Prognostic power of a lipid metabolism gene panel for diffuse gliomas

• DOI: 10.1111/jcmm.14647
• Publication Date: 2019-09-02T04:54:21Z
• Authors: Fan Wu; Zheng Zhao; Rui‐Chao Chai; Yu‐Qing Liu; Guan‐Zhang Li; Hao‐Yu Jiang; Tao Jiang
• Keywords: Gene signature

Abstract Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion cancers. However, the diverse lipid programmes prognostic value during glioma progression remain unclear. Here, metabolism‐related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) Chinese Glioma (CGGA) database. Gene ontology (GO) gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed phosphatidylinositol progress. According to differential between LGG GBM, we developed a nine‐gene Cox proportional hazards model with elastic net penalty, CGGA cohort was used for validation set. Survival revealed obtained could differentiate outcome low‐ high‐risk patients both cohorts. Meanwhile, multivariate regression indicated this signature significantly independent factor diffuse gliomas. GSEA cases associated phenotypes division immune response. Collectively, our findings provided new sight on