Construction and Validation of a Prognostic Model for Cervical Cancer Based on Senescence-Associated Genes

CHEN Jiahui; DENG Jingxian; LI Lesai; PENG Xiaoning; ZHANG Yong

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Journal of Hunan Normal University(Medical Science) ›› 2026, Vol. 23 ›› Issue (1) : 35-44.

Basic Medicine

Construction and Validation of a Prognostic Model for Cervical Cancer Based on Senescence-Associated Genes

CHEN Jiahui¹, DENG Jingxian¹, LI Lesai², PENG Xiaoning¹, ZHANG Yong¹

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Abstract

Objective This study aimed to develop an efficient prognostic model by analyzing the expression of senescence-associated genes (SRGs), combined with transcriptome and single-cell RNA sequencing data, to identify key senescence-related genes with prognostic significance in cervical cancer. Method Genes related to the keyword “senescence” were first obtained from the Genecards database. Using the single-cell RNA sequencing dataset GSE253690 from the Gene Expression Omnibus (GEO) database, senescence-associated scores were calculated for each cell. Based on these scores, differentially expressed genes (DEGs) between the high-score and low-score groups were identified. Subsequently, single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were employed to identify senescence-related module genes in cervical cancer patients. The intersection of DEGs and module genes was subjected to univariate Cox analysis, followed by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to construct a prognostic model based on senescence-associated genes. The GSE44001 and GSE52903 datasets from GEO were used as external validation sets to verify the model's accuracy. The precision of the model in predicting the prognosis of cervical cancer patients was assessed by constructing a clinical nomogram and performing receiver operating characteristic (ROC) curve analysis. Finally, the expression differences of key genes between normal cervical cells and cervical cancer cells were detected via human protein atlas (HPA) analysis and real-time quantitative polymerase chain reaction (RT-qPCR). Results A prognostic model based on senescence-associated genes was successfully constructed and demonstrated good accuracy and predictive precision. Conclusion The senescence-associated gene-based model we developed can effectively assess the prognosis of cervical cancer, providing a new reference for clinicians in selecting treatment strategies.

Key words

cervical cancer / cellular senescence / senescence-associated secretory phenotype / prognostic model

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CHEN Jiahui, DENG Jingxian, LI Lesai, PENG Xiaoning, ZHANG Yong. Construction and Validation of a Prognostic Model for Cervical Cancer Based on Senescence-Associated Genes[J]. Journal of Hunan Normal University(Medical Science). 2026, 23(1): 35-44

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