Abstract C058: Identifying cell-intrinsic drivers of transcriptional plasticity in pancreatic cancer

Abstract

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with few effective therapies. Contributing to the complexity of this deadly cancer, PDAC tumors with similar genomic backgrounds can express divergent transcriptional programs with clinical importance. These transcriptional subtypes, termed “cell states”, have prognostic significance: PDAC tumors in the “classical state” generally have better outcomes and are thought to be more responsive to chemotherapy while those in the “basal state” are more aggressive. Currently, cell state is not used to direct therapy. Cell state is an integrative property shaped by both cell-intrinsic (e.g., mutations, epigenetics) and cell-extrinsic (e.g., growth factors, cytokines) factors. In our prior work, single-cell analysis of clinical PDAC samples demonstrated notable intra-tumoral cell state heterogeneity with evidence for cells that co-expressed both basal and classical markers, suggestive of cell state plasticity. In addition, longitudinal monitoring of patient-derived organoids has shown that cells can shift from classical to coexpressor/basal states as the environment changes, and this shift in cell states can drastically influence drug response. However, it remains unknown which signaling and transcriptional pathways induce basal or classical states, and whether these gene regulatory networks can be targeted therapeutically. Thus, there is a pressing need to devise scalable methods to determine essential drivers for prognostically-relevant cancer cell states. Here, we aim to define transcriptional drivers of basal and classical cell states in pancreatic cancer. We are currently optimizing a flow cytometry-fluorescence in situ hybridization (Flow-FISH) workflow to enable a multi-gene cell state readout. We plan to perform a transcription factor over-expression screen within a cohort of PDAC models using this Flow-FISH readout to identify those factors that can drive cells toward basal (n=3), classical (n=2), or coexpressor (n=3) states. As a proof of concept, we have confirmed that TP63A overexpression induces basal state expression, even in models that initially express a classical phenotype. Through these efforts, we aim to construct high-fidelity isogenic but state-variant PDAC models for use both in therapeutic screening and as a substrate for investigating mechanisms governing cancer cell state plasticity. Citation Format: Yuzhou Evelyn Tong, Walaa E. Katan, Alex Bott, Julia Joung, Alex K. Shalek, Peter S. Winter, Srivatsan Raghavan. Identifying cell-intrinsic drivers of transcriptional plasticity in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C058.