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

pmid:37091977

An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy.

Mengling Li · Baosen Zhou · Chang Zheng

Frontiers in cell and developmental biology · 2023 doi:10.3389/fcell.2023.1163314

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:37091977
kind
science-record
content_hash
sha256:982c83d3787ac2f115078ae3062ed3098a8e7c92c55bfe70508a288d150110c3
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T19:01:45Z
updated_at
2026-11-01T21:30:37Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy.
doi
10.3389/fcell.2023.1163314
pmid
37091977
authors array · 3 items
[0]
Mengling Li
[1]
Baosen Zhou
[2]
Chang Zheng
journal
Frontiers in cell and developmental biology
year
2023
abstract
Targeting the tumor microenvironment is increasingly recognized as an effective treatment of advanced lung adenocarcinoma (LUAD). However, few studies have addressed the efficacy of immunotherapy for LUAD. Here, a novel method for predicting immunotherapy efficacy has been proposed, which combines single-cell and bulk sequencing to characterize the immune microenvironment and metabolic profile of LUAD. TCGA bulk dataset was used to cluster two immune subtypes: C1 with "cold" tumor characteristics and C2 with "hot" tumor characteristics, with different prognosis. The Scissor algorithm, which is based on these two immune subtypes, identified GSE131907 single cell dataset into two groups of epithelial cells, labeled as Scissor_C1 and Scissor_C2. The enrichment revealed that Scissor_C1 was characterized by hypoxia, and a hypoxic microenvironment is a potential inducing factor for tumor invasion, metastasis, and immune therapy non-response. Furthermore, single cell analysis was performed to investigate the molecular mechanism of hypoxic microenvironment-induced invasion, metastasis, and immune therapy non-response in LUAD. Notably, Scissor_C1 cells significantly interacted with T cells and cancer-associated fibroblasts (CAF), and exhibited epithelial-mesenchymal transition and immunosuppressive features. CellChat analysis revealed that a hypoxic microenvironment in Scissor_C1elevated TGFβ signaling and induced ANGPTL4 and SEMA3C secretion. Interaction with endothelial cells with ANGPTL4, which increases vascular permeability and achieves distant metastasis across the vascular endothelium. Additionally, interaction of tumor-associated macrophages (TAM) and Scissor_C1 via the EREG/EFGR pathway induces tyrosine kinase inhibitor drug-resistance in patients with LAUD. Thereafter, a subgroup of CAF cells that exhibited same features as those of Scissor_C1 that exert immunosuppressive functions in the tumor microenvironment were identified. Moreover, the key genes (EPHB2 and COL1A1) in the Scissor_C1 gene network were explored and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cells crosstalk was determined, which is characterized by glutamine secretion by TAM and uptake by Scissor_C1 via SLC38A2 transporter, which may induce glutamine addiction in LUAD cells. Overall, single-cell sequencing clarifies how the tumor microenvironment affects immunotherapy efficacy via molecular mechanisms and biological processes, whereas bulk sequencing explains immunotherapy efficacy based on clinical information.
claims array · 3 items
[0] object · 6 fields
id
claim-method
statement
Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022).
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37091977
locator
sections[6] "2.4 Scissor algorithm for identifying phenotypically related cells" paragraph 2
quote
Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022).
state
complete
[1] object · 6 fields
id
claim-data-access
statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
kind
methodological
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37091977
locator
sections[26] "Data availability statement" paragraph 2
quote
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
state
complete
[2] object · 6 fields
id
claim-target-result
statement
The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.
kind
qualitative
target
null
evidence array · 1 item
[0] object · 3 fields
asset
source:pmid:37091977
locator
sections[16] "3.2 Integrated scRNA-seq analysis to dissect and cluster immune-related epithelial cell populations in LUAD" paragraph 2
quote
The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively (Figures 4A, B).
state
complete
gaps array · 0 items
experiment object · 8 fields
state
complete
objective
The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.
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:37091977
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:GSE131907
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:GSE131907
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 · 4 items
[0] object · 15 fields
id
source:pmid:37091977
role
manuscript
format
xml
media_type
application/xml
uri
https://doi.org/10.3389/fcell.2023.1163314
sha256
sha256:f4e6b09b816785819091c645cc1d4e5f3ba4bea9408094b6d87c2e08e289838e
bytes
49808
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
10.3389/fcell.2023.1163314
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
PMC10113470
source
europe_pmc_fulltext
coverage
whole_body_without_references
text_hash_scope
rendered_section_body
[1] object · 15 fields
id
data:geo:GSE131907
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=GSE131907
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE131907
version
null
note
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
access_statement_kind
data_availability_statement
sample_accessions array · 58 items
[0]
GSM3827114
[1]
GSM3827115
[2]
GSM3827116
[3]
GSM3827117
[4]
GSM3827118
[5]
GSM3827119
[6]
GSM3827120
[7]
GSM3827121
[8]
GSM3827122
[9]
GSM3827123
[10]
GSM3827124
[11]
GSM3827125
[12]
GSM3827126
[13]
GSM3827127
[14]
GSM3827128
[15]
GSM3827129
[16]
GSM3827130
[17]
GSM3827131
[18]
GSM3827132
[19]
GSM3827133
[20]
GSM3827134
[21]
GSM3827135
[22]
GSM3827136
[23]
GSM3827137
[24]
GSM3827138
[25]
GSM3827139
[26]
GSM3827140
[27]
GSM3827141
[28]
GSM3827142
[29]
GSM3827143
[30]
GSM3827144
[31]
GSM3827145
[32]
GSM3827146
[33]
GSM3827147
[34]
GSM3827148
[35]
GSM3827149
[36]
GSM3827150
[37]
GSM3827151
[38]
GSM3827152
[39]
GSM3827153
[40]
GSM3827154
[41]
GSM3827155
[42]
GSM3827156
[43]
GSM3827157
[44]
GSM3827158
[45]
GSM3827159
[46]
GSM3827160
[47]
GSM3827161
[48]
GSM3827162
[49]
GSM3827163
[50]
GSM3827164
[51]
GSM3827165
[52]
GSM3827166
[53]
GSM3827167
[54]
GSM3827168
[55]
GSM3827169
[56]
GSM3827170
[57]
GSM3827171
sample_count
58
group_sizes
null
group_sizes_basis
null
platform
16791
taxon
Homo sapiens
title
Single cell RNA sequencing of lung adenocarcinoma
resolution_checked_at
2026-11-01T18:06:43Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:GSE68465
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=GSE68465
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE68465
version
null
note
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
access_statement_kind
data_availability_statement
sample_accessions array · 462 items
[0]
GSM1672281
[1]
GSM1672282
[2]
GSM1672283
[3]
GSM1672284
[4]
GSM1672285
[5]
GSM1672286
[6]
GSM1672287
[7]
GSM1672288
[8]
GSM1672289
[9]
GSM1672290
[10]
GSM1672291
[11]
GSM1672292
[12]
GSM1672293
[13]
GSM1672294
[14]
GSM1672295
[15]
GSM1672296
[16]
GSM1672297
[17]
GSM1672298
[18]
GSM1672299
[19]
GSM1672300
[20]
GSM1672301
[21]
GSM1672302
[22]
GSM1672303
[23]
GSM1672304
[24]
GSM1672305
[25]
GSM1672306
[26]
GSM1672307
[27]
GSM1672308
[28]
GSM1672309
[29]
GSM1672310
[30]
GSM1672311
[31]
GSM1672312
[32]
GSM1672313
[33]
GSM1672314
[34]
GSM1672315
[35]
GSM1672316
[36]
GSM1672317
[37]
GSM1672318
[38]
GSM1672319
[39]
GSM1672320
[40]
GSM1672321
[41]
GSM1672322
[42]
GSM1672323
[43]
GSM1672324
[44]
GSM1672325
[45]
GSM1672326
[46]
GSM1672327
[47]
GSM1672328
[48]
GSM1672329
[49]
GSM1672330
[50]
GSM1672331
[51]
GSM1672332
[52]
GSM1672333
[53]
GSM1672334
[54]
GSM1672335
[55]
GSM1672336
[56]
GSM1672337
[57]
GSM1672338
[58]
GSM1672339
[59]
GSM1672340
[60]
GSM1672341
[61]
GSM1672342
[62]
GSM1672343
[63]
GSM1672344
[64]
GSM1672345
[65]
GSM1672346
[66]
GSM1672347
[67]
GSM1672348
[68]
GSM1672349
[69]
GSM1672350
[70]
GSM1672351
[71]
GSM1672352
[72]
GSM1672353
[73]
GSM1672354
[74]
GSM1672355
[75]
GSM1672356
[76]
GSM1672357
[77]
GSM1672358
[78]
GSM1672359
[79]
GSM1672360
[80]
GSM1672361
[81]
GSM1672362
[82]
GSM1672363
[83]
GSM1672364
[84]
GSM1672365
[85]
GSM1672366
[86]
GSM1672367
[87]
GSM1672368
[88]
GSM1672369
[89]
GSM1672370
[90]
GSM1672371
[91]
GSM1672372
[92]
GSM1672373
[93]
GSM1672374
[94]
GSM1672375
[95]
GSM1672376
[96]
GSM1672377
[97]
GSM1672378
[98]
GSM1672379
[99]
GSM1672380
[100]
GSM1672381
[101]
GSM1672382
[102]
GSM1672383
[103]
GSM1672384
[104]
GSM1672385
[105]
GSM1672386
[106]
GSM1672387
[107]
GSM1672388
[108]
GSM1672389
[109]
GSM1672390
[110]
GSM1672391
[111]
GSM1672392
[112]
GSM1672393
[113]
GSM1672394
[114]
GSM1672395
[115]
GSM1672396
[116]
GSM1672397
[117]
GSM1672398
[118]
GSM1672399
[119]
GSM1672400
[120]
GSM1672401
[121]
GSM1672402
[122]
GSM1672403
[123]
GSM1672404
[124]
GSM1672405
[125]
GSM1672406
[126]
GSM1672407
[127]
GSM1672408
[128]
GSM1672409
[129]
GSM1672410
[130]
GSM1672411
[131]
GSM1672412
[132]
GSM1672413
[133]
GSM1672414
[134]
GSM1672415
[135]
GSM1672416
[136]
GSM1672417
[137]
GSM1672418
[138]
GSM1672419
[139]
GSM1672420
[140]
GSM1672421
[141]
GSM1672422
[142]
GSM1672423
[143]
GSM1672424
[144]
GSM1672425
[145]
GSM1672426
[146]
GSM1672427
[147]
GSM1672428
[148]
GSM1672429
[149]
GSM1672430
[150]
GSM1672431
[151]
GSM1672432
[152]
GSM1672433
[153]
GSM1672434
[154]
GSM1672435
[155]
GSM1672436
[156]
GSM1672437
[157]
GSM1672438
[158]
GSM1672439
[159]
GSM1672440
[160]
GSM1672441
[161]
GSM1672442
[162]
GSM1672443
[163]
GSM1672444
[164]
GSM1672445
[165]
GSM1672446
[166]
GSM1672447
[167]
GSM1672448
[168]
GSM1672449
[169]
GSM1672450
[170]
GSM1672451
[171]
GSM1672452
[172]
GSM1672453
[173]
GSM1672454
[174]
GSM1672455
[175]
GSM1672456
[176]
GSM1672457
[177]
GSM1672458
[178]
GSM1672459
[179]
GSM1672460
[180]
GSM1672461
[181]
GSM1672462
[182]
GSM1672463
[183]
GSM1672464
[184]
GSM1672465
[185]
GSM1672466
[186]
GSM1672467
[187]
GSM1672468
[188]
GSM1672469
[189]
GSM1672470
[190]
GSM1672471
[191]
GSM1672472
[192]
GSM1672473
[193]
GSM1672474
[194]
GSM1672475
[195]
GSM1672476
[196]
GSM1672477
[197]
GSM1672478
[198]
GSM1672479
[199]
GSM1672480
[200]
GSM1672481
[201]
GSM1672482
[202]
GSM1672483
[203]
GSM1672484
[204]
GSM1672485
[205]
GSM1672486
[206]
GSM1672487
[207]
GSM1672488
[208]
GSM1672489
[209]
GSM1672490
[210]
GSM1672491
[211]
GSM1672492
[212]
GSM1672493
[213]
GSM1672494
[214]
GSM1672495
[215]
GSM1672496
[216]
GSM1672497
[217]
GSM1672498
[218]
GSM1672499
[219]
GSM1672500
[220]
GSM1672501
[221]
GSM1672502
[222]
GSM1672503
[223]
GSM1672504
[224]
GSM1672505
[225]
GSM1672506
[226]
GSM1672507
[227]
GSM1672508
[228]
GSM1672509
[229]
GSM1672510
[230]
GSM1672511
[231]
GSM1672512
[232]
GSM1672513
[233]
GSM1672514
[234]
GSM1672515
[235]
GSM1672516
[236]
GSM1672517
[237]
GSM1672518
[238]
GSM1672519
[239]
GSM1672520
[240]
GSM1672521
[241]
GSM1672522
[242]
GSM1672523
[243]
GSM1672524
[244]
GSM1672525
[245]
GSM1672526
[246]
GSM1672527
[247]
GSM1672528
[248]
GSM1672529
[249]
GSM1672530
[250]
GSM1672531
[251]
GSM1672532
[252]
GSM1672533
[253]
GSM1672534
[254]
GSM1672535
[255]
GSM1672536
[256]
GSM1672537
[257]
GSM1672538
[258]
GSM1672539
[259]
GSM1672540
[260]
GSM1672541
[261]
GSM1672542
[262]
GSM1672543
[263]
GSM1672544
[264]
GSM1672545
[265]
GSM1672546
[266]
GSM1672547
[267]
GSM1672548
[268]
GSM1672549
[269]
GSM1672550
[270]
GSM1672551
[271]
GSM1672552
[272]
GSM1672553
[273]
GSM1672554
[274]
GSM1672555
[275]
GSM1672556
[276]
GSM1672557
[277]
GSM1672558
[278]
GSM1672559
[279]
GSM1672560
[280]
GSM1672561
[281]
GSM1672562
[282]
GSM1672563
[283]
GSM1672564
[284]
GSM1672565
[285]
GSM1672566
[286]
GSM1672567
[287]
GSM1672568
[288]
GSM1672569
[289]
GSM1672570
[290]
GSM1672571
[291]
GSM1672572
[292]
GSM1672573
[293]
GSM1672574
[294]
GSM1672575
[295]
GSM1672576
[296]
GSM1672577
[297]
GSM1672578
[298]
GSM1672579
[299]
GSM1672580
[300]
GSM1672581
[301]
GSM1672582
[302]
GSM1672583
[303]
GSM1672584
[304]
GSM1672585
[305]
GSM1672586
[306]
GSM1672587
[307]
GSM1672588
[308]
GSM1672589
[309]
GSM1672590
[310]
GSM1672591
[311]
GSM1672592
[312]
GSM1672593
[313]
GSM1672594
[314]
GSM1672595
[315]
GSM1672596
[316]
GSM1672597
[317]
GSM1672598
[318]
GSM1672599
[319]
GSM1672600
[320]
GSM1672601
[321]
GSM1672602
[322]
GSM1672603
[323]
GSM1672604
[324]
GSM1672605
[325]
GSM1672606
[326]
GSM1672607
[327]
GSM1672608
[328]
GSM1672609
[329]
GSM1672610
[330]
GSM1672611
[331]
GSM1672612
[332]
GSM1672613
[333]
GSM1672614
[334]
GSM1672615
[335]
GSM1672616
[336]
GSM1672617
[337]
GSM1672618
[338]
GSM1672619
[339]
GSM1672620
[340]
GSM1672621
[341]
GSM1672622
[342]
GSM1672623
[343]
GSM1672624
[344]
GSM1672625
[345]
GSM1672626
[346]
GSM1672627
[347]
GSM1672628
[348]
GSM1672629
[349]
GSM1672630
[350]
GSM1672631
[351]
GSM1672632
[352]
GSM1672633
[353]
GSM1672634
[354]
GSM1672635
[355]
GSM1672636
[356]
GSM1672637
[357]
GSM1672638
[358]
GSM1672639
[359]
GSM1672640
[360]
GSM1672641
[361]
GSM1672642
[362]
GSM1672643
[363]
GSM1672644
[364]
GSM1672645
[365]
GSM1672646
[366]
GSM1672647
[367]
GSM1672648
[368]
GSM1672649
[369]
GSM1672650
[370]
GSM1672651
[371]
GSM1672652
[372]
GSM1672653
[373]
GSM1672654
[374]
GSM1672655
[375]
GSM1672656
[376]
GSM1672657
[377]
GSM1672658
[378]
GSM1672659
[379]
GSM1672660
[380]
GSM1672661
[381]
GSM1672662
[382]
GSM1672663
[383]
GSM1672664
[384]
GSM1672665
[385]
GSM1672666
[386]
GSM1672667
[387]
GSM1672668
[388]
GSM1672669
[389]
GSM1672670
[390]
GSM1672671
[391]
GSM1672672
[392]
GSM1672673
[393]
GSM1672674
[394]
GSM1672675
[395]
GSM1672676
[396]
GSM1672677
[397]
GSM1672678
[398]
GSM1672679
[399]
GSM1672680
[400]
GSM1672681
[401]
GSM1672682
[402]
GSM1672683
[403]
GSM1672684
[404]
GSM1672685
[405]
GSM1672686
[406]
GSM1672687
[407]
GSM1672688
[408]
GSM1672689
[409]
GSM1672690
[410]
GSM1672691
[411]
GSM1672692
[412]
GSM1672693
[413]
GSM1672694
[414]
GSM1672695
[415]
GSM1672696
[416]
GSM1672697
[417]
GSM1672698
[418]
GSM1672699
[419]
GSM1672700
[420]
GSM1672701
[421]
GSM1672702
[422]
GSM1672703
[423]
GSM1672704
[424]
GSM1672705
[425]
GSM1672706
[426]
GSM1672707
[427]
GSM1672708
[428]
GSM1672709
[429]
GSM1672710
[430]
GSM1672711
[431]
GSM1672712
[432]
GSM1672713
[433]
GSM1672714
[434]
GSM1672715
[435]
GSM1672716
[436]
GSM1672717
[437]
GSM1672718
[438]
GSM1672719
[439]
GSM1672720
[440]
GSM1672721
[441]
GSM1672722
[442]
GSM1672723
[443]
GSM1672724
[444]
GSM1672725
[445]
GSM1672726
[446]
GSM1672727
[447]
GSM1672728
[448]
GSM1672729
[449]
GSM1672730
[450]
GSM1672731
[451]
GSM1672732
[452]
GSM1672733
[453]
GSM1672734
[454]
GSM1672735
[455]
GSM1672736
[456]
GSM1672737
[457]
GSM1672738
[458]
GSM1672739
[459]
GSM1672740
[460]
GSM1672741
[461]
GSM1672742
sample_count
462
group_sizes
null
group_sizes_basis
null
platform
96
taxon
Homo sapiens
title
caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE78220
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=GSE78220
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE78220
version
null
note
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
access_statement_kind
data_availability_statement
sample_accessions array · 28 items
[0]
GSM2069823
[1]
GSM2069824
[2]
GSM2069825
[3]
GSM2069826
[4]
GSM2069827
[5]
GSM2069828
[6]
GSM2069829
[7]
GSM2069830
[8]
GSM2069831
[9]
GSM2069832
[10]
GSM2069833
[11]
GSM2069834
[12]
GSM2069835
[13]
GSM2069836
[14]
GSM2069837
[15]
GSM2069838
[16]
GSM2069839
[17]
GSM2069840
[18]
GSM2069841
[19]
GSM2069842
[20]
GSM2069843
[21]
GSM2069844
[22]
GSM2069845
[23]
GSM2069846
[24]
GSM2069847
[25]
GSM2069848
[26]
GSM2069849
[27]
GSM2069850
sample_count
28
group_sizes
null
group_sizes_basis
null
platform
11154
taxon
Homo sapiens
title
mRNA expressions in pre-treatment melanomas undergoing anti-PD-1 checkpoint inhibition therapy
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 6 items
[0]
asset:data:geo:GSE131907 not downloaded
[1]
asset:data:geo:GSE131907 licence not read
[2]
asset:data:geo:GSE68465 not downloaded
[3]
asset:data:geo:GSE68465 licence not read
[4]
asset:data:geo:GSE78220 not downloaded
[5]
asset:data:geo:GSE78220 licence not read
analysis object · 4 fields
state
partial
methods array · 1 item
[0] object · 10 fields
id
method-1
family
null
specific
null
label
Scissor 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
verbatim
quote
Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022).
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
blocked
tier
R4
blocking_axis
method
blocked_on
method:not_determinable
axes object · 3 fields
method object · 5 fields
tier
R4
expressible
false
required_operations array · 0 items
missing_operations array · 0 items
basis
The reader quoted the method the paper names (Scissor algorithm), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
GSE131907
[1]
GSE68465
[2]
GSE78220
resolved_accessions array · 3 items
[0]
GSE131907
[1]
GSE68465
[2]
GSE78220
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
basis
The paper names GSE131907, GSE68465, GSE78220 in 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:37091977
[1]
data:geo:GSE131907
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:GSE131907
gaps array · 1 item
[0]
method:not_determinable
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:37:27Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
13071
completion_tokens
2235
cached_tokens
264
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:37091977
type
paper
label
pmid:37091977
[1] object · 3 fields
id
source:pmid:37091977
type
manuscript
label
PMID 37091977 full text
[2] object · 3 fields
id
data:geo:GSE131907
type
dataset
label
GEO GSE131907
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:37091977
type
paper
label
pmid:37091977
[1] object · 3 fields
id
source:pmid:37091977
type
manuscript
label
PMID 37091977 full text
[2] object · 3 fields
id
data:geo:GSE131907
type
dataset
label
GEO GSE131907
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-37091977
type
extraction
used array · 1 item
[0]
source:pmid:37091977
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE131907
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE131907
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:37091977
parent_hash
sha256:78d2c4471d5afd3c1585582f71c94a6da6f898c816b74f6c2e261243dd00fc6f
fork_of
null
gaps array · 11 items
[0]
asset:data:geo:GSE131907 licence not read
[1]
asset:data:geo:GSE131907 not downloaded
[2]
asset:data:geo:GSE68465 licence not read
[3]
asset:data:geo:GSE68465 not downloaded
[4]
asset:data:geo:GSE78220 licence not read
[5]
asset:data:geo:GSE78220 not downloaded
[6]
execution.not_run
[7]
method.reader_named_unmapped
[8]
review.human_critique
[9]
review.independent_reader
[10]
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
0.93
evidence array · 1 item
[0]
ed and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cell
order_basis
paper_text_order:2235
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
rna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
2 Materials and methods 2.3 Single cell RNA-seq data processing Three quality measures were
order_basis
paper_text_order:2770
id
assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37091977", "kind": "science-record", "revision": 2, "content_hash": "sha256:982c83d3787ac2f115078ae3062ed3098a8e7c92c55bfe70508a288d150110c3", "created_at": "2026-11-01T19:01:45Z", "updated_at": "2026-11-01T21:30:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy.", "doi": "10.3389/fcell.2023.1163314", "pmid": "37091977", "authors": ["Mengling Li", "Baosen Zhou", "Chang Zheng"], "journal": "Frontiers in cell and developmental biology", "year": 2023, "abstract": "Targeting the tumor microenvironment is increasingly recognized as an effective treatment of advanced lung adenocarcinoma (LUAD). However, few studies have addressed the efficacy of immunotherapy for LUAD. Here, a novel method for predicting immunotherapy efficacy has been proposed, which combines single-cell and bulk sequencing to characterize the immune microenvironment and metabolic profile of LUAD. TCGA bulk dataset was used to cluster two immune subtypes: C1 with \"cold\" tumor characteristics and C2 with \"hot\" tumor characteristics, with different prognosis. The Scissor algorithm, which is based on these two immune subtypes, identified GSE131907 single cell dataset into two groups of epithelial cells, labeled as Scissor_C1 and Scissor_C2. The enrichment revealed that Scissor_C1 was characterized by hypoxia, and a hypoxic microenvironment is a potential inducing factor for tumor invasion, metastasis, and immune therapy non-response. Furthermore, single cell analysis was performed to investigate the molecular mechanism of hypoxic microenvironment-induced invasion, metastasis, and immune therapy non-response in LUAD. Notably, Scissor_C1 cells significantly interacted with T cells and cancer-associated fibroblasts (CAF), and exhibited epithelial-mesenchymal transition and immunosuppressive features. CellChat analysis revealed that a hypoxic microenvironment in Scissor_C1elevated TGFβ signaling and induced ANGPTL4 and SEMA3C secretion. Interaction with endothelial cells with ANGPTL4, which increases vascular permeability and achieves distant metastasis across the vascular endothelium. Additionally, interaction of tumor-associated macrophages (TAM) and Scissor_C1 via the EREG/EFGR pathway induces tyrosine kinase inhibitor drug-resistance in patients with LAUD. Thereafter, a subgroup of CAF cells that exhibited same features as those of Scissor_C1 that exert immunosuppressive functions in the tumor microenvironment were identified. Moreover, the key genes (EPHB2 and COL1A1) in the Scissor_C1 gene network were explored and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cells crosstalk was determined, which is characterized by glutamine secretion by TAM and uptake by Scissor_C1 via SLC38A2 transporter, which may induce glutamine addiction in LUAD cells. Overall, single-cell sequencing clarifies how the tumor microenvironment affects immunotherapy efficacy via molecular mechanisms and biological processes, whereas bulk sequencing explains immunotherapy efficacy based on clinical information.", "claims": [{"id": "claim-method", "statement": "Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[6] \"2.4 Scissor algorithm for identifying phenotypically related cells\" paragraph 2", "quote": "Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[26] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[16] \"3.2 Integrated scRNA-seq analysis to dissect and cluster immune-related epithelial cell populations in LUAD\" paragraph 2", "quote": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively (Figures 4A, B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.", "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:37091977"], "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:GSE131907"], "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:GSE131907"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37091977", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcell.2023.1163314", "sha256": "sha256:f4e6b09b816785819091c645cc1d4e5f3ba4bea9408094b6d87c2e08e289838e", "bytes": 49808, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcell.2023.1163314", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10113470", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE131907", "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=GSE131907", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE131907", "version": null, "note": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3827114", "GSM3827115", "GSM3827116", "GSM3827117", "GSM3827118", "GSM3827119", "GSM3827120", "GSM3827121", "GSM3827122", "GSM3827123", "GSM3827124", "GSM3827125", "GSM3827126", "GSM3827127", "GSM3827128", "GSM3827129", "GSM3827130", "GSM3827131", "GSM3827132", "GSM3827133", "GSM3827134", "GSM3827135", "GSM3827136", "GSM3827137", "GSM3827138", "GSM3827139", "GSM3827140", "GSM3827141", "GSM3827142", "GSM3827143", "GSM3827144", "GSM3827145", "GSM3827146", "GSM3827147", "GSM3827148", "GSM3827149", "GSM3827150", "GSM3827151", "GSM3827152", "GSM3827153", "GSM3827154", "GSM3827155", "GSM3827156", "GSM3827157", "GSM3827158", "GSM3827159", "GSM3827160", "GSM3827161", "GSM3827162", "GSM3827163", "GSM3827164", "GSM3827165", "GSM3827166", "GSM3827167", "GSM3827168", "GSM3827169", "GSM3827170", "GSM3827171"], "sample_count": 58, "group_sizes": null, "group_sizes_basis": null, "platform": "16791", "taxon": "Homo sapiens", "title": "Single cell RNA sequencing of lung adenocarcinoma", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE68465", "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=GSE68465", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE68465", "version": null, "note": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1672281", "GSM1672282", "GSM1672283", "GSM1672284", "GSM1672285", "GSM1672286", "GSM1672287", "GSM1672288", "GSM1672289", "GSM1672290", "GSM1672291", "GSM1672292", "GSM1672293", "GSM1672294", "GSM1672295", "GSM1672296", "GSM1672297", "GSM1672298", "GSM1672299", "GSM1672300", "GSM1672301", "GSM1672302", "GSM1672303", "GSM1672304", "GSM1672305", "GSM1672306", "GSM1672307", "GSM1672308", "GSM1672309", "GSM1672310", "GSM1672311", "GSM1672312", "GSM1672313", "GSM1672314", "GSM1672315", "GSM1672316", "GSM1672317", "GSM1672318", "GSM1672319", "GSM1672320", "GSM1672321", "GSM1672322", "GSM1672323", "GSM1672324", "GSM1672325", "GSM1672326", "GSM1672327", "GSM1672328", "GSM1672329", "GSM1672330", "GSM1672331", "GSM1672332", "GSM1672333", "GSM1672334", "GSM1672335", "GSM1672336", "GSM1672337", "GSM1672338", "GSM1672339", "GSM1672340", "GSM1672341", "GSM1672342", "GSM1672343", "GSM1672344", "GSM1672345", "GSM1672346", "GSM1672347", "GSM1672348", "GSM1672349", "GSM1672350", "GSM1672351", "GSM1672352", "GSM1672353", "GSM1672354", "GSM1672355", "GSM1672356", "GSM1672357", "GSM1672358", "GSM1672359", "GSM1672360", "GSM1672361", "GSM1672362", "GSM1672363", "GSM1672364", "GSM1672365", "GSM1672366", "GSM1672367", "GSM1672368", "GSM1672369", "GSM1672370", "GSM1672371", "GSM1672372", "GSM1672373", "GSM1672374", "GSM1672375", "GSM1672376", "GSM1672377", "GSM1672378", "GSM1672379", "GSM1672380", "GSM1672381", "GSM1672382", "GSM1672383", "GSM1672384", "GSM1672385", "GSM1672386", "GSM1672387", "GSM1672388", "GSM1672389", "GSM1672390", "GSM1672391", "GSM1672392", "GSM1672393", "GSM1672394", "GSM1672395", "GSM1672396", "GSM1672397", "GSM1672398", "GSM1672399", "GSM1672400", "GSM1672401", "GSM1672402", "GSM1672403", "GSM1672404", "GSM1672405", "GSM1672406", "GSM1672407", "GSM1672408", "GSM1672409", "GSM1672410", "GSM1672411", "GSM1672412", "GSM1672413", "GSM1672414", "GSM1672415", "GSM1672416", "GSM1672417", "GSM1672418", "GSM1672419", "GSM1672420", "GSM1672421", "GSM1672422", "GSM1672423", "GSM1672424", "GSM1672425", "GSM1672426", "GSM1672427", "GSM1672428", "GSM1672429", "GSM1672430", "GSM1672431", "GSM1672432", "GSM1672433", "GSM1672434", "GSM1672435", "GSM1672436", "GSM1672437", "GSM1672438", "GSM1672439", "GSM1672440", "GSM1672441", "GSM1672442", "GSM1672443", "GSM1672444", "GSM1672445", "GSM1672446", "GSM1672447", "GSM1672448", "GSM1672449", "GSM1672450", "GSM1672451", "GSM1672452", "GSM1672453", "GSM1672454", "GSM1672455", "GSM1672456", "GSM1672457", "GSM1672458", "GSM1672459", "GSM1672460", "GSM1672461", "GSM1672462", "GSM1672463", "GSM1672464", "GSM1672465", "GSM1672466", "GSM1672467", "GSM1672468", "GSM1672469", "GSM1672470", "GSM1672471", "GSM1672472", "GSM1672473", "GSM1672474", "GSM1672475", "GSM1672476", "GSM1672477", "GSM1672478", "GSM1672479", "GSM1672480", "GSM1672481", "GSM1672482", "GSM1672483", "GSM1672484", "GSM1672485", "GSM1672486", "GSM1672487", "GSM1672488", "GSM1672489", "GSM1672490", "GSM1672491", "GSM1672492", "GSM1672493", "GSM1672494", "GSM1672495", "GSM1672496", "GSM1672497", "GSM1672498", "GSM1672499", "GSM1672500", "GSM1672501", "GSM1672502", "GSM1672503", "GSM1672504", "GSM1672505", "GSM1672506", "GSM1672507", "GSM1672508", "GSM1672509", "GSM1672510", "GSM1672511", "GSM1672512", "GSM1672513", "GSM1672514", "GSM1672515", "GSM1672516", "GSM1672517", "GSM1672518", "GSM1672519", "GSM1672520", "GSM1672521", "GSM1672522", "GSM1672523", "GSM1672524", "GSM1672525", "GSM1672526", "GSM1672527", "GSM1672528", "GSM1672529", "GSM1672530", "GSM1672531", "GSM1672532", "GSM1672533", "GSM1672534", "GSM1672535", "GSM1672536", "GSM1672537", "GSM1672538", "GSM1672539", "GSM1672540", "GSM1672541", "GSM1672542", "GSM1672543", "GSM1672544", "GSM1672545", "GSM1672546", "GSM1672547", "GSM1672548", "GSM1672549", "GSM1672550", "GSM1672551", "GSM1672552", "GSM1672553", "GSM1672554", "GSM1672555", "GSM1672556", "GSM1672557", "GSM1672558", "GSM1672559", "GSM1672560", "GSM1672561", "GSM1672562", "GSM1672563", "GSM1672564", "GSM1672565", "GSM1672566", "GSM1672567", "GSM1672568", "GSM1672569", "GSM1672570", "GSM1672571", "GSM1672572", "GSM1672573", "GSM1672574", "GSM1672575", "GSM1672576", "GSM1672577", "GSM1672578", "GSM1672579", "GSM1672580", "GSM1672581", "GSM1672582", "GSM1672583", "GSM1672584", "GSM1672585", "GSM1672586", "GSM1672587", "GSM1672588", "GSM1672589", "GSM1672590", "GSM1672591", "GSM1672592", "GSM1672593", "GSM1672594", "GSM1672595", "GSM1672596", "GSM1672597", "GSM1672598", "GSM1672599", "GSM1672600", "GSM1672601", "GSM1672602", "GSM1672603", "GSM1672604", "GSM1672605", "GSM1672606", "GSM1672607", "GSM1672608", "GSM1672609", "GSM1672610", "GSM1672611", "GSM1672612", "GSM1672613", "GSM1672614", "GSM1672615", "GSM1672616", "GSM1672617", "GSM1672618", "GSM1672619", "GSM1672620", "GSM1672621", "GSM1672622", "GSM1672623", "GSM1672624", "GSM1672625", "GSM1672626", "GSM1672627", "GSM1672628", "GSM1672629", "GSM1672630", "GSM1672631", "GSM1672632", "GSM1672633", "GSM1672634", "GSM1672635", "GSM1672636", "GSM1672637", "GSM1672638", "GSM1672639", "GSM1672640", "GSM1672641", "GSM1672642", "GSM1672643", "GSM1672644", "GSM1672645", "GSM1672646", "GSM1672647", "GSM1672648", "GSM1672649", "GSM1672650", "GSM1672651", "GSM1672652", "GSM1672653", "GSM1672654", "GSM1672655", "GSM1672656", "GSM1672657", "GSM1672658", "GSM1672659", "GSM1672660", "GSM1672661", "GSM1672662", "GSM1672663", "GSM1672664", "GSM1672665", "GSM1672666", "GSM1672667", "GSM1672668", "GSM1672669", "GSM1672670", "GSM1672671", "GSM1672672", "GSM1672673", "GSM1672674", "GSM1672675", "GSM1672676", "GSM1672677", "GSM1672678", "GSM1672679", "GSM1672680", "GSM1672681", "GSM1672682", "GSM1672683", "GSM1672684", "GSM1672685", "GSM1672686", "GSM1672687", "GSM1672688", "GSM1672689", "GSM1672690", "GSM1672691", "GSM1672692", "GSM1672693", "GSM1672694", "GSM1672695", "GSM1672696", "GSM1672697", "GSM1672698", "GSM1672699", "GSM1672700", "GSM1672701", "GSM1672702", "GSM1672703", "GSM1672704", "GSM1672705", "GSM1672706", "GSM1672707", "GSM1672708", "GSM1672709", "GSM1672710", "GSM1672711", "GSM1672712", "GSM1672713", "GSM1672714", "GSM1672715", "GSM1672716", "GSM1672717", "GSM1672718", "GSM1672719", "GSM1672720", "GSM1672721", "GSM1672722", "GSM1672723", "GSM1672724", "GSM1672725", "GSM1672726", "GSM1672727", "GSM1672728", "GSM1672729", "GSM1672730", "GSM1672731", "GSM1672732", "GSM1672733", "GSM1672734", "GSM1672735", "GSM1672736", "GSM1672737", "GSM1672738", "GSM1672739", "GSM1672740", "GSM1672741", "GSM1672742"], "sample_count": 462, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE78220", "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=GSE78220", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE78220", "version": null, "note": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2069823", "GSM2069824", "GSM2069825", "GSM2069826", "GSM2069827", "GSM2069828", "GSM2069829", "GSM2069830", "GSM2069831", "GSM2069832", "GSM2069833", "GSM2069834", "GSM2069835", "GSM2069836", "GSM2069837", "GSM2069838", "GSM2069839", "GSM2069840", "GSM2069841", "GSM2069842", "GSM2069843", "GSM2069844", "GSM2069845", "GSM2069846", "GSM2069847", "GSM2069848", "GSM2069849", "GSM2069850"], "sample_count": 28, "group_sizes": null, "group_sizes_basis": null, "platform": "11154", "taxon": "Homo sapiens", "title": "mRNA expressions in pre-treatment melanomas undergoing anti-PD-1 checkpoint inhibition therapy", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE131907 not downloaded", "asset:data:geo:GSE131907 licence not read", "asset:data:geo:GSE68465 not downloaded", "asset:data:geo:GSE68465 licence not read", "asset:data:geo:GSE78220 not downloaded", "asset:data:geo:GSE78220 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "Scissor algorithm", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022)."}}], "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": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (Scissor algorithm), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "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": ["GSE131907", "GSE68465", "GSE78220"], "resolved_accessions": ["GSE131907", "GSE68465", "GSE78220"], "statements": ["The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."], "basis": "The paper names GSE131907, GSE68465, GSE78220 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:37091977", "data:geo:GSE131907"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE131907"]}, "gaps": ["method:not_determinable"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:37:27Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 13071, "completion_tokens": 2235, "cached_tokens": 264}}, "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:37091977", "type": "paper", "label": "pmid:37091977"}, {"id": "source:pmid:37091977", "type": "manuscript", "label": "PMID 37091977 full text"}, {"id": "data:geo:GSE131907", "type": "dataset", "label": "GEO GSE131907"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37091977", "type": "paper", "label": "pmid:37091977"}, {"id": "source:pmid:37091977", "type": "manuscript", "label": "PMID 37091977 full text"}, {"id": "data:geo:GSE131907", "type": "dataset", "label": "GEO GSE131907"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37091977", "type": "extraction", "used": ["source:pmid:37091977"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE131907", "type": "accession_resolution", "used": ["data:geo:GSE131907"], "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:37091977", "parent_hash": "sha256:78d2c4471d5afd3c1585582f71c94a6da6f898c816b74f6c2e261243dd00fc6f", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:GSE131907 licence not read", "asset:data:geo:GSE131907 not downloaded", "asset:data:geo:GSE68465 licence not read", "asset:data:geo:GSE68465 not downloaded", "asset:data:geo:GSE78220 licence not read", "asset:data:geo:GSE78220 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ed and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cell"], "order_basis": "paper_text_order:2235", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["2 Materials and methods 2.3 Single cell RNA-seq data processing Three quality measures were"], "order_basis": "paper_text_order:2770", "id": "assay:2"}]}