ABSTRACT
Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.
Subject(s)
Biomarkers, Tumor/metabolism , Carcinoma, Pancreatic Ductal/metabolism , Pancreatic Neoplasms/metabolism , Tumor Microenvironment , Adult , Aged , Cell Line, Tumor , Female , Gene Expression Regulation, Neoplastic , Humans , Male , Middle Aged , Single-Cell AnalysisABSTRACT
Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd individuals. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across tumors from affected individuals and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T cell-attracting chemokines. By identifying interacting cellular programs, we reveal the logic underlying spatially organized immune-malignant cell networks.
