Abstract

Abstract Background Cholangiocarcinoma (CCA) is a heterogeneous malignancy. Platinum-based chemotherapy (Gemcitabine and Cisplatin) has been the standard treatment for over a decade and is the base for the current immunotherapy combinations. Response rates are typically between 20-30%. Herein, we present outcomes of preclinical efficacy trials on CCA PDX models in correlation with baseline multiomics profiling of CCA patient-derived xenograft (PDX) models to identify molecular features associated with response. Methods Tumor samples from twenty-eight CCA PDX were used to isolate RNA and protein to be included in multiomics analysis (Phosphoproteomics, Proteomics, and Transcriptomics). A subset of PDX models were treated with various doses of Gemcitabine and Cisplatin. The Median Efficacy Index (MEI) was calculated as the ratio of the difference in median of delta in tumor volume at the last day of the study between the treatment and the control arms divided by the median of delta in tumor volume of the control at the last day of the treatment (positive= growth, negative=inhibition, and 0=no efficacy). A Hierarchical All-Against-All algorithm was utilized to compare multiomics features to the MEI and pathway analysis completed for identified molecular features. Results After conducting preclinical efficacy trials, the five tested CCA PDX models were classified into sensitive, moderately sensitive, and resistant models based on the MEI on each treatment arm. The top up-regulated genes were identified for Gemcitabine response (SRPK2, GLK2, and RIOK2) and Cisplatin response (NTRK1, PRPF4B, and SRPK2). The top up-regulated genes related to Gemcitabine resistance were NTRK1, PIP5K1C, and CSNK2A2, while those related to Cisplatin resistance were SRPK1, PRPF4B, and CSNK2A1. Conclusion Cholangiocarcinoma multiomics signatures can predict therapeutic response to standard-of-care chemotherapy in preclinical models. Novel mechanisms of Gemcitabine and Cisplatin resistance were identified related to NTRK1, SRPK1 and SRPK2. Resistant signatures will be challenged with the appropriate targeted therapies on the resistant CCA PDX models. Citation Format: Amro M. Abdelrahman, Danielle M. Carlson, Erik Jessen, Dong-Gi Mun, Isaac Lynch, Alessandro Fogliati, Stella Konadu Adjei Antwi, Aushinie Abeynayake, Akhilesh Pandey, Mark J. Truty, Gregory J. Gores, Rory L. Smoot. Pretreatment multiomics in conjunction with preclinical trials on patient-derived xenograft models of cholangiocarcinoma can identify chemotherapy response signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6912.

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