Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38455135", "kind": "science-record", "revision": 5, "content_hash": "sha256:95eddd1f64d3df2154c7cac785dff86fe2197ef6e8244e9fd5c082beb7607523", "created_at": "2026-11-01T19:20:23Z", "updated_at": "2026-11-01T22:53:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data.", "doi": "10.5306/wjco.v15.i2.329", "pmid": "38455135", "authors": ["Li-Hua Zhu", "Jun Yang", "Yun-Fei Zhang", "Li Yan", "Wan-Rong Lin", "Wei-Qing Liu"], "journal": "World journal of clinical oncology", "year": 2024, "abstract": "BACKGROUND: Pyroptosis impacts the development of malignant tumors, yet its role in colorectal cancer (CRC) prognosis remains uncertain.\nAIM: To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration.\nMETHODS: Gene expression data were obtained from The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus (GEO). Pyroptosis-related gene expression in cell clusters was analyzed, and enrichment analysis was conducted. A pyroptosis-related risk model was developed using the LASSO regression algorithm, with prediction accuracy assessed through K-M and receiver operating characteristic analyses. A nomogram predicting survival was created, and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations. Finally, the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database.\nRESULTS: An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B, SDHB, BST2, UBE2D2, GJA1, AIM2, PDCD6IP, and SEZ6L2 (P < 0.05). Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis (P < 0.05). Patients with higher risk scores demonstrated increased death risk and reduced overall survival (P < 0.05). Significant differences in immune infiltration were observed between low- and high-risk groups, correlating with pyroptosis-related gene expression.\nCONCLUSION: We developed a pyroptosis-related prognostic model for CRC, affirming its correlation with immune infiltration. This model may prove useful for CRC prognostic evaluation.", "claims": [{"id": "claim-method", "statement": "The LASSO-COX regression algorithm was applied to establish the prognostic model, and the risk score calculation formula was defined as: RiskScore =∑iCoefficient (genei) × expression (genei).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38455135", "locator": "sections[16] \"Model construction and evaluation for clinical prognosis\" paragraph 2", "quote": "The LASSO-COX regression algorithm was applied to establish the prognostic model, and the risk score calculation formula was defined as: RiskScore =∑iCoefficient (genei) × expression (genei)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The scRNA-seq dataset GSE178341, obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database[28], encompasses 61 CRC and 27 non-malignant colorectal tissues.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38455135", "locator": "sections[4] \"Data source\" paragraph 2", "quote": "The scRNA-seq dataset GSE178341, obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database[28], encompasses 61 CRC and 27 non-malignant colorectal tissues."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The pyroptosis-related risk score showed favorable predictive ability for overall survival in colorectal cancer, with AUC values of 63.8% and 63.6% in the training and validation sets, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38455135", "locator": "sections[30] \"Construction and validation of a pyroptosis-related prognostic model\" paragraph 4", "quote": "The results indicated a favorable predictive ability of the risk score for OS in CRC patients, with area under curve (AUC) values of 63.8% and 63.6% for the training and validation sets, respectively (Figure 9E and F)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The pyroptosis-related risk score showed favorable predictive ability for overall survival in colorectal cancer, with AUC values of 63.8% and 63.6% in the training and validation sets, respectively.", "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:38455135"], "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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