A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33163533", "kind": "science-record", "revision": 6, "content_hash": "sha256:4b5e89ff6484385968d9b4bf71fec4a631ce4bd5b73abc187c847ed887b74d85", "created_at": "2026-11-01T15:41:15Z", "updated_at": "2026-11-01T21:24:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients.", "doi": "10.1155/2020/4037639", "pmid": "33163533", "authors": ["Zeyu Wang", "Ningning Zhang", "Jiayu Lv", "Cuihua Ma", "Jie Gu", "Yawei Du", "Yibo Qiu", "Zhiguang Zhang", "Man Li", "Yong Jiang", "Jianqiu Zhao", "Huiqin Du", "Zhiwei Zhang", "Wei Lu", "Yan Zhang"], "journal": "BioMed research international", "year": 2020, "abstract": "BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most aggressive malignancies with poor prognosis. There are many selectable treatments with good prognosis in Barcelona Clinic Liver Cancer- (BCLC-) 0, A, and B HCC patients, but the most crucial factor affecting survival is the high recurrence rate after treatments. Therefore, it is of great significance to predict the recurrence of BCLC-0, BCLC-A, and BCLC-B HCC patients.\nAIM: To develop a gene signature to enhance the prediction of recurrence among HCC patients.\nMATERIALS AND METHODS: The RNA expression data and clinical data of HCC patients were obtained from the Gene Expression Omnibus (GEO) database. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to screen primarily prognostic biomarkers in GSE14520. Multivariate Cox regression analysis was introduced to verify the prognostic role of these genes. Ultimately, 5 genes were demonstrated to be related with the recurrence of HCC patients and a gene signature was established. GSE76427 was adopted to further verify the accuracy of gene signature. Subsequently, a nomogram based on gene signature was performed to predict recurrence. Gene functional enrichment analysis was conducted to investigate the potential biological processes and pathways.\nRESULTS: We identified a five-gene signature which performs a powerful predictive ability in HCC patients. In the training set of GSE14520, area under the curve (AUC) for the five-gene predictive signature of 1, 2, and 3 years were 0.813, 0.786, and 0.766. Then, the relative operating characteristic (ROC) curves of five-gene predictive signature were verified in the GSE14520 validation set, the whole GSE14520, and GSE76427, showed good performance. A nomogram comprising the five-gene signature was built so as to show a good accuracy for predicting recurrence-free survival of HCC patients.\nCONCLUSION: The novel five-gene signature showed potential feasibility of recurrence prediction for early-stage HCC.", "claims": [{"id": "claim-data-access", "statement": "The gene expression and clinical data of HCC in our study were obtained from GEO (https://www.ncbi.nlm.nih.gov/geo).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33163533", "locator": "sections[24] \"Data Availability\" paragraph 2", "quote": "The gene expression and clinical data of HCC in our study were obtained from GEO (https://www.ncbi.nlm.nih.gov/geo)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "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:33163533"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33163533", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2020/4037639", "sha256": "sha256:efe3adcc2d89f193d0771c8a4b449dea0a4586afdac7d251997275172d68e29e", "bytes": 36262, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2020/4037639", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7604585", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "asset:table:pmid:33163533:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:54bc2d3b536385abc2676af4c242e77b00d062e8542a32b559c1ddf2de1c570a", "bytes": 769, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#tab1", "version": null, "note": "Demographic characteristics of HCC patients.", "structure": {"pmcid": "PMC7604585", "section_index": 11, "section_title": "3.1. Patient Characteristics", "row_count": 12, "column_count": 3}, "table": {"label": "Table 1", "caption": "Demographic characteristics of HCC patients.", "rows": [["Clinical and pathological variable", "GSE14520 (n = 190)", "GSE76427 (n = 100)"], ["Gender (male/female)", "161/29", "79/21"], ["Age (years)", "51.22 ± 10.75", "63.32 ± 12.8"], ["AVR-CC (no/yes/NA)", "132/53/5", "NA"], ["ALT (<=50 U/l/>50 U/l)", "117/73", "NA"], ["Main tumor size (<=5 cm/>5 cm/NA)", "133/56/1", "NA"], ["Multinodular (no/yes)", "157/33", "NA"], ["Cirrhosis (no/yes)", "16/174", "NA"], ["TNM stage (I-II/III-IV/NA)", "168/22/0", "85/14/1"], ["CLIP stage(0/1/2/3)", "94/70/25/1", "NA"], ["BCLC stage (0/A/B)", "20/148/22", "4/71/25"], ["AFP (<=300 ng/ml/>300 ng/ml/NA)", "108/79/3", "NA"]], "row_count": 12, "column_count": 3, "numeric_cells": 22, "header_rows": 1, "locator": "section[11]/table-wrap[1]#tab1"}}, {"id": "asset:table:pmid:33163533:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f46559c80f33cc8464026882d392d42b35770f5c1d3a66afac907709cd53c11e", "bytes": 1199, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#tab2", "version": null, "note": "Univariate and multivariate analyses of risk factors related to RFS in HCC patients.", "structure": {"pmcid": "PMC7604585", "section_index": 15, "section_title": "3.5. Independent Recurrence Prediction of Five-Gene Signature from Other Clinical-Pathological Variables", "row_count": 14, "column_count": 7}, "table": {"label": "Table 2", "caption": "Univariate and multivariate analyses of risk factors related to RFS in HCC patients.", "rows": [["Clinical factor", "Univariate analysis", "Multivariate analysis"], ["HR", "95% CI", "P value", "HR", "95% CI", "P value"], ["Gender (male vs. female)", "0.656", "0.300-1.440", "0.294", "", "", ""], ["Age", "0.999", "0.977-1.022", "0.940", "", "", ""], ["ALT (<=50 U/L vs. >50 U/L)", "1.022", "0.617-1.694", "0.931", "", "", ""], ["Main tumor size(<=5 cm vs. >5 cm)", "1.620", "0.958-2.740", "0.072", "", "", ""], ["Multinodular (no vs. yes)", "1.556", "0.871-2.782", "0.135", "", "", ""], ["Cirrhosis (no vs. yes)", "3.428", "0.838-14.022", "0.087", "", "", ""], ["AVR-CC (no vs. yes)", "0.700", "0.386-1.269", "0.240", "", "", ""], ["CLIP stage (0 vs. 1-5)", "0.848", "0.517-1.391", "0.514", "", "", ""], ["TNM stage (I+II vs. III+IV)", "1.758", "1.242-2.489", "0.001", "1.359", "0.906-2.038", "0.138"], ["BCLC stage", "2.586", "1.545-4.331", "<0.001", "1.926", "1.070-3.469", "0.029"], ["AFP (<=300 ng/ml vs. >300 ng/ml)", "0.784", "0.477-1.287", "0.335", "", "", ""], ["Risk score", "1.316", "1.161-1.491", "<0.001", "1.313", "1.153-1.497", "<0.001"]], "row_count": 14, "column_count": 7, "numeric_cells": 51, "header_rows": 2, "locator": "section[15]/table-wrap[1]#tab2"}}], "gaps": []}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}], "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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