Identification of key modules and hub genes in glioblastoma multiforme based on co‐expression network analysis

Abstract

Glioblastoma multiforme (GBM) is the most malignant primary tumour in the central nervous system, but the molecular mechanisms underlying its pathogenesis remain unclear. In this study, data set http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50161 was used to construct a co‐expression network for weighted gene co‐expression network analysis. Two modules (dubbed brown and turquoise) were found to have the strongest correlation with GBM. Functional enrichment analysis indicated that the brown module was involved in the cell cycle, DNA replication, and pyrimidine metabolism. The turquoise module was primarily related to circadian rhythm entrainment, glutamatergic synapses, and axonal guidance. Hub genes were screened by survival analysis using The Cancer Genome Atlas and Human Protein Atlas databases and further tested using the http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290 and Gene Expression Profiling Interactive Analysis databases. The eight hub genes (NUSAP1, SHCBP1, KNL1, SULT4A1, SLC12A5, NUF2, NAPB, and GARNL3) were verified at both the transcriptional and translational levels, and these gene expression levels were significant based on the World Health Organization classification system. These hub genes may be potential biomarkers and therapeutic targets for the accurate diagnosis and management of GBM.

Inhibiting microcephaly genes as alternative to microtubule targeting agents to treat brain tumors

“…Indeed, the analysis of 17 patient-derived cell lines, including 3 anaplastic oligodendrogliomas, 1 anaplastic astrocytoma and 13 GBMs, found KNL1 highly expressed in all of them, with levels 10-fold higher than in normal brain [ 64 ]. Moreover, KNL1 knockdown decreased the proliferation and clonogenic ability of GBM cell line [ 65 ] (Table 2 ). All together, these data indicate that KNL1 depletion could be tested in other HGBT models, to be proposed as a potential new specific target.…”

“… Antineoplastic effects on HGBT Ref. MCPH 4 KNL1 Kinetochore scaffold 1 Binds microtubules at the kinetochore by two distinct microtubule-binding regions at N-terminal [ 61 ] Chromosome misalignment, no microtubule-kinetochore attachment, and multinucleated cell formation [ 59 , 60 ] KNL1 knockdown decreases the proliferation and cloning ability of GBM cells [ 65 ] MCPH 5 ASPM Abnormal spindle-like, microcephaly-associated protein Controls the number and length of astral microtubules and microtubule disassembly at spindle poles [ 71 , 72 ] Altered spindle orientation, cytokinesis failure, apoptosis [ 67 , 70 , 71 ] ASPM loss impairs GBM and MB tumor growth and increases DNA damage [ 50 , 77 – 80 ] MCPH 13 CENPE Centromere-associated protein E Microtubule motor protein. Promotes microtubule elongation at kinetochore and controls the length of astral microtubules [ 98 – 103 ] Chromosome misalignment, no microtubule-kinetochore attachment, altered spindle orientation, mitotic arrest [ 92 – 94 ] CENPE inhibition reduces proliferation of GBM and MB cells, increases DNA damage and induces mitotic catastrophe [ 105 , 106 ] MCPH 17 CIT Citron Rho-interacting serine/threonine kinase Controls the number and length of astral microtubules and promotes microtubule stabilization at midbody [ 71 , 124 ] Altered spindle orientation, cytokinesis failure, apoptosis [ 120 , 126 ] CITK loss impairs MB tum...…”

Bioinformatics analysis of potential core genes for pilocytic astrocytoma

“…Our study discovered that the downregulations of SLC12A5 are associated with poor OS, which suggests that SLC12A5 may mediate cancer progression by affecting the immune in ltrate in malignancies. Besides, with the results of an analysis in GBM patients that SLC12A5 was one of their core genes [9] , we suppose that an indicator of tumor progression may be.…”

Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

“…Functional enrichment analysis identified set of upregulated and downregulated cross genes, which were mainly linked to immune response, inflammatory response, cell membrane, and receptor activity. Li and co-authors [ 16 ] used weighted gene co-expression network analysis to define hub genes.…”