ArticleFrontiers in genetics2025
A lipid metabolism and lysosome-based risk signature for prognosis and immune response prediction in uterine corpus endometrial carcinoma.
Article in Frontiers in genetics, 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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Abstract
Background: The dysregulation of genes related to lipid metabolism and lysosomal function has been reported to significantly contribute to tumor progression. In this study, we systematically explored the roles played by lipid metabolism and lysosomes in uterine corpus endometrial carcinoma (UCEC), aiming to identify potential biomarkers for predicting prognosis and immune checkpoint therapy efficacy. Methods: Genes associated with lipid metabolism and lysosomal function were retrieved from the MSigDB and GO databases. Transcriptomic data and clinical information of patients were acquired from The Cancer Genome Atlas database. A prognostic model was constructed using consensus clustering, univariate Cox regression, and LASSO regression. ROC curves, Kaplan-Meier plots, and calibration curves were employed to assess the predictive capacity of the model, while ssGSEA, TIDE, and IPS were used to evaluate the response of high- and low-risk groups to immunotherapy. Drug sensitivity was assessed with the "oncoPredict" R package. Given that we identified a strong association between Results: An eight-gene ( Conclusion: We constructed a risk prognostic model for UCEC based on a combination of lysosomal- and lipid metabolism-related genes. Our findings highlight the oncogenic potential of PLAAT1 in endometrial cancer and provide novel insights into the diagnosis and therapy of this cancer type.
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