Integrative Machine Learning and Bioinformatics Approach for Identifying Key Biomarkers in Gallbladder Cancer Diagnosis and Progression.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40527859", "kind": "science-record", "revision": 3, "content_hash": "sha256:74dd0699ca542b89fac7e32c6950142c4cc59eb8f50c01c1179e3a9e928e3965", "created_at": "2026-11-01T20:30:37Z", "updated_at": "2026-11-01T22:14:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative Machine Learning and Bioinformatics Approach for Identifying Key Biomarkers in Gallbladder Cancer Diagnosis and Progression.", "doi": "10.1049/syb2.70022", "pmid": "40527859", "authors": ["Rabea Khatun", "Wahia Tasnim", "Maksuda Akter", "Md Manowarul Islam", "Md Ashraf Uddin", "Saurav Chandra Das", "Md Zulfiker Mahmud"], "journal": "IET systems biology", "year": 2025, "abstract": "Gallbladder cancer (GBC) is the most common biliary tract neoplasm. Identifying biomarkers for GBC initiation and progression remains a challenge. This study aimed to identify GBC biomarkers using machine learning and bioinformatics. Differentially expressed genes (DEGs) were identified from two microarray datasets (GSE100363, GSE139682) from the GEO database. Gene Ontology and pathway analyses were performed using DAVID. A protein-protein interaction network was constructed using STRING, and hub genes were identified via three ranking algorithms (degree, MNC and closeness centrality). Feature selection methods (Pearson correlation, recursive feature elimination) were applied to extract key gene subsets. Machine learning models (SVM, NB and RF) were trained on GSE100363 and validated on GSE139682 to assess predictive performance. Biomarkers were further validated using the GEPIA database. A total of 146 DEGs were identified, including 39 upregulated and 107 downregulated genes. Eleven hub genes were identified, with SLIT3, COL7A1 and CLDN4 strongly correlated with GBC. Machine learning results confirmed their diagnostic potential. The study highlights NTRK2, COL14A1, SCN4B, ATP1A2, SLC17A7, SLIT3, COL7A1, CLDN4, CLEC3B, ADCYAP1R1 and MFAP4 as crucial genes associated with GBC. SLIT3, COL7A1 and CLDN4 serve as highly predictive biomarkers, and findings can improve early diagnosis and prognosis, aiding clinical decision-making.", "claims": [{"id": "claim-method", "statement": "We utilised GEO2R to identify DEGs in both GBC tumour and normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40527859", "locator": "sections[6] \"DEGs Identification\" paragraph 3", "quote": "We utilised GEO2R to identify DEGs in both GBC tumour and normal samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40527859", "locator": "sections[34] \"Data Availability Statement\" paragraph 2", "quote": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 146 common differentially expressed genes, including 39 upregulated and 107 downregulated genes, and identified 11 key biomarkers for gallbladder cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40527859", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 146 DEGs were identified, including 39 upregulated and 107 downregulated genes."}, {"asset": "source:pmid:40527859", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The study highlights NTRK2, COL14A1, SCN4B, ATP1A2, SLC17A7, SLIT3, COL7A1, CLDN4, CLEC3B, ADCYAP1R1 and MFAP4 as crucial genes associated with GBC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 146 common differentially expressed genes, including 39 upregulated and 107 downregulated genes, and identified 11 key biomarkers for gallbladder cancer.", "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:40527859"], "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:GSE100363"], "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:GSE100363"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40527859", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1049/syb2.70022", "sha256": "sha256:5608b2486ece99455d46587e1593881ee6be3d938f7c4c524f011a9352f0f8b1", "bytes": 54584, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1049/syb2.70022", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12173711", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE100363", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100363", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE100363", "version": null, "note": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2679559", "GSM2679560", "GSM2679561", "GSM2679562", "GSM2679563", "GSM2679564", "GSM2679565", "GSM2679566"], "sample_count": 8, "group_sizes": null, "group_sizes_basis": null, "platform": "20795", "taxon": "Homo sapiens", "title": "Identification of differentially expressed circRNA in gallbladder cancer compared with matched normal tissue", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE139682", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE139682", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE139682", "version": null, "note": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4146148", "GSM4146149", "GSM4146150", "GSM4146151", "GSM4146152", "GSM4146153", "GSM4146154", "GSM4146155", "GSM4146156", "GSM4146157", "GSM4146158", "GSM4146159", "GSM4146160", "GSM4146161", "GSM4146162", "GSM4146163", "GSM4146164", "GSM4146165", "GSM4146166", "GSM4146167"], "sample_count": 20, "group_sizes": null, "group_sizes_basis": null, "platform": "20795", "taxon": "Homo sapiens", "title": "The gene expression profiles of gallbladder cancer", "resolution_checked_at": "2026-11-01T19:09:46Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE100363 not downloaded", "asset:data:geo:GSE100363 licence not read", "asset:data:geo:GSE139682 not downloaded", "asset:data:geo:GSE139682 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "SVM"}}, {"id": "method-2", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.7, "band": "medium", "quote": "Pearson correlation"}}, {"id": "method-3", "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-4", "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"}}, {"id": "method-5", "family": "network_analysis", "specific": "centrality", "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": "centrality"}}, {"id": "method-6", "family": null, "specific": null, "label": "GEO2R", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "We utilised GEO2R to identify DEGs in both GBC tumour and normal samples."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "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": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: support_vector_machine."}, "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": ["GSE100363", "GSE139682"], "resolved_accessions": ["GSE100363", "GSE139682"], "statements": ["The selected datasets are sourced from free and open‐access source: https://www.ncbi.nlm.nih.gov/gds."], "basis": "The paper names GSE100363, GSE139682 in National Centre for Biotechnology Information's (NCBI) Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "assets": ["source:pmid:40527859", "data:geo:GSE100363"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE100363"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:54:34Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12968, "completion_tokens": 1308, "cached_tokens": 256}}, "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:40527859", "type": "paper", "label": "pmid:40527859"}, {"id": "source:pmid:40527859", "type": "manuscript", "label": "PMID 40527859 full text"}, {"id": "data:geo:GSE100363", "type": "dataset", "label": "GEO GSE100363"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40527859", "type": "paper", "label": "pmid:40527859"}, {"id": "source:pmid:40527859", "type": "manuscript", "label": "PMID 40527859 full text"}, {"id": "data:geo:GSE100363", "type": "dataset", "label": "GEO GSE100363"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40527859", "type": "extraction", "used": ["source:pmid:40527859"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE100363", "type": "accession_resolution", "used": ["data:geo:GSE100363"], "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:40527859", "parent_hash": "sha256:136919560bceec7987bf5b5f9a0b94705e59f3b46fde71a4036781764296b223", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE100363 licence not read", "asset:data:geo:GSE100363 not downloaded", "asset:data:geo:GSE139682 licence not read", "asset:data:geo:GSE139682 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ressed genes (DEGs) were identified from two microarray datasets (GSE100363, GSE139682) from the GEO"], "order_basis": "paper_text_order:389", "id": "assay:1"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["SVM"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}