Analysis and validation of necroptosis-related diagnostic biomarkers associated with immune infiltration in bronchopulmonary dysplasia.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40735606", "kind": "science-record", "revision": 3, "content_hash": "sha256:cd0df048549b1a0266c01fccc0e491b4f4dcebe8ead2fa08dbc7c50424dd6d0f", "created_at": "2026-11-01T20:30:50Z", "updated_at": "2026-11-01T22:14:28Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Analysis and validation of necroptosis-related diagnostic biomarkers associated with immune infiltration in bronchopulmonary dysplasia.", "doi": "10.3389/fped.2025.1578628", "pmid": "40735606", "authors": ["Haixia Tu", "Changjiang Fang", "Ping Gan", "Yunyun Gu", "Nana Peng", "Honghua Jiang", "Weiwei Hou", "Guihua Shu"], "journal": "Frontiers in pediatrics", "year": 2025, "abstract": "Background: Bronchopulmonary dysplasia (BPD) is the most common serious complication in very preterm infants. This study aims to identify necroptosis-related genes (NRGs) and analyze the relationship between necroptosis-related diagnostic markers and immune infiltration in BPD.\nMethods: We obtained the dataset GSE32472 from the GEO database and analyzed the differentially expressed NRGs (DE-NRGs). We identified the biological functions and pathways of DE-NRGs. RF (random forest) and LASSO (least absolute shrinkage and selection operator) algorithms were applied to identify hub genes. We explored the immune landscape of BPD and controls by CIBERSORT. The correlations between hub genes and immune cells were evaluated using Spearman correlation analysis. ELISA was used to verify the diagnostic value of hub genes in patients with BPD in our hospital.\nResults: 27 DE-NRGs were screened. We found the primary biological functions and pathways of DE-NRGs, including necroptosis, and regulation of inflammatory response. Three hub genes (PELI1, PYGL, and STAT4) were identified and utilized to construct a diagnostic nomogram. The AUC value of the nomogram was greater than 0.7 in the validation dataset GSE188944. CIBERSORT showed that the proportions of 6 different immune cell types in the BPD group were higher or lower than the control group (P < 0.05). Correlation analysis showed that three hub genes may correlate with immune cells to varying degrees. Serum ELISA results of PELI1 and PYGL showed no significant difference between BPD and Controls (P > 0.05), the expression level of STAT4 was downregulated in BPD samples (P < 0.05), and the AUC value of the STAT4 was higher than 0.7.\nConclusion: The necroptosis-related gene STAT4 can be a diagnostic marker of BPD patients. The necroptosis-related gene and immune infiltration may be related to the progression of BPD.", "claims": [{"id": "claim-method", "statement": "ROC (receiver operating characteristic) curves were used to assess the diagnostic value of hub genes in BPD, and ROC curve analysis was conducted with the “pROC” R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40735606", "locator": "sections[7] \"Diagnostic value of hub genes on the 5th, and 14th days of life\" paragraph 2", "quote": "ROC (receiver operating characteristic) curves were used to assess the diagnostic value of hub genes in BPD, and ROC curve analysis was conducted with the “pROC” R package."}], "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:40735606", "locator": "sections[23] \"Data availability statement\" 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 necroptosis-related gene STAT4 can be a diagnostic marker of BPD patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40735606", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The necroptosis-related gene STAT4 can be a diagnostic marker of BPD patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The necroptosis-related gene STAT4 can be a diagnostic marker of BPD patients.", "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:40735606"], "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:GSE188944"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:student_t", "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:GSE188944"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:student_t"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40735606", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fped.2025.1578628", "sha256": "sha256:4c08d4700abc7e797715ccc7ac9531ae717ce52a7f1c0e87269896d25893f919", "bytes": 28008, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fped.2025.1578628", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12303952", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE188944", "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=GSE188944", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE188944", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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