{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T18:47:03Z","timestamp":1778870823042,"version":"3.51.4"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T00:00:00Z","timestamp":1737936000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T00:00:00Z","timestamp":1737936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62201150"],"award-info":[{"award-number":["62201150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62301006"],"award-info":[{"award-number":["62301006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Jihua laboratory scienctific project","award":["X210101UZ210"],"award-info":[{"award-number":["X210101UZ210"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BioData Mining"],"DOI":"10.1186\/s13040-025-00426-z","type":"journal-article","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T08:26:28Z","timestamp":1737966388000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A generative deep neural network for pan-digestive tract cancer survival analysis"],"prefix":"10.1186","volume":"18","author":[{"given":"Lekai","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianjun","family":"Lan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqian","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liansheng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junqi","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinpeng","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haotian","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hua","family":"Chai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,27]]},"reference":[{"issue":"1","key":"426_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12859-019-3116-7","volume":"20","author":"J Xu","year":"2019","unstructured":"Xu J, Wu P, Chen Y, Meng Q, Dawood H, Dawood H. A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data. BMC Bioinformatics. 2019;20(1):1\u201311.","journal-title":"BMC Bioinformatics"},{"issue":"4","key":"426_CR2","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1093\/annonc\/mdr333","volume":"23","author":"K Hemminki","year":"2012","unstructured":"Hemminki K, Liu X, Ji J, Sundquist J, Sundquist K. Autoimmune disease and subsequent digestive tract cancer by histology. Ann Oncol. 2012;23(4):927\u201333.","journal-title":"Ann Oncol"},{"issue":"5","key":"426_CR3","doi-asserted-by":"publisher","first-page":"1476","DOI":"10.1093\/bioinformatics\/btz769","volume":"36","author":"R Chen","year":"2020","unstructured":"Chen R, Yang L, Goodison S, Sun Y. Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data. Bioinformatics. 2020;36(5):1476\u201383.","journal-title":"Bioinformatics"},{"issue":"1","key":"426_CR4","first-page":"451","volume":"10","author":"BS Chhikara","year":"2023","unstructured":"Chhikara BS, Parang K. Global Cancer statistics 2022: the trends projection analysis. Chem Biology Lett. 2023;10(1):451\u2013451.","journal-title":"Chem Biology Lett"},{"key":"426_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13073-019-0703-1","volume":"12","author":"ER Malone","year":"2020","unstructured":"Malone ER, Oliva M, Sabatini PJ, Stockley TL, Siu LL. Molecular profiling for precision cancer therapies. Genome Med. 2020;12:1\u201319.","journal-title":"Genome Med"},{"key":"426_CR6","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1016\/j.csbj.2021.01.009","volume":"19","author":"O Menyh\u00e1rt","year":"2021","unstructured":"Menyh\u00e1rt O, Gy\u0151rffy B. Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis. Comput Struct Biotechnol J. 2021;19:949\u201360.","journal-title":"Comput Struct Biotechnol J"},{"key":"426_CR7","doi-asserted-by":"crossref","unstructured":"Qarmiche N, El Kinany K, Otmani N, El Rhazi K, Chaoui NEH. Cluster analysis of dietary patterns associated with colorectal cancer derived from a Moroccan case\u2013control study. BMJ Health Care Inf 2023, 30(1).","DOI":"10.1136\/bmjhci-2022-100710"},{"issue":"1","key":"426_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-017-1188-0","volume":"18","author":"P Lin","year":"2017","unstructured":"Lin P, Troup M, Ho JW. CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data. Genome Biol. 2017;18(1):1\u201311.","journal-title":"Genome Biol"},{"issue":"1","key":"426_CR9","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1038\/nbt.4314","volume":"37","author":"E Becht","year":"2019","unstructured":"Becht E, McInnes L, Healy J, Dutertre C-A, Kwok IW, Ng LG, Ginhoux F, Newell EW. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37(1):38\u201344.","journal-title":"Nat Biotechnol"},{"issue":"9","key":"426_CR10","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41389-019-0157-8","volume":"8","author":"F Gao","year":"2019","unstructured":"Gao F, Wang W, Tan M, Zhu L, Zhang Y, Fessler E, Vermeulen L, Wang X. DeepCC: a novel deep learning-based framework for cancer molecular subtype classification. Oncogenesis. 2019;8(9):44.","journal-title":"Oncogenesis"},{"issue":"1","key":"426_CR11","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1038\/s41523-018-0079-1","volume":"4","author":"HD Couture","year":"2018","unstructured":"Couture HD, Williams LA, Geradts J, Nyante SJ, Butler EN, Marron J, Perou CM, Troester MA, Niethammer M. Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype. NPJ Breast cancer. 2018;4(1):30.","journal-title":"NPJ Breast cancer"},{"issue":"6","key":"426_CR12","doi-asserted-by":"publisher","first-page":"1248","DOI":"10.1158\/1078-0432.CCR-17-0853","volume":"24","author":"K Chaudhary","year":"2018","unstructured":"Chaudhary K, Poirion OB, Lu L, Garmire LX. Deep learning-based Multi-omics Integration robustly predicts survival in Liver Cancer. Clin Cancer Res. 2018;24(6):1248\u201359.","journal-title":"Clin Cancer Res"},{"issue":"1","key":"426_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13040-020-00222-x","volume":"13","author":"L-Y Guo","year":"2020","unstructured":"Guo L-Y, Wu A-H, Wang Y-x, Zhang L-p, Chai H, Liang X-F. Deep learning-based ovarian cancer subtypes identification using multi-omics data. BioData Min. 2020;13(1):1\u201312.","journal-title":"BioData Min"},{"issue":"16","key":"426_CR14","doi-asserted-by":"publisher","first-page":"2231","DOI":"10.1093\/bioinformatics\/btab109","volume":"37","author":"H Yang","year":"2021","unstructured":"Yang H, Chen R, Li D, Wang Z. Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data. Bioinformatics. 2021;37(16):2231\u20137.","journal-title":"Bioinformatics"},{"issue":"5","key":"426_CR15","doi-asserted-by":"publisher","first-page":"bbac377","DOI":"10.1093\/bib\/bbac377","volume":"23","author":"W Han","year":"2022","unstructured":"Han W, Cheng Y, Chen J, Zhong H, Hu Z, Chen S, Zong L, Hong L, Chan T-F, King I. Self-supervised contrastive learning for integrative single cell RNA-seq data analysis. Brief Bioinform. 2022;23(5):bbac377.","journal-title":"Brief Bioinform"},{"issue":"8","key":"426_CR16","doi-asserted-by":"publisher","first-page":"2187","DOI":"10.1093\/bioinformatics\/btac099","volume":"38","author":"Y Cheng","year":"2022","unstructured":"Cheng Y, Ma X. scGAC: a graph attentional architecture for clustering single-cell RNA-seq data. Bioinformatics. 2022;38(8):2187\u201393.","journal-title":"Bioinformatics"},{"key":"426_CR17","doi-asserted-by":"crossref","unstructured":"Guo X, Gao L, Liu X, Yin J. Improved deep embedded clustering with local structure preservation. In: Ijcai: 2017; 2017: 1753\u20131759.","DOI":"10.24963\/ijcai.2017\/243"},{"key":"426_CR18","doi-asserted-by":"crossref","unstructured":"Gan Y, Chen Y, Xu G, Guo W, Zou G. Deep enhanced constraint clustering based on contrastive learning for scRNA-seq data. Brief Bioinform 2023:bbad222.","DOI":"10.1093\/bib\/bbad222"},{"issue":"2","key":"426_CR19","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/j.cell.2018.03.022","volume":"173","author":"KA Hoadley","year":"2018","unstructured":"Hoadley KA, Yau C, Hinoue T, Wolf DM, Lazar AJ, Drill E, Shen R, Taylor AM, Cherniack AD, Thorsson V, et al. Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of Cancer. Cell. 2018;173(2):291\u2013304. e296.","journal-title":"Cell"},{"issue":"2","key":"426_CR20","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.cell.2018.03.035","volume":"173","author":"F Sanchez-Vega","year":"2018","unstructured":"Sanchez-Vega F, Mina M, Armenia J, Chatila WK, Luna A, La KC, Dimitriadoy S, Liu DL, Kantheti HS, Saghafinia S, et al. Oncogenic signaling pathways in the Cancer Genome Atlas. Cell. 2018;173(2):321\u2013e337310.","journal-title":"Cell"},{"issue":"2","key":"426_CR21","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/j.cell.2018.03.033","volume":"173","author":"L Ding","year":"2018","unstructured":"Ding L, Bailey MH, Porta-Pardo E, Thorsson V, Colaprico A, Bertrand D, Gibbs DL, Weerasinghe A, Huang KL, Tokheim C, et al. Perspective on oncogenic processes at the end of the beginning of Cancer Genomics. Cell. 2018;173(2):305\u201320. e310.","journal-title":"Cell"},{"issue":"1","key":"426_CR22","doi-asserted-by":"publisher","first-page":"8971","DOI":"10.1038\/ncomms9971","volume":"6","author":"D Aran","year":"2015","unstructured":"Aran D, Sirota M, Butte A. Systematic pan-cancer analysis of tumour purity. Nat Commun. 2015;6(1):8971.","journal-title":"Nat Commun"},{"issue":"9","key":"426_CR23","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1038\/nrd2135","volume":"5","author":"H Kantarjian","year":"2006","unstructured":"Kantarjian H, Jabbour E, Grimley J, Kirkpatrick P. Dasatinib. Nat Rev Drug Discovery. 2006;5(9):717\u20139.","journal-title":"Nat Rev Drug Discovery"},{"issue":"9","key":"426_CR24","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1038\/nchembio.1590","volume":"10","author":"GE Winter","year":"2014","unstructured":"Winter GE, Radic B, Mayor-Ruiz C, Blomen VA, Trefzer C, Kandasamy RK, Huber KV, Gridling M, Chen D, Klampfl T. The solute carrier SLC35F2 enables YM155-mediated DNA damage toxicity. Nat Chem Biol. 2014;10(9):768\u201373.","journal-title":"Nat Chem Biol"},{"issue":"1","key":"426_CR25","doi-asserted-by":"publisher","first-page":"68","DOI":"10.5114\/wo.2014.47136","volume":"2015","author":"K Tomczak","year":"2015","unstructured":"Tomczak K, Czerwi\u0144ska P, Wiznerowicz M. Review the Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp Oncology\/Wsp\u00f3\u0142czesna Onkologia. 2015;2015(1):68\u201377.","journal-title":"Contemp Oncology\/Wsp\u00f3\u0142czesna Onkologia"},{"issue":"4","key":"426_CR26","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1016\/j.cell.2017.09.028","volume":"171","author":"N Riaz","year":"2017","unstructured":"Riaz N, Havel JJ, Makarov V, Desrichard A, Urba WJ, Sims JS, Hodi FS, Mart\u00edn-Algarra S, Mandal R, Sharfman WH. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell. 2017;171(4):934\u201349. e916.","journal-title":"Cell"},{"key":"426_CR27","doi-asserted-by":"crossref","unstructured":"Hoffman-Censits JH, Grivas P, Van Der Heijden MS, Dreicer R, Loriot Y, Retz M, Vogelzang NJ, Perez-Gracia JL, Rezazadeh A, Bracarda S. IMvigor 210, a phase II trial of atezolizumab (MPDL3280A) in platinum-treated locally advanced or metastatic urothelial carcinoma (mUC). In: American Society of Clinical Oncology; 2016.","DOI":"10.1200\/jco.2016.34.2_suppl.355"},{"issue":"1","key":"426_CR28","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.cell.2016.02.065","volume":"165","author":"W Hugo","year":"2016","unstructured":"Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, Berent-Maoz B, Pang J, Chmielowski B, Cherry G. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 2016;165(1):35\u201344.","journal-title":"Cell"},{"issue":"5","key":"426_CR29","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1136\/gutjnl-2014-308483","volume":"65","author":"E Villa","year":"2016","unstructured":"Villa E, Critelli R, Lei B, Marzocchi G, Camm\u00e0 C, Giannelli G, Pontisso P, Cabibbo G, Enea M, Colopi S. Neoangiogenesis-related genes are hallmarks of fast-growing hepatocellular carcinomas and worst survival. Results from a prospective study. Gut. 2016;65(5):861\u20139.","journal-title":"Gut"},{"issue":"8","key":"426_CR30","doi-asserted-by":"publisher","first-page":"e0133562","DOI":"10.1371\/journal.pone.0133562","volume":"10","author":"D-T Chen","year":"2015","unstructured":"Chen D-T, Davis-Yadley AH, Huang P-Y, Husain K, Centeno BA, Permuth-Wey J, Pimiento JM, Malafa M. Prognostic fifteen-gene signature for early stage pancreatic ductal adenocarcinoma. PLoS ONE. 2015;10(8):e0133562.","journal-title":"PLoS ONE"},{"issue":"1","key":"426_CR31","doi-asserted-by":"publisher","first-page":"4278","DOI":"10.1038\/s41467-019-12159-9","volume":"10","author":"H Jung","year":"2019","unstructured":"Jung H, Kim HS, Kim JY, Sun J-M, Ahn JS, Ahn M-J, Park K, Esteller M, Lee S-H, Choi JK. DNA methylation loss promotes immune evasion of tumours with high mutation and copy number load. Nat Commun. 2019;10(1):4278.","journal-title":"Nat Commun"},{"issue":"10064","key":"426_CR32","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/S0140-6736(16)32455-2","volume":"389","author":"AV Balar","year":"2017","unstructured":"Balar AV, Galsky MD, Rosenberg JE, Powles T, Petrylak DP, Bellmunt J, Loriot Y, Necchi A, Hoffman-Censits J, Perez-Gracia JL. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial. Lancet. 2017;389(10064):67\u201376.","journal-title":"Lancet"},{"issue":"7","key":"426_CR33","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.","journal-title":"Nucleic Acids Res"},{"key":"426_CR34","doi-asserted-by":"crossref","unstructured":"Yu L, Liu C, Yang JYH, Yang P. Ensemble deep learning of embeddings for clustering multimodal single-cell omics data. Bioinformatics 2023:btad382.","DOI":"10.1101\/2023.02.22.529627"},{"key":"426_CR35","doi-asserted-by":"crossref","unstructured":"Liu Q, Song K. ProgCAE: a deep learning-based method that integrates multi-omics data to predict cancer subtypes. Brief Bioinform 2023:bbad196.","DOI":"10.1093\/bib\/bbad196"},{"key":"426_CR36","doi-asserted-by":"publisher","first-page":"104481","DOI":"10.1016\/j.compbiomed.2021.104481","volume":"134","author":"H Chai","year":"2021","unstructured":"Chai H, Zhou X, Zhang Z, Rao J, Zhao H, Yang Y. Integrating multi-omics data through deep learning for accurate cancer prognosis prediction. Comput Biol Med. 2021;134:104481.","journal-title":"Comput Biol Med"},{"issue":"2","key":"426_CR37","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1007\/s11831-022-09821-9","volume":"30","author":"A Dhillon","year":"2023","unstructured":"Dhillon A, Singh A, Bhalla VK. A systematic review on biomarker identification for cancer diagnosis and prognosis in multi-omics: from computational needs to machine learning and deep learning. Arch Comput Methods Eng. 2023;30(2):917\u201349.","journal-title":"Arch Comput Methods Eng"},{"issue":"1","key":"426_CR38","doi-asserted-by":"publisher","first-page":"2102","DOI":"10.1038\/s41467-023-37179-4","volume":"14","author":"P-C Tsai","year":"2023","unstructured":"Tsai P-C, Lee T-H, Kuo K-C, Su F-Y, Lee T-LM, Marostica E, Ugai T, Zhao M, Lau MC, V\u00e4yrynen JP. Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients. Nat Commun. 2023;14(1):2102.","journal-title":"Nat Commun"}],"container-title":["BioData Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-025-00426-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13040-025-00426-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-025-00426-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T08:26:36Z","timestamp":1737966396000},"score":1,"resource":{"primary":{"URL":"https:\/\/biodatamining.biomedcentral.com\/articles\/10.1186\/s13040-025-00426-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,27]]},"references-count":38,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["426"],"URL":"https:\/\/doi.org\/10.1186\/s13040-025-00426-z","relation":{},"ISSN":["1756-0381"],"issn-type":[{"value":"1756-0381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,27]]},"assertion":[{"value":"17 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"All the authors listed have approved the manuscript.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"9"}}