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pmid:32612640

An Analysis Regarding the Association Between the ISLR Gene and Gastric Carcinogenesis.

Shu Li · Wei Zhao · Manyi Sun

Frontiers in genetics · 2020 doi:10.3389/fgene.2020.00620

Paper

complete

Experiment

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Data

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Execution

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title
An Analysis Regarding the Association Between the ISLR Gene and Gastric Carcinogenesis.
doi
10.3389/fgene.2020.00620
pmid
32612640
authors array · 3 items
[0]
Shu Li
[1]
Wei Zhao
[2]
Manyi Sun
journal
Frontiers in genetics
year
2020
abstract
For datasets of gastric cancer collected by TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) repositories, we applied a bioinformatics approach to obtain expression data for the ISLR (immunoglobulin superfamily containing leucine-rich repeat) gene, which is highly expressed in gastric cancer tissues and closely associated with clinical prognosis. Although we did not observe an overall association of ISLR mutation, high expression or copy number variation with survival, hypomethylation of four methylated sites (assessed by the probes cg05195566, cg17258195, cg09664357, and cg07297039) of ISLR was negatively correlated with high expression levels of ISLR and was associated with poor clinical prognosis. In addition, we detected a correlation between ISLR expression and the infiltration levels of several immune cells, especially CD8+ T cells, macrophages and dendritic cells. We also identified a series of genes that were positively and negatively correlated with ISLR expression based on the TCGA-STAD, GSE13861, and GSE29272 datasets. Principal component analysis and random forest analysis were employed to further screen for six hub genes, including ISLR, COL1A2, CDH11, SPARC, COL3A1, and COL1A1, which exhibited a good ability to differentiate between tumor and normal samples. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and gene set enrichment analysis data also suggested a potential relationship between ISLR gene expression and epithelial-mesenchymal transition (EMT). ISLR expression was negatively correlated with sensitivity to PX-12 and NSC632839. Taken together, these results show that the ISLR gene is involved in gastric carcinogenesis, and the underlying molecular mechanisms may include DNA methylation, EMT, and immune cell infiltration.
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We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016).
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sections[4] "Survival Curve Analysis" paragraph 2
quote
We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016).
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sections[23] "Data Availability Statement" paragraph 2
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The datasets generated for this study are available on request to the corresponding author.
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GSM723466
[3]
GSM723467
[4]
GSM723468
[5]
GSM723469
[6]
GSM723470
[7]
GSM723471
[8]
GSM723472
[9]
GSM723473
[10]
GSM723474
[11]
GSM723475
[12]
GSM723476
[13]
GSM723477
[14]
GSM723478
[15]
GSM723479
[16]
GSM723480
[17]
GSM723481
[18]
GSM723482
[19]
GSM723483
[20]
GSM723484
[21]
GSM723485
[22]
GSM723486
[23]
GSM723487
[24]
GSM723488
[25]
GSM723489
[26]
GSM723490
[27]
GSM723491
[28]
GSM723492
[29]
GSM723493
[30]
GSM723494
[31]
GSM723495
[32]
GSM723496
[33]
GSM723497
[34]
GSM723498
[35]
GSM723499
[36]
GSM723500
[37]
GSM723501
[38]
GSM723502
[39]
GSM723503
[40]
GSM723504
[41]
GSM723505
[42]
GSM723506
[43]
GSM723507
[44]
GSM723508
[45]
GSM723509
[46]
GSM723510
[47]
GSM723511
[48]
GSM723512
[49]
GSM723513
[50]
GSM723514
[51]
GSM723515
[52]
GSM723516
[53]
GSM723517
[54]
GSM723518
[55]
GSM723519
[56]
GSM723520
[57]
GSM723521
[58]
GSM723522
[59]
GSM723523
[60]
GSM723524
[61]
GSM723525
[62]
GSM723526
[63]
GSM723527
[64]
GSM723528
[65]
GSM723529
[66]
GSM723530
[67]
GSM723531
[68]
GSM723532
[69]
GSM723533
[70]
GSM723534
[71]
GSM723535
[72]
GSM723536
[73]
GSM723537
[74]
GSM723538
[75]
GSM723539
[76]
GSM723540
[77]
GSM723541
[78]
GSM723542
[79]
GSM723543
[80]
GSM723544
[81]
GSM723545
[82]
GSM723546
[83]
GSM723547
[84]
GSM723548
[85]
GSM723549
[86]
GSM723550
[87]
GSM723551
[88]
GSM723552
[89]
GSM723553
[90]
GSM723554
[91]
GSM723555
[92]
GSM723556
[93]
GSM723557
[94]
GSM723558
[95]
GSM723559
[96]
GSM723560
[97]
GSM723561
[98]
GSM723562
[99]
GSM723563
[100]
GSM723564
[101]
GSM723565
[102]
GSM723566
[103]
GSM723567
[104]
GSM723568
[105]
GSM723569
[106]
GSM723570
[107]
GSM723571
[108]
GSM723572
[109]
GSM723573
[110]
GSM723574
[111]
GSM723575
[112]
GSM723576
[113]
GSM723577
[114]
GSM723578
[115]
GSM723579
[116]
GSM723580
[117]
GSM723581
[118]
GSM723582
[119]
GSM723583
[120]
GSM723584
[121]
GSM723585
[122]
GSM723586
[123]
GSM723587
[124]
GSM723588
[125]
GSM723589
[126]
GSM723590
[127]
GSM723591
[128]
GSM723592
[129]
GSM723593
[130]
GSM723594
[131]
GSM723595
[132]
GSM723596
[133]
GSM723597
[134]
GSM723598
[135]
GSM723599
[136]
GSM723600
[137]
GSM723601
[138]
GSM723602
[139]
GSM723603
[140]
GSM723604
[141]
GSM723605
[142]
GSM723606
[143]
GSM723607
[144]
GSM723608
[145]
GSM723609
[146]
GSM723610
[147]
GSM723611
[148]
GSM723612
[149]
GSM723613
[150]
GSM723614
[151]
GSM723615
[152]
GSM723616
[153]
GSM723617
[154]
GSM723618
[155]
GSM723619
[156]
GSM723620
[157]
GSM723621
[158]
GSM723622
[159]
GSM723623
[160]
GSM723624
[161]
GSM723625
[162]
GSM723626
[163]
GSM723627
[164]
GSM723628
[165]
GSM723629
[166]
GSM723630
[167]
GSM723631
[168]
GSM723632
[169]
GSM723633
[170]
GSM723634
[171]
GSM723635
[172]
GSM723636
[173]
GSM723637
[174]
GSM723638
[175]
GSM723639
[176]
GSM723640
[177]
GSM723641
[178]
GSM723642
[179]
GSM723643
[180]
GSM723644
[181]
GSM723645
[182]
GSM723646
[183]
GSM723647
[184]
GSM723648
[185]
GSM723649
[186]
GSM723650
[187]
GSM723651
[188]
GSM723652
[189]
GSM723653
[190]
GSM723654
[191]
GSM723655
[192]
GSM723656
[193]
GSM723657
[194]
GSM723658
[195]
GSM723659
[196]
GSM723660
[197]
GSM723661
[198]
GSM723662
[199]
GSM723663
[200]
GSM723664
[201]
GSM723665
[202]
GSM723666
[203]
GSM723667
[204]
GSM723668
[205]
GSM723669
[206]
GSM723670
[207]
GSM723671
[208]
GSM723672
[209]
GSM723673
[210]
GSM723674
[211]
GSM723675
[212]
GSM723676
[213]
GSM723677
[214]
GSM723678
[215]
GSM723679
[216]
GSM723680
[217]
GSM723681
[218]
GSM723682
[219]
GSM723683
[220]
GSM723684
[221]
GSM723685
[222]
GSM723686
[223]
GSM723687
[224]
GSM723688
[225]
GSM723689
[226]
GSM723690
[227]
GSM723691
[228]
GSM723692
[229]
GSM723693
[230]
GSM723694
[231]
GSM723695
[232]
GSM723696
[233]
GSM723697
[234]
GSM723698
[235]
GSM723699
[236]
GSM723700
[237]
GSM723701
[238]
GSM723702
[239]
GSM723703
[240]
GSM723704
[241]
GSM723705
[242]
GSM723706
[243]
GSM723707
[244]
GSM723708
[245]
GSM723709
[246]
GSM723710
[247]
GSM723711
[248]
GSM723712
[249]
GSM723713
[250]
GSM723714
[251]
GSM723715
[252]
GSM723716
[253]
GSM723717
[254]
GSM723718
[255]
GSM723719
[256]
GSM723720
[257]
GSM723721
[258]
GSM723722
[259]
GSM723723
[260]
GSM723724
[261]
GSM723725
[262]
GSM723726
[263]
GSM723727
[264]
GSM723728
[265]
GSM723729
[266]
GSM723730
[267]
GSM723731
sample_count
268
group_sizes
null
group_sizes_basis
null
platform
96
taxon
Homo sapiens
title
Affymetrix gene expression array data for cardia and non-cardia gastric cancer samples
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:GSE51105
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=GSE51105
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE51105
version
null
note
The datasets generated for this study are available on request to the corresponding author.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets generated for this study are available on request to the corresponding author.
access_statement_kind
data_availability_statement
sample_accessions array · 94 items
[0]
GSM1238811
[1]
GSM1238812
[2]
GSM1238813
[3]
GSM1238814
[4]
GSM1238815
[5]
GSM1238816
[6]
GSM1238817
[7]
GSM1238818
[8]
GSM1238819
[9]
GSM1238820
[10]
GSM1238821
[11]
GSM1238822
[12]
GSM1238823
[13]
GSM1238824
[14]
GSM1238825
[15]
GSM1238826
[16]
GSM1238827
[17]
GSM1238828
[18]
GSM1238829
[19]
GSM1238830
[20]
GSM1238831
[21]
GSM1238832
[22]
GSM1238833
[23]
GSM1238834
[24]
GSM1238835
[25]
GSM1238836
[26]
GSM1238837
[27]
GSM1238838
[28]
GSM1238839
[29]
GSM1238840
[30]
GSM1238841
[31]
GSM1238842
[32]
GSM1238843
[33]
GSM1238844
[34]
GSM1238845
[35]
GSM1238846
[36]
GSM1238847
[37]
GSM1238848
[38]
GSM1238849
[39]
GSM1238850
[40]
GSM1238851
[41]
GSM1238852
[42]
GSM1238853
[43]
GSM1238854
[44]
GSM1238855
[45]
GSM1238856
[46]
GSM1238857
[47]
GSM1238858
[48]
GSM1238859
[49]
GSM1238860
[50]
GSM1238861
[51]
GSM1238862
[52]
GSM1238863
[53]
GSM1238864
[54]
GSM1238865
[55]
GSM1238866
[56]
GSM1238867
[57]
GSM1238868
[58]
GSM1238869
[59]
GSM1238870
[60]
GSM1238871
[61]
GSM1238872
[62]
GSM1238873
[63]
GSM1238874
[64]
GSM1238875
[65]
GSM1238876
[66]
GSM1238877
[67]
GSM1238878
[68]
GSM1238879
[69]
GSM1238880
[70]
GSM1238881
[71]
GSM1238882
[72]
GSM1238883
[73]
GSM1238884
[74]
GSM1238885
[75]
GSM1238886
[76]
GSM1238887
[77]
GSM1238888
[78]
GSM1238889
[79]
GSM1238890
[80]
GSM1238891
[81]
GSM1238892
[82]
GSM1238893
[83]
GSM1238894
[84]
GSM1238895
[85]
GSM1238896
[86]
GSM1238897
[87]
GSM1238898
[88]
GSM1238899
[89]
GSM1238900
[90]
GSM1238901
[91]
GSM1238902
[92]
GSM1238903
[93]
GSM1238904
sample_count
94
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
A signature predicting poor prognosis in gastric and ovarian cancer represents a coordinated macrophage and stromal-response.
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 · 16 fields
id
asset:table:pmid:32612640:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:5d4210ee2e939df44fbd5d9913849d9809dcb7dda70f83920512eb05c4d88898
bytes
1760
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[1]#T1
version
null
note
Correlation of ISLR expression and the overall survival of gastric cancer patients in the GEO cohort (Kaplan–Meier plotter).
structure object · 5 fields
pmcid
PMC7308588
section_index
14
section_title
Survival Curve Analysis Data
row_count
28
column_count
6
table object · 8 fields
label
TABLE 1
caption
Correlation of ISLR expression and the overall survival of gastric cancer patients in the GEO cohort (Kaplan–Meier plotter).
rows array · 28 items
[0] array · 6 items
[0]
Factor
[1]
Group
[2]
Sample size
[3]
HR
[4]
95% CI
[5]
logRank_P
[1] array · 6 items
[0]
Gender
[1]
Female
[2]
244
[3]
2.4
[4]
1.57–3.68
[5]
3.2E-05
[2] array · 6 items
[0]
[1]
Male
[2]
567
[3]
2.02
[4]
1.58–2.59
[5]
1.2E-08
[3] array · 6 items
[0]
Stage
[1]
Stage 1
[2]
69
[3]
2.7
[4]
0.9–8.07
[5]
0.065
[4] array · 6 items
[0]
[1]
Stage 2
[2]
145
[3]
2.04
[4]
1.11–3.74
[5]
0.019
[5] array · 6 items
[0]
[1]
Stage 3
[2]
319
[3]
2.72
[4]
1.84–4.03
[5]
1.9E-07
[6] array · 6 items
[0]
[1]
Stage 4
[2]
152
[3]
1.82
[4]
1.22–2.71
[5]
0.0029
[7] array · 6 items
[0]
Stage T
[1]
T2
[2]
253
[3]
1.7
[4]
1.12–2.6
[5]
0.013
[8] array · 6 items
[0]
[1]
T3
[2]
208
[3]
1.93
[4]
1.33–2.95
[5]
6.0E-04
[9] array · 6 items
[0]
[1]
T4
[2]
39
[3]
2.66
[4]
1.06–6.68
[5]
0.032
[10] array · 6 items
[0]
Stage N
[1]
N0
[2]
76
[3]
2.95
[4]
1.13–7.69
[5]
0.021
[11] array · 6 items
[0]
[1]
N1
[2]
232
[3]
2.74
[4]
1.78–4.21
[5]
1.8E-06
[12] array · 6 items
[0]
[1]
N2
[2]
129
[3]
3.15
[4]
1.88–5.27
[5]
4.9E-06
[13] array · 6 items
[0]
[1]
N3
[2]
76
[3]
2.08
[4]
1.18–3.67
[5]
0.0097
[14] array · 6 items
[0]
[1]
N1 + 2 + 3
[2]
437
[3]
2.22
[4]
1.69–2.90
[5]
2.9E-09
[15] array · 6 items
[0]
Stage M
[1]
M0
[2]
459
[3]
2.67
[4]
1.44–4.96
[5]
0.0012
[16] array · 6 items
[0]
[1]
M1
[2]
58
[3]
2.12
[4]
1.59–2.82
[5]
1.6E-07
[17] array · 6 items
[0]
HER2
[1]
Negative
[2]
641
[3]
2.09
[4]
1.61–2.72
[5]
1.3E-08
[18] array · 6 items
[0]
[1]
Positive
[2]
425
[3]
1.74
[4]
1.26–2.39
[5]
0.00058
[19] array · 6 items
[0]
Lauren classification
[1]
Intestinal
[2]
336
[3]
2.85
[4]
2.00–4.08
[5]
1.7E-09
[20] array · 6 items
[0]
[1]
Diffuse
[2]
248
[3]
1.94
[4]
1.36–2.77
[5]
0.00018
[21] array · 6 items
[0]
[1]
Mixed
[2]
33
[3]
3.31
[4]
1.17–9.42
[5]
0.018
[22] array · 6 items
[0]
Differentiation
[1]
Poor
[2]
166
[3]
1.31
[4]
0.86–2.01
[5]
0.21
[23] array · 6 items
[0]
[1]
Moderate
[2]
67
[3]
1.75
[4]
0.92–3.34
[5]
0.086
[24] array · 6 items
[0]
[1]
Well
[2]
32
[3]
5.97
[4]
2.25–15.85
[5]
6.1E-05
[25] array · 6 items
[0]
Treatment
[1]
Surgery alone
[2]
393
[3]
1.59
[4]
1.19–2.13
[5]
0.0017
[26] array · 6 items
[0]
[1]
5-Fu based adjuvant
[2]
158
[3]
0.63
[4]
0.44–0.91
[5]
0.013
[27] array · 6 items
[0]
[1]
Other adjuvant
[2]
80
[3]
3.13
[4]
1.30–7.52
[5]
0.0072
locator
section[14]/table-wrap[1]#T1
[7] object · 16 fields
id
asset:table:pmid:32612640:2
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:f18636d686c6113744aa4358deb2c172f577087089bf30ddcc7256bab1746f0a
bytes
769
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[2]#T2
version
null
note
Correlation of ISLR expression and the clinical prognosis of gastric cancer patients in the TCGA-STAD cohort (Cox proportional hazard model).
structure object · 5 fields
pmcid
PMC7308588
section_index
14
section_title
Survival Curve Analysis Data
row_count
10
column_count
5
table object · 8 fields
label
TABLE 2
caption
Correlation of ISLR expression and the clinical prognosis of gastric cancer patients in the TCGA-STAD cohort (Cox proportional hazard model).
rows array · 10 items
[0] array · 5 items
[0]
Factor
[1]
HR
[2]
95% CI_up
[3]
95% CI_down
[4]
Cox_P
[1] array · 5 items
[0]
ISLR
[1]
1.161
[2]
1.026
[3]
1.314
[4]
0.018
[2] array · 5 items
[0]
Purity
[1]
0.638
[2]
0.304
[3]
1.338
[4]
0.234
[3] array · 5 items
[0]
Age
[1]
1.032
[2]
1.011
[3]
1.052
[4]
0.002
[4] array · 5 items
[0]
Gender (male)
[1]
1.133
[2]
0.754
[3]
1.702
[4]
0.549
[5] array · 5 items
[0]
Race (Black)
[1]
1.619
[2]
0.657
[3]
3.992
[4]
0.295
[6] array · 5 items
[0]
Race (White)
[1]
1.109
[2]
0.681
[3]
1.806
[4]
0.679
[7] array · 5 items
[0]
Clinical stage2
[1]
1.471
[2]
0.679
[3]
3.188
[4]
0.328
[8] array · 5 items
[0]
Clinical stage3
[1]
2.428
[2]
1.190
[3]
4.954
[4]
0.015
[9] array · 5 items
[0]
Clinical stage4
[1]
3.813
[2]
1.422
[3]
10.223
[4]
0.008
locator
section[14]/table-wrap[2]#T2
gaps array · 10 items
[0]
asset:data:geo:GSE14210 not downloaded
[1]
asset:data:geo:GSE14210 licence not read
[2]
asset:data:geo:GSE15459 not downloaded
[3]
asset:data:geo:GSE15459 licence not read
[4]
asset:data:geo:GSE22377 not downloaded
[5]
asset:data:geo:GSE22377 licence not read
[6]
asset:data:geo:GSE29272 not downloaded
[7]
asset:data:geo:GSE29272 licence not read
[8]
asset:data:geo:GSE51105 not downloaded
[9]
asset:data:geo:GSE51105 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
family
principal_component_analysis
specific
pca
label
Principal component analysis
dsl_operations array · 1 item
[0]
pca_fit
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
wide_numeric_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
Principal component analysis
[1] object · 10 fields
id
method-2
family
machine_learning
specific
random_forest
label
Machine learning
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
machine_learning_random_forest
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
random forest
[2] object · 10 fields
id
method-3
family
correlation_analysis
specific
pearson
label
Correlation analysis
dsl_operations array · 1 item
[0]
pearson_r
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
band
high
quote
Pearson correlation
[3] object · 10 fields
id
method-4
family
null
specific
null
label
Kaplan–Meier survival analysis
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016).
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
pca_fit
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pca.
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 · 6 items
[0]
GSE14210
[1]
GSE15459
[2]
GSE22377
[3]
GSE29272
[4]
GSE51105
[5]
and GSE62254
resolved_accessions array · 5 items
[0]
GSE14210
[1]
GSE15459
[2]
GSE22377
[3]
GSE29272
[4]
GSE51105
statements array · 1 item
[0]
The datasets generated for this study are available on request to the corresponding author.
basis
The paper names GSE14210, GSE15459, GSE22377, GSE29272, GSE51105 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 · 1 item
[0]
pca_fit
assets array · 4 items
[0]
source:pmid:32612640
[1]
data:geo:GSE14210
[2]
asset:table:pmid:32612640:1
[3]
asset:table:pmid:32612640:2
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:GSE14210
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:21:08Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
30546
completion_tokens
2332
cached_tokens
785
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:32612640
type
paper
label
pmid:32612640
[1] object · 3 fields
id
source:pmid:32612640
type
manuscript
label
PMID 32612640 full text
[2] object · 3 fields
id
data:geo:GSE14210
type
dataset
label
GEO GSE14210
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:32612640
type
paper
label
pmid:32612640
[1] object · 3 fields
id
source:pmid:32612640
type
manuscript
label
PMID 32612640 full text
[2] object · 3 fields
id
data:geo:GSE14210
type
dataset
label
GEO GSE14210
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-32612640
type
extraction
used array · 1 item
[0]
source:pmid:32612640
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE14210
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE14210
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:32612640
parent_hash
sha256:d7d548696b6997f5f98e4e6bf5a45065e07db10aa8bda44d2dafa156e10cff63
fork_of
null
gaps array · 15 items
[0]
asset:data:geo:GSE14210 licence not read
[1]
asset:data:geo:GSE14210 not downloaded
[2]
asset:data:geo:GSE15459 licence not read
[3]
asset:data:geo:GSE15459 not downloaded
[4]
asset:data:geo:GSE22377 licence not read
[5]
asset:data:geo:GSE22377 not downloaded
[6]
asset:data:geo:GSE29272 licence not read
[7]
asset:data:geo:GSE29272 not downloaded
[8]
asset:data:geo:GSE51105 licence not read
[9]
asset:data:geo:GSE51105 not downloaded
[10]
execution.not_run
[11]
method.reader_named_unmapped
[12]
review.human_critique
[13]
review.independent_reader
[14]
review.machine_critique
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
principal_component_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
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pca_fit
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Principal component analysis
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32612640", "kind": "science-record", "revision": 7, "content_hash": "sha256:1d302b71260e0fbdaf31da88e2f7a428e928702728e4483cb7ba1201b680ab09", "created_at": "2026-11-01T15:41:05Z", "updated_at": "2026-11-01T22:01:50Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An Analysis Regarding the Association Between the ISLR Gene and Gastric Carcinogenesis.", "doi": "10.3389/fgene.2020.00620", "pmid": "32612640", "authors": ["Shu Li", "Wei Zhao", "Manyi Sun"], "journal": "Frontiers in genetics", "year": 2020, "abstract": "For datasets of gastric cancer collected by TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) repositories, we applied a bioinformatics approach to obtain expression data for the ISLR (immunoglobulin superfamily containing leucine-rich repeat) gene, which is highly expressed in gastric cancer tissues and closely associated with clinical prognosis. Although we did not observe an overall association of ISLR mutation, high expression or copy number variation with survival, hypomethylation of four methylated sites (assessed by the probes cg05195566, cg17258195, cg09664357, and cg07297039) of ISLR was negatively correlated with high expression levels of ISLR and was associated with poor clinical prognosis. In addition, we detected a correlation between ISLR expression and the infiltration levels of several immune cells, especially CD8+ T cells, macrophages and dendritic cells. We also identified a series of genes that were positively and negatively correlated with ISLR expression based on the TCGA-STAD, GSE13861, and GSE29272 datasets. Principal component analysis and random forest analysis were employed to further screen for six hub genes, including ISLR, COL1A2, CDH11, SPARC, COL3A1, and COL1A1, which exhibited a good ability to differentiate between tumor and normal samples. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and gene set enrichment analysis data also suggested a potential relationship between ISLR gene expression and epithelial-mesenchymal transition (EMT). ISLR expression was negatively correlated with sensitivity to PX-12 and NSC632839. Taken together, these results show that the ISLR gene is involved in gastric carcinogenesis, and the underlying molecular mechanisms may include DNA methylation, EMT, and immune cell infiltration.", "claims": [{"id": "claim-method", "statement": "We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32612640", "locator": "sections[4] \"Survival Curve Analysis\" paragraph 2", "quote": "We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated for this study are available on request to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32612640", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "The datasets generated for this study are available on request to the corresponding author."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:32612640"], "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:GSE14210"], "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:GSE14210"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32612640", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2020.00620", "sha256": 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"sha256:f18636d686c6113744aa4358deb2c172f577087089bf30ddcc7256bab1746f0a", "bytes": 769, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[2]#T2", "version": null, "note": "Correlation of ISLR expression and the clinical prognosis of gastric cancer patients in the TCGA-STAD cohort (Cox proportional hazard model).", "structure": {"pmcid": "PMC7308588", "section_index": 14, "section_title": "Survival Curve Analysis Data", "row_count": 10, "column_count": 5}, "table": {"label": "TABLE 2", "caption": "Correlation of ISLR expression and the clinical prognosis of gastric cancer patients in the TCGA-STAD cohort (Cox proportional hazard model).", "rows": [["Factor", "HR", "95% CI_up", "95% CI_down", "Cox_P"], ["ISLR", "1.161", "1.026", "1.314", "0.018"], ["Purity", "0.638", "0.304", "1.338", "0.234"], ["Age", "1.032", "1.011", "1.052", "0.002"], ["Gender (male)", "1.133", "0.754", "1.702", "0.549"], ["Race (Black)", "1.619", "0.657", "3.992", "0.295"], ["Race (White)", "1.109", "0.681", "1.806", "0.679"], ["Clinical stage2", "1.471", "0.679", "3.188", "0.328"], ["Clinical stage3", "2.428", "1.190", "4.954", "0.015"], ["Clinical stage4", "3.813", "1.422", "10.223", "0.008"]], "row_count": 10, "column_count": 5, "numeric_cells": 38, "header_rows": 1, "locator": "section[14]/table-wrap[2]#T2"}}], "gaps": ["asset:data:geo:GSE14210 not downloaded", "asset:data:geo:GSE14210 licence not read", "asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE22377 not downloaded", "asset:data:geo:GSE22377 licence not read", "asset:data:geo:GSE29272 not downloaded", "asset:data:geo:GSE29272 licence not read", "asset:data:geo:GSE51105 not downloaded", "asset:data:geo:GSE51105 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "Principal component analysis"}}, {"id": "method-2", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-3", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-4", "family": null, "specific": null, "label": "Kaplan–Meier survival analysis", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "We conducted OS (overall survival) and DFS (disease-free survival) analyses of gastric cancer cases in the TCGA-STAD cohort according to the expression status of the ISLR gene through GEPIA2. A group cutoff of “quartile” was set, and the Kaplan–Meier curve was plotted. We also pooled the gastric cancer cases in the GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 datasets for the OS, FP (first progression), and PPS (post progression survival) analyses using the Kaplan–Meier plotter tool (Szasz et al., 2016)."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pca_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pca."}, "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": ["GSE14210", "GSE15459", "GSE22377", "GSE29272", "GSE51105", "and GSE62254"], "resolved_accessions": ["GSE14210", "GSE15459", "GSE22377", "GSE29272", "GSE51105"], "statements": ["The datasets generated for this study are available on request to the corresponding author."], "basis": "The paper names GSE14210, GSE15459, GSE22377, GSE29272, GSE51105 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["pca_fit"], "assets": ["source:pmid:32612640", "data:geo:GSE14210", "asset:table:pmid:32612640:1", "asset:table:pmid:32612640:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE14210"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:21:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 30546, "completion_tokens": 2332, "cached_tokens": 785}}, "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:32612640", "type": "paper", "label": "pmid:32612640"}, {"id": "source:pmid:32612640", "type": "manuscript", "label": "PMID 32612640 full text"}, {"id": "data:geo:GSE14210", "type": "dataset", "label": "GEO GSE14210"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:32612640", "type": "paper", "label": "pmid:32612640"}, {"id": "source:pmid:32612640", "type": "manuscript", "label": "PMID 32612640 full text"}, {"id": "data:geo:GSE14210", "type": "dataset", "label": "GEO GSE14210"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-32612640", "type": "extraction", "used": ["source:pmid:32612640"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE14210", "type": "accession_resolution", "used": ["data:geo:GSE14210"], "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:32612640", "parent_hash": "sha256:d7d548696b6997f5f98e4e6bf5a45065e07db10aa8bda44d2dafa156e10cff63", "fork_of": null, "generation": 6}, "gaps": ["asset:data:geo:GSE14210 licence not read", "asset:data:geo:GSE14210 not downloaded", "asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE22377 licence not read", "asset:data:geo:GSE22377 not downloaded", "asset:data:geo:GSE29272 licence not read", "asset:data:geo:GSE29272 not downloaded", "asset:data:geo:GSE51105 licence not read", "asset:data:geo:GSE51105 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "principal_component_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pca_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Principal component analysis"], "order_basis": "analysis_only", "id": "assay:1"}]}