Steroid Metabolites for Diagnosing and Predicting Clinicopathological Features in Cortisol-Producing Adrenocortical Carcinoma.

Abstract About 60% of adrenocortical carcinomas (ACC) are functional, and Cushing's syndrome is the most frequent diagnosis which has been revealed to have particularly poor prognosis. Since 30% of ACC present steroid hormone-producing disorganization, measurement of steroid metabolites in suspected ACC is recommended. Previous reports demonstrated that steroid hormone precursors or its urine metabolites, using liquid chromatography tandem mass spectrometry (LC-MS/MS) or gas chromatography mass spectrometry (GC-MS) respectively, are useful for distinguishing ACC from adrenocortical adenoma. However, whether steroid metabolites can predict pathological characteristics or prognosis has not been elucidated. Here, we examined 12 serum steroid metabolites using immunoassay, which is a more rapid and less costly method compared to LC-MS/MS, in cortisol-producing ACC and cortisol-producing adenomas (CPA). Further, the correlation of each steroid metabolite to the stage classification and pathological status in ACC was analyzed. Reflected disorganized steroidogenesis, immunoassay revealed all basal levels of steroid precursors were significantly increased in cortisol-producing ACC compared to CPA; especially 17- hydroxypregnenolone (androgen precursor) and 11-deoxycorticosterone (mineralocorticoid precursor) showed large area under ROC curve with high sensitivity and specificity, when setting the cut-off at 1.78 ng/ml and 0.4 mg/ml, respectively. In cortisol-producing ACC, 11-deoxycortisol (glucocorticoid precursor) showed significant positive correlations to predictive prognostic factors of ENSAT classification, while testosterone showed significant positive correlations to Ki67-index in both men and women. In conclusion, measurement of serum steroid metabolites using immunoassay has great potential not only for diagnosis but also for prediction of the clinicopathological features associated with disease prognosis of ACC, as a simple non-invasive method.