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Batalini F, Gulhan DC, Mao V, Tran A, Polak M, Xiong N, Tayob N, Tung NM, Winer EP, Mayer EL, Knappskog S, Lønning PE, Matulonis UA, Konstantinopoulos PA, Solit DB, Won H, Eikesdal HP, Park PJ, Wulf GM. Mutational Signature 3 Detected from Clinical Panel Sequencing is Associated with Responses to Olaparib in Breast and Ovarian Cancers. Clin Cancer Res 2022; 28:4714-4723. [PMID: 36048535 PMCID: PMC9623231 DOI: 10.1158/1078-0432.ccr-22-0749] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/05/2022] [Accepted: 08/29/2022] [Indexed: 01/24/2023]
Abstract
PURPOSE The identification of patients with homologous recombination deficiency (HRD) beyond BRCA1/2 mutations is an urgent task, as they may benefit from PARP inhibitors. We have previously developed a method to detect mutational signature 3 (Sig3), termed SigMA, associated with HRD from clinical panel sequencing data, that is able to reliably detect HRD from the limited sequencing data derived from gene-focused panel sequencing. EXPERIMENTAL DESIGN We apply this method to patients from two independent datasets: (i) high-grade serous ovarian cancer and triple-negative breast cancer (TNBC) from a phase Ib trial of the PARP inhibitor olaparib in combination with the PI3K inhibitor buparlisib (BKM120; NCT01623349), and (ii) TNBC patients who received neoadjuvant olaparib in the phase II PETREMAC trial (NCT02624973). RESULTS We find that Sig3 as detected by SigMA is positively associated with improved progression-free survival and objective responses. In addition, comparison of Sig3 detection in panel and exome-sequencing data from the same patient samples demonstrated highly concordant results and superior performance in comparison with the genomic instability score. CONCLUSIONS Our analyses demonstrate that HRD can be detected reliably from panel-sequencing data that are obtained as part of routine clinical care, and that this approach can identify patients beyond those with germline BRCA1/2mut who might benefit from PARP inhibitors. Prospective clinical utility testing is warranted.
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Affiliation(s)
- Felipe Batalini
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Beth Israel Deaconess Medical Center, Division of Medical Oncology and Cancer Research Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Doga C. Gulhan
- Harvard Medical School, Department of Biomedical Informatics, Boston, Massachusetts
| | - Victor Mao
- Harvard Medical School, Department of Biomedical Informatics, Boston, Massachusetts
| | - Antuan Tran
- Harvard Medical School, Department of Biomedical Informatics, Boston, Massachusetts
| | - Madeline Polak
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, Massachusetts
| | - Niya Xiong
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Data Sciences, Boston, Massachusetts
| | - Nabihah Tayob
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Data Sciences, Boston, Massachusetts
| | - Nadine M. Tung
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Beth Israel Deaconess Medical Center, Division of Medical Oncology and Cancer Research Institute, Boston, Massachusetts
| | - Eric P. Winer
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, Massachusetts
| | - Erica L. Mayer
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, Massachusetts
| | - Stian Knappskog
- University of Bergen, Department of Clinical Science, Bergen, Norway
| | - Per E. Lønning
- University of Bergen, Department of Clinical Science, Bergen, Norway
| | - Ursula A. Matulonis
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Gynecologic Oncology, Boston, Massachusetts
| | - Panagiotis A. Konstantinopoulos
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Dana-Farber Cancer Institute, Department of Gynecologic Oncology, Boston, Massachusetts
| | - David B. Solit
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Helen Won
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Hans P. Eikesdal
- University of Bergen, Department of Clinical Science, Bergen, Norway
| | - Peter J. Park
- Harvard Medical School, Department of Biomedical Informatics, Boston, Massachusetts
| | - Gerburg M. Wulf
- Harvard Medical School, Department of Medicine, Boston, Massachusetts
- Beth Israel Deaconess Medical Center, Division of Medical Oncology and Cancer Research Institute, Boston, Massachusetts
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