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pmid:37595258
Comprehensive characterization of pyroptosis phenotypes with distinct tumor immune profiles in gastric cancer to aid immunotherapy.
Kaida Huang · Yubiao Lin · Guoqin Qiu · Shengyu Wang · Lihua Feng · Zhigao Zheng · Yingqin Gao · Xin Fan · Wenhui Zheng · Jianmin Zhuang · Fanghong Luo · Shuitu Feng
Aging · 2023 doi:10.18632/aging.204958
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Experiment
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Complete file
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Herein, this study was conducted to uncover the implication of pyroptosis in immunomodulation and tumor microenvironment (TME) in gastric cancer.\nMETHODS: Prognostic pyroptosis-related genes were extracted to identify different pyroptosis phenotypes and pyroptosis genomic phenotypes via unsupervised clustering analysis in the gastric cancer meta-cohort cohort (GSE15459, GSE62254, GSE84437, GSE26253 and TCGA-STAD). The activation of hallmark gene sets was quantified by GSVA and immune cell infiltration was estimated via ssGSEA and CIBERSORT. Through PCA algorithm, pyroptosis score was conducted. The predictors of immune response (TMB and IPS) and genetic mutations were evaluated. The efficacy of pyroptosis score in predicting immune response was verified in two anti-PD-1 therapy cohorts.\nRESULTS: Three different pyroptosis phenotypes with different prognosis, biological pathways and tumor immune microenvironment were established among 1275 gastric cancer patients, corresponding to three immune phenotypes: immune-inflamed, immune-desert, and immune-excluded. According to the pyroptosis score, patients were separated into high and low pyroptosis score groups. Low pyroptosis score indicated favorable survival outcomes, enhanced immune responses, and increased mutation frequency. Moreover, low pyroptosis score patients displayed more clinical benefits from anti-PD-1 and prolonged survival time.\nCONCLUSION: Our findings uncovered a nonnegligible role of pyroptosis in immunomodulation and TME multiformity and complicacy in gastric cancer. Quantifying the pyroptosis score in individual tumors may tailor more effective immunotherapeutic strategies.", "claims": [{"id": "claim-method", "statement": "Univariate-cox regression analysis of 33 pyroptosis-related genes showed that GPX4 (HR: 1.24 (1.06–1.46); p = 0.008), NLRP7 (HR: 0.86 (0.76–0.96; p = 0.009), CASP6 (HR: 0.87: (0.76–0.99); p = 0.032), NLRP6 (HR: 0.90 (0.82–0.99); p = 0.04), IL6 (HR: 1.07 (1.00–1.13); p = 0.047), CASP5 (HR: 0.90 (0.82–0.99); p = 0.023), CASP4 (HR: 0.84 (0.71–0.999); p = 0.048) and TIRAP (HR: 0.73 (0.59–0.91); p = 0.004) had significant correlations to prognosis across 1275 gastric cancer patients. Through the ConsensusClusterPlus package, we stratified gastric cancer specimens to three different pyroptosis phenotypes according to the expressions of above 8 prognostic pyroptosis-related genes with unsupervised clustering method (Figure 2C–2E; Supplementary Table 1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37595258", "locator": "sections[4] \"Identification of three distinct pyroptosis phenotypes in gastric cancer\" paragraph 2", "quote": "Univariate-cox regression analysis of 33 pyroptosis-related genes showed that GPX4 (HR: 1.24 (1.06–1.46); p = 0.008), NLRP7 (HR: 0.86 (0.76–0.96; p = 0.009), CASP6 (HR: 0.87: (0.76–0.99); p = 0.032), NLRP6 (HR: 0.90 (0.82–0.99); p = 0.04), IL6 (HR: 1.07 (1.00–1.13); p = 0.047), CASP5 (HR: 0.90 (0.82–0.99); p = 0.023), CASP4 (HR: 0.84 (0.71–0.999); p = 0.048) and TIRAP (HR: 0.73 (0.59–0.91); p = 0.004) had significant correlations to prognosis across 1275 gastric cancer patients. Through the ConsensusClusterPlus package, we stratified gastric cancer specimens to three different pyroptosis phenotypes according to the expressions of above 8 prognostic pyroptosis-related genes with unsupervised clustering method (Figure 2C–2E; Supplementary Table 1)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are included within the supplementary information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37595258", "locator": "sections[28] \"Availability of data and materials\" paragraph 2", "quote": "The data used to support the findings of this study are included within the supplementary information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Three pyroptosis phenotypes with distinct prognosis and immune profiles were identified in gastric cancer, and a pyroptosis score was used to stratify patients by survival, immune response, mutation status, and potential treatment sensitivity.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37595258", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Three different pyroptosis phenotypes with different prognosis, biological pathways and tumor immune microenvironment were established among 1275 gastric cancer patients, corresponding to three immune phenotypes: immune-inflamed, immune-desert, and immune-excluded."}, {"asset": "source:pmid:37595258", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "According to the pyroptosis score, patients were separated into high and low pyroptosis score groups. Low pyroptosis score indicated favorable survival outcomes, enhanced immune responses, and increased mutation frequency."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Three pyroptosis phenotypes with distinct prognosis and immune profiles were identified in gastric cancer, and a pyroptosis score was used to stratify patients by survival, immune response, mutation status, and potential treatment sensitivity.", "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:37595258"], "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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"identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE26253 not downloaded", "asset:data:geo:GSE26253 licence not read", "asset:data:geo:GSE62254 not downloaded", "asset:data:geo:GSE62254 licence not read", "asset:data:geo:GSE78220 not downloaded", "asset:data:geo:GSE78220 licence not read", "asset:data:geo:GSE84437 not downloaded", "asset:data:geo:GSE84437 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Univariate-cox regression analysis of 33 pyroptosis-related genes showed that GPX4 (HR: 1.24 (1.06–1.46); p = 0.008), NLRP7 (HR: 0.86 (0.76–0.96; p = 0.009), CASP6 (HR: 0.87: (0.76–0.99); p = 0.032), NLRP6 (HR: 0.90 (0.82–0.99); p = 0.04), IL6 (HR: 1.07 (1.00–1.13); p = 0.047), CASP5 (HR: 0.90 (0.82–0.99); p = 0.023), CASP4 (HR: 0.84 (0.71–0.999); p = 0.048) and TIRAP (HR: 0.73 (0.59–0.91); p = 0.004) had significant correlations to prognosis across 1275 gastric cancer patients. Through the ConsensusClusterPlus package, we stratified gastric cancer specimens to three different pyroptosis phenotypes according to the expressions of above 8 prognostic pyroptosis-related genes with unsupervised clustering method (Figure 2C–2E; Supplementary Table 1)."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "group_comparison", "specific": "anova", "label": "Group comparison", "dsl_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "analysis of variance"}}, {"id": "method-4", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-5", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "PCA"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["GSE15459", "GSE62254", "GSE84437", "GSE26253", "GSE78220"], "resolved_accessions": ["GSE15459", "GSE62254", "GSE84437", "GSE26253", "GSE78220"], "statements": ["The data used to support the findings of this study are included within the supplementary information files."], "basis": "The paper names GSE15459, GSE62254, GSE84437, GSE26253, GSE78220 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:37595258", "data:geo:GSE15459"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE15459"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:51:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 16477, "completion_tokens": 2219, "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:37595258", "type": "paper", "label": "pmid:37595258"}, {"id": "source:pmid:37595258", "type": "manuscript", "label": "PMID 37595258 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37595258", "type": "paper", "label": "pmid:37595258"}, {"id": "source:pmid:37595258", "type": "manuscript", "label": "PMID 37595258 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37595258", "type": "extraction", "used": ["source:pmid:37595258"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE15459", "type": "accession_resolution", "used": ["data:geo:GSE15459"], "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:37595258", "parent_hash": "sha256:a64b91ae929b81cfe7fd7fd0a0757334987bfef8667adb417b14e00e0ff0034e", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE26253 licence not read", "asset:data:geo:GSE26253 not downloaded", "asset:data:geo:GSE62254 licence not read", "asset:data:geo:GSE62254 not downloaded", "asset:data:geo:GSE78220 licence not read", "asset:data:geo:GSE78220 not downloaded", "asset:data:geo:GSE84437 licence not read", "asset:data:geo:GSE84437 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "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": ["re ultimately included for further analysis. RNA-seq profiles (FPKM value) of 32 controls and 375", "ND METHODS Sample curation and preprocessing Transcriptome data or complete patient information of gast"], "order_basis": "paper_text_order:1900", "id": "assay:1"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["e original “CEL” files of microarrays on the Affymetrix platform were obtained, with subsequent back"], "order_basis": "paper_text_order:2546", "id": "assay:2"}, {"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": ["Univariate-cox regression analysis of 33 pyroptosis-related genes showed that GPX4 (HR: 1.24 (1.06–1.46); p = 0.008), NLRP7 (HR: 0.86 (0.76–0.96; p = 0.009), CASP6 (HR: 0.87: (0.76–0.99); p = 0.032), NLRP6 (HR: 0.90 (0.82–0.99); p = 0.04), IL6 (HR: 1.07 (1.00–1.13); p = 0.047), CASP5 (HR: 0.90 (0.82–0.99); p = 0.023), CASP4 (HR: 0.84 (0.71–0.999); p = 0.048) and TIRAP (HR: 0.73 (0.59–0.91); p = 0.004) had significant correlations to prognosis across 1275 gastric cancer patients. Through the ConsensusClusterPlus package, we stratified gastric cancer specimens to three different pyroptosis phenotypes according to the expressions of above 8 prognostic pyroptosis-related genes with unsupervised clustering method (Figure 2C–2E; Supplementary Table 1)."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}