ABSTRACT
The majority of pituitary adenomas occur in a sporadic context, and in the absence of known genetic predisposition. Three common variants at the NEBL (rs2359536), PCDH15 (rs10763170) and CDK8 (rs17083838) loci were previously associated with sporadic pituitary adenomas in the Han Chinese population, but these findings have not yet been replicated in any other population. The aim of this case-control study was to assess if these variants are associated with susceptibility to sporadic pituitary adenomas in the Portuguese population. Genotype and allele frequencies were determined in 570 cases and in 546 controls. The CDK8 rs17083838 minor allele (A allele) was significantly associated with sporadic pituitary adenomas, under an additive (odds ratio (OR) 1.73, 95% confidence interval (CI) 1.19-2.50, p = 0.004) and dominant (OR 1.82, 95% CI 1.24-2.68, p = 0.002) inheritance model. The NEBL rs2359536 and PCDH15 rs10763170 variants were not associated with the overall risk for the disease, although a borderline significant association was observed between the PCDH15 rs10763170 minor allele (T allele) and somatotrophinomas (dominant model, OR 1.55, 95% CI 1.02-2.35, p = 0.035). These findings suggest that the CDK8 rs17083838 variant, and possibly the PCDH15 rs10763170 variant, may increase susceptibility to sporadic pituitary adenomas in the Portuguese population.
Subject(s)
Adenoma , Cyclin-Dependent Kinase 8 , Pituitary Neoplasms , Adenoma/genetics , Case-Control Studies , Cyclin-Dependent Kinase 8/genetics , Genetic Predisposition to Disease , Genotype , Humans , Pituitary Neoplasms/genetics , Polymorphism, Single Nucleotide , PortugalABSTRACT
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.
