Abstract
Simple SummaryThe histological differential diagnosis of adrenocortical adenoma and carcinoma is difficult and requires great expertise. MiRNAs were shown to be useful for the differential diagnosis of benign and malignant tumors of several organs, and several findings have suggested their utility in adrenocortical tumors as well. Here, we have selected tissue miRNAs based on the literature search, and used machine learning to identify novel clinically applicable miRNA combinations. Combinations with high sensitivity and specificity (both over 90%) have been identified that could be promising for clinical use. Besides being a useful adjunct to histological examination, these miRNA combinations could enable preoperative adrenal biopsy in patients with adrenal tumors suspicious for malignancy.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 (hsa-miR-195 + hsa-miR-210 + hsa-miR-503; hsa-miR-210 + hsa-miR-375 + hsa-miR-503 and hsa-miR-210 + hsa-miR-483-5p + hsa-miR-503) 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.
Highlights
Adrenal tumors are relatively frequent with a prevalence of 4.2% in high-resolution abdominal imaging studies [1]
The discovery cohort was comprised of 10 adrenocortical adenoma (ACA), 10 adrenocortical carcinoma (ACC), 10 normal adrenal cortex (NAC) and the independent validation cohort contained another 21 ACC and 22 ACA FFPE samples (Table S1)
We assessed the applicability for various miRNA combinations established by an artificial intelligence approach that could reliably be utilized as markers of adrenocortical malignancy
Summary
Adrenal tumors are relatively frequent with a prevalence of 4.2% in high-resolution abdominal imaging studies [1]. Adrenocortical carcinoma (ACC) has a poor prognosis, as less than a third of the patients survive at least 5 years [2,3,4]. ACC is the rarest among adrenal tumors, with an annual incidence of 0.7–2/million, it is included in the differential diagnosis of any incidentally discovered adrenal mass [3]. Adrenocortical adenoma (ACA) is the most frequent diagnosis (49–69% in surgical series) among adrenal tumors [5]. In addition to tumors of the adrenal cortex, myelolipoma, which is invariably benign and contains fat and bone marrow elements, and pheochromocytoma, of an adrenal medullary origin causing severe blood pressure fluctuations, may occur [5]. The differentiation of adrenocortical adenoma and carcinoma is often challenging
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