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pmid:30971889

Construction of Potential Glioblastoma Multiforme-Related miRNA-mRNA Regulatory Network.

Weiyang Lou · Bisha Ding · Liang Xu · Weimin Fan

Frontiers in molecular neuroscience · 2019 doi:10.3389/fnmol.2019.00066

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:30971889
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2026-11-01T15:40:44Z
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2026-11-01T22:00:29Z
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title
Construction of Potential Glioblastoma Multiforme-Related miRNA-mRNA Regulatory Network.
doi
10.3389/fnmol.2019.00066
pmid
30971889
authors array · 4 items
[0]
Weiyang Lou
[1]
Bisha Ding
[2]
Liang Xu
[3]
Weimin Fan
journal
Frontiers in molecular neuroscience
year
2019
abstract
Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated. Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. Three thousand and twenty seven and 3,879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1,715 upregulated DEGs and 1,259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB, and MYO5A expression was significantly associated with patients' OS. Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. In the future, more experiments need to be performed to validate our current findings.
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GSE90603 dataset can be found in the GEO database and GBM mRNA data can be downloaded from TCGA database.
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title
miRNA Expression data from Glioblastoma Multiforme patient tumor samples, healthy brain tissue (partly from GBM patients) and NHA cell line and Human fetal astrocyte cell line
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The top 10 enriched KEGG pathways for the intersection of target genes of upregulated DE-miRNAs and downregulated DEGs.
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The top 10 enriched KEGG pathways for the intersection of target genes of downregulated DE-miRNAs and upregulated DE-mRNAs.
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Identification of Potential miRNA-mRNA Regulatory Pathways
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software
label
MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:30971889
parent_hash
sha256:14ba89892f4c0abce9b029394924e52387136cc63fbf89ef22fc648e913359e9
fork_of
null
gaps array · 6 items
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asset:data:geo:GSE90603 licence not read
[1]
asset:data:geo:GSE90603 not downloaded
[2]
execution.not_run
[3]
review.human_critique
[4]
review.independent_reader
[5]
review.machine_critique
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_id
microarray
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO dat
order_basis
paper_text_order:387
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
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normalise_counts
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differential_expression_fit
[2]
fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
LIMMA
order_basis
consumes_earlier_output
id
assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30971889", "kind": "science-record", "revision": 7, "content_hash": "sha256:b6309ee4fb3158578305a9fe21b35732b5a75bec2e59c7dbfb7df62a55212a33", "created_at": "2026-11-01T15:40:44Z", "updated_at": "2026-11-01T22:00:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of Potential Glioblastoma Multiforme-Related miRNA-mRNA Regulatory Network.", "doi": "10.3389/fnmol.2019.00066", "pmid": "30971889", "authors": ["Weiyang Lou", "Bisha Ding", "Liang Xu", "Weimin Fan"], "journal": "Frontiers in molecular neuroscience", "year": 2019, "abstract": "Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated. Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. Three thousand and twenty seven and 3,879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1,715 upregulated DEGs and 1,259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB, and MYO5A expression was significantly associated with patients' OS. Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. 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