Scarborough Jessica, Weaver Davis, Scott Jacob
Department of Medicine, University of California San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA.
Department of Translational Hematology and Oncology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA; Systems Biology and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.
Hematol Oncol Clin North Am. 2025 Apr;39(2):295-307. doi: 10.1016/j.hoc.2024.11.003. Epub 2024 Dec 17.
Gene expression signatures (GES) are a powerful tool in oncology used for classification, prognostication, and therapeutic response prediction of malignancies. In this article, we review the disease site guidelines by the National Comprehensive Cancer Network that use GES for treatment planning and clinical use. We identified 4 cancer types for which treatment decisions are frequently influenced by GES. Future developments in the field of GES are likely to include expanded data sources to personalize radiation therapy dosing and predict response to immunotherapy. Ongoing challenges in GES may be addressed to ensure that all patients with cancer benefit from precision oncology.
基因表达特征(GES)是肿瘤学中用于恶性肿瘤分类、预后评估和治疗反应预测的强大工具。在本文中,我们回顾了美国国立综合癌症网络的疾病部位指南,该指南将GES用于治疗规划和临床应用。我们确定了4种癌症类型,其治疗决策经常受到GES的影响。GES领域未来的发展可能包括扩大数据源,以实现放射治疗剂量的个性化并预测对免疫治疗的反应。GES中持续存在的挑战可能会得到解决,以确保所有癌症患者都能从精准肿瘤学中受益。