Immune-oncology targets and therapeutic response of cell pyroptosis-related genes with prognostic implications in neuroblastoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39548036", "kind": "science-record", "revision": 3, "content_hash": "sha256:d7e438ca50bb6b841b464cc808b9fb5fec562b259dc1bf03a45250305bfc7915", "created_at": "2026-11-01T20:29:48Z", "updated_at": "2026-11-01T22:13:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immune-oncology targets and therapeutic response of cell pyroptosis-related genes with prognostic implications in neuroblastoma.", "doi": "10.1007/s12672-024-01518-8", "pmid": "39548036", "authors": ["Xingyu Liu", "Zhongya Xu", "Hanjun Yin", "Xu Zhao", "Jinjiang Duan", "Kai Zhou", "Qiyang Shen"], "journal": "Discover oncology", "year": 2024, "abstract": "OBJECTIVE: Construction of a neuroblastoma (NB) prognostic predictive model based on pyroptosis-related genes (PRGs) to improve individualized management of NB patients.\nMETHODS: The NB cohort GSE49711 was obtained from the Gene Expression Omnibus (GEO) database, and a total of 498 patients were enrolled into the study, which were randomized into a training set and a test set at a ratio of 1:1, with 250 patients in the training set and 248 patients in the test set. A risk prediction model was constructed using the training set, and the GSE49711 cohort and test set were used as internal validation to verify the reliability of the model. Independent predictors associated with prognosis were screened using univariate and multivariate COX regression analyses, and risk score models were constructed. Single-cell gene set enrichment analysis (ssGSEA) was used to assess the relationship between PRGs and the tumor immune microenvironment. Nomograms were constructed to extend the clinical usability of the model and the reliability of the model was verified using ROC curves and calibration curves. Protein interaction networks of risk genes were mapped using the String database, and the expression of PRGs in NB cell lines was staged using the CCLE database.\nRESULTS: A prognostic model was first developed with the training set: the risk score formula was (- 0.30 × GSDMB) + (- 0.46 × IL-18) + (- 0.21 × NLRP3) + (0.56 × AIM2). Patients were categorized into high- and low-risk groups based on the median risk score value. Survival analysis showed that NB patients in the high-risk group had a significantly lower survival rate than those in the low-risk group (P < 0.001). In both the GSE49711 overall cohort and the test cohort, survival analyses showed that patients in the high-risk group had significantly lower survival than those in the low-risk group (P < 0.001). Single-cell gene set enrichment analysis was used to assess the relationship between PRGs and the tumor immune microenvironment. Time-dependent ROC curves assessed the predictive performance of the nomogram in 5-, 7.5-, and 10-year survival with areas under the curve (AUC) of 0.843, 0.802 and 0.797, respectively. The calibration curves show good clinical predictive performance for nomograms.\nCONCLUSION: The results suggest that PRGs may serve as a novel prognostic marker for NB patients to provide new immunotherapeutic targets for the clinical treatment of NB patients.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate COX regression analyses were performed on the 20 included PRGs to screen for independent influences associated with prognosis, with an inclusion criterion of P < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39548036", "locator": "sections[4] \"Construction and validation of a prognostic prediction model based on PRGs\" paragraph 2", "quote": "Univariate and multivariate COX regression analyses were performed on the 20 included PRGs to screen for independent influences associated with prognosis, with an inclusion criterion of P < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39548036", "locator": "sections[21] \"Data availability\" paragraph 2", "quote": "The data that support the findings of this study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A four-gene prognostic risk model was developed with the formula (− 0.30 × GSDMB) + (− 0.46 × IL-18) + (− 0.21 × NLRP3) + (0.56 × AIM2).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39548036", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A prognostic model was first developed with the training set: the risk score formula was (− 0.30 × GSDMB) + (− 0.46 × IL-18) + (− 0.21 × NLRP3) + (0.56 × AIM2)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A four-gene prognostic risk model was developed with the formula (− 0.30 × GSDMB) + (− 0.46 × IL-18) + (− 0.21 × NLRP3) + (0.56 × AIM2).", "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:39548036"], "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:GSE49711"], "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:GSE49711"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39548036", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-024-01518-8", "sha256": 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