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微小 RNA 指导的前列腺癌基因表达:文献和数据库概述。

MicroRNA-guided gene expression in prostate cancer: Literature and database overview.

机构信息

Institute of Chemical Biology and Fundamental Medicine, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia and 'E. Meshalkin National Medical Research Center' of the Ministry of Health of the Russian Federation, Novosibirsk, Russia.

出版信息

J Gene Med. 2018 May;20(5):e3016. doi: 10.1002/jgm.3016. Epub 2018 Apr 30.

Abstract

Insight into the aberrant expression of microRNAs (miRNAs) and the genes that they regulate during the progression of cancer in general and prostate cancer (PCa) in particular is one of the most important issues in current molecular biomedicine and allows for the discovery of therapeutic or diagnostic miRNA targets. The present study aimed to analyze the available data regarding the direct or indirect effects of miRNAs on the expression of the mRNAs involved in carcinogenesis and to enable updating and optimizing the selection of the corresponding targets. The present review focuses on the data related to the genes with miRNA-dependent expression during the development of PCa. The data used in this review have been extracted from research papers and the databases STRING, PANTHER and TargetScan, with a special focus on the genes directly associated with cell transformation and the maintenance of the transformed genotype, as well as tumor invasion and spread. The search for miRNA markers of PCa and therapeutically active molecules should rely on bioinformatics resources, such as data from recent experimental studies, as well as meta-analysis and cross-analysis of the data on the state of the tumor, patient status, histological/immunohistological data and data on mRNA-miRNA coexpression.

摘要

深入了解 microRNAs (miRNAs) 在癌症进展中的异常表达,以及它们调节的基因,是当前分子生物医学的最重要问题之一,有助于发现治疗或诊断 miRNA 靶点。本研究旨在分析 miRNA 对参与致癌作用的 mRNAs 表达的直接或间接影响的现有数据,并能够更新和优化相应靶标的选择。本综述重点关注与 PCa 发展过程中 miRNA 依赖性表达相关的基因的数据。本综述中使用的数据来自研究论文和 STRING、PANTHER 和 TargetScan 数据库,特别关注与细胞转化和转化基因型维持以及肿瘤侵袭和转移直接相关的基因。寻找 PCa 的 miRNA 标志物和治疗活性分子应该依赖于生物信息学资源,例如来自最近的实验研究的数据,以及对肿瘤状态、患者状况、组织学/免疫组织学数据和 mRNA-miRNA 共表达数据的元分析和交叉分析。

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