The promising novel biomarkers and candidate small molecule drugs in lower‐grade glioma: Evidence from bioinformatics analysis of high‐throughput data

Abstract

Overall survival of patients with low‐grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty‐eight nodes with 603 interactions were obtained from the establishment of protein‐protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients’ prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS‐275 (enrichment score = −0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

GABRD promotes progression and predicts poor prognosis in colorectal cancer

“…Although Gross et al observed a ubiquitous overexpression of GABRD across various cancer types in the TCGA dataset, these authors did not go any further to explore the prognostic significance of GABRD overexpression in specific tumor types [10]. GABRD has also been referred to in tumors in several other studies [9,11,38,39], but many of these are based on bioinformatic data and the functional relevance of GABRD to carcinogenesis and tumor progression remains to be elucidated.…”

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

“…GBM is one of the most commonly seen primary malignant brain tumor in adults with an overall poor prognosis (Ostrom et al, 2018;Zhang et al, 2019;Jin et al, 2020). The recurrence rate of GBM is particularly high.…”

Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

“…The human interactome map has a higher coverage on proteins encoded by human genes; therefore, it can provide additional insights than those based only on pathway databases. Moreover, PPI networks have been used to infer candidate genes for different types of cancer (44)(45)(46)(47)(48). These networks are sensitive to disruption of high degree proteins (proteins with numerous interaction partners, also named hub genes) (49,50) since protein degree correlates with its gene essentiality for phenotype survival.…”