Pyroptosis related genes signature predicts prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36127654", "kind": "science-record", "revision": 4, "content_hash": "sha256:142c66098c4b5564e0e120c016f28d5ad4b5feffa383b8b561be5ccef0edcff1", "created_at": "2026-11-01T18:15:24Z", "updated_at": "2026-11-01T22:07:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Pyroptosis related genes signature predicts prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma.", "doi": "10.1186/s12885-022-10097-2", "pmid": "36127654", "authors": ["Guoxu Fang", "Qinghua Zhang", "Jianhui Fan", "Haitao Li", "Zongren Ding", "Jun Fu", "Yijun Wu", "Yongyi Zeng", "Jingfeng Liu"], "journal": "BMC cancer", "year": 2022, "abstract": "Little is known on the relationship between the expression of pyroptosis related genes (PRGs) and prognosis of hepatocellular carcinoma (HCC). In this study, a specific PRGs prognostic model was developed with an aim to improve therapeutic efficiency among HCC patients. In total, 42 PRGs that were differentially expressed between HCC tissues and adjacent tissues and we exhibited the mutation frequency, classification, the location of copy number variation (CNV) alteration and the CNV variation frequency of PRGs. Two clusters were distinguished by the consensus clustering analysis based on the 42 differentially expressed genes (DEGs). There were significant differences in clinical features including T stage, grade, gender, and stage among different clusters. Kaplan-Meier curve analysis showed that cluster 1 had a better prognosis than cluster 2. The prognostic value of PRGs for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Based on the univariate analysis and multivariate analysis, a 10-gene signature was built and all HCC patients in the TCGA cohort were divided into low-risk group and high-risk group. HCC patients in the high-risk group showed significantly lower survival possibilities than those in the low-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, HCC patients from International Cancer Genome Consortium (ICGC)-LIRI-JP cohort and Gene Expression Omnibus (GEO) cohort (GSE14520) were divided into two risk subgroups. The result showed that overall survival (OS) time was decreased in the high-risk group. Combined with the clinical characteristics, the risk score was an independent factor for predicting the OS of HCC patients. Then, ROC curve and survival analysis were performed to evaluate the prognostic prediction value of the model. Finally, we constructed a PRGs clinical characteristics nomogram to further predict HCC patient survival probability. There were significant differences in immune cell infiltration, GSEA enrichment pathway, IC50 of chemotherapeutics, PRGs mutation frequency between high-risk group and low-risk group. This work suggests PRGs signature played a crucial role in predicting the prognosis, infiltration of cancer microenvironment, and sensitivity of chemotherapeutic agents.", "claims": [{"id": "claim-method", "statement": "To assess the prognostic value of the PRGs, Cox regression analysis was employed to evaluate the correlations between each gene and survival status in the TCGA cohort.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36127654", "locator": "sections[6] \"Development and validation of the PRGs prognostic model\" paragraph 2", "quote": "To assess the prognostic value of the PRGs, Cox regression analysis was employed to evaluate the correlations between each gene and survival status in the TCGA cohort."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data included in this study are available upon request by contact with the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36127654", "locator": "sections[30] \"Availability of data and materials\" paragraph 2", "quote": "All data included in this study are available upon request by contact with the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Patients in the high-risk group showed a higher death rate and a shorter survival time than those in the low-risk group.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36127654", "locator": "sections[15] \"Development of a prognostic gene model in the TCGA cohort\" paragraph 2", "quote": "Patients in the high-risk group showed a higher death rate and a shorter survival time than those in the low-risk group (Fig. 4C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Patients in the high-risk group showed a higher death rate and a shorter survival time than those in the low-risk group.", "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:36127654"], "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:GSE14520"], "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:GSE14520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36127654", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12885-022-10097-2", "sha256": 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