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pmid:35450397

Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes.

Hongfan Zhao · Zihao Chen · Yunze Fang · Mingqiang Su · Yipeng Xu · Zhifeng Wang · Michael Adu Gyamfi · Junfeng Zhao

Journal of immunology research · 2022 doi:10.1155/2022/1793005

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2026-11-01T18:14:18Z
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title
Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes.
doi
10.1155/2022/1793005
pmid
35450397
authors array · 8 items
[0]
Hongfan Zhao
[1]
Zihao Chen
[2]
Yunze Fang
[3]
Mingqiang Su
[4]
Yipeng Xu
[5]
Zhifeng Wang
[6]
Michael Adu Gyamfi
[7]
Junfeng Zhao
journal
Journal of immunology research
year
2022
abstract
Background: Bladder cancer (BLCA) is one of the most common cancers and ranks ninth among all cancers. Extracellular matrix (ECM) genes activate a number of pathways that facilitate tumor development. This study is aimed at providing models to predict BLCA survival and recurrence by ECM genes. Methods: Expression data from BLCA samples in GSE32894, GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts were downloaded and analyzed. The ECM-related genes were obtained by differentially expressed gene analysis, stage-associated gene analysis, and random forest variable selection. The ECM was constructed in GSE32894 by the hub ECM-related genes and validated in GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts. The correlations of the ECM score with cells (T cells, fibroblasts, etc.) and the response to immunotherapeutic drugs were investigated. Four machine learning models were selected and used to construct models to predict the recurrence of BLCA. A total of 15 paired BLCA and normal tissue specimens, human immortalized uroepithelial cell lines, and bladder cancer cell lines were selected for the validation of the difference in expression of FSTL1 between normal tissues and BLCA. Results: Six ECM genes (CTHRC1, MMP11, COL10A1, FSTL1, SULF1, and COL5A3) were recognized to be the hub ECM-related genes. The ECM score of each BLCA patient was calculated using these six selected ECM-related genes. BLCA patients with a high ECM score group had significantly lower overall survival rates than patients in the low ECM score group. We found that the ECM score was positively associated with immune cells and fibroblasts and negatively correlated with tumor purity. When treated with immunotherapy, BLCA patients with a high ECM score presented a high response rate and better prognosis. We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was an overall decrease in the mRNA expression of FSTL1 in cancer tissues compared to their adjacent normal tissues. Subsequent in vitro validation demonstrated that the FSTL1 expression was downregulated at the gene and protein level compared to that in SVH cells. Conclusion: Taken together, our results indicate that ECM-related genes correlate with immune cells, overall survival, and recurrence of BLCA. This study provides a machine learning model for predicting the survival and recurrence of BLCA patients.
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Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05).
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sections[4] "2.2. Identification of Differentially Expressed Genes (DEGs) and Stage-Associated Genes (SAGs)" paragraph 2
quote
Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05).
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The datasets used in this study are available from the corresponding author on reasonable request.
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We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence.
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We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence.
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We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence.
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title
Predective Value of Prognosis-Related Gene Expression Study in Primary Bladder Cancer
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Combination of a novel gene expression signature with a clinical nomogram improves the prediction of survival in high-risk bladder cancer  
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[126]
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[127]
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[128]
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[129]
GSM806932
[130]
GSM806933
sample_count
131
group_sizes
null
group_sizes_basis
null
platform
6947
taxon
Homo sapiens
title
Integrated genomic and gene expression profiling identifies two major gene/genomic circuits operating in urothelial carcinoma (gene expression)
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE32894
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=GSE32894
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE32894
version
null
note
The datasets used in this study are available from the corresponding author on reasonable request.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets used in this study are available from the corresponding author on reasonable request.
access_statement_kind
data_availability_statement
sample_accessions array · 308 items
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[1]
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[26]
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[27]
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[28]
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[29]
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[30]
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[31]
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[32]
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[33]
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[34]
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[35]
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[36]
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[38]
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[41]
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[42]
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[45]
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[46]
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[47]
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[48]
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[49]
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[50]
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[51]
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[52]
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[53]
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[54]
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[55]
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[56]
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[57]
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[58]
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[59]
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[60]
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[62]
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[63]
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[64]
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[65]
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[66]
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[67]
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[68]
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[69]
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[70]
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[71]
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[72]
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[73]
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[74]
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[75]
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[76]
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[77]
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[78]
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[79]
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[80]
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[81]
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[82]
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[83]
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[84]
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[85]
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[86]
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[87]
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[88]
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[89]
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[90]
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[91]
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[92]
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[93]
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[94]
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[95]
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[96]
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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]
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[109]
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[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]
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[119]
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[120]
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[121]
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[122]
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[123]
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[124]
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[125]
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[126]
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[127]
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[128]
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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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[140]
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[141]
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[142]
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[143]
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[144]
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[145]
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[146]
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[147]
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[148]
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[149]
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[150]
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[151]
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[152]
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[153]
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[154]
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[155]
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[156]
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[157]
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[160]
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[170]
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[171]
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[172]
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[173]
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[174]
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[175]
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[176]
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[190]
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[204]
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[222]
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[223]
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[225]
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sample_count
308
group_sizes
null
group_sizes_basis
null
platform
6947
taxon
Homo sapiens
title
A Molecular Taxonomy of Urothelial Carcinoma
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE13507 not downloaded
[1]
asset:data:geo:GSE13507 licence not read
[2]
asset:data:geo:GSE31684 not downloaded
[3]
asset:data:geo:GSE31684 licence not read
[4]
asset:data:geo:GSE32548 not downloaded
[5]
asset:data:geo:GSE32548 licence not read
[6]
asset:data:geo:GSE32894 not downloaded
[7]
asset:data:geo:GSE32894 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
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correlation_analysis
specific
pearson
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Correlation analysis
dsl_operations array · 1 item
[0]
pearson_r
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
1
band
verbatim
quote
Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05).
[1] object · 10 fields
id
method-2
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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
0.8
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high
quote
Kaplan-Meier
[2] object · 10 fields
id
method-3
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machine_learning
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random_forest
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Machine learning
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missing_operations array · 1 item
[0]
machine_learning_random_forest
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
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medium
quote
random forest
[3] object · 10 fields
id
method-4
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machine_learning
specific
support_vector_machine
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Machine learning
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[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.8
band
high
quote
SVM
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gaps array · 1 item
[0]
method.reader_differs_from_extractor
capability object · 3 fields
state
complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
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Computational analysis platform
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[0]
meta_analysis
[1]
machine_learning
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survival_analysis
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[4]
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[5]
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[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
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complete
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R1
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nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
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[0]
pearson_r
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: pearson.
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 · 4 items
[0]
GSE32894
[1]
GSE13507
[2]
GSE31684
[3]
GSE32548
resolved_accessions array · 4 items
[0]
GSE32894
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GSE13507
[2]
GSE31684
[3]
GSE32548
statements array · 1 item
[0]
The datasets used in this study are available from the corresponding author on reasonable request.
basis
The paper names GSE32894, GSE13507, GSE31684, GSE32548 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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[0]
pearson_r
assets array · 2 items
[0]
source:pmid:35450397
[1]
data:geo:GSE13507
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[0]
run_analysis
must_build object · 5 fields
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readers array · 0 items
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[0]
data:geo:GSE13507
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T17:43:03Z
independence
single_reader
evidence_check object · 2 fields
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verbatim
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verbatim
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5
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10987
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1857
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264
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[0] object · 4 fields
id
extraction
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complete
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MiniMax-M3.1-Flash
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minimax
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review.independent_reader
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review.machine_critique
[2]
review.human_critique
execution object · 5 fields
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absent
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not_run
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null
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[0]
execution.not_run
provenance object · 7 fields
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[0] object · 3 fields
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pmid:35450397
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paper
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pmid:35450397
[1] object · 3 fields
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source:pmid:35450397
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manuscript
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PMID 35450397 full text
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data:geo:GSE13507
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dataset
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GEO GSE13507
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[0] object · 4 fields
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activity-reading-sci-2026-11-01
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classification
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pmid:35450397
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paper
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pmid:35450397
[1] object · 3 fields
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source:pmid:35450397
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manuscript
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PMID 35450397 full text
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data:geo:GSE13507
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dataset
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GEO GSE13507
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agent:corpus-assay-engine
[1] object · 4 fields
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activity-read-35450397
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extraction
used array · 1 item
[0]
source:pmid:35450397
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agent:minimax-reader
[2] object · 4 fields
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activity-resolve-GSE13507
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accession_resolution
used array · 1 item
[0]
data:geo:GSE13507
agent
agent:corpus-assay-engine
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[0] object · 3 fields
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agent:corpus-assay-engine
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Corpus assay engine
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agent:minimax-reader
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MiniMax literature reader
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reading-sci-2026-11-01
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343fb30756ba6ec3
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2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
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pmid:35450397
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sha256:a8c031cdcfb2b52b0f097b162c113d7cb1805497e4998d45a1eb288677ba88ea
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null
gaps array · 13 items
[0]
asset:data:geo:GSE13507 licence not read
[1]
asset:data:geo:GSE13507 not downloaded
[2]
asset:data:geo:GSE31684 licence not read
[3]
asset:data:geo:GSE31684 not downloaded
[4]
asset:data:geo:GSE32548 licence not read
[5]
asset:data:geo:GSE32548 not downloaded
[6]
asset:data:geo:GSE32894 licence not read
[7]
asset:data:geo:GSE32894 not downloaded
[8]
execution.not_run
[9]
method.reader_differs_from_extractor
[10]
review.human_critique
[11]
review.independent_reader
[12]
review.machine_critique
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[0] object · 11 fields
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data_generation
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99e1195c7d6f
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partial
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assay_lexicon
99e1195c7d6f
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0.99
evidence array · 2 items
[0]
ting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was
[1]
g bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was
order_basis
paper_text_order:1987
id
assay:1
[1] object · 11 fields
role
data_generation
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cell_culture
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99e1195c7d6f
required_operations array · 0 items
support_state
partial
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assay_lexicon
99e1195c7d6f
confidence
0.77
evidence array · 1 item
[0]
ll lines (RPMI-1640 medium, Gibco, USA) were cultured in the medium supplemented with 10% fetal bovin
order_basis
paper_text_order:2833
id
assay:2
[2] object · 11 fields
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data_generation
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99e1195c7d6f
required_operations array · 0 items
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partial
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99e1195c7d6f
confidence
0.99
evidence array · 4 items
[0]
and TCGA-BLCA. Table S3: the information of immunohistochemistry (IHC) images from the Human Protein Atlas (H
[1]
of COL5A3, CTHRC1, FSTL1, MMP11, and SULF1. Immunohistochemistry images of COL5A3 in the normal bladder (A) a
[2]
dder (A) and the bladder cancer samples (B). Immunohistochemistry images of CTHRC1 in the normal bladder (C) a
[3]
dder (C) and the bladder cancer samples (D). Immunohistochemistry images of FSTL1 in the normal bladder (E) an
order_basis
paper_text_order:4624
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assay:3
[3] object · 11 fields
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analysis
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correlation_analysis
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f2132e96ae6c7a4e
required_operations array · 1 item
[0]
pearson_r
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Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05).
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35450397", "kind": "science-record", "revision": 4, "content_hash": "sha256:ccebc952937bf6a88d46285ffe086ee2ac925294c503298c9e292bc1baf8dfd8", "created_at": "2026-11-01T18:14:18Z", "updated_at": "2026-11-01T22:06:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes.", "doi": "10.1155/2022/1793005", "pmid": "35450397", "authors": ["Hongfan Zhao", "Zihao Chen", "Yunze Fang", "Mingqiang Su", "Yipeng Xu", "Zhifeng Wang", "Michael Adu Gyamfi", "Junfeng Zhao"], "journal": "Journal of immunology research", "year": 2022, "abstract": "Background: Bladder cancer (BLCA) is one of the most common cancers and ranks ninth among all cancers. Extracellular matrix (ECM) genes activate a number of pathways that facilitate tumor development. This study is aimed at providing models to predict BLCA survival and recurrence by ECM genes.\nMethods: Expression data from BLCA samples in GSE32894, GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts were downloaded and analyzed. The ECM-related genes were obtained by differentially expressed gene analysis, stage-associated gene analysis, and random forest variable selection. The ECM was constructed in GSE32894 by the hub ECM-related genes and validated in GSE13507, GSE31684, GSE32548, and TCGA-BLCA cohorts. The correlations of the ECM score with cells (T cells, fibroblasts, etc.) and the response to immunotherapeutic drugs were investigated. Four machine learning models were selected and used to construct models to predict the recurrence of BLCA. A total of 15 paired BLCA and normal tissue specimens, human immortalized uroepithelial cell lines, and bladder cancer cell lines were selected for the validation of the difference in expression of FSTL1 between normal tissues and BLCA.\nResults: Six ECM genes (CTHRC1, MMP11, COL10A1, FSTL1, SULF1, and COL5A3) were recognized to be the hub ECM-related genes. The ECM score of each BLCA patient was calculated using these six selected ECM-related genes. BLCA patients with a high ECM score group had significantly lower overall survival rates than patients in the low ECM score group. We found that the ECM score was positively associated with immune cells and fibroblasts and negatively correlated with tumor purity. When treated with immunotherapy, BLCA patients with a high ECM score presented a high response rate and better prognosis. We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was an overall decrease in the mRNA expression of FSTL1 in cancer tissues compared to their adjacent normal tissues. Subsequent in vitro validation demonstrated that the FSTL1 expression was downregulated at the gene and protein level compared to that in SVH cells.\nConclusion: Taken together, our results indicate that ECM-related genes correlate with immune cells, overall survival, and recurrence of BLCA. This study provides a machine learning model for predicting the survival and recurrence of BLCA patients.", "claims": [{"id": "claim-method", "statement": "Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35450397", "locator": "sections[4] \"2.2. Identification of Differentially Expressed Genes (DEGs) and Stage-Associated Genes (SAGs)\" paragraph 2", "quote": "Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in this study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35450397", "locator": "sections[24] \"Data Availability\" paragraph 2", "quote": "The datasets used in this study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35450397", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We also found that the combination of FSTL1, stage, age, and gender achieved an AUC value of 0.76 in predicting bladder cancer recurrence.", "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:35450397"], "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:GSE13507"], "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:GSE13507"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35450397", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/1793005", "sha256": 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Based on the RT-qPCR results of FSTL1 gene expression, there was", "g bladder cancer recurrence. Based on the RT-qPCR results of FSTL1 gene expression, there was"], "order_basis": "paper_text_order:1987", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["ll lines (RPMI-1640 medium, Gibco, USA) were cultured in the medium supplemented with 10% fetal bovin"], "order_basis": "paper_text_order:2833", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["and TCGA-BLCA. Table S3: the information of immunohistochemistry (IHC) images from the Human Protein Atlas (H", "of COL5A3, CTHRC1, FSTL1, MMP11, and SULF1. Immunohistochemistry images of COL5A3 in the normal bladder (A) a", "dder (A) and the bladder cancer samples (B). Immunohistochemistry images of CTHRC1 in the normal bladder (C) a", "dder (C) and the bladder cancer samples (D). Immunohistochemistry images of FSTL1 in the normal bladder (E) an"], "order_basis": "paper_text_order:4624", "id": "assay:3"}, {"role": "analysis", "definition_id": "correlation_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pearson_r"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Using the mRNA expression profiles from GSE32894 and TCGA-BLCA, we determined the genes associated with the tumor stage. In order to select the SAGs, a Pearson correlation analysis was conducted (a p value of 0.05)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}