Classifying the tumor immune microenvironment in cervical cancer based on nuclear cytoplasmic consistent genes

Treatment options for advanced or recurrent cervical cancer (CC) remain limited, highlighting the urgent need for effective molecular biomarkers and therapeutic strategies. This study investigates nuclear-cytoplasmic consistent genes (NCCGs) in CC and other epithelial-derived malignancies, exploring their potential in molecular subtyping, prognosis evaluation, and therapeutic response prediction. NCCGs were identified using single-cell sequencing and single-nucleus RNA sequencing data. Through Cox regression and single-sample gene set enrichment analysis, TCGA-CESC cohort were stratified into high-risk (HRG) and low-risk (LRG) groups. Pan-cancer analysis of 14 TCGA epithelial-derived malignancies, including BLCA and BRCA, validated the classification capability and prognostic relevance of NCCGs. Clinical utility in predicting chemotherapy and immunotherapy responses was assessed using GSE168009 and IMvigor210CoreBiologies cohorts. NCCGs effectively stratified CC cohort into HRG and LRG. LRG demonstrated significantly better survival (HR = 3.24, 95% CI 1.57-6.7) and higher immune scores, including elevated CD8⁺ T and memory CD4⁺ T cell levels. Pan-cancer analysis confirmed NCCGs' ability to differentiate HRG and LRG and associate with overall survival. LRG also showed greater sensitivity to PD-1/CTLA4 inhibitors and chemotherapeutic agents (e.g., Panobinostat and Doxorubicin). The NCCG-based risk score showed robust accuracy in predicting chemotherapy and immunotherapy efficacy. This study reveals the molecular mechanisms and clinical significance of NCCGs in CC and epithelial-origin cancers. NCCGs hold value in molecular classification, prognostic assessment, and predicting therapeutic responses, offering new markers and targets for precision medicine.