Abstract 4083: Case study of single-cell protein activity-based drug prediction and validation for precision treatment of cholangiocarcinoma

Abstract

Abstract Cholangiocarcinoma (CCA) is an aggressive biliary adenocarcinoma, with a median survival ranging from 12 to 37 months and no effective treatment options [Dhanasekaran et al. 2013]. Studies of the CCA tumor micro-environment (TME) and intratumoral heterogeneity have been limited, despite clinically significant interaction between tumor and stromal or immune components across other tumor types. Single-cell RNA Sequencing (scRNASeq) has emerged as a valuable technique to characterize the TME. Here we present a case study profiling CCA TME at the resolution of scRNASeq, and the first application of a unique OncoTarget (OTar) and OncoTreat (OTr) approach [Alvarez et al. 2018, Zeleke et al. 2020, Mundi et al. 2021] to predict and identify actionable drug targets at the single-cell level. These are both CLIA-certified algorithms for personalized drug prediction, now adapted for the first time to drug sensitivity prediction at the level of individual tumor cells. scRNASeq from a human CCA sample revealed significant tumor immune infiltration, with T-cells comprising the largest population, and fewer than 10% of cells identified as tumor cells, such that transcriptional profiles from RNA-Seq derived from whole tumor samples would be dominated by non-tumor cells. VIPER-based protein activity inference of tumor cells identified three sub-populations, not distinguished by gene expression alone [Alvarez et al. 2016]. These were characterized by upregulation of KRAS pathway, TNFa signaling with epithelial-mesenchymal transition, and upregulation of MYC targets, respectively. Consensus OTar/OTr drug prediction analysis on both scRNASeq tumor cells and bulk RNA-Seq of an engrafted PDX model from resected tumor at the time of biopsy ranked Glasdegib, Plicamycin, Flavopiridol, AT9283, and Dacinostat as the top 5 drugs with best overall tumor cell coverage. Therefore, we administered these drugs to a cohort of 8 PDX-bearing mice per treatment arm. Dacinostat and Plicamycin significantly reduced tumor growth rate (p=0.007 and p=0.03, respectively), with Dacinostat stabilizing tumor size over 28 days of treatment. Both of these drugs significantly extended survival time by Kaplan-Meier regression (p=0.001 and p=0.03, respectively). Furthermore, scRNASeq data of drug-treated PDXs showed that Dacinostat uniformly depleted all three tumor sub-populations compared to Vehicle control, whereas one of the tumor sub-clusters was resistant to Plicamycin, consistent with single-cell drug sensitivity predicted by OTr. Given the in vivo activity of these two drugs in inhibiting tumor growth, and the effectiveness of Dacinostat across observed tumor cell phenotypes, as well as the high immune infiltration of this CCA sample, these drugs may be translated into pre-clinical and clinical trials alone and in combination with checkpoint immunotherapy. Citation Format: Lorenzo Tomassoni, Aleksandar Obradovic, Filemon Dela Cruz, Daoqi Yu, Elise Fraser, Susan E. Bates, Yvonne Saenger, Andrea Califano. Case study of single-cell protein activity-based drug prediction and validation for precision treatment of cholangiocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4083.