Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.
Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran; Max Planck Institute of Molecular Plant Physiology, Posdam, Germany.
J Biomed Inform. 2019 Jun;94:103180. doi: 10.1016/j.jbi.2019.103180. Epub 2019 Apr 27.
In recent studies, non-coding protein RNAs have been identified as microRNA that can be used as biomarkers for early diagnosis and treatment of cancer, that decrease mortality in cancer. A microRNA may target hundreds or thousands of genes and a gene may regulate several microRNAs, so determining which microRNA is associated with which cancer is a big challenge. Many computational methods have been performed to detect micoRNAs association with cancer, but more effort is needed with higher accuracy. Increasing research has shown that relationship between microRNAs and TFs play a significant role in the diagnosis of cancer. Therefore, we developed a new computational framework (CAMIRADA) to identify cancer-related microRNAs based on the relationship between microRNAs and disease genes (DG) in the protein network, the functional relationships between microRNAs and Transcription Factors (TF) on the co-expression network, and the relationship between microRNAs and the Differential Expression Gene (DEG) on co-expression network. The CAMIRADA was applied to assess breast cancer data from two HMDD and miR2Disease databases. In this study, the AUC for the 65 microRNAs of the top of the list was 0.95, which was more accurate than the similar methods used to detect microRNAs associated with the cancer artery.
在最近的研究中，已经确定了非编码蛋白质 RNA 作为 microRNA，可以用作癌症早期诊断和治疗的生物标志物，降低癌症死亡率。一个 microRNA 可能靶向数百个或数千个基因，一个基因可能调节几个 microRNAs，因此确定哪些 microRNA 与哪种癌症相关是一个巨大的挑战。已经有许多计算方法被用于检测与癌症相关的 microRNAs，但需要更高的准确性来进行更多的努力。越来越多的研究表明，microRNAs 与 TF 之间的关系在癌症的诊断中起着重要作用。因此，我们开发了一种新的计算框架（CAMIRADA），基于蛋白质网络中 microRNAs 与疾病基因（DG）之间的关系、共表达网络中 microRNAs 与转录因子（TF）之间的功能关系以及共表达网络中 microRNAs 与差异表达基因（DEG）之间的关系，来识别与癌症相关的 microRNAs。CAMIRADA 被应用于从两个 HMDD 和 miR2Disease 数据库评估乳腺癌数据。在这项研究中，列表顶部的 65 个 microRNAs 的 AUC 为 0.95，比用于检测与癌症相关的 microRNAs 的类似方法更准确。
