ArticleBMC cancer2020
Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- GOT1 inhibits hepatocellular carcinoma progression by regulating SLC25A5-dependent mitochondrial apoptosis.Oncogene · 2026Article
- Pathogenic Mechanisms in Cervical Cancer: Energy Metabolism, Hypoxia and Therapy.Life (Basel, Switzerland) · 2026Review
- Transcriptomics and single-cell RNA sequencing uncover prognostic characteristics and immune regulatory mechanisms of lactylation in cervical cancer.BioImpacts : BI · 2026Article
- Construction of a lipid metabolism-based prognostic gene signature in cervical squamous cell carcinoma and validation of LIPG's oncogenic role.Cancer cell international · 2025Article
- PFKM Promotes the Progression of Gastric Cancer by Up-regulating CNTN1 Expression Through H3K18la Modification.Applied biochemistry and biotechnology · 2025Article
- Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer.Scientific reports · 2025Article
- Predictive Value and Immunological Role of the HSPA5 Gene in Cervical Cancer.Biochemical genetics · 2025Article
- Cross-talk between cuproptosis and ferroptosis to identify immune landscape in cervical cancer for mRNA vaccines development.European journal of medical research · 2024Article
- A hypoxia-derived gene signature to suggest cisplatin-based therapeutic responses in patients with cervical cancer.Computational and structural biotechnology journal · 2024Article
- Oncogenic HPV-induced high expression of ESM1 predicts poor prognosis and regulates aerobic glycolysis in cervical cancer.iScience · 2024Article
- Increased Gene Expression ofCells · 2023Article
- Metabolism-associated molecular classification of cervical cancer.BMC women's health · 2023Article
- Research progress on the GRP78 gene in the diagnosis, treatment and immunity of cervical cancer.European journal of medical research · 2023Review
- Article
- Characterization of glycometabolism and tumor immune microenvironment for predicting clinical outcomes in gastric cancer.iScience · 2023Article
- Identification of Novel Genes and Associated Drugs in Cervical Cancer by Bioinformatics Methods.Medical science monitor : international medical journal of experimental and clinical research · 2022Article
- Identifying a cervical cancer survival signature based on mRNA expression and genome-wide copy number variations.Experimental biology and medicine (Maywood, N.J.) · 2022Article
- Construction and Verification of a Combined Hypoxia and Immune Index for Clear Cell Renal Cell Carcinoma.Frontiers in genetics · 2022Article
- Comprehensive Proteomic Analysis of Colon Cancer Tissue Revealed the Reason for the Worse Prognosis of Right-Sided Colon Cancer and Mucinous Colon Cancer at the Protein Level.Current oncology (Toronto, Ont.) · 2021Article
- Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis.Cancer cell international · 2021Article
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11 authors.
Funding
Abstract
backgroundCervical cancer (CC) is one of the most common gynaecological cancers. The gene signature is believed to be reliable for predicting cancer patient survival. However, there is no relevant study on the relationship between the glycolysis-related gene (GRG) signature and overall survival (OS) of patients with CC.
methodsWe extracted the mRNA expression profiles of 306 tumour and 13 normal tissues from the University of California Santa Cruz (UCSC) Database. Then, we screened out differentially expressed glycolysis-related genes (DEGRGs) among these mRNAs. All patients were randomly divided into training cohort and validation cohort according to the ratio of 7: 3. Next, univariate and multivariate Cox regression analyses were carried out to select the GRG with predictive ability for the prognosis of the training cohort. Additionally, risk score model was constructed and validated it in the validation cohort.
resultsSix mRNAs were obtained that were associated with patient survival. The filtered mRNAs were classified into the protective type (GOT1) and the risk type (HSPA5, ANGPTL4, PFKM, IER3 and PFKFB4). Additionally, by constructing the prognostic risk score model, we found that the OS of the high-risk group was notably poorer, which showed good predictive ability both in training cohort and validation cohort. And the six-gene signature is a prognostic indicator independent of clinicopathological features. Through the verification of PCR, the results showed that compared with the normal cervial tissuses, the expression level of six mRNAs were significantly higher in the CC tissue, which was consistent with our findings.
conclusionsWe constructed a glycolysis-related six-gene signature to predict the prognosis of patients with CC using bioinformatics methods. We provide a thorough comprehension of the effect of glycolysis in patients with CC and provide new targets and ideas for individualized treatment.
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