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pmid:35433683

Construction and Validation of a 15-Top-prognostic-gene-based Signature to Indicate the Dichotomized Clinical Outcome and Response to Targeted Therapy for Bladder Cancer Patients.

Hongbing Gu · Chaozhao Liang

Frontiers in cell and developmental biology · 2022 doi:10.3389/fcell.2022.725024

Paper

complete

Experiment

complete

Data

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Analysis

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Construction and Validation of a 15-Top-prognostic-gene-based Signature to Indicate the Dichotomized Clinical Outcome and Response to Targeted Therapy for Bladder Cancer Patients.
doi
10.3389/fcell.2022.725024
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35433683
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Hongbing Gu
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Chaozhao Liang
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Frontiers in cell and developmental biology
year
2022
abstract
The clinical outcome of heterogeneous bladder cancer (BCa) is impacted by varying molecular characteristics and clinical features, and new molecular classification is necessary to recognize patients with dichotomized prognosis. We enrolled a total of 568 BCa patients from the TCGA-BLCA and GSE13507 cohorts. A total of 107 candidate genes, which were mostly involved in the extracellular matrix-associated pathway, were first selected through the consensus value of the area under the receiver operating characteristic curve (AUC). Furthermore, absolute shrinkage and selection operation regression analysis was implemented to reveal the 15 genes and establish the prognostic signature. The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76-3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76-3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208-34.731). Multivariate Cox analysis involving the signature and clinical features indicated that the signature is an independent factor for the prediction of BCa prognosis. We also explored potential targeted therapy for BCa patients with high- or low-risk scores and found that patients with high risk were more suitable for chemotherapy with gemcitabine, doxorubicin, cisplatin, paclitaxel, and vinblastine (all p < 0.05), but anti-PD-L1 therapy was useless. We knocked down HEYL with siRNAs in T24 and 5,637 cells, and observed the decreased protein level of HEYL, and inhibited cell viability and cell invasion. In summary, we proposed and validated a 15-top-prognostic gene-based signature to indicate the dichotomized prognosis and response to targeted therapy.
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The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated by the “pROC” package to assess the prognostic ability of all included genes and screen the genes included in the analysis with optimal cutoff values (TCGA-BLCA: 0.60; GSE13507: 0.65). Furthermore, to construct an accurate prognostic model, the least absolute shrinkage and selector operation (LASSO) regression analysis was implemented for screening candidate genes by using the “glmnet” package. The minimum lambda value was defined as a cutoff point to minimize the mean cross-validated error. These genes selected via LASSO analysis were used to calculate the risk score of each patient with the gene expression value and coefficient.
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The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated by the “pROC” package to assess the prognostic ability of all included genes and screen the genes included in the analysis with optimal cutoff values (TCGA-BLCA: 0.60; GSE13507: 0.65). Furthermore, to construct an accurate prognostic model, the least absolute shrinkage and selector operation (LASSO) regression analysis was implemented for screening candidate genes by using the “glmnet” package. The minimum lambda value was defined as a cutoff point to minimize the mean cross-validated error. These genes selected via LASSO analysis were used to calculate the risk score of each patient with the gene expression value and coefficient.
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The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76–3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76–3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208–34.731).
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The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76–3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76–3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208–34.731).
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The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76–3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76–3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208–34.731).
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title
Predective Value of Prognosis-Related Gene Expression Study in Primary Bladder Cancer
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activity-reading-sci-2026-11-01
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classification
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paper
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pmid:35433683
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source:pmid:35433683
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manuscript
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PMID 35433683 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
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activity-read-35433683
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extraction
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source:pmid:35433683
agent
agent:minimax-reader
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activity-resolve-GSE13507
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accession_resolution
used array · 1 item
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data:geo:GSE13507
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agent:corpus-assay-engine
agents array · 2 items
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agent:corpus-assay-engine
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software
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Corpus assay engine
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agent:minimax-reader
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software
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MiniMax literature reader
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reading-sci-2026-11-01
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343fb30756ba6ec3
capability_table_fingerprint
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lineage object · 4 fields
parent_id
pmid:35433683
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sha256:de3e1746b8d2e2a6321e144652ac3eb1a95c8b7dde7de9953fa85118054e23d5
fork_of
null
gaps array · 6 items
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asset:data:geo:GSE13507 licence not read
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asset:data:geo:GSE13507 not downloaded
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execution.not_run
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review.human_critique
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review.independent_reader
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review.machine_critique
assays array · 5 items
[0] object · 11 fields
role
data_generation
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western_blot
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source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
. Cell Culture, Proliferation, Invasion, and Western Blotting We cultured the T24 and 5,637 BCa cell lines
[1]
nder a light microscope (Nikon Corporation). Western blotting was performed to confirm the knockdown of HE
order_basis
paper_text_order:2970
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assay:1
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cell_culture
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99e1195c7d6f
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iferation, Invasion, and Western Blotting We cultured the T24 and 5,637 BCa cell lines in RPMI-164
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paper_text_order:2990
id
assay:2
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data_generation
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transfection
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99e1195c7d6f
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0.99
evidence array · 2 items
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a cell lines 5,637 and T24 were respectively transfected with 50 pmol negative control, si-HEYL-1#, a
[1]
estern blotting was performed to confirm the knockdown of HEYL at the protein level. Anti-HEYL and
order_basis
paper_text_order:3165
id
assay:3
[3] object · 11 fields
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apoptosis_assay
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able S1. We evaluated cell viability via the MTT assay. A total of 5,000 cells were seeded in
[1]
for 0, 1, 2, and 3 days. Then, 50 µl of 0.5% MTT reagent was added to each well, and the cell
order_basis
paper_text_order:3484
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assay:4
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The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated by the “pROC” package to assess the prognostic ability of all included genes and screen the genes included in the analysis with optimal cutoff values (TCGA-BLCA: 0.60; GSE13507: 0.65). Furthermore, to construct an accurate prognostic model, the least absolute shrinkage and selector operation (LASSO) regression analysis was implemented for screening candidate genes by using the “glmnet” package. The minimum lambda value was defined as a cutoff point to minimize the mean cross-validated error. These genes selected via LASSO analysis were used to calculate the risk score of each patient with the gene expression value and coefficient.
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Complete file
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We enrolled a total of 568 BCa patients from the TCGA-BLCA and GSE13507 cohorts. A total of 107 candidate genes, which were mostly involved in the extracellular matrix-associated pathway, were first selected through the consensus value of the area under the receiver operating characteristic curve (AUC). Furthermore, absolute shrinkage and selection operation regression analysis was implemented to reveal the 15 genes and establish the prognostic signature. The newly defined prognostic signature could precisely separate BCa patients into subgroups with favorable and poor prognosis in the training TCGA-BLCA cohort (p < 0.001, HR = 2.41, and 95% CI: 1.76-3.29), as well as the testing GSE13507 cohort (p < 0.001, HR = 7.32, and 95% CI: 1.76-3.29) and external validation E-MTAB-4321 cohort (p < 0.001, HR = 10.56, 95% CI: 3.208-34.731). Multivariate Cox analysis involving the signature and clinical features indicated that the signature is an independent factor for the prediction of BCa prognosis. We also explored potential targeted therapy for BCa patients with high- or low-risk scores and found that patients with high risk were more suitable for chemotherapy with gemcitabine, doxorubicin, cisplatin, paclitaxel, and vinblastine (all p < 0.05), but anti-PD-L1 therapy was useless. We knocked down HEYL with siRNAs in T24 and 5,637 cells, and observed the decreased protein level of HEYL, and inhibited cell viability and cell invasion. In summary, we proposed and validated a 15-top-prognostic gene-based signature to indicate the dichotomized prognosis and response to targeted therapy.", "claims": [{"id": "claim-method", "statement": "The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated by the “pROC” package to assess the prognostic ability of all included genes and screen the genes included in the analysis with optimal cutoff values (TCGA-BLCA: 0.60; GSE13507: 0.65). Furthermore, to construct an accurate prognostic model, the least absolute shrinkage and selector operation (LASSO) regression analysis was implemented for screening candidate genes by using the “glmnet” package. The minimum lambda value was defined as a cutoff point to minimize the mean cross-validated error. 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A run that reproduces the effect is judged against this threshold."}], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE13507"], "resolved_accessions": ["GSE13507"], "statements": ["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/Supplementary Material."], "basis": "The paper names GSE13507 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": ["cox_ph"], "assets": ["source:pmid:35433683", "data:geo:GSE13507"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE13507"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:42:29Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 14865, "completion_tokens": 2186, "cached_tokens": 128}}, "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:35433683", "type": "paper", "label": "pmid:35433683"}, {"id": "source:pmid:35433683", "type": "manuscript", "label": "PMID 35433683 full text"}, {"id": "data:geo:GSE13507", "type": "dataset", "label": "GEO GSE13507"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35433683", "type": "paper", "label": "pmid:35433683"}, {"id": "source:pmid:35433683", "type": "manuscript", "label": "PMID 35433683 full text"}, {"id": "data:geo:GSE13507", "type": "dataset", "label": "GEO GSE13507"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35433683", "type": "extraction", "used": ["source:pmid:35433683"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE13507", "type": "accession_resolution", "used": ["data:geo:GSE13507"], "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:35433683", "parent_hash": "sha256:de3e1746b8d2e2a6321e144652ac3eb1a95c8b7dde7de9953fa85118054e23d5", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE13507 licence not read", "asset:data:geo:GSE13507 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": [". Cell Culture, Proliferation, Invasion, and Western Blotting We cultured the T24 and 5,637 BCa cell lines", "nder a light microscope (Nikon Corporation). Western blotting was performed to confirm the knockdown of HE"], "order_basis": "paper_text_order:2970", "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": ["iferation, Invasion, and Western Blotting We cultured the T24 and 5,637 BCa cell lines in RPMI-164"], "order_basis": "paper_text_order:2990", "id": "assay:2"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["a cell lines 5,637 and T24 were respectively transfected with 50 pmol negative control, si-HEYL-1#, a", "estern blotting was performed to confirm the knockdown of HEYL at the protein level. Anti-HEYL and"], "order_basis": "paper_text_order:3165", "id": "assay:3"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["able S1. We evaluated cell viability via the MTT assay. A total of 5,000 cells were seeded in", "for 0, 1, 2, and 3 days. Then, 50 µl of 0.5% MTT reagent was added to each well, and the cell"], "order_basis": "paper_text_order:3484", "id": "assay:4"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated by the “pROC” package to assess the prognostic ability of all included genes and screen the genes included in the analysis with optimal cutoff values (TCGA-BLCA: 0.60; GSE13507: 0.65). Furthermore, to construct an accurate prognostic model, the least absolute shrinkage and selector operation (LASSO) regression analysis was implemented for screening candidate genes by using the “glmnet” package. The minimum lambda value was defined as a cutoff point to minimize the mean cross-validated error. These genes selected via LASSO analysis were used to calculate the risk score of each patient with the gene expression value and coefficient."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}