Vietnam National University, Ho Chi Minh City, 70000, Vietnam.
Department of Physiology and Animal Biotechnology, Faculty of Biology and Biotechnology, University of Science, Ho Chi Minh City, 70000, Vietnam.
Breast Cancer Res Treat. 2022 Nov;196(1):1-15. doi: 10.1007/s10549-022-06728-8. Epub 2022 Sep 9.
Circulating microRNAs (miRNAs) are potential diagnostic biomarkers for breast cancer (BC). The application of miRNA panels could improve the performance of screening tests. Here, we integrated bioinformatic tools and meta-analyses to select circulating miRNAs with high diagnostic accuracy and combined these markers to develop diagnostic panels for BC.
Analyses across databases were performed to identify potential BC-related circulating miRNAs. Next, a comprehensive meta-analysis was conducted for each miRNA following the PRISMA guidelines. An electronic and manual search for relevant literature was carried out by two reviewers through PubMed, ScienceDirect, Biomed Central, and Google Scholar. The quality of the included studies was assessed using the QUADAS-2, and the statistical analyses were performed using R software 4.1.1. Finally, the accurate biomarkers confirmed through meta-analyses were combined into diagnostic models for BC.
Twenty-seven circulating miRNAs were identified as BC-related by bioinformatic tools. After screening, only 10 miRNAs presented in 45 studies were eligible for meta-analyses. By assessing pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio, 8 miRNAs (miR-21, miR-30b, miR-125b, miR-145, miR221 miR-222, and miR-335) were revealed as promising BC diagnostic biomarkers. Two panels constructed from these miRNAs showed excellent diagnostic accuracy for BC, with areas under the SROC curve of 0.917 and 0.944.
We identified 8 potential circulating miRNAs and 2 diagnostic models that are useful for diagnosing BC. However, the established miRNA panels have not been tested in any experimental studies and thus should be validated in large case-control studies for clinical use.
循环 microRNAs（miRNAs）是乳腺癌（BC）潜在的诊断生物标志物。miRNA 谱的应用可以提高筛查试验的性能。在这里，我们整合了生物信息学工具和荟萃分析，以选择具有高诊断准确性的循环 miRNA，并将这些标记物组合起来，开发用于 BC 的诊断面板。
对数据库进行分析以确定潜在的与 BC 相关的循环 miRNAs。接下来，按照 PRISMA 指南对每个 miRNA 进行综合荟萃分析。两位评审员通过 PubMed、ScienceDirect、Biomed Central 和 Google Scholar 进行电子和手动搜索相关文献。使用 QUADAS-2 评估纳入研究的质量，并使用 R 软件 4.1.1 进行统计分析。最后，通过荟萃分析确认准确的生物标志物，并将其组合成用于 BC 的诊断模型。
通过生物信息学工具确定了 27 个与 BC 相关的循环 miRNAs。经过筛选，只有 10 个 miRNAs 在 45 项研究中符合荟萃分析的条件。通过评估汇总敏感性、特异性、阳性似然比、阴性似然比和诊断优势比，发现 8 个 miRNA（miR-21、miR-30b、miR-125b、miR-145、miR221、miR-222 和 miR-335）是有前途的 BC 诊断生物标志物。由这些 miRNA 构建的两个面板对 BC 具有出色的诊断准确性，SROC 曲线下面积分别为 0.917 和 0.944。
我们确定了 8 个潜在的循环 miRNAs 和 2 个用于诊断 BC 的诊断模型。然而，所建立的 miRNA 面板尚未在任何实验研究中进行测试，因此应在大型病例对照研究中进行验证，以便用于临床。
