Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38702814", "kind": "science-record", "revision": 3, "content_hash": "sha256:a3bdd1e1aed4ea1038c135e4b06fe04458f9c94c60a4be0ac2a276db4f29947e", "created_at": "2026-11-01T19:20:40Z", "updated_at": "2026-11-01T22:11:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.", "doi": "10.1186/s12967-024-05238-z", "pmid": "38702814", "authors": ["Yan-Jie Zhong", "Xi-Mei Luo", "Fei Liu", "Zhi-Qiang He", "Si-Qi Yang", "Wen-Jie Ma", "Jun-Ke Wang", "Yu-Shi Dai", "Rui-Qi Zou", "Ya-Fei Hu", "Tian-Run Lv", "Fu-Yu Li", "Hai-Jie Hu"], "journal": "Journal of translational medicine", "year": 2024, "abstract": "BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood.\nMETHODS: To address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue.\nRESULTS: Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs.\nCONCLUSIONS: This study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.", "claims": [{"id": "claim-method", "statement": "Additionally, we utilized Weighted Gene Coexpression Network Analysis (WGCNA) to pinpoint coexpressed gene modules most significantly linked to CAF infiltration.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38702814", "locator": "sections[5] \"Differentially expressed gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) for module identification\" paragraph 2", "quote": "Additionally, we utilized Weighted Gene Coexpression Network Analysis (WGCNA) to pinpoint coexpressed gene modules most significantly linked to CAF infiltration."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during the current study are available in the TCGA database (https://portal.gdc.cancer.gov/), GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38702814", "locator": "sections[26] \"Data availability\" paragraph 2", "quote": "The datasets generated during the current study are available in the TCGA database (https://portal.gdc.cancer.gov/), GEO database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38702814", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained.", "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:38702814"], "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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