{"title":"Artificial intelligence-driven integration of multi-omics and radiomics: A new hope for precision cancer diagnosis and prognosis","authors":"Jordi Camps , Andrea Jiménez-Franco , Raquel García-Pablo , Jorge Joven , Meritxell Arenas","doi":"10.1016/j.bbadis.2025.167841","DOIUrl":null,"url":null,"abstract":"<div><div>Despite advances in cancer diagnosis and treatment, the disease remains a major health challenge. Integrating multi-omics, radiomics, and artificial intelligence has improved detection, prognosis, and treatment monitoring. Molecular multi-omics provides insights into tumor biology, while radiomics extracts imaging features for outcome prediction. Liquid biopsy and circulating tumor DNA aid early detection and personalized therapy. Artificial intelligence-driven models integrate data to identify biomarkers and guide precision oncology. Despite challenges like cost and data integration, future advancements aim to enhance resolution, scalability, and non-invasive diagnostics. This mini-review explores these methodologies, their clinical impact, and their potential in personalized cancer treatment.</div></div>","PeriodicalId":8821,"journal":{"name":"Biochimica et biophysica acta. Molecular basis of disease","volume":"1871 6","pages":"Article 167841"},"PeriodicalIF":4.2000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochimica et biophysica acta. Molecular basis of disease","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925443925001863","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/9 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Despite advances in cancer diagnosis and treatment, the disease remains a major health challenge. Integrating multi-omics, radiomics, and artificial intelligence has improved detection, prognosis, and treatment monitoring. Molecular multi-omics provides insights into tumor biology, while radiomics extracts imaging features for outcome prediction. Liquid biopsy and circulating tumor DNA aid early detection and personalized therapy. Artificial intelligence-driven models integrate data to identify biomarkers and guide precision oncology. Despite challenges like cost and data integration, future advancements aim to enhance resolution, scalability, and non-invasive diagnostics. This mini-review explores these methodologies, their clinical impact, and their potential in personalized cancer treatment.
尽管在癌症诊断和治疗方面取得了进步，但癌症仍然是一项重大的健康挑战。多组学、放射组学和人工智能的结合改善了检测、预后和治疗监测。分子多组学可深入了解肿瘤生物学，而放射组学可提取成像特征进行结果预测。液体活检和循环肿瘤 DNA 有助于早期检测和个性化治疗。人工智能驱动的模型可整合数据，识别生物标记物，指导精准肿瘤学。尽管存在成本和数据整合等挑战，但未来的进步旨在提高分辨率、可扩展性和无创诊断。这篇微型综述探讨了这些方法、它们的临床影响及其在个性化癌症治疗中的潜力。
期刊介绍：
BBA Molecular Basis of Disease addresses the biochemistry and molecular genetics of disease processes and models of human disease. This journal covers aspects of aging, cancer, metabolic-, neurological-, and immunological-based disease. Manuscripts focused on using animal models to elucidate biochemical and mechanistic insight in each of these conditions, are particularly encouraged. Manuscripts should emphasize the underlying mechanisms of disease pathways and provide novel contributions to the understanding and/or treatment of these disorders. Highly descriptive and method development submissions may be declined without full review. The submission of uninvited reviews to BBA - Molecular Basis of Disease is strongly discouraged, and any such uninvited review should be accompanied by a coverletter outlining the compelling reasons why the review should be considered.
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