Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis
The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
|
Series: | Biomolecules |
Subjects: | |
Online Access: | https://www.mdpi.com/2218-273X/9/5/201 |
id |
doaj-12932b24d8ad46c2b4da03b6ec960339 |
---|---|
record_format |
Article |
spelling |
doaj-12932b24d8ad46c2b4da03b6ec9603392020-11-24T21:28:38ZengMDPI AGBiomolecules2218-273X2019-05-019520110.3390/biom9050201biom9050201Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics AnalysisAli Mohamed Alshabi0Basavaraj Vastrad1Ibrahim Ahmed Shaikh2Chanabasayya Vastrad3Department of Clinical Pharmacy, College of Pharmacy, Najran University, Najran 61441, Saudi ArabiaDepartment of Pharmaceutics, SET`S College of Pharmacy, Dharwad, Karnataka 580002, IndiaDepartment of Pharmacology, College of Pharmacy, Najran University, Najran 61441, Saudi ArabiaBiostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, IndiaThe present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and TF-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs was carried out. A total of 590 DEGs, including 243 up regulated and 347 down regulated genes, were diagnosed between scrambled shRNA expression and Lin7A knock down. The up-regulated genes were enriched in ribosome, mitochondrial translation termination, translation, and peptide biosynthetic process. The down-regulated genes were enriched in focal adhesion, VEGFR3 signaling in lymphatic endothelium, extracellular matrix organization, and extracellular matrix. The current study screened the genes in the PPI network, extracted modules, miRNA-target genes regulatory network, and TF-target genes regulatory network with higher degrees as hub genes, which included <i>NPM1, CUL4A, YIPF1, SHC1, AKT1, VLDLR, RPL14, P3H2, DTNA, FAM126B, RPL34</i>, and <i>MYL5</i>. Survival analysis indicated that the high expression of <i>RPL36A</i> and <i>MRPL35</i> were predicting longer survival of GBM, while high expression of <i>AP1S1</i> and <i>AKAP12</i> were predicting shorter survival of GBM. High expression of <i>RPL36A</i> and <i>AP1S1</i> were associated with pathogenesis of GBM, while low expression of <i>ALPL</i> was associated with pathogenesis of GBM. In conclusion, the current study diagnosed DEGs between scrambled shRNA expression and Lin7A knock down samples, which could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new diagnostic markers might be used as therapeutic targets for GBM.https://www.mdpi.com/2218-273X/9/5/201glioblastoma multiformtopology analysismiRNA-target gene networkTF-target gene networkdifferential gene expression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ali Mohamed Alshabi Basavaraj Vastrad Ibrahim Ahmed Shaikh Chanabasayya Vastrad |
spellingShingle |
Ali Mohamed Alshabi Basavaraj Vastrad Ibrahim Ahmed Shaikh Chanabasayya Vastrad Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis Biomolecules glioblastoma multiform topology analysis miRNA-target gene network TF-target gene network differential gene expression |
author_facet |
Ali Mohamed Alshabi Basavaraj Vastrad Ibrahim Ahmed Shaikh Chanabasayya Vastrad |
author_sort |
Ali Mohamed Alshabi |
title |
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis |
title_short |
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis |
title_full |
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis |
title_fullStr |
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis |
title_full_unstemmed |
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis |
title_sort |
identification of crucial candidate genes and pathways in glioblastoma multiform by bioinformatics analysis |
publisher |
MDPI AG |
series |
Biomolecules |
issn |
2218-273X |
publishDate |
2019-05-01 |
description |
The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and TF-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs was carried out. A total of 590 DEGs, including 243 up regulated and 347 down regulated genes, were diagnosed between scrambled shRNA expression and Lin7A knock down. The up-regulated genes were enriched in ribosome, mitochondrial translation termination, translation, and peptide biosynthetic process. The down-regulated genes were enriched in focal adhesion, VEGFR3 signaling in lymphatic endothelium, extracellular matrix organization, and extracellular matrix. The current study screened the genes in the PPI network, extracted modules, miRNA-target genes regulatory network, and TF-target genes regulatory network with higher degrees as hub genes, which included <i>NPM1, CUL4A, YIPF1, SHC1, AKT1, VLDLR, RPL14, P3H2, DTNA, FAM126B, RPL34</i>, and <i>MYL5</i>. Survival analysis indicated that the high expression of <i>RPL36A</i> and <i>MRPL35</i> were predicting longer survival of GBM, while high expression of <i>AP1S1</i> and <i>AKAP12</i> were predicting shorter survival of GBM. High expression of <i>RPL36A</i> and <i>AP1S1</i> were associated with pathogenesis of GBM, while low expression of <i>ALPL</i> was associated with pathogenesis of GBM. In conclusion, the current study diagnosed DEGs between scrambled shRNA expression and Lin7A knock down samples, which could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new diagnostic markers might be used as therapeutic targets for GBM. |
topic |
glioblastoma multiform topology analysis miRNA-target gene network TF-target gene network differential gene expression |
url |
https://www.mdpi.com/2218-273X/9/5/201 |
work_keys_str_mv |
AT alimohamedalshabi identificationofcrucialcandidategenesandpathwaysinglioblastomamultiformbybioinformaticsanalysis AT basavarajvastrad identificationofcrucialcandidategenesandpathwaysinglioblastomamultiformbybioinformaticsanalysis AT ibrahimahmedshaikh identificationofcrucialcandidategenesandpathwaysinglioblastomamultiformbybioinformaticsanalysis AT chanabasayyavastrad identificationofcrucialcandidategenesandpathwaysinglioblastomamultiformbybioinformaticsanalysis |
_version_ |
1725969303224713216 |