ArticleBMC genomics2022
Construction and validation of a novel Ferroptosis-related gene signature predictive model in rectal Cancer.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- An ABCC1-based risk model is effective in the diagnosis of synchronous peritoneal metastasis in advanced colorectal cancer.British journal of cancer · 2025Article
- Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer.Briefings in bioinformatics · 2025Article
- Expression Analysis of FANCD2 in Endometrial Carcinoma.Cancer management and research · 2024Article
- Identification and Validation of Potential Ferroptosis-Related Genes in Glucocorticoid-Induced Osteonecrosis of the Femoral Head.Medicina (Kaunas, Lithuania) · 2023Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRectal cancer (RC) is one of the most common malignant tumors. Ferroptosis is an iron-dependent form of cell death, which plays an important role in various cancers. However, the correlation between ferroptosis-related genes (FRGs) and prognosis in RC remains unclear.
methodsGene expression data from The Cancer Genome Atlas Rectum adenocarcinoma (TCGA-READ) and GSE87211 were downloaded. Clustering and functional enrichment were evaluated. A FRGs risk score was established based on the univariate Cox analysis and the Least absolute shrinkage and selection operator (LASSO) analysis. K-M analysis and ROC analysis were conducted to determine prognostic values. qRT-PCR was performed to validate levels of mRNA expression. Multivariate Cox analysis was used to build a prognostic prediction model based on the risk score.
resultsBased on FRGs, RC patients were grouped into two clusters. In the functional enrichment of differentially expressed genes between the two clusters, immune-related pathways dominated. A novel FRGs signature with 14 genes related to the overall survival (OS) of RC was established. qRT-PCR of the 14 genes identified TP63, ISCU, PLIN4, MAP3K5, OXSR, FANCD2 and ATM were overexpressed in RC tissue; HSPB1, MAPK1, ABCC1, PANX1, MAPK9 and ATG7 were underexpressed; TUBE1 had no difference. The high-risk group had a significantly lower OS than the low-risk group (P < 0.001), and ROC curve analysis confirmed the signature's predictive capacity. Multivariate analysis demonstrated that the risk score and age were independent prognostic factors.
conclusionA novel FRGs model can be used to predict the prognosis in RC, as well as to guide individual treatment.
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