Abstract
BACKGROUND: Ubiquitination, a pivotal posttranslational modification, plays a central role in regulating many biological processes. Nevertheless, its prognostic significance in cervical cancer remain largely unexplored. METHODS: Using unsupervised consensus cluster analysis, we identified molecular subtypes based on ubiquitin-associated genes. We also employed WGCNA to identify co-expressed genes and constructed a risk prognosis model using LASSO-penalized multivariate Cox analysis. We analyzed and illustrated the somatic mutational characteristics of patients according to their risk groups. To further our understanding, we assessed the correlation between the risk model and immune infiltration using the TIDE algorithm. Lastly, we investigated whether USP21 could influence the malignant behavior of cervical cancer cells. RESULTS: TCGA-CESC samples were classified into three distinct subtypes based on ubiquitin-related genes. WGCNA analysis identified 1549 genes. We then developed a robust 13-gene signature (KLHL22, UBXN11, FBXO25, ANKRD13A, WSB1, WDTC1, ASB1, INPPL1, USP21, MIB2, USP30, TRIM32, SOCS1) that consistently performed well across various datasets. The risk classification significantly correlated with survival in both univariate and multivariate analyses. Additionally, mutation distribution in the CESC cohort varied among risk groups. Specifically, the high-risk group showed higher levels of TIDE scores, T-cell exclusion, CAF scores, and MDSC scores compared to the low-risk group. We also found that USP21 could promote the migration ability of cervical cells. CONCLUSION: This study successfully established and validated a novel 13-gene signature, a valuable marker for predicting cervical cancer patient survival.