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pmid:35784457

Characterization of Ligand-Receptor Pair in Bladder Cancer Develops a Validated Scoring Model for Prognosis and Treatment Response.

Chuang Wang · Honglei Wan · Han Zhang · Bo Yang · Wen-Kuan Huang · Wenguo Sun

Frontiers in cell and developmental biology · 2022 doi:10.3389/fcell.2022.915798

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Experiment

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Data

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title
Characterization of Ligand-Receptor Pair in Bladder Cancer Develops a Validated Scoring Model for Prognosis and Treatment Response.
doi
10.3389/fcell.2022.915798
pmid
35784457
authors array · 6 items
[0]
Chuang Wang
[1]
Honglei Wan
[2]
Han Zhang
[3]
Bo Yang
[4]
Wen-Kuan Huang
[5]
Wenguo Sun
journal
Frontiers in cell and developmental biology
year
2022
abstract
The role of ligand-receptor (LR) pairs in disease progression has been explored in bladder cancer. However, the relationship of LR pairs with cancer prognosis and treatment response remains poorly understood. We characterized the LR pair network and identified three distinct molecular subtypes with distinct biologic features based on the TCGA database (n = 406) and validated in GSE13507 (n = 165) and GSE32894 (n = 224). Three subtypes were compared for differences in patient clinical characteristics, genomic, and transcriptomic features. A multivariate Lasso Cox regression model was applied to construct an LR pairs-based scoring model to stratify the prognostic risk of patients. We demonstrated the high LR. score patients had better responses in chemotherapy, while low LR. score patients may benefit from immune checkpoint blockade (ICB). Collectively, we identified three LR pair-related subtypes associated with prognosis. We constructed and validated a LR pairs-based gene signature, which helps to predict prognosis and differentiate the susceptible population to chemotherapy and immunotherapy in patients with bladder cancer. Among the LR pairs significantly related to prognosis, ANAX1-EGFR axis was found to be potential therapeutic target for treatment of bladder cancer.
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To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.).
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sections[17] "Clinical Characteristics of the Ligand-Receptor score" paragraph 2
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To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.).
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The dataset were from public TCGA and GEO datasets. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article.
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sections[21] "Data Availability Statement" paragraph 2
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The dataset were from public TCGA and GEO datasets. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article.
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LR. score was a reliable and independent prognostic biomarker for bladder cancer, with HR = 2.42, 95% confidence interval 1.75–3.34, p = 8.57E-08.
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We found LR. score to be a reliable and independent prognostic biomarker for assessing patient prognosis (Figures 7A,B; HR = 2.42, 95% confidence interval 1.75–3.34, p = 8.57E-08).
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sections[17] "Clinical Characteristics of the Ligand-Receptor score" paragraph 2
quote
We found LR. score to be a reliable and independent prognostic biomarker for assessing patient prognosis (Figures 7A,B; HR = 2.42, 95% confidence interval 1.75–3.34, p = 8.57E-08).
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LR. score was a reliable and independent prognostic biomarker for bladder cancer, with HR = 2.42, 95% confidence interval 1.75–3.34, p = 8.57E-08.
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title
Predective Value of Prognosis-Related Gene Expression Study in Primary Bladder Cancer
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sample_count
308
group_sizes
null
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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
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gaps array · 4 items
[0]
asset:data:geo:GSE13507 not downloaded
[1]
asset:data:geo:GSE13507 licence not read
[2]
asset:data:geo:GSE32894 not downloaded
[3]
asset:data:geo:GSE32894 licence not read
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partial
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[0] object · 10 fields
id
method-1
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survival_analysis
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cox_proportional_hazards
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Survival analysis
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[0]
cox_ph
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parameters object · 0 fields
data_shapes array · 1 item
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time_to_event_with_censoring
evidence object · 3 fields
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1
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To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.).
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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
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two_or_more_groups_continuous
evidence object · 3 fields
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high
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Wilcoxon
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method-3
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survival_analysis
specific
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Survival analysis
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[0]
logrank_test
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data_shapes array · 1 item
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time_to_event_with_censoring
evidence object · 3 fields
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0.8
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high
quote
log-rank
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id
target-published-estimate
claim_id
claim-target-result
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cox_ph
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per cent
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null
state
complete
note
The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none.
[1] object · 8 fields
id
target-published-estimate-hazard-ratio
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claim-target-result
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cox_ph
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hazard ratio
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null
state
complete
note
The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none.
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id
target-published-estimate-p-value
claim_id
claim-target-result
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cox_ph
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p-value
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null
state
complete
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The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold.
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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[1]
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[7]
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[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
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R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
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true
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[0]
cox_ph
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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
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[0]
GSE13507
[1]
GSE32894
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[0]
GSE13507
[1]
GSE32894
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[0]
The dataset were from public TCGA and GEO datasets. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article.
basis
The paper names GSE13507, GSE32894 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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[0]
cox_ph
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[0]
source:pmid:35784457
[1]
data:geo:GSE13507
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[0]
run_analysis
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[0]
data:geo:GSE13507
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partial
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extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
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minimax
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minimax
read_at
2026-11-01T17:53:28Z
independence
single_reader
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verbatim
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verbatim
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5
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13109
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3297
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128
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id
extraction
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complete
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minimax
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absent
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not_run
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null
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execution.not_run
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pmid:35784457
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paper
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pmid:35784457
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source:pmid:35784457
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manuscript
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PMID 35784457 full text
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data:geo:GSE13507
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dataset
label
GEO GSE13507
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activity-reading-sci-2026-11-01
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classification
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pmid:35784457
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paper
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pmid:35784457
[1] object · 3 fields
id
source:pmid:35784457
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manuscript
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PMID 35784457 full text
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id
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-35784457
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extraction
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[0]
source:pmid:35784457
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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
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agent:corpus-assay-engine
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343fb30756ba6ec3
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partial
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99e1195c7d6f
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[0]
sion of all patient LR pairs. Otherwise, the patient was assigned as “low.” The expression of LR was calculate
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paper_text_order:1661
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assay:1
[1] object · 11 fields
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supported
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f2132e96ae6c7a4e
evidence array · 1 item
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To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.).
order_basis
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35784457", "kind": "science-record", "revision": 4, "content_hash": "sha256:f3d6f54254b0e302450473240acc6f451545ebb37bc4507092d3478604ee0ade", "created_at": "2026-11-01T18:14:49Z", "updated_at": "2026-11-01T22:06:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Characterization of Ligand-Receptor Pair in Bladder Cancer Develops a Validated Scoring Model for Prognosis and Treatment Response.", "doi": "10.3389/fcell.2022.915798", "pmid": "35784457", "authors": ["Chuang Wang", "Honglei Wan", "Han Zhang", "Bo Yang", "Wen-Kuan Huang", "Wenguo Sun"], "journal": "Frontiers in cell and developmental biology", "year": 2022, "abstract": "The role of ligand-receptor (LR) pairs in disease progression has been explored in bladder cancer. However, the relationship of LR pairs with cancer prognosis and treatment response remains poorly understood. We characterized the LR pair network and identified three distinct molecular subtypes with distinct biologic features based on the TCGA database (n = 406) and validated in GSE13507 (n = 165) and GSE32894 (n = 224). Three subtypes were compared for differences in patient clinical characteristics, genomic, and transcriptomic features. A multivariate Lasso Cox regression model was applied to construct an LR pairs-based scoring model to stratify the prognostic risk of patients. We demonstrated the high LR. score patients had better responses in chemotherapy, while low LR. score patients may benefit from immune checkpoint blockade (ICB). Collectively, we identified three LR pair-related subtypes associated with prognosis. We constructed and validated a LR pairs-based gene signature, which helps to predict prognosis and differentiate the susceptible population to chemotherapy and immunotherapy in patients with bladder cancer. Among the LR pairs significantly related to prognosis, ANAX1-EGFR axis was found to be potential therapeutic target for treatment of bladder cancer.", "claims": [{"id": "claim-method", "statement": "To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35784457", "locator": "sections[17] \"Clinical Characteristics of the Ligand-Receptor score\" paragraph 2", "quote": "To test whether the LR. score could be used as an independent prognostic factor, we performed univariate and multivariate Cox regression analyses using patients’ clinical characteristics (including age, gender, TNM, Stage, Grade, etc.)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset were from public TCGA and GEO datasets. 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