Multiparameter imaging reveals clinically relevant cancer cell – stroma interaction dynamics in head and neck cancer
Epithelial tumors are characterized by abundant inter- and intra-tumor heterogeneity, which complicates diagnostics and treatment. The contribution of cancer-stroma interactions to this heterogeneity is poorly understood. Here we report a paradigm to quantify phenotypic diversity in head and neck squamous cell carcinoma (HNSCC) with single cell resolution. By combining cell state markers with morphological features, we identify phenotypic signatures that correlate with clinical features, including metastasis and recurrence. Integration of tumor and stromal signatures reveals that partial epithelial-mesenchymal transition (pEMT) renders disease outcome highly sensitive to stromal composition, generating a strong prognostic and predictive signature. Spatial transcriptomics and subsequent analyses of cancer spheroid dynamics identifies cancer-associated fibroblast–pEMT axis as a nexus for intercompartment signaling that reprograms pEMT cells into an invasive phenotype. Taken together, we establish a paradigm to identify clinically relevant tumor phenotypes, and discover a cell state-dependent interplay between stromal and epithelial compartments that drives cancer aggression. Overall design: Fresh samples from eight tongue carcinoma patients were collected from patients undergoing surgery at Helsinki University Hospital in 2022. Samples were fresh frozen in OCT and 10 µm sections were cut and mounted onto the ST arrays (10X Genomics Visium).