Background: Adrenocortical carcinoma is a rare finding among common adrenocortical tumors, but it is highly aggressive and requires early detection and treatment. Still, the differential diagnosis between benign and malignant lesions is difficult even for experienced pathologists and there is a significant need for novel diagnostic methods. In this study we aimed to reveal a complete set of microRNAs expressed in the adrenal gland and to identify easily detectable, stable and objective biomarkers of adrenocortical malignancy.
Methods: We employed next-generation sequencing to analyze microRNA profiles in a unique set of 51 samples, assigned to either a learning dataset including 7 adrenocortical carcinomas (ACCs), 8 adrenocortical adenomas (AAs) and 8 control samples (NAs), or a validation dataset including 8 ACCs, 10 AAs and 10 NAs. The results were validated in real-time Q-PCR.
Results: We detected 411 miRNAs expressed in 1763 length isoforms in the examined samples. Fifteen miRNAs differentiate between malignant (ACC) and non-malignant (AA + NA) tissue in the test set of independent samples. Expression levels of 6 microRNAs, miR-503-5p, miR-483-3p, miR-450a-5p, miR-210, miR-483-5p, miR-421, predict sample status (malignancy/non-malignancy) with at least 95% accuracy in both datasets. The best single-gene malignancy marker, miR-483-3p, has been validated by real-time RT PCR.
Conclusions: As a result of the study we propose clinically valid and easily detectable biomarkers of adrenocortical malignancy that may significantly facilitate morphological examination. Since microRNAs can be detected in blood, the study brings tools for development of non-invasive diagnostics of adrenocortical carcinomas.
Keywords: NGS; adrenocortical carcinoma; cancer diagnostics; microRNA; next-generation sequencing.