Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.
肿瘤精准治疗（Precision oncology）的目标旨在依据癌症病人遗传信息的个体化差异，来为这些病人设计最合适的治疗策略。目前基因组学已经给我们提供了与驱动癌症的关键突变以及高风险位点相关的大量有用的数据。然而，如何将这些信息转化为治疗药物仍然是一个艰巨的挑战。转录组学揭示了各种信使RNA（mRNA）和非编码RNA（non-coding RNA，ncRNA）的表达情况，因而能够很好地破译基因组学中的遗传密码。在本综述中，我们以乳腺癌作为例子，重点介绍这些丰富的RNA资源在精准医疗药物开发中的应用，主要表现在3个方面：（1）利用mRNA表达谱对三阴性乳腺癌（triple-negative breast cancer，TNBC）进行分类并提出相应的候选靶向治疗策略；（2）高通量RNA干预技术（RNA interference， RNAi）在乳腺癌中的研究进展和成果；（3）微小RNA（microRNA， miRNA）是表征细胞谱系和调控乳腺癌细胞生物学活性的重要功能分子。我们总结了转录组学在乳腺癌治疗中的应用，提出在肿瘤精准治疗中不同类别的组学的数据整合的一个重要任务在于揭示隐藏其中的核心信号调控网络。





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