Uncovering the pathogenesis of obesity complicated with papillary thyroid carcinoma via bioinformatics and experimental validation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37671970", "kind": "science-record", "revision": 5, "content_hash": "sha256:87766e28e09c557f129519d5cd24d089149d05314e2bd1e5073fe824790e5382", "created_at": "2026-11-01T19:02:28Z", "updated_at": "2026-11-01T22:52:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Uncovering the pathogenesis of obesity complicated with papillary thyroid carcinoma via bioinformatics and experimental validation.", "doi": "10.18632/aging.204993", "pmid": "37671970", "authors": ["Kaisheng Yuan", "Di Hu", "Xiaocong Mo", "Ruiqi Zeng", "Bing Wu", "Zunhao Zhang", "Ruixiang Hu", "Cunchuan Wang"], "journal": "Aging", "year": 2023, "abstract": "This study aimed to investigate the common molecular mechanism between obesity and papillary thyroid cancer (PTC), the most common pathological type of thyroid cancer. In this study, we obtained gene expression datasets for obesity (GSE151839) and PTC (GSE33630) from the Gene Expression Omnibus (GEO). We used the Perl program and R software to identify differentially expressed genes (DEGs) and common genes, perform GO function and KEGG pathway enrichment analysis, construct a protein-protein interaction (PPI) network, identify hub genes, and perform transcription factors (TFs) analysis. After undergoing validation in external datasets and in vitro experiments, common targets for both diseases were ultimately identified. A total of 23 genes that were differentially expressed (DEGs) between obesity and papillary thyroid carcinoma (PTC) were identified in our study. Among these DEGs, 17 genes were up-regulated while 6 genes were down-regulated. Then the top ten key genes were identified from the PPI network using cytoHubba and MCODE plug-in. Further evidence from external datasets revealed that MMP9, MNDA, TNC, and CHIT1 were identified as hub genes for both diseases. The study utilized Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST) to perform an enrichment analysis of TFs. This analysis identified ELF4 and STAT3 as common TFs for both diseases. Additionally, in vitro experiments were conducted to further analyze the clinical significance and biological functions of these TFs. The identification and investigation of hub genes and their corresponding TFs that regulate abnormalities in obesity and PTC can enhance our comprehension of the underlying connection between these two diseases, thus leading to the development of novel diagnostic approaches.", "claims": [{"id": "claim-method", "statement": "DEGs between the case and control groups for obesity and PTC were obtained using the “limma” package in R software (version 4.2.2).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37671970", "locator": "sections[13] \"Identification of DEGs\" paragraph 2", "quote": "DEGs between the case and control groups for obesity and PTC were obtained using the “limma” package in R software (version 4.2.2)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data will be made available on request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37671970", "locator": "sections[22] \"Availability of data and materials\" paragraph 2", "quote": "Data will be made available on request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "By taking the intersection of the two groups of DEGs, a total of 23 common DEGs were obtained, with 17 being up-regulated (Figure 1E) and 6 being down-regulated (Figure 1F).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37671970", "locator": "sections[3] \"Identification of DEGs\" paragraph 2", "quote": "By taking the intersection of the two groups of DEGs, a total of 23 common DEGs were obtained, with 17 being up-regulated (Figure 1E) and 6 being down-regulated (Figure 1F)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "By taking the intersection of the two groups of DEGs, a total of 23 common DEGs were obtained, with 17 being up-regulated (Figure 1E) and 6 being down-regulated (Figure 1F).", "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:37671970"], "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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