Turai Péter István, Herold Zoltán, Nyirő Gábor, Borka Katalin, Micsik Tamás, Tőke Judit, Szücs Nikolette, Tóth Miklós, Patócs Attila, Igaz Peter
Department of Endocrinology, ENS@T Research Center of Excellence, Faculty of Medicine, Semmelweis University, H-1083 Budapest, Hungary.
Department of Internal Medicine and Oncology, Faculty of Medicine, Semmelweis University, H-1083 Budapest, Hungary.
Cancers (Basel). 2022 Feb 11;14(4):895. doi: 10.3390/cancers14040895.
The histological analysis of adrenal tumors is difficult and requires great expertise. Tissue microRNA (miRNA) expression is distinct between benign and malignant tumors of several organs and can be useful for diagnostic purposes. MiRNAs are stable and their expression can be reliably reproduced from archived formalin-fixed, paraffin-embedded (FFPE) tissue blocks. Our purpose was to assess the potential applicability of combinations of literature-based miRNAs as markers of adrenocortical malignancy. Archived FFPE tissue samples from 10 adrenocortical carcinoma (ACC), 10 adrenocortical adenoma (ACA) and 10 normal adrenal cortex samples were analyzed in a discovery cohort, while 21 ACC and 22 ACA patients were studied in a blind manner in the validation cohort. The expression of miRNA was determined by RT-qPCR. Machine learning and neural network-based methods were used to find the best performing miRNA combination models. To evaluate diagnostic applicability, ROC-analysis was performed. We have identified three miRNA combinations ( + + ; + + and + + ) as unexpectedly good predictors to determine adrenocortical malignancy with sensitivity and specificity both of over 90%. These miRNA panels can supplement the histological examination of removed tumors and could even be performed from small volume adrenal biopsy samples preoperatively.
肾上腺肿瘤的组织学分析难度较大,需要专业知识。组织微小RNA(miRNA)表达在多个器官的良性和恶性肿瘤之间存在差异,可用于诊断。miRNA稳定,其表达可从存档的福尔马林固定、石蜡包埋(FFPE)组织块中可靠重现。我们的目的是评估基于文献的miRNA组合作为肾上腺皮质恶性肿瘤标志物的潜在适用性。在一个发现队列中分析了来自10例肾上腺皮质癌(ACC)、10例肾上腺皮质腺瘤(ACA)和10例正常肾上腺皮质样本的存档FFPE组织样本,而在验证队列中以盲法研究了21例ACC和22例ACA患者。通过RT-qPCR测定miRNA的表达。使用基于机器学习和神经网络的方法来寻找性能最佳的miRNA组合模型。为评估诊断适用性,进行了ROC分析。我们确定了三种miRNA组合(++;+++和+++)作为意外良好的预测指标,用于确定肾上腺皮质恶性肿瘤,敏感性和特异性均超过90%。这些miRNA检测板可补充切除肿瘤的组织学检查,甚至可在术前从小体积肾上腺活检样本中进行检测。