Five Genes Associated With Survival in Patients With Lower-grade Gliomas Were Identified by Information-theoretical Analysis

Abstract

Background/Aim: Understanding of the molecular events associated with progression and survival differences in patients with lower-grade gliomas (LGGs) is still unclear. The comparison of findings across studies using different datasets and methods is essential for a new molecular-based classification system. The aim of the study was to identify biomarkers for prognostic classification of patients with LGGs, and furthermore to lay a foundation for future development of targeted therapies for LGGs. Patients and Methods: Using information-theoretic and statistical approaches, we analyzed mRNA expression data for 18,413 genes from LGG samples in order to identify candidate biomarkers for survival. The candidate genes were then evaluated for their potential as prognostic biomarkers using multivariable Cox regression analyses that adjusted for the effects of age and grade. Results: WEE1, EMP3, E2F7, CD58 and NSUN7 genes were identified as candidate biomarkers of LGGs and their high expression was associated with significantly shorter survival. The hazard ratios for mortality were 5.02 (95% CI=3.40-7.40) for WEE1, for EMP3, for E2F7, for ) for NSUN7. In addition, the expression pattern of these genes, associated with shorter survival in LGGs, was also observed in glioblastoma multiforme. Conclusion: Identification of genes associated with poor outcomes will provide insights into novel biological mechanisms that may lead to improvement in progression and survival for patients with LGGs.

Low expression of CDHR1 is an independent unfavorable prognostic factor in glioma

“…Consistent with the high expression in GBM subtype, previous reports suggested that CCDC109B [27], CD58 [28], CLIC1 [29], EFEMP2 [30], EMP3 [31][32][33], LAMC1 [34], LGALS1 [35], PDLIM1 [36] and TNFRSF1A [37,38] were all bad prognostic factors in glioma, as were summarized in Fig. 2A.…”

The role of RNA m5C modification in cancer metastasis

“…For mRNA, DNMT2 and NSUN2 are the main writers, since mRNA m 5 C is critical for numerous cellular biological processes, such as cell growth, differentiation, movement and RNA modification. Furthermore, NSUN2 and NSUN7 bind to noncoding RNAs that regulate cell metabolism 21 , 55 , 115 . Writers of RNA m 5 C usually work in partnership with readers.…”

“…Taking the typical m 5 C methylase NSUN2 as an example, NSUN2 has been shown to participate in multiple pan-cancer pathways: promoting cell progression, migration and invasion in breast cancer [57,109]; promoting tumorigenesis and development in skin cancer [27]; promoting cell growth, tumor progression and metastasis in urothelial carcinoma of the bladder [54]; promoting tumorigenesis and cell proliferation in gall bladder cancer [110]; increasing the sensitivity of HeLa cells to 5-fluorouracil [28]; promoting cell migration, invasion and drug resistance in esophageal squamous cell carcinoma (ESCC) [111]; promoting proliferation in gastric cancer [112]; promoting tumorigenesis, migration and invasion in hepatocellular carcinoma (HCC) [113]. NSUN4, NSUN5, NSUN6 and NSUN7 are associated with cancer development in HCC, head and neck squamous cell carcinoma (HNSCC), pancreatic cancer and glioma [29,[114][115][116]. In addition, the tumor immune microenvironment is affected by NSUN2 and NSUN6 through multiple pathways, such as the regulation of RNA metabolism, the cell cycle and immune cell activation [117].…”

Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

“…Gene biomarkers have always been at the forefront of the development of personalized medicine, especially in the field of cancer. Gene signature-based RNA expression obtained by analyzing gene profiling has been shown to predict the tumor behavior and to distinguish patients with specific tumor grades and/or prognosis ( 13 , 14 ) in various types of cancer, such as esophageal squamous cell carcinoma, hepatocellular carcinoma, bladder carcinoma, breast cancer, and glioblastoma. In the current study, we aimed to analyze the gene expression profile and develop an effective gene signature for accurate prognosis prediction of LGG patients.…”