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pmid:35966318

Novel hypoxia features with appealing implications in discriminating the prognosis, immune escape and drug responses of 947 hepatocellular carcinoma patients.

Mingyuan Luan · Hongzong Si

Translational cancer research · 2022 doi:10.21037/tcr-22-253

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

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pmid:35966318
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title
Novel hypoxia features with appealing implications in discriminating the prognosis, immune escape and drug responses of 947 hepatocellular carcinoma patients.
doi
10.21037/tcr-22-253
pmid
35966318
authors array · 2 items
[0]
Mingyuan Luan
[1]
Hongzong Si
journal
Translational cancer research
year
2022
abstract
Background: Hypoxia has a profound impact on the development and progression of hepatocellular carcinoma (HCC). This study aimed to explore and elucidate how hypoxia affect prognosis, immune escape and drug responses in HCC. Methods: HCC-specific hypoxia signatures were identified based on the intersect of differentially expressed genes (DEGs) of GSE41666 and GSE15366. The hypoxia score was calculated using the gene set variation analysis (GSVA) function and validated on GSE18494. We collected five cohorts [The Cancer Genome Atlas (TCGA), GSE14520, GSE39791, GSE36376, GSE57957] for further analysis. First, we analyzed the effect of the hypoxia score on prognosis. Next, we systematically analyzed the potential hypoxia-related immune escape mechanisms and the effect of hypoxia upon immunotherapy. Then, we predicted and screened potential sensitive drugs for HCC patients with high hypoxia levels using machine learning and docking. Results: We constructed a novel HCC-specific hypoxia score and undertook further analysis in five cohorts (TCGA, GSE14520, GSE39791, GSE36376, GSE57957). We observed that patients with high hypoxia scores exhibited worse overall survival (OS) in TCGA and GSE14520. We also constructed a hypoxia-related nomogram that had good performance in predicting HCC patients' prognosis. Furthermore, patients with lower hypoxia scores had a lower risk of immune escape and thus may benefit from immunotherapy. Finally, we predicted and screened VLX600 as the candidate drug for HCC patients with high hypoxia scores. We further explored and elucidated why VLX600 was more sensitive in HCC patients with high hypoxia than with low hypoxia HCC patients using weighted gene co-expression network analysis (WGCNA). Conclusions: This study provides further evidence of the link between hypoxia and prognosis and immune escape in HCC patients. Moreover, our research screened VLX600 as a potential drug for HCC patients with high hypoxia levels and elucidated the potential mechanism.
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For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test.
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sections[9] "Statistical analysis" paragraph 2
quote
For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test.
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TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
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sections[3] "HCC data sets downloading and preprocessing" paragraph 2
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TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
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The study constructed a novel HCC-specific hypoxia score that was associated with prognosis and immune escape and identified VLX600 as a potential drug for HCC patients with high hypoxia levels.
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sections[0] "Abstract" paragraph 3
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We constructed a novel HCC-specific hypoxia score and undertook further analysis in five cohorts (TCGA, GSE14520, GSE39791, GSE36376, GSE57957).
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The study constructed a novel HCC-specific hypoxia score that was associated with prognosis and immune escape and identified VLX600 as a potential drug for HCC patients with high hypoxia levels.
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GSM363449
[475]
GSM363450
[476]
GSM363451
[477]
GSM712532
[478]
GSM712533
[479]
GSM712534
[480]
GSM712535
[481]
GSM712536
[482]
GSM712537
[483]
GSM712538
[484]
GSM712539
[485]
GSM712540
[486]
GSM712541
[487]
GSM712542
sample_count
488
group_sizes
null
group_sizes_basis
null
platform
3921;571
taxon
Homo sapiens
title
Gene expression data of human hepatocellular carcinoma (HCC)
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:GSE15366
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=GSE15366
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE15366
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 4 items
[0]
GSM385703
[1]
GSM385704
[2]
GSM385705
[3]
GSM385706
sample_count
4
group_sizes
null
group_sizes_basis
null
platform
6480
taxon
Homo sapiens
title
Chronic Hypoxia predicts Poor Prognosis in Hepatocellular Carcinoma
resolution_checked_at
2026-11-01T18:06:43Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE18494
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=GSE18494
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE18494
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 36 items
[0]
GSM460669
[1]
GSM460670
[2]
GSM460671
[3]
GSM460672
[4]
GSM460673
[5]
GSM460674
[6]
GSM460675
[7]
GSM460676
[8]
GSM460677
[9]
GSM460678
[10]
GSM460679
[11]
GSM460680
[12]
GSM460681
[13]
GSM460682
[14]
GSM460683
[15]
GSM460684
[16]
GSM460685
[17]
GSM460686
[18]
GSM460687
[19]
GSM460688
[20]
GSM460689
[21]
GSM460690
[22]
GSM460691
[23]
GSM460692
[24]
GSM460693
[25]
GSM460694
[26]
GSM460695
[27]
GSM460696
[28]
GSM460697
[29]
GSM460698
[30]
GSM460699
[31]
GSM460700
[32]
GSM460701
[33]
GSM460702
[34]
GSM460703
[35]
GSM460704
sample_count
36
group_sizes
null
group_sizes_basis
null
platform
9419
taxon
Homo sapiens
title
Expression profiling of hypoxic HepG2 hepatoma, U87 glioma, and MDA-MB231 breast cancer cells: time course
resolution_checked_at
2026-11-01T18:06:43Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE36376
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=GSE36376
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE36376
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 433 items
[0]
GSM890128
[1]
GSM890129
[2]
GSM890130
[3]
GSM890131
[4]
GSM890132
[5]
GSM890133
[6]
GSM890134
[7]
GSM890135
[8]
GSM890136
[9]
GSM890137
[10]
GSM890138
[11]
GSM890139
[12]
GSM890140
[13]
GSM890141
[14]
GSM890142
[15]
GSM890143
[16]
GSM890144
[17]
GSM890145
[18]
GSM890146
[19]
GSM890147
[20]
GSM890148
[21]
GSM890149
[22]
GSM890150
[23]
GSM890151
[24]
GSM890152
[25]
GSM890153
[26]
GSM890154
[27]
GSM890155
[28]
GSM890156
[29]
GSM890157
[30]
GSM890158
[31]
GSM890159
[32]
GSM890160
[33]
GSM890161
[34]
GSM890162
[35]
GSM890163
[36]
GSM890164
[37]
GSM890165
[38]
GSM890166
[39]
GSM890167
[40]
GSM890168
[41]
GSM890169
[42]
GSM890170
[43]
GSM890171
[44]
GSM890172
[45]
GSM890173
[46]
GSM890174
[47]
GSM890175
[48]
GSM890176
[49]
GSM890177
[50]
GSM890178
[51]
GSM890179
[52]
GSM890180
[53]
GSM890181
[54]
GSM890182
[55]
GSM890183
[56]
GSM890184
[57]
GSM890185
[58]
GSM890186
[59]
GSM890187
[60]
GSM890188
[61]
GSM890189
[62]
GSM890190
[63]
GSM890191
[64]
GSM890192
[65]
GSM890193
[66]
GSM890194
[67]
GSM890195
[68]
GSM890196
[69]
GSM890197
[70]
GSM890198
[71]
GSM890199
[72]
GSM890200
[73]
GSM890201
[74]
GSM890202
[75]
GSM890203
[76]
GSM890204
[77]
GSM890205
[78]
GSM890206
[79]
GSM890207
[80]
GSM890208
[81]
GSM890209
[82]
GSM890210
[83]
GSM890211
[84]
GSM890212
[85]
GSM890213
[86]
GSM890214
[87]
GSM890215
[88]
GSM890216
[89]
GSM890217
[90]
GSM890218
[91]
GSM890219
[92]
GSM890220
[93]
GSM890221
[94]
GSM890222
[95]
GSM890223
[96]
GSM890224
[97]
GSM890225
[98]
GSM890226
[99]
GSM890227
[100]
GSM890228
[101]
GSM890229
[102]
GSM890230
[103]
GSM890231
[104]
GSM890232
[105]
GSM890233
[106]
GSM890234
[107]
GSM890235
[108]
GSM890236
[109]
GSM890237
[110]
GSM890238
[111]
GSM890239
[112]
GSM890240
[113]
GSM890241
[114]
GSM890242
[115]
GSM890243
[116]
GSM890244
[117]
GSM890245
[118]
GSM890246
[119]
GSM890247
[120]
GSM890248
[121]
GSM890249
[122]
GSM890250
[123]
GSM890251
[124]
GSM890252
[125]
GSM890253
[126]
GSM890254
[127]
GSM890255
[128]
GSM890256
[129]
GSM890257
[130]
GSM890258
[131]
GSM890259
[132]
GSM890260
[133]
GSM890261
[134]
GSM890262
[135]
GSM890263
[136]
GSM890264
[137]
GSM890265
[138]
GSM890266
[139]
GSM890267
[140]
GSM890268
[141]
GSM890269
[142]
GSM890270
[143]
GSM890271
[144]
GSM890272
[145]
GSM890273
[146]
GSM890274
[147]
GSM890275
[148]
GSM890276
[149]
GSM890277
[150]
GSM890278
[151]
GSM890279
[152]
GSM890280
[153]
GSM890281
[154]
GSM890282
[155]
GSM890283
[156]
GSM890284
[157]
GSM890285
[158]
GSM890286
[159]
GSM890287
[160]
GSM890288
[161]
GSM890289
[162]
GSM890290
[163]
GSM890291
[164]
GSM890292
[165]
GSM890293
[166]
GSM890294
[167]
GSM890295
[168]
GSM890296
[169]
GSM890297
[170]
GSM890298
[171]
GSM890299
[172]
GSM890300
[173]
GSM890301
[174]
GSM890302
[175]
GSM890303
[176]
GSM890304
[177]
GSM890305
[178]
GSM890306
[179]
GSM890307
[180]
GSM890308
[181]
GSM890309
[182]
GSM890310
[183]
GSM890311
[184]
GSM890312
[185]
GSM890313
[186]
GSM890314
[187]
GSM890315
[188]
GSM890316
[189]
GSM890317
[190]
GSM890318
[191]
GSM890319
[192]
GSM890320
[193]
GSM890321
[194]
GSM890322
[195]
GSM890323
[196]
GSM890324
[197]
GSM890325
[198]
GSM890326
[199]
GSM890327
[200]
GSM890328
[201]
GSM890329
[202]
GSM890330
[203]
GSM890331
[204]
GSM890332
[205]
GSM890333
[206]
GSM890334
[207]
GSM890335
[208]
GSM890336
[209]
GSM890337
[210]
GSM890338
[211]
GSM890339
[212]
GSM890340
[213]
GSM890341
[214]
GSM890342
[215]
GSM890343
[216]
GSM890344
[217]
GSM890345
[218]
GSM890346
[219]
GSM890347
[220]
GSM890348
[221]
GSM890349
[222]
GSM890350
[223]
GSM890351
[224]
GSM890352
[225]
GSM890353
[226]
GSM890354
[227]
GSM890355
[228]
GSM890356
[229]
GSM890357
[230]
GSM890358
[231]
GSM890359
[232]
GSM890360
[233]
GSM890361
[234]
GSM890362
[235]
GSM890363
[236]
GSM890364
[237]
GSM890365
[238]
GSM890366
[239]
GSM890367
[240]
GSM890368
[241]
GSM890369
[242]
GSM890370
[243]
GSM890371
[244]
GSM890372
[245]
GSM890373
[246]
GSM890374
[247]
GSM890375
[248]
GSM890376
[249]
GSM890377
[250]
GSM890378
[251]
GSM890379
[252]
GSM890380
[253]
GSM890381
[254]
GSM890382
[255]
GSM890383
[256]
GSM890384
[257]
GSM890385
[258]
GSM890386
[259]
GSM890387
[260]
GSM890388
[261]
GSM890389
[262]
GSM890390
[263]
GSM890391
[264]
GSM890392
[265]
GSM890393
[266]
GSM890394
[267]
GSM890395
[268]
GSM890396
[269]
GSM890397
[270]
GSM890398
[271]
GSM890399
[272]
GSM890400
[273]
GSM890401
[274]
GSM890402
[275]
GSM890403
[276]
GSM890404
[277]
GSM890405
[278]
GSM890406
[279]
GSM890407
[280]
GSM890408
[281]
GSM890409
[282]
GSM890410
[283]
GSM890411
[284]
GSM890412
[285]
GSM890413
[286]
GSM890414
[287]
GSM890415
[288]
GSM890416
[289]
GSM890417
[290]
GSM890418
[291]
GSM890419
[292]
GSM890420
[293]
GSM890421
[294]
GSM890422
[295]
GSM890423
[296]
GSM890424
[297]
GSM890425
[298]
GSM890426
[299]
GSM890427
[300]
GSM890428
[301]
GSM890429
[302]
GSM890430
[303]
GSM890431
[304]
GSM890432
[305]
GSM890433
[306]
GSM890434
[307]
GSM890435
[308]
GSM890436
[309]
GSM890437
[310]
GSM890438
[311]
GSM890439
[312]
GSM890440
[313]
GSM890441
[314]
GSM890442
[315]
GSM890443
[316]
GSM890444
[317]
GSM890445
[318]
GSM890446
[319]
GSM890447
[320]
GSM890448
[321]
GSM890449
[322]
GSM890450
[323]
GSM890451
[324]
GSM890452
[325]
GSM890453
[326]
GSM890454
[327]
GSM890455
[328]
GSM890456
[329]
GSM890457
[330]
GSM890458
[331]
GSM890459
[332]
GSM890460
[333]
GSM890461
[334]
GSM890462
[335]
GSM890463
[336]
GSM890464
[337]
GSM890465
[338]
GSM890466
[339]
GSM890467
[340]
GSM890468
[341]
GSM890469
[342]
GSM890470
[343]
GSM890471
[344]
GSM890472
[345]
GSM890473
[346]
GSM890474
[347]
GSM890475
[348]
GSM890476
[349]
GSM890477
[350]
GSM890478
[351]
GSM890479
[352]
GSM890480
[353]
GSM890481
[354]
GSM890482
[355]
GSM890483
[356]
GSM890484
[357]
GSM890485
[358]
GSM890486
[359]
GSM890487
[360]
GSM890488
[361]
GSM890489
[362]
GSM890490
[363]
GSM890491
[364]
GSM890492
[365]
GSM890493
[366]
GSM890494
[367]
GSM890495
[368]
GSM890496
[369]
GSM890497
[370]
GSM890498
[371]
GSM890499
[372]
GSM890500
[373]
GSM890501
[374]
GSM890502
[375]
GSM890503
[376]
GSM890504
[377]
GSM890505
[378]
GSM890506
[379]
GSM890507
[380]
GSM890508
[381]
GSM890509
[382]
GSM890510
[383]
GSM890511
[384]
GSM890512
[385]
GSM890513
[386]
GSM890514
[387]
GSM890515
[388]
GSM890516
[389]
GSM890517
[390]
GSM890518
[391]
GSM890519
[392]
GSM890520
[393]
GSM890521
[394]
GSM890522
[395]
GSM890523
[396]
GSM890524
[397]
GSM890525
[398]
GSM890526
[399]
GSM890527
[400]
GSM890528
[401]
GSM890529
[402]
GSM890530
[403]
GSM890531
[404]
GSM890532
[405]
GSM890533
[406]
GSM890534
[407]
GSM890535
[408]
GSM890536
[409]
GSM890537
[410]
GSM890538
[411]
GSM890539
[412]
GSM890540
[413]
GSM890541
[414]
GSM890542
[415]
GSM890543
[416]
GSM890544
[417]
GSM890545
[418]
GSM890546
[419]
GSM890547
[420]
GSM890548
[421]
GSM890549
[422]
GSM890550
[423]
GSM890551
[424]
GSM890552
[425]
GSM890553
[426]
GSM890554
[427]
GSM890555
[428]
GSM890556
[429]
GSM890557
[430]
GSM890558
[431]
GSM890559
[432]
GSM890560
sample_count
433
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Gene Expression Profiles of both tumor and adjacent non-tumor liver Identify Hepatocellular Carcinoma Patients at High Risk of Recurrence after Curative Hepatectomy
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 · 15 fields
id
data:geo:GSE39791
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=GSE39791
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE39791
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 144 items
[0]
GSM979051
[1]
GSM979052
[2]
GSM979053
[3]
GSM979054
[4]
GSM979055
[5]
GSM979056
[6]
GSM979057
[7]
GSM979058
[8]
GSM979059
[9]
GSM979060
[10]
GSM979061
[11]
GSM979062
[12]
GSM979063
[13]
GSM979064
[14]
GSM979065
[15]
GSM979066
[16]
GSM979067
[17]
GSM979068
[18]
GSM979069
[19]
GSM979070
[20]
GSM979071
[21]
GSM979072
[22]
GSM979073
[23]
GSM979074
[24]
GSM979075
[25]
GSM979076
[26]
GSM979077
[27]
GSM979078
[28]
GSM979079
[29]
GSM979080
[30]
GSM979081
[31]
GSM979082
[32]
GSM979083
[33]
GSM979084
[34]
GSM979085
[35]
GSM979086
[36]
GSM979087
[37]
GSM979088
[38]
GSM979089
[39]
GSM979090
[40]
GSM979091
[41]
GSM979092
[42]
GSM979093
[43]
GSM979094
[44]
GSM979095
[45]
GSM979096
[46]
GSM979097
[47]
GSM979098
[48]
GSM979099
[49]
GSM979100
[50]
GSM979101
[51]
GSM979102
[52]
GSM979103
[53]
GSM979104
[54]
GSM979105
[55]
GSM979106
[56]
GSM979107
[57]
GSM979108
[58]
GSM979109
[59]
GSM979110
[60]
GSM979111
[61]
GSM979112
[62]
GSM979113
[63]
GSM979114
[64]
GSM979115
[65]
GSM979116
[66]
GSM979117
[67]
GSM979118
[68]
GSM979119
[69]
GSM979120
[70]
GSM979121
[71]
GSM979122
[72]
GSM979123
[73]
GSM979124
[74]
GSM979125
[75]
GSM979126
[76]
GSM979127
[77]
GSM979128
[78]
GSM979129
[79]
GSM979130
[80]
GSM979131
[81]
GSM979132
[82]
GSM979133
[83]
GSM979134
[84]
GSM979135
[85]
GSM979136
[86]
GSM979137
[87]
GSM979138
[88]
GSM979139
[89]
GSM979140
[90]
GSM979141
[91]
GSM979142
[92]
GSM979143
[93]
GSM979144
[94]
GSM979145
[95]
GSM979146
[96]
GSM979147
[97]
GSM979148
[98]
GSM979149
[99]
GSM979150
[100]
GSM979151
[101]
GSM979152
[102]
GSM979153
[103]
GSM979154
[104]
GSM979155
[105]
GSM979156
[106]
GSM979157
[107]
GSM979158
[108]
GSM979159
[109]
GSM979160
[110]
GSM979161
[111]
GSM979162
[112]
GSM979163
[113]
GSM979164
[114]
GSM979165
[115]
GSM979166
[116]
GSM979167
[117]
GSM979168
[118]
GSM979169
[119]
GSM979170
[120]
GSM979171
[121]
GSM979172
[122]
GSM979173
[123]
GSM979174
[124]
GSM979175
[125]
GSM979176
[126]
GSM979177
[127]
GSM979178
[128]
GSM979179
[129]
GSM979180
[130]
GSM979181
[131]
GSM979182
[132]
GSM979183
[133]
GSM979184
[134]
GSM979185
[135]
GSM979186
[136]
GSM979187
[137]
GSM979188
[138]
GSM979189
[139]
GSM979190
[140]
GSM979191
[141]
GSM979192
[142]
GSM979193
[143]
GSM979194
sample_count
144
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Hepatic regeneration gene expression signature predicts late recurrence of hepatocellular carcinoma
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[6] object · 15 fields
id
data:geo:GSE41666
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=GSE41666
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE41666
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 24 items
[0]
GSM1021500
[1]
GSM1021501
[2]
GSM1021502
[3]
GSM1021503
[4]
GSM1021504
[5]
GSM1021505
[6]
GSM1021506
[7]
GSM1021507
[8]
GSM1021508
[9]
GSM1021509
[10]
GSM1021510
[11]
GSM1021511
[12]
GSM1021512
[13]
GSM1021513
[14]
GSM1021514
[15]
GSM1021515
[16]
GSM1021516
[17]
GSM1021517
[18]
GSM1021518
[19]
GSM1021519
[20]
GSM1021520
[21]
GSM1021521
[22]
GSM1021522
[23]
GSM1021523
sample_count
24
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Disulphide bond inhibitors in 2 cancer cell lines
resolution_checked_at
2026-11-01T18:06:44Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[7] object · 15 fields
id
data:geo:GSE57957
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=GSE57957
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE57957
version
null
note
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
access_statement_kind
repository_route_statement
sample_accessions array · 78 items
[0]
GSM1398645
[1]
GSM1398646
[2]
GSM1398647
[3]
GSM1398648
[4]
GSM1398649
[5]
GSM1398650
[6]
GSM1398651
[7]
GSM1398652
[8]
GSM1398653
[9]
GSM1398654
[10]
GSM1398655
[11]
GSM1398656
[12]
GSM1398657
[13]
GSM1398658
[14]
GSM1398659
[15]
GSM1398660
[16]
GSM1398661
[17]
GSM1398662
[18]
GSM1398663
[19]
GSM1398664
[20]
GSM1398665
[21]
GSM1398666
[22]
GSM1398667
[23]
GSM1398668
[24]
GSM1398669
[25]
GSM1398670
[26]
GSM1398671
[27]
GSM1398672
[28]
GSM1398673
[29]
GSM1398674
[30]
GSM1398675
[31]
GSM1398676
[32]
GSM1398677
[33]
GSM1398678
[34]
GSM1398679
[35]
GSM1398680
[36]
GSM1398681
[37]
GSM1398682
[38]
GSM1398683
[39]
GSM1398684
[40]
GSM1398685
[41]
GSM1398686
[42]
GSM1398687
[43]
GSM1398688
[44]
GSM1398689
[45]
GSM1398690
[46]
GSM1398691
[47]
GSM1398692
[48]
GSM1398693
[49]
GSM1398694
[50]
GSM1398695
[51]
GSM1398696
[52]
GSM1398697
[53]
GSM1398698
[54]
GSM1398699
[55]
GSM1398700
[56]
GSM1398701
[57]
GSM1398702
[58]
GSM1398703
[59]
GSM1398704
[60]
GSM1398705
[61]
GSM1398706
[62]
GSM1398707
[63]
GSM1398708
[64]
GSM1398709
[65]
GSM1398710
[66]
GSM1398711
[67]
GSM1398712
[68]
GSM1398713
[69]
GSM1398714
[70]
GSM1398715
[71]
GSM1398716
[72]
GSM1398717
[73]
GSM1398718
[74]
GSM1398719
[75]
GSM1398720
[76]
GSM1398721
[77]
GSM1398722
sample_count
78
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Expression profile of Hepatocellular Carcinoma
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 14 items
[0]
asset:data:geo:GSE14520 not downloaded
[1]
asset:data:geo:GSE14520 licence not read
[2]
asset:data:geo:GSE15366 not downloaded
[3]
asset:data:geo:GSE15366 licence not read
[4]
asset:data:geo:GSE18494 not downloaded
[5]
asset:data:geo:GSE18494 licence not read
[6]
asset:data:geo:GSE36376 not downloaded
[7]
asset:data:geo:GSE36376 licence not read
[8]
asset:data:geo:GSE39791 not downloaded
[9]
asset:data:geo:GSE39791 licence not read
[10]
asset:data:geo:GSE41666 not downloaded
[11]
asset:data:geo:GSE41666 licence not read
[12]
asset:data:geo:GSE57957 not downloaded
[13]
asset:data:geo:GSE57957 licence not read
analysis object · 4 fields
state
partial
methods array · 5 items
[0] object · 10 fields
id
method-1
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
1
band
verbatim
quote
For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test.
[1] object · 10 fields
id
method-2
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
[2] object · 10 fields
id
method-3
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
0.8
band
high
quote
Cox regression
[3] object · 10 fields
id
method-4
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
logrank
[4] object · 10 fields
id
method-5
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.8
band
high
quote
protein-protein interaction
targets array · 0 items
gaps array · 1 item
[0]
method.group_comparison_wilcoxon
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
false
required_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
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 · 7 items
[0]
GSE41666
[1]
GSE15366
[2]
GSE18494
[3]
GSE36376
[4]
GSE14520
[5]
GSE39791
[6]
GSE57957
resolved_accessions array · 7 items
[0]
GSE41666
[1]
GSE15366
[2]
GSE18494
[3]
GSE36376
[4]
GSE14520
[5]
GSE39791
[6]
GSE57957
statements array · 1 item
[0]
TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13).
basis
The paper names GSE41666, GSE15366, GSE18494, GSE36376, GSE14520, GSE39791, GSE57957 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 2 items
[0]
source:pmid:35966318
[1]
data:geo:GSE14520
steps array · 0 items
must_build object · 5 fields
dsl_operations array · 1 item
[0] object · 3 fields
operation
group_comparison_wilcoxon
priority
null
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE14520
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
2026-11-01T18:00:22Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
5
usage object · 3 fields
prompt_tokens
18402
completion_tokens
3601
cached_tokens
128
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:35966318
type
paper
label
pmid:35966318
[1] object · 3 fields
id
source:pmid:35966318
type
manuscript
label
PMID 35966318 full text
[2] object · 3 fields
id
data:geo:GSE14520
type
dataset
label
GEO GSE14520
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:35966318
type
paper
label
pmid:35966318
[1] object · 3 fields
id
source:pmid:35966318
type
manuscript
label
PMID 35966318 full text
[2] object · 3 fields
id
data:geo:GSE14520
type
dataset
label
GEO GSE14520
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-35966318
type
extraction
used array · 1 item
[0]
source:pmid:35966318
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE14520
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE14520
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:35966318
parent_hash
sha256:1ad70a48af25e68286d1664a3cf44a07151d9b9b4bf83c43f1826cde25880d56
fork_of
null
gaps array · 20 items
[0]
asset:data:geo:GSE14520 licence not read
[1]
asset:data:geo:GSE14520 not downloaded
[2]
asset:data:geo:GSE15366 licence not read
[3]
asset:data:geo:GSE15366 not downloaded
[4]
asset:data:geo:GSE18494 licence not read
[5]
asset:data:geo:GSE18494 not downloaded
[6]
asset:data:geo:GSE36376 licence not read
[7]
asset:data:geo:GSE36376 not downloaded
[8]
asset:data:geo:GSE39791 licence not read
[9]
asset:data:geo:GSE39791 not downloaded
[10]
asset:data:geo:GSE41666 licence not read
[11]
asset:data:geo:GSE41666 not downloaded
[12]
asset:data:geo:GSE57957 licence not read
[13]
asset:data:geo:GSE57957 not downloaded
[14]
execution.not_run
[15]
method.group_comparison_wilcoxon
[16]
review.human_critique
[17]
review.independent_reader
[18]
review.machine_critique
[19]
step:run_analysis blocked on method:group_comparison_wilcoxon
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_id
animal_model
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.77
evidence array · 1 item
[0]
rient starvation and tumor growth inhibition in vivo (46). Therefore, VLX600 showed good performa
order_basis
paper_text_order:8712
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
group_comparison
definition_version
f2132e96ae6c7a4e
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test.
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:35966318", "kind": "science-record", "revision": 5, "content_hash": "sha256:a59535612d8c7adb9f0c5c4293bc1a35b3afbcc25d4efa9960376399f73553c0", "created_at": "2026-11-01T18:15:05Z", "updated_at": "2026-11-01T22:49:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Novel hypoxia features with appealing implications in discriminating the prognosis, immune escape and drug responses of 947 hepatocellular carcinoma patients.", "doi": "10.21037/tcr-22-253", "pmid": "35966318", "authors": ["Mingyuan Luan", "Hongzong Si"], "journal": "Translational cancer research", "year": 2022, "abstract": "Background: Hypoxia has a profound impact on the development and progression of hepatocellular carcinoma (HCC). This study aimed to explore and elucidate how hypoxia affect prognosis, immune escape and drug responses in HCC.\nMethods: HCC-specific hypoxia signatures were identified based on the intersect of differentially expressed genes (DEGs) of GSE41666 and GSE15366. The hypoxia score was calculated using the gene set variation analysis (GSVA) function and validated on GSE18494. We collected five cohorts [The Cancer Genome Atlas (TCGA), GSE14520, GSE39791, GSE36376, GSE57957] for further analysis. First, we analyzed the effect of the hypoxia score on prognosis. Next, we systematically analyzed the potential hypoxia-related immune escape mechanisms and the effect of hypoxia upon immunotherapy. Then, we predicted and screened potential sensitive drugs for HCC patients with high hypoxia levels using machine learning and docking.\nResults: We constructed a novel HCC-specific hypoxia score and undertook further analysis in five cohorts (TCGA, GSE14520, GSE39791, GSE36376, GSE57957). We observed that patients with high hypoxia scores exhibited worse overall survival (OS) in TCGA and GSE14520. We also constructed a hypoxia-related nomogram that had good performance in predicting HCC patients' prognosis. Furthermore, patients with lower hypoxia scores had a lower risk of immune escape and thus may benefit from immunotherapy. Finally, we predicted and screened VLX600 as the candidate drug for HCC patients with high hypoxia scores. We further explored and elucidated why VLX600 was more sensitive in HCC patients with high hypoxia than with low hypoxia HCC patients using weighted gene co-expression network analysis (WGCNA).\nConclusions: This study provides further evidence of the link between hypoxia and prognosis and immune escape in HCC patients. Moreover, our research screened VLX600 as a potential drug for HCC patients with high hypoxia levels and elucidated the potential mechanism.", "claims": [{"id": "claim-method", "statement": "For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35966318", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. 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"asset:data:geo:GSE41666 licence not read", "asset:data:geo:GSE57957 not downloaded", "asset:data:geo:GSE57957 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "For comparisons of two groups, we used wilcoxon rank-sum test. For comparisons of more than two groups, we used Kruskal-Wallis tests. The two-sided Fisher’s exact test was performed for the contingency tables. All statistical P values were two-sided. The survival curves of each data set were generated by Kaplan-Meier analysis, and statistically significant differences were determined through the log-rank test."}}, {"id": "method-2", "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-3", "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": 0.8, "band": "high", "quote": "Cox regression"}}, {"id": "method-4", "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": "logrank"}}, {"id": "method-5", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "protein-protein interaction"}}], "targets": [], "gaps": ["method.group_comparison_wilcoxon"]}, "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": false, "required_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon."}, "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": ["GSE41666", "GSE15366", "GSE18494", "GSE36376", "GSE14520", "GSE39791", "GSE57957"], "resolved_accessions": ["GSE41666", "GSE15366", "GSE18494", "GSE36376", "GSE14520", "GSE39791", "GSE57957"], "statements": ["TCGA gene expression data [transcripts per million (TPM) and row counts], copy number data, mutation data, clinical data and sample information of HCC were downloaded from Xena (13)."], "basis": "The paper names GSE41666, GSE15366, GSE18494, GSE36376, GSE14520, GSE39791, GSE57957 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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