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Mol Cell Proteomics. 2018 Aug;17(8):1470-1486. doi: 10.1074/mcp.RA118.000633. Epub 2018 Apr 9.

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants.

Author information

1
From the ‡Cancer Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
2
§Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia.
3
¶Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, South Australia 5005, Australia.
4
‖South Australian Health and Medical Research Institute, Adelaide, South Australia 5000, Australia.
5
**Cancer Division, The Kinghorn Cancer Centre/Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.
6
‡‡Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia.
7
§§Department of Medical Oncology, Chris O'Brien Lifehouse, Camperdown, New South Wales 2050, Australia.
8
¶¶School of Medicine, Flinders University, Bedford Park, SA 5042, Australia.
9
From the ‡Cancer Program, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia; roger.daly@monash.edu.

Abstract

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses.

KEYWORDS:

Biomarker: Diagnostic; Biomarker: Prognostic; Cancer therapeutics; Hsp90 inhibitors; Patient cohorts; Prostate cancer biomarkers; Tumor microenvironment; ex vivo; patient-derived explants

PMID:
29632047
PMCID:
PMC6072547
DOI:
10.1074/mcp.RA118.000633
[Indexed for MEDLINE]
Free PMC Article

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