A novel NFAT1-IL6/JAK/STAT3 signaling pathway related nomogram predicts overall survival in gliomas

• Published in: Scientific reports Vol. 13; no. 1; p. 11401
• Main Authors: Zhang, Chao, Wang, Yu, Shao, Wei, Zhou, Dongrui, Yu, Dong, Hou, Shiqiang, Lin, Ning
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.07.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/1647; 631/45; 631/67; 692/4017; 692/4028; 692/53; 692/617; 692/699; Correlation analysis; Genomes; Glioma; Glioma - genetics; Humanities and Social Sciences; Humans; Interleukin-6 - genetics; Medical prognosis; multidisciplinary; NF-AT1 protein; NF-kappa B; NF-κB protein; Nomograms; Prediction models; Prognosis; Protein biosynthesis; Protein synthesis; Science; Science (multidisciplinary); Signal Transduction; Snakes; Stat3 protein; STAT3 Transcription Factor - genetics; Survival; Training; Transcription factors
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-38629-1

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.