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pmid:30816530

In silico analysis identified miRNA‑based therapeutic agents against glioblastoma multiforme.

Dan-Dan Xiong · Wen-Qing Xu · Rong-Quan He · Yi-Wu Dang · Gang Chen · Dian-Zhong Luo

Oncology reports · 2019 doi:10.3892/or.2019.7022

Paper

complete

Experiment

partial

Data

partial

Analysis

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Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:30816530
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paper object · 10 fields
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title
In silico analysis identified miRNA‑based therapeutic agents against glioblastoma multiforme.
doi
10.3892/or.2019.7022
pmid
30816530
authors array · 6 items
[0]
Dan-Dan Xiong
[1]
Wen-Qing Xu
[2]
Rong-Quan He
[3]
Yi-Wu Dang
[4]
Gang Chen
[5]
Dian-Zhong Luo
journal
Oncology reports
year
2019
abstract
MicroRNAs (miRNAs or miRs) contribute to the development of various malignant neoplasms, including glioblastoma multiforme (GBM). The present study aimed to explore the pathogenesis of GBM and to identify latent therapeutic agents for patients with GBM, based on an in silico analysis. Gene chips that provide miRNA expression profiling in GBM were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEMs) were also determined via the RobustRankAggreg algorithm. The target genes of DEMs were predicted and then intersected with GBM‑associated genes that were collected from the Gene Expression Profiling Interactive Analysis. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the overlapping genes were then performed. Simultaneously, a connectivity map (CMap) analysis was performed to screen for potential therapeutic agents for GBM. A total of 10 DEMs (hsa‑miR‑196a, hsa‑miR‑10b, hsa‑miR‑196b, hsa‑miR‑18b, hsa‑miR‑542‑3p, hsa‑miR‑129‑3p, hsa‑miR‑1224‑5p, hsa‑miR‑876‑3p and hsa‑miR‑770‑5p) were obtained from three GEO gene chips (GSE25631, GSE42657 and GSE61710). Then, 1,720 target genes of the 10 miRNAs and 4,185 differently expressed genes in GBM were collected. By intersecting the aforementioned gene clusters, the present study identified 390 overlapping genes. GO and KEGG analyses of the 390 genes demonstrated that these genes were involved in certain cancer‑associated biological functions and pathways. Eight genes [(GTPase NRas (NRAS), calcium/calmodulin‑dependent protein kinase type II subunit Gamma (CAMK2G), platelet‑derived growth factor receptor alpha (PDGFRA), calmodulin 3 (CALM3), cyclin‑dependent kinase 6 (CDK6), calcium/calmodulin‑dependent protein kinase type II subunit beta (CAMK2B), retinoblastoma‑associated protein (RB1) and protein kinase C beta type (PRKCB)] that were centralized in the glioma pathway were selected for CMap analysis. Three chemicals (W‑13, gefitinib and exemestane) were identified as putative therapeutic agents for GBM. In summary, the present study identified three miRNA‑based chemicals for use as a therapy for GBM. However, more experimental data are needed to verify the therapeutic properties of these latent drugs in GBM.
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Genome-wide analysis of microRNA expression in surgical specimens of primary glioblastoma multiform
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Screening of 10 DEMs in GBM by the RobustRankAggreg method
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Five top upregulated miRNAs and five top downregulated miRNAs from Gene Expression Omnibus.
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Screening of 10 DEMs in GBM by the RobustRankAggreg method
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Five top upregulated miRNAs and five top downregulated miRNAs from Gene Expression Omnibus.
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Lakomy et al
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Karsy M et al
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Qian et al
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hsa-miR-876-3p
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Three chemicals identified as therapeutic agents for glioblastoma multiforme from CMap analysis.
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Identification of three potential chemicals for GBM treatment using CMap analysis
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Table III.
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Three chemicals identified as therapeutic agents for glioblastoma multiforme from CMap analysis.
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application/vnd.jats.table+json
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verified
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identifier
section[16]/table-wrap[1]#tIV-or-41-04-2194
version
null
note
Results of protein-ligand docking.
structure object · 5 fields
pmcid
PMC6412522
section_index
16
section_title
Exploration of the interactions between the three chemicals and the eight genes
row_count
22
column_count
7
table object · 8 fields
label
Table IV.
caption
Results of protein-ligand docking.
rows array · 22 items
[0] array · 7 items
[0]
Gene symbol
[1]
Protein name
[2]
PDB ID
[3]
Chemical
[4]
Total score
[5]
Crash
[6]
Polar
[1] array · 7 items
[0]
CDK6
[1]
Cyclin-dependent kinase 6
[2]
1BI7
[3]
W-13
[4]
6.9158
[5]
−0.6018
[6]
1.0852
[2] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
4.5461
[5]
−1.5497
[6]
1.0374
[3] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
4.2617
[5]
−0.6835
[6]
1.2109
[4] array · 7 items
[0]
RB1
[1]
Retinoblastoma-associated protein
[2]
2QDJ
[3]
W-13
[4]
6.1141
[5]
−0.7408
[6]
2.1589
[5] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
5.1361
[5]
−3.0039
[6]
1.0429
[6] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
4.5673
[5]
−1.2303
[6]
2.2315
[7] array · 7 items
[0]
CAMK2G
[1]
Calcium/calmodulin-dependent protein kinase type II subunit gamma
[2]
2V7O
[3]
W-13
[4]
6.5899
[5]
−0.9631
[6]
2.1155
[8] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
5.5314
[5]
−0.8239
[6]
4.6009
[9] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
5.5085
[5]
−2.4882
[6]
2.8500
[10] array · 7 items
[0]
CAMK2B
[1]
Calcium/calmodulin-dependent protein kinase type II subunit beta
[2]
3BHH
[3]
W-13
[4]
6.9781
[5]
−0.8004
[6]
2.9012
[11] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
5.4665
[5]
−1.7396
[6]
3.6928
[12] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
4.7782
[5]
−1.8678
[6]
4.6573
[13] array · 7 items
[0]
NRAS
[1]
GTPase NRas
[2]
3CON
[3]
W-13
[4]
6.9580
[5]
−0.7966
[6]
3.5558
[14] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
5.1191
[5]
−1.6695
[6]
2.1113
[15] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
3.7527
[5]
−1.3243
[6]
1.6902
[16] array · 7 items
[0]
PRKCB
[1]
Protein kinase C beta type
[2]
3PFQ
[3]
W-13
[4]
5.9087
[5]
−0.7642
[6]
4.3292
[17] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
5.9886
[5]
−0.9356
[6]
2.5291
[18] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
3.5943
[5]
−0.6226
[6]
2.3138
[19] array · 7 items
[0]
PDGFRA
[1]
Platelet-derived growth factor receptor alpha
[2]
5K5X
[3]
W-13
[4]
6.7711
[5]
−1.3263
[6]
4.9966
[20] array · 7 items
[0]
[1]
[2]
[3]
Gefitinib
[4]
4.0157
[5]
−1.0638
[6]
1.1911
[21] array · 7 items
[0]
[1]
[2]
[3]
Exemestane
[4]
4.8780
[5]
−0.9005
[6]
2.6185
locator
section[16]/table-wrap[1]#tIV-or-41-04-2194
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asset:data:geo:GSE25631 not downloaded
[1]
asset:data:geo:GSE25631 licence not read
[2]
asset:data:geo:GSE42657 not downloaded
[3]
asset:data:geo:GSE42657 licence not read
[4]
asset:data:geo:GSE61710 not downloaded
[5]
asset:data:geo:GSE61710 licence not read
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partial
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id
method-1
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group_comparison
specific
student_t_test
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Group comparison
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missing_operations array · 1 item
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student_t
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parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Student's t-test
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method-2
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network_analysis
specific
ppi_network
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Network / pathway analysis
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[0]
build_graph
[1]
centrality_scores
[2]
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edge_list
evidence object · 3 fields
score
0.8
band
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quote
PPI
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method-3
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null
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null
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RobustRankAggreg
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parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
reordered
quote
“The DEMs in the individual gene chips were then integrated and ranked with RobustRankAggreg (20), which is an R package for the comprehensive integration of the gene list.”
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gaps array · 2 items
[0]
method.reader_named_unmapped
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method.student_t
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capability:computational_analysis
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Computational analysis platform
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[0]
meta_analysis
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machine_learning
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survival_analysis
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molecular_docking
[6]
network_analysis
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differential_expression
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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complete
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R1
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nothing:replicable_now
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R1
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student_t
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: student_t_test.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
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owned
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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tier
R1
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[0]
GSE25631
[1]
GSE42657
[2]
GSE61710
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[0]
GSE25631
[1]
GSE42657
[2]
GSE61710
statements array · 1 item
[0]
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.
basis
The paper names GSE25631, GSE42657, GSE61710 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:30816530
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data:geo:GSE25631
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asset:table:pmid:30816530:1
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asset:table:pmid:30816530:2
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asset:table:pmid:30816530:3
[5]
asset:table:pmid:30816530:4
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student_t
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null
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[0]
data:geo:GSE25631
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partial
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extraction_review
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MiniMax-M3.1-Flash
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minimax
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minimax
read_at
2026-10-31T18:13:58Z
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single_reader
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method
reordered
availability
verbatim
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3
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extraction
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complete
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MiniMax-M3.1-Flash
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minimax
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pmid:30816530
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paper
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pmid:30816530
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source:pmid:30816530
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manuscript
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PMID 30816530 full text
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data:geo:GSE25631
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dataset
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GEO GSE25631
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activity-reading-sci-2026-11-01
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pmid:30816530
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pmid:30816530
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source:pmid:30816530
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PMID 30816530 full text
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data:geo:GSE25631
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dataset
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GEO GSE25631
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agent:corpus-assay-engine
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source:pmid:30816530
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agent:minimax-reader
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activity-resolve-GSE25631
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accession_resolution
used array · 1 item
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data:geo:GSE25631
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agent:corpus-assay-engine
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agent:corpus-assay-engine
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agent:minimax-reader
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MiniMax literature reader
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pmid:30816530
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gaps array · 13 items
[0]
asset:data:geo:GSE25631 licence not read
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[2]
asset:data:geo:GSE42657 licence not read
[3]
asset:data:geo:GSE42657 not downloaded
[4]
asset:data:geo:GSE61710 licence not read
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asset:data:geo:GSE61710 not downloaded
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execution.not_run
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method.reader_named_unmapped
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microarray
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99e1195c7d6f
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99e1195c7d6f
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evidence array · 1 item
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from GEO. The basic information of the three microarray datasets are presented in Table I and the ma
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ein kinase C beta type; CALM3, calmodulin 3. Immunohistochemistry staining of the proteins encoded by the 8 mi
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30816530", "kind": "science-record", "revision": 7, "content_hash": "sha256:526ae01c763b530c399e33d3143b93eb40005a2e8acc5945f1f1155df54e00ee", "created_at": "2026-11-01T15:40:42Z", "updated_at": "2026-11-01T22:00:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "In silico analysis identified miRNA‑based therapeutic agents against glioblastoma multiforme.", "doi": "10.3892/or.2019.7022", "pmid": "30816530", "authors": ["Dan-Dan Xiong", "Wen-Qing Xu", "Rong-Quan He", "Yi-Wu Dang", "Gang Chen", "Dian-Zhong Luo"], "journal": "Oncology reports", "year": 2019, "abstract": "MicroRNAs (miRNAs or miRs) contribute to the development of various malignant neoplasms, including glioblastoma multiforme (GBM). The present study aimed to explore the pathogenesis of GBM and to identify latent therapeutic agents for patients with GBM, based on an in silico analysis. Gene chips that provide miRNA expression profiling in GBM were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEMs) were also determined via the RobustRankAggreg algorithm. The target genes of DEMs were predicted and then intersected with GBM‑associated genes that were collected from the Gene Expression Profiling Interactive Analysis. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the overlapping genes were then performed. Simultaneously, a connectivity map (CMap) analysis was performed to screen for potential therapeutic agents for GBM. A total of 10 DEMs (hsa‑miR‑196a, hsa‑miR‑10b, hsa‑miR‑196b, hsa‑miR‑18b, hsa‑miR‑542‑3p, hsa‑miR‑129‑3p, hsa‑miR‑1224‑5p, hsa‑miR‑876‑3p and hsa‑miR‑770‑5p) were obtained from three GEO gene chips (GSE25631, GSE42657 and GSE61710). Then, 1,720 target genes of the 10 miRNAs and 4,185 differently expressed genes in GBM were collected. By intersecting the aforementioned gene clusters, the present study identified 390 overlapping genes. GO and KEGG analyses of the 390 genes demonstrated that these genes were involved in certain cancer‑associated biological functions and pathways. Eight genes [(GTPase NRas (NRAS), calcium/calmodulin‑dependent protein kinase type II subunit Gamma (CAMK2G), platelet‑derived growth factor receptor alpha (PDGFRA), calmodulin 3 (CALM3), cyclin‑dependent kinase 6 (CDK6), calcium/calmodulin‑dependent protein kinase type II subunit beta (CAMK2B), retinoblastoma‑associated protein (RB1) and protein kinase C beta type (PRKCB)] that were centralized in the glioma pathway were selected for CMap analysis. Three chemicals (W‑13, gefitinib and exemestane) were identified as putative therapeutic agents for GBM. In summary, the present study identified three miRNA‑based chemicals for use as a therapy for GBM. 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