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pmid:32035007

Comprehensive Analysis of Differential Gene Expression to Identify Common Gene Signatures in Multiple Cancers.

Jin-Min Xue · Yi Liu · Ling-Hong Wan · Yu-Xi Zhu

Medical science monitor : international medical journal of experimental and clinical research · 2020 doi:10.12659/MSM.919953

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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pmid:32035007
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2026-11-01T15:40:56Z
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title
Comprehensive Analysis of Differential Gene Expression to Identify Common Gene Signatures in Multiple Cancers.
doi
10.12659/MSM.919953
pmid
32035007
authors array · 4 items
[0]
Jin-Min Xue
[1]
Yi Liu
[2]
Ling-Hong Wan
[3]
Yu-Xi Zhu
journal
Medical science monitor : international medical journal of experimental and clinical research
year
2020
abstract
BACKGROUND With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers - lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer - and the potential therapeutic targets in public databases. MATERIAL AND METHODS Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored. RESULTS We found 12 cross DEGs in the 5 databases (screening conditions: "adj p<0.05" and "logFC>2 or logFC<-2"). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape: TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration. CONCLUSIONS Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.
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We performed a survival analysis of hub-genes by using GEPIA.
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sections[9] "Hub-gene survival analysis" paragraph 2
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We performed a survival analysis of hub-genes by using GEPIA.
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GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.
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GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.
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Gene expression profiling of chronic hepatitis B induced HCC and adjacent-normal tissues
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Breast Cancer Gene Expression Analysis
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[29]
GSM1551340
[30]
GSM1551341
[31]
GSM1551342
[32]
GSM1551343
[33]
GSM1551344
[34]
GSM1551345
[35]
GSM1551346
[36]
GSM1551347
[37]
GSM1551348
[38]
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[39]
GSM1551350
[40]
GSM1551351
[41]
GSM1551352
[42]
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[43]
GSM1551354
[44]
GSM1551355
[45]
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[46]
GSM1551357
[47]
GSM1551358
[48]
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[49]
GSM1551360
[50]
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[51]
GSM1551362
[52]
GSM1551363
[53]
GSM1551364
[54]
GSM1551365
[55]
GSM1551366
[56]
GSM1551367
[57]
GSM1551368
[58]
GSM1551369
[59]
GSM1551370
[60]
GSM1551371
[61]
GSM1551372
[62]
GSM1551373
[63]
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[64]
GSM1551375
[65]
GSM1551376
[66]
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[67]
GSM1551378
[68]
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[69]
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[70]
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[71]
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[72]
GSM1551383
[73]
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[74]
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[75]
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[76]
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[77]
GSM1551388
[78]
GSM1551389
[79]
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[80]
GSM1551391
[81]
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[82]
GSM1551393
[83]
GSM1551394
[84]
GSM1551395
[85]
GSM1551396
[86]
GSM1551397
[87]
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[88]
GSM1551399
[89]
GSM1551400
[90]
GSM1551401
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GSM1551402
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[93]
GSM1551404
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[95]
GSM1551406
[96]
GSM1551407
[97]
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[98]
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[99]
GSM1551410
[100]
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[101]
GSM1551412
[102]
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[103]
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GSM1551415
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[106]
GSM1551417
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[108]
GSM1551419
[109]
GSM1551420
[110]
GSM1551421
[111]
GSM1551422
[112]
GSM1551423
[113]
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[114]
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[115]
GSM1551426
[116]
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[117]
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[118]
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[119]
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[120]
GSM1551431
[121]
GSM1551432
[122]
GSM1551433
[123]
GSM1551434
[124]
GSM1551435
[125]
GSM1551436
[126]
GSM1551437
[127]
GSM1551438
sample_count
128
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression analysis of cervical cancer progression
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 15 fields
id
data:geo:GSE66272
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66272
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE66272
version
null
note
GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.
access_statement_kind
repository_route_statement
sample_accessions array · 54 items
[0]
GSM1618387
[1]
GSM1618388
[2]
GSM1618389
[3]
GSM1618390
[4]
GSM1618391
[5]
GSM1618392
[6]
GSM1618393
[7]
GSM1618394
[8]
GSM1618395
[9]
GSM1618396
[10]
GSM1618397
[11]
GSM1618398
[12]
GSM1618399
[13]
GSM1618400
[14]
GSM1618401
[15]
GSM1618402
[16]
GSM1618403
[17]
GSM1618404
[18]
GSM1618405
[19]
GSM1618406
[20]
GSM1618407
[21]
GSM1618408
[22]
GSM1618409
[23]
GSM1618410
[24]
GSM1618411
[25]
GSM1618412
[26]
GSM1618413
[27]
GSM1618414
[28]
GSM1618415
[29]
GSM1618416
[30]
GSM1618417
[31]
GSM1618418
[32]
GSM1618419
[33]
GSM1618420
[34]
GSM1618421
[35]
GSM1618422
[36]
GSM1618423
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GSM1618424
[38]
GSM1618425
[39]
GSM1618426
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GSM1618428
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GSM1618429
[43]
GSM1618430
[44]
GSM1618431
[45]
GSM1618432
[46]
GSM1618433
[47]
GSM1618434
[48]
GSM1618435
[49]
GSM1618436
[50]
GSM1618437
[51]
GSM1618438
[52]
GSM1618439
[53]
GSM1618440
sample_count
54
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Genome-wide analysis of gene expression patterns in human kidney cancer
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 10 items
[0]
asset:data:geo:GSE121248 not downloaded
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asset:data:geo:GSE121248 licence not read
[2]
asset:data:geo:GSE19188 not downloaded
[3]
asset:data:geo:GSE19188 licence not read
[4]
asset:data:geo:GSE42568 not downloaded
[5]
asset:data:geo:GSE42568 licence not read
[6]
asset:data:geo:GSE63514 not downloaded
[7]
asset:data:geo:GSE63514 licence not read
[8]
asset:data:geo:GSE66272 not downloaded
[9]
asset:data:geo:GSE66272 licence not read
analysis object · 4 fields
state
partial
methods array · 1 item
[0] object · 10 fields
id
method-1
family
null
specific
null
label
survival analysis
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
We performed a survival analysis of hub-genes by using GEPIA.
targets array · 0 items
gaps array · 1 item
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method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
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machine_learning
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survival_analysis
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statistical_regression
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pca
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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
blocked
tier
R4
blocking_axis
method
blocked_on
method:not_determinable
axes object · 3 fields
method object · 5 fields
tier
R4
expressible
false
required_operations array · 0 items
missing_operations array · 0 items
basis
The reader quoted the method the paper names (survival analysis), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible.
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 · 5 items
[0]
GSE42568
[1]
GSE19188
[2]
GSE121248
[3]
GSE63514
[4]
GSE66272
resolved_accessions array · 5 items
[0]
GSE42568
[1]
GSE19188
[2]
GSE121248
[3]
GSE63514
[4]
GSE66272
statements array · 1 item
[0]
GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.
basis
The paper names GSE42568, GSE19188, GSE121248, GSE63514, GSE66272 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 2 items
[0]
source:pmid:32035007
[1]
data:geo:GSE121248
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE121248
gaps array · 1 item
[0]
method:not_determinable
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
2026-10-31T18:18:21Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
16357
completion_tokens
1971
cached_tokens
784
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
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review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:32035007
type
paper
label
pmid:32035007
[1] object · 3 fields
id
source:pmid:32035007
type
manuscript
label
PMID 32035007 full text
[2] object · 3 fields
id
data:geo:GSE121248
type
dataset
label
GEO GSE121248
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:32035007
type
paper
label
pmid:32035007
[1] object · 3 fields
id
source:pmid:32035007
type
manuscript
label
PMID 32035007 full text
[2] object · 3 fields
id
data:geo:GSE121248
type
dataset
label
GEO GSE121248
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-32035007
type
extraction
used array · 1 item
[0]
source:pmid:32035007
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE121248
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE121248
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
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
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:32035007
parent_hash
sha256:3f602446dea6409ee5278dc5532f9f55426589d99a36777273985d8c0be362be
fork_of
null
gaps array · 15 items
[0]
asset:data:geo:GSE121248 licence not read
[1]
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[2]
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[3]
asset:data:geo:GSE19188 not downloaded
[4]
asset:data:geo:GSE42568 licence not read
[5]
asset:data:geo:GSE42568 not downloaded
[6]
asset:data:geo:GSE63514 licence not read
[7]
asset:data:geo:GSE63514 not downloaded
[8]
asset:data:geo:GSE66272 licence not read
[9]
asset:data:geo:GSE66272 not downloaded
[10]
execution.not_run
[11]
method.reader_named_unmapped
[12]
review.human_critique
[13]
review.independent_reader
[14]
review.machine_critique
Complete file
{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32035007", "kind": "science-record", "revision": 4, "content_hash": "sha256:fde297857c3a89813d617c21a0771b9db80ab1edcb4a0656859ecb8c461cf113", "created_at": "2026-11-01T15:40:56Z", "updated_at": "2026-11-01T21:22:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive Analysis of Differential Gene Expression to Identify Common Gene Signatures in Multiple Cancers.", "doi": "10.12659/MSM.919953", "pmid": "32035007", "authors": ["Jin-Min Xue", "Yi Liu", "Ling-Hong Wan", "Yu-Xi Zhu"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2020, "abstract": "BACKGROUND With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers - lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer - and the potential therapeutic targets in public databases. MATERIAL AND METHODS Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored. RESULTS We found 12 cross DEGs in the 5 databases (screening conditions: \"adj p<0.05\" and \"logFC>2 or logFC<-2\"). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape: TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration. CONCLUSIONS Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.", "claims": [{"id": "claim-method", "statement": "We performed a survival analysis of hub-genes by using GEPIA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32035007", "locator": "sections[9] \"Hub-gene survival analysis\" paragraph 2", "quote": "We performed a survival analysis of hub-genes by using GEPIA."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32035007", "locator": "sections[12] \"Datasets for research\" paragraph 2", "quote": "GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included."}], "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:32035007"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE121248"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE121248"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32035007", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12659/MSM.919953", "sha256": "sha256:e181e80e71287fce4e267274f8e35c2c3456818caeaffe1241610647bde7429a", "bytes": 21841, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.12659/MSM.919953", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7027371", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE121248", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121248", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE121248", "version": null, "note": "GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "GSE42568 analyzed the difference in gene expression between breast cancer and normal tissues, and 121 samples were included.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM3428716", "GSM3428717", "GSM3428718", "GSM3428719", "GSM3428720", "GSM3428721", "GSM3428722", "GSM3428723", "GSM3428724", "GSM3428725", "GSM3428726", "GSM3428727", "GSM3428728", "GSM3428729", "GSM3428730", "GSM3428731", "GSM3428732", "GSM3428733", "GSM3428734", "GSM3428735", "GSM3428736", "GSM3428737", "GSM3428738", "GSM3428739", "GSM3428740", "GSM3428741", "GSM3428742", "GSM3428743", "GSM3428744", "GSM3428745", "GSM3428746", "GSM3428747", "GSM3428748", "GSM3428749", "GSM3428750", "GSM3428751", "GSM3428752", "GSM3428753", "GSM3428754", "GSM3428755", "GSM3428756", "GSM3428757", "GSM3428758", "GSM3428759", "GSM3428760", "GSM3428761", "GSM3428762", "GSM3428763", 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