Comprehensive characterization of endoplasmic reticulum stress in bladder cancer revealing the association with tumor immune microenvironment and prognosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37091788", "kind": "science-record", "revision": 4, "content_hash": "sha256:aa79002b4b2800cbd75ff7d30a29b5a5767a3cff418a9376d5257066cbb7940a", "created_at": "2026-11-01T19:01:45Z", "updated_at": "2026-11-01T22:51:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive characterization of endoplasmic reticulum stress in bladder cancer revealing the association with tumor immune microenvironment and prognosis.", "doi": "10.3389/fgene.2023.1097179", "pmid": "37091788", "authors": ["Yuda Lin", "Tengfei Li", "Zhuolun Li", "Chong Shen", "Zhouliang Wu", "Zhe Zhang", "Zhi Li", "Shaobo Yang", "Zejin Wang", "Peng Li", "Chong Fu", "Jian Guo", "Hailong Hu"], "journal": "Frontiers in genetics", "year": 2023, "abstract": "Background: This study constructs a molecular subtype and prognostic model of bladder cancer (BLCA) through endoplasmic reticulum stress (ERS) related genes, thus helping to clinically guide accurate treatment and prognostic assessment. Methods: The Bladder Cancer (BLCA) gene expression data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We clustered by ERS-related genes which obtained through GeneCards database, results in the establishment of a new molecular typing of bladder cancer. Further, we explored the characteristics of each typology in terms of immune microenvironment, mutations, and drug screening. By analyzing the ERS-related genes with univariate Cox, LASSO and multivariate Cox analyses, we also developed the four-gene signature, while validating the prognostic effect of the model in GSE32894 and GSE13507 cohorts. Finally, we evaluated the prognostic value of the clinical data in the high and low ERS score groups and constructed a prognostic score line graph by Nomogram. Results: We constructed four molecular subtypes (C1- C4) of bladder cancer, in which patients with C2 had a poor prognosis and those with C3 had a better prognosis. The C2 had a high degree of TP53 mutation, significant immune cell infiltration and high immune score. In contrast, C3 had a high degree of FGFR3 mutation, insignificant immune cell infiltration, and reduced immune checkpoint expression. After that, we built ERS-related risk signature to calculate ERS score, including ATP2A3, STIM2, VWF and P4HB. In the GSE32894 and GSE13507, the signature also had good predictive value for prognosis. In addition, ERS scores were shown to correlate well with various clinical features. Finally, we correlated the ERS clusters and ERS score. Patients with high ERS score were more likely to have the C2 phenotype, while patients with low ERS score were C3. Conclusion: In summary, we identified four novel molecular subtypes of BLCA by ERS-related genes which could provide some new insights into precision medicine. Prognostic models constructed from ERS-related genes can be used to predict clinical outcomes. Our study contributes to the study of personalized treatment and mechanisms of BLCA.", "claims": [{"id": "claim-method", "statement": "The 258 ERS-related genes were analyzed by Univariate Cox analysis and 75 prognosis-related genes were obtained (Supplementary Figure S5). After LASSO analysis, 21 genes were included in the Multivariable Cox analysis (Figures 6A, B). Ultimately, we developed the 4-gene prognostic signature.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091788", "locator": "sections[21] \"Construction of prognostic signature\" paragraph 2", "quote": "The 258 ERS-related genes were analyzed by Univariate Cox analysis and 75 prognosis-related genes were obtained (Supplementary Figure S5). After LASSO analysis, 21 genes were included in the Multivariable Cox analysis (Figures 6A, B). Ultimately, we developed the 4-gene prognostic signature."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091788", "locator": "sections[31] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "For the OS survival prediction of ERS signature, the AUC of the ROC curves for 1, 3 and 5, years were 0.698, 0.687, and 0.702 (Figure 6D).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37091788", "locator": "sections[21] \"Construction of prognostic signature\" paragraph 2", "quote": "For the OS survival prediction of ERS signature, the AUC of the ROC curves for 1, 3 and 5, years were 0.698, 0.687, and 0.702 (Figure 6D)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "For the OS survival prediction of ERS signature, the AUC of the ROC curves for 1, 3 and 5, years were 0.698, 0.687, and 0.702 (Figure 6D).", "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:37091788"], "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. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:37091788", "data:geo:GSE130001"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE130001"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:37:21Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 16971, "completion_tokens": 1910, "cached_tokens": 264}}, "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:37091788", "type": "paper", "label": "pmid:37091788"}, {"id": "source:pmid:37091788", "type": "manuscript", "label": "PMID 37091788 full text"}, {"id": "data:geo:GSE130001", "type": "dataset", "label": "GEO GSE130001"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37091788", "type": "paper", "label": "pmid:37091788"}, {"id": "source:pmid:37091788", "type": "manuscript", "label": "PMID 37091788 full text"}, {"id": "data:geo:GSE130001", "type": "dataset", "label": "GEO GSE130001"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37091788", "type": "extraction", "used": ["source:pmid:37091788"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE130001", "type": "accession_resolution", "used": ["data:geo:GSE130001"], "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:37091788", "parent_hash": "sha256:01c5132da6ebc8e581fe6f94962e9111702102f74752b0e68295f57eb109b2d0", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE130001 licence not read", "asset:data:geo:GSE130001 not downloaded", "asset:data:geo:GSE13507 licence not read", "asset:data:geo:GSE13507 not downloaded", "asset:data:geo:GSE32894 licence not read", "asset:data:geo:GSE32894 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["According to the manufacturer’s instructions RNA-seq was performed using the QuantSeq kit FWD HT", "e level of significance was set at p < 0.05. RNA sequencing of BLCA samples An RNeasy Mini Kit (Qiagen,", "h38. Finally, we obtained the baseline phase RNA sequencing results for 29 patients (named the TMU-BLCA"], "order_basis": "paper_text_order:2643", "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": ["of Xi’an Jiaotong University. All cells were cultured in RPMI1640 or MEM with 10% fetal bovine serum"], "order_basis": "paper_text_order:4029", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["RS signature gene expression levels in using RT-qPCR in 4 BLCA cell lines (T24, 253J-BV, EJ, UMUC", "signature gene expression levels in using RT-qPCR in 4 BLCA cell lines (T24, 253J-BV, EJ, UMUC"], "order_basis": "paper_text_order:6263", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The 258 ERS-related genes were analyzed by Univariate Cox analysis and 75 prognosis-related genes were obtained (Supplementary Figure S5). After LASSO analysis, 21 genes were included in the Multivariable Cox analysis (Figures 6A, B). Ultimately, we developed the 4-gene prognostic signature."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}