ArticlePeerJ2026
A prognostic signature based on methionine metabolism-related genes for cervical cancer: integrated transcriptomic and experimental validation.
Article in PeerJ, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Background: Cervical cancer (CC) remains one of the most prevalent malignancies in the female reproductive system. Methionine metabolism (MM) plays a pivotal role in various biological processes and has been implicated in cancer progression. However, its mechanisms in CC remain unclear. Methods: Transcriptomic data from 305 patients in The Cancer Genome Atlas (TCGA) (training cohort) and 299 patients from the Gene Expression Omnibus (GEO) (GSE44001) (external validation cohort) were analyzed for differentially expressed MM-related genes (MM-RGs). Prognostic MM-RGs were identified using Cox regression, proportional hazards testing, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. A risk model was constructed and validated. Functional enrichment (Gene Set Enrichment Analysis/Gene Set Variation Analysis (GSEA/GSVA)), Results: Eight MM-RGs (MTHFD1, SMYD2, MSRB3, MTR, ENOPH1, DNMT3B, SLC38A7, PEMT) were identified as prognostic genes. A robust risk score model was developed, stratifying patients into high- and low-risk groups with significant differences in survival outcomes. Functional enrichment revealed pathways such as ECM-receptor interaction and focal adhesion. Immune analysis indicated altered infiltration of Tregs and mast cells. Conclusion: This study establishes a novel MM-based prognostic model for CC and based on
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