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pmid:33604283

Identification of Key Gene Signatures Associated With Bone Metastasis in Castration-Resistant Prostate Cancer Using Co-Expression Analysis.

Zhongxiang Yu · Hanlin Zou · Huihao Wang · Qi Li · Dong Yu

Frontiers in oncology · 2020 doi:10.3389/fonc.2020.571524

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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pmid:33604283
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title
Identification of Key Gene Signatures Associated With Bone Metastasis in Castration-Resistant Prostate Cancer Using Co-Expression Analysis.
doi
10.3389/fonc.2020.571524
pmid
33604283
authors array · 5 items
[0]
Zhongxiang Yu
[1]
Hanlin Zou
[2]
Huihao Wang
[3]
Qi Li
[4]
Dong Yu
journal
Frontiers in oncology
year
2020
abstract
About 80-90% of castration-resistant prostate cancer (CRPC) patients would develop bone metastasis. However, the molecular mechanisms of bone metastasis are still not clear. This study aimed to detect the differences between the tumor and normal samples in bone after metastatic colonization. Four transcriptional datasets (GSE32269, GSE101607, GSE29650, and GSE74685) were obtained from the GEO database. 1983 differentially expressed genes (DEGs) were first identified between tumor and normal marrow samples in GSE32269. Most of the top 10 up-regulated DEGs are related with prostate cancer, and the top 10 down-regulated DEGs are mainly related with bone development. Seven co-expression modules were then detected based on the 1469 DEGs shared by the four datasets. Three of them were found highly preserved among the four datasets. Enrichment analysis showed that the three modules were respectively enriched in Cell adhesion molecules (CAMs), Leukocyte transendothelial migration and cell cycle, which might play significantly important roles in the tumor development in bone marrow. Ten, 17, and 99 hub genes for each module were then identified. And four genes (C3AR1, IL10RA, LY86, and MS4A6A) were detect to be tightly related to progression of bone metastatic CRPC. ROC curve was plotted and AUC was calculated to distinguish tumor and normal bone marrow samples as well as bone and non-bone metastatic CRPCs. The present study identified key genes and modules involved in bone metastatic CRPCs, which may provide new insights and biomarkers for understanding of the molecular mechanisms of bone metastatic CRPC.
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The eBayes analysis was used to detect the differentially expressed genes (DEGs) between metastatic bone marrow samples and normal marrow samples in GSE32269 using limma package (14).
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sections[4] "Identification of Differentially Expressed Genes" paragraph 2
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The eBayes analysis was used to detect the differentially expressed genes (DEGs) between metastatic bone marrow samples and normal marrow samples in GSE32269 using limma package (14).
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score
0.8
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high
quote
limma
[1] object · 10 fields
id
method-2
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network_analysis
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label
Network / pathway analysis
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pathway_enrich
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evidence object · 3 fields
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0.8
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GO enrichment
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id
method-3
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diagnostic_evaluation
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roc
label
Diagnostic test evaluation
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confusion_counts
[1]
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[2]
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[3]
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[4]
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[5]
published_precision_envelope
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data_shapes array · 1 item
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reference_standard_and_test
evidence object · 3 fields
score
0.7
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quote
ROC curve
[3] object · 10 fields
id
method-4
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null
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null
label
eBayes analysis
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missing_operations array · 0 items
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evidence object · 3 fields
score
1
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quote
The eBayes analysis was used to detect the differentially expressed genes (DEGs) between metastatic bone marrow samples and normal marrow samples in GSE32269 using limma package (14).
targets array · 0 items
gaps array · 1 item
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method.reader_named_unmapped
capability object · 3 fields
state
complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
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assay_families array · 9 items
[0]
meta_analysis
[1]
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[3]
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[5]
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
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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: limma_voom.
capability object · 4 fields
tier
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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.
data object · 6 fields
tier
R1
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accessions array · 4 items
[0]
GSE32269
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GSE101607
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GSE29650
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GSE74685
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[0]
GSE32269
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GSE101607
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GSE29650
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GSE74685
statements array · 1 item
[0]
Publicly available datasets were analyzed in this study, these can be found in here: the NCBI Gene Expression Omnibus (GSE32269, GSE101607, GSE29650 and GSE74685).
basis
The paper names GSE32269, GSE101607, GSE29650, GSE74685 in NCBI 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
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fdr_bh
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run_analysis
must_build object · 5 fields
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data_gaps array · 1 item
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data:geo:GSE101607
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
2026-10-31T18:27:03Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
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3
usage object · 3 fields
prompt_tokens
17980
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1428
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6152
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extraction
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complete
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pmid:33604283
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paper
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pmid:33604283
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source:pmid:33604283
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manuscript
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PMID 33604283 full text
[2] object · 3 fields
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data:geo:GSE101607
type
dataset
label
GEO GSE101607
activities array · 3 items
[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:33604283
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paper
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pmid:33604283
[1] object · 3 fields
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source:pmid:33604283
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manuscript
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PMID 33604283 full text
[2] object · 3 fields
id
data:geo:GSE101607
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dataset
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GEO GSE101607
agent
agent:corpus-assay-engine
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activity-read-33604283
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activity-resolve-GSE101607
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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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software
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MiniMax literature reader
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
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lineage object · 4 fields
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asset:data:geo:GSE32269 licence not read
[5]
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[6]
asset:data:geo:GSE74685 licence not read
[7]
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33604283", "kind": "science-record", "revision": 7, "content_hash": "sha256:bce6376679b52b10ad151cf71039ab87a532e1718834209e084f06d6135f1ad2", "created_at": "2026-11-01T15:41:25Z", "updated_at": "2026-11-01T22:03:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Gene Signatures Associated With Bone Metastasis in Castration-Resistant Prostate Cancer Using Co-Expression Analysis.", "doi": "10.3389/fonc.2020.571524", "pmid": "33604283", "authors": ["Zhongxiang Yu", "Hanlin Zou", "Huihao Wang", "Qi Li", "Dong Yu"], "journal": "Frontiers in oncology", "year": 2020, "abstract": "About 80-90% of castration-resistant prostate cancer (CRPC) patients would develop bone metastasis. However, the molecular mechanisms of bone metastasis are still not clear. This study aimed to detect the differences between the tumor and normal samples in bone after metastatic colonization. Four transcriptional datasets (GSE32269, GSE101607, GSE29650, and GSE74685) were obtained from the GEO database. 1983 differentially expressed genes (DEGs) were first identified between tumor and normal marrow samples in GSE32269. Most of the top 10 up-regulated DEGs are related with prostate cancer, and the top 10 down-regulated DEGs are mainly related with bone development. Seven co-expression modules were then detected based on the 1469 DEGs shared by the four datasets. Three of them were found highly preserved among the four datasets. Enrichment analysis showed that the three modules were respectively enriched in Cell adhesion molecules (CAMs), Leukocyte transendothelial migration and cell cycle, which might play significantly important roles in the tumor development in bone marrow. Ten, 17, and 99 hub genes for each module were then identified. And four genes (C3AR1, IL10RA, LY86, and MS4A6A) were detect to be tightly related to progression of bone metastatic CRPC. ROC curve was plotted and AUC was calculated to distinguish tumor and normal bone marrow samples as well as bone and non-bone metastatic CRPCs. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE32269", "GSE101607", "GSE29650", "GSE74685"], "resolved_accessions": ["GSE32269", "GSE101607", "GSE29650", "GSE74685"], "statements": ["Publicly available datasets were analyzed in this study, these can be found in here: the NCBI Gene Expression Omnibus (GSE32269, GSE101607, GSE29650 and GSE74685)."], "basis": "The paper names GSE32269, GSE101607, GSE29650, GSE74685 in NCBI Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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