Evidence map›Paper›PMID 41244925›Full record

ArticleFrontiers in oncology2025

Diabetes-associated differentially expressed genes as prognostic biomarkers and therapeutic targets in endometrial cancer: a comprehensive molecular analysis.

Ting Zhang, Ruiqing Sun, Xuejun Lian, Changyu Wang, Yuping Li, Kang Liu

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Article in Frontiers in oncology, 2025. 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

Authors and funding

6 authors.

Ting ZhangDepartment of Gynecology, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.
Ruiqing SunDepartment of Gynecology, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.
Xuejun LianDepartment of Gynecology, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.
Changyu WangDepartment of Gynecology, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.
Yuping LiDepartment of Gynecology, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.
Kang LiuDepartment of Burn and Plastic Surgery, Affiliated Chenggong Hospital of Xiamen University, Xiamen, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( 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

Indexed as

biomarkersdiabetesDM-DEGsprognostic modeUCEC

Identifiers

PMID41244925
PMCPMC12611713

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.