Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes.

Autor:	Yu K; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States., Basu A; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States., Yau C; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States., Wolf DM; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, United States., Goodarzi H; University of California, San Francisco, San Francisco, CA, United States., Bandyopadhyay S; University of California, San Francisco, San Francisco, CA, United States., Korkola JE; Oregon Health and Science University, Portland, OR, United States., Hirst GL; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States., Asare S; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States.; QuantumLeap Healthcare Collaborative, San Francisco, CA, United States., DeMichele A; University of Pennsylvania, Philadelphia, PA, United States., Hylton N; University of California, San Francisco, San Francisco, CA, United States., Yee D; University of Minnesota, Minneapolis, MN, United States., Esserman L; Department of Surgery, University of California, San Francisco, San Francisco, CA, United States., van 't Veer L; Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, United States., Sirota M; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States.; Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in oncology [Front Oncol] 2023 Jun 13; Vol. 13, pp. 1192208. Date of Electronic Publication: 2023 Jun 13 (Print Publication: 2023).
DOI:	10.3389/fonc.2023.1192208
Abstrakt:	Introduction: Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes. Methods: In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival. Results: We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line. Conclusion: We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel. Competing Interests: HG is co-founder and holds stock in ExaiBio; SB reports institutional research funding and consulting fees from Revolution Medicines; and is an employee of and holds stock in Rezo Therapeutics. JK is a co-founder and holds stock in Convergent Genomics. GH reports spousal stock holdings in Moderna, Exact Sciences, Gilead and Nanostring. DY reports consulting fees from Martell Diagnostics and honoraria and meeting travel support from PER. LE reports institutional research funding from Merck, sits on the Blue Cross Blue Shield Medical Advisory Panel; and is a website author of UpToDate. LvV is co-founder, a part-time employee, and holds stock in Agendia NV, and holds stock in ExaiBio. MS reports consulting fees from Exxagen; and holds stock in Aria Pharmaceuticals and Somnics. All other authors declare no competing interests. (Copyright © 2023 Yu, Basu, Yau, Wolf, Goodarzi, Bandyopadhyay, Korkola, Hirst, Asare, DeMichele, Hylton, Yee, Esserman, van ‘t Veer and Sirota.)
Databáze:	MEDLINE
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