Identification and Validation of Inflammatory Response-Related Gene Signatures to Predict the Prognosis of Neuroblastoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35535346", "kind": "science-record", "revision": 3, "content_hash": "sha256:b83b3f507c1d55571ac7dae0fcabb729c2022e5cea4ae5d0831224b76d277942", "created_at": "2026-11-01T18:14:25Z", "updated_at": "2026-11-01T21:27:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Inflammatory Response-Related Gene Signatures to Predict the Prognosis of Neuroblastoma.", "doi": "10.1155/2022/2417351", "pmid": "35535346", "authors": ["Jiye Song", "Liang Song", "Zhenmei Lv", "Jianke Liu", "Xuan Feng", "Song Zhang", "Aiqin Song"], "journal": "International journal of genomics", "year": 2022, "abstract": "Background: Neuroblastoma (NB) is the third most common malignant tumor in children. The inflammation is believed to be closely related to NB patients' prognosis. However, there is no comprehensive research to study the role of inflammatory response-related gene (IRRG) in NB patients.\nMethods: We downloaded the gene expression profiles of NB patients from GEO and TARGET database, and the expression of 200 IRRGs was extracted. Then, we performed differentially analysis between INSS stage 4 and INSS stage 4S NB patients. The univariate and multivariate Cox regression analyses were performed to screen out the overall survival- (OS-) and event-free survival- (EFS-) related IRRGs in GSE49710, and two signatures were constructed; both signatures were evaluated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic (ROC) curve. Finally, the TARGET cohort was used to validate IRRG signatures, and the independence of the prognostic IRRG signatures was evaluated by integrating clinical information.\nResults: We screened out 10 OS-related IRRGs and 11 EFS-related IRRGs. Then, we identified that OS- and EFS-related IRRG signatures and found that the OS and EFS of NB patients in the low-risk group were significantly superior than those in the high-risk group (both P value < 0.0001). The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, respectively. In addition, we found that both IRRG signatures can be used as independent prognostic indicators for patients with NB. Both IRRG signatures still have good predictive ability in validation cohort.\nConclusions: We constructed and validated two prognostic gene signatures based on IRRGs. Our study helped us to better understand the role of inflammation in NB and provided new insights for the prognosis assessment and treatment strategy for NB patients.", "claims": [{"id": "claim-method", "statement": "Univariate Cox analysis, LASSO analysis, and multivariate Cox regression analysis were selected for survival analyses and construct prognostic signature.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35535346", "locator": "sections[8] \"2.6. Statistical Analyses\" paragraph 2", "quote": "Univariate Cox analysis, LASSO analysis, and multivariate Cox regression analysis were selected for survival analyses and construct prognostic signature."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35535346", "locator": "sections[18] \"Data Availability\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35535346", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, 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:35535346"], "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:GSE49710"], "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:GSE49710"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35535346", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/2417351", "sha256": "sha256:90aa6196e4351e0f6ffff89a24c86373bc61c46b948acd05d03b731fb29228f1", "bytes": 39935, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/2417351", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9078807", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE49710", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49710", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE49710", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. 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