Bioinformatics Analysis of the Key Genes and Pathways in Multiple Myeloma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36090706", "kind": "science-record", "revision": 5, "content_hash": "sha256:7850f87020a4823586012d57abeb4eef34d4d5acfd18c9a6c9ef4b398a864e27", "created_at": "2026-11-01T18:15:19Z", "updated_at": "2026-11-01T22:50:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Analysis of the Key Genes and Pathways in Multiple Myeloma.", "doi": "10.2147/IJGM.S377321", "pmid": "36090706", "authors": ["Xinge Sheng", "Shuo Wang", "Meijiao Huang", "Kaiwen Fan", "Jiaqi Wang", "Quanyi Lu"], "journal": "International journal of general medicine", "year": 2022, "abstract": "Objective: To study the differentially expressed genes between multiple myeloma and healthy whole blood samples by bioinformatics analysis, find out the key genes involved in the occurrence, development and prognosis of multiple myeloma, and analyze and predict their functions.\nMethods: The gene chip data GSE146649 was downloaded from the GEO expression database. The gene chip data GSE146649 was analyzed by R language to obtain the genes with different expression in multiple myeloma and healthy samples, and the cluster analysis heat map was constructed. At the same time, the protein-protein interaction (PPI) networks of these DEGs were established by STRING and Cytoscape software. The gene co-expression module was constructed by weighted correlation network analysis (WGCNA). The hub genes were identified from key gene and central gene. TCGA database was used to analyze the expression of differentially expressed genes in patients with multiple myeloma. Finally, the expression level of TNFSF11 in whole blood samples from patients with multiple myeloma was analyzed by RT qPCR.\nResults: We identified four genes (TNFSF11, FGF2, SGMS2, IGFBP7) as hub genes of multiple myeloma. Then, TCGA database was used to analyze the survival of TNFSF11, FGF2, SGMS2 and IGFBP7 in patients with multiple myeloma. Finally, the expression level of TNFSF11 in whole blood samples from patients with multiple myeloma was analyzed by RT qPCR.\nConclusion: The study suggests that TNFSF11, FGF2, SGMS2 and IGFBP7 are important research targets to explore the pathogenesis, diagnosis and treatment of multiple myeloma.", "claims": [{"id": "claim-method", "statement": "The original data set of GSE146649 is analyzed by using GEO2R software (https://www.ncbi.nlm.nih.gov/geo/geo2r/), a network tool using R’s “limma” software package to screen DEGs between multiple myeloma and normal tissues.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36090706", "locator": "sections[4] \"Identification of Differentially Expressed Genes\" paragraph 2", "quote": "The original data set of GSE146649 is analyzed by using GEO2R software (https://www.ncbi.nlm.nih.gov/geo/geo2r/), a network tool using R’s “limma” software package to screen DEGs between multiple myeloma and normal tissues."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GEO belongs to public databases. Users can download relevant data for free for research and publish relevant articles. Our study is based on open-source data and therefore has no other conflicts of interest.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36090706", "locator": "sections[26] \"Ethics Approval and Consent to Participate\" paragraph 2", "quote": "GEO belongs to public databases. Users can download relevant data for free for research and publish relevant articles. Our study is based on open-source data and therefore has no other conflicts of interest."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified four genes (TNFSF11, FGF2, SGMS2, IGFBP7) as hub genes of multiple myeloma.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36090706", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified four genes (TNFSF11, FGF2, SGMS2, IGFBP7) as hub genes of multiple myeloma."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified four genes (TNFSF11, FGF2, SGMS2, IGFBP7) as hub genes of multiple myeloma.", "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:36090706"], "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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Users can download relevant data for free for research and publish relevant articles. Our study is based on open-source data and therefore has no other conflicts of interest.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "GEO belongs to public databases. Users can download relevant data for free for research and publish relevant articles. 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