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长非编码 RNA 在人类癌症精准医学中的潜力。

The potential of long noncoding RNAs for precision medicine in human cancer.

机构信息

Department of Oncology of the First Affiliated Hospital, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China; Hefei National Laboratory for Physical Sciences at Microscale, The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230027, China.

Department of Oncology of the First Affiliated Hospital, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China.

出版信息

Cancer Lett. 2021 Mar 31;501:12-19. doi: 10.1016/j.canlet.2020.11.040. Epub 2020 Dec 24.

DOI:10.1016/j.canlet.2020.11.040
PMID:33359450
Abstract

Precision medicine promises to better classify patients by individual clinical and biological biomarkers, which may provide an accurate assessment of disease risk, diagnosis, prognosis and treatment response. Cancer frequently displays substantial inter-tumor and intra-tumor heterogeneity and hence oncology is well suited for application of precision approaches. Recent studies have demonstrated that dysregulated lncRNAs play pivotal roles in tumor heterogeneity. In this review, attention is focused on the potential applications of lncRNAs as biomarker candidates for cancer risk evaluation, detection, surveillance and prognosis. LncRNAs are often stable in clinical samples and easily detected. The functional implications and therapeutic potential of targeting lncRNAs in human cancer are further discussed. Finally, existing deficiencies and future perspectives in translating fundamental lncRNA knowledge into clinical practice are highlighted.

摘要

精准医学有望通过个体临床和生物标志物更好地对患者进行分类,这可能为疾病风险、诊断、预后和治疗反应提供更准确的评估。癌症经常表现出显著的肿瘤间和肿瘤内异质性,因此肿瘤学非常适合应用精准方法。最近的研究表明,失调的 lncRNA 在肿瘤异质性中发挥关键作用。在这篇综述中,我们关注 lncRNA 作为癌症风险评估、检测、监测和预后的生物标志物候选物的潜在应用。lncRNA 在临床样本中通常很稳定,易于检测。进一步讨论了靶向人类癌症中的 lncRNA 的功能意义和治疗潜力。最后,强调了将基础 lncRNA 知识转化为临床实践中存在的现有缺陷和未来展望。

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