Integrative analysis of single-cell and bulk transcriptomes reveals metabolic heterogeneity and identifies PFKP as a therapeutic target in cervical cancer
Cervical cancer (CC) is still a major gynecological tumor among women globally. The heterogeneity landscape and prognostic value of metabolic reprogramming in CC remain unclear. Our research first uncovered metabolic heterogeneity and identified three distinct metabolic subtypes in CC. Based on transcriptomic differences between metabolic subtypes, we developed a robust prognostic signature (TPM3, MAP7, PFKP, IL3RA, ISCU) using machine learning, which robustly stratified patient risk. CC patients with higher risk scores presented unfavorable outcomes and showed an immunosuppressive status. Functional experiments confirmed that phosphofructokinase, platelet (PFKP) promotes CC proliferation and glycolysis. Moreover, we demonstrated that Suramin effectively suppressed CC tumor growth by inhibiting PFKP-mediated glycolysis. Our findings provide a robust prognostic model and disclose PFKP as a potential therapeutic target in CC, offering insightful guidance on cancer management of CC patients.