Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance [GeoMx]

Objectives: This study aimed to delineate progression continuum and stage-related transcriptional programs underlying cSCC evolution, identify candidate biomarkers for risk stratification and invasion, and assess the broader relevance of these molecular signatures across human cancers. Methods: We applied bulk RNA sequencing (HTG EdgeSeq) and spatial transcriptomics (GeoMx DSP) to profile skin biopsies from 8 patients recruited in collaboration with Bordeaux University Hospital. Importantly, each patient simultaneously presented four stages (healthy skin, pre-malignant lesion, tumor core, and invasive front) providing a unique framework to interrogate the full molecular trajectory of cSCC progression within individuals. Results: Spatial transcriptomic analyses identified more than 2,000 differentially expressed genes (adjusted p < 0.01) whose expression in squamous cells changed across disease stages. These genes were organized into 18 coordinated expression programs reflecting progressive biological rewiring during tumor evolution. Pathways related to cellular stress responses, proliferation, extracellular matrix remodeling, and inflammation were progressively upregulated, whereas differentiation programs and lipid and amino acid metabolism were consistently downregulated. In contrast, peritumoral macrophages showed increased expression of genes involved in purine metabolism, glycolysis, and pyruvate metabolism across progression. To assess the broader clinical relevance of the progression-associated gene programs, we developed a Snakemake-based pipeline to systematically screen 32 solid and hematological malignancies from The Cancer Genome Atlas. This workflow is designed to be fully reproducible and readily extensible, enabling other researchers to perform similar progression and survival analyses across cancer types. Notably, we defined a cSCC-progression signature which significantly correlated with poor overall survival (p < 0.05) in 10 additional cancer types. Furthermore , we last identified 12 cSCC stage-specific biomarkers, whose expression was confirmed to be stage-specific via Visium HD. Conclusions: Together, this study provides a spatially resolved and stage-aware transcriptomic map of cSCC progression, identifies coordinated gene programs underlying disease evolution, and defines progression-associated signatures with prognostic relevance across multiple cancers, highlighting their potential clinical utility.