Department of Biomedicine, School of Health Sciences, Universiti Sains Malaysia, Kelantan, Malaysia.
Molecular Pathology Unit, Cancer Research Centre, Institute for Medical Research, Ministry of Health, Kuala Lumpur, Malaysia.
Asian Pac J Cancer Prev. 2021 May 1;22(5):1375-1381. doi: 10.31557/APJCP.2021.22.5.1375.
This study aimed to characterize the miRNA expression profiles from plasma samples of our local breast cancer patients in comparison to healthy control by using miRNA PCR Array.
In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control.
Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95.
miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing.
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本研究旨在通过 miRNA PCR 阵列比较本地乳腺癌患者与健康对照者的血浆样本中的 miRNA 表达谱。
本研究采用 miRNA 阵列方法分析 8 例早期乳腺癌患者和 9 例年龄匹配(±2 岁)健康对照者的血浆 miRNA 谱,然后进行差异基因表达分析、独立 T 检验和构建接收者操作特征(ROC)曲线,以确定这些检测方法区分乳腺癌和健康对照的能力。
基于 372 个 miRNA 的微阵列分析,根据 2 倍以上的倍数变化值提取了一组 40 个差异 miRNA。我们进一步将乳腺癌患者的 40 个 miRNA 分为明显表达 2 倍以上的亚组。在这一组中,我们发现与健康受试者的 miRNA 表达相比,24 个 miRNA 显著上调,16 个 miRNA 显著下调。ROC 曲线分析显示,7 个 miRNA(miR-125b-5p、miR-142-3p、miR-145-5p、miR-193a-5p、miR-27b-3p、miR-22-5p 和 miR-423-5p)的曲线下面积(AUC)值>0.7(AUC p 值<0.05)。差异基因表达分析、ROC 分析和独立 T 检验的重叠结果导致 3 个 miRNA(miR-27b-3p、miR-22-5p、miR-145-5p)。这三个 miRNA 的 Cohen's 效应量较大,d 值大于 0.95。
miR-27b-3p、miR-22-5p、miR-145-5p 可能是区分乳腺癌患者与健康对照者的潜在生物标志物。正在对这三个 miRNA 在外部样本中的验证研究。