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pmid:39182089
Screening and molecular docking verification of feature genes related to phospholipid metabolism in hepatocarcinoma caused by hepatitis B.
Jian Zhang · Fengmei Zhang · Lei Zhang · Meiling Zhang · Shuye Liu · Ying Ma
Lipids in health and disease · 2024 doi:10.1186/s12944-024-02253-3
Paper
complete
Experiment
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Data
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Analysis
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Execution
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Complete file
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This study is anticipated to present a fresh perspective for disease therapy targets of hepatocarcinoma caused by hepatitis B virus in the future by screening feature genes related to phospholipid metabolism.\nMETHODS: This study analysed GSE121248 to pinpoint differentially expressed genes (DEGs). By examining the overlap between the metabolism-related genes and DEGs, the research focused on the genes involved in phospholipid metabolism. To find feature genes, functional enrichment studies were carried out and a network diagram was proposed. These findings were validated via data base of The Cancer Genome Atlas (TCGA). Further analyses included immune infiltration studies and metabolomics. Finally, the relationships between differentially abundant metabolites and feature genes were confirmed by molecular docking, providing a thorough comprehension of the molecular mechanisms.\nRESULTS: The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes. In the TCGA database, the seven feature genes also had certain diagnostic efficiency. Immune infiltration analysis revealed that feature genes regulate the infiltration of various immune cells. Metabolomics successfully identified the different metabolites of the phospholipid metabolism pathway between patients and normal individuals. The docking study indicated that different metabolites may play essential roles in causing disease by targeting feature genes.\nCONCLUSIONS: In this study, for the first time, it reveals the possible involvement of genes linked to phospholipid metabolism-related genes using bioinformatics analysis. Identifying genes and probable therapeutic targets could provide clues for the further treatment of disease.", "claims": [{"id": "claim-method", "statement": "The online analysis tool GEO2R was used for DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39182089", "locator": "sections[12] \"Selection of DEGs\" paragraph 2", "quote": "The online analysis tool GEO2R was used for DEGs."}], "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:39182089", "locator": "sections[27] \"notes\" paragraph 1", "quote": "No datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39182089", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes.", "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:39182089"], "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:GSE121248"], "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:GSE121248"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39182089", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12944-024-02253-3", "sha256": "sha256:d59230f536a46ca29487de26024a80ba26b0859e9806e6de7830d8c04edf15ba", "bytes": 33085, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12944-024-02253-3", "version": null, "note": "Full article fetched from PMC; 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