Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study.

COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.

Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm.

PURPOSE: The purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC). MATERIALS AND METHODS: Patients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard. RESULTS: Fifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55-88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80-99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60-87). CONCLUSION: A multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

Artificial Intelligence in Endocrinology: On Track Toward Great Opportunities.

In endocrinology, the types and quantity of digital data are increasing rapidly. Computing capabilities are also developing at an incredible rate, as illustrated by the recent expansion in the use of popular generative artificial intelligence (AI) applications. Numerous diagnostic and therapeutic devices using AI have already entered routine endocrine practice, and developments in this field are expected to continue to accelerate. Endocrinologists will need to be supported in managing AI applications. Beyond technological training, interdisciplinary vision is needed to encompass the ethical and legal aspects of AI, to manage the profound impact of AI on patient/provider relationships, and to maintain an optimal balance between human input and AI in endocrinology.

Prognostic impact of hypothalamic perforation in adult patients with craniopharyngioma: a cohort study.

CONTEXT: Outcome of craniopharyngioma is related to its locoregional extension, which impacts resectability and the risk of surgical complications. To maximize resection and minimize complications, optic tract localization, temporal lobe extension and hypothalamic involvement are essential for surgical management. OBJECTIVE: To assess the outcome of craniopharyngiomas depending on their relation to the hypothalamus location. METHODS: We conducted a retrospective analysis of 79 patients with a craniopharyngioma who underwent surgery from 2007 to 2022. Craniopharyngiomas were classified in three groups, depending on the type of hypothalamus involvement assessed by preoperative MRI: infra-hypothalamic (type A, n=33); perforating the hypothalamus (type B, n=40); supra-hypothalamic (type C, n=6). Surgical strategy was guided by the type of hypothalamic involvement, favoring endonasal approaches for type A and type B, and transcranial approaches for type C. RESULTS: Long-term disease control was achieved in 33/33 (100%), 37/40 (92%) and 5/6 (83%) patients in type A, B and C respectively. In type B, vision was improved in 32/36 (89%) patients, while hypothalamic function was improved, stable or worsened in 6/40 (15%), 32/40 (80%) and 2/40 (5%) patients respectively. Papillary craniopharyngiomas were found in 5/33 (15%), 9/40 (22%) and 3/6 (50%) patients in types A, B and C respectively. In four patients, BRAF/MEK inhibitors were used, with significant tumor shrinkage in all cases. CONCLUSION: Craniopharyngiomas located below the hypothalamus or perforating it can be safely treated by transsphenoidal surgery. For supra-hypothalamic craniopharyngiomas, postoperative results are less favorable, and documenting a BRAF-mutation may improve outcome, if targeted therapy was efficient enough to replace surgical debulking.

Carney complex predisposes to breast cancer: prospective study of 50 women.

OBJECTIVE: Carney complex (CNC) is a rare genetic syndrome, mostly due to germline loss-of-function pathogenic variants in PRKAR1A. Carney complex includes pigmented skin lesions, cardiac myxomas, primary pigmented nodular adrenocortical dysplasia, and various breast benign tumors. DESIGN: The present study was designed to describe the characteristics of breast lesions in CNC patients and their association with other manifestations of CNC and PRKAR1A genotype. METHODS: A 3-year follow-up multicenter French prospective study of CNC patients included 50 women who were analyzed for CNC manifestations and particularly breast lesions, with breast imaging, genotyping, and hormonal settings. RESULTS: Among the 38 women with breast imaging, 14 (39%) had breast lesions, half of them bilateral. Ten women (26%) presented with benign lesions and six with breast carcinomas (16%): one had ductal carcinoma in situ at 54, and five had invasive cancer before 50 years old, whom one with contralateral breast cancer during follow-up. The occurrence of breast cancer was more frequent in women with PRKAR1A pathogenic variant odds ratio = 6.34 (1.63-17.91) than in general population of same age. The mean age at breast cancer diagnosis was 44.7 years old: 17 years younger than in the general population. Breast cancer patients had good prognosis factors. All breast carcinomas occurred in individuals with familial CNC and PRKAR1A pathogenic variants. Loss of heterozygosity at the PRKAR1A locus in the 2 invasive breast carcinomas analyzed suggested a driver role of this tumor suppressor gene. CONCLUSIONS: As CNC could predispose to breast carcinoma, an adequate screening strategy and follow-up should be discussed in affected women. CLINICAL TRIAL REGISTRATION: ClinicalTrial.gov NCT00668291.

Consensus statement by the French Society of Endocrinology (SFE) and French Society of Pediatric Endocrinology & Diabetology (SFEDP) for the diagnosis of Cushing's syndrome: Genetics of Cushing's syndrome.

Cushing's syndrome is due to overproduction of cortisol, leading to abnormal and prolonged exposure to cortisol. The most common etiology is Cushing disease, while adrenal causes are rarer. Knowledge of the genetics of Cushing's syndrome, and particularly the adrenal causes, has improved considerably over the last 10 years, thanks in particular to technical advances in high-throughput sequencing. The present study, by a group of experts from the French Society of Endocrinology and the French Society of Pediatric Endocrinology and Diabetology, reviewed the literature on germline genetic alterations leading to a predisposition to develop Cushing's syndrome. The review led to a consensus statement on genetic screening for Cushing disease and adrenal Cushing's syndrome.

Pituitary surgery outcome in patients 75 years and older: a retrospective study.

BACKGROUND: As the population ages, the number of elderly patients with an indication for pituitary surgery is rising. Information on the outcome of patients aged over 75 is limited. This study reports a large series assessing the feasibility of surgical resection in this specific age range, focusing on surgical complications and postoperative results. METHODS: A retrospective cohort study of patients with pituitary adenomas and Rathke's cleft cysts was conducted. All patients were aged 75 years or over and treated by a single expert neurosurgical team. A control population included 2379 younger adult patients operated by the same surgeons during the same period. RESULTS: Between 2008 and 2022, 155 patients underwent surgery. Indication was based on vision impairment in most patients (79%). Median follow-up was 13 months (range: 3-96). The first surgery was performed with an endoscopic transsellar approach, an extended endonasal transtuberculum approach and a microscopic transcranial approach in 96%, 3%, and 1% of patients, respectively. Single surgery was sufficient to obtain volume control in 97% of patients. From Kaplan-Meier estimates, 2-year and 5-year disease control with a single surgery were 97.3% and 86.2%, respectively. Resection higher than 80% was achieved in 77% of patients. No vision worsening occurred. In acromegaly and Cushing's disease, endocrine remission was obtained in 90% of non-invasive adenomas. Surgical complications were noted in 5% of patients, with 30-day mortality, hematoma, cerebrospinal fluid leak, meningitis, and epistaxis occurring in 0.6%, 0.6%, 1.9%, 0.6%, and 1.3% respectively. New endocrine anterior deficits occurred in only 5%, while no persistent diabetes insipidus was noted. Compared with younger patients, the complication rate was not statistically different. CONCLUSIONS: Surgery beyond the age of 75, mainly relying on an endoscopic endonasal transsellar approach, is effective and safe, provided that patients are managed in tertiary centers.

DNA hypermethylation driven by DNMT1 and DNMT3A favors tumor immune escape contributing to the aggressiveness of adrenocortical carcinoma.

BACKGROUND: Adrenocortical carcinoma is rare and aggressive endocrine cancer of the adrenal gland. Within adrenocortical carcinoma, a recently described subtype characterized by a CpG island methylator phenotype (CIMP) has been associated with an especially poor prognosis. However, the drivers of CIMP remain unknown. Furthermore, the functional relation between CIMP and poor clinical outcomes of patients with adrenocortical carcinoma stays elusive. RESULTS: Here, we show that CIMP in adrenocortical carcinoma is linked to the increased expression of DNA methyltransferases DNMT1 and DNMT3A driven by a gain of gene copy number and cell hyperproliferation. Importantly, we demonstrate that CIMP contributes to tumor aggressiveness by favoring tumor immune escape. This effect could be at least partially reversed by treatment with the demethylating agent 5-azacytidine. CONCLUSIONS: In sum, our findings suggest that co-treatment with demethylating agents might enhance the efficacy of immunotherapy and could represent a novel therapeutic approach for patients with high CIMP adrenocortical carcinoma.

Embryonic stem cell factor FOXD3 (Genesis) defects in gastrointestinal stromal tumors.

Gastrointestinal stromal tumors (GISTs) are mesenchymal neoplasms, believed to originate from the interstitial cells of Cajal (ICC), often caused by overexpression of tyrosine kinase receptors (TKR) KIT or PDGFRA. Here, we present evidence that the embryonic stem cell factor FOXD3, first identified as 'Genesis' and involved in both gastrointestinal and neural crest cell development, is implicated in GIST pathogenesis; its involvement is investigated both in vitro and in zebrafish and a mouse model of FOXD3 deficiency. Samples from a total of 58 patients with wild-type GISTs were used for molecular analyses, including Sanger sequencing, comparative genomic hybridization, and methylation analysis. Immunohistochemistry and western blot evaluation were used to assess FOXD3 expression. Additionally, we conducted in vitro functional studies in tissue samples and in transfected cells to confirm the pathogenicity of the identified genetic variants. Germline partially inactivating FOXD3 sequence variants (p.R54H and p.Ala88_Gly91del) were found in patients with isolated GISTs. Chromosome 1p loss was the most frequent chromosomal abnormality identified in tumors. In vitro experiments demonstrate the impairment of FOXD3 in the presence of those variants. Animal studies showed disruption of the GI neural network and changes in the number and distribution in the ICC. FOXD3 suppresses KIT expression in human cells; its inactivation led to an increase in ICC in zebrafish, as well as mice, providing evidence for a functional link between FOXD3 defects and KIT overexpression leading to GIST formation.

The World Health Organization classifications of pituitary neuroendocrine tumours: a clinico-pathological appraisal.

The classification of tumours of the pituitary gland has recently been revised in the 2021 5th edition World Health Organization (WHO) Classification of Central Nervous System Tumours (CNS5) and 2022 5th edition WHO Classification of Endocrine and Neuroendocrine Tumours (ENDO5). This brief review aims to appraise the most relevant changes and updates introduced in the two classifications. A new nomenclature has been introduced in CNS5 and ENDO5 to align adenohypophyseal tumours with the classification framework of neuroendocrine neoplasia. The term pituitary neuroendocrine tumour (PitNET) with subtype information has therefore been adopted and preferred to adenoma. Pituitary carcinoma has been replaced by metastatic PitNET. The ICD-O coding has been changed from benign to malignant in line with NETs from other organs. Histological typing and subtyping based on immunohistochemistry for lineage-restricted pituitary transcription factors are regarded as the cornerstone for accurate classification. Such an approach does not fully reflect the complexity and dynamics of pituitary tumorigenesis and the variability of transcription factors expression. ENDO5 does not support a grading and/or staging system and argues that histological typing and subtyping are more robust than proliferation rate and invasiveness to stratify tumours with low or high risk of recurrence. However, the prognostic and predictive relevance of histotype is not fully validated. Recent studies suggest the existence of clinically relevant molecular subgroups and emphasize the need for a standardized, histo-molecular integrated approach to the diagnosis of PitNETs to further our understanding of their biology and overcome the unsolved issue of grading and/or staging system.

C-peptide level concomitant with hypoglycemia gives better performances than insulin for the diagnosis of endogenous hyperinsulinism: a single-center study of 159 fasting trials.

INTRODUCTION: Diagnosis of endogenous hyperinsulinism relies on the occurrence of a hypoglycemia, concomitant with inadequate high insulin and C-peptide levels. However, diagnostic cutoffs are not consensual among the different learned societies. The objective of this work was to propose optimized cutoffs for these three parameters for the diagnosis of endogenous hyperinsulinism. METHODS: All the patients having performed a fasting trial in Cochin Hospital Endocrinology Department between February 2012 and August 2022 were included. The results of glycemia, insulin and C-peptide levels during fasting trial were collected and analyzed. RESULTS: One hundred and fifty-nine patients were included: 26 with endogenous hyperinsulinism and 133 without endogenous hyperinsulinism. ROC analysis of glycemia nadir during fasting trial identified the value of 2.3 mmol/L as the optimal cutoff, ensuring a sensitivity of 100% associated with a specificity of 81%. ROC analysis of insulin and C-peptide levels concomitant with hypoglycemia <2.3 mmol/L showed very good diagnostic performances of both parameters with respective cutoffs of 3.1 mUI/L (=21.5 pmol/L; sensitivity = 96%; specificity = 92%) and 0.30 nmol/L (sensitivity = 96%; specificity = 100%). Insulin to glycemia ratio as well as C-peptide to glycemia ratio (in pmol/mmol) at the time of glycemia nadir did not show better diagnostic performances than C-peptide alone. CONCLUSION: A C-peptide level 0.3 nmol/L concomitant with a hypoglycemia <2.3 mmol/L appears as the best criterion to make the diagnosis of endogenous hyperinsulinism. Insulin level can be underestimated on hemolyzed blood samples, frequently observed in fasting trial, and thus shows lower diagnostic performances.

Positive Correlation Between 18 F-FDG Uptake and Tumor-Proliferating Antigen Ki-67 Expression in Adrenocortical Carcinomas.

PURPOSE OF THE REPORT: Adrenocortical carcinoma (ACC) is an extremely rare endocrine malignancy, which cannot always be diagnosed during conventional radiology and hormonal investigations. 18 F-FDG PET could help predict malignancy, but more data are necessary to support future guidelines. METHODS: A cohort of 63 patients with histologically proven ACC (n = 55) or metastatic ACC with steroid oversecretion (n = 8) was assembled. All patients underwent an 18 F-FDG PET, and the SUV max and the adrenal-to-liver SUV max ratio were calculated. The 18 F-FDG PET parameters were compared with clinical, pathological, and outcome data. RESULTS: Fifty-six of 63 patients (89%) had an ACC with an adrenal-to-liver SUV max ratio >1.45, which was a previously defined cutoff value to predict malignancy with 100% sensitivity. Seven ACCs (11%) had a lower uptake (adrenal-to-liver SUV max <1.45), most of them with a proliferation marker Ki-67 expression level <10%. A positive correlation between 18 F-FDG PET parameters (SUV max and adrenal-to-liver SUV max ratio) and tumor size, ENSAT (European Network for the Study of Adrenal Tumors) staging, total Weiss score, and the Ki-67 was found. The strong correlation between SUV max and Ki-67 ( r = 0.47, P = 0.0009) suggests a relationship between 18 F-FDG uptake levels and tumor proliferation. No statistically significant associations between outcome parameters (progression-free or overall survival) and 18 F-FDG PET parameters were found. CONCLUSIONS: This large cohort study shows that most cases of ACC demonstrate high 18 F-FDG uptake. However, the positive correlation observed between SUV max and Ki-67 expression levels seems to explain the possibility of identifying some ACC with a low or inexistent 18 F-FDG uptake. These findings have practical implications for the management of patients with an adrenal mass.

Artificial intelligence in adrenal imaging: A critical review of current applications.

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps from detection to analysis does not exist yet, multiple AI algorithms have been developed and tested with encouraging results. However, AI in this setting is still at an early stage. In this regard, most published studies about AI in adrenal gland imaging report preliminary results that do not have yet daily applications in clinical practice. In this review, recent developments and current results of AI in the field of adrenal imaging are presented. Limitations and future perspectives of AI are discussed.

Whole blood methylome-derived features to discriminate endocrine hypertension.

BACKGROUND: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches. RESULTS: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL. CONCLUSIONS: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Corticotroph tumor progression speed after adrenalectomy.

Objectives: After bilateral adrenalectomy in Cushing's disease, corticotroph tumor progression occurs in one-third to half of patients. However, progression speed is variable, ranging from slow to rapid. The aim was to explore corticotroph progression speed, its consequences and its risk factors. Design: A retrospective single-center observational study. Methods: In total,103 patients with Cushing's disease who underwent bilateral adrenalectomy between 1990 and 2020 were included. Clinical, biological, histological and MRI features were collected. Median duration of follow-up after bilateral adrenalectomy was 9.31 years. Results: In total,44 patients progressed (43%). Corticotroph tumor progression speed ranged from 1 to 40.7 mm per year. Progression speed was not different before and after bilateral adrenalectomy (P = 0.29). In univariate analyses, predictive factors for rapid corticotroph tumor progression included the severity of Cushing's disease before adrenalectomy as the cause of adrenalectomy, high ACTH in the year following adrenalectomy and high Ki67 immunopositivity in the tumor. During follow-up, early morning ACTH absolute variation was associated with corticotroph tumor progression speed (P-value = 0.001). ACTH measurement after dynamic testing did not improve this association. Conclusion: After adrenalectomy, corticotroph progression speed is highly variable and manageable with MRI and ACTH surveillance. Progression speed does not seem related to bilateral adrenalectomy but rather to intrinsic properties of highly proliferative and secreting tumors.

Real-life efficacy and predictors of response to immunotherapy in pituitary tumors: a cohort study.

Objective: After temozolomide failure, no evidence-based treatment is available for pituitary carcinomas (PCs) and aggressive pituitary tumors (APTs). To date, only 12 cases treated with immune-checkpoint inhibitors (ICIs) have been published, showing encouraging efficacy. Predictive factors of response are lacking. Here, we aimed to assess the real-life efficacy and predictors of response to ICIs in PCs and APTs. Design and methods: This study is a multicentric, retrospective, observational cohort study, including all PCs and APTs treated with ICIs in France up to March 2022. PD-L1 immunohistochemistry and CD8+ T cell infiltration were evaluated centrally. Results: Six PCs (four corticotroph and two lactotroph) and nine APTs (five corticotroph and four lactotroph) were included. The real-life efficacy of ICIs was lower than previously published data. Three corticotroph tumors (33.3%) showed partial response, one (11.1%) stable disease, while five (55.6%) progressed. One lactotroph tumor (16.7%) showed partial response, one (16.7%) stable disease, while four (66.7%) progressed. PCs responded far better than APTs, with 4/6 PCs showing partial response compared to 0/9 APTs. Corticotroph tumors responded slightly better than lactotroph tumors. In the four responsive corticotroph tumors, PD-L1 staining was negative and CD8+ T cell infiltration attained a maximum of 1% in the tumor center. Conclusions: Confirmation of the presence or absence of metastases is necessary before starting ICIs. After temozolomide failure, ICIs appear as a good therapeutic option for PCs, especially for corticotroph carcinomas. Negative PD-L1 staining and very low CD8+ T cell infiltration in the tumor center should not preclude ICI administration in corticotroph carcinomas. Significance statement: This is the first study to assess the real-life efficacy of ICIs in pituitary carcinomas (PCs) and aggressive pituitary tumors. We also assessed potential predictors of response and are the first to assess the predictive value of CD8+ cell infiltration. We identified the tumor type as a major predictor, ICIs proving far more effective in treating PCs. Our study provides evidence that ICIs are a good option after temozolomide failure for PCs (four of six responded), especially for corticotroph carcinomas (three of four responded). We also provide evidence that negative PD-L1 staining and very low CD8+ cell infiltration in the tumor center should not preclude ICI administration in corticotroph carcinomas. Moreover, our findings point toward the need to systematically perform extension workup before starting ICIs.

TP53 mutations in functional corticotroph tumors are linked to invasion and worse clinical outcome.

Corticotroph macroadenomas are rare but difficult to manage intracranial neoplasms. Mutations in the two Cushing's disease mutational hotspots USP8 and USP48 are less frequent in corticotroph macroadenomas and invasive tumors. There is evidence that TP53 mutations are not as rare as previously thought in these tumors. The aim of this study was to determine the prevalence of TP53 mutations in corticotroph tumors, with emphasis on macroadenomas, and their possible association with clinical and tumor characteristics. To this end, the entire TP53 coding region was sequenced in 86 functional corticotroph tumors (61 USP8 wild type; 66 macroadenomas) and the clinical characteristics of patients with TP53 mutant tumors were compared with TP53/USP8 wild type and USP8 mutant tumors. We found pathogenic TP53 variants in 9 corticotroph tumors (all macroadenomas and USP8 wild type). TP53 mutant tumors represented 14% of all functional corticotroph macroadenomas and 24% of all invasive tumors, were significantly larger and invasive, and had higher Ki67 indices and Knosp grades compared to wild type tumors. Patients with TP53 mutant tumors had undergone more therapeutic interventions, including radiation and bilateral adrenalectomy. In conclusion, pathogenic TP53 variants are more frequent than expected, representing a relevant amount of functional corticotroph macroadenomas and invasive tumors. TP53 mutations associated with more aggressive tumor features and difficult to manage disease.

Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study.

BACKGROUND: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. METHODS: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. FINDINGS: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. INTERPRETATION: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. FUNDING: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1).

Outcome of giant pituitary tumors requiring surgery.

Objective: The management of giant pituitary tumors is complex, with few publications and recommendations. Consequently, patient's care mainly relies on clinical experience. We report here a first large series of patients with giant pituitary tumors managed by a multidisciplinary expert team, focusing on treatments and outcome. Methods: A retrospective cohort study was conducted. Giant pituitary tumors were defined by a main diameter > 40mm. Macroprolactinomas sensitive to dopamine agonists were excluded. All patients were operated by a single neurosurgical team. After surgery, multimodal management was proposed, including hormone replacement, radiotherapy and anti-tumor medical therapies. Outcome was modeled using Kaplan-Meyer representation. A logistic regression model was built to identify the risk factors associated with surgical complications. Results: 63 consecutive patients presented a giant adenoma, most often with visual defects. Patients were operated once, twice or three times in 59%, 40% and 1% of cases respectively, mainly through endoscopic endonasal approach. Giant adenomas included gonadotroph, corticotroph, somatotroph, lactotroph and mixed GH-PRL subtypes in 67%, 14%, 11%, 6% and 2% of patients respectively. Vision improved in 89% of patients with prior visual defects. Severe surgical complications occurred in 11% of patients, mainly for tumors > 50 mm requiring microscopic transcranial approach. Additional radiotherapy was needed for 29% of patients, 3 to 56 months after first surgery. For 6% of patients, Temozolomide treatment was required, 19 to 66 months after first surgery. Conclusions: Giant pituitary tumors require multimodal management, with a central role of surgery. Most often, tumor control can be achieved by expert multidisciplinary teams.

Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios.

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing's syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.