Proteome-based molecular subtyping and therapeutic target prediction in cervical cancer.

Cervical cancer (CC) represents a leading malignant threat to women’s health globally. Patients with advanced-stage CC frequently encounter limited therapeutic efficacy and prominent drug resistance, highlighting the urgent need for molecular-driven precision treatment strategies. Herein, we developed a proteomics-based molecular classification for CC. A total of 198 CC patients were classified into four distinct molecular subtypes: CC-I (n = 55), CC-II (n = 32), CC-III (n = 43), and CC-IV (n = 68). This classification system was further validated in an independent cohort, confirming its clinical reliability. Survival analysis indicated significant prognostic differences among the four subtypes (log-rank test, p < 0.001). Functional analysis revealed distinct molecular characteristics: CC-I and CC-IV were characterized by enrichment of immune-related pathways, while CC-II and CC-III displayed upregulated metabolism-associated pathways. Notably, CC-IV overexpressed pathways associated with cell cycle regulation, p53 signaling, and DNA repair, potentially contributing to its aggressive phenotype. Meanwhile, CC-I and CC-IV had higher immune scores and were enriched with T cells and B cells, suggesting potential favorable responsiveness to immunotherapies. Focusing on the CC-IV, we observed that high CDK4/6 expression was correlated with poor clinical outcomes. Patient-derived organoid (PDO) models confirmed that CDK4/6 inhibitor (palbociclib) had significant growth-inhibitory effects on CC patients with high CDK4/6 expression. In conclusion, this study established the first validated proteome-based molecular subtyping system for CC, and identified actionable therapeutic targets, and provided a robust foundation for personalized treatment strategies in CC.