Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32793465", "kind": "science-record", "revision": 6, "content_hash": "sha256:2269dcdd42d645c56cc17e5f20125ddae6ed84aa685752602e88a3e6b5145b08", "created_at": "2026-11-01T15:41:07Z", "updated_at": "2026-11-01T21:23:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival.", "doi": "10.3389/fonc.2020.01031", "pmid": "32793465", "authors": ["Renguo Guan", "Weimin Guo", "Weifeng Hong", "Ye Lin", "Xiongfeng Zou", "Ning Shi", "Dongyang Yang", "Yu Zhou", "Zhixiang Jian", "Haosheng Jin", "Weidong Lin", "Min Yu"], "journal": "Frontiers in oncology", "year": 2020, "abstract": "This study aimed to identify aberrantly methylated differentially methylated CpG sites (DMCs) and investigate their prognostic value in hepatocellular carcinoma (HCC). A total of 2,404 DMCs were selected from Gene Expression Omnibus (GEO) and validated by The Cancer Genome Atlas (TCGA). The TCGA cohort was divided into a training cohort and a validating cohort. First, the prognostic model based on six DMCs, including cg08351331, cg02910574, cg09947274, cg17589341, cg24652919, and cg26545968, was constructed based on the least absolute shrinkage and selection operator (LASSO) regression Cox analysis. The area under the curve (AUC) of the DMC-based model was 0.765 in the training cohort and 0.734 in the validating cohort. The accuracy of a model combining the DMC signature and American Joint Committee on Cancer (AJCC) stage, with an AUC of 0.795, was better than that of the DMCs or AJCC stage alone. Second, further analysis revealed that the methylation rate of cg08351331 was negatively associated with the expression of its relative gene, lipopolysaccharide-binding protein (LBP). Besides, the gene expression of LBP was significantly associated with poor overall survival in patients with hepatitis B virus (HBV) infection. Finally, these findings were confirmed by GSE57956 data and our own cohort. In conclusion, we established an accurate DMC-based prognostic model that could be combined with AJCC stage to improve the accuracy of prognostic prediction in HCC. Moreover, our preliminary data indicate that LBP may be a new key factor in HBV-induced HCC initiation through the regulation of its methylation.", "claims": [{"id": "claim-method", "statement": "Then, these survival-related DMCs were subjected to the least absolute shrinkage and selection operator (LASSO) regression Cox analysis (simulation times = 1,000) to identify a reliable DMC combination for HCC survival prediction.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32793465", "locator": "sections[6] \"Construction of the Prognosis Risk Model Based on DMCs\" paragraph 2", "quote": "Then, these survival-related DMCs were subjected to the least absolute shrinkage and selection operator (LASSO) regression Cox analysis (simulation times = 1,000) to identify a reliable DMC combination for HCC survival prediction."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in this study can be found in the Cancer Genome Atlas (https://tcgadata.nci.nih.gov/tcga/); the NCBI Gene Expression Omnibus (GSE54503, GSE57956, GSE37988, and GSE73003).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32793465", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "The datasets analyzed in this study can be found in the Cancer Genome Atlas (https://tcgadata.nci.nih.gov/tcga/); the NCBI Gene Expression Omnibus (GSE54503, GSE57956, GSE37988, and GSE73003)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:32793465"], "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:GSE37988"], "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:GSE37988"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32793465", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2020.01031", "sha256": 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