Zhang, Bing

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

Abstract Platinum-based DNA cross-linking agents are widely used anti-cancer drugs. Tumor resistance to platinum compounds is a major determinant of patient survival, including in high grade serous ovarian cancer (HGSOC). Remarkably, despite >30 years of literature on platinum responses in human cancer, none of these findings is used clinically as a predictive biomarker to stratify patients for platinum resistance, nor exploited therapeutically to treat platinum-resistant disease. Thus, understanding mechanisms of platinum resistance is an urgent goal, both to identify predictive biomarkers of platinum response (to spare patients with platinum-resistant tumors futile platinum therapy) and to develop efficacious therapies for platinum-resistant disease. To better understand mechanisms underlying platinum resistance in HGSOC, we performed comprehensive, dynamic (+/-carboplatin), multiomic profiling of DNA, RNA, protein and post-translational modifications (phosphorylation, ubiquitination, acetylation) to identify the cellular networks that respond to platinum treatment and associate with platinum resistance in three HGSOC intra-patient cell line pairs (PEA1S/PEA2R, PEO1S/PEO4R, PEO14S/PEO23R). The cell line pairs were derived from ascites or pleural effusions (Langdon et al., 1988) from three patients both before (PEA1S, PEO1S, PEO14S) and after (PEA2R, PEO4R, PEO23R, respectively) their tumors became clinically platinum resistant (i.e., in vivo development of resistance). The molecular profiles revealed extensive responses to carboplatin and differential responses between platinum-sensitive and platinum-resistant cells. Higher oxidative phosphorylation and fatty acid oxidation (FAO) pathway expression were observed in the platinum-resistant cells, which was further validated in patient-derived xenograft (PDX) models. We show that pharmacologic inhibition or CRISPR knockout of CPT1A, which represents a rate limiting step of FAO, sensitize HGSOC cells to platinum. Thus, FAO, and CPT1A in particular, represent a candidate therapeutic target to overcome platinum resistance in HGSOC. Citation Format: Hong Wang, Dongqing Hugang, Shrabanti Chowdhury, Sara Savage, Richard Ivey, Jacob Kennedy, Jeffrey Whiteaker, Chenwei Lin, Xiaonan Hou, Catherine Huntoon, Uliana Voytovich, Zahra Shire, Qing Yu, Steven Gygi, Andrew Hoofnagle, Zachary Herbert, Anna Calinawan, Larry Karnitz, S. John Weroha, Scott Kaufmann, Bing Zhang, Pei Wang, Michael Birrer, Amanda Paulovich. Multiomic analysis identifies CPT1A and fatty acid oxidation as a potential therapeutic target in platinum-refractory high grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1426.

Abstract Although high-grade serous ovarian cancers (HGSOC) are highly chemosensitive with an 85% initial response rate to platinum-based chemotherapy, 15% of patients are “exceptional nonresponders,” with platinum-refractory tumors that remain stable or progress during treatment. Unfortunately, we have no predictive biomarkers to identify refractory patients up front, and they receive futile chemotherapy through which most patients become too ill to be eligible for clinical trials. Hence, no progress has been made in treating these deadly tumors. The goal of this study is to identify mechanisms of platinum refractoriness to: i) predict refractory HGSOCs up front and ii) identify potential new drug targets in refractory disease to point to desperately needed new therapeutic approaches. Of note, 80-90% of patients who are initially platinum responsive will relapse and develop platinum-resistant disease, and it is possible that findings in platinum-refractory tumors might also provide insights into platinum-resistant tumors. Our NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC)-funded approach combines genomic and proteomic (“proteogenomic”) analyses of both preclinical models (0, 8, and 24 hours post-platinum exposure) and treatment-naïve human tumors. For preclinical models, we studied a well-characterized collection of patient-derived xenograft (PDX) models (10 sensitive, 10 refractory), as well as intrapatient HGSOC cell line pairs derived from patients before and after the development of platinum resistance. For the PDX models, proteogenomic profiling included RNASeq, WES, global proteomics, and phosphoproteomics at all 3 time points (0, 8, 24 hours). For cell line models (3 sensitive, 3 resistant), proteogenomic profiling was performed at all 3 timepoints (0, 8, 24 hours), and experiments were performed in complete biologic triplicate. Analyses included RNASeq, WES, global proteomics, phosphoproteomics, ubiquitin proteome, acetylated proteome, and pTyr. A large collection of 275 human HGSOCs (an approximate equal balance of platinum sensitive and refractory tumors) is currently undergoing proteomic profiling, and genomic profiles (WGS, RNASeq) will be performed on a subset. In parallel, we have performed a comprehensive review of 31 years of published work on platinum responses of human cancers, identifying ~700 genes implicated in the response and scoring each gene with respect to strength of the published evidence. Using a Bayesian approach, we are integrating the curated candidates from the literature with our empirical proteogenomic datasets to identify a candidate signature for detecting platinum-refractory disease prior to chemotherapy. We are also performing gene-regulatory network analysis to identify potential drivers of chemo response. NextGen, targeted, multiplex, multiple reaction monitoring mass spectrometry-based assays are being developed to quantify proteins in the signature for validation studies, using independent patient cohorts. This abstract is also being presented as Poster A62. Citation Format: Jacob J. Kennedy, Shrabanti Chowdhury, Sara R. Savage, Xiaonan Hou, Catherine J. Huntoon, Richard G. Ivey, Qing Yu, Chenwei Lin, Dongqing Huang, Lei Zhao, Uliana J. Voytovich, Regine M. Schoenherr, Zahra Shire, Steven J. Skates, Jeffrey R. Whiteaker, Andrew N. Hoofnagle, Samuel C. Mok, Bing Zhang, Larry M. Karnitz, S. John Weroha, Steven P. Gygi, Scott H. Kaufmann, Pei Wang, Michael J. Birrer, Amanda G. Paulovich. Proteogenomic approach to identify mechanisms of platinum refractoriness in high-grade serous ovarian cancers [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr PR02.