BACKGROUND Cervical cancer (CC) remains the fourth leading cause of cancer-related deaths in women globally, with poor prognosis for metastatic and recurrent cases. Although genomic alterations have been extensively characterized, global proteogenomic landscape of the disease is largely under explored.METHODS Here, we present the first genome-wide proteogenomic characterization of CC, analyzing 139 tumor-normal tissue pairs using whole-genome sequencing, transcriptomics, proteomics, and phosphoproteomics.RESULTS We identified 4 distinct molecular subtypes with unique clinical outcomes: epithelial-mesenchymal transition (EMT, C1), proliferation (C2), immune response (C3), and epithelial differentiation (C4). A 4-protein classifier (CDH13, TP53BP1, NNMT, HSPB1) was developed with strong prognostic and predictive value, particularly for immunotherapy response in subtype C3. Phosphoproteomic profiling uncovered subtype-specific kinase activity, identifying actionable therapeutic targets.CONCLUSION Our findings further revealed previously uncharacterized somatic copy number alterations, extrachromosomal DNA landscape, and human-HPV fusion peptides, with implications for genetic heterogeneity and therapeutic targets. This study enhances the understanding of cervical cancer through deeper proteogenomic insights and facilitates the development of personalized therapeutic strategies to improve patient outcomes.FUNDING Noncommunicable Chronic Diseases-National Science and Technology Major Project (2025ZD0544102);The National Natural Science Foundation of China (82172584); Key Technology R&D Program of Hubei (2024BCB057 and 2025BCB053); National Natural Science Foundation of China (82373260); the “4+X” clinical trial programs of Women’s Hospital, School of Medicine, Zhejiang University (LY2022004); and the programs of Zhejiang Traditional Chinese Medicine Innovation Team (CZ2024009); and Guangxi Natural Science Foundation (2024GXNSFBA010045).
Xun Tian, Mansheng Li, Zhi Wang, Tian Fang, Yi Liu, Jin Fang, Lejing Wang, Zhichao Jiang, Xingyu Zhao, Chen Cao, Zhiqiang Yu, Meiying Yang, Songfeng Wu, Yifan Wu, Rui Tian, Hui Wang, Yunping Zhu, Zheng Hu