Identification of potential therapeutic targets from bioinformatics analysis of necroptosis and immune infiltration in acute myocardial infarction.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39261934", "kind": "science-record", "revision": 3, "content_hash": "sha256:f315bc7d596a42f55fce28b469f2206ba17417aad17c9362c6f15819d712799b", "created_at": "2026-11-01T20:29:24Z", "updated_at": "2026-11-01T22:12:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of potential therapeutic targets from bioinformatics analysis of necroptosis and immune infiltration in acute myocardial infarction.", "doi": "10.1186/s13019-024-03038-6", "pmid": "39261934", "authors": ["Likang Ma", "Keyuan Chen", "Jiakang Li", "Linfeng Xie", "Zhaofeng Zhang", "Mohammad Zarif", "Tianci Chai", "Qingsong Wu", "Liangwan Chen", "Zhihuang Qiu"], "journal": "Journal of cardiothoracic surgery", "year": 2024, "abstract": "INTRODUCTION: Acute myocardial infarction (AMI) is a serious, deadly disease with a high incidence. However, it remains unclear how necroptosis affects the pathophysiology of AMI. Using bioinformatic analyses, this study investigated necroptosis in AMI.\nMETHODS: We obtained the GSE66360 dataset related to AMI by the GEO database. Venn diagrams were used to identify necroptosis-related differential genes (NRDEGs). The genes with differential expression in AMI were analyzed using gene set enrichment analysis, and a PPI network was established. A transcription factor prediction and enrichment analysis were conducted for the NRDEGs, and the relationships between AMI, NRDEGs, and immune cells were determined. Finally, in the additional dataset, NRDEG expression levels, immune infiltration, and ROC curve analysis were confirmed, and gene expression levels were further verified experimentally.\nRESULTS: GSEA revealed that necroptosis pathways were significantly enriched in AMI. We identified 10 NRDEGs, including TNF, TLR4, FTH1 and so on. Enrichment analysis indicated that the NOD-like receptor and NF-kappa B signaling pathways were significantly enriched. Four NRDEGs, FTH1, IFNGR1, STAT3, and TLR4, were identified; however, additional datasets and further experimental validation are required to confirm their roles. In addition, we determined that a high abundance of macrophages and neutrophils prompted AMI development.\nCONCLUSIONS: In this study, four potential genes that affect the development of AMI through necroptosis (FTH1, IFNGR1, STAT3, and TLR4) were identified. In addition, we found that a high abundance of macrophages and neutrophils affected AMI. This helps determine the pathological mechanism of necroptosis and immune cells that influence AMI and provides a novel strategy for targeted therapy.", "claims": [{"id": "claim-method", "statement": "Then we performed follow-up gene set enrichment analysis (GSEA) on differential genes with adjusted p-values (< 0.05), and we identified the genes with |logFC| > 1 that were associated with necroptosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39261934", "locator": "sections[4] \"Identification of differential genes related to necroptosis\" paragraph 2", "quote": "Then we performed follow-up gene set enrichment analysis (GSEA) on differential genes with adjusted p-values (< 0.05), and we identified the genes with |logFC| > 1 that were associated with necroptosis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset(s) supporting the conclusions of this article is(are) available in the Gene Expression Omnibus database (GEO) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi. 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GSE66360, GSE60993 and GSE61144)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In this study, four potential genes that affect the development of AMI through necroptosis (FTH1, IFNGR1, STAT3, and TLR4) were identified.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39261934", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "In this study, four potential genes that affect the development of AMI through necroptosis (FTH1, IFNGR1, STAT3, and TLR4) were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In this study, four potential genes that affect the development of AMI through necroptosis (FTH1, IFNGR1, STAT3, and TLR4) were identified.", "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:39261934"], "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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As the mice were opened and their chests were exposed, the he", "ished animal models of myocardial infarction in mice (Fig. 10a) and verified levels of these gene"], "order_basis": "paper_text_order:2018", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ified levels of these gene expression. Using qPCR to detect the gene expression levels in the", "he expression levels of the mRNA obtained by qPCR, n = 4 in each group. 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