Comprehensive analysis of genes based on chr1p/19q co-deletion reveals a robust 4-gene prognostic signature for lower grade glioma.

Purpose: The chr1p/19q co-deletion is a favorable prognostic factor in patients with lower grade glioma. The aim of this study was to reveal key genes for prognosis and establish prognostic gene signatures based on genes encoded by chr1p/19q. Materials and methods: The data was downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between lower grade glioma tissue and normal brain were identified. The univariate COX regression, robust likelihood-base survival analysis (rbsurv) and multivariate COX regression analysis were used to establish the 4-gene-signature based on the DEGs. The receiver operating characteristic (ROC) curve and the Kaplan-Mere curve were used to verify the prediction accuracy of the signature. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were also performed to explore the reasons for good prognosis in patients with chr1p/19q deletion. Results: A total of 1346 DEGs were identified between lower grade glioma samples and normal brain samples in GSE16011, including 56 up-regulated mRNAs located on chr1p and 20 up-regulated mRNAs located on chr19q. We established a 4-gene-signature that was significantly associated with survival based on the 76 gene. The AUC of the 4-gene-signature for 5-year OS in TCGA and CGGA was 0.837 and 0.876, respectively, which was superior compared to other parameters such as chr1p/19q co-deletion, IDH mutant, WHO grade and histology type, especially in chr1p/19q non-co-deletion patients. GSEA and KEGG analysis suggested that the prolongation of chr1p/19q in patients could be associated with cell cycle and DNA mismatch repairing. Conclusions: We established a robust 4-gene-signature based on the chr1p/19q and we explored the potential function of these newly identified survival-associated genes by bioinformatics analysis. The 4-gene from the signature are promising molecular targets to be used in the future.