High-Resolution, Accurate-Mass (HRAM) Mass Spectrometry Urine Steroid Profiling in the Diagnosis of Adrenal Disorders.

BACKGROUND: Steroid profiling is a promising diagnostic tool with adrenal tumors, Cushing syndrome (CS), and disorders of steroidogenesis. Our objective was to develop a multiple-steroid assay using liquid-chromatography, high-resolution, accurate-mass mass spectrometry (HRAM LC-MS) and to validate the assay in patients with various adrenal disorders. METHODS: We collected 24-h urine samples from 114 controls and 71 patients with adrenal diseases. An HRAM LC-MS method was validated for quantitative analysis of 26 steroid metabolites in hydrolyzed urine samples. Differences in steroid excretion between patients were analyzed based on Z-score deviation from control reference intervals. RESULTS: Limits of quantification were 20 ng/mL. Dilution linearity ranged from 80% to 120% with means of 93% to 110% for all but 2 analytes. Intraassay and interassay imprecision ranged from 3% to 18% for all but 1 analyte. Control women had lower excretion of androgen and glucocorticoid precursors/metabolites than men (P < 0.001), but no difference in mineralocorticoids was seen (P = 0.06). Androgens decreased with age in both sexes (P < 0.001). Compared with patients with adrenocortical adenoma (ACA), patients with adrenocortical carcinoma (ACC) had 11 steroids with increased Z scores, especially tetrahydro-11-deoxycortisol (14 vs 0.5, P < 0.001), pregnanetriol (7.5 vs -0.4, P = 0.001), and 5-pregnenetriol (5.4 vs -0.4, P = 0.01). Steroid profiling also demonstrated metabolite abnormalities consistent with enzymatic defects in congenital adrenal hyperplasia and differences in pituitary vs adrenal CS. CONCLUSIONS: Our HRAM LC-MS assay successfully quantifies 26 steroids in urine. The statistically significant differences in steroid production of ACC vs ACA, adrenal vs pituitary CS, and in congenital adrenal hyperplasia should allow for improved diagnosis of patients with these diseases.

Simplified urinary steroid profiling by LC-MS as diagnostic tool for malignancy in adrenocortical tumors.

OBJECTIVES: Preoperative identification of malignant adrenal tumors is challenging. 24-h urinary steroid profiling by LC-MS/MS and machine learning has demonstrated high diagnostic power, but the unavailability of bioinformatic models for public use has limited its routine application. We here aimed to increase usability with a novel classification model for the differentiation of adrenocortical adenoma (ACA) and adrenocortical carcinoma (ACC). METHODS: Eleven steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) were quantified by LC-MS/MS in 24-h urine samples from 352 patients with adrenal tumor (281 ACA, 71 ACC). Random forest modelling and decision tree algorithms were applied in training (n = 188) and test sets (n = 80) and independently validated in 84 patients with paired 24-h and spot urine. RESULTS: After examining different models, a decision tree using excretions of only 5-pregnenetriol and tetrahydro-11-deoxycortisol classified three groups with low, intermediate, and high risk for malignancy. 148/217 ACA were classified as being at low, 67 intermediate, and 2 high risk of malignancy. Conversely, none of the ACC demonstrated a low-risk profile leading to a negative predictive value of 100% for malignancy. In the independent validation cohort, the negative predictive value was again 100% in both 24-h urine and spot urine with a positive predictive value of 87.5% and 86.7%, respectively. CONCLUSIONS: This simplified LC-MS/MS-based classification model using 24-h-urine provided excellent results for exclusion of ACC and can help to avoid unnecessary surgeries. Analysis of spot urine led to similarly satisfactory results suggesting that cumbersome 24-h urine collection might be dispensable after future validation.

Simultaneous analysis of mitotane and its main metabolites in human blood and urine samples by SPE-HPLC technique.

Adrenocortical carcinoma (ACC) is a rare malignancy with an incompletely understood pathogenesis and a poor prognosis. The adrenalytic activity of mitotane has made it the most important single drug in the treatment of ACC. Unfortunately, the exact mechanism of mitotane action is still unknown. It is believed that mitotane belongs to the class of drugs that require metabolic transformation by cytochrome P450 for therapeutic action; therefore determination of plasma levels of not only mitotane but also its metabolites would help in carrying out the treatment. The objective of this work was to develop and validate an SPE-HPLC method for simultaneous determination of mitotane and its metabolites in different biological fluids. The sample preparation consisted of a solid-phase extraction on a Discovery DSC(18) cartridge, while analysis of extracts was performed on a Symmetry C(18) column. The usefulness of the proposed method was confirmed by analysis of plasma, red cell and urine samples from patient chronically treated with 1.5 g of mitotane. The patient involved in this study had a high plasma concentration of mitotane and none of the investigated metabolites were found. In order to investigate whether the polymorphism of CYP2C9 and CYP2C19 enzymes could be related to the metabolism of mitotane, RT-PCR analysis was performed.

Clinicopathological features, biochemical and molecular markers in 5 patients with adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a very rare malignant tumor with poor prognosis. To gain insight into the pathogenic significance of ACC, we studied clinicopathological features and gene expression profile in ACC. We analyzed five ACC cases (two men and three women) with the median age of 45-year-old who underwent adrenalectomy at our institute. Endocrine studies revealed that two cases had subclinical Cushing's syndrome (SCS) and one with concomitant estrogen-secreting tumor, while the rest of three cases had non-functioning tumors. Analysis of urinary steroids profile by gas chromatography/mass spectrometry showed increased metabolites of corticosteroid precursors, such as 17-OH pregnenolone, 17-OH progesterone, dehydroepiandorosterone (DHEA), and 11-deoxycortisol in all five cases. The pathological diagnosis of ACC was based on Weiss's criteria with its score ≥ 3. The mean size of the resected tumors was 87 mm and Ki67/MIB1 labeling index, a proliferative marker, was 3-27%. Immunohistochemical analysis revealed a disorganized expression of several steroidogenic enzymes, such as 3ß-hydroxysteroid dehydrogenase, 17α-hydroxylase, and DHEA-sulfotransferase. Among several genes determined by RT-PCR, insulin-like growth factor (IGF)-II mRNA was consistently and abundantly expressed in all 5 tumor tissues. Postoperatively, two cases with SCS developed local recurrence and liver metastasis. The present study suggests that the disorganized expression of steroidogenic enzymes and the overexpression of IGF-II by the tumor are hallmarks of ACC, which could be used as biochemical and molecular markers for ACC.

Urine Steroid Metabolomics as a Novel Tool for Detection of Recurrent Adrenocortical Carcinoma.

CONTEXT: Urine steroid metabolomics, combining mass spectrometry-based steroid profiling and machine learning, has been described as a novel diagnostic tool for detection of adrenocortical carcinoma (ACC). OBJECTIVE, DESIGN, SETTING: This proof-of-concept study evaluated the performance of urine steroid metabolomics as a tool for postoperative recurrence detection after microscopically complete (R0) resection of ACC. PATIENTS AND METHODS: 135 patients from 14 clinical centers provided postoperative urine samples, which were analyzed by gas chromatography-mass spectrometry. We assessed the utility of these urine steroid profiles in detecting ACC recurrence, either when interpreted by expert clinicians or when analyzed by random forest, a machine learning-based classifier. Radiological recurrence detection served as the reference standard. RESULTS: Imaging detected recurrent disease in 42 of 135 patients; 32 had provided pre- and post-recurrence urine samples. 39 patients remained disease-free for ≥3 years. The urine "steroid fingerprint" at recurrence resembled that observed before R0 resection in the majority of cases. Review of longitudinally collected urine steroid profiles by 3 blinded experts detected recurrence by the time of radiological diagnosis in 50% to 72% of cases, improving to 69% to 92%, if a preoperative urine steroid result was available. Recurrence detection by steroid profiling preceded detection by imaging by more than 2 months in 22% to 39% of patients. Specificities varied considerably, ranging from 61% to 97%. The computational classifier detected ACC recurrence with superior accuracy (sensitivity = specificity = 81%). CONCLUSION: Urine steroid metabolomics is a promising tool for postoperative recurrence detection in ACC; availability of a preoperative urine considerably improves the ability to detect ACC recurrence.

Use of urinary steroid profiling for diagnosing and monitoring adrenocortical tumours.

It has been suggested that urinary steroid profiling may be used to provide information aiding the diagnosis and monitoring of adrenocortical carcinoma. Nonetheless, the abnormal patterns suggestive of adrenal malignancy are not well defined. We retrospectively studied the urinary steroid profiles of five patients with adrenocortical carcinoma at presentation and at follow-up, and compared these results with those from 76 patients with benign adrenocortical adenoma and 172 healthy controls. Three abnormal patterns of urinary steroid excretion were identified in patients with adrenocortical carcinoma at presentation and/or follow-up of residual disease: (1) hypersecretion in multiple steroid axes; (2) excretion of unusual metabolites, notably 5-pregnene-3alpha,16alpha,20alpha-triol, 5-pregnene-3beta,16alpha,20alpha-triol, and neonatal steroid metabolites in the post-neonatal period; (3) increase of tetrahydro-11-deoxycortisol relative to total cortisol metabolites. These preliminary findings offer ways in which urinary steroid profiling performed using gas chromatography-mass spectrometry can be helpful in the diagnosis and monitoring of adrenocortical carcinoma.

Comparison of plasma and urinary microRNA-483-5p for the diagnosis of adrenocortical malignancy.

INTRODUCTION: Minimally invasive circulating microRNAs might be used for the preoperative differentiation of adrenocortical carcinoma (ACC) and adrenocortical adenoma (ACA). So far, the best blood-borne microRNA biomarker of ACC is circulating hsa-miR-483-5p. The expression of urinary hsa-miR-483-5p as a non-invasive marker of malignancy and its correlation with plasma hsa-miR-483-5p, has not been investigated, yet. AIM: Our aim was to investigate the expression of urinary hsa-miR-483-5p and its correlation with its plasma counterpart. METHODS: Plasma and urinary samples from 23 ACC and 23 ACA patients were analysed using real-time RT-qPCR. To evaluate the diagnostic applicability of hsa-miR-483-5p, ROC-analysis was performed. RESULTS: Significant overexpression of hsa-miR-483-5p was observed in carcinoma patients' plasma samples compared to adenoma patients' (p < 0.0001, sensitivity: 87%, specificity: 78.3%). In urinary samples, however, no significant difference could be detected between ACC and ACA patients. CONCLUSIONS: Plasma hsa-miR-483-5p has been confirmed as significantly overexpressed in adrenocortical cancer patients and thus might be exploited as a minimally invasive preoperative marker of malignancy. The applicability of urinary hsa-miR-483-5p for the diagnosis of adrenocortical malignancy could not be confirmed.

Different Types of Urinary Steroid Profiling Obtained by High-Performance Liquid Chromatography and Gas Chromatography-Mass Spectrometry in Patients with Adrenocortical Carcinoma.

Urinary steroid profiling (USP) was studied using high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) methods in 108 patients with adrenocortical adenoma (ACA) and in 31 patients with adrenocortical carcinoma (ACC). Thirteen ACC and Cushing's syndrome (ACC-CS) patients had two types of USP as well as 18 ACC patients without hypercortisolism. These four types differed by androgen and glucocorticoid secretion of the adrenal cortex. Fifteen main ACC features were observed by GC-MS. Urinary excretion of dehydroepiandrosterone (DHEA) was increased in 67.7 % of ACC patients and tetrahydro-11-deoxycortisol (THS) in 74.2 %. By combination of the following parameters: THS >900 µg/24 h and/or DHEA >1500 µg/24 h with ratios of 3α,16,20-pregnentriol/3ß,16,20-pregnentriol (3α,16,20dP3/3ß,16,20dP3) less than 6.0 and 3α,17,20dP3/3ß,17,20dP3 less than 9.0 and the detection of "non-classical" 5-en-pregnens, not found in ACA and healthy persons, 100 % sensitivity and specificity of ACC and ACA differential diagnosis were achieved. Features of 21-hydroxylase and 11ß-hydroxylase deficiency were observed by GC-MS in 32.2 and 61.3 % of the ACC patients, respectively. Additional features for ACC-CS diagnostic were increased urinary excretion of 6ß-hydroxycortisol, 18-hydroxycorticosterone, the sum (UFF + UFE) obtained by HPLC, tetrahydrocorticosterone, and the sum (THF + THE + allo-THF) obtained by GC-MS.

Circulating vascular endothelial growth factor and active renin concentrations and prostaglandin E2 urinary excretion in patients with adrenal tumours.

OBJECTIVES: The aim of the present study was to determine vascular endothelial growth factor (VEGF), prostaglandin E(2) (PGE(2)) and active renin levels in patients with hormonally active adrenal tumours. DESIGN: The study was comprised of 16 patients with primary aldosteronism, 13 patients with active Cushing's syndrome due to adrenal adenomas, 8 patients with adrenal carcinomas, 19 patients with phaeochromocytoma and 19 healthy volunteers. METHODS: Active renin in plasma was determined by a two-site immunoradiometric assay. VEGF in sera samples and PGE(2) in 24-h urine were measured by ELISA. RESULTS: VEGF was significantly elevated in all the four groups of patients as compared with the controls. VEGF levels in patients with Cushing's syndrome were higher than those in patients with primary aldosteronism. Patients with adrenal carcinomas had the highest VEGF levels and the differences reached significance as compared with patients with primary aldosteronism and phaeochromocytoma. PGE(2) levels were not significantly different among groups. Active renin was significantly the lowest in patients with primary aldosteronism and significantly the highest in patients with phaeochromocytoma compared with the controls. Active renin in patients with primary aldosteronism was significantly lower than in those with Cushing's syndrome, phaeochromocytoma and adrenal carcinoma. CONCLUSIONS: Our data indicated that the mean level of VEGF in patients with all investigated adrenal tumours was significantly higher than in healthy controls. The cortisol-producing tumours appear to have increased angiogenic potential. Angiogenesis is probably associated not only with malignancy but also with functional activity of the adrenal tumors.

Mitotane therapy in adrenocortical cancer induces CYP3A4 and inhibits 5α-reductase, explaining the need for personalized glucocorticoid and androgen replacement.

CONTEXT: Mitotane [1-(2-chlorophenyl)-1-(4-chlorophenyl)-2,2-dichloroethane] is the first-line treatment for metastatic adrenocortical carcinoma (ACC) and is also regularly used in the adjuvant setting after presumed complete removal of the primary tumor. Mitotane is considered an adrenolytic substance, but there is limited information on distinct effects on steroidogenesis. However, adrenal insufficiency and male hypogonadism are widely recognized side effects of mitotane treatment. OBJECTIVE: Our objective was to define the impact of mitotane treatment on in vivo steroidogenesis in patients with ACC. SETTING AND DESIGN: At seven European specialist referral centers for adrenal tumors, we analyzed 24-h urine samples (n = 127) collected from patients with ACC before and during mitotane therapy in the adjuvant setting (n = 23) or for metastatic ACC (n = 104). Urinary steroid metabolite excretion was profiled by gas chromatography/mass spectrometry in comparison with healthy controls (n = 88). RESULTS: We found a sharp increase in the excretion of 6ß-hydroxycortisol over cortisol (P < 0.001), indicative of a strong induction of the major drug-metabolizing enzyme cytochrome P450 3A4. The contribution of 6ß-hydroxycortisol to total glucocorticoid metabolites increased from 2% (median, interquartile range 1-4%) to 56% (39-71%) during mitotane treatment. Furthermore, we documented strong inhibition of systemic 5α-reductase activity, indicated by a significant decrease in 5α-reduced steroids, including 5α-tetrahydrocortisol, 5α-tetrahydrocorticosterone, and androsterone (all P < 0.001). The degree of inhibition was similar to that in patients with inactivating 5α-reductase type 2 mutations (n = 23) and patients receiving finasteride (n = 5), but cluster analysis of steroid data revealed a pattern of inhibition distinct from these two groups. Longitudinal data showed rapid onset and long-lasting duration of the observed effects. CONCLUSIONS: Cytochrome P450 3A4 induction by mitotane results in rapid inactivation of more than 50% of administered hydrocortisone, explaining the need for doubling hydrocortisone replacement in mitotane-treated patients. Strong inhibition of 5α-reductase activity is in line with the clinical observation of relative inefficiency of testosterone replacement in mitotane-treated men, calling for replacement by 5α-reduced androgens.

Urine steroid metabolomics as a biomarker tool for detecting malignancy in adrenal tumors.

CONTEXT: Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2-11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values. OBJECTIVE: Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy. DESIGN: Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19-84 yr) and 45 ACC patients (20-80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26-201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids. RESULTS: Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers. CONCLUSIONS: Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.