Potential diagnostic value of serum microRNAs for 19 cancer types: a meta-analysis of bioinformatics data

Cancer is the second most common cause of mortality worldwide, accounting for almost 10 million deaths in 2020. These deaths were partly due to delayed diagnosis that led to deferred treatment. Therefore, new diagnostic methods are necessary to enhance the accuracy of noninvasive cancer detection. The present study developed a microRNA (miRNA)-based serum diagnostic marker for detecting a wide range of cancers. The study involved 61,019 serum samples from 19 different cancer types. A miRNA prediction model was established through bioinformatics analysis of serum samples from various cancer pathologies and qRT-PCR results from studies in PubMed aligned to the analysis criteria. R software v.4.1.1 with the limma data analysis package was used for single gene expression series data series, and batchNormalize and robustRankAggreg were used to predict the changes in miRNA expression in multiple datasets. GO and KEGG analyses showed that these miRNAs play a role in cancer-related biological signaling pathways. Finally, the diagnostic capability of these miRNA biomarkers was assessed using area under the curve analysis. The study predicted that 7 miRNAs were upregulated and 10 miRNAs were downregulated in 19 different types of cancer. Some miRNAs showed significant differential expression in a specific cancer type. Additionally, downstream genes regulated by miRNAs focused on many cancer-related molecular signaling pathways. In this review, we summarize the current understanding of miRNAs in various cancers, with a particular focus on their potential as future noninvasive diagnostic biomarkers. The emphasis is on their capacity for achieving high accuracy and cost savings compared to conventional biomarkers.

癌症是全球范围内第二大常见致死性病因，2020年因癌症导致的死亡人数近1000万。此类死亡案例中，部分源于诊断延迟引发的治疗延误。因此，开发新型诊断方法以提升无创癌症检测的准确性已成为迫切需求。本研究构建了基于微小核糖核酸（microRNA, miRNA）的血清诊断标志物，可用于多种癌症的检测。
本研究共纳入19种不同癌症类型的61019份血清样本。通过对各类癌症病理血清样本开展生物信息学分析，并结合PubMed数据库中符合分析标准的相关研究的实时定量逆转录聚合酶链反应（quantitative reverse transcription polymerase chain reaction, qRT-PCR）结果，建立了miRNA预测模型。针对单基因表达序列数据，本研究采用R软件v4.1.1及其limma数据分析包，并借助batchNormalize与robustRankAggreg工具对多数据集的miRNA表达变化进行预测。
基因本体（Gene Ontology, GO）与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析结果显示，上述miRNA参与癌症相关的生物学信号通路。最终，通过曲线下面积（Area Under the Curve, AUC）分析评估了这些miRNA生物标志物的诊断性能。
本研究预测，在19种不同癌症类型中，共有7种miRNA呈上调表达，10种miRNA呈下调表达。部分miRNA在特定癌症类型中呈现显著的差异表达。此外，miRNA调控的下游基因富集于诸多癌症相关分子信号通路。
本综述总结了当前学界对各类癌症中miRNA的研究认知，特别聚焦于其作为未来无创诊断生物标志物的潜力，并着重阐述了相较于传统生物标志物，此类miRNA标志物在实现高检测精度与成本节约方面的显著优势。