Identification of anoikis-related genes in heart failure: bioinformatics and experimental validation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40819162", "kind": "science-record", "revision": 3, "content_hash": "sha256:f6feed66e312e863023616f8629b4d3e436129f7cb1c7c1c16aa495059f32e44", "created_at": "2026-11-01T20:30:54Z", "updated_at": "2026-11-01T22:14:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of anoikis-related genes in heart failure: bioinformatics and experimental validation.", "doi": "10.1186/s41065-025-00532-2", "pmid": "40819162", "authors": ["Lina Zhang", "Jianjun Gu", "Yan Jiang", "Juan Xue", "Ye Zhu"], "journal": "Hereditas", "year": 2025, "abstract": "BACKGROUND: Heart failure (HF) is a common clinical syndrome caused by ventricular dysfunction and one of the leading causes of mortality worldwide. Previous studies have suggested that anoikis is relevant to HF. This study aimed to identify hub genes associated with anoikis that may offer therapeutic targets for HF.\nMATERIALS AND METHODS: Gene expression data for GSE36074 were obtained from the Gene Expression Omnibus (GEO) and anoikis-related genes (ARGs) were extracted from GeneCards. GEO2R was used to screen for differentially expressed genes (DEGs), then by overlapping DEGs with ARGs, differentially expressed ARGs (DEARGs) were screened. The biological functions of the DEARGs were determined using DAVID. Subsequently, two machine learning (ML) algorithms were employed to identify hub DEARGs: least absolute shrinkage and selection operator (LASSO) and random forest (RF). In addition, miRNA-hub DEARGs and drug-hub DEARGs networks were constructed. Lastly, the hub DEARGs were validated by quantitative reverse transcription PCR (RT-qPCR) and Immunofluorescence (IF).\nRESULTS: A total of 138 DEARGs were identified in GSE36074. Functional analysis of DEARGs revealed that they were primarily enriched in the positive regulation of the apoptotic process, PI3K-Akt, and FoxO signaling pathways. Subsequently, two hub DEARGs (Tln1 and TGFβ2) were screened using LASSO and RF algorithms. According to the miRNA-hub DEARGs networks, Tln1 and TGFβ2 were regulated by 34 and 68 miRNAs, respectively. Moreover, drug-hub DEARGs networks showed that Gemogenovatucel-t, Lerdelimumab, Belagenpumatucel-l, Fresolimumab, Bintrafusp alfa, Trabedersen and Luspatercept-aamt are potential drugs that could target TGFβ2. Finally, RT-qPCR and IF validation of two key DEARGs (Tln1 and TGFβ2) supported our bioinformatics analysis.\nCONCLUSIONS: These findings suggest that Tln1 and TGFβ2 may play important roles in HF development through the regulation of anoikis and may serve as therapeutic targets for HF.\nCLINICAL TRIAL NUMBER: Not applicable.", "claims": [{"id": "claim-method", "statement": "To further screen for hub DEARGs, two ML algorithms were employed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40819162", "locator": "sections[6] \"Identification of hub DEARGs\" paragraph 2", "quote": "To further screen for hub DEARGs, two ML algorithms were employed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "No datasets were generated or analysed during the current study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40819162", "locator": "sections[26] \"Data availability\" paragraph 2", "quote": "No datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 138 differentially expressed anoikis-related genes and selected Tln1 and TGFβ2 as the two hub DEARGs using LASSO and RF.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40819162", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 138 DEARGs were identified in GSE36074."}, {"asset": "source:pmid:40819162", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Subsequently, two hub DEARGs (Tln1 and TGFβ2) were screened using LASSO and RF algorithms."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The analysis identified 138 differentially expressed anoikis-related genes and selected Tln1 and TGFβ2 as the two hub DEARGs using LASSO and RF.", "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:40819162"], "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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RESULTS: A tot", "tial drugs that could target TGFβ2. Finally, RT-qPCR and IF validation of two key DEARGs (Tln1 an", "y quantitative reverse transcription PCR (RT-qPCR) and Immunofluorescence (IF). RESULTS: A tot", "l drugs that could target TGFβ2. Finally, RT-qPCR and IF validation of two key DEARGs (Tln1 an"], "order_basis": "paper_text_order:1063", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["tive reverse transcription PCR (RT-qPCR) and Immunofluorescence (IF). 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