ArticleScientific reports2023
A novel NFAT1-IL6/JAK/STAT3 signaling pathway related nomogram predicts overall survival in gliomas.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 8 citations in OpenAlex.
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- Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk.Cancer medicine · 2026Article
- Mendelian Randomization in Conjunction with WGCNA Was Employed to Investigate the Potential Role of the Liver-Brain Axis in the Pathogenesis of Hepatocellular Carcinoma and Alzheimer's Disease.Molecular neurobiology · 2025Article
- Development of a prognostic model based on seven mitochondrial autophagy- and ferroptosis-related genes in lung adenocarcinoma.BMC medical genomics · 2025Article
- Integration of histone modification-based risk signature with drug sensitivity analysis reveals novel therapeutic strategies for lower-grade glioma.Frontiers in pharmacology · 2024Article
- Prognostic significance of CNNM4 in ovarian cancer: a comprehensive bioinformatics analysis.Frontiers in oncology · 2024Article
- Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application.NPJ digital medicine · 2023Article
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7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The NFAT1-mediated IL6/JAK-STAT signaling pathway has been observed to contribute to malignant progression in glioma patients. To predict the overall survival (OS) rate of these patients, a prognostic model was developed based on this pathway. Two datasets, mRNAseq_325 and mRNAseq_693, were obtained from the China Glioma Genome Atlas (CGGA), excluding some patients with a lack of survival information, resulting in the inclusion of 684 glioma cases. The two groups were randomly divided into training and validation groups to analyze the differential expression of NFAT1 in pan-cancer and investigate the relationship between differential NFAT1 expression and glioma clinicopathological factors and Transcriptional subtypes. A prediction model based on the IL6/JAK/STAT signaling pathway was constructed using the LASSO-COX dimension reduction analysis to predict the OS of glioma patients. Pearson correlation analysis was utilized to identify gene sets associated with patient risk scores and to perform GO and KEGG analyses. NFAT1 is differentially expressed in a variety of cancers and is enriched in the more malignant potential glioma subtypes. It is an independent prognostic factor in glioma patients, and its expression is significantly positively correlated with the IL6/JAK/STAT signalling pathway in glioma patients. The final prediction model incorporating the seven candidate genes together with other prognostic factors showed strong predictive performance in both the training and validation groups. Risk scores of glioma patients were correlated with processes such as NF-κB and protein synthesis in glioma patients. This individualized prognostic model can be used to predict the OS rate of patients with glioma at 1, 2, 3, 5, and 10 years, providing a reference value for the treatment of glioma patients.
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