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pmid:33403032

Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer.

Zhipeng Hong · Qinglan Wang · Chengye Hong · Meimei Liu · Pengqin Qiu · Rongrong Lin · Xiaolan Lin · Fangfang Chen · Qiuhuang Li · Lingling Liu · Chuan Wang · Debo Chen

Journal of Cancer · 2021 doi:10.7150/jca.48245

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title
Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer.
doi
10.7150/jca.48245
pmid
33403032
authors array · 12 items
[0]
Zhipeng Hong
[1]
Qinglan Wang
[2]
Chengye Hong
[3]
Meimei Liu
[4]
Pengqin Qiu
[5]
Rongrong Lin
[6]
Xiaolan Lin
[7]
Fangfang Chen
[8]
Qiuhuang Li
[9]
Lingling Liu
[10]
Chuan Wang
[11]
Debo Chen
journal
Journal of Cancer
year
2021
abstract
Breast cancer (BC), with complex tumorigenesis and progression, remains the most common malignancy in women. We aimed to explore some novel and significant genes with unfavorable prognoses and potential pathways involved in BC initiation and progression via bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002, which included a total of 651 BC tissues and 44 normal breast tissues, were obtained from the Gene Expression Omnibus (GEO) database, and 124 differentially expressed genes (DEGs) were identified between BC tissues and normal breast tissues via R software and an online Venn diagram tool. Database for Annotation, Visualization and Integration Discovery (DAVID) software showed that 65 upregulated DEGs were mainly enriched in the regulation of the cell cycle, and Search Tool for the Retrieval of Interacting Genes (STRING) software identified the 39 closest associated upregulated DEGs in protein-protein interactions (PPIs), which validated the high expression of genes in BC tissues by the Gene Expression Profiling Interactive Analysis (GEPIA) tool. In addition, 36 out of 39 BC patients showed significantly worse outcomes by Kaplan-Meier plotter (KM plotter), and an additional Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that seven genes (cyclin E2 (CCNE2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), mitotic checkpoint serine/threonine kinase B (BUB1B), dual-specificity protein kinase (TTK), cell division cycle 20 (CDC20), and pituitary tumor transforming gene 1 (PTTG1)) were markedly enriched in the cell cycle pathway. Analysis of the clinicopathological characteristics of hub genes revealed that seven cell cycle-related genes (CCRGs) were significantly highly expressed in four BC subtypes (luminal A, luminal B, HER2-positive and triple-negative (TNBC)), and except for the CCNE2 gene, high expression levels were significantly associated with tumor pathological grade and stage and metastatic events of BC. Furthermore, genetic mutation analysis indicated that genetic alterations of CCRGs could also significantly affect BC patients' prognosis. A quantitative real-time polymerase chain reaction (qRT-PCR) assay found that the seven CCRGs were significantly differentially expressed in BC cell lines. Integration of published multilevel expression data and a bioinformatics computational approach were used to predict and construct a regulation mechanism: a transcription factor (TF)-microRNA (miRNA)-messenger RNA (mRNA) regulation network. The present work is the first to construct a regulatory network of TF-miRNA-mRNA in BC for CCRGs and provides new insights into the molecular mechanism of BC.
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We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs.
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We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs.
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Microarray datasets of GSE42568, GSE45827 and GSE54002 were all processed on the GPL570 platform ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array) and contained 104 BC tissues and 17 normal breast tissues, 130 BC tissues and 11 normal breast tissues, and 417 BC tissues and 16 breast tissues, respectively.
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[254]
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[255]
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[269]
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[273]
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[274]
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[278]
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[282]
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[283]
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[284]
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[285]
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[287]
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[288]
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[292]
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[294]
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[295]
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[297]
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[298]
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[299]
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[300]
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[301]
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[302]
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[303]
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[304]
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[306]
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[307]
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[308]
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[309]
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[313]
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[314]
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[316]
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[317]
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[318]
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[319]
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[320]
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[322]
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[323]
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[328]
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[332]
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[336]
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[338]
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[339]
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[346]
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sample_count
433
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression profiling of LCM captured breast cancer cells
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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gaps array · 6 items
[0]
asset:data:geo:GSE42568 not downloaded
[1]
asset:data:geo:GSE42568 licence not read
[2]
asset:data:geo:GSE45827 not downloaded
[3]
asset:data:geo:GSE45827 licence not read
[4]
asset:data:geo:GSE54002 not downloaded
[5]
asset:data:geo:GSE54002 licence not read
analysis object · 4 fields
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partial
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[0] object · 10 fields
id
method-1
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differential_expression
specific
edger
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Differential expression analysis
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[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
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[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
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verbatim
quote
We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs.
[1] object · 10 fields
id
method-2
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group_comparison
specific
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Group comparison
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[0]
group_summary
[1]
welch_t
[2]
bootstrap_mean_difference
[3]
group_comparison_anova
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
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0.8
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high
quote
analysis of variance
[2] object · 10 fields
id
method-3
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survival_analysis
specific
kaplan_meier
label
Survival analysis
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[0]
survival_km
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
quote
Kaplan-Meier
[3] object · 10 fields
id
method-4
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survival_analysis
specific
log_rank_test
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Survival analysis
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[0]
logrank_test
missing_operations array · 0 items
parameters object · 2 fields
hazard_ratio
he log-rank p value and hazard ratio (HR) with 95% confidenc
p_value
The log-rank p value and hazard ratio (HR) w
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[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
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high
quote
log-rank
[4] object · 10 fields
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method-5
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differential_expression
specific
limma_voom
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Differential expression analysis
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[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
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[0]
count_matrix_with_condition
evidence object · 3 fields
score
0.8
band
high
quote
limma
[5] object · 10 fields
id
method-6
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
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[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
PPI
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
capability object · 3 fields
state
complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
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[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
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: edger.
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 · 3 items
[0]
GSE42568
[1]
GSE45827
[2]
GSE54002
resolved_accessions array · 3 items
[0]
GSE42568
[1]
GSE45827
[2]
GSE54002
statements array · 1 item
[0]
Microarray datasets of GSE42568, GSE45827 and GSE54002 were all processed on the GPL570 platform ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array) and contained 104 BC tissues and 17 normal breast tissues, 130 BC tissues and 11 normal breast tissues, and 417 BC tissues and 16 breast tissues, respectively.
basis
The paper names GSE42568, GSE45827, GSE54002 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 · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:33403032
[1]
data:geo:GSE42568
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[0]
run_analysis
must_build object · 5 fields
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readers array · 0 items
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data_gaps array · 1 item
[0]
data:geo:GSE42568
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
2026-10-31T18:25:49Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
40313
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1740
cached_tokens
784
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[0] object · 4 fields
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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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[0]
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[1]
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[2]
review.human_critique
execution object · 5 fields
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absent
status
not_run
mode
null
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[0]
execution.not_run
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entities array · 3 items
[0] object · 3 fields
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pmid:33403032
type
paper
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pmid:33403032
[1] object · 3 fields
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source:pmid:33403032
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manuscript
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PMID 33403032 full text
[2] object · 3 fields
id
data:geo:GSE42568
type
dataset
label
GEO GSE42568
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[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
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[0] object · 3 fields
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pmid:33403032
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paper
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pmid:33403032
[1] object · 3 fields
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source:pmid:33403032
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manuscript
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PMID 33403032 full text
[2] object · 3 fields
id
data:geo:GSE42568
type
dataset
label
GEO GSE42568
agent
agent:corpus-assay-engine
[1] object · 4 fields
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activity-read-33403032
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extraction
used array · 1 item
[0]
source:pmid:33403032
agent
agent:minimax-reader
[2] object · 4 fields
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activity-resolve-GSE42568
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE42568
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
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agent:corpus-assay-engine
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software
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Corpus assay engine
[1] object · 3 fields
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agent:minimax-reader
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software
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MiniMax literature reader
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reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:33403032
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sha256:a13417279c883c942fd1660a653728d4b26d5b7448fd612eeec46aa1f8f09f3e
fork_of
null
gaps array · 11 items
[0]
asset:data:geo:GSE42568 licence not read
[1]
asset:data:geo:GSE42568 not downloaded
[2]
asset:data:geo:GSE45827 licence not read
[3]
asset:data:geo:GSE45827 not downloaded
[4]
asset:data:geo:GSE54002 licence not read
[5]
asset:data:geo:GSE54002 not downloaded
[6]
execution.not_run
[7]
method.reader_differs_from_extractor
[8]
review.human_critique
[9]
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[10]
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assays array · 5 items
[0] object · 11 fields
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data_generation
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microarray
definition_version
99e1195c7d6f
required_operations array · 0 items
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partial
source_hashes object · 1 field
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99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
a bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002,
[1]
ecimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) pa
order_basis
paper_text_order:409
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
rna_seq
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]
(KM plotter) system contained gene ChIP and RNA-seq data sources from the TCGA, European Genome-
order_basis
paper_text_order:3625
id
assay:2
[2] object · 11 fields
role
data_generation
definition_id
cell_culture
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99e1195c7d6f
required_operations array · 0 items
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partial
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99e1195c7d6f
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0.99
evidence array · 3 items
[0]
mycin. MCF-7 cells and MDA-MB-231 cells were cultured in DMEM (Gibco, Carlsbad, CA, United States) co
[1]
ithelial cell line MCF-10A and BC cell lines MCF-7 and MDA-MB-231 were purchased from the Cell
[2]
e and 1 unit (U)/ml penicillin/streptomycin. MCF-7 cells and MDA-MB-231 cells were cultured in
order_basis
paper_text_order:4149
id
assay:3
[3] object · 11 fields
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data_generation
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99e1195c7d6f
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partial
source_hashes object · 1 field
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99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
e protein expression of CCRGs in BC, we used IHC to compare the protein expression between no
[1]
es via the Human Protein Atlas database. The IHC map of CCRGs is shown in Figure 7 and confir
[2]
f data available in the Human Protein Atlas. IHC analysis and RNA expression analysis of gene
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We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33403032", "kind": "science-record", "revision": 9, "content_hash": "sha256:6aa4ac745dc8be6c074b8bbaffd0c3ffe47dd6987dee37f7a8ad9f6d34c0c9cf", "created_at": "2026-11-01T15:41:21Z", "updated_at": "2026-11-01T22:45:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer.", "doi": "10.7150/jca.48245", "pmid": "33403032", "authors": ["Zhipeng Hong", "Qinglan Wang", "Chengye Hong", "Meimei Liu", "Pengqin Qiu", "Rongrong Lin", "Xiaolan Lin", "Fangfang Chen", "Qiuhuang Li", "Lingling Liu", "Chuan Wang", "Debo Chen"], "journal": "Journal of Cancer", "year": 2021, "abstract": "Breast cancer (BC), with complex tumorigenesis and progression, remains the most common malignancy in women. We aimed to explore some novel and significant genes with unfavorable prognoses and potential pathways involved in BC initiation and progression via bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002, which included a total of 651 BC tissues and 44 normal breast tissues, were obtained from the Gene Expression Omnibus (GEO) database, and 124 differentially expressed genes (DEGs) were identified between BC tissues and normal breast tissues via R software and an online Venn diagram tool. Database for Annotation, Visualization and Integration Discovery (DAVID) software showed that 65 upregulated DEGs were mainly enriched in the regulation of the cell cycle, and Search Tool for the Retrieval of Interacting Genes (STRING) software identified the 39 closest associated upregulated DEGs in protein-protein interactions (PPIs), which validated the high expression of genes in BC tissues by the Gene Expression Profiling Interactive Analysis (GEPIA) tool. In addition, 36 out of 39 BC patients showed significantly worse outcomes by Kaplan-Meier plotter (KM plotter), and an additional Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that seven genes (cyclin E2 (CCNE2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), mitotic checkpoint serine/threonine kinase B (BUB1B), dual-specificity protein kinase (TTK), cell division cycle 20 (CDC20), and pituitary tumor transforming gene 1 (PTTG1)) were markedly enriched in the cell cycle pathway. Analysis of the clinicopathological characteristics of hub genes revealed that seven cell cycle-related genes (CCRGs) were significantly highly expressed in four BC subtypes (luminal A, luminal B, HER2-positive and triple-negative (TNBC)), and except for the CCNE2 gene, high expression levels were significantly associated with tumor pathological grade and stage and metastatic events of BC. Furthermore, genetic mutation analysis indicated that genetic alterations of CCRGs could also significantly affect BC patients' prognosis. A quantitative real-time polymerase chain reaction (qRT-PCR) assay found that the seven CCRGs were significantly differentially expressed in BC cell lines. Integration of published multilevel expression data and a bioinformatics computational approach were used to predict and construct a regulation mechanism: a transcription factor (TF)-microRNA (miRNA)-messenger RNA (mRNA) regulation network. The present work is the first to construct a regulatory network of TF-miRNA-mRNA in BC for CCRGs and provides new insights into the molecular mechanism of BC.", "claims": [{"id": "claim-method", "statement": "We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33403032", "locator": "sections[4] \"Data processing and differential analysis\" paragraph 2", "quote": "We detected and removed batch effects in each dataset (Supplementary Figure S1) and then classified the BC specimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) packages edgeR and limma to identify DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray datasets of GSE42568, GSE45827 and GSE54002 were all processed on the GPL570 platform ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array) and contained 104 BC tissues and 17 normal breast tissues, 130 BC tissues and 11 normal breast tissues, and 417 BC tissues and 16 breast tissues, respectively.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33403032", "locator": "sections[3] \"Collection of microarray data information from GEO datasets\" paragraph 2", "quote": "Microarray datasets of GSE42568, GSE45827 and GSE54002 were all processed on the GPL570 platform ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array) and contained 104 BC tissues and 17 normal breast tissues, 130 BC tissues and 11 normal breast tissues, and 417 BC tissues and 16 breast tissues, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33403032"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002,", "ecimens and normal breast specimens in three microarray datasets using R software (version 3.4.4) pa"], "order_basis": "paper_text_order:409", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["(KM plotter) system contained gene ChIP and RNA-seq data sources from the TCGA, European Genome-"], "order_basis": "paper_text_order:3625", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["mycin. MCF-7 cells and MDA-MB-231 cells were cultured in DMEM (Gibco, Carlsbad, CA, United States) co", "ithelial cell line MCF-10A and BC cell lines MCF-7 and MDA-MB-231 were purchased from the Cell", "e and 1 unit (U)/ml penicillin/streptomycin. MCF-7 cells and MDA-MB-231 cells were cultured in"], "order_basis": "paper_text_order:4149", "id": "assay:3"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["e protein expression of CCRGs in BC, we used IHC to compare the protein expression between no", "es via the Human Protein Atlas database. The IHC map of CCRGs is shown in Figure 7 and confir", "f data available in the Human Protein Atlas. 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