1. Novel targets and their functions in the prognosis of uterine corpus endometrial cancer patients.
- Author
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Sui X, Feng P, Guo J, Chen X, Chen R, Zhang Y, He F, and Deng F
- Subjects
- Humans, Female, Prognosis, Gene Expression Profiling, Nomograms, Transcriptome genetics, Middle Aged, Endometrial Neoplasms genetics, Endometrial Neoplasms pathology, Biomarkers, Tumor genetics, Gene Expression Regulation, Neoplastic, ROC Curve
- Abstract
Aberrant mRNA expression is implicated in uterine corpus endometrial carcinoma (UCEC) oncogenesis and progression. However, effective prognostic biomarkers for UCEC remain limited. We aimed to construct a reliable multi-gene risk model using gene expression profiles. Utilizing TCGA data (543 UCEC samples, 35 controls), we identified 1517 differentially acting genes. Weighted gene co-expression complex analysis (WGCCA), hub gene screening, and risk regression analysis (RRA) were employed to determine prognosis-related genes and construct the risk model. Nomograms visualized risk scores and receiver operator characteristic (ROC) curves assessed model performance. Seven novel prognosis-related hub genes (ANGPT1, ASB2, GAL, GDF7, ONECUT2, SV2B, TRPC6) were identified. The model's concordance index (C index) by multivariate Cox regression analysis was 0.79. ROC curves yielded AUCs of 0.811 (3-year) and 0.79 (5-year), demonstrating the model's efficacy in predicting UCEC survival. Our study proposes a promising seven-biomarker risk model for predicting UCEC prognosis, offering potential clinical utility., Competing Interests: Declarations Conflict of interest The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)
- Published
- 2024
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