Silva pattern-guided proteomics reveals coordinated tumor-stroma remodeling in cervical adenocarcinoma

Objective: Characterize proteome alterations within the tumor microenvironment of endocervical adenocarcinoma (ECA) stratified by Silva patterns. Methods: Pathology review assigned 32 ECA as Silva A (n10), Silva B (n11) and Silva C (n11) tumors. Tumors underwent laser-microdissection enrichment of tumor and adjacent stromal cells followed by multiplexed, quantitative proteomic analyses. Comparative analyses were performed using hierarchical clustering and differential statistics with LIMMA and included prediction of pathway alterations and prioritization of proteins mapping as putative drug targets. Results: Quantitative proteomic analyses identified 7300 proteins across all microcompartment samples. Unsupervised analyses showed stark differences between tumor and stroma populations and distinguished Silva C stroma from Silva patterns A/B. Tumors partitioned into clusters enriched for mitochondrial metabolism, immune signaling, or extracellular-matrix pathways; stroma formed complementary clusters characterized by matrix remodeling, immunity, or cell-cycle programs. Compared to patterns A and B, Silva C tumor and stroma cells exhibited large numbers of protein alterations and included candidates shared between tumor–stroma subpopulations (CPA3, NNMT), highlighting microenvironment reciprocity. Strong tumor-stroma correlations (Spearman ρ > 0.83) underscored coordinated remodeling, and stromal protein alterations enriched in Silva C cases, suggested pronounced immune activation in these tumors. Candidate drug targets altered between Silva A and C tumors included PDGFRB, CDK4, EGFR, MAP2K1/2, and CEACAM5. Conclusions: Silva C ECA exhibits a distinctive immune- and matrix-centric tumor–stroma axis based on proteome alterations observed. Tumor microenvironment-resolved proteomics identified Silva pattern-specific biomarkers and therapeutic vulnerabilities that warrant functional and clinical validation.