Bertherat, Jérôme

Abstract Context Biochemical test results are central to clinical decision-making for the diagnosis and management of Cushing syndrome (CS). With emerging research and increasing availability of different tests, updated consensus on the utility of these biomarkers is warranted. Objective To establish an updated consensus on the role of biomarkers in the diagnosis and monitoring of adrenocorticotropic hormone-dependent CS, address novel therapeutic approaches, and identify areas for future research. Design A modified 2-round Delphi panel was conducted. Consensus was defined as ≥70% agreement/disagreement for Likert-scale statements or ≥70% selection of the same option for single-choice questions. Setting Participants represented a range of international expertise. Participants Forty-one participants took part in the Delphi panel, with no attrition between rounds (one nonclinician was not required to complete the second round). An 8-member Steering Committee guided statement development. Results Of statements designed to reach consensus, 45% (14/31) and 44% (11/25) statements reached consensus in Rounds 1 and 2, respectively. Notably, most panelists reported the use of late-night salivary cortisol for diagnosis of mild CS and for monitoring following pituitary surgery or medical or radiation therapy. Most panelists responded that block-and-replace therapies can be considered in patients with cyclical or severe CS, and consensus was reached that restoration of circadian rhythm is a treatment goal for patients with CS. Conclusion Areas of alignment among experts on the diagnosis and monitoring of CS are presented. The findings from this study are intended to support clinicians in their clinical decision-making and highlight priority areas for future research.

Abstract Disclosure: A. Prete: HRA Pharmaceuticals, Lundbeck, Diurnal. L. Adbi: None. J.T. Bain: None. F. Shaheen: None. O. Suntornlohanakul: None. E. Deflorenne: None. A. Blanchard: None. M. Nestola: None. C. Pamporaki: None. I. Tizianel: None. E. Nowak: None. J. Bertherat: None. D.A. Vassiliadi: None. I. Bancos: None. C.M. Dennedy: None. D. Kastelan: None. M. Fassnacht: None. P. Mulatero: None. U. Ambroziak: None. A. Tabarin: None. M. Quinkler: None. S. Puglisi: None. J. Deinum: None. G.Å. Ueland: None. L. Lenzini: None. F. Beuschlein: None. M. Reincke: None. F. Ceccato: None. G. Eisenhofer: None. S.M. Corsello: None. L. Amar: None. M. Zennaro: None. N. Karavitaki: None. A.E. Taylor: None. W. Arlt: None. Introduction: Twenty-four-hour urinary free cortisol is used to diagnose Cushing’s syndrome (CS); amongst its limitations is failure to differentiate ACTH-dependent CS (AD-CS) from ACTH-independent CS (AI-CS). We tested the performance of urine steroid metabolomics (USM), the computational analysis of 24-hour urine steroid metabolome data by machine learning, for the diagnosis and differential diagnosis of CS. Given the physiological diurnal rhythm of cortisol secretion and its loss in CS, we also hypothesised that the difference in glucocorticoid excretion between CS and controls should be higher during nighttime, thereby facilitating more sensitive detection of CS. Methods: 264 subjects completed a 24-hour urine collection (40 AD-CS, 103 AI-CS due to adrenocortical adenoma or hyperplasia, 121 healthy subjects). A subset of 52 individuals (13 CS, 39 healthy) provided a nighttime urine collection and a daytime urine collection. Mass spectrometry-based multi-steroid profiling was used to quantify the urinary excretion of 27 steroid metabolites. Data were analysed by generalised matrix learning vector quantisation (a prototype-based supervised machine learning approach), multiple linear regression adjusted for age, sex, and BMI, and multiple logistic regression adjusted for age, sex, and BMI. Results: Twenty-four-hour USM demonstrated very high accuracy in differentiating CS from healthy individuals (AUC-ROC 0.99, 95%CI 0.99-0.99), reflected by higher urinary excretion of glucocorticoid and glucocorticoid precursor metabolites in CS. USM yielded high accuracy in differentiating AD-CS from AI-CS (AUC-ROC 0.91, 95%CI 0.89-0.94), with androgen metabolites being the most discriminatory. We observed significant sex differences in steroid excretion in both healthy individuals and those with CS. Women exhibited markedly lower excretion of both glucocorticoids and mineralocorticoids compared to men: average glucocorticoid excretion was reduced by 43% in healthy women and 30% in CS women, while average mineralocorticoid excretion was 29% lower in healthy women and 51% lower in CS women (results adjusted for age and BMI). Timed steroid excretion in healthy individuals reflected the diurnal pattern of adrenal steroid secretion, with lower nighttime than daytime excretion of glucocorticoid metabolites. Nighttime glucocorticoid metabolite excretion (AUC-ROC 1.00, 95%CI 0.99-1.00) performed better than daytime (AUC-ROC 0.91, 95%CI 0.77-1.00) and 24-hour excretion (AUC-ROC 0.94, 95%CI 0.86-1.00) in separating CS cases from healthy individuals. Conclusions: USM is a non-invasive, one-step candidate test for the accurate diagnosis and differential diagnosis of CS. Timed nighttime urine collection leverages cortisol circadian rhythmicity and improves the diagnostic accuracy of the current reference standard 24-hour collection. Presentation: Sunday, July 13, 2025

1 Background: The ESE-ENSAT guidelines on ACC management suggest adjuvant mitotane for patients at high risk of recurrence. This indication has limited evidence base, lacking results from randomized controlled trials. No suggestion for or against adjuvant mitotane in low-risk patients was given, since studies did not stratify patients for prognosis. The randomized controlled study ADIUVO compared the efficacy of adjuvant mitotane treatment vs. observation in prolonging recurrence-free survival (RFS) in patients at low-intermediate risk of recurrence. Methods: The main inclusion criteria were: stage I-III ACC, R0 surgery, and Ki-67 ≤10%. Patients were randomly assigned 1:1 to adjuvant mitotane or observation. The primary endpoint of the study was RFS. Patients who refused randomization were eligible for the ADIUVO OBSERVATIONAL study. In this prospective, observational study, patients were managed as in ADIUVO except for randomization. A total of 91 patients were enrolled in ADIUVO, 45 in the mitotane and 46 in the observation arm. Baseline characteristics of patients were perfectly matched between the 2 arms: median age, 51 vs. 50.5 years; female, 73% vs. 67%; stage I, 20% vs. 26%; stage II, 67% vs. 63%, stage III, 13% vs. 11%; ACC secretion 44% vs. 36%; Weiss 5 vs. 5; respectively. In ADIUVO OBSERVATIONAL, 42 patients were treated with mitotane and 53 were untreated. Baseline characteristics of patients were matched between the 2 groups and with mitotane and observation groups in ADIUVO. Thus, the ADIUVO OBSERVATIONAL cohort was analyzed in parallel to deal with the lower than expected recruitment in ADIUVO. Results: In the ADIUVO study, recurrences were 8 in the MIT and 11 in the OBS arm, while deaths were 2 and 5, respectively. RFS and overall survival (OS) did not significantly differ between the 2 arms. In the OBS arm, the HR for recurrence was 1.321 (95%CI, 0.55-3.32, p = 0.54) and HR for death 2.171 (95%CI, 0.52-12.12, p = 0.29). The survival analysis in the ADIUVO OBSERVATIONAL study confirmed that of ADIUVO. Given the outcome of both studies, the NNT is 55. Conclusions: ACC patients at low-intermediate risk of recurrence after surgery are a minority; however, they show a far better prognosis than expected (5-yr RFS is 75%) and do not benefit significantly from adjuvant mitotane. The results of the ADIUVO study do not support routine use of adjuvant mitotane in this subset of patients, who may thus avoid a potentially toxic treatment. This is an important step toward personalization of ACC care. Clinical trial information: NCT00777244.

Abstract 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.

Abstract Several types of adrenocortical tumors that lead to Cushing syndrome may be caused by aberrant cyclic AMP (cAMP) signaling. We recently identified patients with micronodular adrenocortical hyperplasia who were carriers of inactivating mutations in the 2q-located phosphodiesterase 11A (PDE11A) gene. We now studied the frequency of two missense substitutions, R804H and R867G, in conserved regions of the enzyme in several sets of normal controls, including 745 individuals enrolled in a longitudinal cohort study, the New York Cancer Project. In the latter, we also screened for the presence of the previously identified PDE11A nonsense mutations. R804H and R867G were frequent among patients with adrenocortical tumors; although statistical significance was not reached, these variants affected significantly enzymatic function in vitro with variable increases in cAMP and/or cyclic guanosine 3′,5′-monophosphate levels in HeLa and HEK293 cells. Adrenocortical tissues carrying the R804H mutation showed 2q allelic losses and higher cyclic nucleotide levels and cAMP-responsive element binding protein phosphorylation. We conclude that missense mutations of the PDE11A gene that affect enzymatic activity in vitro are present in the general population; protein-truncating PDE11A mutations may also contribute to a predisposition to other tumors, in addition to their association with adrenocortical hyperplasia. We speculate that PDE11A genetic defects may be associated with adrenal pathology in a wider than previously suspected clinical spectrum that includes asymptomatic individuals. (Cancer Res 2006; 66(24): 11571-5)