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Identifying and characterizing cancer driver gene is crucial for understanding cancer biology and guiding precision oncology. Integrating multi-omics data can reveal the intricate molecular interactions underlying cancer progression and treatment responses. We developed a graph convolutional network (GCN) framework, DriverOmicsNet, that integrates multi-omics data using STRING protein\u2013protein interaction networks and correlation-based weighted gene correlation network analysis (WGCNA). We applied this framework to 15 cancer types, analyzing 5555 tumor samples to predict cancer-related features such as homologous recombination deficiency, cancer stemness, immune clusters, tumor stage, and survival outcomes. DriverOmicsNet demonstrated superior predictive accuracy and model performance metrics across all target labels when compared with GCN models based on STRING network alone. Gene expression emerged as the most significant feature, reflecting the dynamic and functional state of cancer cells. The combined use of STRING PPI and WGCNA networks enhanced the identification of key driver genes and their interactions. Our study highlights the effectiveness of using GCNs to integrate multi-omics data for precision oncology. The integration of STRING PPI and WGCNA networks provides a comprehensive framework that improves predictive power and facilitates the understanding of cancer biology, paving the way for more tailored treatments.<\/jats:p>","DOI":"10.1093\/bib\/bbaf412","type":"journal-article","created":{"date-parts":[[2025,7,26]],"date-time":"2025-07-26T11:47:40Z","timestamp":1753530460000},"source":"Crossref","is-referenced-by-count":3,"title":["DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8054-0944","authenticated-orcid":false,"given":"Yang-Hong","family":"Dai","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, Tri-Service General Hospital, National Defense Medical University , No. 325, Sec. 2, Chenggong Rd., Neihu District, Taipei City 114202, Taiwan ,","place":["Republic of China"]},{"name":"Department of Oncology, University of Oxford , Oxford, OX3 7DQ ,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0977-8743","authenticated-orcid":false,"given":"Chia-Jung","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, National Cheng Kung University , No. 1, University Rd., Tainan City 701, Taiwan ,","place":["Republic of China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2496-996X","authenticated-orcid":false,"given":"Po-Chien","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Tri-Service General Hospital, National Defense Medical University , No. 325, Sec. 2, Chenggong Rd., Neihu District, Taipei City 114202, Taiwan ,","place":["Republic of 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Biology, National Yang Ming Chiao Tung University , No. 75, Boai St., East Dist., Hsinchu City 300197, Taiwan ,","place":["Republic of China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4379-5416","authenticated-orcid":false,"given":"Yu-Guang","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Hematology\/Oncology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University , No. 325, Sec. 2, Chenggong Rd., Neihu District, Taipei City 114202, Taiwan ,","place":["Republic of China"]},{"name":"The Center for Cell Therapy and Regenerative Medicine, Tri-Service General Hospital , Taipei, Taiwan ,","place":["Republic of 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