Evidence map›Paper›PMID 42234248›Full record

ArticleDiscover oncology2026

Construction and validation of a novel prognostic risk model in cervical cancer: integrating lactylation-related genes linked to radiotherapy‑associated transcriptional changes.

Yi Tang, Liyu Ning, Xinru Yang, Na Li, Yanyu Li, Yun Zhou, Hui Hui

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Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Yi Tang *The Affiliated Xuzhou Clinical College of Xuzhou Medical University, No. 209, Tongshan Road, Xuzhou, 221004, Jiangsu, P.R. China.
Liyu Ning *Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Xinru YangThe Affiliated Xuzhou Clinical College of Xuzhou Medical University, No. 209, Tongshan Road, Xuzhou, 221004, Jiangsu, P.R. China.
Na LiDepartment of Radiation Oncology, Xuzhou Central Hospital Affiliated to Southeast University, No. 199, Jiefang South Road, Xuzhou, 221009, Jiangsu, P.R. China.
Yanyu LiDepartment of Gynecology and Obstetrics, Xuzhou Central Hospital Affiliated to Southeast University, Xuzhou, 221009, China.
Yun ZhouThe Affiliated Xuzhou Clinical College of Xuzhou Medical University, No. 209, Tongshan Road, Xuzhou, 221004, Jiangsu, P.R. China. zhouyun3232@outlook.com.
Hui HuiDepartment of Radiation Oncology, Xuzhou Central Hospital Affiliated to Southeast University, No. 199, Jiefang South Road, Xuzhou, 221009, Jiangsu, P.R. China. whuihui18@163.com.

Funding

2025 Annual Pengcheng Talent Program Project of Xuzhou Municipal Health Commission No. 2025TD08
6 · The paper itself

Abstract

backgroundThe association between lactylation and tumor radiotherapy has become a widely studied hotspot. However, the prognostic value of lactylation-related genes (LRGs) linked to radiotherapy‑associated transcriptional changes in cervical cancer remains unclear.

methodsBased on gene expression data from public databases and LRGs, we identified key genes for cervical cancer prognostics and verified their expression levels. Subsequently, LASSO regression with 10-fold cross-validation was used for model construction and internal validation. Patients were divided into different groups according to the optimal cut-off value of risk score, and their differences in biological function/pathway, immunoregulation, and tumor mutation burden (TMB) were analyzed. A nomogram for predicting the survival probability was also constructed.

resultsOur study identified two key genes (RFC4 and STMN1), whose expression was upregulated in tumor tissues but significantly downregulated during radiotherapy. The risk model incorporating the two genes was verified internally and exhibited favourable prognostic stratification capability. Patients were divided into high- and low-risk groups; differentially expressed genes between the groups were significantly enriched for immune-, angiogenesis-, and metabolism-related functions/pathways. Furthermore, the two groups exhibited distinct immune cell infiltration levels and gene mutation, with the low-risk group showing superior survival outcomes. Multivariate Cox analysis identified risk score, overall stage, and T stage as independent prognostic factors (P < 0.05). The nomogram incorporating these factors effectively predicted 1-year, 2-year, and 3-year survival rates.

conclusionThis study provides a promising prognostic model for risk stratification of cervical cancer patients and identifies two biomarkers, which will help promote the understanding of the relationship between radiotherapy, lactylation, and prognosis in cervical cancer.

Indexed as

Cervical cancerLactylationPrognostic risk modelRadiotherapy

Identifiers

PMID42234248
PMCPMC13447652

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