FAP and cancer: To clarify the role of CXCR4 and FAP, we utilized a pan-cancer machine learning (ML) approach based on transcriptomic data of 29 cancer entities from The Cancer Genome Atlas (TCGA) database, searching for entity-independent mRNA and microRNA (miR) signatures best characterizing CXCR4 and FAP overexpression.