Abstract 7479: Single-cell OncoTreat: Novel therapeutic candidates by high resolution inference and validation of drug sensitivities in heterogeneous cholangiocarcinoma tumors
Authors: Aleksandar Obradovic, Lorenzo Tomassoni, Daoqi You, Charles Drake, Filemon Dela Cruz, Andrew Kung, Andrea Califano
Journal: Cancer Research (2025)

Abstract Cholangiocarcinoma is an aggressive biliary adenocarcinoma with limited treatment options. Stromal infiltration and intratumoral heterogeneity in this tumor type prevents identification of actionable dependencies from bulk-tissue profiles. While cholangiocarcinoma illustrates these challenges, they are common across many other aggressive tumors.To address these challenges, we introduce a single-cell RNA-Sequencing (scRNA-Seq) framework for prioritization of drugs to treat heterogeneous tumor cell subpopulations. Single-cell analyses can bypass limitations of sample size in a precision medicine approach by providing large tumor cell “cohorts” even from individual patients, with the advantage that cell subpopulations can be effectively distinguished. Unfortunately, &amp;gt;80% of genes in each cell profiled by scRNA-Seq are typically undetectable, limiting discoverability of therapeutic targets and drug sensitivities. The VIPER algorithm addresses this by inferring the transcriptional activity of a protein from expression of its downstream target genes. By then identifying aberrantly activated proteins, each cell can be matched to an empiric database of cell line drug perturbation RNA-Seq, ranking drugs which empirically inhibit the proteins aberrantly activated in each cell. We refer to this approach as single-cell OncoTreat.Analysis of tumor cells across six patients by this approach has revealed three distinct sub-phenotypes of cholangiocarcinoma cells, with conserved proteomic signatures, and distinct predicted drug sensitivities. A seventh patient recapitulated these phenotypes, with drug predictions validated in a low-passage, patient-derived xenograft (PDX) model. The top-ranked drug by integrated analysis of all tumor cells was plicamycin, which at sub-cluster level only two of three clusters were predicted to respond to. Conversely, dacinostat was inferred to be active against all three tumor-cell sub-phenotypes. Tumor growth studies in PDX demonstrated growth rate control with both plicamycin and dacinostat, but much improved survival time with dacinostat, outperforming gemcitabine + cisplatin standard of care. Post-treatment scRNA-Seq confirmed predicted subpopulation-specific effects, such that dacinostat depleted all three tumor sub-phenotypes, while plicamycin depleted only the two predicted, allowing the third to reconstitute a treatment-resistant tumor. To our knowledge, this is the first report of dacinostat as an HDAC inhibitor effective in cholangiocarcinoma treatment, in vivo. Ultimately, this approach suggests promising candidates for follow-up trials in cholangiocarcinoma, and is highly generalizable to elucidate complementary dependencies of other aggressive, heterogeneous tumors. Citation Format: Aleksandar Obradovic, Lorenzo Tomassoni, Daoqi You, Charles Drake, Filemon Dela Cruz, Andrew Kung, Andrea Califano. Single-cell OncoTreat: Novel therapeutic candidates by high resolution inference and validation of drug sensitivities in heterogeneous cholangiocarcinoma tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7479.