Overlapping histological features between benign and malignant lesions and a lack of firm diagnostic criteria for malignancy result in high rates of inter-observer variation in the diagnosis of melanocytic lesions. We aimed to investigate the differential expression of five miRNAs (21, 200c, 204, 205, and 211) in benign naevi (n = 42), dysplastic naevi (n = 41), melanoma in situ (n = 42), and melanoma (n = 42) and evaluate their potential as diagnostic biomarkers of melanocytic lesions. Real-time PCR showed differential miRNA expression profiles between benign naevi; dysplastic naevi and melanoma in situ; and invasive melanoma. We applied a random forest machine learning algorithm to classify cases based on their miRNA expression profiles, which resulted in a ROC curve analysis of 0.99 for malignant melanoma and greater than 0.9 for all other groups. This indicates an overall very high accuracy of our panel of miRNAs as a diagnostic biomarker of benign, dysplastic, and malignant melanocytic lesions. However, the impact of variable lesion percentage and spatial expression patterns of miRNAs on these real-time PCR results was also considered. In situ hybridisation confirmed the expression of miRNA 21 and 211 in melanocytes, while demonstrating expression of miRNA 205 only in keratinocytes, thus calling into question its value as a biomarker of melanocytic lesions. In conclusion, we have validated some miRNAs, including miRNA 21 and 211, as potential diagnostic biomarkers of benign, dysplastic, and malignant melanocytic lesions. However, we also highlight the crucial importance of considering tissue morphology and spatial expression patterns when using molecular techniques for the discovery and validation of new biomarkers.

中文翻译：

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微RNA 21、200c、204、205和211在良性、发育不良和恶性黑素细胞病变中的差异表达及其作为诊断生物标志物的作用的严格评估。


良性和恶性病变之间的重叠组织学特征以及缺乏严格的恶性肿瘤诊断标准导致黑素细胞病变诊断中观察者间的高变异率。我们的目的是研究 5 种 miRNA（21、200c、204、205 和 211）在良性痣 (n = 42)、发育不良痣 (n = 41)、原位黑色素瘤 (n = 42) 和黑色素瘤中的差异表达(n = 42) 并评估它们作为黑素细胞病变诊断生物标志物的潜力。实时 PCR 显示良性痣之间 miRNA 表达谱存在差异；发育不良痣和原位黑色素瘤；和侵袭性黑色素瘤。我们应用随机森林机器学习算法根据 miRNA 表达谱对病例进行分类，得出恶性黑色素瘤的 ROC 曲线分析为 0.99，所有其他组的 ROC 曲线分析均大于 0.9。这表明我们的 miRNA 组作为良性、发育不良和恶性黑素细胞病变的诊断生物标志物的总体准确性非常高。然而，还考虑了不同病变百分比和 miRNA 空间表达模式对这些实时 PCR 结果的影响。原位杂交证实了 miRNA 21 和 211 在黑素细胞中的表达，同时证明 miRNA 205 仅在角质形成细胞中表达，从而质疑其作为黑素细胞病变生物标志物的价值。总之，我们已经验证了一些 miRNA，包括 miRNA 21 和 211，作为良性、发育不良和恶性黑素细胞病变的潜在诊断生物标志物。然而，我们还强调了在使用分子技术发现和验证新生物标志物时考虑组织形态和空间表达模式的至关重要性。