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pmid:33934539

A novel five-gene signature predicts overall survival of patients with hepatocellular carcinoma.

Zhigang Wang · Leyu Pan · Deliang Guo · Xiaofeng Luo · Jie Tang · Weihua Yang · Yuxian Zhang · Anni Luo · Yang Gu · Yuxuan Pan

Cancer medicine · 2021 doi:10.1002/cam4.3900

Paper

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Experiment

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Data

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Analysis

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pmid:33934539
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2026-11-01T15:41:34Z
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2026-11-01T22:03:40Z
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paper object · 10 fields
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title
A novel five-gene signature predicts overall survival of patients with hepatocellular carcinoma.
doi
10.1002/cam4.3900
pmid
33934539
authors array · 10 items
[0]
Zhigang Wang
[1]
Leyu Pan
[2]
Deliang Guo
[3]
Xiaofeng Luo
[4]
Jie Tang
[5]
Weihua Yang
[6]
Yuxian Zhang
[7]
Anni Luo
[8]
Yang Gu
[9]
Yuxuan Pan
journal
Cancer medicine
year
2021
abstract
Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.
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After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/).
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sections[0] "Abstract" paragraph 1
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After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set.
[1] object · 3 fields
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sections[3] "Data source" paragraph 2
quote
The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/).
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The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
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sections[30] "DATA AVAILABILITY STATEMENT" paragraph 2
quote
The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
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https://doi.org/10.1002/cam4.3900
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The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
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The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
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GSM712540
[486]
GSM712541
[487]
GSM712542
sample_count
488
group_sizes
null
group_sizes_basis
null
platform
3921;571
taxon
Homo sapiens
title
Gene expression data of human hepatocellular carcinoma (HCC)
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:GSE54236
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=GSE54236
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE54236
version
null
note
The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
access_statement_kind
data_availability_statement
sample_accessions array · 161 items
[0]
GSM1310570
[1]
GSM1310571
[2]
GSM1310572
[3]
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[4]
GSM1310574
[5]
GSM1310575
[6]
GSM1310576
[7]
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[8]
GSM1310578
[9]
GSM1310579
[10]
GSM1310580
[11]
GSM1310581
[12]
GSM1310582
[13]
GSM1310583
[14]
GSM1310584
[15]
GSM1310585
[16]
GSM1310586
[17]
GSM1310587
[18]
GSM1310588
[19]
GSM1310589
[20]
GSM1310590
[21]
GSM1310591
[22]
GSM1310592
[23]
GSM1310593
[24]
GSM1310594
[25]
GSM1310595
[26]
GSM1310596
[27]
GSM1310597
[28]
GSM1310598
[29]
GSM1310599
[30]
GSM1310600
[31]
GSM1310601
[32]
GSM1310602
[33]
GSM1310603
[34]
GSM1310604
[35]
GSM1310605
[36]
GSM1310606
[37]
GSM1310607
[38]
GSM1310608
[39]
GSM1310609
[40]
GSM1310610
[41]
GSM1310611
[42]
GSM1310612
[43]
GSM1310613
[44]
GSM1310614
[45]
GSM1310615
[46]
GSM1310616
[47]
GSM1310617
[48]
GSM1310618
[49]
GSM1310619
[50]
GSM1310620
[51]
GSM1310621
[52]
GSM1310622
[53]
GSM1310623
[54]
GSM1310624
[55]
GSM1310625
[56]
GSM1310626
[57]
GSM1310627
[58]
GSM1310628
[59]
GSM1310629
[60]
GSM1310630
[61]
GSM1310631
[62]
GSM1310632
[63]
GSM1310633
[64]
GSM1310634
[65]
GSM1310635
[66]
GSM1310636
[67]
GSM1310637
[68]
GSM1310638
[69]
GSM1310639
[70]
GSM1310640
[71]
GSM1310641
[72]
GSM1310642
[73]
GSM1310643
[74]
GSM1310644
[75]
GSM1310645
[76]
GSM1310646
[77]
GSM1310647
[78]
GSM1310648
[79]
GSM1310649
[80]
GSM1310650
[81]
GSM1310651
[82]
GSM1310652
[83]
GSM1310653
[84]
GSM1310654
[85]
GSM1310655
[86]
GSM1310656
[87]
GSM1310657
[88]
GSM1310658
[89]
GSM1310659
[90]
GSM1310660
[91]
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[92]
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[93]
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[94]
GSM1310664
[95]
GSM1310665
[96]
GSM1310666
[97]
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[98]
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[99]
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[100]
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[101]
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[102]
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[103]
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[104]
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[105]
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[106]
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[107]
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[108]
GSM1310678
[109]
GSM1310679
[110]
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[111]
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[112]
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[113]
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[114]
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[115]
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[116]
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[117]
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[118]
GSM1310688
[119]
GSM1310689
[120]
GSM1310690
[121]
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[122]
GSM1310692
[123]
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[124]
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[125]
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[126]
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[129]
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[130]
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[131]
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[132]
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[133]
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[134]
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[135]
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[136]
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[137]
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[138]
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[139]
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[142]
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[143]
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[147]
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[150]
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[151]
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[152]
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[155]
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[156]
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[157]
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GSM1310728
[159]
GSM1310729
[160]
GSM1310730
sample_count
161
group_sizes
null
group_sizes_basis
null
platform
6480
taxon
Homo sapiens
title
Prospective gene expression analysis of human RNA samples from Hepatocellular Carcinoma in relation with growth rate and survival
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[3] object · 16 fields
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asset:table:pmid:33934539:1
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jats-table
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null
note
The clinical information of five‐gene signature in two datasets
structure object · 5 fields
pmcid
PMC8178492
section_index
16
section_title
Independent prognostic role of the gene signature
row_count
35
column_count
7
table object · 8 fields
label
TABLE1 1
caption
The clinical information of five‐gene signature in two datasets
rows array · 35 items
[0] array · 3 items
[0]
Characteristics
[1]
GSE14520
[2]
TCGA‐LIHC
[1] array · 6 items
[0]
High risk
[1]
Low risk
[2]
p value
[3]
High risk
[4]
Low risk
[5]
p value
[2] array · 7 items
[0]
Gender
[1]
[2]
[3]
0.534
[4]
[5]
[6]
0.698
[3] array · 7 items
[0]
Female
[1]
12
[2]
18
[3]
[4]
30
[5]
88
[6]
[4] array · 7 items
[0]
Male
[1]
88
[2]
103
[3]
[4]
67
[5]
178
[6]
[5] array · 7 items
[0]
Age (years)
[1]
[2]
[3]
0.023
[4]
[5]
[6]
0.511
[6] array · 7 items
[0]
≤65
[1]
94
[2]
102
[3]
[4]
55
[5]
161
[6]
[7] array · 7 items
[0]
>65
[1]
6
[2]
19
[3]
[4]
42
[5]
105
[6]
[8] array · 7 items
[0]
ALT (U/L)
[1]
[2]
[3]
0.11
[4]
[5]
[6]
[9] array · 7 items
[0]
≤50
[1]
53
[2]
77
[3]
[4]
[5]
[6]
[10] array · 7 items
[0]
>50
[1]
47
[2]
44
[3]
[4]
[5]
[6]
[11] array · 7 items
[0]
Tumor size (cm)
[1]
[2]
[3]
0.003
[4]
[5]
[6]
[12] array · 7 items
[0]
≤5
[1]
53
[2]
87
[3]
[4]
[5]
[6]
[13] array · 7 items
[0]
>5
[1]
47
[2]
33
[3]
[4]
[5]
[6]
[14] array · 7 items
[0]
Multinodular
[1]
[2]
[3]
0.058
[4]
[5]
[6]
[15] array · 7 items
[0]
No
[1]
74
[2]
102
[3]
[4]
[5]
[6]
[16] array · 7 items
[0]
Yes
[1]
26
[2]
19
[3]
[4]
[5]
[6]
[17] array · 7 items
[0]
Cirrhosis
[1]
[2]
[3]
0.041
[4]
[5]
[6]
[18] array · 7 items
[0]
No
[1]
4
[2]
14
[3]
[4]
[5]
[6]
[19] array · 7 items
[0]
Yes
[1]
96
[2]
107
[3]
[4]
[5]
[6]
[20] array · 6 items
[0]
Serum AFP (ng/ml)
[1]
[2]
<0.001
[3]
[4]
[5]
[21] array · 7 items
[0]
≤300
[1]
41
[2]
77
[3]
[4]
[5]
[6]
[22] array · 7 items
[0]
>300
[1]
59
[2]
41
[3]
[4]
[5]
[6]
[23] array · 7 items
[0]
TNM stage
[1]
[2]
[3]
<0.001
[4]
[5]
[6]
<0.001
[24] array · 7 items
[0]
I + II
[1]
62
[2]
108
[3]
[4]
53
[5]
201
[6]
[25] array · 7 items
[0]
III + IV
[1]
37
[2]
12
[3]
[4]
35
[5]
42
[6]
[26] array · 7 items
[0]
BMI (kg/m2)
[1]
[2]
[3]
[4]
[5]
[6]
0.097
[27] array · 7 items
[0]
<27
[1]
[2]
[3]
[4]
66
[5]
154
[6]
[28] array · 7 items
[0]
≥27
[1]
[2]
[3]
[4]
24
[5]
88
[6]
[29] array · 7 items
[0]
Tumor grade
[1]
[2]
[3]
[4]
[5]
[6]
0.004
[30] array · 7 items
[0]
1 + 2
[1]
[2]
[3]
[4]
50
[5]
180
[6]
[31] array · 7 items
[0]
3 + 4
[1]
[2]
[3]
[4]
46
[5]
82
[6]
[32] array · 7 items
[0]
Cancer status
[1]
[2]
[3]
[4]
[5]
[6]
0.535
[33] array · 7 items
[0]
Tumor free
[1]
[2]
[3]
[4]
58
[5]
173
[6]
[34] array · 7 items
[0]
With tumor
[1]
[2]
[3]
[4]
30
[5]
76
[6]
locator
section[16]/table-wrap[1]#cam43900-tbl-0001
gaps array · 4 items
[0]
asset:data:geo:GSE14520 not downloaded
[1]
asset:data:geo:GSE14520 licence not read
[2]
asset:data:geo:GSE54236 not downloaded
[3]
asset:data:geo:GSE54236 licence not read
analysis object · 4 fields
state
partial
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[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
reordered
quote
After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/).
[1] object · 10 fields
id
method-2
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group_comparison
specific
wilcoxon
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Group comparison
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missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Wilcoxon
[2] object · 10 fields
id
method-3
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survival_analysis
specific
kaplan_meier
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Survival analysis
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[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
0.7
band
medium
quote
Kaplan-Meier
[3] object · 10 fields
id
method-4
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model_calibration
specific
decision_curve
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Model calibration / clinical utility
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[0]
calibration_bins
[1]
net_benefit
missing_operations array · 0 items
parameters object · 0 fields
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[0]
predictions_and_outcomes
evidence object · 3 fields
score
0.7
band
medium
quote
decision curve analysis
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id
method-5
family
contingency_analysis
specific
fisher_exact
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Categorical (contingency table) analysis
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[0]
contingency_table
[1]
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
Fisher's exact
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 · 1 item
[0]
cox_ph
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: cox_proportional_hazards.
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 · 2 items
[0]
GSE14520
[1]
GSE54236
resolved_accessions array · 2 items
[0]
GSE14520
[1]
GSE54236
statements array · 1 item
[0]
The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.
basis
The paper names GSE14520, GSE54236 in Gene Expression Omnibus (GEO) database in NCBI 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]
cox_ph
assets array · 3 items
[0]
source:pmid:33934539
[1]
data:geo:GSE14520
[2]
asset:table:pmid:33934539:1
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[0]
run_analysis
must_build object · 5 fields
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converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE14520
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:29:37Z
independence
single_reader
evidence_check object · 2 fields
method
reordered
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
29906
completion_tokens
1935
cached_tokens
528
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
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review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
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null
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gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:33934539
type
paper
label
pmid:33934539
[1] object · 3 fields
id
source:pmid:33934539
type
manuscript
label
PMID 33934539 full text
[2] object · 3 fields
id
data:geo:GSE14520
type
dataset
label
GEO GSE14520
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[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
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[0] object · 3 fields
id
pmid:33934539
type
paper
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pmid:33934539
[1] object · 3 fields
id
source:pmid:33934539
type
manuscript
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PMID 33934539 full text
[2] object · 3 fields
id
data:geo:GSE14520
type
dataset
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GEO GSE14520
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-33934539
type
extraction
used array · 1 item
[0]
source:pmid:33934539
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE14520
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE14520
agent
agent:corpus-assay-engine
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[0] object · 3 fields
id
agent:corpus-assay-engine
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Corpus assay engine
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id
agent:minimax-reader
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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:33934539
parent_hash
sha256:1f34c4dc97b9d2812acbd88675af6005671e6d763008e15b407128f39d6c061f
fork_of
null
gaps array · 9 items
[0]
asset:data:geo:GSE14520 licence not read
[1]
asset:data:geo:GSE14520 not downloaded
[2]
asset:data:geo:GSE54236 licence not read
[3]
asset:data:geo:GSE54236 not downloaded
[4]
execution.not_run
[5]
method.reader_differs_from_extractor
[6]
review.human_critique
[7]
review.independent_reader
[8]
review.machine_critique
assays array · 2 items
[0] object · 11 fields
role
data_generation
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99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic
order_basis
paper_text_order:1892
id
assay:1
[1] object · 11 fields
role
analysis
definition_id
survival_analysis
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f2132e96ae6c7a4e
required_operations array · 1 item
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cox_ph
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/).
order_basis
consumes_earlier_output
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assay:2
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33934539", "kind": "science-record", "revision": 7, "content_hash": "sha256:be62f79d822b6961e13c911d818724fde61db419cdbd4bd6a0429e4fe4c3e4a8", "created_at": "2026-11-01T15:41:34Z", "updated_at": "2026-11-01T22:03:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel five-gene signature predicts overall survival of patients with hepatocellular carcinoma.", "doi": "10.1002/cam4.3900", "pmid": "33934539", "authors": ["Zhigang Wang", "Leyu Pan", "Deliang Guo", "Xiaofeng Luo", "Jie Tang", "Weihua Yang", "Yuxian Zhang", "Anni Luo", "Yang Gu", "Yuxuan Pan"], "journal": "Cancer medicine", "year": 2021, "abstract": "Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.", "claims": [{"id": "claim-method", "statement": "After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33934539", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set."}, {"asset": "source:pmid:33934539", "locator": "sections[3] \"Data source\" paragraph 2", "quote": "The GSE14520 and GSE54236 two datasets contained HCC genes expression and clinical information were downloaded from GEO database in NCBI (https://www.ncbi.nlm.nih.gov/pmc/)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33934539", "locator": "sections[30] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request."}], "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:33934539"], "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:GSE14520"], "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:GSE14520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33934539", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/cam4.3900", "sha256": "sha256:48ba277b3c235d8b496721517ef9d9322e6c2562b90fe429dcd942f15cf54caf", "bytes": 38833, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/cam4.3900", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8178492", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE14520", "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=GSE14520", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE14520", "version": null, "note": "The source of all data during this research is included in this article. The R codes used in this study are available from the corresponding author by request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The source of all data during this research is included in this article. 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The R codes used in this study are available from the corresponding author by request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The source of all data during this research is included in this article. 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null, "sha256": "sha256:088c2c95c09f811ccff20370e4b4655c37ec9ef9354d67324a7c7f0ca227133e", "bytes": 1520, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[16]/table-wrap[1]#cam43900-tbl-0001", "version": null, "note": "The clinical information of five‐gene signature in two datasets", "structure": {"pmcid": "PMC8178492", "section_index": 16, "section_title": "Independent prognostic role of the gene signature", "row_count": 35, "column_count": 7}, "table": {"label": "TABLE1 1", "caption": "The clinical information of five‐gene signature in two datasets", "rows": [["Characteristics", "GSE14520", "TCGA‐LIHC"], ["High risk", "Low risk", "p value", "High risk", "Low risk", "p value"], ["Gender", "", "", "0.534", "", "", "0.698"], ["Female", "12", "18", "", "30", "88", ""], ["Male", "88", "103", "", "67", "178", ""], ["Age (years)", "", "", "0.023", "", "", "0.511"], ["≤65", "94", "102", "", "55", "161", ""], [">65", "6", "19", "", "42", "105", ""], ["ALT (U/L)", "", "", "0.11", "", "", ""], ["≤50", "53", "77", "", "", "", ""], [">50", "47", "44", "", "", "", ""], ["Tumor size (cm)", "", "", "0.003", "", "", ""], ["≤5", "53", "87", "", "", "", ""], [">5", "47", "33", "", "", "", ""], ["Multinodular", "", "", "0.058", "", "", ""], ["No", "74", "102", "", "", "", ""], ["Yes", "26", "19", "", "", "", ""], ["Cirrhosis", "", "", "0.041", "", "", ""], ["No", "4", "14", "", "", "", ""], ["Yes", "96", "107", "", "", "", ""], ["Serum AFP (ng/ml)", "", "<0.001", "", "", ""], ["≤300", "41", "77", "", "", "", ""], [">300", "59", "41", "", "", "", ""], ["TNM stage", "", "", "<0.001", "", "", "<0.001"], ["I + II", "62", "108", "", "53", "201", ""], ["III + IV", "37", "12", "", "35", "42", ""], ["BMI (kg/m2)", "", "", "", "", "", "0.097"], ["<27", "", "", "", "66", "154", ""], ["≥27", "", "", "", "24", "88", ""], ["Tumor grade", "", "", "", "", "", "0.004"], ["1 + 2", "", "", "", "50", "180", ""], ["3 + 4", "", "", 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