Dendritic Cell-Related Gene Signatures in Hepatocellular Carcinoma: An Analysis for Prognosis and Therapy Efficacy Evaluation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39309303", "kind": "science-record", "revision": 3, "content_hash": "sha256:aaaeef640acf5556d9b0987699fe12f8fa2a30448e7173efb514d3b196dd6bce", "created_at": "2026-11-01T20:29:29Z", "updated_at": "2026-11-01T22:12:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Dendritic Cell-Related Gene Signatures in Hepatocellular Carcinoma: An Analysis for Prognosis and Therapy Efficacy Evaluation.", "doi": "10.2147/JHC.S481338", "pmid": "39309303", "authors": ["Huasheng Huang", "Shayong Peng", "Yongguang Wei", "Chenlu Lan", "Wei Qin", "Xiwen Liao", "Cheng-Kun Yang", "Guangzhi Zhu", "Xin Zhou", "Tao Peng"], "journal": "Journal of hepatocellular carcinoma", "year": 2024, "abstract": "Background: This study aimed to identify dendritic cells (DCs) related genes in hepatocellular carcinoma (HCC) patients, establish DC-related subtypes and signatures, and correlate them with prognosis and treatment response.\nMethods: DC-related genes were screened using Weighted Gene Co-expression Network Analysis (WGCNA) based on RNA sequencing from the TCGA (374 samples), GSE14520 (242 samples), and GSE76427 datasets (115 samples), following immune infiltration assessment by the TIME method. Two DC-related subtypes in HCC were identified through unsupervised clustering. A DC-related signature (DCRS) predictive of overall survival was constructed using LASSO and Cox regression models, and validated across the three datasets. Additionally, genetic mutation characteristics, immune infiltration levels, and treatment sensitivity were explored in DCRS risk groups. The expression levels of DCRS genes and risk scores were validated in the transcriptome of 13 HCC patients receiving combined targeted therapy and immunotherapy in the Guangxi cohort using Wilcoxon test.\nResults: A signature consisting of 13 genes related to DCs was constructed, and the superior prognostic consistency of the low DCRS risk group was validated across the TCGA (P=0.003), GSE76427 (P=0.005), and GSE14520 (P=0.047) datasets. Furthermore, in the 147-sample transarterial chemoembolization (TACE) treatment dataset GSE104580, the response group exhibited lower risk scores than the non-response group (P=0.01), whereas in the 140-sample Sorafenib treatment dataset GSE109211 (P=0.041) and the 17-sample anti-PD-1 treatment dataset GSE202069 (P=0.027), the risk scores were higher in the response group. We also validated the gene expression levels of DCRS and the higher risk scores in the response group of the Guangxi cohort (P=0.034).\nConclusion: A DCRS consisting of 13 genes was established in HCC, facilitating the prediction of patient prognosis and responsiveness to TACE, targeted therapy, and immunotherapy.", "claims": [{"id": "claim-method", "statement": "In the training set, univariate Cox regression was initially performed, followed by LASSO regression analysis using the glmnet package. The resulting genes with the minimum λ value were used to construct a multivariate Cox regression model with the smallest Akaike information criterion (AIC) through stepwise regression (backward).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39309303", "locator": "sections[7] \"Identification of a DCRS for HCC\" paragraph 2", "quote": "In the training set, univariate Cox regression was initially performed, followed by LASSO regression analysis using the glmnet package. The resulting genes with the minimum λ value were used to construct a multivariate Cox regression model with the smallest Akaike information criterion (AIC) through stepwise regression (backward)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding author, Prof. Tao Peng, upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39309303", "locator": "sections[30] \"Data Sharing Statement\" paragraph 2", "quote": "The datasets used and/or analyzed during the current study are available from the corresponding author, Prof. Tao Peng, upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A dendritic cell-related signature consisting of 13 genes was established for predicting prognosis and treatment response in hepatocellular carcinoma.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39309303", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "A DCRS consisting of 13 genes was established in HCC, facilitating the prediction of patient prognosis and responsiveness to TACE, targeted therapy, and immunotherapy."}, {"asset": "source:pmid:39309303", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A signature consisting of 13 genes related to DCs was constructed, and the superior prognostic consistency of the low DCRS risk group was validated across the TCGA (P=0.003), GSE76427 (P=0.005), and GSE14520 (P=0.047) datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A dendritic cell-related signature consisting of 13 genes was established for predicting prognosis and treatment response in hepatocellular carcinoma.", "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:39309303"], "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:GSE104580"], "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:GSE104580"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39309303", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/JHC.S481338", "sha256": 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