Journal of Personalized Medicine · 2021 · 28 citations · 35 references
MedicineMolecular BiologyOncologyGene Expression AnalysisMolecular OncologyTumor HeterogeneityCancer GenomicsCancer Stem Cell BiologyCancer Stem CellsDifferential Gene Expression AnalysisGlioblastomaTherapeutic ResistanceCancer Stem Cell IdentificationEnrichment AnalysisGene Expression SignaturesGenomic Predictors Of RecurrenceGlioblastoma PrognosisGlioblastoma Therapeutic ResistancePrognostic Factors AnalysisPrognostic Gene Signatures
The molecular heterogeneity of gene expression profiles of glioblastoma multiforme (GBM) are the most important prognostic factors for tumor recurrence and drug resistance. Thus, the aim of this study was to identify potential target genes related to temozolomide (TMZ) resistance and GBM recurrence. The genomic data of patients with GBM from The Cancer Genome Atlas (TCGA; 154 primary and 13 recurrent tumors) and a local cohort (29 primary and 4 recurrent tumors), samples from different tumor regions from a local cohort (29 tumor and 25 peritumoral regions), and Gene Expression Omnibus data (GSE84465, single-cell RNA sequencing; 3589 cells) were included in this study. Critical gene signatures were identified based an analysis of differentially expressed genes (DEGs). DEGs were further used to evaluate gene enrichment levels among primary and recurrent GBMs and different tumor regions through gene set enrichment analysis. Protein–protein interactions (PPIs) were incorporated into gene regulatory networks to identify the affected metabolic pathways. The enrichment levels of 135 genes were identified in the peritumoral regions as being risk signatures for tumor recurrence. Fourteen genes (DVL1, PRKACB, ARRB1, APC, MAPK9, CAMK2A, PRKCB, CACNA1A, ERBB4, RASGRF1, NF1, RPS6KA2, MAPK8IP2, and PPM1A) derived from the PPI network of 135 genes were upregulated and involved in the regulation of cancer stem cell (CSC) development and relevant signaling pathways (Notch, Hedgehog, Wnt, and MAPK). The single-cell data analysis results indicated that 14 key genes were mainly expressed in oligodendrocyte progenitor cells, which could produce a CSC niche in the peritumoral region. The enrichment levels of 336 genes were identified as biomarkers for evaluating TMZ resistance in the solid tumor region. Eleven genes (ARID5A, CDC42EP3, CDKN1A, FLT3, JUNB, MAP2K3, MYBPC2, RGS14, RNASEK, TBC1D30, and TXNDC11) derived from the PPI network of 336 genes were upregulated and may be associated with a high risk of TMZ resistance; these genes were identified in both the TCGA and local cohorts. Furthermore, the expression patterns of ARID5A, CDKN1A, and MAP2K3 were identical to the gene signatures of TMZ-resistant cell lines. The identified enrichment levels of the two gene sets expressed in tumor and peritumoral regions are potentially helpful for evaluating TMZ resistance in GBM. Moreover, these key genes could be used as biomarkers, potentially providing new molecular strategies for GBM treatment.
35
KEGG: Kyoto Encyclopedia of Genes and Genomes
Minoru Kanehisa · Nucleic Acids Research · 2000 · 39.2K citations · Full text
KEGG: Kyoto Encyclopedia of Genes and Genomes
Hiroyuki Ogata, Susumu Goto, Kazushige Sato et al. · Nucleic Acids Research · 1999 · 32.4K citations · Full text
WGCNA: an R package for weighted correlation network analysis
Peter Langfelder, Steve Horvath · BMC Bioinformatics · 2008 · 29.1K citations · Full text
Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype
Daehwan Kim, Joseph M. Paggi, Chanhee Park et al. · Nature Biotechnology · 2019 · 15.7K citations · Full text