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Traditional single-omics approaches often fail to capture this complexity. Multi-omics integration offers a more holistic understanding, but many existing methods either lack interpretability or fail to model cross-omics correlations effectively. Methods: we developed MOFNet, a novel supervised deep learning framework for multi-omics integration, incorporating a similarity graph pooling (SGO) module and a view correlation discovery network (VCDN). MOFNet processes omics data\u2014including mRNA expression, DNA methylation, and miRNA expression\u2014via omics-specific graph learning and cross-omics label space fusion. Three cancer types\u2014breast cancer (BRCA), low-grade glioma (LGG), and stomach adenocarcinoma (STAD)\u2014were analyzed using datasets from the cancer genome atlas (TCGA). Statistical evaluation was performed using accuracy, weighted F1 score, and macro F1 score across stratified training\/testing splits. Results: MOFNet achieved superior performance across all datasets. For BRCA, it obtained an accuracy of 85.17%, F1_weighted of 85.36%, and macro F1 of 80.93%, outperforming all baseline models by up to 18.25%. In LGG and STAD, MOFNet also showed robust gains, with maximum improvements of 23.72% and 21.56%, respectively. Omics ablation studies demonstrated enhanced performance with multi-omics integration. Functional enrichment analysis revealed that MOFNet-identified key features were involved in biologically relevant pathways such as cell cycle regulation, synaptic signaling, and ion transport. Conclusions: MOFNet enables scalable and interpretable multi-omics data fusion for cancer subtype classification, significantly improving predictive accuracy while retaining only 25% of input features. The integration of SGO and VCDN modules offers both biological interpretability and computational efficiency. These results suggest MOFNet's promising application in precision oncology and biomarker discovery.<\/jats:p>\n                  <jats:p\/>","DOI":"10.1039\/d5mo00221d","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T13:43:18Z","timestamp":1759326198000},"page":"690-705","update-policy":"https:\/\/doi.org\/10.1039\/rsc_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["MOFNet: a deep learning framework for multi-omics data fusion in cancer subtype classification"],"prefix":"10.1093","volume":"21","author":[{"given":"Guangji","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University a , Jinan, Shandong 250061, China zpliu@sdu.edu.cn \u00a0 202335017@mail.sdu.edu.cn \u00a0 a420028118@gmail.com \u00a0 pp_li@mail.sdu.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunxiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University a , Jinan, Shandong 250061, China zpliu@sdu.edu.cn \u00a0 202335017@mail.sdu.edu.cn \u00a0 a420028118@gmail.com \u00a0 pp_li@mail.sdu.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengpai","family":"Li","sequence":"additional","affiliation":[{"name":"School of Bioengineering, Dalian University of Technology b , Dalian, Liaoning 116024, China"},{"name":"Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University a , Jinan, Shandong 250061, China zpliu@sdu.edu.cn \u00a0 202335017@mail.sdu.edu.cn \u00a0 a420028118@gmail.com \u00a0 pp_li@mail.sdu.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duanchen","family":"Sun","sequence":"additional","affiliation":[{"name":"National Center for Applied Mathematics, Shandong University c , Jinan, Shandong 250100, China dcsun@sdu.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixia","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Mathematics and Systems Science, Xinjiang University d , \u00dcr\u00fcmqi, Xinjiang 830046, China yangzhx@xju.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7742-9161","authenticated-orcid":false,"given":"Zhi-Ping","family":"Liu","sequence":"additional","affiliation":[{"name":"National Center for Applied Mathematics, Shandong University c , Jinan, Shandong 250100, China dcsun@sdu.edu.cn"},{"name":"Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University a , Jinan, Shandong 250061, China zpliu@sdu.edu.cn \u00a0 202335017@mail.sdu.edu.cn \u00a0 a420028118@gmail.com \u00a0 pp_li@mail.sdu.edu.cn"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"2026013001291991800_cit1","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780195175448.001.0001","volume-title":"Cancer Biology","author":"Ruddon","year":"2007"},{"key":"2026013001291991800_cit2","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.immuni.2004.07.017","volume":"21","author":"Dunn","year":"2004","journal-title":"Immunity"},{"key":"2026013001291991800_cit3","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1038\/nature10888","volume":"482","author":"Lujambio","year":"2012","journal-title":"Nature"},{"key":"2026013001291991800_cit4","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.knosys.2018.01.025","volume":"146","author":"Wang","year":"2018","journal-title":"Knowl.-Based Syst."},{"key":"2026013001291991800_cit5","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1002\/sim.9953","article-title":"et al.","volume":"43","author":"Mallick","year":"2024","journal-title":"Stat. 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