Zahi I. Mitri, Allison L. Creason, Jayne M. Stommel, Daniel Bottomly, Tugba Y. Ozmen, Matthew J. Rames, Furkan Ozmen, Boyoung Jeong, Natalia Lukashchuk, Jack Ashton, Jeong Youn Lim, Shamilene Sivagnanam, Konjit Betra, Jinho Lee, Marilyne Labrie, SMMART Clinical Trials Program, Lisa M. Coussens, Christopher L. Corless, Shannon K. McWeeney, Gordon B. Mills
{"title":"Adaptive Responses to PARP Inhibition Predict Response to Olaparib and Durvalumab: Multi-omic Analysis of Serial Biopsies in the AMTEC Trial","authors":"Zahi I. Mitri, Allison L. Creason, Jayne M. Stommel, Daniel Bottomly, Tugba Y. Ozmen, Matthew J. Rames, Furkan Ozmen, Boyoung Jeong, Natalia Lukashchuk, Jack Ashton, Jeong Youn Lim, Shamilene Sivagnanam, Konjit Betra, Jinho Lee, Marilyne Labrie, SMMART Clinical Trials Program, Lisa M. Coussens, Christopher L. Corless, Shannon K. McWeeney, Gordon B. Mills","doi":"10.1101/2024.08.29.24312245","DOIUrl":null,"url":null,"abstract":"In syngeneic murine breast cancer models, poly ADP-ribose polymerase inhibitor (PARPi) and anti-PD-L1 combinations induce deep, sustained responses independent of <em>BRCA1/2</em> mutation status. We therefore investigated this combination in the AMTEC clinical trial, in which a one-month olaparib run-in was followed by combined olaparib and durvalumab in participants with <em>BRCA1/2</em> wild-type metastatic triple negative breast cancer. To characterize adaptive responses to olaparib monotherapy, paired biopsies taken before and during PARPi lead-in were deeply characterized by DNA, RNA, and protein multi-omic analyses, including spatially-resolved single cell proteomics for tumor and immune contexture. We identified multiple potential tumor-intrinsic and microenvironmental biomarkers from pre-treatment and on-olaparib biopsies that robustly predicted participant response to combined olaparib and durvalumab. Notably, the on-olaparib biopsy provided the greatest information content, suggesting that adaptation of malignant cells and the tumor ecosystem to PARPi can serve as a predictor of potential benefit from combined PARPi and anti-PD-L1 therapy.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"21 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.29.24312245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In syngeneic murine breast cancer models, poly ADP-ribose polymerase inhibitor (PARPi) and anti-PD-L1 combinations induce deep, sustained responses independent of BRCA1/2 mutation status. We therefore investigated this combination in the AMTEC clinical trial, in which a one-month olaparib run-in was followed by combined olaparib and durvalumab in participants with BRCA1/2 wild-type metastatic triple negative breast cancer. To characterize adaptive responses to olaparib monotherapy, paired biopsies taken before and during PARPi lead-in were deeply characterized by DNA, RNA, and protein multi-omic analyses, including spatially-resolved single cell proteomics for tumor and immune contexture. We identified multiple potential tumor-intrinsic and microenvironmental biomarkers from pre-treatment and on-olaparib biopsies that robustly predicted participant response to combined olaparib and durvalumab. Notably, the on-olaparib biopsy provided the greatest information content, suggesting that adaptation of malignant cells and the tumor ecosystem to PARPi can serve as a predictor of potential benefit from combined PARPi and anti-PD-L1 therapy.