{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T02:47:00Z","timestamp":1782701220812,"version":"3.54.5"},"reference-count":66,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"King\u2019s EPSRC DRIVE-Health Centre"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background\/Objectives: Interpretation of high-dimensional molecular profiling data requires computational strategies that go beyond single-layer analyses to resolve coordinated biological programs. Although multi-omics integration has advanced latent structure discovery, translating these cross-omics signals into interpretable, functionally meaningful molecular states remains a central challenge. Methods: Here, we present an interpretable, pathway-centric multi-omics integration framework that combines expression, DNA methylation, and copy-number alteration data to capture nonlinear cross-omics interactions and enable biologically grounded representations of molecular states. We apply this framework towards oesophageal adenocarcinoma, a malignancy that remains relatively underexplored in integrative multi-omics and systems-level analyses, despite its rising incidence and poor prognosis. Results: Using samples spanning Barrett\u2019s oesophagus and oesophageal adenocarcinoma from the Oesophageal Cancer Clinical and Molecular Stratification consortium, we demonstrate the framework\u2019s ability to resolve coordinated oncogenic, metabolic, immune, and cell-cycle programs that evolve across disease states. Conclusions: Together, this work establishes a scalable and interpretable computational strategy for pathway-based multi-omics integration, along with providing a generalisable approach for molecular state assignment in complex biological systems.<\/jats:p>","DOI":"10.3390\/cancers18132080","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T02:16:44Z","timestamp":1782699404000},"page":"2080","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mapping Molecular Transitions in Barrett\u2019s-Associated Oesophageal Adenocarcinoma via Multi-Omics Integration and Pathway Activity Modelling"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7110-0856","authenticated-orcid":false,"given":"Sabaoon","family":"Zeb","sequence":"first","affiliation":[{"name":"Department of Informatics, Faculty of Natural, Mathematical and Engineering Sciences, King\u2019s College London, London WC2B 4BG, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0347-7002","authenticated-orcid":false,"given":"Pedro Henrique","family":"da Costa Avelar","sequence":"additional","affiliation":[{"name":"Department of Informatics, Faculty of Natural, Mathematical and Engineering Sciences, King\u2019s College London, London WC2B 4BG, UK"},{"name":"Institute for Infocomm Research, Agency for Science Technology and Research (A*STAR), 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2321-8091","authenticated-orcid":false,"given":"Vicky","family":"Goh","sequence":"additional","affiliation":[{"name":"Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King\u2019s College London, London SE1 7EH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8403-1282","authenticated-orcid":false,"given":"Sophia","family":"Tsoka","sequence":"additional","affiliation":[{"name":"Department of Informatics, Faculty of Natural, Mathematical and Engineering Sciences, King\u2019s College London, London WC2B 4BG, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"649","DOI":"10.5603\/rpor.102823","article-title":"An omics-based tumor microenvironment approach and its prospects","volume":"29","author":"Nema","year":"2024","journal-title":"Rep. Pract. Oncol. Radiother."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"167120","DOI":"10.1016\/j.bbadis.2024.167120","article-title":"Multi-OMICS approaches in cancer biology: New era in cancer therapy","volume":"1870","author":"Chakraborty","year":"2024","journal-title":"Biochim. Biophys. Acta (BBA)-Mol. Basis Dis."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/nrgastro.2013.150","article-title":"The\u2018\u2013omics\u2019 revolution and oesophageal adenocarcinoma","volume":"11","author":"Weaver","year":"2014","journal-title":"Nat. Rev. Gastroenterol. Hepatol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gao, Q., Wu, H., Duan, L., Lv, G., and Quan, D. (2025). Multi-omics analysis of the tumor microenvironment after metastasis: Advancing toward personalized immunotherapy and molecular targeted strategies. Front. Immunol., 16.","DOI":"10.3389\/fimmu.2025.1648987"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3735","DOI":"10.1016\/j.csbj.2021.06.030","article-title":"Integration strategies of multi-omics data for machine learning analysis","volume":"19","author":"Picard","year":"2021","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e8124","DOI":"10.15252\/msb.20178124","article-title":"Multi-Omics Factor Analysis\u2014A framework for unsupervised integration of multi-omics data sets","volume":"14","author":"Argelaguet","year":"2018","journal-title":"Mol. Syst. Biol."},{"key":"ref_7","unstructured":"Mo, Q., and Shen, R. (2025, November 01). iClusterPlus: Integrative Clustering of Multiple Genomic Data Sets. R Package Version 1.19. Available online: https:\/\/www.bioconductor.org\/packages\/\/release\/bioc\/vignettes\/iClusterPlus\/inst\/doc\/iManual.pdf."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jiang, M.Z., Aguet, F., Ardlie, K., Chen, J., Cornell, E., Cruz, D., Durda, P., Gabriel, S.B., Gerszten, R.E., and Guo, X. (2023). Canonical correlation analysis for multi-omics: Application to cross-cohort analysis. PLoS Genet., 19.","DOI":"10.1371\/journal.pgen.1010517"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.csbj.2022.11.050","article-title":"A guide to multi-omics data collection and integration for translational medicine","volume":"21","author":"Athieniti","year":"2023","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"6388","DOI":"10.1073\/pnas.1219651110","article-title":"Pathway-based personalized analysis of cancer","volume":"110","author":"Drier","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Liu, P., Page, D., Ahlquist, P., Ong, I.M., and Gitter, A. (2025). MPAC: A computational framework for inferring pathway activities from multi-omic data. bioRxiv.","DOI":"10.1101\/2024.06.15.599113"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1038\/s41467-017-02391-6","article-title":"Perturbation-response genes reveal signaling footprints in cancer gene expression","volume":"9","author":"Schubert","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"vbac016","DOI":"10.1093\/bioadv\/vbac016","article-title":"decoupleR: Ensemble of computational methods to infer biological activities from omics data","volume":"2","author":"Braunger","year":"2022","journal-title":"Bioinform. Adv."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, S., Papageorgiou, L.G., Theofilatos, K., and Tsoka, S. (2023). Optimisation models for pathway activity inference in cancer. Cancers, 15.","DOI":"10.3390\/cancers15061787"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"da Costa Avelar, P.H., Ou-Yang, L., Wu, M., and Tsoka, S. (2024). Pathway activity autoencoders for enhanced omics analysis and clinical interpretability. Proceedings of the 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE.","DOI":"10.1109\/BIBM62325.2024.10822388"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1038\/s41591-023-02676-y","article-title":"A decade of the Oesophageal Cancer Clinical and Molecular Stratification Consortium","volume":"30","author":"Peters","year":"2024","journal-title":"Nat. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1038\/s41467-022-28237-4","article-title":"Multi-omic cross-sectional cohort study of pre-malignant Barrett\u2019s esophagus reveals early structural variation and retrotransposon activity","volume":"13","author":"Jammula","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1038\/ng.3659","article-title":"Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance","volume":"48","author":"Secrier","year":"2016","journal-title":"Nat. Genet."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"100764","DOI":"10.1016\/j.mcpro.2024.100764","article-title":"Multi-omic analysis of esophageal adenocarcinoma uncovers candidate therapeutic targets and cancer-selective posttranscriptional regulation","volume":"23","author":"Mayordomo","year":"2024","journal-title":"Mol. Cell. Proteom."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"229","DOI":"10.3322\/caac.21834","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"Cancer J. Clin."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.1016\/S0140-6736(24)02226-8","article-title":"Oesophageal cancer","volume":"404","author":"Yang","year":"2024","journal-title":"Lancet"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1038\/s41575-021-00419-3","article-title":"Global burden and epidemiology of Barrett oesophagus and oesophageal cancer","volume":"18","author":"Thrift","year":"2021","journal-title":"Nat. Rev. Gastroenterol. Hepatol."},{"key":"ref_23","unstructured":"R Core Team (2016). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: http:\/\/www.R-project.org\/."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/wics.101","article-title":"Principal component analysis","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., and Melville, J. (2018). Umap: Uniform manifold approximation and projection for dimension reduction. arXiv.","DOI":"10.21105\/joss.00861"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"lqaa078","DOI":"10.1093\/nargab\/lqaa078","article-title":"ComBat-seq: Batch effect adjustment for RNA-seq count data","volume":"2","author":"Zhang","year":"2020","journal-title":"NAR Genom. Bioinform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","article-title":"Silhouettes: A graphical aid to the interpretation and validation of cluster analysis","volume":"20","author":"Rousseeuw","year":"1987","journal-title":"J. Comput. Appl. Math."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1111\/j.1469-8137.1912.tb05611.x","article-title":"The distribution of the flora in the alpine zone","volume":"11","author":"Jaccard","year":"1912","journal-title":"New Phytol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1093\/bioinformatics\/btu049","article-title":"Minfi: A flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays","volume":"30","author":"Aryee","year":"2014","journal-title":"Bioinformatics"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.cels.2015.12.004","article-title":"The molecular signatures database hallmark gene set collection","volume":"1","author":"Liberzon","year":"2015","journal-title":"Cell Syst."},{"key":"ref_32","unstructured":"Seshan, V.E., and Olshen, A. (2025, November 01). DNAcopy: DNA Copy Number Data Analysis. R Package Version 1.87.0. Available online: https:\/\/bioconductor.org\/packages\/DNAcopy."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Lawrence, M., Huber, W., Pag\u00e8s, H., Aboyoun, P., Carlson, M., Gentleman, R., Morgan, M.T., and Carey, V.J. (2013). Software for Computing and Annotating Genomic Ranges. PLoS Comput. Biol., 9.","DOI":"10.1371\/journal.pcbi.1003118"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Smedley, D., Haider, S., Ballester, B., Holland, R., London, D., Thorisson, G., and Kasprzyk, A. (2009). BioMart\u2013biological queries made easy. BMC Genom., 10.","DOI":"10.1186\/1471-2164-10-22"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"McKight, P.E., and Najab, J. (2010). Kruskal-wallis test. The Corsini Encyclopedia of Psychology, John Wiley & Sons, Inc.","DOI":"10.1002\/9780470479216.corpsy0491"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"119","DOI":"10.21037\/acs.2017.03.14","article-title":"AJCC\/UICC staging of cancers of the esophagus and esophagogastric junction: Application to clinical practice","volume":"6","author":"Rice","year":"2017","journal-title":"Ann. Cardiothorac. Surg."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Chen, X.w., and Jeong, J.C. (2007). Enhanced recursive feature elimination. Proceedings of the Sixth International Conference on Machine Learning and Applications (ICMLA 2007), IEEE.","DOI":"10.1109\/ICMLA.2007.35"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v033.i01","article-title":"Regularization paths for generalized linear models via coordinate descent","volume":"33","author":"Friedman","year":"2010","journal-title":"J. Stat. Softw."},{"key":"ref_39","unstructured":"Lundberg, S.M., and Lee, S.I. (2017). A unified approach to interpreting model predictions. NIPS\u201917: Proceedings of the 31st International Conference on Neural Information Processing Systems, Curran Associates Inc."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"786","DOI":"10.21105\/joss.00786","article-title":"iml: An R package for interpretable machine learning","volume":"3","author":"Molnar","year":"2018","journal-title":"J. Open Source Softw."},{"key":"ref_41","unstructured":"Therneau, T.M. (A Package for Survival Analysis in R, 2023). A Package for Survival Analysis in R, R Package version 3.6-3."},{"key":"ref_42","unstructured":"Kassambara, A., Kosinski, M., and Biecek, P. (Survminer: Drawing Survival Curves Using \u2019ggplot2\u2019, 2021). Survminer: Drawing Survival Curves Using \u2019ggplot2\u2019, R Package version 0.4.9."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"185","DOI":"10.2307\/2344317","article-title":"Asymptotically efficient rank invariant test procedures","volume":"135","author":"Peto","year":"1972","journal-title":"J. R. Stat. Soc. Ser. A (Gen.)"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"(2015). Pathway and network analysis of cancer genomes. Nat. Methods, 12, 615\u2013621.","DOI":"10.1038\/nmeth.3440"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1158\/0008-5472.CAN-03-2438","article-title":"Biomarkers of esophageal adenocarcinoma and Barrett\u2019s esophagus","volume":"64","author":"McManus","year":"2004","journal-title":"Cancer Res."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Barchi, A., Dell\u2019Anna, G., Massimino, L., Mandarino, F.V., Vespa, E., Viale, E., Passaretti, S., Annese, V., Malesci, A., and Danese, S. (2025). Unraveling the pathogenesis of Barrett\u2019s esophagus and esophageal adenocarcinoma: The \u201comics\u201d era. Front. Oncol., 14.","DOI":"10.3389\/fonc.2024.1458138"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.bbcan.2019.05.003","article-title":"From genetics to signaling pathways: Molecular pathogenesis of esophageal adenocarcinoma","volume":"1872","author":"Gokulan","year":"2019","journal-title":"Biochim. Biophys. Acta (BBA)-Rev. Cancer"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3155","DOI":"10.1038\/s41467-023-38891-x","article-title":"Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy","volume":"14","author":"Newell","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1682","DOI":"10.1053\/j.gastro.2020.01.044","article-title":"Identification of subtypes of Barrett\u2019s esophagus and esophageal adenocarcinoma based on DNA methylation profiles and integration of transcriptome and genome data","volume":"158","author":"Jammula","year":"2020","journal-title":"Gastroenterology"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Sun, Q., Liu, R., Zhang, H., Zong, L., Li, T., and Zhang, L. (2025). Lipidomic and transcriptomic analysis and its therapeutic implications in Chinese Kazakh patients with esophageal squamous cell carcinoma. BMC Cancer, 25.","DOI":"10.1186\/s12885-025-14858-7"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1002\/1878-0261.12902","article-title":"A novel prognostic mRNA\/miRNA signature for esophageal cancer and its immune landscape in cancer progression","volume":"15","author":"Zhao","year":"2021","journal-title":"Mol. Oncol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"e810","DOI":"10.1002\/ctm2.810","article-title":"Elevation of fatty acid desaturase 2 in esophageal adenocarcinoma increases polyunsaturated lipids and may exacerbate bile acid-induced DNA damage","volume":"12","author":"Molendijk","year":"2022","journal-title":"Clin. Transl. Med."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3101","DOI":"10.1038\/s41467-019-10898-3","article-title":"Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma","volume":"10","author":"Mourikis","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1053\/j.gastro.2017.07.007","article-title":"The evolving genomic landscape of Barrett\u2019s esophagus and esophageal adenocarcinoma","volume":"153","author":"Contino","year":"2017","journal-title":"Gastroenterology"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2300","DOI":"10.1038\/s41467-022-29767-7","article-title":"Somatic whole genome dynamics of precancer in Barrett\u2019s esophagus reveals features associated with disease progression","volume":"13","author":"Paulson","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Ergun, P., Kipcak, S., and Bor, S. (2023). Epigenetic alterations from Barrett\u2019s esophagus to esophageal adenocarcinoma. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24097817"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1016\/j.jcmgh.2022.01.023","article-title":"The immune underpinnings of Barrett\u2019s-associated adenocarcinogenesis: A retrial of nefarious immunologic co-conspirators","volume":"13","author":"Tambunting","year":"2022","journal-title":"Cell. Mol. Gastroenterol. Hepatol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"e143888","DOI":"10.1172\/jci.insight.143888","article-title":"Immune determinants of Barrett\u2019s progression to esophageal adenocarcinoma","volume":"6","author":"Lagisetty","year":"2021","journal-title":"JCI Insight"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1038\/ng.2760","article-title":"Pan-cancer patterns of somatic copy number alteration","volume":"45","author":"Zack","year":"2013","journal-title":"Nat. Genet."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1546","DOI":"10.1126\/science.1235122","article-title":"Cancer genome landscapes","volume":"339","author":"Vogelstein","year":"2013","journal-title":"Science"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.tranon.2019.10.013","article-title":"PIK3CA and KRAS amplification in esophageal adenocarcinoma and their impact on the inflammatory tumor microenvironment and prognosis","volume":"13","author":"Essakly","year":"2020","journal-title":"Transl. Oncol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"e57189","DOI":"10.7554\/eLife.57189","article-title":"Repurposing of KLF5 activates a cell cycle signature during the progression from a precursor state to oesophageal adenocarcinoma","volume":"9","author":"Rogerson","year":"2020","journal-title":"eLife"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1053\/j.gastro.2021.10.038","article-title":"Abnormal TP53 predicts risk of progression in patients with Barrett\u2019s esophagus regardless of a diagnosis of dysplasia","volume":"162","author":"Redston","year":"2022","journal-title":"Gastroenterology"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1111\/his.15442","article-title":"The future is now: Advancing p53 immunohistochemistry in Barrett\u2019s oesophagus and its implication for the everyday pathologist","volume":"88","author":"Chornenkyy","year":"2025","journal-title":"Histopathology"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"D672","DOI":"10.1093\/nar\/gkad1025","article-title":"The reactome pathway knowledgebase 2024","volume":"52","author":"Milacic","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"D672","DOI":"10.1093\/nar\/gkae909","article-title":"KEGG: Biological systems database as a model of the real world","volume":"53","author":"Kanehisa","year":"2025","journal-title":"Nucleic Acids Res."}],"container-title":["Cancers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6694\/18\/13\/2080\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T02:36:22Z","timestamp":1782700582000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6694\/18\/13\/2080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,26]]},"references-count":66,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["cancers18132080"],"URL":"https:\/\/doi.org\/10.3390\/cancers18132080","relation":{},"ISSN":["2072-6694"],"issn-type":[{"value":"2072-6694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,26]]}}}