Cancer Research. 2020 ; Vol. 26, No. 1. pp. 159-170.
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AU - Wells, Jason D.

AU - Ung, Matthew

AU - Hampsch, Riley A.

AU - Traphagen, Nicole A.

AU - Yang, Wei

AU - Liu, Stephanie C.

AU - Zeldenrust, Megan A.

AU - Wang, Liewei

AU - Kalari, Krishna R.

AU - Yu, Jia

AU - Boughey, Judy C.

AU - Demidenko, Eugene

AU - Kettenbach, Arminja N.

AU - Cheng, Chao

AU - Goetz, Matthew P.

AU - Miller, Todd W.

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N2 - Purpose: We hypothesized that integrated analysis of cancer types from different lineages would reveal novel molecularly defined subgroups with unique therapeutic vulnerabilities. On the basis of the molecular similarities between subgroups of breast and ovarian cancers, we analyzed these cancers as a single cohort to test our hypothesis. Experimental Design: Identification of transcriptional subgroups of cancers and drug sensitivity analyses were performed using mined data. Cell line sensitivity to Hsp90 inhibitors (Hsp90i) was tested in vitro. The ability of a transcriptional signature to predict Hsp90i sensitivity was validated using cell lines, and cell line- and patient-derived xenograft (PDX) models. Mechanisms of Hsp90i sensitivity were uncovered using immunoblot and RNAi. Results: Transcriptomic analyses of breast and ovarian cancer cell lines uncovered two mixed subgroups comprised primarily of triple-negative breast and multiple ovarian cancer subtypes. Drug sensitivity analyses revealed that cells of one mixed subgroup are significantly more sensitive to Hsp90i compared with cells from all other cancer lineages evaluated. A gene expression classifier was generated that predicted Hsp90i sensitivity in vitro, and in cell line- and PDXs. Cells from the Hsp90i-sensitive subgroup underwent apoptosis mediated by Hsp90i-induced upregulation of the proapoptotic proteins Bim and PUMA. Conclusions: Our findings identify Hsp90i as a potential therapeutic strategy for a transcriptionally defined subgroup of ovarian and breast cancers. This study demonstrates that gene expression profiles may be useful to identify therapeutic vulnerabilities in tumor types with limited targetable genetic alterations, and to identify molecularly definable cancer subgroups that transcend lineage.

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