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

Abstract

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.

Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

“…In the present study, we performed the stratification, AUC, C-index calculation, and nomogram analyses to confirm it. In line with previous studies [10,22,26], our results showed that the OS of patients with the same age and IDH1 mutation status can be further stratified by the risk score. Also, the AUC and C-index of risk score were obviously higher than age (AUC = 0:827 vs. 0.564; C-index = 0:812 vs. 0.743) and IDH1 mutation status (AUC = 0:827 vs. 0.646; C-index = 0:812 vs. 0.733).…”

“…Furthermore, the poor prognosis of LGG was traditionally determined according to clinical characteristics, including older age [23] and IDH1 nonmutational status [24,25]. Thus, whether the risk score was superior or added additional prognostic value to these current clinical systems for prognosis prediction was also an important focus in the signature studies [10,22,26]. In the present study, we performed the stratification, AUC, C-index calculation, and nomogram analyses to confirm it.…”

Identification and validation of a three-gene signature as a candidate prognostic biomarker for lower grade glioma

“…With the development of sequencing technology, molecular biomarkers for the diagnosis of LGG have attracted widespread attention (Cancer Genome Atlas Research Network et al, 2015). Prognostic factors for the low-grade glioma that are well known include IDH mutations (Batsios et al, 2019;Ye et al, 2019), 1p/19q co-deficiency (Zhang et al, 2019a), ATRX mutation (Ren et al, Figure 11 Comparison of our 3-gene model and other literature models. The-dependent ROC analysis was performed to compare the three models in predicting 1-year, 3-year, and 5-year overall survival in TCGA dataset (A-C) and CGGA dataset (D-F).…”

“…Recently, Zeng et al (2018) reported a model containing three genes (EMP3, GSX2, EMILIN3) based on integrative analysis of DNA methylation and gene expression in TCGA dataset. Zhang et al (2019a) also reported a 4-gene (EMP3, GNG12, KIF2C, IFI44) prognostic signature based on genes encodes by chr1p/19q. To compare the prognostic values of our prognostic signature and their model, we performed time-dependent ROC curve analysis in our model and other models based on the risk score calculated by the regression coefficients which obtained by themselves and the expression level of members in their signature were shown in both TCGA and CGGA dataset.…”

Peer Review #1 of "Identification and validation of a three-gene signature as a candidate prognostic biomarker for lower grade glioma (v0.1)"

“…Recently，Chen X.P et al reported a model containing 3 genes(EMP3、GSX2、EMILIN3) based on integrative analysis of DNA methylation and gene expression in TCGA dataset (Zeng et al 2018).Chuang Zhang et al also reported a 4-gene(EMP3、GNG12、KIF2C、IFI44) prognostic signature based on genes encodes by chr1p/19q (Zhang et al 2019a). To compare the prognostic values of our prognostic signature and their model，we performed time-dependent ROC curve analysis in our model and other models based on the risk score calculated by the regression coefficients which obtained by themselves and the expression level of members in their signature showed in both TCGA and CGGA dataset.…”