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pmid:33446695

Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba.

Hua Ma · Zhihui He · Jing Chen · Xu Zhang · Pingping Song

Scientific reports · 2021 doi:10.1038/s41598-020-79235-9

Paper

complete

Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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paper object · 10 fields
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title
Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba.
doi
10.1038/s41598-020-79235-9
pmid
33446695
authors array · 5 items
[0]
Hua Ma
[1]
Zhihui He
[2]
Jing Chen
[3]
Xu Zhang
[4]
Pingping Song
journal
Scientific reports
year
2021
abstract
Gastric cancer (GC) is one of the most common types of malignancy. Its potential molecular mechanism has not been clarified. In this study, we aimed to explore potential biomarkers and prognosis-related hub genes associated with GC. The gene chip dataset GSE79973 was downloaded from the GEO datasets and limma package was used to identify the differentially expressed genes (DEGs). A total of 1269 up-regulated and 330 down-regulated genes were identified. The protein-protein interactions (PPI) network of DEGs was constructed by STRING V11 database, and 11 hub genes were selected through intersection of 11 topological analysis methods of CytoHubba in Cytoscape plug-in. All the 11 selected hub genes were found in the module with the highest score from PPI network of all DEGs by the molecular complex detection (MCODE) clustering algorithm. In order to explore the role of the 11 hub genes, we performed GO function and KEGG pathway analysis for them and found that the genes were enriched in a variety of functions and pathways among which cellular senescence, cell cycle, viral carcinogenesis and p53 signaling pathway were the most associated with GC. Kaplan-Meier analysis revealed that 10 out of the 11 hub genes were related to the overall survival of GC patients. Further, seven of the 11 selected hub genes were verified significantly correlated with GC by uni- or multivariable Cox model and LASSO regression analysis including C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1. C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1 may serve as potential prognostic biomarkers and therapeutic targets for GC.
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Using the Kaplan–Meier plotter database, the prognostic value of the 11 hub genes were evaluated in GC patients.
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sections[7] "Survival analysis" paragraph 2
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Using the Kaplan–Meier plotter database, the prognostic value of the 11 hub genes were evaluated in GC patients.
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sections[28] "Data availability" paragraph 2
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Expression data from gastric cancer
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Regulation of 11 hub genes.
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Survival analysis
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Table 1
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Regulation of 11 hub genes.
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Log FC
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p value
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FN1
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5.82E-−06
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4.96E−05
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0.000173126
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0.005086582
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0.011692519
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1.240762245
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4.32E−05
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0.000227121
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Cox analysis and LASSO regression analysis
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Univariate and multivariate Cox analysis.
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Regulation of 11 hub genes.
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Cox analysis and LASSO regression analysis
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Univariate and multivariate Cox analysis.
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1.100769547
[7]
1.00269362
[8]
1.20843852
[9]
0.043751763
[10] array · 10 items
[0]
FN1
[1]
1.125876038
[2]
1.008258757
[3]
1.25721383
[4]
0.035198627
[5]
CCNB1
[6]
1.478932638
[7]
1.056967554
[8]
2.069355618
[9]
0.022416923
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[0]
BUB1B
[1]
1.122389719
[2]
1.00533721
[3]
1.25307078
[4]
0.03990889
[5]
CDC20
[6]
0.689337825
[7]
0.509422258
[8]
0.932795201
[9]
0.015918054
locator
section[9]/table-wrap[1]#Tab2
gaps array · 4 items
[0]
asset:data:geo:GSE19826 not downloaded
[1]
asset:data:geo:GSE19826 licence not read
[2]
asset:data:geo:GSE79973 not downloaded
[3]
asset:data:geo:GSE79973 licence not read
analysis object · 4 fields
state
partial
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[0] object · 10 fields
id
method-1
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survival_analysis
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kaplan_meier
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Survival analysis
dsl_operations array · 1 item
[0]
survival_km
missing_operations array · 0 items
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data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
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0.7
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medium
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Kaplan-Meier
[1] object · 10 fields
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method-2
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survival_analysis
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cox_proportional_hazards
label
Survival analysis
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[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
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medium
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Cox model
[2] object · 10 fields
id
method-3
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
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[0]
count_matrix_with_condition
evidence object · 3 fields
score
0.7
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medium
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limma
[3] object · 10 fields
id
method-4
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
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[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
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PPI
[4] object · 10 fields
id
method-5
family
null
specific
null
label
Kaplan–Meier analysis using the Kaplan–Meier plotter database
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Using the Kaplan–Meier plotter database, the prognostic value of the 11 hub genes were evaluated in GC patients.
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
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complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
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Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
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[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
tier
R1
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nothing:replicable_now
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method object · 5 fields
tier
R1
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true
required_operations array · 1 item
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survival_km
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 2 items
[0]
GSE79973
[1]
GSE19826
resolved_accessions array · 2 items
[0]
GSE79973
[1]
GSE19826
statements array · 1 item
[0]
The datasets used and analyzed during the current study are available online.
basis
The paper names GSE79973, GSE19826 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
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survival_km
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[0]
source:pmid:33446695
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asset:table:pmid:33446695:3
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asset:table:pmid:33446695:4
steps array · 1 item
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run_analysis
must_build object · 5 fields
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readers array · 0 items
capabilities array · 0 items
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data:geo:GSE19826
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:26:05Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
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usage object · 3 fields
prompt_tokens
26380
completion_tokens
1669
cached_tokens
792
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[0] object · 4 fields
id
extraction
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MiniMax-M3.1-Flash
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minimax
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[1]
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absent
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not_run
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execution.not_run
provenance object · 7 fields
entities array · 3 items
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id
pmid:33446695
type
paper
label
pmid:33446695
[1] object · 3 fields
id
source:pmid:33446695
type
manuscript
label
PMID 33446695 full text
[2] object · 3 fields
id
data:geo:GSE19826
type
dataset
label
GEO GSE19826
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:33446695
type
paper
label
pmid:33446695
[1] object · 3 fields
id
source:pmid:33446695
type
manuscript
label
PMID 33446695 full text
[2] object · 3 fields
id
data:geo:GSE19826
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dataset
label
GEO GSE19826
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33446695
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extraction
used array · 1 item
[0]
source:pmid:33446695
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE19826
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE19826
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
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software
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Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
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MiniMax literature reader
source_run_id
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:33446695
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sha256:666b44d07cb95e78723bfedd071eede7bf65ad1d665ae4780c80ce8c15475ec4
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null
gaps array · 9 items
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asset:data:geo:GSE19826 licence not read
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asset:data:geo:GSE79973 licence not read
[3]
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execution.not_run
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assays array · 1 item
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role
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support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Kaplan-Meier
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assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33446695", "kind": "science-record", "revision": 5, "content_hash": "sha256:a01f02dbf8864069a266c760806dd65309a5787eb6f76f26a0ef1f4707bff029", "created_at": "2026-11-01T15:41:22Z", "updated_at": "2026-11-01T22:02:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba.", "doi": "10.1038/s41598-020-79235-9", "pmid": "33446695", "authors": ["Hua Ma", "Zhihui He", "Jing Chen", "Xu Zhang", "Pingping Song"], "journal": "Scientific reports", "year": 2021, "abstract": "Gastric cancer (GC) is one of the most common types of malignancy. Its potential molecular mechanism has not been clarified. In this study, we aimed to explore potential biomarkers and prognosis-related hub genes associated with GC. The gene chip dataset GSE79973 was downloaded from the GEO datasets and limma package was used to identify the differentially expressed genes (DEGs). A total of 1269 up-regulated and 330 down-regulated genes were identified. The protein-protein interactions (PPI) network of DEGs was constructed by STRING V11 database, and 11 hub genes were selected through intersection of 11 topological analysis methods of CytoHubba in Cytoscape plug-in. All the 11 selected hub genes were found in the module with the highest score from PPI network of all DEGs by the molecular complex detection (MCODE) clustering algorithm. In order to explore the role of the 11 hub genes, we performed GO function and KEGG pathway analysis for them and found that the genes were enriched in a variety of functions and pathways among which cellular senescence, cell cycle, viral carcinogenesis and p53 signaling pathway were the most associated with GC. Kaplan-Meier analysis revealed that 10 out of the 11 hub genes were related to the overall survival of GC patients. Further, seven of the 11 selected hub genes were verified significantly correlated with GC by uni- or multivariable Cox model and LASSO regression analysis including C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1. 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