Abstract 2667: Full spectrum profiling flow cytometry to study cancer-associated fibroblast heterogeneity

It is now well appreciated that tumor growth depends on the tumor microenvironment (TME) comprising various non-malignant stromal cell types, including cancer-associated fibroblasts (CAFs). Cancer-associated fibroblasts (CAFs) are responsible for secreting the extracellular matrix (ECM) prominent in certain solid tumors such as pancreatic adenocarcinoma (PDAC). Despite our increasing knowledge of CAFs, therapeutic targeting of CAFs is currently not a feasible strategy, as CAFs are highly heterogeneous and extremely plastic, with each CAF population able to adopt both tumor-promoting and -restraining functions. We hypothesize that the plasticity and functional heterogeneity of CAFs can be explained by their flexible metabolism in response to environmental cues and the existence of discrete metabolic states within CAF subpopulations. While metabolic states can be predicted from single-cell transcriptomic data, this does not provide information on metabolic activity and potential, nor does it allow perturbations required for validation. Scalable and tractable methods to assess metabolic activity and CAF heterogeneity in parallel at the single cell level are needed to distinguish numerous existing CAF states do not exist. To address this need, in this work, we developed a strategy to study CAF metabolic activity and phenotypic heterogeneity at the single-cell level. We designed and optimized a 25-plex immunophenotyping panel of CAF and fibroblast markers that can be combined with numerous metabolic probes via Full Spectrum Profiling (FSP) flow cytometry. In addition, we compiled an analysis pipeline to facilitate the analysis of high-dimensional flow cytometry data. Using established 2D and 3D mono- and co-culture assays, we demonstrate the potential of our panel to be multiplexed with chemical probes for cell proliferation, lipid content, lipid uptake, fatty acid oxidation, glucose uptake, cholesterol content, hypoxia, or mitochondrial potential. Deploying our strategy in a KPC organoid-derived murine model of PDAC, we observed subpopulations of CAFs with differing metabolic potentials that are consistent with our predictions from transcriptomic metabolic modeling. With the high throughput and single-cell nature of FSP, our strategy represents a novel and modular tool for studying CAF phenotypic and metabolic heterogeneity. Citation Format: Kevin Muñoz Forti, Marta Storl-Desmond, Daniel Martínez, Sayana Issac, Shan Cao, Simon Schwörer. Full spectrum profiling flow cytometry to study cancer-associated fibroblast heterogeneity [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 2667.