Identification and Validation of a Nine-Gene Amino Acid Metabolism-Related Risk Signature in HCC.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34557495", "kind": "science-record", "revision": 7, "content_hash": "sha256:3f95c61a6dc30a1a9ef1a0938843463dcb51af9c85b632af8c5f2ce7d6da306f", "created_at": "2026-11-01T15:41:53Z", "updated_at": "2026-11-01T22:04:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of a Nine-Gene Amino Acid Metabolism-Related Risk Signature in HCC.", "doi": "10.3389/fcell.2021.731790", "pmid": "34557495", "authors": ["Yajuan Zhao", "Junli Zhang", "Shuhan Wang", "Qianqian Jiang", "Keshu Xu"], "journal": "Frontiers in cell and developmental biology", "year": 2021, "abstract": "Background: Hepatocellular carcinoma (HCC) is the world's second most deadly cancer, and metabolic reprogramming is its distinguishing feature. Among metabolite profiling, variation in amino acid metabolism supports tumor proliferation and metastasis to the most extent, yet a systematic study on the role of amino acid metabolism-related genes in HCC is still lacking. An effective amino acid metabolism-related prediction signature is urgently needed to assess the prognosis of HCC patients for individualized treatment. Materials and Methods: RNA-seq data of HCC from the TCGA-LIHC and GSE14520 (GPL3921) datasets were defined as the training set and validation set, respectively. Amino acid metabolic genes were extracted from the Molecular Signature Database. Univariate Cox and LASSO regression analyses were performed to build a predictive risk signature. K-M curves, ROC curves, and univariate and multivariate Cox regression were conducted to evaluate the predictive value of this risk signature. Functional enrichment was analyzed by GSEA and CIBERSORTx software. Results: A nine-gene amino acid metabolism-related risk signature including B3GAT3, B4GALT2, CYB5R3, GNPDA1, GOT2, HEXB, HMGCS2, PLOD2, and SEPHS1 was constructed to predict the overall survival (OS) of HCC patients. Patients were separated into high-risk and low-risk groups based on risk scores and low-risk patients had lower risk scores and longer survival time. Univariate and multivariate Cox regression verified that this signature was an independent risk factor for HCC. ROC curves showed that this risk signature can effectively predict the 1-, 2-, 3- and 5-year survival times of patients with HCC. Additionally, prognostic nomograms were established based on the training set and validation set. These genes were closely correlated with the immune regulation. Conclusion: Our study identified a nine-gene amino acid metabolism-related risk signature and built predictive nomograms for OS in HCC. These findings will help us to personalize the treatment of liver cancer patients.", "claims": [{"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34557495", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation."}], "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:34557495"], "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. 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set.", "structure": {"pmcid": "PMC8452960", "section_index": 3, "section_title": "Data Collection", "row_count": 53, "column_count": 3}, "table": {"label": "TABLE 1", "caption": "The clinicopathological characteristics of HCC patients in the training set and validation set.", "rows": [["Parameter", "", "Total (%)"], ["TCGA", "", "n = 370"], [""], ["Survival status", "Alive", "244 (65.9)"], ["", "Dead", "126 (34.1)"], ["Age", "≤65 years", "231 (62.4)"], ["", ">65 years", "138 (37.3)"], ["Gender", "Male", "249 (67.3)"], ["", "Female", "121 (32.7)"], ["Histological grade", "G1", "55 (14.9)"], ["", "G2", "177 (47.8)"], ["", "G3", "121 (32.7)"], ["", "G4", "12 (3.2)"], ["Stage", "I", "170 (45.9)"], ["", "II", "86 (23.2)"], ["", "III", "85 (23.0)"], ["", "IV", "5 (1.4)"], ["T", "T1", "180 (48.6)"], ["", "T2", "94 (25.4)"], ["", "T3", "80 (21.6)"], ["", "T4", "13 (3.5)"], ["N", "N0", "251 (67.8)"], ["", "N1", "4 (1.1)"], ["", "NA", "115 (31.1)"], ["M", "M0", "265 (71.6)"], ["", "M1", "4 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"application/vnd.jats.table+json", "uri": null, "sha256": "sha256:38307db9a157dec7e31967c9363b24061251966fc1cc27d3d937fa9cd5d50295", "bytes": 1814, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[1]#T2", "version": null, "note": "Detail information of nine genes in the risk signature.", "structure": {"pmcid": "PMC8452960", "section_index": 14, "section_title": "Building a Nine-Gene Amino Acid Metabolism-Related Risk Signature", "row_count": 10, "column_count": 3}, "table": {"label": "TABLE 2", "caption": "Detail information of nine genes in the risk signature.", "rows": [["Gene symbol", "Full name", "Function of the encoded protein"], ["B3GAT3", "Beta-1, 3-glucuronyltransferase 3", "B3GAT3 is a glycosyltransferase that plays an important role in proteoglycan (PG) biosynthesis"], ["B4GALT2", "Beta-1, 4-galactosyltransferase 2", "B4GALT2 is a beta-1, 4-galactosyltransferase (beta4GalT) and synthesizes N-acetyllactosamine in glycolipids and glycoproteins"], ["CYB5R3", "Cytochrome b5 reductase 3", "CYB5R3 encodes cytochrome b5 reductase, functions in desaturation and elongation of fatty acids, in cholesterol biosynthesis, and in drug metabolism"], ["GNPDA1", "Glucosamine-6-phosphate deaminase 1", "GNPDA1 links the hexosamine system with the glycolytic pathway and promotes the catabolism of hexosamines derived from glycoproteins, glycolipids, and sialic acids into phosphate sugars to provide energy sources"], ["GOT2", "Glutamic-oxaloacetic transaminase 2", "GOT plays a role in amino acid metabolism and the urea and tricarboxylic acid cycles"], ["HEXB", "Hexosaminidase subunit beta", "HEXB catalyzes the degradation of the ganglioside GM2, and other molecules containing terminal N-acetyl hexosamines"], ["HMGCS2", "3-hydroxy-3-methylglutaryl-CoA synthase 2", "HMGCS2 is a mitochondrial enzyme that catalyzes the first reaction of ketogenesis, a metabolic pathway that provides lipid-derived 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