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pmid:33758160

Genome-Scale Analysis Identified NID2, SPARC, and MFAP2 as Prognosis Markers of Overall Survival in Gastric Cancer.

Zexing Shan · Wentao Wang · Yilin Tong · Jianjun Zhang

Medical science monitor : international medical journal of experimental and clinical research · 2021 doi:10.12659/MSM.929558

Paper

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Experiment

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title
Genome-Scale Analysis Identified NID2, SPARC, and MFAP2 as Prognosis Markers of Overall Survival in Gastric Cancer.
doi
10.12659/MSM.929558
pmid
33758160
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Zexing Shan
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Wentao Wang
[2]
Yilin Tong
[3]
Jianjun Zhang
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Medical science monitor : international medical journal of experimental and clinical research
year
2021
abstract
BACKGROUND Gastric cancer is the most common gastrointestinal tumor, and the rates of recurrence and metastasis are high. Research results on molecular biomarkers used for prognosis of gastric cancer remain inconclusive. This study aimed to explore the gene expression module of gastric cancer and to determine potential prognostic biomarkers. MATERIAL AND METHODS Three microarray datasets (GSE13911, GSE79973, and GSE29272) from Gene Expression Omnibus (GEO), including 206 pairs of gastric tumors and adjacent normal samples, were used for analysis of differentially expressed genes (DEGs). The 3 microarray datasets yielded 144 genes associated with the progression and prognosis of gastric cancer. After this, a risk score model was developed for result validation using an independent dataset from The Cancer Genome Atlas. RESULTS The validation of the independent dataset showed significantly increased NID2, SPARC, and MFAP2 expression in gastric tumor tissues, which were associated with poor outcomes in gastric cancer patients. Moreover, the high risk score obtained was associated with poor overall survival (HR: 1.787; 1.069-2.986; P=0.027). Subgroup analyses revealed that these significant prognostic values were detected in patients aged <65.0 years, tumors in the antrum/distal colon, grade 3 tumors, or TNM-M0 stages of cancer. CONCLUSIONS The findings of this study show that NID2, SPARC, and MFAP2 are upregulated in gastric tumor tissues and are significantly associated with poor overall survival. Therefore, the predictive values of the risk score model employed for the prognosis of gastric cancer could be improved by using these 3 upregulated DEGs.
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The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17].
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The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17].
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Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples. These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip). GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively. The raw probe-level data in this study were downloaded in CEL files
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Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples.
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These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip).
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GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively.
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The raw probe-level data in this study were downloaded in CEL files
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GSM2109551
sample_count
20
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Expression data from gastric cancer and paried normal tissues
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 16 fields
id
asset:table:pmid:33758160:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:7c40c5dddc8e4faf2c9ede213f8e143d26b17de739c6f3fa849de83db92cf2c8
bytes
1694
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[7]/table-wrap[1]#t1-medscimonit-27-e929558
version
null
note
Common differentially expressed genes identified in gastric cancer.
structure object · 5 fields
pmcid
PMC8006563
section_index
7
section_title
Identification of DEGs Between Gastric Tumors and Adjacent Normal Samples
row_count
50
column_count
4
table object · 8 fields
label
Table 1
caption
Common differentially expressed genes identified in gastric cancer.
rows array · 50 items
[0] array · 2 items
[0]
Regulation
[1]
DEGs (gene symbol)
[1] array · 4 items
[0]
Upregulated
[1]
APOC1
[2]
CTSB
[3]
NEK2
[2] array · 3 items
[0]
APOE
[1]
CXCL8
[2]
NID2
[3] array · 3 items
[0]
ASPM
[1]
ECT2
[2]
NT5DC2
[4] array · 3 items
[0]
ASPN
[1]
FAP
[2]
OLFML2B
[5] array · 3 items
[0]
BGN
[1]
FBN1
[2]
PMEPA1
[6] array · 3 items
[0]
CAMK2N1
[1]
FCER1G
[2]
PRC1
[7] array · 3 items
[0]
CDH11
[1]
FN1
[2]
RAB31
[8] array · 3 items
[0]
CEMIP
[1]
GPNMB
[2]
RARRES1
[9] array · 3 items
[0]
CEP55
[1]
HOXC6
[2]
S100A10
[10] array · 3 items
[0]
COL10A1
[1]
IGF2BP3
[2]
SERPINH1
[11] array · 3 items
[0]
COL11A1
[1]
IGFBP7
[2]
SFRP4
[12] array · 3 items
[0]
COL1A1
[1]
INHBA
[2]
SPARC
[13] array · 3 items
[0]
COL1A2
[1]
KPNA2
[2]
SPP1
[14] array · 3 items
[0]
COL3A1
[1]
LEF1
[2]
SULF1
[15] array · 3 items
[0]
COL4A1
[1]
LOC100129518///SOD2
[2]
THBS1
[16] array · 3 items
[0]
COL4A2
[1]
LOC101928916///NNMT
[2]
THBS2
[17] array · 3 items
[0]
COL5A1
[1]
LY6E
[2]
THY1
[18] array · 3 items
[0]
COL5A2
[1]
MEST
[2]
TIMP1
[19] array · 3 items
[0]
COL6A3
[1]
MFAP2
[2]
TOP2A
[20] array · 3 items
[0]
CSE1L
[1]
CST1
[2]
VCAN
[21] array · 3 items
[0]
MIR1292///SNORD110///SNORD86///SNORD57///NOP56
[1]
[2]
[22] array · 4 items
[0]
Downregulated
[1]
AADAC
[2]
COL2A1
[3]
KCNE2
[23] array · 3 items
[0]
ADAM28
[1]
CPA2
[2]
KCNJ15
[24] array · 3 items
[0]
ADGRG2
[1]
CYP2C18
[2]
KCNJ16
[25] array · 3 items
[0]
ADH1C
[1]
DGKD
[2]
KIAA1324
[26] array · 3 items
[0]
AKR1B10
[1]
EPB41L4B
[2]
KLF4
[27] array · 3 items
[0]
AKR1C1
[1]
ESRRG
[2]
KRT20
[28] array · 3 items
[0]
AKR7A3
[1]
ETNPPL
[2]
LIPF
[29] array · 3 items
[0]
ALDH1A1
[1]
FA2H
[2]
LOC101930400///AKR1C2
[30] array · 3 items
[0]
ALDH3A1
[1]
FBP2
[2]
LTF
[31] array · 3 items
[0]
ALDH6A1
[1]
FCGBP
[2]
MAOA
[32] array · 3 items
[0]
ATP4A
[1]
FMO5
[2]
METTL7A
[33] array · 3 items
[0]
ATP4B
[1]
FOLR1
[2]
MT1E
[34] array · 3 items
[0]
AZGP1
[1]
GC
[2]
MT1F
[35] array · 3 items
[0]
AZGP1P1///AZGP1
[1]
GIF
[2]
MT1G
[36] array · 3 items
[0]
CA2
[1]
GKN1
[2]
MT1H
[37] array · 3 items
[0]
CA9
[1]
GPRC5C
[2]
MT1HL1
[38] array · 3 items
[0]
CAPN9
[1]
GSTA1
[2]
MT1M
[39] array · 3 items
[0]
CCKBR
[1]
HDC
[2]
MT1X
[40] array · 3 items
[0]
CHGA
[1]
HPGD
[2]
MT2A
[41] array · 3 items
[0]
CHIA
[1]
IGH
[2]
MUC5AC
[42] array · 3 items
[0]
CKM
[1]
IGHA2///IGHA1///IGH
[2]
MYOC
[43] array · 3 items
[0]
CKMT2
[1]
JCHAIN
[2]
MYRF
[44] array · 3 items
[0]
NEDD4L
[1]
PIK3C2G
[2]
SLC16A7
[45] array · 3 items
[0]
PBLD
[1]
PXMP2
[2]
SLC28A2
[46] array · 3 items
[0]
PDGFD
[1]
RNASE1
[2]
SOSTDC1
[47] array · 3 items
[0]
PGA4///PGA3///PGA5
[1]
S100P
[2]
SULT1C2
[48] array · 3 items
[0]
PGC
[1]
UGT2B15
[2]
TMPRSS2
[49] array · 3 items
[0]
XK
[1]
XYLT2
[2]
locator
section[7]/table-wrap[1]#t1-medscimonit-27-e929558
[5] object · 16 fields
id
asset:table:pmid:33758160:2
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:9282bffd937dae9427b1bdb2f555134423895f3f401f822dba9e14e929b124a4
bytes
4748
access
open
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verified
reader
read_table
reader_status
available
identifier
section[8]/table-wrap[1]#t2-medscimonit-27-e929558
version
null
note
GO analysis of the 144 differentially expressed genes.
structure object · 5 fields
pmcid
PMC8006563
section_index
8
section_title
Functional Enrichment Analysis of DEGs
row_count
22
column_count
7
table object · 8 fields
label
Table 2
caption
GO analysis of the 144 differentially expressed genes.
rows array · 22 items
[0] array · 7 items
[0]
Category
[1]
Term
[2]
Count
[3]
P value
[4]
Benjamini
[5]
FDR
[6]
Genes
[1] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0030198 ~extracellular matrix organization
[2]
21
[3]
5.81E-17
[4]
1.15E-13
[5]
1.78E-13
[6]
COL4A2, COL4A1, OLFML2B, COL3A1, FBN1, COL2A1, SPARC, NID2, COL5A2, COL5A1, BGN, COL6A3, COL1A2, MFAP2, VCAN, COL1A1, THBS1, COL11A1, SPP1, FN1, COL10A1
[2] array · 7 items
[0]
GOTERM_MF_DIRECT
[1]
GO: 0005201 ~extracellular matrix structural constituent
[2]
13
[3]
9.89E-14
[4]
3.07E-11
[5]
1.33E-10
[6]
COL4A2, BGN, COL4A1, COL3A1, FBN1, COL1A2, COL2A1, VCAN, COL1A1, MUC5AC, COL5A2, COL11A1, COL5A1
[3] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005576 ~extracellular region
[2]
42
[3]
4.25E-13
[4]
7.69E-11
[5]
5.24E-10
[6]
GC, CHIA, IGFBP7, COL3A1, JCHAIN, APOC1, CXCL8, COL2A1, TIMP1, AZGP1, APOE, COL6A3, CPA2, LTF, PDGFD, THBS1, COL11A1, THBS2, SPP1, COL10A1, FN1, ADAM28, COL4A2, COL4A1, OLFML2B, FBN1, GIF, NID2, SPARC, COL5A2, COL5A1, INHBA, BGN, SFRP4, CEMIP, COL1A2, VCAN, MFAP2, COL1A1, CTSB, MUC5AC, LIPF
[4] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0031012 ~extracellular matrix
[2]
20
[3]
5.14E-13
[4]
4.65E-11
[5]
6.33E-10
[6]
ASPN, COL4A2, COL4A1, IGFBP7, COL3A1, FBN1, COL2A1, NID2, COL5A2, COL5A1, BGN, APOE, COL6A3, COL1A2, VCAN, COL1A1, THBS1, THBS2, MYOC, FN1
[5] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005615 ~extracellular space
[2]
38
[3]
8.88E-13
[4]
5.36E-11
[5]
1.10E-09
[6]
GC, CHIA, PGC, IGFBP7, COL3A1, JCHAIN, CXCL8, COL2A1, SERPINH1, ALDH3A1, TIMP1, AZGP1, APOE, SOSTDC1, FAP, COL6A3, CPA2, LTF, PDGFD, THBS1, MYOC, SPP1, FN1, ATP4A, FBN1, GIF, CST1, SPARC, CHGA, SFRP4, SULF1, COL1A2, VCAN, COL1A1, CTSB, MUC5AC, CA2, GKN1
[6] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0030574 ~collagen catabolic process
[2]
12
[3]
2.42E-12
[4]
1.26E-09
[5]
3.85E-09
[6]
COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, CTSB, COL11A1, COL5A2, COL5A1, COL10A1
[7] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0070062 ~extracellular exosome
[2]
51
[3]
3.44E-10
[4]
1.56E-08
[5]
4.24E-07
[6]
RARRES1, PGC, IGFBP7, KIAA1324, AZGP1, APOE, LTF, AKR7A3, PDGFD, AKR1C1, ALDH6A1, FBP2, METTL7A, THY1, BGN, AKR1B10, COL1A2, CTSB, CA2, GC, GPRC5C, JCHAIN, APOC1, SERPINH1, PBLD, TIMP1, ALDH1A1, CSE1L, FOLR1, COL6A3, SULT1C2, NEDD4L, THBS1, MYOC, SPP1, FN1, MEST, GSTA1, TMPRSS2, RNASE1, COL4A2, S100P, FBN1, S100A10, NID2, ADGRG2, COL5A1, MUC5AC, FCGBP, HPGD, CDH11
[8] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005581 ~collagen trimer
[2]
11
[3]
1.32E-09
[4]
4.79E-08
[5]
1.63E-06
[6]
COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, COL11A1, SERPINH1, COL5A2, COL5A1, COL10A1, TIMP1
[9] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005788 ~endoplasmic reticulum lumen
[2]
14
[3]
1.55E-09
[4]
4.68E-08
[5]
1.91E-06
[6]
COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, PDGFD, THBS1, SERPINH1, COL5A2, COL11A1, COL5A1, COL10A1
[10] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0071294~cellular response to zinc ion
[2]
7
[3]
5.25E-09
[4]
1.82E-06
[5]
8.34E-06
[6]
MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F
[11] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0045926~negative regulation of growth
[2]
7
[3]
5.25E-09
[4]
1.82E-06
[5]
8.34E-06
[6]
MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F
[12] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005578 ~proteinaceous extracellular matrix
[2]
15
[3]
1.01E-08
[4]
2.62E-07
[5]
1.25E-05
[6]
ASPN, OLFML2B, FBN1, SPARC, COL5A2, COL5A1, TIMP1, BGN, COL6A3, COL1A2, VCAN, COL11A1, MYOC, FN1, COL10A1
[13] array · 7 items
[0]
GOTERM_MF_DIRECT
[1]
GO: 0048407 ~platelet-derived growth factor binding
[2]
6
[3]
1.07E-08
[4]
1.66E-06
[5]
1.44E-05
[6]
COL4A1, COL3A1, COL1A2, COL2A1, COL1A1, COL5A1
[14] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0030199~collagen fibril organization
[2]
8
[3]
1.97E-08
[4]
5.12E-06
[5]
3.13E-05
[6]
COL3A1, COL1A2, COL2A1, COL1A1, COL11A1, SERPINH1, COL5A2, COL5A1
[15] array · 7 items
[0]
GOTERM_MF_DIRECT
[1]
GO: 0050840 ~extracellular matrix binding
[2]
6
[3]
1.39E-06
[4]
1.44E-04
[5]
0.001872262
[6]
BGN, OLFML2B, SPARC, THBS1, COL11A1, SPP1
[16] array · 7 items
[0]
GOTERM_CC_DIRECT
[1]
GO: 0005604 ~basement membrane
[2]
8
[3]
1.76E-06
[4]
3.99E-05
[5]
0.002172174
[6]
COL4A1, FBN1, COL2A1, NID2, SPARC, THBS2, COL5A1, TIMP1
[17] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0007155 ~cell adhesion
[2]
16
[3]
3.26E-06
[4]
6.77E-04
[5]
0.005182285
[6]
ATP4B, IGFBP7, NID2, COL5A1, THY1, AZGP1, FAP, COL6A3, VCAN, COL1A1, THBS1, GPNMB, THBS2, SPP1, FN1, CDH11
[18] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0071276~cellular response to cadmium ion
[2]
5
[3]
8.02E-06
[4]
0.001386589
[5]
0.012731623
[6]
MT1E, MT1H, MT1X, MT1G, MT1F
[19] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0007586~digestion
[2]
7
[3]
9.91E-06
[4]
0.001467951
[5]
0.015725541
[6]
CHIA, CCKBR, PGC, AKR1B10, CAPN9, GKN1, AKR1C1
[20] array · 7 items
[0]
GOTERM_BP_DIRECT
[1]
GO: 0001501~skeletal system development
[2]
9
[3]
1.26E-05
[4]
0.001632159
[5]
0.019983654
[6]
COL3A1, FBN1, COL1A2, COL2A1, VCAN, COL1A1, COL5A2, COL10A1, CDH11
[21] array · 7 items
[0]
GOTERM_MF_DIRECT
[1]
GO: 0005178 ~integrin binding
[2]
8
[3]
1.58E-05
[4]
0.001223983
[5]
0.021220906
[6]
FAP, COL3A1, FBN1, THBS1, GPNMB, COL5A1, FN1, THY1
locator
section[8]/table-wrap[1]#t2-medscimonit-27-e929558
[6] object · 16 fields
id
asset:table:pmid:33758160:3
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table
format
jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:69b1c22dc1299a386761a5b9771c4aa4492890bee9cf90ed170544d4492987cf
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2311
access
open
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verified
reader
read_table
reader_status
available
identifier
section[8]/table-wrap[2]#t3-medscimonit-27-e929558
version
null
note
KEGG pathway enrichment analysis of the 144 differentially expressed genes.
structure object · 5 fields
pmcid
PMC8006563
section_index
8
section_title
Functional Enrichment Analysis of DEGs
row_count
15
column_count
6
table object · 8 fields
label
Table 3
caption
KEGG pathway enrichment analysis of the 144 differentially expressed genes.
rows array · 15 items
[0] array · 6 items
[0]
Category
[1]
Term
[2]
Count
[3]
P value
[4]
FDR
[5]
Genes
[1] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04512: ECM-receptor interaction
[2]
14
[3]
3.93E-12
[4]
4.53E-09
[5]
COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1
[2] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04974: Protein digestion and absorption
[2]
12
[3]
1.48E-09
[4]
1.70E-06
[5]
COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, CPA2, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1, COL10A1
[3] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04510: Focal adhesion
[2]
15
[3]
2.34E-08
[4]
2.69E-05
[5]
COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, PDGFD, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1
[4] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa05146: Amoebiasis
[2]
11
[3]
1.36E-07
[4]
1.57E-04
[5]
COL4A2, COL4A1, COL3A1, COL1A2, CXCL8, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1, FN1
[5] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04978: Mineral absorption
[2]
7
[3]
5.95E-06
[4]
0.006851
[5]
MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F
[6] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04151: PI3K-Akt signaling pathway
[2]
15
[3]
1.22E-05
[4]
0.014013
[5]
COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, PDGFD, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1
[7] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04971: Gastric acid secretion
[2]
7
[3]
1.13E-04
[4]
0.129558
[5]
KCNJ16, KCNJ15, CCKBR, ATP4A, ATP4B, KCNE2, CA2
[8] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04611: Platelet activation
[2]
8
[3]
4.23E-04
[4]
0.486191
[5]
COL3A1, COL1A2, FCER1G, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1
[9] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa00982: Drug metabolism – cytochrome P450
[2]
6
[3]
7.27E-04
[4]
0.833392
[5]
GSTA1, FMO5, MAOA, ADH1C, UGT2B15, ALDH3A1
[10] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa00980: Metabolism of xenobiotics by cytochrome P450
[2]
6
[3]
0.001069
[4]
1.223788
[5]
GSTA1, ADH1C, AKR7A3, UGT2B15, AKR1C1, ALDH3A1
[11] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa05204: Chemical carcinogenesis
[2]
5
[3]
0.010061
[4]
10.99085
[5]
GSTA1, CYP2C18, ADH1C, UGT2B15, ALDH3A1
[12] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa00340: Histidine metabolism
[2]
3
[3]
0.022373
[4]
22.93516
[5]
HDC, MAOA, ALDH3A1
[13] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa00830: Retinol metabolism
[2]
4
[3]
0.030117
[4]
29.67766
[5]
ALDH1A1, CYP2C18, ADH1C, UGT2B15
[14] array · 6 items
[0]
KEGG_PATHWAY
[1]
hsa04966: Collecting duct acid secretion
[2]
3
[3]
0.032861
[4]
31.93507
[5]
ATP4A, ATP4B, CA2
locator
section[8]/table-wrap[2]#t3-medscimonit-27-e929558
[7] object · 16 fields
id
asset:table:pmid:33758160:4
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:e4c41a93e7f409baaa92c010208510b57a1681845baf2b0803ec75acdf4fa72e
bytes
2441
access
open
state
verified
reader
read_table
reader_status
available
identifier
section[10]/table-wrap[1]#t4-medscimonit-27-e929558
version
null
note
Baseline characteristics of patients in high and low risk score groups.
structure object · 5 fields
pmcid
PMC8006563
section_index
10
section_title
Risk Score and Overall Survival for Patients with Gastric Cancer
row_count
37
column_count
7
table object · 8 fields
label
Table 4
caption
Baseline characteristics of patients in high and low risk score groups.
rows array · 37 items
[0] array · 3 items
[0]
[1]
Pre-propensity score matching
[2]
Post-propensity score matching
[1] array · 6 items
[0]
Low
[1]
High
[2]
P
[3]
Low
[4]
High
[5]
P
[2] array · 7 items
[0]
Age, median (Q1, Q3)
[1]
67.00 (58.00,72.00)
[2]
67.00 (58.00,72.00)
[3]
0.960
[4]
67.00 (58.00,72.00)
[5]
68.00 (59.00,72.00)
[6]
0.617
[3] array · 7 items
[0]
Gender
[1]
[2]
[3]
[4]
[5]
[6]
[4] array · 7 items
[0]
Female
[1]
55 (33.13)
[2]
62 (37.13)
[3]
0.445
[4]
49 (35.51)
[5]
50 (36.23)
[6]
0.900
[5] array · 5 items
[0]
Male
[1]
111 (66.87)
[2]
105 (62.87)
[3]
89 (64.49)
[4]
88 (63.77)
[6] array · 7 items
[0]
Race
[1]
[2]
[3]
[4]
[5]
[6]
[7] array · 7 items
[0]
White
[1]
96 (57.83)
[2]
114 (68.26)
[3]
0.031
[4]
89 (64.49)
[5]
92 (66.67)
[6]
0.932
[8] array · 5 items
[0]
Asian
[1]
38 (22.89)
[2]
33 (19.76)
[3]
34 (24.64)
[4]
27 (19.57)
[9] array · 5 items
[0]
Others
[1]
32 (19.28)
[2]
20 (11.98)
[3]
15 (10.87)
[4]
19 (13.77)
[10] array · 7 items
[0]
Anatomic tumor site
[1]
[2]
[3]
[4]
[5]
[6]
[11] array · 7 items
[0]
Antrum/distal
[1]
61 (36.75)
[2]
63 (37.72)
[3]
0.394
[4]
54 (39.13)
[5]
51 (36.96)
[6]
0.955
[12] array · 5 items
[0]
Fundus/body
[1]
56 (33.73)
[2]
62 (37.13)
[3]
47 (34.06)
[4]
51 (36.96)
[13] array · 5 items
[0]
Cardia/proximal
[1]
24 (14.46)
[2]
20 (11.98)
[3]
19 (13.77)
[4]
17 (12.32)
[14] array · 5 items
[0]
Gastroesophageal junction
[1]
18 (10.84)
[2]
20 (11.98)
[3]
13 (9.42)
[4]
18 (13.04)
[15] array · 5 items
[0]
Others
[1]
7 (4.22)
[2]
2 (1.20)
[3]
5 (3.62)
[4]
1 (0.72)
[16] array · 7 items
[0]
Grade
[1]
[2]
[3]
[4]
[5]
[6]
[17] array · 7 items
[0]
G1
[1]
4 (2.41)
[2]
4 (2.40)
[3]
0.930
[4]
4 (2.90)
[5]
4 (2.90)
[6]
0.917
[18] array · 5 items
[0]
G2
[1]
60 (36.14)
[2]
55 (32.93)
[3]
48 (34.78)
[4]
43 (31.16)
[19] array · 5 items
[0]
G3
[1]
98 (59.04)
[2]
103 (61.68)
[3]
83 (60.14)
[4]
87 (63.04)
[20] array · 5 items
[0]
Gx
[1]
4 (2.41)
[2]
5 (2.99)
[3]
3 (2.17)
[4]
4 (2.90)
[21] array · 7 items
[0]
TNM-T
[1]
[2]
[3]
[4]
[5]
[6]
[22] array · 7 items
[0]
T1–2
[1]
44 (26.51)
[2]
38 (22.75)
[3]
0.427
[4]
35 (25.36)
[5]
36 (26.09)
[6]
0.891
[23] array · 5 items
[0]
T3–4
[1]
122 (73.49)
[2]
129 (77.25)
[3]
103 (74.64)
[4]
102 (73.91)
[24] array · 7 items
[0]
TNM-N
[1]
[2]
[3]
[4]
[5]
[6]
[25] array · 7 items
[0]
N0
[1]
53 (31.93)
[2]
55 (32.93)
[3]
0.533
[4]
44 (31.88)
[5]
47 (34.06)
[6]
0.419
[26] array · 5 items
[0]
N1
[1]
38 (22.89)
[2]
46 (27.54)
[3]
33 (23.91)
[4]
40 (28.99)
[27] array · 5 items
[0]
N2
[1]
41 (24.70)
[2]
31 (18.56)
[3]
35 (25.36)
[4]
24 (17.39)
[28] array · 5 items
[0]
N3
[1]
34 (20.48)
[2]
35 (20.96)
[3]
26 (18.84)
[4]
27 (19.57)
[29] array · 7 items
[0]
TNM-M
[1]
[2]
[3]
[4]
[5]
[6]
[30] array · 7 items
[0]
M0
[1]
157 (94.58)
[2]
153 (91.62)
[3]
0.287
[4]
131 (94.93)
[5]
128 (92.75)
[6]
0.453
[31] array · 5 items
[0]
M1
[1]
9 (5.42)
[2]
14 (8.38)
[3]
7 (5.07)
[4]
10 (7.25)
[32] array · 7 items
[0]
Stage
[1]
[2]
[3]
[4]
[5]
[6]
[33] array · 7 items
[0]
I
[1]
29 (17.47)
[2]
15 (8.98)
[3]
0.029
[4]
22 (15.94)
[5]
15 (10.87)
[6]
0.073
[34] array · 5 items
[0]
II
[1]
42 (25.30)
[2]
62 (37.13)
[3]
38 (27.54)
[4]
55 (39.86)
[35] array · 5 items
[0]
III
[1]
75 (45.18)
[2]
67 (40.12)
[3]
63 (45.65)
[4]
50 (36.23)
[36] array · 5 items
[0]
IV
[1]
14 (8.43)
[2]
20 (11.98)
[3]
10 (7.25)
[4]
16 (11.59)
locator
section[10]/table-wrap[1]#t4-medscimonit-27-e929558
[8] object · 16 fields
id
asset:table:pmid:33758160:5
role
table
format
jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:afdf43fabfc387b9a06d411a79707e97e7690bb40a8e6dfd1c3fdf8e3f9d5c16
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1752
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verified
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read_table
reader_status
available
identifier
section[10]/table-wrap[2]#t5-medscimonit-27-e929558
version
null
note
Subgroup analyses for overall survival before and after propensity score analysis.
structure object · 5 fields
pmcid
PMC8006563
section_index
10
section_title
Risk Score and Overall Survival for Patients with Gastric Cancer
row_count
19
column_count
6
table object · 8 fields
label
Table 5
caption
Subgroup analyses for overall survival before and after propensity score analysis.
rows array · 19 items
[0] array · 4 items
[0]
Factors
[1]
Group
[2]
Before propensity score
[3]
Propensity score analysis
[1] array · 4 items
[0]
HR and 95% CI
[1]
P-value
[2]
HR and 95%CI
[3]
P-value
[2] array · 6 items
[0]
Age (years)
[1]
<65.0
[2]
2.949 (1.283–6.774)
[3]
0.011
[4]
2.840 (1.161–6.945)
[5]
0.022
[3] array · 5 items
[0]
>65.0
[1]
1.581 (0.890–2.808)
[2]
0.118
[3]
1.363 (0.725–2.562)
[4]
0.337
[4] array · 6 items
[0]
Race
[1]
White
[2]
1.700 (0.907–3.186)
[3]
0.098
[4]
1.530 (0.781–2.997)
[5]
0.215
[5] array · 5 items
[0]
Asian
[1]
8.072 (0.823–79.156)
[2]
0.073
[3]
6.308 (0.571–69.650)
[4]
0.133
[6] array · 6 items
[0]
Anatomic tumor site
[1]
Antrum/distal
[2]
3.278 (1.553–6.922)
[3]
0.002
[4]
3.018 (1.353–6.732)
[5]
0.007
[7] array · 5 items
[0]
Fundus/body
[1]
1.904 (0.805–4.504)
[2]
0.143
[3]
1.392 (0.563–3.438)
[4]
0.474
[8] array · 5 items
[0]
Position-others
[1]
1.082 (0.423–2.770)
[2]
0.869
[3]
1.133 (0.408–3.150)
[4]
0.810
[9] array · 6 items
[0]
Grade
[1]
1–2
[2]
1.933 (0.904–4.131)
[3]
0.089
[4]
1.320 (0.592–2.942)
[5]
0.497
[10] array · 5 items
[0]
3
[1]
2.376 (1.275–4.428)
[2]
0.006
[3]
2.576 (1.267–5.238)
[4]
0.009
[11] array · 6 items
[0]
TNM-T
[1]
T1–2
[2]
3.838 (1.130–13.038)
[3]
0.031
[4]
3.590 (0.937–13.760)
[5]
0.062
[12] array · 5 items
[0]
T3–4
[1]
1.856 (1.103–3.124)
[2]
0.020
[3]
1.639 (0.926–2.901)
[4]
0.090
[13] array · 6 items
[0]
TNM-N
[1]
N0–1
[2]
1.873 (0.923–3.802)
[3]
0.082
[4]
1.746 (0.840–3.627)
[5]
0.135
[14] array · 5 items
[0]
N2–3
[1]
2.127 (1.114–4.064)
[2]
0.022
[3]
1.695 (0.812–3.539)
[4]
0.160
[15] array · 6 items
[0]
TNM-M
[1]
M0
[2]
2.132 (1.274–3.567)
[3]
0.004
[4]
1.843 (1.055–3.217)
[5]
0.032
[16] array · 5 items
[0]
M1
[1]
1.103 (0.333–3.651)
[2]
0.872
[3]
1.149 (0.305–4.329)
[4]
0.837
[17] array · 6 items
[0]
Stage
[1]
I and II
[2]
2.305 (0.855–6.215)
[3]
0.099
[4]
2.291 (0.782–6.712)
[5]
0.131
[18] array · 5 items
[0]
III and IV
[1]
2.095 (1.191–3.685)
[2]
0.010
[3]
1.652 (0.893–3.055)
[4]
0.110
locator
section[10]/table-wrap[2]#t5-medscimonit-27-e929558
gaps array · 6 items
[0]
asset:data:geo:GSE13911 not downloaded
[1]
asset:data:geo:GSE13911 licence not read
[2]
asset:data:geo:GSE29272 not downloaded
[3]
asset:data:geo:GSE29272 licence not read
[4]
asset:data:geo:GSE79973 not downloaded
[5]
asset:data:geo:GSE79973 licence not read
analysis object · 4 fields
state
partial
methods array · 5 items
[0] object · 10 fields
id
method-1
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17].
[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
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
log-rank
[3] object · 10 fields
id
method-4
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
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
pathway enrichment
[4] object · 10 fields
id
method-5
family
contingency_analysis
specific
chi_square
label
Categorical (contingency table) analysis
dsl_operations array · 1 item
[0]
chi_square_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
categorical_cross_tabulation
evidence object · 3 fields
score
0.8
band
high
quote
chi-square
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
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 · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
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: limma_voom.
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]
GSE13911
[1]
GSE79973
[2]
GSE29272
resolved_accessions array · 3 items
[0]
GSE13911
[1]
GSE79973
[2]
GSE29272
statements array · 1 item
[0]
Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples. These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip). GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively. The raw probe-level data in this study were downloaded in CEL files
basis
The paper names GSE13911, GSE79973, GSE29272 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 · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 7 items
[0]
source:pmid:33758160
[1]
data:geo:GSE13911
[2]
asset:table:pmid:33758160:1
[3]
asset:table:pmid:33758160:2
[4]
asset:table:pmid:33758160:3
[5]
asset:table:pmid:33758160:4
[6]
asset:table:pmid:33758160:5
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE13911
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
2026-10-31T18:28:18Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
19594
completion_tokens
1522
cached_tokens
784
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:33758160
type
paper
label
pmid:33758160
[1] object · 3 fields
id
source:pmid:33758160
type
manuscript
label
PMID 33758160 full text
[2] object · 3 fields
id
data:geo:GSE13911
type
dataset
label
GEO GSE13911
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:33758160
type
paper
label
pmid:33758160
[1] object · 3 fields
id
source:pmid:33758160
type
manuscript
label
PMID 33758160 full text
[2] object · 3 fields
id
data:geo:GSE13911
type
dataset
label
GEO GSE13911
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33758160
type
extraction
used array · 1 item
[0]
source:pmid:33758160
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE13911
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE13911
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:33758160
parent_hash
sha256:3bff16d80642b820eb138dfede67d56dd5799475ae5111d2af66761628042a3e
fork_of
null
gaps array · 11 items
[0]
asset:data:geo:GSE13911 licence not read
[1]
asset:data:geo:GSE13911 not downloaded
[2]
asset:data:geo:GSE29272 licence not read
[3]
asset:data:geo:GSE29272 not downloaded
[4]
asset:data:geo:GSE79973 licence not read
[5]
asset:data:geo:GSE79973 not downloaded
[6]
execution.not_run
[7]
method.reader_differs_from_extractor
[8]
review.human_critique
[9]
review.independent_reader
[10]
review.machine_critique
assays array · 2 items
[0] object · 11 fields
role
data_generation
definition_id
microarray
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
ostic biomarkers. MATERIAL AND METHODS Three microarray datasets (GSE13911, GSE79973, and GSE29272)
[1]
differentially expressed genes (DEGs). The 3 microarray datasets yielded 144 genes associated with t
[2]
sted t-statistics from the linear models for microarray data [17]. Genes with |log2 fold change (FC)
order_basis
paper_text_order:442
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
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normalise_counts
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differential_expression_fit
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fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17].
order_basis
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id
assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33758160", "kind": "science-record", "revision": 9, "content_hash": "sha256:68148ed1101d332e52b8ef7616e22e9b8c14f54472c2931c90302be73491287b", "created_at": "2026-11-01T15:41:30Z", "updated_at": "2026-11-01T22:46:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Genome-Scale Analysis Identified NID2, SPARC, and MFAP2 as Prognosis Markers of Overall Survival in Gastric Cancer.", "doi": "10.12659/MSM.929558", "pmid": "33758160", "authors": ["Zexing Shan", "Wentao Wang", "Yilin Tong", "Jianjun Zhang"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2021, "abstract": "BACKGROUND Gastric cancer is the most common gastrointestinal tumor, and the rates of recurrence and metastasis are high. Research results on molecular biomarkers used for prognosis of gastric cancer remain inconclusive. This study aimed to explore the gene expression module of gastric cancer and to determine potential prognostic biomarkers. MATERIAL AND METHODS Three microarray datasets (GSE13911, GSE79973, and GSE29272) from Gene Expression Omnibus (GEO), including 206 pairs of gastric tumors and adjacent normal samples, were used for analysis of differentially expressed genes (DEGs). The 3 microarray datasets yielded 144 genes associated with the progression and prognosis of gastric cancer. After this, a risk score model was developed for result validation using an independent dataset from The Cancer Genome Atlas. RESULTS The validation of the independent dataset showed significantly increased NID2, SPARC, and MFAP2 expression in gastric tumor tissues, which were associated with poor outcomes in gastric cancer patients. Moreover, the high risk score obtained was associated with poor overall survival (HR: 1.787; 1.069-2.986; P=0.027). Subgroup analyses revealed that these significant prognostic values were detected in patients aged <65.0 years, tumors in the antrum/distal colon, grade 3 tumors, or TNM-M0 stages of cancer. CONCLUSIONS The findings of this study show that NID2, SPARC, and MFAP2 are upregulated in gastric tumor tissues and are significantly associated with poor overall survival. Therefore, the predictive values of the risk score model employed for the prognosis of gastric cancer could be improved by using these 3 upregulated DEGs.", "claims": [{"id": "claim-method", "statement": "The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33758160", "locator": "sections[5] \"Statistical Analysis\" paragraph 2", "quote": "The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples. These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip). GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively. The raw probe-level data in this study were downloaded in CEL files", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33758160", "locator": "sections[3] \"Gastric Cancer Datasets\" paragraph 2", "quote": "Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples."}, {"asset": "source:pmid:33758160", "locator": "sections[3] \"Gastric Cancer Datasets\" paragraph 2", "quote": "These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip)."}, {"asset": "source:pmid:33758160", "locator": "sections[3] \"Gastric Cancer Datasets\" paragraph 2", "quote": "GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively."}, {"asset": "source:pmid:33758160", "locator": "sections[4] \"Data Preprocessing\" paragraph 2", "quote": "The raw probe-level data in this study were downloaded in CEL files"}], "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:33758160"], "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:GSE13911"], "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:GSE13911"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33758160", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12659/MSM.929558", "sha256": "sha256:cccee2a4d2052c6d9f011e47721d80ed84f07cf57743dd427e6f3b92eedc9985", "bytes": 24018, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.12659/MSM.929558", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8006563", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13911", "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=GSE13911", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13911", "version": null, "note": "Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples. 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"SERPINH1"], ["COL11A1", "IGFBP7", "SFRP4"], ["COL1A1", "INHBA", "SPARC"], ["COL1A2", "KPNA2", "SPP1"], ["COL3A1", "LEF1", "SULF1"], ["COL4A1", "LOC100129518///SOD2", "THBS1"], ["COL4A2", "LOC101928916///NNMT", "THBS2"], ["COL5A1", "LY6E", "THY1"], ["COL5A2", "MEST", "TIMP1"], ["COL6A3", "MFAP2", "TOP2A"], ["CSE1L", "CST1", "VCAN"], ["MIR1292///SNORD110///SNORD86///SNORD57///NOP56", "", ""], ["Downregulated", "AADAC", "COL2A1", "KCNE2"], ["ADAM28", "CPA2", "KCNJ15"], ["ADGRG2", "CYP2C18", "KCNJ16"], ["ADH1C", "DGKD", "KIAA1324"], ["AKR1B10", "EPB41L4B", "KLF4"], ["AKR1C1", "ESRRG", "KRT20"], ["AKR7A3", "ETNPPL", "LIPF"], ["ALDH1A1", "FA2H", "LOC101930400///AKR1C2"], ["ALDH3A1", "FBP2", "LTF"], ["ALDH6A1", "FCGBP", "MAOA"], ["ATP4A", "FMO5", "METTL7A"], ["ATP4B", "FOLR1", "MT1E"], ["AZGP1", "GC", "MT1F"], ["AZGP1P1///AZGP1", "GIF", "MT1G"], ["CA2", "GKN1", "MT1H"], ["CA9", "GPRC5C", "MT1HL1"], ["CAPN9", "GSTA1", "MT1M"], ["CCKBR", "HDC", "MT1X"], ["CHGA", "HPGD", "MT2A"], ["CHIA", "IGH", "MUC5AC"], ["CKM", "IGHA2///IGHA1///IGH", "MYOC"], ["CKMT2", "JCHAIN", "MYRF"], ["NEDD4L", "PIK3C2G", "SLC16A7"], ["PBLD", "PXMP2", "SLC28A2"], ["PDGFD", "RNASE1", "SOSTDC1"], ["PGA4///PGA3///PGA5", "S100P", "SULT1C2"], ["PGC", "UGT2B15", "TMPRSS2"], ["XK", "XYLT2", ""]], "row_count": 50, "column_count": 4, "numeric_cells": 22, "header_rows": 1, "locator": "section[7]/table-wrap[1]#t1-medscimonit-27-e929558"}}, {"id": "asset:table:pmid:33758160:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:9282bffd937dae9427b1bdb2f555134423895f3f401f822dba9e14e929b124a4", "bytes": 4748, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[1]#t2-medscimonit-27-e929558", "version": null, "note": "GO analysis of the 144 differentially expressed genes.", "structure": {"pmcid": "PMC8006563", "section_index": 8, "section_title": "Functional Enrichment Analysis of DEGs", "row_count": 22, "column_count": 7}, "table": {"label": "Table 2", "caption": "GO analysis of the 144 differentially expressed genes.", "rows": [["Category", "Term", "Count", "P value", "Benjamini", "FDR", "Genes"], ["GOTERM_BP_DIRECT", "GO: 0030198 ~extracellular matrix organization", "21", "5.81E-17", "1.15E-13", "1.78E-13", "COL4A2, COL4A1, OLFML2B, COL3A1, FBN1, COL2A1, SPARC, NID2, COL5A2, COL5A1, BGN, COL6A3, COL1A2, MFAP2, VCAN, COL1A1, THBS1, COL11A1, SPP1, FN1, COL10A1"], ["GOTERM_MF_DIRECT", "GO: 0005201 ~extracellular matrix structural constituent", "13", "9.89E-14", "3.07E-11", "1.33E-10", "COL4A2, BGN, COL4A1, COL3A1, FBN1, COL1A2, COL2A1, VCAN, COL1A1, MUC5AC, COL5A2, COL11A1, COL5A1"], ["GOTERM_CC_DIRECT", "GO: 0005576 ~extracellular region", "42", "4.25E-13", "7.69E-11", "5.24E-10", "GC, CHIA, IGFBP7, COL3A1, JCHAIN, APOC1, CXCL8, COL2A1, TIMP1, AZGP1, APOE, COL6A3, CPA2, LTF, PDGFD, THBS1, COL11A1, THBS2, SPP1, COL10A1, FN1, ADAM28, COL4A2, COL4A1, OLFML2B, FBN1, GIF, NID2, SPARC, COL5A2, COL5A1, INHBA, BGN, SFRP4, CEMIP, COL1A2, VCAN, MFAP2, COL1A1, CTSB, MUC5AC, LIPF"], ["GOTERM_CC_DIRECT", "GO: 0031012 ~extracellular matrix", "20", "5.14E-13", "4.65E-11", "6.33E-10", "ASPN, COL4A2, COL4A1, IGFBP7, COL3A1, FBN1, COL2A1, NID2, COL5A2, COL5A1, BGN, APOE, COL6A3, COL1A2, VCAN, COL1A1, THBS1, THBS2, MYOC, FN1"], ["GOTERM_CC_DIRECT", "GO: 0005615 ~extracellular space", "38", "8.88E-13", "5.36E-11", "1.10E-09", "GC, CHIA, PGC, IGFBP7, COL3A1, JCHAIN, CXCL8, COL2A1, SERPINH1, ALDH3A1, TIMP1, AZGP1, APOE, SOSTDC1, FAP, COL6A3, CPA2, LTF, PDGFD, THBS1, MYOC, SPP1, FN1, ATP4A, FBN1, GIF, CST1, SPARC, CHGA, SFRP4, SULF1, COL1A2, VCAN, COL1A1, CTSB, MUC5AC, CA2, GKN1"], ["GOTERM_BP_DIRECT", "GO: 0030574 ~collagen catabolic process", "12", "2.42E-12", "1.26E-09", "3.85E-09", "COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, CTSB, COL11A1, COL5A2, COL5A1, COL10A1"], ["GOTERM_CC_DIRECT", "GO: 0070062 ~extracellular exosome", "51", "3.44E-10", "1.56E-08", "4.24E-07", "RARRES1, PGC, IGFBP7, KIAA1324, AZGP1, APOE, LTF, AKR7A3, PDGFD, AKR1C1, ALDH6A1, FBP2, METTL7A, THY1, BGN, AKR1B10, COL1A2, CTSB, CA2, GC, GPRC5C, JCHAIN, APOC1, SERPINH1, PBLD, TIMP1, ALDH1A1, CSE1L, FOLR1, COL6A3, SULT1C2, NEDD4L, THBS1, MYOC, SPP1, FN1, MEST, GSTA1, TMPRSS2, RNASE1, COL4A2, S100P, FBN1, S100A10, NID2, ADGRG2, COL5A1, MUC5AC, FCGBP, HPGD, CDH11"], ["GOTERM_CC_DIRECT", "GO: 0005581 ~collagen trimer", "11", "1.32E-09", "4.79E-08", "1.63E-06", "COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, COL11A1, SERPINH1, COL5A2, COL5A1, COL10A1, TIMP1"], ["GOTERM_CC_DIRECT", "GO: 0005788 ~endoplasmic reticulum lumen", "14", "1.55E-09", "4.68E-08", "1.91E-06", "COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, COL2A1, COL1A1, PDGFD, THBS1, SERPINH1, COL5A2, COL11A1, COL5A1, COL10A1"], ["GOTERM_BP_DIRECT", "GO: 0071294~cellular response to zinc ion", "7", "5.25E-09", "1.82E-06", "8.34E-06", "MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F"], ["GOTERM_BP_DIRECT", "GO: 0045926~negative regulation of growth", "7", "5.25E-09", "1.82E-06", "8.34E-06", "MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F"], ["GOTERM_CC_DIRECT", "GO: 0005578 ~proteinaceous extracellular matrix", "15", "1.01E-08", "2.62E-07", "1.25E-05", "ASPN, OLFML2B, FBN1, SPARC, COL5A2, COL5A1, TIMP1, BGN, COL6A3, COL1A2, VCAN, COL11A1, MYOC, FN1, COL10A1"], ["GOTERM_MF_DIRECT", "GO: 0048407 ~platelet-derived growth factor binding", "6", "1.07E-08", "1.66E-06", "1.44E-05", "COL4A1, COL3A1, COL1A2, COL2A1, COL1A1, COL5A1"], ["GOTERM_BP_DIRECT", "GO: 0030199~collagen fibril organization", "8", "1.97E-08", "5.12E-06", "3.13E-05", "COL3A1, COL1A2, COL2A1, COL1A1, COL11A1, SERPINH1, COL5A2, COL5A1"], ["GOTERM_MF_DIRECT", "GO: 0050840 ~extracellular matrix binding", "6", "1.39E-06", "1.44E-04", "0.001872262", "BGN, OLFML2B, SPARC, THBS1, COL11A1, SPP1"], ["GOTERM_CC_DIRECT", "GO: 0005604 ~basement membrane", "8", "1.76E-06", "3.99E-05", "0.002172174", "COL4A1, FBN1, COL2A1, NID2, SPARC, THBS2, COL5A1, TIMP1"], ["GOTERM_BP_DIRECT", "GO: 0007155 ~cell adhesion", "16", "3.26E-06", "6.77E-04", "0.005182285", "ATP4B, IGFBP7, NID2, COL5A1, THY1, AZGP1, FAP, COL6A3, VCAN, COL1A1, THBS1, GPNMB, THBS2, SPP1, FN1, CDH11"], ["GOTERM_BP_DIRECT", "GO: 0071276~cellular response to cadmium ion", "5", "8.02E-06", "0.001386589", "0.012731623", "MT1E, MT1H, MT1X, MT1G, MT1F"], ["GOTERM_BP_DIRECT", "GO: 0007586~digestion", "7", "9.91E-06", "0.001467951", "0.015725541", "CHIA, CCKBR, PGC, AKR1B10, CAPN9, GKN1, AKR1C1"], ["GOTERM_BP_DIRECT", "GO: 0001501~skeletal system development", "9", "1.26E-05", "0.001632159", "0.019983654", "COL3A1, FBN1, COL1A2, COL2A1, VCAN, COL1A1, COL5A2, COL10A1, CDH11"], ["GOTERM_MF_DIRECT", "GO: 0005178 ~integrin binding", "8", "1.58E-05", "0.001223983", "0.021220906", "FAP, COL3A1, FBN1, THBS1, GPNMB, COL5A1, FN1, THY1"]], "row_count": 22, "column_count": 7, "numeric_cells": 118, "header_rows": 1, "locator": "section[8]/table-wrap[1]#t2-medscimonit-27-e929558"}}, {"id": "asset:table:pmid:33758160:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:69b1c22dc1299a386761a5b9771c4aa4492890bee9cf90ed170544d4492987cf", "bytes": 2311, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[2]#t3-medscimonit-27-e929558", "version": null, "note": "KEGG pathway enrichment analysis of the 144 differentially expressed genes.", "structure": {"pmcid": "PMC8006563", "section_index": 8, "section_title": "Functional Enrichment Analysis of DEGs", "row_count": 15, "column_count": 6}, "table": {"label": "Table 3", "caption": "KEGG pathway enrichment analysis of the 144 differentially expressed genes.", "rows": [["Category", "Term", "Count", "P value", "FDR", "Genes"], ["KEGG_PATHWAY", "hsa04512: ECM-receptor interaction", "14", "3.93E-12", "4.53E-09", "COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1"], ["KEGG_PATHWAY", "hsa04974: Protein digestion and absorption", "12", "1.48E-09", "1.70E-06", "COL4A2, COL4A1, COL3A1, COL6A3, COL1A2, CPA2, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1, COL10A1"], ["KEGG_PATHWAY", "hsa04510: Focal adhesion", "15", "2.34E-08", "2.69E-05", "COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, PDGFD, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1"], ["KEGG_PATHWAY", "hsa05146: Amoebiasis", "11", "1.36E-07", "1.57E-04", "COL4A2, COL4A1, COL3A1, COL1A2, CXCL8, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1, FN1"], ["KEGG_PATHWAY", "hsa04978: Mineral absorption", "7", "5.95E-06", "0.006851", "MT1M, MT2A, MT1E, MT1H, MT1X, MT1G, MT1F"], ["KEGG_PATHWAY", "hsa04151: PI3K-Akt signaling pathway", "15", "1.22E-05", "0.014013", "COL4A2, COL4A1, COL3A1, COL2A1, COL5A2, COL5A1, COL6A3, COL1A2, PDGFD, COL1A1, THBS1, COL11A1, THBS2, SPP1, FN1"], ["KEGG_PATHWAY", "hsa04971: Gastric acid secretion", "7", "1.13E-04", "0.129558", "KCNJ16, KCNJ15, CCKBR, ATP4A, ATP4B, KCNE2, CA2"], ["KEGG_PATHWAY", "hsa04611: Platelet activation", "8", "4.23E-04", "0.486191", "COL3A1, COL1A2, FCER1G, COL2A1, COL1A1, COL11A1, COL5A2, COL5A1"], ["KEGG_PATHWAY", "hsa00982: Drug metabolism – cytochrome P450", "6", "7.27E-04", "0.833392", "GSTA1, FMO5, MAOA, ADH1C, UGT2B15, ALDH3A1"], ["KEGG_PATHWAY", "hsa00980: Metabolism of xenobiotics by cytochrome P450", "6", "0.001069", "1.223788", "GSTA1, ADH1C, AKR7A3, UGT2B15, AKR1C1, ALDH3A1"], ["KEGG_PATHWAY", "hsa05204: Chemical carcinogenesis", "5", "0.010061", "10.99085", "GSTA1, CYP2C18, ADH1C, UGT2B15, ALDH3A1"], ["KEGG_PATHWAY", "hsa00340: Histidine metabolism", "3", "0.022373", "22.93516", "HDC, MAOA, ALDH3A1"], ["KEGG_PATHWAY", "hsa00830: Retinol metabolism", "4", "0.030117", "29.67766", "ALDH1A1, CYP2C18, ADH1C, UGT2B15"], ["KEGG_PATHWAY", "hsa04966: Collecting duct acid secretion", "3", "0.032861", "31.93507", "ATP4A, ATP4B, CA2"]], "row_count": 15, "column_count": 6, "numeric_cells": 67, "header_rows": 1, "locator": "section[8]/table-wrap[2]#t3-medscimonit-27-e929558"}}, {"id": "asset:table:pmid:33758160:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:e4c41a93e7f409baaa92c010208510b57a1681845baf2b0803ec75acdf4fa72e", "bytes": 2441, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#t4-medscimonit-27-e929558", "version": null, "note": "Baseline characteristics of patients in high and low risk score groups.", "structure": {"pmcid": "PMC8006563", "section_index": 10, "section_title": "Risk Score and Overall Survival for Patients with Gastric Cancer", "row_count": 37, "column_count": 7}, "table": {"label": "Table 4", "caption": "Baseline characteristics of patients in high and low risk score groups.", "rows": [["", "Pre-propensity score matching", "Post-propensity score matching"], ["Low", "High", "P", "Low", "High", "P"], ["Age, median (Q1, Q3)", "67.00 (58.00,72.00)", "67.00 (58.00,72.00)", "0.960", "67.00 (58.00,72.00)", "68.00 (59.00,72.00)", "0.617"], ["Gender", "", "", "", "", "", ""], ["Female", "55 (33.13)", "62 (37.13)", "0.445", "49 (35.51)", "50 (36.23)", "0.900"], ["Male", "111 (66.87)", "105 (62.87)", "89 (64.49)", "88 (63.77)"], ["Race", "", "", "", "", "", ""], ["White", "96 (57.83)", "114 (68.26)", "0.031", "89 (64.49)", "92 (66.67)", "0.932"], ["Asian", "38 (22.89)", "33 (19.76)", "34 (24.64)", "27 (19.57)"], ["Others", "32 (19.28)", "20 (11.98)", "15 (10.87)", "19 (13.77)"], ["Anatomic tumor site", "", "", "", "", "", ""], ["Antrum/distal", "61 (36.75)", "63 (37.72)", "0.394", "54 (39.13)", "51 (36.96)", "0.955"], ["Fundus/body", "56 (33.73)", "62 (37.13)", "47 (34.06)", "51 (36.96)"], ["Cardia/proximal", "24 (14.46)", "20 (11.98)", "19 (13.77)", "17 (12.32)"], ["Gastroesophageal junction", "18 (10.84)", "20 (11.98)", "13 (9.42)", "18 (13.04)"], ["Others", "7 (4.22)", "2 (1.20)", "5 (3.62)", "1 (0.72)"], ["Grade", "", "", "", "", "", ""], ["G1", "4 (2.41)", "4 (2.40)", "0.930", "4 (2.90)", "4 (2.90)", "0.917"], ["G2", "60 (36.14)", "55 (32.93)", "48 (34.78)", "43 (31.16)"], ["G3", "98 (59.04)", "103 (61.68)", "83 (60.14)", "87 (63.04)"], ["Gx", "4 (2.41)", "5 (2.99)", "3 (2.17)", "4 (2.90)"], ["TNM-T", "", "", "", "", "", ""], ["T1–2", "44 (26.51)", "38 (22.75)", "0.427", "35 (25.36)", "36 (26.09)", "0.891"], ["T3–4", "122 (73.49)", "129 (77.25)", "103 (74.64)", "102 (73.91)"], ["TNM-N", "", "", "", "", "", ""], ["N0", "53 (31.93)", "55 (32.93)", "0.533", "44 (31.88)", "47 (34.06)", "0.419"], ["N1", "38 (22.89)", "46 (27.54)", "33 (23.91)", "40 (28.99)"], ["N2", "41 (24.70)", "31 (18.56)", "35 (25.36)", "24 (17.39)"], ["N3", "34 (20.48)", "35 (20.96)", "26 (18.84)", "27 (19.57)"], ["TNM-M", "", "", "", "", "", ""], ["M0", "157 (94.58)", "153 (91.62)", "0.287", "131 (94.93)", "128 (92.75)", "0.453"], ["M1", "9 (5.42)", "14 (8.38)", "7 (5.07)", "10 (7.25)"], ["Stage", "", "", "", "", "", ""], ["I", "29 (17.47)", "15 (8.98)", "0.029", "22 (15.94)", "15 (10.87)", "0.073"], ["II", "42 (25.30)", "62 (37.13)", "38 (27.54)", "55 (39.86)"], ["III", "75 (45.18)", "67 (40.12)", "63 (45.65)", "50 (36.23)"], ["IV", "14 (8.43)", "20 (11.98)", "10 (7.25)", "16 (11.59)"]], "row_count": 37, "column_count": 7, "numeric_cells": 128, "header_rows": 2, "locator": "section[10]/table-wrap[1]#t4-medscimonit-27-e929558"}}, {"id": "asset:table:pmid:33758160:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:afdf43fabfc387b9a06d411a79707e97e7690bb40a8e6dfd1c3fdf8e3f9d5c16", "bytes": 1752, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[2]#t5-medscimonit-27-e929558", "version": null, "note": "Subgroup analyses for overall survival before and after propensity score analysis.", "structure": {"pmcid": "PMC8006563", "section_index": 10, "section_title": "Risk Score and Overall Survival for Patients with Gastric Cancer", "row_count": 19, "column_count": 6}, "table": {"label": "Table 5", "caption": "Subgroup analyses for overall survival before and after propensity score analysis.", "rows": [["Factors", "Group", "Before propensity score", "Propensity score analysis"], ["HR and 95% CI", "P-value", "HR and 95%CI", "P-value"], ["Age (years)", "<65.0", "2.949 (1.283–6.774)", "0.011", "2.840 (1.161–6.945)", "0.022"], [">65.0", "1.581 (0.890–2.808)", "0.118", "1.363 (0.725–2.562)", "0.337"], ["Race", "White", "1.700 (0.907–3.186)", "0.098", "1.530 (0.781–2.997)", "0.215"], ["Asian", "8.072 (0.823–79.156)", "0.073", "6.308 (0.571–69.650)", "0.133"], ["Anatomic tumor site", "Antrum/distal", "3.278 (1.553–6.922)", "0.002", "3.018 (1.353–6.732)", "0.007"], ["Fundus/body", "1.904 (0.805–4.504)", "0.143", "1.392 (0.563–3.438)", "0.474"], ["Position-others", "1.082 (0.423–2.770)", "0.869", "1.133 (0.408–3.150)", "0.810"], ["Grade", "1–2", "1.933 (0.904–4.131)", "0.089", "1.320 (0.592–2.942)", "0.497"], ["3", "2.376 (1.275–4.428)", "0.006", "2.576 (1.267–5.238)", "0.009"], ["TNM-T", "T1–2", "3.838 (1.130–13.038)", "0.031", "3.590 (0.937–13.760)", "0.062"], ["T3–4", "1.856 (1.103–3.124)", "0.020", "1.639 (0.926–2.901)", "0.090"], ["TNM-N", "N0–1", "1.873 (0.923–3.802)", "0.082", "1.746 (0.840–3.627)", "0.135"], ["N2–3", "2.127 (1.114–4.064)", "0.022", "1.695 (0.812–3.539)", "0.160"], ["TNM-M", "M0", "2.132 (1.274–3.567)", "0.004", "1.843 (1.055–3.217)", "0.032"], ["M1", "1.103 (0.333–3.651)", "0.872", "1.149 (0.305–4.329)", "0.837"], ["Stage", "I and II", "2.305 (0.855–6.215)", "0.099", "2.291 (0.782–6.712)", "0.131"], ["III and IV", "2.095 (1.191–3.685)", "0.010", "1.652 (0.893–3.055)", "0.110"]], "row_count": 19, "column_count": 6, "numeric_cells": 78, "header_rows": 2, "locator": "section[10]/table-wrap[2]#t5-medscimonit-27-e929558"}}], "gaps": ["asset:data:geo:GSE13911 not downloaded", "asset:data:geo:GSE13911 licence not read", "asset:data:geo:GSE29272 not downloaded", "asset:data:geo:GSE29272 licence not read", "asset:data:geo:GSE79973 not downloaded", "asset:data:geo:GSE79973 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17]."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival 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["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE13911", "GSE79973", "GSE29272"], "resolved_accessions": ["GSE13911", "GSE79973", "GSE29272"], "statements": ["Three independent gastric cancer microarray datasets – GSE13911, GSE79973, and GSE29272 – were used to identify the DEGs, with 206 pairs of gastric tumors and adjacent normal samples. These datasets were generated on the basis of GPL570 platforms (Affymetrix Human Genome U113 Plus 2.0 Array) and GPL6947 platforms (Illumina HumanHT-12 V3.0 expression beadchip). GSE13911 and GSE79973 datasets composed 62 and 10 pairs of matched primary gastric tumors and their adjacent normal tissues, respectively. The raw probe-level data in this study were downloaded in CEL files"], "basis": "The paper names GSE13911, GSE79973, GSE29272 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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:33758160", "data:geo:GSE13911", "asset:table:pmid:33758160:1", "asset:table:pmid:33758160:2", "asset:table:pmid:33758160:3", "asset:table:pmid:33758160:4", "asset:table:pmid:33758160:5"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE13911"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:28:18Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 19594, "completion_tokens": 1522, "cached_tokens": 784}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:33758160", "type": "paper", "label": "pmid:33758160"}, {"id": "source:pmid:33758160", "type": "manuscript", "label": "PMID 33758160 full text"}, {"id": "data:geo:GSE13911", "type": "dataset", "label": "GEO GSE13911"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33758160", "type": "paper", "label": "pmid:33758160"}, {"id": "source:pmid:33758160", "type": "manuscript", "label": "PMID 33758160 full text"}, {"id": "data:geo:GSE13911", "type": "dataset", "label": "GEO GSE13911"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33758160", "type": "extraction", "used": ["source:pmid:33758160"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE13911", "type": "accession_resolution", "used": ["data:geo:GSE13911"], "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:33758160", "parent_hash": "sha256:3bff16d80642b820eb138dfede67d56dd5799475ae5111d2af66761628042a3e", "fork_of": null, "generation": 8}, "gaps": ["asset:data:geo:GSE13911 licence not read", "asset:data:geo:GSE13911 not downloaded", "asset:data:geo:GSE29272 licence not read", "asset:data:geo:GSE29272 not downloaded", "asset:data:geo:GSE79973 licence not read", "asset:data:geo:GSE79973 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ostic biomarkers. MATERIAL AND METHODS Three microarray datasets (GSE13911, GSE79973, and GSE29272)", "differentially expressed genes (DEGs). The 3 microarray datasets yielded 144 genes associated with t", "sted t-statistics from the linear models for microarray data [17]. Genes with |log2 fold change (FC)"], "order_basis": "paper_text_order:442", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The identified DEGs were evaluated using the LIMMA package, with bayesian adjusted t-statistics from the linear models for microarray data [17]."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}