癌症治疗是一个快速发展且不断扩大的领域。目前的方法包括手术、传统化疗和免疫疗法等新型生物制剂，它们共同构成了广泛的治疗手段。然而，过多的选择对于为任何特定患者制定最合适的治疗方案可能具有临床挑战性。幸运的是，生物标志物可以极大地促进最合适的选择。近年来，基于 RNA 的生物标志物已被证明是最有前途的。这些分子的范围从小非编码 RNA 到蛋白质编码基因转录本，在癌症管理，尤其是癌症治疗中具有重要价值。与在整个治疗过程中保持稳定的 DNA 对应物相比，RNA 生物标志物是动态的。这可以在治疗开始之前预测成功，并可以识别可以反映反应的表达变化。此外，改进的核酸技术允许从几乎所有生物流体/基质中提取 RNA，并以极高的分析灵敏度进行评估。此外，样本主要是通过微创程序获得的，因此可以连续使用来实时评估治疗反应。本章为读者提供了有关当前已知 RNA 生物标志物、利用人工智能识别此类分子以及推动个性化肿瘤学时代的临床决策的最新研究。版权所有 © 2024。由 Elsevier Inc. 出版。

Cancer therapy is a rapidly evolving and constantly expanding field. Current approaches include surgery, conventional chemotherapy and novel biologic agents as in immunotherapy, that together compose a wide armamentarium. The plethora of choices can, however, be clinically challenging in prescribing the most suitable treatment for any given patient. Fortunately, biomarkers can greatly facilitate the most appropriate selection. In recent years, RNA-based biomarkers have proven most promising. These molecules that range from small noncoding RNAs to protein coding gene transcripts can be valuable in cancer management and especially in cancer therapeutics. Compared to their DNA counterparts which are stable throughout treatment, RNA-biomarkers are dynamic. This allows prediction of success prior to treatment start and can identify alterations in expression that could reflect response. Moreover, improved nucleic acid technology allows RNA to be extracted from practically every biofluid/matrix and evaluated with exceedingly high analytic sensitivity. In addition, samples are largely obtained by minimally invasive procedures and as such can be used serially to assess treatment response real-time. This chapter provides the reader insight on currently known RNA biomarkers, the latest research employing Artificial Intelligence in the identification of such molecules and in clinical decisions driving forward the era of personalized oncology.Copyright © 2024. Published by Elsevier Inc.