ArticleScientific reports2024
Identifying colorectal cancer subtypes and establishing a prognostic model using metabolic plasticity and ferroptosis genes.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
- Iron, inflammation, and intestinal tumors: the crucial triad in colorectal cancer progression and therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
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Authors and funding
5 authors.
Funding
Abstract
Metabolic plasticity and ferroptosis are essential for colorectal cancer (CRC) progression. The effects and prognostic value of metabolic plasticity- and ferroptosis-related genes (MPFRGs) in CRC remain unclear. We established a prognostic model for CRC patients by identifying important genes in metabolic plasticity and ferroptosis. Data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus; MPFRG data were obtained from GeneCards and FerrDb. We performed functional (to explore differences between the two metabolic subtypes) and single-sample gene set (to assess the immune environment) enrichment analyses. Immunophenotype, tumor immunological dysfunction, and exclusion scores were assessed to determine patient immune responses. A least absolute shrinkage and selection operator-Cox regression model comprising 10 significant differentially expressed genes of metabolic plasticity and ferroptosis (MPFDEGs) was constructed using TCGA training cohort and validated using the GSE17536 and GSE39582 datasets. We established a nomogram comprising metabolic plasticity- and ferroptosis-based signatures, revealing the clinical application and potential molecular mechanisms underlying the role of MPFRGs in CRC. Our model (developed based on 10 MPFDEGs) is efficient for calculating the overall survival of CRC patients. Our findings provide new strategies for the clinical management and individualized treatment of these patients.
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