ORIGINAL RESEARCH article
Front. Oncol.
Sec. Gynecological Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1591040
This article is part of the Research TopicAdvances in Diagnosis and Treatment of Endometrial CancerView all 14 articles
Diabetes-Associated Differentially Expressed Genes as Prognostic Biomarkers and Therapeutic Targets in Endometrial Cancer: A Comprehensive Molecular Analysis
Provisionally accepted
- Chenggong Hospital, Xiamen University, Xiamen, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: Uterine corpus endometrial carcinoma (UCEC) is a prevalent malignancy increasingly observed in patients with diabetes mellitus. A comprehensive understanding of the intricate molecular interplay between diabetes and UCEC is crucial to develop effective prognostic and therapeutic strategies. This study aims to elucidate the relationship between diabetes and UCEC by identifying diabetes-related differentially expressed genes (DM-DEGs) and to establish a prognostic model to enhance clinical outcomes. Methods: Transcriptomic data sourced from The Cancer Genome Atlas (TCGA) was analyzed alongside diabetes-associated genes from GeneCards. Differential expression analysis revealed 931 differentially expressed genes (DEGs) in the training cohort and 1,206 DEGs in the validation cohort. By intersecting these DEGs with diabetes-related genes, we pinpointed 186 DM-DEGs, which were further subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Results: The univariate Cox analysis identified 17 DM-DEGs that demonstrated significant prognostic relevance. Through protein-protein interaction assessments, a LASSO regression model discerning five pivotal genes (TRPC1, SELENOP, CDKN2A, GSN, PGR) for prognostic modeling was constructed. This model successfully stratified patients into high- and low-risk cohorts, with Kaplan-Meier survival analysis and Receiver Operating Characteristic (ROC) curve assessment confirming notable survival differentiations. A personalized nomogram, integrating clinical parameters and risk scores, exhibited robust predictive capability, yielding a C-index of 0.781. Gene set enrichment analysis (GSEA) suggested significant involvement in pathways related to glucose and lipid metabolism. Conclusion: In conclusion, our study establishes and validates a robust prognostic signature based on diabetes-related genes (DM-DEGs) for UCEC. This signature not only effectively stratifies patient risk but also delineates specific molecular pathways, such as those involving SELENOP, CDKN2A, and PGR, through which the diabetic milieu may drive tumor aggressiveness. These findings provide a mechanistic rationale for the diabetes-UCEC link and pave the way for developing personalized treatment strategies. Future work should focus on translating this signature into clinical practice and elucidating the precise biological roles of these DM-DEGs.
Keywords: UCEC1, Diabetes2, DM-DEGs3, Biomarkers4, prognostic mode5
Received: 10 Mar 2025; Accepted: 16 Oct 2025.
Copyright: © 2025 Zhang, Sun, Lian, Wang, Li and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kang Liu, liuk828@126.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.