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Abstract Sensitivity to therapeutic agents is impacted both by genetic heterogeneity between patients or among clones within a tumor and by heterogeneity of epigenetic cell states. Prior work demonstrates that human pancreatic tumors comprise malignant cells in a mixture of multiple cell states with distinct genetic dependencies, leading to a reservoir of chemoresistance across the tumor; targeting just one or two malignant cell states is insufficient to achieve durable therapeutic responses. One approach to overcome this challenge is to identify agents with efficacy against malignant cells in multiple cell states. However, in the absence of genetic distinctions between cell states, identifying therapeutic vulnerabilities for each malignant cell state present in a patient’s tumor in real time remains a challenge. OncoTreat is a CLIA certified algorithm that matches drugs to patients based on tumor gene expression profiles. The approach utilizes regulatory network analysis, a systems biology framework that transforms gene expression data into regulatory protein activity profiles, in a manner that facilitates the identification of master transcriptional regulators of cell state. We carried out a Phase 1 clinical trial of the OncoTreat framework to examine feasibility for implementing RNA-based precision medicine in patients with metastatic pancreatic ductal adenocarcinoma (2nd line and beyond). Patient-derived xenografts were established from subjects prior to 1st line therapy, and selected agents matched by OncoTreat were assessed co-clinically while subjects received standard of care regimens, with the potential for subsequent treatment with successful agents upon progression. Two subjects in the study matched to selenexor, an XPO1 inhibitor that is FDA approved for multiple myeloma. Co-clinical studies of selinexor in patient-derived xenograft models generated from the matched subjects showed prolonged survival compared to control regimens. Single-cell RNA sequencing analysis of these tumors found that the activity of master regulators confirmed that the activity of selinexor-responsive master regulators were inverted in response to treatment in vivo, reducing the fraction of malignant cells in the tumors. Strikingly, selenexor treatment was associated with significant inhibition of RAS/MAPK signaling, suggesting a potential novel role for selinexor targeting Ras. Together, these data indicate a potential therapeutic vulnerability for a subset of PDAC patients that can be predicted by a CLIA-certified RNA-based precision medicine platform. Citation Format: Alvaro Curiel-Garcia, Lorenzo Tomassoni, Tanner C. Dalton, Amanda R. Decker-Farrell, Carmine F. Palermo, Daniel R. Ross, Stephen A. Sastra, Urszula N. Wasko, Isabel M. Goncalves, Prabhot Mundi, Basil S. Bakir, Rachael A. Safyan, Hanina Hibshoosh, Gulam A. Manji, Andrea Califano, Kenneth P. Olive. RNA-based precision medicine predicts sensitivity to selinexor in select pancreatic ductal adenocarcinoma patients 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 (6Suppl): Abstract nr 934.
Curiel‐García et al. (Fri,) studied this question.