Department of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Graduate Program in Genetics, Genomics, and Bioinformatics, University of California, Riverside, CA, USA.
Nucleic Acids Res. 2022 Jan 7;50(D1):D1139-D1146. doi: 10.1093/nar/gkab784.
MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10 554 samples from 33 TCGA projects and 28 633 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.
微小 RNA（miRNAs）在基因调控网络中发挥着关键作用，已成为人类癌症有前途的诊断和预后生物标志物。特别是分泌到循环系统中的循环 miRNA 以非常稳定的形式存在，具有作为癌症早期检测非侵入性生物标志物的巨大潜力。迫切需要新颖且用户友好的工具来促进对来自癌症基因组图谱（TCGA）和大规模循环 miRNA 分析研究的大量 miRNA 表达数据进行数据挖掘。为了填补这一空白，我们开发了 CancerMIRNome，这是一个综合数据库，用于基于来自 33 个 TCGA 项目的 10554 个样本和来自 40 个公共循环 miRNome 数据集的 28633 个样本对 miRNA 表达谱进行交互式分析和可视化。一系列先进的生物信息学工具和机器学习算法已被打包到 CancerMIRNome 中，允许对多个癌症类型的感兴趣 miRNA 进行泛癌症分析，并对 miRNome 谱进行全面分析以识别失调的 miRNA 并开发诊断或预后特征。数据分析和可视化模块将极大地促进对有价值资源的利用，并促进 miRNA 生物标志物在癌症中的转化应用。CancerMIRNome 数据库可在 http://bioinfo.jialab-ucr.org/CancerMIRNome 上公开获取。
