MMP14 is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37274806", "kind": "science-record", "revision": 4, "content_hash": "sha256:3619926fffc2c12db6ca00324d393ec650d5ce9e68245e4137274167765a6fb5", "created_at": "2026-11-01T19:01:59Z", "updated_at": "2026-11-01T22:52:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "MMP14 is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration.", "doi": "10.3748/wjg.v29.i19.2961", "pmid": "37274806", "authors": ["Jun Wu", "Yang Guo", "Zhi-Fan Zuo", "Zi-Wei Zhu", "Lei Han"], "journal": "World journal of gastroenterology", "year": 2023, "abstract": "BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a malignant tumor of the hepatobiliary system with concealed onset, strong invasiveness and poor prognosis.\nAIM: To explore the disease characteristic genes that may be helpful in the diagnosis of ICC and affect immune cell infiltration.\nMETHODS: We downloaded two ICC-related human gene expression profiles from GEO database as the training group (GSE26566 and GSE32958 datasets) for difference analysis, and performed enrichment analysis on differential genes. The least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF), three machine learning algorithms, were used to screen the characteristic genes. Double verification was carried out on GSE107943 and The Cancer Genome Atlas, two verification groups. Receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the diagnostic efficacy of genes for ICC. CIBERSORT and ssGSEA algorithms were used to evaluate the effect of characteristic genes on immune infiltration pattern. Human Protein Atlas (HPA) was used to analyze the protein expression level of the target gene.\nRESULTS: A total of 1091 differential genes were obtained in the training group. Enrichment analysis showed that the above genes were mainly enriched in small molecular catabolism, complement and coagulation cascade, bile secretion and other functions and pathways. Twenty-five characteristic genes were screened by LASSO regression, 19 by SVM-RFE algorithm, and 30 by RF algorithm. Three algorithms were used in combination to determine the characteristic gene of ICC: MMP14. The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively). Comprehensive analysis of immune infiltration showed that MMP14 could affect the infiltration of monocytes, activated memory CD4 T cells, resting memory CD4 T cells, and other immune cells, and was closely related to the expression of CD200, cytotoxic T-lymphocyte-associated antigen 4, CD14, CD44, and other immune checkpoints. The results of immunohistochemistry in HPA database showed was indeed overexpressed in ICC.\nCONCLUSION: MMP14 can be used as a disease characteristic gene of ICC, and may regulate the distribution of immune-infiltrating cells in the ICC tumor microenvironment, which provides a new method for the determination of ICC diagnostic markers and screening of therapeutic targets.", "claims": [{"id": "claim-method", "statement": "The limma package was used to analyze the differences between the two verification groups of GSE107943 and TCGA to determine whether the differential expression of disease characteristic genes in the verification group was consistent with that of the training group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37274806", "locator": "sections[8] \"Assessing the diagnostic value of ICC signature genes\" paragraph 2", "quote": "The limma package was used to analyze the differences between the two verification groups of GSE107943 and TCGA to determine whether the differential expression of disease characteristic genes in the verification group was consistent with that of the training group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The bioinformatic data could be downloaded from the public databases, and no additional data are available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37274806", "locator": "sections[32] \"Data sharing statement\" paragraph 2", "quote": "The bioinformatic data could be downloaded from the public databases, and no additional data are available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37274806", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively).", "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:37274806"], "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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