{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:16:32Z","timestamp":1776399392362,"version":"3.51.2"},"reference-count":41,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fili\u00e8re Sant\u00e9 Maladie Rare du Foie de l\u2019Adulte et de l\u2019Enfant","award":["MEAE AMBASS FRANCE AU PEROU FSPI - S-AC23007"],"award-info":[{"award-number":["MEAE AMBASS FRANCE AU PEROU FSPI - S-AC23007"]}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Biomolecules"],"abstract":"<jats:p>Hepatoblastoma is the most common primary liver cancer in children. Poor outcomes are primarily associated with patients who have distant metastases. Using the Mammalian Metabolic Enzyme Database, we investigated the overexpression of metabolic enzymes in hepatoblastoma tumors compared to noncancerous liver tissue in the GSE131329 transcriptome dataset. For the overexpressed enzymes, we applied ElasticNet machine learning to assess their predictive value for metastasis. A metabolic expression score was then computed from the significant enzymes and integrated into a clinical-biological logistic regression model. Forty-one overexpressed enzymes distinguished hepatoblastoma tumors from noncancerous liver tissues. Eighteen of these enzymes predicted metastasis status with an AUC of 0.90, demonstrating 85.7% sensitivity and 92.3% specificity. ElasticNet machine learning identified DNMT3B and PFKFB4 as key predictors of metastasis. Univariate analyses confirmed the significance of these enzymes, with respective p-values of 0.0058 and 0.0091. A metabolic score based on DNMT3B and PFKFB4 expression discriminated metastasis status and high-risk CHIC scores (p-value = 0.005). The metabolic score was more sensitive than the C1\/C2 classifier in predicting metastasis (accuracy: 0.72 vs. 0.55). In a regression model integrating the metabolic score with epidemiological parameters (gender, age at diagnosis, histological type, and clinical PRETEXT stage), the metabolic score was confirmed as an independent adverse predictor of metastasis (p-value = 0.003, odds ratio: 2.12). This study identified the dual overexpression of PFKFB4 and DNMT3B in hepatoblastoma patients at risk of metastasis (high-risk CHIC classification). The combined tumor expression of DNMT3B and PFKFB4 was used to compute a metabolic score, which was validated as an independent predictor of metastatic status in hepatoblastoma.<\/jats:p>","DOI":"10.3390\/biom14111394","type":"journal-article","created":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T04:59:54Z","timestamp":1730437194000},"page":"1394","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Single-Cell RNA-Seq Analysis Links DNMT3B and PFKFB4 Transcriptional Profiles with Metastatic Traits in Hepatoblastoma"],"prefix":"10.3390","volume":"14","author":[{"given":"Christophe","family":"Desterke","sequence":"first","affiliation":[{"name":"Facult\u00e9 de M\u00e9decine du Kremlin Bic\u00eatre, Universit\u00e9 Paris-Sud, Universit\u00e9 Paris-Saclay, 94270 Le Kremlin-Bic\u00eatre, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1428-4852","authenticated-orcid":false,"given":"Raquel","family":"Franc\u00e9s","sequence":"additional","affiliation":[{"name":"Cell and Tissue Biology Group, Anatomy and Cell Biology Department, University of Cantabria-IDIVAL, 39011 Santander, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1215-5857","authenticated-orcid":false,"given":"Claudia","family":"Monge","sequence":"additional","affiliation":[{"name":"International Joint Laboratory of Molecular Anthropological Oncology (LOAM), IRD, INEN, Lima 15038, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6541-5395","authenticated-orcid":false,"given":"Agn\u00e8s","family":"Marchio","sequence":"additional","affiliation":[{"name":"International Joint Laboratory of Molecular Anthropological Oncology (LOAM), IRD, INEN, Lima 15038, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9407-1592","authenticated-orcid":false,"given":"Pascal","family":"Pineau","sequence":"additional","affiliation":[{"name":"International Joint Laboratory of Molecular Anthropological Oncology (LOAM), IRD, INEN, Lima 15038, Peru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5726-8814","authenticated-orcid":false,"given":"Jorge","family":"Mata-Garrido","sequence":"additional","affiliation":[{"name":"Cell and Tissue Biology Group, Anatomy and Cell Biology Department, University of Cantabria-IDIVAL, 39011 Santander, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/S1470-2045(00)00018-8","article-title":"SIOPEL Trials Using Preoperative Chemotherapy in Hepatoblastoma","volume":"1","author":"Perilongo","year":"2000","journal-title":"Lancet Oncol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1053\/jpsu.2002.32886","article-title":"Outcome of Hepatoblastoma Treated with the JPLT-1 (Japanese Study Group for Pediatric Liver Tumor) Protocol-1: A Report from the Japanese Study Group for Pediatric Liver Tumor","volume":"37","author":"Sasaki","year":"2002","journal-title":"J. Pediatr. Surg."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/S1470-2045(16)30598-8","article-title":"Risk-Stratified Staging in Paediatric Hepatoblastoma: A Unified Analysis from the Children\u2019s Hepatic Tumors International Collaboration","volume":"18","author":"Meyers","year":"2017","journal-title":"Lancet Oncol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1002\/pbc.23069","article-title":"Prognostic Implications of Serum Alpha-Fetoprotein Response during Treatment of Hepatoblastoma","volume":"57","author":"Koh","year":"2011","journal-title":"Pediatr. Blood Cancer"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1016","DOI":"10.1002\/pbc.22088","article-title":"Predictive Power of Pretreatment Prognostic Factors in Children with Hepatoblastoma: A Report from the Children\u2019s Oncology Group","volume":"53","author":"Meyers","year":"2009","journal-title":"Pediatr. Blood Cancer"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1007\/BF02471004","article-title":"The Clinical Features and Prognosis of Hepatoblastoma: Follow-up Studies Done on Pediatric Tumors Enrolled in the Japanese Pediatric Tumor Registry between 1971 and 1980. Part I","volume":"20","author":"Hata","year":"1990","journal-title":"Jpn. J. Surg."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00383-010-2708-0","article-title":"Outcome of Hepatoblastomas Treated Using the Japanese Study Group for Pediatric Liver Tumor (JPLT) Protocol-2: Report from the JPLT","volume":"27","author":"Hishiki","year":"2011","journal-title":"Pediatr. Surg. Int."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.ejca.2015.09.023","article-title":"The Children\u2019s Hepatic Tumors International Collaboration (CHIC): Novel Global Rare Tumor Database Yields New Prognostic Factors in Hepatoblastoma and Becomes a Research Model","volume":"52","author":"Czauderna","year":"2016","journal-title":"Eur. J. Cancer"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Hiyama, E. (2019). Gene Expression Profiling in Hepatoblastoma Cases of the Japanese Study Group for Pediatric Liver Tumors-2 (JPLT-2) Trial, Science Repository OU.","DOI":"10.31487\/j.EJMC.2018.01.003"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1038\/s41576-020-0270-8","article-title":"The Evolving Metabolic Landscape of Chromatin Biology and Epigenetics","volume":"21","author":"Dai","year":"2020","journal-title":"Nat. Rev. Genet."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1002\/jcb.10286","article-title":"Chromatin Remodeling, Histone Modifications, and DNA Methylation\u2014How Does It All Fit Together?","volume":"87","author":"Geiman","year":"2002","journal-title":"J. Cell. Biochem."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1038\/nm.2305","article-title":"Cancer Epigenetics Reaches Mainstream Oncology","volume":"17","author":"Esteller","year":"2011","journal-title":"Nat. Med."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.3892\/ol.2016.4789","article-title":"Genome-Wide Analysis of DNA Methylation in Hepatoblastoma Tissues","volume":"12","author":"Cui","year":"2016","journal-title":"Oncol. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1846","DOI":"10.1093\/bioinformatics\/btm254","article-title":"GEOquery: A Bridge between the Gene Expression Omnibus (GEO) and BioConductor","volume":"23","author":"Davis","year":"2007","journal-title":"Bioinformatics"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"D991","DOI":"10.1093\/nar\/gks1193","article-title":"NCBI GEO: Archive for Functional Genomics Data Sets\u2014Update","volume":"41","author":"Barrett","year":"2013","journal-title":"Nucleic Acids Res."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Monge, C., Franc\u00e9s, R., Marchio, A., Pineau, P., Desterke, C., and Matta-Garrido, J. (2024). Activated Metabolic Transcriptional Program in Tumor Cells from Hepatoblastoma. Int. J. Mol. Sci. Preprints, 2024090699.","DOI":"10.20944\/preprints202409.0699.v1"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"F533","DOI":"10.1152\/ajprenal.00601.2016","article-title":"From 20th Century Metabolic Wall Charts to 21st Century Systems Biology: Database of Mammalian Metabolic Enzymes","volume":"312","author":"Corcoran","year":"2017","journal-title":"Am. J. Physiol. Ren. Physiol."},{"key":"ref_18","first-page":"1","article-title":"FactoMineR: An R Package for Multivariate Analysis","volume":"25","author":"Josse","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., and M\u00fcller, M. (2011). pROC: An Open-Source Package for R and S+ to Analyze and Compare ROC Curves. BMC Bioinform., 12.","DOI":"10.1186\/1471-2105-12-77"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building Predictive Models in R Using the Caret Package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Soft."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tay, J.K., Narasimhan, B., and Hastie, T. (2023). Elastic Net Regularization Paths for All Generalized Linear Models. J. Stat. Soft., 106.","DOI":"10.18637\/jss.v106.i01"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1198\/106186007X237856","article-title":"Residual-Based Shadings for Visualizing (Conditional) Independence","volume":"16","author":"Zeileis","year":"2007","journal-title":"J. Comput. Graph. Stat."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.ccr.2008.11.002","article-title":"Hepatic Stem-like Phenotype and Interplay of Wnt\/Beta-Catenin and Myc Signaling in Aggressive Childhood Liver Cancer","volume":"14","author":"Cairo","year":"2008","journal-title":"Cancer Cell"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/S0168-9525(98)01636-9","article-title":"The DNA Methylation Paradox","volume":"15","author":"Jones","year":"1999","journal-title":"Trends Genet."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Rivas, M.P., Aguiar, T.F.M., Fernandes, G.R., Caires-J\u00fanior, L.C., Goulart, E., Telles-Silva, K.A., Cypriano, M., De Toledo, S.R.C., Rosenberg, C., and Carraro, D.M. (2019). TET Upregulation Leads to 5-Hydroxymethylation Enrichment in Hepatoblastoma. Front. Genet., 10.","DOI":"10.3389\/fgene.2019.00553"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"226","DOI":"10.14715\/cmb\/2022.68.1.27","article-title":"Role of DNA Methyltransferases (DNMTs) in Metastasis","volume":"68","author":"Qureshi","year":"2022","journal-title":"Cell Mol. Biol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1158\/0008-5472.CAN-18-0692","article-title":"DNA Methylation Controls Metastasis-Suppressive 14q32-Encoded miRNAs","volume":"79","author":"Oshima","year":"2019","journal-title":"Cancer Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3527","DOI":"10.3892\/or.2017.5579","article-title":"MicroRNA-26a Inhibits Proliferation and Metastasis of Human Hepatocellular Carcinoma by Regulating DNMT3B-MEG3 Axis","volume":"37","author":"Li","year":"2017","journal-title":"Oncol. Rep."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1042\/BJ20040752","article-title":"6-Phosphofructo-2-Kinase\/Fructose-2,6-Bisphosphatase: Head-to-Head with a Bifunctional Enzyme That Controls Glycolysis","volume":"381","author":"Rider","year":"2004","journal-title":"Biochem. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"6670","DOI":"10.18632\/oncotarget.2213","article-title":"Fructose-2,6-Bisphosphate Synthesis by 6-Phosphofructo-2-Kinase\/Fructose-2,6-Bisphosphatase 4 (PFKFB4) Is Required for the Glycolytic Response to Hypoxia and Tumor Growth","volume":"5","author":"Chesney","year":"2014","journal-title":"Oncotarget"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6248","DOI":"10.7150\/thno.28721","article-title":"CD44ICD Promotes Breast Cancer Stemness via PFKFB4-Mediated Glucose Metabolism","volume":"8","author":"Gao","year":"2018","journal-title":"Theranostics"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1016\/j.biochi.2005.04.007","article-title":"Overexpression of 6-Phosphofructo-2-Kinase\/Fructose-2,6-Bisphosphatase-4 in the Human Breast and Colon Malignant Tumors","volume":"87","author":"Minchenko","year":"2005","journal-title":"Biochimie"},{"key":"ref_33","first-page":"46","article-title":"6-Phosphofructo-2-Kinase\/Fructose-2,6-Bisphosphatase Gene Family Overexpression in Human Lung Tumor","volume":"77","author":"Minchenko","year":"2005","journal-title":"Ukr. Biokhim. Zh."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1016\/j.jcmgh.2023.02.015","article-title":"PFKFB4 Is a Metabolic Driver of HCC Progression and Chemoresistance Through ROS Mitigation","volume":"15","author":"Olaizola","year":"2023","journal-title":"Cell. Mol. Gastroenterol. Hepatol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"111756","DOI":"10.1016\/j.celrep.2022.111756","article-title":"Hypoxic Activation of PFKFB4 in Breast Tumor Microenvironment Shapes Metabolic and Cellular Plasticity to Accentuate Metastatic Competence","volume":"41","author":"Dai","year":"2022","journal-title":"Cell Rep."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1038\/s41586-018-0018-1","article-title":"Metabolic Enzyme PFKFB4 Activates Transcriptional Coactivator SRC-3 to Drive Breast Cancer","volume":"556","author":"Dasgupta","year":"2018","journal-title":"Nature"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e202201377","DOI":"10.26508\/lsa.202201377","article-title":"PFKFB4 Interacts with ICMT and Activates RAS\/AKT Signaling-Dependent Cell Migration in Melanoma","volume":"5","author":"Sittewelle","year":"2022","journal-title":"Life Sci. Alliance"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Hsin, M.-C., Hsieh, Y.-H., Hsiao, Y.-H., Chen, P.-N., Wang, P.-H., and Yang, S.-F. (2021). Carbonic Anhydrase IX Promotes Human Cervical Cancer Cell Motility by Regulating PFKFB4 Expression. Cancers, 13.","DOI":"10.3390\/cancers13051174"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4372","DOI":"10.7150\/ijbs.72397","article-title":"DNMT3B-mediated FAM111B methylation promotes papillary thyroid tumor glycolysis, growth and metastasis","volume":"18","author":"Zhu","year":"2022","journal-title":"Int. J. Biol. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Shen, L., Du, J., Xia, Y., Tan, Z., Fu, Y., Yang, Q., Li, X., Tang, G., Jiang, Y., and Wang, J. (2016). Genome-wide landscape of DNA methylomes and their relationship with mRNA and miRNA transcriptomes in oxidative and glycolytic skeletal muscles. Sci. Rep., 6.","DOI":"10.1038\/srep32186"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1002\/jcb.22684","article-title":"Transcriptional and post-transcriptional control of DNA methyltransferase 3B is regulated by phosphatidylinositol 3 kinase\/Akt pathway in human hepatocellular carcinoma cell lines","volume":"111","author":"Mei","year":"2010","journal-title":"J. Cell Biochem."}],"updated-by":[{"DOI":"10.3390\/biom15060769","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000}}],"container-title":["Biomolecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-273X\/14\/11\/1394\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T15:07:02Z","timestamp":1754233622000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-273X\/14\/11\/1394"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,31]]},"references-count":41,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["biom14111394"],"URL":"https:\/\/doi.org\/10.3390\/biom14111394","relation":{"correction":[{"id-type":"doi","id":"10.3390\/biom15060769","asserted-by":"object"}]},"ISSN":["2218-273X"],"issn-type":[{"value":"2218-273X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,31]]}}}