California University of Science and Medicine, Colton, CA, United States of America.
PLoS One. 2022 Jun 10;17(6):e0269554. doi: 10.1371/journal.pone.0269554. eCollection 2022.
Cancer consistently remains one of the top causes of death in the United States every year, with many cancer deaths preventable if detected early. Circulating serum miRNAs are a promising, minimally invasive supplement or even an alternative to many current screening procedures. Many studies have shown that different serum miRNAs can discriminate healthy individuals from those with certain types of cancer. Although many of those miRNAs are often reported to be significant in one cancer type, they are also altered in other cancer types. Currently, very few studies have investigated serum miRNA biomarkers for multiple cancer types for general cancer screening purposes.
To identify serum miRNAs that would be useful in screening multiple types of cancers, microarray cancer datasets were curated, yielding 13 different types of cancer with a total of 3352 cancer samples and 2809 non-cancer samples. The samples were divided into training and validation sets. One hundred random forest models were built using the training set to select candidate miRNAs. The selected miRNAs were then used in the validation set to see how well they differentiate cancer from normal samples in an independent dataset. Furthermore, the interactions between these miRNAs and their target mRNAs were investigated.
The random forest models achieved an average of 97% accuracy in the training set with 95% bootstrap confidence interval of 0.9544 to 0.9778. The selected miRNAs were hsa-miR-663a, hsa-miR-6802-5p, hsa-miR-6784-5p, hsa-miR-3184-5p, and hsa-miR-8073. Each miRNA exhibited high area under the curve (AUC) value using receiver operating characteristic analysis. Moreover, the combination of four out of five miRNAs achieved the highest AUC value of 0.9815 with high sensitivity of 0.9773, indicating that these miRNAs have a high potential for cancer screening. miRNA-mRNA and protein-protein interaction analysis provided insights into how these miRNAs play a role in cancer.
癌症一直是美国每年死亡的主要原因之一，如果早期发现，许多癌症死亡是可以预防的。循环血清 microRNA 是一种很有前途的微创补充方法，甚至可以替代许多当前的筛查程序。许多研究表明，不同的血清 microRNA 可以区分健康个体和患有某些类型癌症的个体。尽管许多 microRNA 经常被报道在一种癌症类型中具有重要意义，但它们在其他癌症类型中也发生了改变。目前，很少有研究调查用于多种癌症类型的一般癌症筛查的血清 microRNA 生物标志物。
为了确定可用于筛查多种癌症的血清 microRNA，我们整理了 microarray 癌症数据集，得到了 13 种不同类型的癌症，共有 3352 个癌症样本和 2809 个非癌症样本。这些样本被分为训练集和验证集。使用训练集构建了 100 个随机森林模型来选择候选 microRNA。然后，在验证集中使用这些选定的 microRNA 来观察它们在独立数据集上区分癌症与正常样本的效果。此外，还研究了这些 microRNA 及其靶 mRNA 之间的相互作用。
随机森林模型在训练集上的平均准确率为 97%，95%置信区间为 0.9544 至 0.9778。选定的 microRNA 是 hsa-miR-663a、hsa-miR-6802-5p、hsa-miR-6784-5p、hsa-miR-3184-5p 和 hsa-miR-8073。每个 microRNA 在接受者操作特征分析中均表现出高 AUC 值。此外，五分之四的 microRNA 的组合实现了 0.9815 的最高 AUC 值和 0.9773 的高灵敏度，表明这些 microRNA 具有很高的癌症筛查潜力。microRNA-mRNA 和蛋白质-蛋白质相互作用分析提供了这些 microRNA 如何在癌症中发挥作用的见解。
