Corpus Engine Towards a reproducible .science file.
← All .science files

pmid:33116619

Gene Expression Along with Genomic Copy Number Variation and Mutational Analysis Were Used to Develop a 9-Gene Signature for Estimating Prognosis of COAD.

Yiping Lu · Si Wu · Changwan Cui · Miao Yu · Shuang Wang · Yuanyi Yue · Miao Liu · Zhengrong Sun

OncoTargets and therapy · 2020 doi:10.2147/OTT.S255590

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:33116619
kind
science-record
content_hash
sha256:8f217a809a3f35b17e0e5e97d58786ca157ed22b7a1c8b79cbbc732ba3bb12e7
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:41:14Z
updated_at
2026-11-01T22:02:24Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Gene Expression Along with Genomic Copy Number Variation and Mutational Analysis Were Used to Develop a 9-Gene Signature for Estimating Prognosis of COAD.
doi
10.2147/OTT.S255590
pmid
33116619
authors array · 8 items
[0]
Yiping Lu
[1]
Si Wu
[2]
Changwan Cui
[3]
Miao Yu
[4]
Shuang Wang
[5]
Yuanyi Yue
[6]
Miao Liu
[7]
Zhengrong Sun
journal
OncoTargets and therapy
year
2020
abstract
PURPOSE: This study aims to systematically analyze multi-omics data to explore new prognosis biomarkers in colon adenocarcinoma (COAD). MATERIALS AND METHODS: Multi-omics data of COAD and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox analysis was used to select genes which significantly related to the overall survival. GISTIC 2.0 software was used to identify significant amplification or deletion. Mutsig 2.0 software was used to identify significant mutation genes. The 9-gene signature was screened by random forest algorithm and Cox regression analysis. GSE17538 dataset was used as an external dataset to verify the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes in clinical specimens. RESULTS: A total of 71 candidate genes are obtained by integrating genomic variation, mutation and prognostic data. Then, 9-gene signature was established, which includes HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, PYGO2, CTNNA1, PTPRK, and NAT1. The 9-gene signature is an independent prognostic risk factor for COAD patients. In addition, the signature shows good predicting performance and clinical practicality in training set, testing set and external verification set. The results of qPCR based on clinical samples showed that the expression of HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, and PYGO2 was increased in colon cancer tissues and the expression of CTNNA1, PTPRK, NAT1 was decreased in colon cancer tissues. CONCLUSION: In this study, 9-gene signature is constructed as a new prognostic marker to predict the survival of COAD patients.
claims array · 1 item
[0] object · 6 fields
id
claim-data-access
statement
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:33116619
locator
sections[3] "Data Acquisition and Processing" paragraph 2
quote
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
state
complete
gaps array · 0 items
experiment object · 8 fields
state
complete
objective
null
steps array · 3 items
[0] object · 13 fields
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.
parameters object · 0 fields
inputs array · 1 item
[0]
source:pmid:33116619
outputs array · 1 item
[0]
the published estimate and its evidence
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
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.
parameters object · 0 fields
inputs array · 1 item
[0]
data:geo:GSE17538
outputs array · 1 item
[0]
the source data with its repository provenance
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
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.
parameters object · 0 fields
inputs array · 1 item
[0]
data:geo:GSE17538
outputs array · 1 item
[0]
the replicated result and its comparison
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
state
partial
assets array · 10 items
[0] object · 15 fields
id
source:pmid:33116619
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.2147/OTT.S255590
sha256
sha256:73f57e38fdc6eb2cffd2f22cf2b6196810383dffc6a5e49436bb26f007010c71
bytes
36368
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.2147/OTT.S255590
version
null
note
Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.
structure object · 4 fields
pmcid
PMC7569059
source
europe_pmc_fulltext
coverage
whole_body
text_hash_scope
rendered_section_body
[1] object · 15 fields
id
data:geo:GSE17538
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=GSE17538
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE17538
version
null
note
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
access_statement_kind
repository_route_statement
sample_accessions array · 244 items
[0]
GSM437093
[1]
GSM437094
[2]
GSM437095
[3]
GSM437096
[4]
GSM437097
[5]
GSM437098
[6]
GSM437099
[7]
GSM437100
[8]
GSM437101
[9]
GSM437102
[10]
GSM437103
[11]
GSM437104
[12]
GSM437105
[13]
GSM437106
[14]
GSM437107
[15]
GSM437108
[16]
GSM437109
[17]
GSM437110
[18]
GSM437111
[19]
GSM437112
[20]
GSM437113
[21]
GSM437114
[22]
GSM437115
[23]
GSM437116
[24]
GSM437117
[25]
GSM437118
[26]
GSM437119
[27]
GSM437120
[28]
GSM437121
[29]
GSM437122
[30]
GSM437123
[31]
GSM437124
[32]
GSM437125
[33]
GSM437126
[34]
GSM437127
[35]
GSM437128
[36]
GSM437129
[37]
GSM437130
[38]
GSM437131
[39]
GSM437132
[40]
GSM437133
[41]
GSM437134
[42]
GSM437135
[43]
GSM437136
[44]
GSM437137
[45]
GSM437138
[46]
GSM437139
[47]
GSM437140
[48]
GSM437141
[49]
GSM437142
[50]
GSM437143
[51]
GSM437144
[52]
GSM437145
[53]
GSM437146
[54]
GSM437147
[55]
GSM437148
[56]
GSM437149
[57]
GSM437150
[58]
GSM437151
[59]
GSM437152
[60]
GSM437153
[61]
GSM437154
[62]
GSM437155
[63]
GSM437156
[64]
GSM437157
[65]
GSM437158
[66]
GSM437159
[67]
GSM437160
[68]
GSM437161
[69]
GSM437162
[70]
GSM437163
[71]
GSM437164
[72]
GSM437165
[73]
GSM437166
[74]
GSM437167
[75]
GSM437168
[76]
GSM437169
[77]
GSM437170
[78]
GSM437171
[79]
GSM437172
[80]
GSM437173
[81]
GSM437174
[82]
GSM437175
[83]
GSM437176
[84]
GSM437177
[85]
GSM437178
[86]
GSM437179
[87]
GSM437180
[88]
GSM437181
[89]
GSM437182
[90]
GSM437183
[91]
GSM437184
[92]
GSM437185
[93]
GSM437186
[94]
GSM437187
[95]
GSM437188
[96]
GSM437189
[97]
GSM437190
[98]
GSM437191
[99]
GSM437192
[100]
GSM437193
[101]
GSM437194
[102]
GSM437195
[103]
GSM437196
[104]
GSM437197
[105]
GSM437198
[106]
GSM437199
[107]
GSM437200
[108]
GSM437201
[109]
GSM437202
[110]
GSM437203
[111]
GSM437204
[112]
GSM437205
[113]
GSM437206
[114]
GSM437207
[115]
GSM437208
[116]
GSM437209
[117]
GSM437210
[118]
GSM437211
[119]
GSM437212
[120]
GSM437213
[121]
GSM437214
[122]
GSM437215
[123]
GSM437216
[124]
GSM437217
[125]
GSM437218
[126]
GSM437219
[127]
GSM437220
[128]
GSM437221
[129]
GSM437222
[130]
GSM437223
[131]
GSM437224
[132]
GSM437225
[133]
GSM437226
[134]
GSM437227
[135]
GSM437228
[136]
GSM437229
[137]
GSM437230
[138]
GSM437231
[139]
GSM437232
[140]
GSM437233
[141]
GSM437234
[142]
GSM437235
[143]
GSM437236
[144]
GSM437237
[145]
GSM437238
[146]
GSM437239
[147]
GSM437240
[148]
GSM437241
[149]
GSM437242
[150]
GSM437243
[151]
GSM437244
[152]
GSM437245
[153]
GSM437246
[154]
GSM437247
[155]
GSM437248
[156]
GSM437249
[157]
GSM437250
[158]
GSM437251
[159]
GSM437252
[160]
GSM437253
[161]
GSM437254
[162]
GSM437255
[163]
GSM437256
[164]
GSM437257
[165]
GSM437258
[166]
GSM437259
[167]
GSM437260
[168]
GSM437261
[169]
GSM437262
[170]
GSM437263
[171]
GSM437264
[172]
GSM437265
[173]
GSM437266
[174]
GSM437267
[175]
GSM437268
[176]
GSM437269
[177]
GSM437270
[178]
GSM437271
[179]
GSM437272
[180]
GSM437273
[181]
GSM437274
[182]
GSM437275
[183]
GSM437276
[184]
GSM437277
[185]
GSM437278
[186]
GSM437279
[187]
GSM437280
[188]
GSM437281
[189]
GSM437282
[190]
GSM437283
[191]
GSM437284
[192]
GSM437285
[193]
GSM437286
[194]
GSM437287
[195]
GSM437288
[196]
GSM437289
[197]
GSM437290
[198]
GSM437291
[199]
GSM437292
[200]
GSM437293
[201]
GSM437294
[202]
GSM437295
[203]
GSM437296
[204]
GSM437297
[205]
GSM437298
[206]
GSM437299
[207]
GSM437300
[208]
GSM437301
[209]
GSM437302
[210]
GSM437303
[211]
GSM437304
[212]
GSM437305
[213]
GSM437306
[214]
GSM437307
[215]
GSM437308
[216]
GSM437309
[217]
GSM437310
[218]
GSM437311
[219]
GSM437312
[220]
GSM437313
[221]
GSM437314
[222]
GSM437315
[223]
GSM437316
[224]
GSM437317
[225]
GSM437318
[226]
GSM437319
[227]
GSM437320
[228]
GSM437321
[229]
GSM437322
[230]
GSM437323
[231]
GSM437324
[232]
GSM472192
[233]
GSM472193
[234]
GSM472194
[235]
GSM472195
[236]
GSM472196
[237]
GSM472197
[238]
GSM472198
[239]
GSM472199
[240]
GSM472200
[241]
GSM472201
[242]
GSM472202
[243]
GSM472203
sample_count
244
group_sizes
null
group_sizes_basis
null
platform
570;1261
taxon
Mus musculus; Homo sapiens
title
Experimentally Derived Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:GSE19234
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=GSE19234
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE19234
version
null
note
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
access_statement_kind
repository_route_statement
sample_accessions array · 44 items
[0]
GSM476606
[1]
GSM476607
[2]
GSM476608
[3]
GSM476609
[4]
GSM476610
[5]
GSM476611
[6]
GSM476612
[7]
GSM476613
[8]
GSM476614
[9]
GSM476615
[10]
GSM476616
[11]
GSM476617
[12]
GSM476618
[13]
GSM476619
[14]
GSM476620
[15]
GSM476621
[16]
GSM476622
[17]
GSM476623
[18]
GSM476624
[19]
GSM476625
[20]
GSM476626
[21]
GSM476627
[22]
GSM476628
[23]
GSM476629
[24]
GSM476630
[25]
GSM476631
[26]
GSM476632
[27]
GSM476633
[28]
GSM476634
[29]
GSM476635
[30]
GSM476636
[31]
GSM476637
[32]
GSM476638
[33]
GSM476639
[34]
GSM476640
[35]
GSM476641
[36]
GSM476642
[37]
GSM476643
[38]
GSM476644
[39]
GSM476645
[40]
GSM476646
[41]
GSM476647
[42]
GSM476648
[43]
GSM476649
sample_count
44
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Immune profile and mitotic index of metastatic melanoma lesions enhance clinical staging in predicting patient survival.
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE24551
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=GSE24551
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE24551
version
null
note
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
access_statement_kind
repository_route_statement
sample_accessions array · 333 items
[0]
GSM712082
[1]
GSM712083
[2]
GSM712084
[3]
GSM712085
[4]
GSM712086
[5]
GSM712087
[6]
GSM712088
[7]
GSM712089
[8]
GSM712090
[9]
GSM712091
[10]
GSM712092
[11]
GSM712093
[12]
GSM712094
[13]
GSM712095
[14]
GSM712096
[15]
GSM712097
[16]
GSM712098
[17]
GSM712099
[18]
GSM712100
[19]
GSM712101
[20]
GSM712102
[21]
GSM712103
[22]
GSM712104
[23]
GSM712105
[24]
GSM712106
[25]
GSM712107
[26]
GSM712108
[27]
GSM712109
[28]
GSM712110
[29]
GSM712111
[30]
GSM712112
[31]
GSM712113
[32]
GSM712114
[33]
GSM712115
[34]
GSM712116
[35]
GSM712117
[36]
GSM712118
[37]
GSM712119
[38]
GSM712120
[39]
GSM712121
[40]
GSM712122
[41]
GSM712123
[42]
GSM712124
[43]
GSM712125
[44]
GSM712126
[45]
GSM712127
[46]
GSM712128
[47]
GSM712129
[48]
GSM712130
[49]
GSM712131
[50]
GSM712132
[51]
GSM712133
[52]
GSM712134
[53]
GSM712135
[54]
GSM712136
[55]
GSM712137
[56]
GSM712138
[57]
GSM712139
[58]
GSM712140
[59]
GSM712141
[60]
GSM712142
[61]
GSM712143
[62]
GSM712144
[63]
GSM712145
[64]
GSM712146
[65]
GSM712147
[66]
GSM712148
[67]
GSM712149
[68]
GSM712150
[69]
GSM712151
[70]
GSM712152
[71]
GSM712153
[72]
GSM712154
[73]
GSM712155
[74]
GSM712156
[75]
GSM712157
[76]
GSM712158
[77]
GSM712159
[78]
GSM712160
[79]
GSM712161
[80]
GSM712162
[81]
GSM712163
[82]
GSM712164
[83]
GSM712195
[84]
GSM712196
[85]
GSM712197
[86]
GSM712198
[87]
GSM712199
[88]
GSM712200
[89]
GSM712201
[90]
GSM712202
[91]
GSM712203
[92]
GSM712204
[93]
GSM712205
[94]
GSM712206
[95]
GSM712207
[96]
GSM712208
[97]
GSM712209
[98]
GSM712210
[99]
GSM712211
[100]
GSM712212
[101]
GSM712213
[102]
GSM712214
[103]
GSM712215
[104]
GSM712216
[105]
GSM712218
[106]
GSM712221
[107]
GSM712224
[108]
GSM712226
[109]
GSM712228
[110]
GSM712231
[111]
GSM712234
[112]
GSM712237
[113]
GSM712238
[114]
GSM712241
[115]
GSM712243
[116]
GSM712245
[117]
GSM712248
[118]
GSM712251
[119]
GSM712253
[120]
GSM712255
[121]
GSM712257
[122]
GSM712258
[123]
GSM712259
[124]
GSM712260
[125]
GSM712261
[126]
GSM712262
[127]
GSM712263
[128]
GSM712264
[129]
GSM712265
[130]
GSM712266
[131]
GSM712267
[132]
GSM712268
[133]
GSM712269
[134]
GSM712270
[135]
GSM712271
[136]
GSM712272
[137]
GSM712273
[138]
GSM712274
[139]
GSM712275
[140]
GSM712276
[141]
GSM712277
[142]
GSM712278
[143]
GSM712279
[144]
GSM712280
[145]
GSM712281
[146]
GSM712282
[147]
GSM712283
[148]
GSM712284
[149]
GSM712285
[150]
GSM712286
[151]
GSM712287
[152]
GSM712288
[153]
GSM712289
[154]
GSM712290
[155]
GSM712291
[156]
GSM712292
[157]
GSM712293
[158]
GSM712294
[159]
GSM712295
[160]
GSM712296
[161]
GSM712297
[162]
GSM712298
[163]
GSM712299
[164]
GSM712300
[165]
GSM712301
[166]
GSM712398
[167]
GSM712399
[168]
GSM712400
[169]
GSM712401
[170]
GSM712402
[171]
GSM712403
[172]
GSM712404
[173]
GSM712405
[174]
GSM712406
[175]
GSM712407
[176]
GSM712408
[177]
GSM712409
[178]
GSM712410
[179]
GSM712411
[180]
GSM712412
[181]
GSM712413
[182]
GSM712414
[183]
GSM712415
[184]
GSM712416
[185]
GSM712417
[186]
GSM712418
[187]
GSM712419
[188]
GSM712420
[189]
GSM712421
[190]
GSM712422
[191]
GSM712423
[192]
GSM712424
[193]
GSM712425
[194]
GSM712426
[195]
GSM712427
[196]
GSM712428
[197]
GSM712429
[198]
GSM712430
[199]
GSM712431
[200]
GSM712432
[201]
GSM712433
[202]
GSM712434
[203]
GSM712435
[204]
GSM712436
[205]
GSM712437
[206]
GSM712438
[207]
GSM712439
[208]
GSM712440
[209]
GSM712441
[210]
GSM712442
[211]
GSM712443
[212]
GSM712444
[213]
GSM712445
[214]
GSM712446
[215]
GSM712447
[216]
GSM712448
[217]
GSM712449
[218]
GSM712450
[219]
GSM712451
[220]
GSM712452
[221]
GSM712453
[222]
GSM712454
[223]
GSM712455
[224]
GSM712456
[225]
GSM712457
[226]
GSM712458
[227]
GSM712459
[228]
GSM712460
[229]
GSM712461
[230]
GSM712462
[231]
GSM712463
[232]
GSM712464
[233]
GSM712465
[234]
GSM712466
[235]
GSM712467
[236]
GSM712468
[237]
GSM712469
[238]
GSM712470
[239]
GSM712471
[240]
GSM712472
[241]
GSM712473
[242]
GSM712474
[243]
GSM712573
[244]
GSM712574
[245]
GSM712575
[246]
GSM712576
[247]
GSM712577
[248]
GSM712578
[249]
GSM712579
[250]
GSM712580
[251]
GSM712581
[252]
GSM712582
[253]
GSM712583
[254]
GSM712584
[255]
GSM712585
[256]
GSM712586
[257]
GSM712587
[258]
GSM712588
[259]
GSM712589
[260]
GSM712590
[261]
GSM712591
[262]
GSM712592
[263]
GSM712593
[264]
GSM712594
[265]
GSM712595
[266]
GSM712596
[267]
GSM712597
[268]
GSM712598
[269]
GSM712599
[270]
GSM712600
[271]
GSM712601
[272]
GSM712602
[273]
GSM712603
[274]
GSM712604
[275]
GSM712605
[276]
GSM712606
[277]
GSM712607
[278]
GSM712608
[279]
GSM712609
[280]
GSM712610
[281]
GSM712611
[282]
GSM712612
[283]
GSM712613
[284]
GSM712614
[285]
GSM712615
[286]
GSM712616
[287]
GSM712617
[288]
GSM712618
[289]
GSM712619
[290]
GSM712620
[291]
GSM712621
[292]
GSM712622
[293]
GSM712623
[294]
GSM712624
[295]
GSM712625
[296]
GSM712626
[297]
GSM712627
[298]
GSM712628
[299]
GSM712629
[300]
GSM712630
[301]
GSM712631
[302]
GSM712632
[303]
GSM712633
[304]
GSM712634
[305]
GSM712635
[306]
GSM712636
[307]
GSM712637
[308]
GSM712638
[309]
GSM712639
[310]
GSM712640
[311]
GSM712641
[312]
GSM712642
[313]
GSM712643
[314]
GSM712644
[315]
GSM712645
[316]
GSM712646
[317]
GSM712647
[318]
GSM712648
[319]
GSM712649
[320]
GSM714419
[321]
GSM714420
[322]
GSM714421
[323]
GSM714422
[324]
GSM714423
[325]
GSM714424
[326]
GSM714425
[327]
GSM714426
[328]
GSM714427
[329]
GSM714428
[330]
GSM714429
[331]
GSM714430
[332]
GSM714431
sample_count
333
group_sizes
null
group_sizes_basis
null
platform
5175;11028
taxon
Homo sapiens
title
Exon level expression profiling of colorectal cancer tissue samples
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE39582
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=GSE39582
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE39582
version
null
note
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
access_statement_kind
repository_route_statement
sample_accessions array · 585 items
[0]
GSM1681353
[1]
GSM1681354
[2]
GSM1681355
[3]
GSM1681356
[4]
GSM1681357
[5]
GSM1681358
[6]
GSM1681359
[7]
GSM1681360
[8]
GSM1681361
[9]
GSM1681362
[10]
GSM1681363
[11]
GSM1681364
[12]
GSM1681365
[13]
GSM1681366
[14]
GSM1681367
[15]
GSM1681368
[16]
GSM1681369
[17]
GSM1681370
[18]
GSM1681371
[19]
GSM971957
[20]
GSM971958
[21]
GSM971959
[22]
GSM971960
[23]
GSM971961
[24]
GSM971962
[25]
GSM971963
[26]
GSM971964
[27]
GSM971965
[28]
GSM971966
[29]
GSM971967
[30]
GSM971968
[31]
GSM971969
[32]
GSM971970
[33]
GSM971971
[34]
GSM971972
[35]
GSM971973
[36]
GSM971974
[37]
GSM971975
[38]
GSM971976
[39]
GSM971977
[40]
GSM971978
[41]
GSM971979
[42]
GSM971980
[43]
GSM971981
[44]
GSM971982
[45]
GSM971983
[46]
GSM971984
[47]
GSM971985
[48]
GSM971986
[49]
GSM971987
[50]
GSM971988
[51]
GSM971989
[52]
GSM971990
[53]
GSM971991
[54]
GSM971992
[55]
GSM971993
[56]
GSM971994
[57]
GSM971995
[58]
GSM971996
[59]
GSM971997
[60]
GSM971998
[61]
GSM971999
[62]
GSM972000
[63]
GSM972001
[64]
GSM972002
[65]
GSM972003
[66]
GSM972004
[67]
GSM972005
[68]
GSM972006
[69]
GSM972007
[70]
GSM972008
[71]
GSM972009
[72]
GSM972010
[73]
GSM972011
[74]
GSM972012
[75]
GSM972013
[76]
GSM972014
[77]
GSM972015
[78]
GSM972016
[79]
GSM972017
[80]
GSM972018
[81]
GSM972019
[82]
GSM972020
[83]
GSM972021
[84]
GSM972022
[85]
GSM972023
[86]
GSM972024
[87]
GSM972025
[88]
GSM972026
[89]
GSM972027
[90]
GSM972028
[91]
GSM972029
[92]
GSM972030
[93]
GSM972031
[94]
GSM972032
[95]
GSM972033
[96]
GSM972034
[97]
GSM972035
[98]
GSM972036
[99]
GSM972037
[100]
GSM972038
[101]
GSM972039
[102]
GSM972040
[103]
GSM972041
[104]
GSM972042
[105]
GSM972043
[106]
GSM972044
[107]
GSM972045
[108]
GSM972046
[109]
GSM972047
[110]
GSM972048
[111]
GSM972049
[112]
GSM972050
[113]
GSM972051
[114]
GSM972052
[115]
GSM972053
[116]
GSM972054
[117]
GSM972055
[118]
GSM972056
[119]
GSM972057
[120]
GSM972058
[121]
GSM972059
[122]
GSM972060
[123]
GSM972061
[124]
GSM972062
[125]
GSM972063
[126]
GSM972064
[127]
GSM972065
[128]
GSM972066
[129]
GSM972067
[130]
GSM972068
[131]
GSM972069
[132]
GSM972070
[133]
GSM972071
[134]
GSM972072
[135]
GSM972073
[136]
GSM972074
[137]
GSM972075
[138]
GSM972076
[139]
GSM972077
[140]
GSM972078
[141]
GSM972079
[142]
GSM972080
[143]
GSM972081
[144]
GSM972082
[145]
GSM972083
[146]
GSM972084
[147]
GSM972085
[148]
GSM972086
[149]
GSM972087
[150]
GSM972088
[151]
GSM972089
[152]
GSM972090
[153]
GSM972091
[154]
GSM972092
[155]
GSM972093
[156]
GSM972094
[157]
GSM972095
[158]
GSM972096
[159]
GSM972097
[160]
GSM972098
[161]
GSM972099
[162]
GSM972100
[163]
GSM972101
[164]
GSM972102
[165]
GSM972103
[166]
GSM972104
[167]
GSM972105
[168]
GSM972106
[169]
GSM972107
[170]
GSM972108
[171]
GSM972109
[172]
GSM972110
[173]
GSM972111
[174]
GSM972112
[175]
GSM972113
[176]
GSM972114
[177]
GSM972115
[178]
GSM972116
[179]
GSM972117
[180]
GSM972118
[181]
GSM972119
[182]
GSM972120
[183]
GSM972121
[184]
GSM972122
[185]
GSM972123
[186]
GSM972124
[187]
GSM972125
[188]
GSM972126
[189]
GSM972127
[190]
GSM972128
[191]
GSM972129
[192]
GSM972130
[193]
GSM972131
[194]
GSM972132
[195]
GSM972133
[196]
GSM972134
[197]
GSM972135
[198]
GSM972136
[199]
GSM972137
[200]
GSM972138
[201]
GSM972139
[202]
GSM972140
[203]
GSM972141
[204]
GSM972142
[205]
GSM972143
[206]
GSM972144
[207]
GSM972145
[208]
GSM972146
[209]
GSM972147
[210]
GSM972148
[211]
GSM972149
[212]
GSM972150
[213]
GSM972151
[214]
GSM972152
[215]
GSM972153
[216]
GSM972154
[217]
GSM972155
[218]
GSM972156
[219]
GSM972157
[220]
GSM972158
[221]
GSM972159
[222]
GSM972160
[223]
GSM972161
[224]
GSM972162
[225]
GSM972163
[226]
GSM972164
[227]
GSM972165
[228]
GSM972166
[229]
GSM972167
[230]
GSM972168
[231]
GSM972169
[232]
GSM972170
[233]
GSM972171
[234]
GSM972172
[235]
GSM972173
[236]
GSM972174
[237]
GSM972175
[238]
GSM972176
[239]
GSM972177
[240]
GSM972178
[241]
GSM972179
[242]
GSM972180
[243]
GSM972181
[244]
GSM972182
[245]
GSM972183
[246]
GSM972184
[247]
GSM972185
[248]
GSM972186
[249]
GSM972187
[250]
GSM972188
[251]
GSM972189
[252]
GSM972190
[253]
GSM972191
[254]
GSM972192
[255]
GSM972193
[256]
GSM972194
[257]
GSM972195
[258]
GSM972196
[259]
GSM972197
[260]
GSM972198
[261]
GSM972199
[262]
GSM972200
[263]
GSM972201
[264]
GSM972202
[265]
GSM972203
[266]
GSM972204
[267]
GSM972205
[268]
GSM972206
[269]
GSM972207
[270]
GSM972208
[271]
GSM972209
[272]
GSM972210
[273]
GSM972211
[274]
GSM972212
[275]
GSM972213
[276]
GSM972214
[277]
GSM972215
[278]
GSM972216
[279]
GSM972217
[280]
GSM972218
[281]
GSM972219
[282]
GSM972220
[283]
GSM972221
[284]
GSM972222
[285]
GSM972223
[286]
GSM972224
[287]
GSM972225
[288]
GSM972226
[289]
GSM972227
[290]
GSM972228
[291]
GSM972229
[292]
GSM972230
[293]
GSM972231
[294]
GSM972232
[295]
GSM972233
[296]
GSM972234
[297]
GSM972235
[298]
GSM972236
[299]
GSM972237
[300]
GSM972238
[301]
GSM972239
[302]
GSM972240
[303]
GSM972241
[304]
GSM972242
[305]
GSM972243
[306]
GSM972244
[307]
GSM972245
[308]
GSM972246
[309]
GSM972247
[310]
GSM972248
[311]
GSM972249
[312]
GSM972250
[313]
GSM972251
[314]
GSM972252
[315]
GSM972253
[316]
GSM972254
[317]
GSM972255
[318]
GSM972256
[319]
GSM972257
[320]
GSM972258
[321]
GSM972259
[322]
GSM972260
[323]
GSM972261
[324]
GSM972262
[325]
GSM972263
[326]
GSM972264
[327]
GSM972265
[328]
GSM972266
[329]
GSM972267
[330]
GSM972268
[331]
GSM972269
[332]
GSM972270
[333]
GSM972271
[334]
GSM972272
[335]
GSM972273
[336]
GSM972274
[337]
GSM972275
[338]
GSM972276
[339]
GSM972277
[340]
GSM972278
[341]
GSM972279
[342]
GSM972280
[343]
GSM972281
[344]
GSM972282
[345]
GSM972283
[346]
GSM972284
[347]
GSM972285
[348]
GSM972286
[349]
GSM972287
[350]
GSM972288
[351]
GSM972289
[352]
GSM972290
[353]
GSM972291
[354]
GSM972292
[355]
GSM972293
[356]
GSM972294
[357]
GSM972295
[358]
GSM972296
[359]
GSM972297
[360]
GSM972298
[361]
GSM972299
[362]
GSM972300
[363]
GSM972301
[364]
GSM972302
[365]
GSM972303
[366]
GSM972304
[367]
GSM972305
[368]
GSM972306
[369]
GSM972307
[370]
GSM972308
[371]
GSM972309
[372]
GSM972310
[373]
GSM972311
[374]
GSM972312
[375]
GSM972313
[376]
GSM972314
[377]
GSM972315
[378]
GSM972316
[379]
GSM972317
[380]
GSM972318
[381]
GSM972319
[382]
GSM972320
[383]
GSM972321
[384]
GSM972322
[385]
GSM972323
[386]
GSM972324
[387]
GSM972325
[388]
GSM972326
[389]
GSM972327
[390]
GSM972328
[391]
GSM972329
[392]
GSM972330
[393]
GSM972331
[394]
GSM972332
[395]
GSM972333
[396]
GSM972334
[397]
GSM972335
[398]
GSM972336
[399]
GSM972337
[400]
GSM972338
[401]
GSM972339
[402]
GSM972340
[403]
GSM972341
[404]
GSM972342
[405]
GSM972343
[406]
GSM972344
[407]
GSM972345
[408]
GSM972346
[409]
GSM972347
[410]
GSM972348
[411]
GSM972349
[412]
GSM972350
[413]
GSM972351
[414]
GSM972352
[415]
GSM972353
[416]
GSM972354
[417]
GSM972355
[418]
GSM972356
[419]
GSM972357
[420]
GSM972358
[421]
GSM972359
[422]
GSM972360
[423]
GSM972361
[424]
GSM972362
[425]
GSM972363
[426]
GSM972364
[427]
GSM972365
[428]
GSM972366
[429]
GSM972367
[430]
GSM972368
[431]
GSM972369
[432]
GSM972370
[433]
GSM972371
[434]
GSM972372
[435]
GSM972373
[436]
GSM972374
[437]
GSM972375
[438]
GSM972376
[439]
GSM972377
[440]
GSM972378
[441]
GSM972379
[442]
GSM972380
[443]
GSM972381
[444]
GSM972382
[445]
GSM972383
[446]
GSM972384
[447]
GSM972385
[448]
GSM972386
[449]
GSM972387
[450]
GSM972388
[451]
GSM972389
[452]
GSM972390
[453]
GSM972391
[454]
GSM972392
[455]
GSM972393
[456]
GSM972394
[457]
GSM972395
[458]
GSM972396
[459]
GSM972397
[460]
GSM972398
[461]
GSM972399
[462]
GSM972400
[463]
GSM972401
[464]
GSM972402
[465]
GSM972403
[466]
GSM972404
[467]
GSM972405
[468]
GSM972406
[469]
GSM972407
[470]
GSM972408
[471]
GSM972409
[472]
GSM972410
[473]
GSM972411
[474]
GSM972412
[475]
GSM972413
[476]
GSM972414
[477]
GSM972415
[478]
GSM972416
[479]
GSM972417
[480]
GSM972418
[481]
GSM972419
[482]
GSM972420
[483]
GSM972421
[484]
GSM972422
[485]
GSM972423
[486]
GSM972424
[487]
GSM972425
[488]
GSM972426
[489]
GSM972427
[490]
GSM972428
[491]
GSM972429
[492]
GSM972430
[493]
GSM972431
[494]
GSM972432
[495]
GSM972433
[496]
GSM972434
[497]
GSM972435
[498]
GSM972436
[499]
GSM972437
[500]
GSM972438
[501]
GSM972439
[502]
GSM972440
[503]
GSM972441
[504]
GSM972442
[505]
GSM972443
[506]
GSM972444
[507]
GSM972445
[508]
GSM972446
[509]
GSM972447
[510]
GSM972448
[511]
GSM972449
[512]
GSM972450
[513]
GSM972451
[514]
GSM972452
[515]
GSM972453
[516]
GSM972454
[517]
GSM972455
[518]
GSM972456
[519]
GSM972457
[520]
GSM972458
[521]
GSM972459
[522]
GSM972460
[523]
GSM972461
[524]
GSM972462
[525]
GSM972463
[526]
GSM972464
[527]
GSM972465
[528]
GSM972466
[529]
GSM972467
[530]
GSM972468
[531]
GSM972469
[532]
GSM972470
[533]
GSM972471
[534]
GSM972472
[535]
GSM972473
[536]
GSM972474
[537]
GSM972475
[538]
GSM972476
[539]
GSM972477
[540]
GSM972478
[541]
GSM972479
[542]
GSM972480
[543]
GSM972481
[544]
GSM972482
[545]
GSM972483
[546]
GSM972484
[547]
GSM972485
[548]
GSM972486
[549]
GSM972487
[550]
GSM972488
[551]
GSM972489
[552]
GSM972490
[553]
GSM972491
[554]
GSM972492
[555]
GSM972493
[556]
GSM972494
[557]
GSM972495
[558]
GSM972496
[559]
GSM972497
[560]
GSM972498
[561]
GSM972499
[562]
GSM972500
[563]
GSM972501
[564]
GSM972502
[565]
GSM972503
[566]
GSM972504
[567]
GSM972505
[568]
GSM972506
[569]
GSM972507
[570]
GSM972508
[571]
GSM972509
[572]
GSM972510
[573]
GSM972511
[574]
GSM972512
[575]
GSM972513
[576]
GSM972514
[577]
GSM972515
[578]
GSM972516
[579]
GSM972517
[580]
GSM972518
[581]
GSM972519
[582]
GSM972520
[583]
GSM972521
[584]
GSM972522
sample_count
585
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 16 fields
id
asset:table:pmid:33116619:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:227d61ab934aebf930aaa9489a3b8f5cd1466a8f926bd65e00de0ae47bccab5b
bytes
1131
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[1]#t0001
version
null
note
Clinical Information Statistics
structure object · 5 fields
pmcid
PMC7569059
section_index
14
section_title
Preprocessing Data Statistics
row_count
25
column_count
6
table object · 8 fields
label
Table 1
caption
Clinical Information Statistics
rows array · 25 items
[0] array · 5 items
[0]
Characteristics
[1]
TCGA Training Datasets (n=226)
[2]
TCGA Test Datasets (n=227)
[3]
p value
[4]
GSE17538 (n=238)
[1] array · 6 items
[0]
Age (years)
[1]
≤50
[2]
31
[3]
29
[4]
0.875
[5]
32
[2] array · 4 items
[0]
>50
[1]
195
[2]
198
[3]
206
[3] array · 6 items
[0]
Survival times (years)
[1]
Median
[2]
1.81
[3]
1.97
[4]
–
[5]
2.38
[4] array · 4 items
[0]
Mean
[1]
2.25
[2]
2.44
[3]
3.12
[5] array · 6 items
[0]
Survival status
[1]
Living
[2]
178
[3]
176
[4]
0.839
[5]
145
[6] array · 4 items
[0]
Dead
[1]
48
[2]
51
[3]
55
[7] array · 6 items
[0]
Gender
[1]
Female
[2]
104
[3]
109
[4]
0.739
[5]
114
[8] array · 4 items
[0]
Male
[1]
122
[2]
118
[3]
124
[9] array · 6 items
[0]
Lymphatic invasion
[1]
NO
[2]
125
[3]
128
[4]
0.695
[5]
–
[10] array · 4 items
[0]
YES
[1]
81
[2]
75
[3]
–
[11] array · 6 items
[0]
pathologic_T
[1]
T1
[2]
6
[3]
5
[4]
0.769
[5]
–
[12] array · 4 items
[0]
T2
[1]
35
[2]
43
[3]
–
[13] array · 4 items
[0]
T3
[1]
157
[2]
153
[3]
–
[14] array · 4 items
[0]
T4
[1]
28
[2]
25
[3]
–
[15] array · 6 items
[0]
pathologic_N
[1]
N0
[2]
127
[3]
139
[4]
0.454
[5]
–
[16] array · 4 items
[0]
N1
[1]
54
[2]
52
[3]
–
[17] array · 4 items
[0]
N2
[1]
45
[2]
36
[3]
–
[18] array · 4 items
[0]
N3
[1]
0
[2]
0
[3]
–
[19] array · 6 items
[0]
pathologic_M
[1]
M0
[2]
165
[3]
168
[4]
0.956
[5]
–
[20] array · 4 items
[0]
M1/MX
[1]
57
[2]
56
[3]
–
[21] array · 6 items
[0]
AJCC stage
[1]
Stage Ⅰ
[2]
34
[3]
42
[4]
0.332
[5]
28
[22] array · 4 items
[0]
Stage Ⅱ
[1]
82
[2]
92
[3]
72
[23] array · 4 items
[0]
Stage III
[1]
73
[2]
57
[3]
76
[24] array · 4 items
[0]
Stage Ⅳ
[1]
30
[2]
32
[3]
56
locator
section[14]/table-wrap[1]#t0001
[6] object · 16 fields
id
asset:table:pmid:33116619:2
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:e2121ce1abf78a1b31ce39dc7176d7620c469da298df71946eaf77c63dad14e5
bytes
1526
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[2]#t0002
version
null
note
Information on Top20 Prognosis-Related Genes
structure object · 5 fields
pmcid
PMC7569059
section_index
14
section_title
Preprocessing Data Statistics
row_count
21
column_count
6
table object · 8 fields
label
Table 2
caption
Information on Top20 Prognosis-Related Genes
rows array · 21 items
[0] array · 6 items
[0]
ENGSID
[1]
Genesymbol
[2]
HR
[3]
Coefficient
[4]
z score
[5]
p value
[1] array · 6 items
[0]
ENSG00000241697
[1]
TMEFF1
[2]
1.552
[3]
0.440
[4]
4.737
[5]
2.17E-06
[2] array · 6 items
[0]
ENSG00000160117
[1]
ANKLE1
[2]
1.525
[3]
0.422
[4]
4.691
[5]
2.72E-06
[3] array · 6 items
[0]
ENSG00000214128
[1]
TMEM213
[2]
1.427
[3]
0.355
[4]
4.559
[5]
5.13E-06
[4] array · 6 items
[0]
ENSG00000090932
[1]
DLL3
[2]
1.622
[3]
0.483
[4]
4.528
[5]
5.95E-06
[5] array · 6 items
[0]
ENSG00000268940
[1]
CT45A1
[2]
1.361
[3]
0.308
[4]
4.522
[5]
6.11E-06
[6] array · 6 items
[0]
ENSG00000159556
[1]
ISL2
[2]
1.528
[3]
0.424
[4]
4.502
[5]
6.72E-06
[7] array · 6 items
[0]
ENSG00000205456
[1]
TP53TG3D
[2]
1.474
[3]
0.388
[4]
4.407
[5]
1.05E-05
[8] array · 6 items
[0]
ENSG00000100156
[1]
SLC16A8
[2]
1.473
[3]
0.387
[4]
4.381
[5]
1.18E-05
[9] array · 6 items
[0]
ENSG00000182759
[1]
MAFA
[2]
1.471
[3]
0.386
[4]
4.321
[5]
1.56E-05
[10] array · 6 items
[0]
ENSG00000106689
[1]
LHX2
[2]
1.472
[3]
0.387
[4]
4.284
[5]
1.84E-05
[11] array · 6 items
[0]
ENSG00000148331
[1]
ASB6
[2]
2.035
[3]
0.711
[4]
4.275
[5]
1.91E-05
[12] array · 6 items
[0]
ENSG00000269437
[1]
NXF2B
[2]
1.425
[3]
0.354
[4]
4.269
[5]
1.96E-05
[13] array · 6 items
[0]
ENSG00000124260
[1]
MAGEA10
[2]
1.366
[3]
0.312
[4]
4.262
[5]
2.02E-05
[14] array · 6 items
[0]
ENSG00000126890
[1]
CTAG2
[2]
1.346
[3]
0.297
[4]
4.210
[5]
2.56E-05
[15] array · 6 items
[0]
ENSG00000184029
[1]
DSCR4
[2]
1.414
[3]
0.347
[4]
4.172
[5]
3.02E-05
[16] array · 6 items
[0]
ENSG00000187730
[1]
GABRD
[2]
1.480
[3]
0.392
[4]
4.153
[5]
3.29E-05
[17] array · 6 items
[0]
ENSG00000149927
[1]
DOC2A
[2]
1.600
[3]
0.470
[4]
4.127
[5]
3.68E-05
[18] array · 6 items
[0]
ENSG00000075043
[1]
KCNQ2
[2]
1.428
[3]
0.356
[4]
4.126
[5]
3.69E-05
[19] array · 6 items
[0]
ENSG00000110148
[1]
CCKBR
[2]
1.404
[3]
0.339
[4]
4.113
[5]
3.91E-05
[20] array · 6 items
[0]
ENSG00000121905
[1]
HPCA
[2]
1.492
[3]
0.400
[4]
4.107
[5]
4.01E-05
locator
section[14]/table-wrap[2]#t0002
[7] object · 16 fields
id
asset:table:pmid:33116619:3
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:ef8bfd1df3bf245a1d4a6b1b757b8b8219e7f9a3739c362a06ec36256a2ecfc0
bytes
1006
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[18]/table-wrap[1]#t0003
version
null
note
9- Genes Significantly Associated with the Overall Survival in the Training Dataset
structure object · 5 fields
pmcid
PMC7569059
section_index
18
section_title
Establishing 9-Gene Signature to Divide Samples in TCGA Training Cohort
row_count
10
column_count
7
table object · 8 fields
label
Table 3
caption
9- Genes Significantly Associated with the Overall Survival in the Training Dataset
rows array · 10 items
[0] array · 7 items
[0]
Ensembl Gene ID
[1]
Symbol
[2]
HR
[3]
Z-score
[4]
P value
[5]
Importance
[6]
Relative Importance
[1] array · 7 items
[0]
ENSG00000170178
[1]
HOXD12
[2]
1.30
[3]
2.349091
[4]
1.88E-02
[5]
0.0096
[6]
1
[2] array · 7 items
[0]
ENSG00000163481
[1]
RNF25
[2]
1.52
[3]
2.540626
[4]
1.11E-02
[5]
0.0094
[6]
0.9848
[3] array · 7 items
[0]
ENSG00000139899
[1]
CBLN3
[2]
1.39
[3]
2.249482
[4]
2.45E-02
[5]
0.0088
[6]
0.9242
[4] array · 7 items
[0]
ENSG00000088538
[1]
DOCK3
[2]
1.52
[3]
3.782743
[4]
1.55E-04
[5]
0.0078
[6]
0.8182
[5] array · 7 items
[0]
ENSG00000044115
[1]
CTNNA1
[2]
0.73
[3]
−2.399278
[4]
1.64E-02
[5]
0.0064
[6]
0.6667
[6] array · 7 items
[0]
ENSG00000152894
[1]
PTPRK
[2]
0.71
[3]
−2.371469
[4]
1.77E-02
[5]
0.0049
[6]
0.5152
[7] array · 7 items
[0]
ENSG00000187726
[1]
DNAJB13
[2]
1.28
[3]
2.639895
[4]
8.29E-03
[5]
0.0046
[6]
0.4848
[8] array · 7 items
[0]
ENSG00000171428
[1]
NAT1
[2]
0.70
[3]
−2.402113
[4]
1.63E-02
[5]
0.0045
[6]
0.4697
[9] array · 7 items
[0]
ENSG00000163348
[1]
PYGO2
[2]
1.47
[3]
2.390166
[4]
1.68E-02
[5]
0.0032
[6]
0.3333
locator
section[18]/table-wrap[1]#t0003
[8] object · 16 fields
id
asset:table:pmid:33116619:4
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:b2775da1979b3501a0a73063906b2ee59aeaf4428d381a68155e466c97023a4e
bytes
1688
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[21]/table-wrap[1]#t0004
version
null
note
Univariate and Multivariate Cox Regression Analyses
structure object · 5 fields
pmcid
PMC7569059
section_index
21
section_title
Univariate and Multivariate Cox Regression Analysis
row_count
23
column_count
7
table object · 8 fields
label
Table 4
caption
Univariate and Multivariate Cox Regression Analyses
rows array · 23 items
[0] array · 3 items
[0]
Variables
[1]
Univariate Analysis
[2]
Multivariable Analysis
[1] array · 6 items
[0]
HR
[1]
95% CI of HR
[2]
P value
[3]
HR
[4]
95% CI of HR
[5]
P value
[2] array · 1 item
[0]
TCGA training datasets
[3] array · 1 item
[0]
9-gene risk score
[4] array · 7 items
[0]
Low-risk score
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[5] array · 7 items
[0]
High-risk score
[1]
3.97
[2]
2.04–7.73
[3]
4.9E-05
[4]
3.05
[5]
1.36–6.84
[6]
0.007
[6] array · 7 items
[0]
Age(≤50/>50)
[1]
1.02
[2]
0.99–1.05
[3]
6.0E-02
[4]
1.04
[5]
1.00–1.07
[6]
0.016
[7] array · 7 items
[0]
Gender female
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[8] array · 7 items
[0]
Gender male
[1]
1.05
[2]
0.59–1.86
[3]
0.87
[4]
0.66
[5]
0.31–1.37
[6]
0.265
[9] array · 7 items
[0]
Lymphatic Invasion NO
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[10] array · 7 items
[0]
Lymphatic Invasion YES
[1]
2.58
[2]
1.35–4.91
[3]
0.00
[4]
1.94
[5]
0.66–5.68
[6]
0.227
[11] array · 7 items
[0]
Pathologic T 1/ T 2
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[12] array · 7 items
[0]
Pathologic T 3
[1]
1.55
[2]
0.54–4.43
[3]
0.412
[4]
0.15
[5]
0.01–1.34
[6]
0.091
[13] array · 7 items
[0]
Pathologic T 4
[1]
5.15
[2]
1.66–16
[3]
0.005
[4]
0.43
[5]
0.04–4.13
[6]
0.461
[14] array · 7 items
[0]
Pathologic N 0
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[15] array · 7 items
[0]
Pathologic N 1
[1]
1.38
[2]
0.63–2.96
[3]
0.413
[4]
0.24
[5]
0.04–1.56
[6]
0.136
[16] array · 7 items
[0]
Pathologic N 2
[1]
3.00
[2]
1.58–5.66
[3]
0.001
[4]
0.49
[5]
0.07–3.21
[6]
0.456
[17] array · 7 items
[0]
Pathologic M 0
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[18] array · 7 items
[0]
Pathologic M 1
[1]
4.52
[2]
2.33–8.73
[3]
7.42E-06
[4]
2.28
[5]
0.89–5.79
[6]
0.080
[19] array · 7 items
[0]
Pathologic M X
[1]
1.82
[2]
0.77–4.26
[3]
0.168
[4]
1.56
[5]
0.50–4.84
[6]
0.440
[20] array · 7 items
[0]
AJCC Stage Ⅰ
[1]
1 (Ref)
[2]
[3]
[4]
1 (Ref)
[5]
[6]
[21] array · 7 items
[0]
AJCC Stage Ⅱ
[1]
1.94
[2]
0.43–8.65
[3]
0.3854
[4]
13.42
[5]
0.68–262.17
[6]
0.087
[22] array · 7 items
[0]
AJCC Stage III/Ⅳ
[1]
4.28
[2]
1.01–17.98
[3]
0.047
[4]
37.58
[5]
1.42–990.93
[6]
0.030
locator
section[21]/table-wrap[1]#t0004
[9] object · 16 fields
id
asset:table:pmid:33116619:5
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:e70f1e000edfa96c6ca12d108db3d9f1dfd4d130ab162cc9e72a325f14e2f926
bytes
2458
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[22]/table-wrap[1]#t0005
version
null
note
GSEA Analysis of 9-Gene Signature
structure object · 5 fields
pmcid
PMC7569059
section_index
22
section_title
Analysis of Pathways Enriched in High-Risk and Low-Risk Groups Using GSEA
row_count
30
column_count
6
table object · 8 fields
label
Table 5
caption
GSEA Analysis of 9-Gene Signature
rows array · 30 items
[0] array · 6 items
[0]
Name
[1]
SIZE
[2]
ES
[3]
NES
[4]
NOM p-val
[5]
FDR q-val
[1] array · 6 items
[0]
KEGG_O_GLYCAN_BIOSYNTHESIS
[1]
26
[2]
−0.650
[3]
−1.907
[4]
0.000
[5]
0.355
[2] array · 6 items
[0]
KEGG_UBIQUITIN_MEDIATED_PROTEOLYSIS
[1]
133
[2]
−0.502
[3]
−1.882
[4]
0.006
[5]
0.245
[3] array · 6 items
[0]
KEGG_ERBB_SIGNALING_PATHWAY
[1]
87
[2]
−0.455
[3]
−1.772
[4]
0.008
[5]
0.494
[4] array · 6 items
[0]
KEGG_ENDOMETRIAL_CANCER
[1]
52
[2]
−0.493
[3]
−1.716
[4]
0.008
[5]
0.586
[5] array · 6 items
[0]
KEGG_OOCYTE_MEIOSIS
[1]
110
[2]
−0.455
[3]
−1.716
[4]
0.008
[5]
0.471
[6] array · 6 items
[0]
KEGG_THYROID_CANCER
[1]
29
[2]
−0.511
[3]
−1.709
[4]
0.006
[5]
0.415
[7] array · 6 items
[0]
KEGG_COLORECTAL_CANCER
[1]
62
[2]
−0.470
[3]
−1.701
[4]
0.012
[5]
0.377
[8] array · 6 items
[0]
KEGG_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION
[1]
44
[2]
−0.584
[3]
−1.690
[4]
0.056
[5]
0.356
[9] array · 6 items
[0]
KEGG_PROSTATE_CANCER
[1]
89
[2]
−0.445
[3]
−1.689
[4]
0.019
[5]
0.321
[10] array · 6 items
[0]
KEGG_APOPTOSIS
[1]
86
[2]
−0.438
[3]
−1.680
[4]
0.021
[5]
0.312
[11] array · 6 items
[0]
KEGG_INSULIN_SIGNALING_PATHWAY
[1]
136
[2]
−0.393
[3]
−1.675
[4]
0.010
[5]
0.292
[12] array · 6 items
[0]
KEGG_BASAL_TRANSCRIPTION_FACTORS
[1]
34
[2]
−0.546
[3]
−1.657
[4]
0.025
[5]
0.306
[13] array · 6 items
[0]
KEGG_RENAL_CELL_CARCINOMA
[1]
70
[2]
−0.448
[3]
−1.602
[4]
0.037
[5]
0.413
[14] array · 6 items
[0]
KEGG_ADHERENS_JUNCTION
[1]
73
[2]
−0.455
[3]
−1.596
[4]
0.046
[5]
0.400
[15] array · 6 items
[0]
KEGG_DORSO_VENTRAL_AXIS_FORMATION
[1]
24
[2]
−0.511
[3]
−1.585
[4]
0.035
[5]
0.398
[16] array · 6 items
[0]
KEGG_NEUROTROPHIN_SIGNALING_PATHWAY
[1]
125
[2]
−0.399
[3]
−1.585
[4]
0.040
[5]
0.374
[17] array · 6 items
[0]
KEGG_RENIN_ANGIOTENSIN_SYSTEM
[1]
17
[2]
−0.527
[3]
−1.583
[4]
0.035
[5]
0.356
[18] array · 6 items
[0]
KEGG_ENDOCYTOSIS
[1]
177
[2]
−0.379
[3]
−1.570
[4]
0.042
[5]
0.365
[19] array · 6 items
[0]
KEGG_PEROXISOME
[1]
78
[2]
−0.470
[3]
−1.568
[4]
0.063
[5]
0.351
[20] array · 6 items
[0]
KEGG_AMINO_SUGAR_AND_NUCLEOTIDE_SUGAR_METABOLISM
[1]
44
[2]
−0.451
[3]
−1.550
[4]
0.054
[5]
0.373
[21] array · 6 items
[0]
KEGG_PROPANOATE_METABOLISM
[1]
32
[2]
−0.525
[3]
−1.544
[4]
0.064
[5]
0.370
[22] array · 6 items
[0]
KEGG_LONG_TERM_POTENTIATION
[1]
68
[2]
−0.402
[3]
−1.534
[4]
0.023
[5]
0.375
[23] array · 6 items
[0]
KEGG_FATTY_ACID_METABOLISM
[1]
41
[2]
−0.484
[3]
−1.533
[4]
0.100
[5]
0.360
[24] array · 6 items
[0]
KEGG_STARCH_AND_SUCROSE_METABOLISM
[1]
50
[2]
−0.441
[3]
−1.517
[4]
0.056
[5]
0.380
[25] array · 6 items
[0]
KEGG_CHRONIC_MYELOID_LEUKEMIA
[1]
73
[2]
−0.417
[3]
−1.507
[4]
0.086
[5]
0.387
[26] array · 6 items
[0]
KEGG_P53_SIGNALING_PATHWAY
[1]
66
[2]
−0.420
[3]
−1.502
[4]
0.056
[5]
0.383
[27] array · 6 items
[0]
KEGG_BIOSYNTHESIS_OF_UNSATURATED_FATTY_ACIDS
[1]
20
[2]
−0.506
[3]
−1.496
[4]
0.069
[5]
0.383
[28] array · 6 items
[0]
KEGG_TGF_BETA_SIGNALING_PATHWAY
[1]
85
[2]
−0.399
[3]
−1.493
[4]
0.059
[5]
0.374
[29] array · 6 items
[0]
KEGG_NICOTINATE_AND_NICOTINAMIDE_METABOLISM
[1]
22
[2]
−0.423
[3]
−1.467
[4]
0.0391
[5]
0.4133
locator
section[22]/table-wrap[1]#t0005
gaps array · 8 items
[0]
asset:data:geo:GSE17538 not downloaded
[1]
asset:data:geo:GSE17538 licence not read
[2]
asset:data:geo:GSE19234 not downloaded
[3]
asset:data:geo:GSE19234 licence not read
[4]
asset:data:geo:GSE24551 not downloaded
[5]
asset:data:geo:GSE24551 licence not read
[6]
asset:data:geo:GSE39582 not downloaded
[7]
asset:data:geo:GSE39582 licence not read
analysis object · 4 fields
state
partial
methods array · 6 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[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
0.8
band
high
quote
Kaplan-Meier
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[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
band
medium
quote
Cox regression
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
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
0.8
band
high
quote
log-rank
[3] object · 10 fields
id
method-4
family
machine_learning
specific
random_forest
label
Machine learning
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
machine_learning_random_forest
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
random forest
[4] object · 10 fields
id
method-5
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.8
band
high
quote
ROC curve
[5] object · 10 fields
id
method-6
family
null
specific
null
label
Random survival forest algorithm
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
reordered
quote
“The importance of prognostic genes is sequenced using R package random survival forest.”
targets array · 0 items
gaps array · 1 item
[0]
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
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[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 · 1 item
[0]
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 · 4 items
[0]
GSE17538
[1]
GSE39582
[2]
GSE24551
[3]
GSE19234
resolved_accessions array · 4 items
[0]
GSE17538
[1]
GSE39582
[2]
GSE24551
[3]
GSE19234
statements array · 1 item
[0]
Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).
basis
The paper names GSE17538, GSE39582, GSE24551, GSE19234 in 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 · 1 item
[0]
survival_km
assets array · 7 items
[0]
source:pmid:33116619
[1]
data:geo:GSE17538
[2]
asset:table:pmid:33116619:1
[3]
asset:table:pmid:33116619:2
[4]
asset:table:pmid:33116619:3
[5]
asset:table:pmid:33116619:4
[6]
asset:table:pmid:33116619:5
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:GSE17538
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
2026-10-31T18:23:38Z
independence
single_reader
evidence_check object · 2 fields
method
reordered
availability
null
calls
3
usage object · 3 fields
prompt_tokens
29966
completion_tokens
1648
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
[0]
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:33116619
type
paper
label
pmid:33116619
[1] object · 3 fields
id
source:pmid:33116619
type
manuscript
label
PMID 33116619 full text
[2] object · 3 fields
id
data:geo:GSE17538
type
dataset
label
GEO GSE17538
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:33116619
type
paper
label
pmid:33116619
[1] object · 3 fields
id
source:pmid:33116619
type
manuscript
label
PMID 33116619 full text
[2] object · 3 fields
id
data:geo:GSE17538
type
dataset
label
GEO GSE17538
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33116619
type
extraction
used array · 1 item
[0]
source:pmid:33116619
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE17538
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE17538
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
label
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:33116619
parent_hash
sha256:71c5c529ae821094dc1b93bf789f932f2a2b506607e80043247d49faeecac7a8
fork_of
null
gaps array · 13 items
[0]
asset:data:geo:GSE17538 licence not read
[1]
asset:data:geo:GSE17538 not downloaded
[2]
asset:data:geo:GSE19234 licence not read
[3]
asset:data:geo:GSE19234 not downloaded
[4]
asset:data:geo:GSE24551 licence not read
[5]
asset:data:geo:GSE24551 not downloaded
[6]
asset:data:geo:GSE39582 licence not read
[7]
asset:data:geo:GSE39582 not downloaded
[8]
execution.not_run
[9]
method.reader_named_unmapped
[10]
review.human_critique
[11]
review.independent_reader
[12]
review.machine_critique
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes
[1]
nd external verification set. The results of qPCR based on clinical samples showed that the ex
order_basis
paper_text_order:815
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
survival_km
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Kaplan-Meier
order_basis
consumes_earlier_output
id
assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33116619", "kind": "science-record", "revision": 8, "content_hash": "sha256:8f217a809a3f35b17e0e5e97d58786ca157ed22b7a1c8b79cbbc732ba3bb12e7", "created_at": "2026-11-01T15:41:14Z", "updated_at": "2026-11-01T22:02:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Gene Expression Along with Genomic Copy Number Variation and Mutational Analysis Were Used to Develop a 9-Gene Signature for Estimating Prognosis of COAD.", "doi": "10.2147/OTT.S255590", "pmid": "33116619", "authors": ["Yiping Lu", "Si Wu", "Changwan Cui", "Miao Yu", "Shuang Wang", "Yuanyi Yue", "Miao Liu", "Zhengrong Sun"], "journal": "OncoTargets and therapy", "year": 2020, "abstract": "PURPOSE: This study aims to systematically analyze multi-omics data to explore new prognosis biomarkers in colon adenocarcinoma (COAD).\nMATERIALS AND METHODS: Multi-omics data of COAD and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox analysis was used to select genes which significantly related to the overall survival. GISTIC 2.0 software was used to identify significant amplification or deletion. Mutsig 2.0 software was used to identify significant mutation genes. The 9-gene signature was screened by random forest algorithm and Cox regression analysis. GSE17538 dataset was used as an external dataset to verify the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes in clinical specimens.\nRESULTS: A total of 71 candidate genes are obtained by integrating genomic variation, mutation and prognostic data. Then, 9-gene signature was established, which includes HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, PYGO2, CTNNA1, PTPRK, and NAT1. The 9-gene signature is an independent prognostic risk factor for COAD patients. In addition, the signature shows good predicting performance and clinical practicality in training set, testing set and external verification set. The results of qPCR based on clinical samples showed that the expression of HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, and PYGO2 was increased in colon cancer tissues and the expression of CTNNA1, PTPRK, NAT1 was decreased in colon cancer tissues.\nCONCLUSION: In this study, 9-gene signature is constructed as a new prognostic marker to predict the survival of COAD patients.", "claims": [{"id": "claim-data-access", "statement": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33116619", "locator": "sections[3] \"Data Acquisition and Processing\" paragraph 2", "quote": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/)."}], "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:33116619"], "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:GSE17538"], "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:GSE17538"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33116619", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/OTT.S255590", "sha256": "sha256:73f57e38fdc6eb2cffd2f22cf2b6196810383dffc6a5e49436bb26f007010c71", "bytes": 36368, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/OTT.S255590", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7569059", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17538", "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=GSE17538", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17538", "version": null, "note": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM437093", "GSM437094", "GSM437095", "GSM437096", "GSM437097", "GSM437098", "GSM437099", "GSM437100", "GSM437101", "GSM437102", "GSM437103", "GSM437104", "GSM437105", "GSM437106", "GSM437107", "GSM437108", "GSM437109", "GSM437110", "GSM437111", "GSM437112", "GSM437113", "GSM437114", "GSM437115", "GSM437116", "GSM437117", "GSM437118", "GSM437119", "GSM437120", "GSM437121", "GSM437122", "GSM437123", "GSM437124", "GSM437125", "GSM437126", "GSM437127", "GSM437128", "GSM437129", "GSM437130", "GSM437131", "GSM437132", "GSM437133", "GSM437134", "GSM437135", "GSM437136", "GSM437137", "GSM437138", "GSM437139", "GSM437140", "GSM437141", "GSM437142", "GSM437143", "GSM437144", "GSM437145", "GSM437146", "GSM437147", "GSM437148", "GSM437149", "GSM437150", "GSM437151", "GSM437152", "GSM437153", "GSM437154", "GSM437155", "GSM437156", "GSM437157", "GSM437158", "GSM437159", "GSM437160", "GSM437161", "GSM437162", "GSM437163", "GSM437164", "GSM437165", "GSM437166", "GSM437167", "GSM437168", "GSM437169", "GSM437170", "GSM437171", "GSM437172", "GSM437173", "GSM437174", "GSM437175", "GSM437176", "GSM437177", "GSM437178", "GSM437179", "GSM437180", "GSM437181", "GSM437182", "GSM437183", "GSM437184", "GSM437185", "GSM437186", "GSM437187", "GSM437188", "GSM437189", "GSM437190", "GSM437191", "GSM437192", "GSM437193", "GSM437194", "GSM437195", "GSM437196", "GSM437197", "GSM437198", "GSM437199", "GSM437200", "GSM437201", "GSM437202", "GSM437203", "GSM437204", "GSM437205", "GSM437206", "GSM437207", "GSM437208", "GSM437209", "GSM437210", "GSM437211", "GSM437212", "GSM437213", "GSM437214", "GSM437215", "GSM437216", "GSM437217", "GSM437218", "GSM437219", "GSM437220", "GSM437221", "GSM437222", "GSM437223", "GSM437224", "GSM437225", "GSM437226", "GSM437227", "GSM437228", "GSM437229", "GSM437230", "GSM437231", "GSM437232", "GSM437233", "GSM437234", "GSM437235", "GSM437236", "GSM437237", "GSM437238", "GSM437239", "GSM437240", "GSM437241", "GSM437242", "GSM437243", "GSM437244", "GSM437245", "GSM437246", "GSM437247", "GSM437248", "GSM437249", "GSM437250", "GSM437251", "GSM437252", "GSM437253", "GSM437254", "GSM437255", "GSM437256", "GSM437257", "GSM437258", "GSM437259", "GSM437260", "GSM437261", "GSM437262", "GSM437263", "GSM437264", "GSM437265", "GSM437266", "GSM437267", "GSM437268", "GSM437269", "GSM437270", "GSM437271", "GSM437272", "GSM437273", "GSM437274", "GSM437275", "GSM437276", "GSM437277", "GSM437278", "GSM437279", "GSM437280", "GSM437281", "GSM437282", "GSM437283", "GSM437284", "GSM437285", "GSM437286", "GSM437287", "GSM437288", "GSM437289", "GSM437290", "GSM437291", "GSM437292", "GSM437293", "GSM437294", "GSM437295", "GSM437296", "GSM437297", "GSM437298", "GSM437299", "GSM437300", "GSM437301", "GSM437302", "GSM437303", "GSM437304", "GSM437305", "GSM437306", "GSM437307", "GSM437308", "GSM437309", "GSM437310", "GSM437311", "GSM437312", "GSM437313", "GSM437314", "GSM437315", "GSM437316", "GSM437317", "GSM437318", "GSM437319", "GSM437320", "GSM437321", "GSM437322", "GSM437323", "GSM437324", "GSM472192", "GSM472193", "GSM472194", "GSM472195", "GSM472196", "GSM472197", "GSM472198", "GSM472199", "GSM472200", "GSM472201", "GSM472202", "GSM472203"], "sample_count": 244, "group_sizes": null, "group_sizes_basis": null, "platform": "570;1261", "taxon": "Mus musculus; Homo sapiens", "title": "Experimentally Derived Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE19234", "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=GSE19234", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19234", "version": null, "note": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM476606", "GSM476607", "GSM476608", "GSM476609", "GSM476610", "GSM476611", "GSM476612", "GSM476613", "GSM476614", "GSM476615", "GSM476616", "GSM476617", "GSM476618", "GSM476619", "GSM476620", "GSM476621", "GSM476622", "GSM476623", "GSM476624", "GSM476625", "GSM476626", "GSM476627", "GSM476628", "GSM476629", "GSM476630", "GSM476631", "GSM476632", "GSM476633", "GSM476634", "GSM476635", "GSM476636", "GSM476637", "GSM476638", "GSM476639", "GSM476640", "GSM476641", "GSM476642", "GSM476643", "GSM476644", "GSM476645", "GSM476646", "GSM476647", "GSM476648", "GSM476649"], "sample_count": 44, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Immune profile and mitotic index of metastatic melanoma lesions enhance clinical staging in predicting patient survival.", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE24551", "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=GSE24551", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE24551", "version": null, "note": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM712082", "GSM712083", "GSM712084", "GSM712085", "GSM712086", "GSM712087", "GSM712088", "GSM712089", "GSM712090", "GSM712091", "GSM712092", "GSM712093", "GSM712094", "GSM712095", "GSM712096", "GSM712097", "GSM712098", "GSM712099", "GSM712100", "GSM712101", "GSM712102", "GSM712103", "GSM712104", "GSM712105", "GSM712106", "GSM712107", "GSM712108", "GSM712109", "GSM712110", "GSM712111", "GSM712112", "GSM712113", "GSM712114", "GSM712115", "GSM712116", "GSM712117", "GSM712118", "GSM712119", "GSM712120", "GSM712121", "GSM712122", "GSM712123", "GSM712124", "GSM712125", "GSM712126", "GSM712127", "GSM712128", "GSM712129", "GSM712130", "GSM712131", "GSM712132", "GSM712133", "GSM712134", "GSM712135", "GSM712136", "GSM712137", "GSM712138", "GSM712139", "GSM712140", "GSM712141", "GSM712142", "GSM712143", "GSM712144", "GSM712145", "GSM712146", "GSM712147", "GSM712148", "GSM712149", "GSM712150", "GSM712151", "GSM712152", "GSM712153", "GSM712154", "GSM712155", "GSM712156", "GSM712157", "GSM712158", "GSM712159", "GSM712160", "GSM712161", "GSM712162", "GSM712163", "GSM712164", "GSM712195", "GSM712196", "GSM712197", "GSM712198", "GSM712199", "GSM712200", "GSM712201", "GSM712202", "GSM712203", "GSM712204", "GSM712205", "GSM712206", "GSM712207", "GSM712208", "GSM712209", "GSM712210", "GSM712211", "GSM712212", "GSM712213", "GSM712214", "GSM712215", "GSM712216", "GSM712218", "GSM712221", "GSM712224", "GSM712226", "GSM712228", "GSM712231", "GSM712234", "GSM712237", "GSM712238", "GSM712241", "GSM712243", "GSM712245", "GSM712248", "GSM712251", "GSM712253", "GSM712255", "GSM712257", "GSM712258", "GSM712259", "GSM712260", "GSM712261", "GSM712262", "GSM712263", "GSM712264", "GSM712265", "GSM712266", "GSM712267", "GSM712268", "GSM712269", "GSM712270", "GSM712271", "GSM712272", "GSM712273", "GSM712274", "GSM712275", "GSM712276", "GSM712277", "GSM712278", "GSM712279", "GSM712280", "GSM712281", "GSM712282", "GSM712283", "GSM712284", "GSM712285", "GSM712286", "GSM712287", "GSM712288", "GSM712289", "GSM712290", "GSM712291", "GSM712292", "GSM712293", "GSM712294", "GSM712295", "GSM712296", "GSM712297", "GSM712298", "GSM712299", "GSM712300", "GSM712301", "GSM712398", "GSM712399", "GSM712400", "GSM712401", "GSM712402", "GSM712403", "GSM712404", "GSM712405", "GSM712406", "GSM712407", "GSM712408", "GSM712409", "GSM712410", "GSM712411", "GSM712412", "GSM712413", "GSM712414", "GSM712415", "GSM712416", "GSM712417", "GSM712418", "GSM712419", "GSM712420", "GSM712421", "GSM712422", "GSM712423", "GSM712424", "GSM712425", "GSM712426", "GSM712427", "GSM712428", "GSM712429", "GSM712430", "GSM712431", "GSM712432", "GSM712433", "GSM712434", "GSM712435", "GSM712436", "GSM712437", "GSM712438", "GSM712439", "GSM712440", "GSM712441", "GSM712442", "GSM712443", "GSM712444", "GSM712445", "GSM712446", "GSM712447", "GSM712448", "GSM712449", "GSM712450", "GSM712451", "GSM712452", "GSM712453", "GSM712454", "GSM712455", "GSM712456", "GSM712457", "GSM712458", "GSM712459", "GSM712460", "GSM712461", "GSM712462", "GSM712463", "GSM712464", "GSM712465", "GSM712466", "GSM712467", "GSM712468", "GSM712469", "GSM712470", "GSM712471", "GSM712472", "GSM712473", "GSM712474", "GSM712573", "GSM712574", "GSM712575", "GSM712576", "GSM712577", "GSM712578", "GSM712579", "GSM712580", "GSM712581", "GSM712582", "GSM712583", "GSM712584", "GSM712585", "GSM712586", "GSM712587", "GSM712588", "GSM712589", "GSM712590", "GSM712591", "GSM712592", "GSM712593", "GSM712594", "GSM712595", "GSM712596", "GSM712597", "GSM712598", "GSM712599", "GSM712600", "GSM712601", "GSM712602", "GSM712603", "GSM712604", "GSM712605", "GSM712606", "GSM712607", "GSM712608", "GSM712609", "GSM712610", "GSM712611", "GSM712612", "GSM712613", "GSM712614", "GSM712615", "GSM712616", "GSM712617", "GSM712618", "GSM712619", "GSM712620", "GSM712621", "GSM712622", "GSM712623", "GSM712624", "GSM712625", "GSM712626", "GSM712627", "GSM712628", "GSM712629", "GSM712630", "GSM712631", "GSM712632", "GSM712633", "GSM712634", "GSM712635", "GSM712636", "GSM712637", "GSM712638", "GSM712639", "GSM712640", "GSM712641", "GSM712642", "GSM712643", "GSM712644", "GSM712645", "GSM712646", "GSM712647", "GSM712648", "GSM712649", "GSM714419", "GSM714420", "GSM714421", "GSM714422", "GSM714423", "GSM714424", "GSM714425", "GSM714426", "GSM714427", "GSM714428", "GSM714429", "GSM714430", "GSM714431"], "sample_count": 333, "group_sizes": null, "group_sizes_basis": null, "platform": "5175;11028", "taxon": "Homo sapiens", "title": "Exon level expression profiling of colorectal cancer tissue samples", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE39582", "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=GSE39582", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE39582", "version": null, "note": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1681353", "GSM1681354", "GSM1681355", "GSM1681356", "GSM1681357", "GSM1681358", "GSM1681359", "GSM1681360", "GSM1681361", "GSM1681362", "GSM1681363", "GSM1681364", "GSM1681365", "GSM1681366", "GSM1681367", "GSM1681368", "GSM1681369", "GSM1681370", "GSM1681371", "GSM971957", "GSM971958", "GSM971959", "GSM971960", "GSM971961", "GSM971962", "GSM971963", "GSM971964", "GSM971965", "GSM971966", "GSM971967", "GSM971968", "GSM971969", "GSM971970", "GSM971971", "GSM971972", "GSM971973", "GSM971974", "GSM971975", "GSM971976", "GSM971977", "GSM971978", "GSM971979", "GSM971980", "GSM971981", "GSM971982", "GSM971983", "GSM971984", "GSM971985", "GSM971986", "GSM971987", "GSM971988", "GSM971989", "GSM971990", "GSM971991", "GSM971992", "GSM971993", "GSM971994", "GSM971995", "GSM971996", "GSM971997", "GSM971998", "GSM971999", "GSM972000", "GSM972001", "GSM972002", "GSM972003", "GSM972004", "GSM972005", "GSM972006", "GSM972007", "GSM972008", "GSM972009", "GSM972010", "GSM972011", "GSM972012", "GSM972013", "GSM972014", "GSM972015", "GSM972016", "GSM972017", "GSM972018", "GSM972019", "GSM972020", "GSM972021", "GSM972022", "GSM972023", "GSM972024", "GSM972025", "GSM972026", "GSM972027", "GSM972028", "GSM972029", "GSM972030", "GSM972031", "GSM972032", "GSM972033", "GSM972034", "GSM972035", "GSM972036", "GSM972037", "GSM972038", "GSM972039", "GSM972040", "GSM972041", "GSM972042", "GSM972043", "GSM972044", "GSM972045", "GSM972046", "GSM972047", "GSM972048", "GSM972049", "GSM972050", "GSM972051", "GSM972052", "GSM972053", "GSM972054", "GSM972055", "GSM972056", "GSM972057", "GSM972058", "GSM972059", "GSM972060", "GSM972061", "GSM972062", "GSM972063", "GSM972064", "GSM972065", "GSM972066", "GSM972067", "GSM972068", "GSM972069", "GSM972070", "GSM972071", "GSM972072", "GSM972073", "GSM972074", "GSM972075", "GSM972076", "GSM972077", "GSM972078", "GSM972079", "GSM972080", "GSM972081", "GSM972082", "GSM972083", "GSM972084", "GSM972085", "GSM972086", "GSM972087", "GSM972088", "GSM972089", "GSM972090", "GSM972091", "GSM972092", "GSM972093", "GSM972094", "GSM972095", "GSM972096", "GSM972097", "GSM972098", "GSM972099", "GSM972100", "GSM972101", "GSM972102", "GSM972103", "GSM972104", "GSM972105", "GSM972106", "GSM972107", "GSM972108", "GSM972109", "GSM972110", "GSM972111", "GSM972112", "GSM972113", "GSM972114", "GSM972115", "GSM972116", "GSM972117", "GSM972118", "GSM972119", "GSM972120", "GSM972121", "GSM972122", "GSM972123", "GSM972124", "GSM972125", "GSM972126", "GSM972127", "GSM972128", "GSM972129", "GSM972130", "GSM972131", "GSM972132", "GSM972133", "GSM972134", "GSM972135", "GSM972136", "GSM972137", "GSM972138", "GSM972139", "GSM972140", "GSM972141", "GSM972142", "GSM972143", "GSM972144", "GSM972145", "GSM972146", "GSM972147", "GSM972148", "GSM972149", "GSM972150", "GSM972151", "GSM972152", "GSM972153", "GSM972154", "GSM972155", "GSM972156", "GSM972157", "GSM972158", "GSM972159", "GSM972160", "GSM972161", "GSM972162", "GSM972163", "GSM972164", "GSM972165", "GSM972166", "GSM972167", "GSM972168", "GSM972169", "GSM972170", "GSM972171", "GSM972172", "GSM972173", "GSM972174", "GSM972175", "GSM972176", "GSM972177", "GSM972178", "GSM972179", "GSM972180", "GSM972181", "GSM972182", "GSM972183", "GSM972184", "GSM972185", "GSM972186", "GSM972187", "GSM972188", "GSM972189", "GSM972190", "GSM972191", "GSM972192", "GSM972193", "GSM972194", "GSM972195", "GSM972196", "GSM972197", "GSM972198", "GSM972199", "GSM972200", "GSM972201", "GSM972202", "GSM972203", "GSM972204", "GSM972205", "GSM972206", "GSM972207", "GSM972208", "GSM972209", "GSM972210", "GSM972211", "GSM972212", "GSM972213", "GSM972214", "GSM972215", "GSM972216", "GSM972217", "GSM972218", "GSM972219", "GSM972220", "GSM972221", "GSM972222", "GSM972223", "GSM972224", "GSM972225", "GSM972226", "GSM972227", "GSM972228", "GSM972229", "GSM972230", "GSM972231", "GSM972232", "GSM972233", "GSM972234", "GSM972235", "GSM972236", "GSM972237", "GSM972238", "GSM972239", "GSM972240", "GSM972241", "GSM972242", "GSM972243", "GSM972244", "GSM972245", "GSM972246", "GSM972247", "GSM972248", "GSM972249", "GSM972250", "GSM972251", "GSM972252", "GSM972253", "GSM972254", "GSM972255", "GSM972256", "GSM972257", "GSM972258", "GSM972259", "GSM972260", "GSM972261", "GSM972262", "GSM972263", "GSM972264", "GSM972265", "GSM972266", "GSM972267", "GSM972268", "GSM972269", "GSM972270", "GSM972271", "GSM972272", "GSM972273", "GSM972274", "GSM972275", "GSM972276", "GSM972277", "GSM972278", "GSM972279", "GSM972280", "GSM972281", "GSM972282", "GSM972283", "GSM972284", "GSM972285", "GSM972286", "GSM972287", "GSM972288", "GSM972289", "GSM972290", "GSM972291", "GSM972292", "GSM972293", "GSM972294", "GSM972295", "GSM972296", "GSM972297", "GSM972298", "GSM972299", "GSM972300", "GSM972301", "GSM972302", "GSM972303", "GSM972304", "GSM972305", "GSM972306", "GSM972307", "GSM972308", "GSM972309", "GSM972310", "GSM972311", "GSM972312", "GSM972313", "GSM972314", "GSM972315", "GSM972316", "GSM972317", "GSM972318", "GSM972319", "GSM972320", "GSM972321", "GSM972322", "GSM972323", "GSM972324", "GSM972325", "GSM972326", "GSM972327", "GSM972328", "GSM972329", "GSM972330", "GSM972331", "GSM972332", "GSM972333", "GSM972334", "GSM972335", "GSM972336", "GSM972337", "GSM972338", "GSM972339", "GSM972340", "GSM972341", "GSM972342", "GSM972343", "GSM972344", "GSM972345", "GSM972346", "GSM972347", "GSM972348", "GSM972349", "GSM972350", "GSM972351", "GSM972352", "GSM972353", "GSM972354", "GSM972355", "GSM972356", "GSM972357", "GSM972358", "GSM972359", "GSM972360", "GSM972361", "GSM972362", "GSM972363", "GSM972364", "GSM972365", "GSM972366", "GSM972367", "GSM972368", "GSM972369", "GSM972370", "GSM972371", "GSM972372", "GSM972373", "GSM972374", "GSM972375", "GSM972376", "GSM972377", "GSM972378", "GSM972379", "GSM972380", "GSM972381", "GSM972382", "GSM972383", "GSM972384", "GSM972385", "GSM972386", "GSM972387", "GSM972388", "GSM972389", "GSM972390", "GSM972391", "GSM972392", "GSM972393", "GSM972394", "GSM972395", "GSM972396", "GSM972397", "GSM972398", "GSM972399", "GSM972400", "GSM972401", "GSM972402", "GSM972403", "GSM972404", "GSM972405", "GSM972406", "GSM972407", "GSM972408", "GSM972409", "GSM972410", "GSM972411", "GSM972412", "GSM972413", "GSM972414", "GSM972415", "GSM972416", "GSM972417", "GSM972418", "GSM972419", "GSM972420", "GSM972421", "GSM972422", "GSM972423", "GSM972424", "GSM972425", "GSM972426", "GSM972427", "GSM972428", "GSM972429", "GSM972430", "GSM972431", "GSM972432", "GSM972433", "GSM972434", "GSM972435", "GSM972436", "GSM972437", "GSM972438", "GSM972439", "GSM972440", "GSM972441", "GSM972442", "GSM972443", "GSM972444", "GSM972445", "GSM972446", "GSM972447", "GSM972448", "GSM972449", "GSM972450", "GSM972451", "GSM972452", "GSM972453", "GSM972454", "GSM972455", "GSM972456", "GSM972457", "GSM972458", "GSM972459", "GSM972460", "GSM972461", "GSM972462", "GSM972463", "GSM972464", "GSM972465", "GSM972466", "GSM972467", "GSM972468", "GSM972469", "GSM972470", "GSM972471", "GSM972472", "GSM972473", "GSM972474", "GSM972475", "GSM972476", "GSM972477", "GSM972478", "GSM972479", "GSM972480", "GSM972481", "GSM972482", "GSM972483", "GSM972484", "GSM972485", "GSM972486", "GSM972487", "GSM972488", "GSM972489", "GSM972490", "GSM972491", "GSM972492", "GSM972493", "GSM972494", "GSM972495", "GSM972496", "GSM972497", "GSM972498", "GSM972499", "GSM972500", "GSM972501", "GSM972502", "GSM972503", "GSM972504", "GSM972505", "GSM972506", "GSM972507", "GSM972508", "GSM972509", "GSM972510", "GSM972511", "GSM972512", "GSM972513", "GSM972514", "GSM972515", "GSM972516", "GSM972517", "GSM972518", "GSM972519", "GSM972520", "GSM972521", "GSM972522"], "sample_count": 585, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33116619:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:227d61ab934aebf930aaa9489a3b8f5cd1466a8f926bd65e00de0ae47bccab5b", "bytes": 1131, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[1]#t0001", "version": null, "note": "Clinical Information Statistics", "structure": {"pmcid": "PMC7569059", "section_index": 14, "section_title": "Preprocessing Data Statistics", "row_count": 25, "column_count": 6}, "table": {"label": "Table 1", "caption": "Clinical Information Statistics", "rows": [["Characteristics", "TCGA Training Datasets (n=226)", "TCGA Test Datasets (n=227)", "p value", "GSE17538 (n=238)"], ["Age (years)", "≤50", "31", "29", "0.875", "32"], [">50", "195", "198", "206"], ["Survival times (years)", "Median", "1.81", "1.97", "–", "2.38"], ["Mean", "2.25", "2.44", "3.12"], ["Survival status", "Living", "178", "176", "0.839", "145"], ["Dead", "48", "51", "55"], ["Gender", "Female", "104", "109", "0.739", "114"], ["Male", "122", "118", "124"], ["Lymphatic invasion", "NO", "125", "128", "0.695", "–"], ["YES", "81", "75", "–"], ["pathologic_T", "T1", "6", "5", "0.769", "–"], ["T2", "35", "43", "–"], ["T3", "157", "153", "–"], ["T4", "28", "25", "–"], ["pathologic_N", "N0", "127", "139", "0.454", "–"], ["N1", "54", "52", "–"], ["N2", "45", "36", "–"], ["N3", "0", "0", "–"], ["pathologic_M", "M0", "165", "168", "0.956", "–"], ["M1/MX", "57", "56", "–"], ["AJCC stage", "Stage Ⅰ", "34", "42", "0.332", "28"], ["Stage Ⅱ", "82", "92", "72"], ["Stage III", "73", "57", "76"], ["Stage Ⅳ", "30", "32", "56"]], "row_count": 25, "column_count": 6, "numeric_cells": 73, "header_rows": 1, "locator": "section[14]/table-wrap[1]#t0001"}}, {"id": "asset:table:pmid:33116619:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:e2121ce1abf78a1b31ce39dc7176d7620c469da298df71946eaf77c63dad14e5", "bytes": 1526, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[2]#t0002", "version": null, "note": "Information on Top20 Prognosis-Related Genes", "structure": {"pmcid": "PMC7569059", "section_index": 14, "section_title": "Preprocessing Data Statistics", "row_count": 21, "column_count": 6}, "table": {"label": "Table 2", "caption": "Information on Top20 Prognosis-Related Genes", "rows": [["ENGSID", "Genesymbol", "HR", "Coefficient", "z score", "p value"], ["ENSG00000241697", "TMEFF1", "1.552", "0.440", "4.737", "2.17E-06"], ["ENSG00000160117", "ANKLE1", "1.525", "0.422", "4.691", "2.72E-06"], ["ENSG00000214128", "TMEM213", "1.427", "0.355", "4.559", "5.13E-06"], ["ENSG00000090932", "DLL3", "1.622", "0.483", "4.528", "5.95E-06"], ["ENSG00000268940", "CT45A1", "1.361", "0.308", "4.522", "6.11E-06"], ["ENSG00000159556", "ISL2", "1.528", "0.424", "4.502", "6.72E-06"], ["ENSG00000205456", "TP53TG3D", "1.474", "0.388", "4.407", "1.05E-05"], ["ENSG00000100156", "SLC16A8", "1.473", "0.387", "4.381", "1.18E-05"], ["ENSG00000182759", "MAFA", "1.471", "0.386", "4.321", "1.56E-05"], ["ENSG00000106689", "LHX2", "1.472", "0.387", "4.284", "1.84E-05"], ["ENSG00000148331", "ASB6", "2.035", "0.711", "4.275", "1.91E-05"], ["ENSG00000269437", "NXF2B", "1.425", "0.354", "4.269", "1.96E-05"], ["ENSG00000124260", "MAGEA10", "1.366", "0.312", "4.262", "2.02E-05"], ["ENSG00000126890", "CTAG2", "1.346", "0.297", "4.210", "2.56E-05"], ["ENSG00000184029", "DSCR4", "1.414", "0.347", "4.172", "3.02E-05"], ["ENSG00000187730", "GABRD", "1.480", "0.392", "4.153", "3.29E-05"], ["ENSG00000149927", "DOC2A", "1.600", "0.470", "4.127", "3.68E-05"], ["ENSG00000075043", "KCNQ2", "1.428", "0.356", "4.126", "3.69E-05"], ["ENSG00000110148", "CCKBR", "1.404", "0.339", "4.113", "3.91E-05"], ["ENSG00000121905", "HPCA", "1.492", "0.400", "4.107", "4.01E-05"]], "row_count": 21, "column_count": 6, "numeric_cells": 105, "header_rows": 1, "locator": "section[14]/table-wrap[2]#t0002"}}, {"id": "asset:table:pmid:33116619:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:ef8bfd1df3bf245a1d4a6b1b757b8b8219e7f9a3739c362a06ec36256a2ecfc0", "bytes": 1006, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[18]/table-wrap[1]#t0003", "version": null, "note": "9- Genes Significantly Associated with the Overall Survival in the Training Dataset", "structure": {"pmcid": "PMC7569059", "section_index": 18, "section_title": "Establishing 9-Gene Signature to Divide Samples in TCGA Training Cohort", "row_count": 10, "column_count": 7}, "table": {"label": "Table 3", "caption": "9- Genes Significantly Associated with the Overall Survival in the Training Dataset", "rows": [["Ensembl Gene ID", "Symbol", "HR", "Z-score", "P value", "Importance", "Relative Importance"], ["ENSG00000170178", "HOXD12", "1.30", "2.349091", "1.88E-02", "0.0096", "1"], ["ENSG00000163481", "RNF25", "1.52", "2.540626", "1.11E-02", "0.0094", "0.9848"], ["ENSG00000139899", "CBLN3", "1.39", "2.249482", "2.45E-02", "0.0088", "0.9242"], ["ENSG00000088538", "DOCK3", "1.52", "3.782743", "1.55E-04", "0.0078", "0.8182"], ["ENSG00000044115", "CTNNA1", "0.73", "−2.399278", "1.64E-02", "0.0064", "0.6667"], ["ENSG00000152894", "PTPRK", "0.71", "−2.371469", "1.77E-02", "0.0049", "0.5152"], ["ENSG00000187726", "DNAJB13", "1.28", "2.639895", "8.29E-03", "0.0046", "0.4848"], ["ENSG00000171428", "NAT1", "0.70", "−2.402113", "1.63E-02", "0.0045", "0.4697"], ["ENSG00000163348", "PYGO2", "1.47", "2.390166", "1.68E-02", "0.0032", "0.3333"]], "row_count": 10, "column_count": 7, "numeric_cells": 57, "header_rows": 1, "locator": "section[18]/table-wrap[1]#t0003"}}, {"id": "asset:table:pmid:33116619:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:b2775da1979b3501a0a73063906b2ee59aeaf4428d381a68155e466c97023a4e", "bytes": 1688, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[21]/table-wrap[1]#t0004", "version": null, "note": "Univariate and Multivariate Cox Regression Analyses", "structure": {"pmcid": "PMC7569059", "section_index": 21, "section_title": "Univariate and Multivariate Cox Regression Analysis", "row_count": 23, "column_count": 7}, "table": {"label": "Table 4", "caption": "Univariate and Multivariate Cox Regression Analyses", "rows": [["Variables", "Univariate Analysis", "Multivariable Analysis"], ["HR", "95% CI of HR", "P value", "HR", "95% CI of HR", "P value"], ["TCGA training datasets"], ["9-gene risk score"], ["Low-risk score", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["High-risk score", "3.97", "2.04–7.73", "4.9E-05", "3.05", "1.36–6.84", "0.007"], ["Age(≤50/>50)", "1.02", "0.99–1.05", "6.0E-02", "1.04", "1.00–1.07", "0.016"], ["Gender female", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["Gender male", "1.05", "0.59–1.86", "0.87", "0.66", "0.31–1.37", "0.265"], ["Lymphatic Invasion NO", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["Lymphatic Invasion YES", "2.58", "1.35–4.91", "0.00", "1.94", "0.66–5.68", "0.227"], ["Pathologic T 1/ T 2", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["Pathologic T 3", "1.55", "0.54–4.43", "0.412", "0.15", "0.01–1.34", "0.091"], ["Pathologic T 4", "5.15", "1.66–16", "0.005", "0.43", "0.04–4.13", "0.461"], ["Pathologic N 0", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["Pathologic N 1", "1.38", "0.63–2.96", "0.413", "0.24", "0.04–1.56", "0.136"], ["Pathologic N 2", "3.00", "1.58–5.66", "0.001", "0.49", "0.07–3.21", "0.456"], ["Pathologic M 0", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["Pathologic M 1", "4.52", "2.33–8.73", "7.42E-06", "2.28", "0.89–5.79", "0.080"], ["Pathologic M X", "1.82", "0.77–4.26", "0.168", "1.56", "0.50–4.84", "0.440"], ["AJCC Stage Ⅰ", "1 (Ref)", "", "", "1 (Ref)", "", ""], ["AJCC Stage Ⅱ", "1.94", "0.43–8.65", "0.3854", "13.42", "0.68–262.17", "0.087"], ["AJCC Stage III/Ⅳ", "4.28", "1.01–17.98", "0.047", "37.58", "1.42–990.93", "0.030"]], "row_count": 23, "column_count": 7, "numeric_cells": 98, "header_rows": 2, "locator": "section[21]/table-wrap[1]#t0004"}}, {"id": "asset:table:pmid:33116619:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:e70f1e000edfa96c6ca12d108db3d9f1dfd4d130ab162cc9e72a325f14e2f926", "bytes": 2458, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[22]/table-wrap[1]#t0005", "version": null, "note": "GSEA Analysis of 9-Gene Signature", "structure": {"pmcid": "PMC7569059", "section_index": 22, "section_title": "Analysis of Pathways Enriched in High-Risk and Low-Risk Groups Using GSEA", "row_count": 30, "column_count": 6}, "table": {"label": "Table 5", "caption": "GSEA Analysis of 9-Gene Signature", "rows": [["Name", "SIZE", "ES", "NES", "NOM p-val", "FDR q-val"], ["KEGG_O_GLYCAN_BIOSYNTHESIS", "26", "−0.650", "−1.907", "0.000", "0.355"], ["KEGG_UBIQUITIN_MEDIATED_PROTEOLYSIS", "133", "−0.502", "−1.882", "0.006", "0.245"], ["KEGG_ERBB_SIGNALING_PATHWAY", "87", "−0.455", "−1.772", "0.008", "0.494"], ["KEGG_ENDOMETRIAL_CANCER", "52", "−0.493", "−1.716", "0.008", "0.586"], ["KEGG_OOCYTE_MEIOSIS", "110", "−0.455", "−1.716", "0.008", "0.471"], ["KEGG_THYROID_CANCER", "29", "−0.511", "−1.709", "0.006", "0.415"], ["KEGG_COLORECTAL_CANCER", "62", "−0.470", "−1.701", "0.012", "0.377"], ["KEGG_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION", "44", "−0.584", "−1.690", "0.056", "0.356"], ["KEGG_PROSTATE_CANCER", "89", "−0.445", "−1.689", "0.019", "0.321"], ["KEGG_APOPTOSIS", "86", "−0.438", "−1.680", "0.021", "0.312"], ["KEGG_INSULIN_SIGNALING_PATHWAY", "136", "−0.393", "−1.675", "0.010", "0.292"], ["KEGG_BASAL_TRANSCRIPTION_FACTORS", "34", "−0.546", "−1.657", "0.025", "0.306"], ["KEGG_RENAL_CELL_CARCINOMA", "70", "−0.448", "−1.602", "0.037", "0.413"], ["KEGG_ADHERENS_JUNCTION", "73", "−0.455", "−1.596", "0.046", "0.400"], ["KEGG_DORSO_VENTRAL_AXIS_FORMATION", "24", "−0.511", "−1.585", "0.035", "0.398"], ["KEGG_NEUROTROPHIN_SIGNALING_PATHWAY", "125", "−0.399", "−1.585", "0.040", "0.374"], ["KEGG_RENIN_ANGIOTENSIN_SYSTEM", "17", "−0.527", "−1.583", "0.035", "0.356"], ["KEGG_ENDOCYTOSIS", "177", "−0.379", "−1.570", "0.042", "0.365"], ["KEGG_PEROXISOME", "78", "−0.470", "−1.568", "0.063", "0.351"], ["KEGG_AMINO_SUGAR_AND_NUCLEOTIDE_SUGAR_METABOLISM", "44", "−0.451", "−1.550", "0.054", "0.373"], ["KEGG_PROPANOATE_METABOLISM", "32", "−0.525", "−1.544", "0.064", "0.370"], ["KEGG_LONG_TERM_POTENTIATION", "68", "−0.402", "−1.534", "0.023", "0.375"], ["KEGG_FATTY_ACID_METABOLISM", "41", "−0.484", "−1.533", "0.100", "0.360"], ["KEGG_STARCH_AND_SUCROSE_METABOLISM", "50", "−0.441", "−1.517", "0.056", "0.380"], ["KEGG_CHRONIC_MYELOID_LEUKEMIA", "73", "−0.417", "−1.507", "0.086", "0.387"], ["KEGG_P53_SIGNALING_PATHWAY", "66", "−0.420", "−1.502", "0.056", "0.383"], ["KEGG_BIOSYNTHESIS_OF_UNSATURATED_FATTY_ACIDS", "20", "−0.506", "−1.496", "0.069", "0.383"], ["KEGG_TGF_BETA_SIGNALING_PATHWAY", "85", "−0.399", "−1.493", "0.059", "0.374"], ["KEGG_NICOTINATE_AND_NICOTINAMIDE_METABOLISM", "22", "−0.423", "−1.467", "0.0391", "0.4133"]], "row_count": 30, "column_count": 6, "numeric_cells": 146, "header_rows": 1, "locator": "section[22]/table-wrap[1]#t0005"}}], "gaps": ["asset:data:geo:GSE17538 not downloaded", "asset:data:geo:GSE17538 licence not read", "asset:data:geo:GSE19234 not downloaded", "asset:data:geo:GSE19234 licence not read", "asset:data:geo:GSE24551 not downloaded", "asset:data:geo:GSE24551 licence not read", "asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-4", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-5", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.8, "band": "high", "quote": "ROC curve"}}, {"id": "method-6", "family": null, "specific": null, "label": "Random survival forest algorithm", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "reordered", "quote": "“The importance of prognostic genes is sequenced using R package random survival forest.”"}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"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": {"tier": "R1", "reachable": true, "accessions": ["GSE17538", "GSE39582", "GSE24551", "GSE19234"], "resolved_accessions": ["GSE17538", "GSE39582", "GSE24551", "GSE19234"], "statements": ["Level-3 RNA-sequencing data, the clinicopathological、 SNP 、 copy number segments and survival data of patients with COAD were downloaded from the UCSC Xena browser (https://xenabrowser.net/)."], "basis": "The paper names GSE17538, GSE39582, GSE24551, GSE19234 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:33116619", "data:geo:GSE17538", "asset:table:pmid:33116619:1", "asset:table:pmid:33116619:2", "asset:table:pmid:33116619:3", "asset:table:pmid:33116619:4", "asset:table:pmid:33116619:5"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE17538"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:23:38Z", "independence": "single_reader"}, "evidence_check": {"method": "reordered", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 29966, "completion_tokens": 1648, "cached_tokens": 784}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:33116619", "type": "paper", "label": "pmid:33116619"}, {"id": "source:pmid:33116619", "type": "manuscript", "label": "PMID 33116619 full text"}, {"id": "data:geo:GSE17538", "type": "dataset", "label": "GEO GSE17538"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33116619", "type": "paper", "label": "pmid:33116619"}, {"id": "source:pmid:33116619", "type": "manuscript", "label": "PMID 33116619 full text"}, {"id": "data:geo:GSE17538", "type": "dataset", "label": "GEO GSE17538"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33116619", "type": "extraction", "used": ["source:pmid:33116619"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE17538", "type": "accession_resolution", "used": ["data:geo:GSE17538"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:33116619", "parent_hash": "sha256:71c5c529ae821094dc1b93bf789f932f2a2b506607e80043247d49faeecac7a8", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE17538 licence not read", "asset:data:geo:GSE17538 not downloaded", "asset:data:geo:GSE19234 licence not read", "asset:data:geo:GSE19234 not downloaded", "asset:data:geo:GSE24551 licence not read", "asset:data:geo:GSE24551 not downloaded", "asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes", "nd external verification set. The results of qPCR based on clinical samples showed that the ex"], "order_basis": "paper_text_order:815", "id": "assay:1"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}