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https://hdl.handle.net/2440/137269
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Type: | Journal article |
Title: | Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin |
Author: | Berthelet, J. Foroutan, M. Bhuva, D.D. Whitfield, H.J. El-Saafin, F. Cursons, J. Serrano, A. Merdas, M. Lim, E. Charafe-Jauffret, E. Ginestier, C. Ernst, M. Hollande, F. Anderson, R.L. Pal, B. Yeo, B. Davis, M.J. Merino, D. |
Citation: | Cancers, 2022; 14(10):1-18 |
Publisher: | MDPI AG |
Issue Date: | 2022 |
ISSN: | 2072-6694 2072-6694 |
Statement of Responsibility: | Jean Berthelet, Momeneh Foroutan, Dharmesh D. Bhuva, Holly J. Whitfield, Farrah El-Saafin, Joseph Cursons, Antonin Serrano, Michal Merdas, Elgene Lim, Emmanuelle Charafe-Jauffret, Christophe Ginestier, Matthias Ernst, Frédéric Hollande, Robin L. Anderson, Bhupinder Pal, Belinda Yeo, Melissa J. Davis, and Delphine Merino |
Abstract: | The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer samples to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine. |
Keywords: | breast cancer; pharmacogenomics; predictive modeling; drug sensitivity; precision medicine; cisplatin |
Rights: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
DOI: | 10.3390/cancers14102404 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/1128609 http://purl.org/au-research/grants/nhmrc/1141361 http://purl.org/au-research/grants/nhmrc/1164081 |
Published version: | http://dx.doi.org/10.3390/cancers14102404 |
Appears in Collections: | Medical Sciences publications |
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hdl_137269.pdf | Published version | 2.4 MB | Adobe PDF | View/Open |
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