Abstract 6213: Single cell imaging uncovers a coordinated tumor-immune-stroma spectrum with genomic associations in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) has consistent genomic drivers and established classical and basal transcriptional subtypes, but despite this, there exist many intermediate state tumors, a multiplicity of copy number aberrations and low frequency mutations, and a complex, spatially heterogeneous tumor microenvironment. These elements are not random; they are evidence of coordinated biological programs and evolving signaling networks that underlie tumor progression. Merging data from these varied molecular and spatial layers is essential to clinically define and therapeutically target a) tumors that fall into the ‘grey zone’ of pancreatic cancer subtyping and b) specific collusive epithelial-stromal niches.To identify the in situ interdependencies between distinct tumor cell states, fibroblast phenotypes, deposited extracellular matrix, immune infiltrate, and vasculature, we performed imaging mass cytometry on three serial sections of a PDAC tissue microarray (221 resected tumors, ∼4 cores each), generating 800 multiplexed images (40-43 channels) each focused on deeply profiling a different cell lineage. We captured 76 immune and stromal cell types and states, as well as six cancer cell types that recapitulated the classical and basal PDAC signatures, plus four discrete “intermediate” states with distinct associations to RNA subtype (n = 92), tumor ploidy (n = 192), and patient outcome. We clustered our immune and stromal cell populations to define 8 recurrent microenvironments, and found the microenvironment dominated by CD105+ CAFs was significantly spatially associated to classical tumor cells with strong epithelial differentiation transcription factor expression (pairwise Fisher’s exact test, odds ratio = 3.7), ECM-rich microenvironments were proximal to basal tumor cells (odds ratio = 4.3), and pMLC2+ CAFs were enriched near the poor-prognosis, low-ploidy S100A4+ tumor phenotype (odds ratio = 4.2). We additionally denote a specific fibroblast-centric microenvironment associated with neoadjuvant treated tumors (n = 26). Using matched 30X whole-genome sequencing (n = 192), we found specific mutations and copy number changes that were associated changes in tumor and microenvironment composition, and performed Lasso-based machine learning to determine the most important cross-omic features for overall survival prediction. Together, our findings define a phenotypic and molecular framework of PDAC from genome to tumor-microenvironment, provide insight into the connection between tumor phenotype and stromal niches, and offer a refined basis for patient stratification. Citation Format: Ferris Nowlan, Noor Shakfa, Sibyl Drissler, Tan Tiak Ju, Elizabeth Sunnucks, Edward LY Chen, Cassandra J. Wong, Brendon Seale, Zhen Yuan Lin, Michelle Chan-Seng-Yue, Amy Zhang, Sabiq Chaudhary, Chengxin Yu, Golnaz Abazari, Michael Geuenich, Matthew Watson, Jiaxi Peng, Somaieh Afiuni-Zadeh, Ayelet Borgida, Ricardo Gonzalez, Sheng-Ben Liang, Klaudia Nowak, Miralem Mrkonjic, Anna Dodd, Julie M. Wilson, Kieran Campbell, Jenn Gorman, Barbara Grünwald, Robert C. Grant, Jennifer J. Knox, Anne-Claude Gringas, Faiyaz Notta, Steven Gallinger, Grainne O'Kane, Hartland Jackson. Single cell imaging uncovers a coordinated tumor-immune-stroma spectrum with genomic associations in pancreatic ductal adenocarcinoma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6213.