Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31889904", "kind": "science-record", "revision": 8, "content_hash": "sha256:8e82940597e829129907bef06b2fbed3cb0568d1bc213deb1925ee4b2a246a72", "created_at": "2026-11-01T15:40:54Z", "updated_at": "2026-11-01T22:44:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma.", "doi": "10.1186/s12935-019-1080-y", "pmid": "31889904", "authors": ["Cheng Zhang", "Bingye Zhang", "Di Meng", "Chunlin Ge"], "journal": "Cancer cell international", "year": 2019, "abstract": "BACKGROUND: The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis.\nMETHODS: The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database.\nRESULTS: We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA.\nCONCLUSIONS: Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.", "claims": [{"id": "claim-method", "statement": "In this study, GEO2R was adopted to screen for differentially methylated genes (DMGs). |t| > 2 and P < 0.05 were considered statistically significant. In addition, differentially expressed genes (DEGs) were identified using the limma R package with a threshold of |log2FoldChange| > 2 and P < 0.05. Using the lookup function (VLOOKUP) of excel, we overlapped the GSE38860 and GSE119336 datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31889904", "locator": "sections[4] \"Identification of MeDEGs\" paragraph 2", "quote": "In this study, GEO2R was adopted to screen for differentially methylated genes (DMGs). |t| > 2 and P < 0.05 were considered statistically significant. In addition, differentially expressed genes (DEGs) were identified using the limma R package with a threshold of |log2FoldChange| > 2 and P < 0.05. Using the lookup function (VLOOKUP) of excel, we overlapped the GSE38860 and GSE119336 datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are included in the article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31889904", "locator": "sections[19] \"Availability of data and materials\" paragraph 2", "quote": "The data used to support the findings of this study are included in the article."}], "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:31889904"], "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:GSE119336"], "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:GSE119336"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31889904", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12935-019-1080-y", "sha256": 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"available", "identifier": "section[10]/table-wrap[1]#Tab1", "version": null, "note": "Gene ontology enrichment analysis of MeDEGs", "structure": {"pmcid": "PMC6933876", "section_index": 10, "section_title": "Functional enrichment analysis of MeDEGs", "row_count": 43, "column_count": 5}, "table": {"label": "Table 1", "caption": "Gene ontology enrichment analysis of MeDEGs", "rows": [["Category", "Term ID", "Term description", "Count", "False discovery rate"], ["Hypermethylated downregulated genes"], ["BP_FAT", "GO:0019752", "Carboxylic acid metabolic process", "22", "5.98E−07"], ["BP_FAT", "GO:0071466", "Cellular response to xenobiotic stimulus", "9", "8.39E−05"], ["BP_FAT", "GO:0006805", "Xenobiotic metabolic process", "7", "8.00E−04"], ["BP_FAT", "GO:0042737", "Drug catabolic process", "7", "8.00E−04"], ["BP_FAT", "GO:0045861", "Negative regulation of proteolysis", "11", "8.00E−04"], ["BP_FAT", "GO:0006953", "Acute-phase response", "5", "1.30E−03"], ["BP_FAT", "GO:0010951", "Negative 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"format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:e4a4c801eb234378f131b2f9a77cb7f7dbed6fed666932dd55fc2109c50bf667", "bytes": 767, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[1]#Tab3", "version": null, "note": "Verification of the expression levels of 7 hypomethylated upregulated genes and 2 hypermethylated downregulated genes based on TCGA databases", "structure": {"pmcid": "PMC6933876", "section_index": 12, "section_title": "Verification of hub genes", "row_count": 10, "column_count": 4}, "table": {"label": "Table 3", "caption": "Verification of the expression levels of 7 hypomethylated upregulated genes and 2 hypermethylated downregulated genes based on TCGA databases", "rows": [["Category", "Gene ID", "logFC", "P value"], ["Upregulated", "TOP2A", "4.343206", "2.81E−27"], ["Upregulated", "PLK1", "4.137076", "2.59E−24"], ["Upregulated", "BIRC5", 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"evidence": {"score": 1.0, "band": "verbatim", "quote": "In this study, GEO2R was adopted to screen for differentially methylated genes (DMGs). |t| > 2 and P < 0.05 were considered statistically significant. In addition, differentially expressed genes (DEGs) were identified using the limma R package with a threshold of |log2FoldChange| > 2 and P < 0.05. Using the lookup function (VLOOKUP) of excel, we overlapped the GSE38860 and GSE119336 datasets."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "Protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "Pathway enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE119336", "GSE38860"], "resolved_accessions": ["GSE119336", "GSE38860"], "statements": ["The data used to support the findings of this study are included in the article."], "basis": "The paper names GSE119336, GSE38860 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:31889904", "data:geo:GSE119336", "asset:table:pmid:31889904:1", "asset:table:pmid:31889904:2", "asset:table:pmid:31889904:3"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE119336"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:17:41Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 33849, "completion_tokens": 1825, "cached_tokens": 792}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:31889904", "type": "paper", "label": "pmid:31889904"}, {"id": "source:pmid:31889904", "type": "manuscript", "label": "PMID 31889904 full text"}, {"id": "data:geo:GSE119336", "type": "dataset", "label": "GEO GSE119336"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:31889904", "type": "paper", "label": "pmid:31889904"}, {"id": "source:pmid:31889904", "type": "manuscript", "label": "PMID 31889904 full text"}, {"id": "data:geo:GSE119336", "type": "dataset", "label": "GEO GSE119336"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-31889904", "type": "extraction", "used": ["source:pmid:31889904"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE119336", "type": "accession_resolution", "used": ["data:geo:GSE119336"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:31889904", "parent_hash": "sha256:c512252761902a132fe442775afa6d96e0149f8df3a2c528d4ba1f7ae37d5617", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE119336 licence not read", "asset:data:geo:GSE119336 not downloaded", "asset:data:geo:GSE38860 licence not read", "asset:data:geo:GSE38860 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["In this study, GEO2R was adopted to screen for differentially methylated genes (DMGs). |t| > 2 and P < 0.05 were considered statistically significant. In addition, differentially expressed genes (DEGs) were identified using the limma R package with a threshold of |log2FoldChange| > 2 and P < 0.05. Using the lookup function (VLOOKUP) of excel, we overlapped the GSE38860 and GSE119336 datasets."], "order_basis": "analysis_only", "id": "assay:1"}]}