Occurrence Of Parathyroid Tumors Research Articles

9220 Machine Learning Methods In Differential Diagnosis Of Genetically Confirmed Multiple Endocrine Neoplasia Type 1 And Its Phenocopies

Abstract Disclosure: D. Trukhina: None. K. Voronov: None. E. Mamedova: None. A. Solodovnikov: None. Z. Belaya: None. Background. MEN-1 is a rare autosomal dominant disorder caused by mutations in the MEN1 gene encoding the menin protein (gMEN1). This syndrome is characterised by the occurrence of parathyroid tumours, gastroenteropancreatic neuroendocrine tumours, pituitary adenomas, and other endocrine and non-endocrine neoplasms. If a patient with the MEN-1 phenotype does not have any mutation in the MEN1 gene, the condition is considered a phenocopy of the syndrome (phMEN1). The goal of this study was to develop a machine learning algorithm to estimate the probability of gMEN-1 vs phMEN-1 based on easily available clinical features at first line differential diagnostics. Materials and methods. A single-center, one-stage, cohort, retrospective study was carried out. Patients were randomly stratified into 2 cohorts: training (80%) and test (20%). Eight machine learning algorithms were used to develop predictive models: Logistic Regression, k-nearest neighbors (kNN), Naive Bayes, binary decision tree (CART), C5.0 decision tree algorithms, Bagged CART, Random Forest, Gradient Boosting (Stochastic Gradient Boosting, GBM). Results. The study included 95 patients with genetically confirmed gMEN-1 syndrome and 60 patients with its phenocopies. As a result of preliminary data processing and selection for the most informative features, the final variables for the classification and prediction of gMEN-1 syndrome were identified: the number of affected parathyroid glands, age at diagnostics, pancreatic tumour existence, heredity, type of pituitary adenoma secretion, and gender. The kNN algorithm demonstrated the best diagnostic performance in a training sample (ROC-AUC - 0.96, sensitivity - 84%, specificity - 100%), which was confirmed in a test sample (ROC-AUC - 1.0; sensitivity - 94.4%, specificity - 100%) to determine genetically confirmed MEN-1 syndrome. Conclusion. The k-nearest neighbours (kNN) algorithm may be used as a first-line differential diagnostics method to select patients to be refered for genetic testing for gMEN-1. Presentation: 6/1/2024

7845 Machine Learning Methods In Differential Diagnosis Of Genetically Confirmed Multiple Endocrine Neoplasia Type 1 And Its Phenocopies

Abstract Disclosure: D. Trukhina: None. K. Voronov: None. E. Mamedova: None. A. Solodovnikov: None. Z. Belaya: None. Background. MEN-1 is a rare autosomal dominant disorder caused by mutations in the MEN1 gene encoding the menin protein (gMEN1). This syndrome is characterised by the occurrence of parathyroid tumours, gastroenteropancreatic neuroendocrine tumours, pituitary adenomas, and other endocrine and non-endocrine neoplasms. If a patient with the MEN-1 phenotype does not have any mutation in the MEN1 gene, the condition is considered a phenocopy of the syndrome (phMEN1).The goal of this study was to develop a machine learning algorithm to estimate the probability of gMEN-1 vs phMEN-1 based on easily available clinical features at first line differential diagnostics. Materials and methods. A single-center, one-stage, cohort, retrospective study was carried out. Patients were randomly stratified into 2 cohorts: training (80%) and test (20%). Eight machine learning algorithms were used to develop predictive models: Logistic Regression, k-nearest neighbors (kNN), Naive Bayes, binary decision tree (CART), C5.0 decision tree algorithms, Bagged CART, Random Forest, Gradient Boosting (Stochastic Gradient Boosting, GBM). Results. The study included 95 patients with genetically confirmed gMEN-1 syndrome and 60 patients with its phenocopies. As a result of preliminary data processing and selection for the most informative features, the final variables for the classification and prediction of gMEN-1 syndrome were identified: the number of affected parathyroid glands, age at diagnostics, pancreatic tumour existence, heredity, type of pituitary adenoma secretion, and gender. The kNN algorithm demonstrated the best diagnostic performance in a training sample (ROC-AUC - 0.96, sensitivity - 84%, specificity - 100%), which was confirmed in a test sample (ROC-AUC - 1.0; sensitivity - 94.4%, specificity - 100%) to determine genetically confirmed MEN-1 syndrome. Conclusion. The k-nearest neighbours (kNN) algorithm may be used as a first-line differential diagnostics method to select patients to be refered for genetic testing for gMEN-1. Presentation: 6/1/2024

Plasma miRNA expression in patients with genetically confirmed multiple endocrine neoplasia type 1 syndrome and its phenocopies

MEN-1 is a rare autosomal dominant disease caused by mutations in MEN1 gene encoding the menin protein. This syndrome is characterized by the occurrence of parathyroid tumors, gastroenteropancreatic neuroendocrine tumors, pituitary adenomas, as well as other endocrine and non-endocrine tumors. If a patient with the MEN-1 phenotype carry no mutations in the MEN1 gene, the condition considers a phenocopy of syndrome (phMEN1). The possible cause of this changes could be changes in epigenetic regulation, particularly in microRNA expression that might affect menin signaling pathways. to identify differently expressed circulating miRNAs in plasma in patients with genetically confirmed MEN-1 syndrome, its phenocopies and healthy controls. single-center, case-control study was conducted. We assessed plasma microRNA expression in patients with genetically confirmed MEN-1 (gMEN1), phMEN1 and healthy controls. Morning plasma samples were collected from fasting patients and stored at -80°C. Total RNA isolation was performed using miRNeasy Mini Kit with QIAcube. Thelibraries were prepared by the QIAseq miRNA Library Kit following the manufacturer. Circulating miRNA sequencing was done on Illumina NextSeq 500 (Illumina). Subsequent data processing was performed using the DESeq2 bioinformatics algorithm. we enrolled 21 consecutive patients with gMEN1 and 11 patients with phMEN1, along with 12 gender matched controls. Median age of gMEN1 was 38,0 [34,0; 41,0]; in phMEN1 - 59,0 [51,0; 60,0]; control - 59,5 [51,5; 62,5]. The gMEN1 group differed in age (p<0.01) but not gender (р=0.739) or BMI (р=0.116) compared to phMEN1 and controls group, the last two groups did not differ by these parameters (p>0.05). 25 microRNA were differently expressed in groups gMEN1 and phMEN1 (21 upregulated microRNAs, 4 - downregulated). Comparison of samples from the phMEN-1 group and relatively healthy controls revealed 10 differently expressed microRNAs: 5 - upregulated; 5 - downregulated. In the gMEN-1 and control groups, 26 differently expressed microRNAs were found: 24 - upregulated; 2 - downregulated. The miRNAs most differing in expression among the groups were selected for further validation by RT-qPCR (in the groups of gMEN1 vs phMEN1 - miR-3613-5p, miR-335-5p, miR-32-5p, miR-425-3p, miR-25-5p, miR-576-5p, miR-215-5p, miR-30a-3p, miR-141-3p, miR-760, miR-501-3p; gMEN1 vs control - miR-1976, miR-144-5p miR-532-3p, miR-375; as well as in phMEN1 vs control - miR-944, miR-191-5p, miR-98-5p). In a pilot study, we detected microRNAs that may be expressed differently between patients with gMEN-1 and phMEN-1. The results need to be validated using different measurement method with larger sample size.

THU081 Differences In Circulating Microrna Levels In Genetically Confirmed Multiple Endocrine Neoplasia Type 1 And Multiple Endocrine Neoplasia Type 1 Phenocopies As Assessed By Next Generation Sequencing

Abstract Disclosure: D.A. Trukhina: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). E.O. Mamedova: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). P.A. Koshkin: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). A.G. Nikitin: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). G.A. Melnichenko: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). Z.E. Belaya: Grant Recipient; Self; Russian Science Foundation (project N 19-15-00398-П). Multiple endocrine neoplasia type 1 (MEN1) is a rare disease caused by mutations in the MEN1 gene encoding the menin protein (gMEN1). This syndrome is characterized by the occurrence of parathyroid tumors, gastroenteropancreatic neuroendocrine tumors (GEP-NETs), pituitary adenomas, as well as other endocrine and non-endocrine tumors. Patients with MEN1 phenotype without MEN1 mutations are considered MEN1 phenocopies (phMEN1). It has not been studied whether the development of MEN1 phenocopies is determined by epigenetic changes, particularly by altered microRNA expression, which can affect menin. Materials & methods Single-center, case-control study: assessment of plasma microRNA expression in patients with gMEN1, phMEN1 and healthy controls. Morning plasma samples were collected from fasting patients and gender-matched controls and stored at –80C. Total RNA isolation was performed using miRNeasy Mini Kit with QIAcube. The libraries were prepared by the QIAseq miRNA Library Kit. Circulating miRNA sequencing was performed on Illumina NextSeq 500. Subsequent data processing was performed using DESeq2 bioinformatics algorithm. Results We enrolled 24 patients with gMEN1 and 12 patients with phMEN1, along with 12 gender-matched controls. The median age of gMEN1 patients was 39 [35; 46]; in phMEN1 — 59 [51;60]; control — 59 [51.5; 62.5]. The gMEN1 group differed in age (p<0,01) compared to phMEN1 and control groups. We divided all assessed microRNAs into 3 groups based on the significance of the results: the first group consisted of samples with the highest level of detected microRNAs (>50 counts), the second group — moderate (10–50), the third group — the lowest (<10).98 microRNAs were differently expressed in groups gMEN1 and phMEN1 (84 upregulated microRNAs, 14 — downregulated). We found increased expression of microRNAs in gMEN1 which interact with menin: hsa-miR-421 (p adj = 0.0004362), hsa-miR-664a-5p (p adj = 0.0037814). We found several microRNAs associated with intestinal and pituitary tumors in gMEN1 and phMEN1 groups: up-regulated hsa-miR-7-5p (p adj = 0.0000084); downregulated hsa-miR-423-5p (p adj < 0.000001) and hsa-miR-432-5p (p adj = 0.0087227). 84 microRNA were differently expressed in groups gMEN1 and control (67 up-regulated microRNAs, 17 — downregulated). When comparing gMEN1 with phMEN1 and control a decrease in hsa-let-7a-5p miRNA was found, which, according to the literature, is downregulated in Men1 gene knockout cell lines. The phMEN1 vs control group showed downregulation of hsa-miR-122-5p (p adj = 0.0080138) and upregulation of hsa-miR-191-5p (p adj = 0.0002144), hsa-miR-486-5p (p adj = 0.0491822) that has been detected in GEP-NETs. Conclusion We found microRNAs which could potentially become biomarkers in the differential diagnosis of gMEN1 and phMEN1. The results need to be validated using a different measurement method with a larger sample size. Presentation: Thursday, June 15, 2023

The role of non-coding RNAs in the pathogenesis of multiple endocrine neoplasia syndrome type 1

Changes in the expression of non-coding ribonucleic acids (ncRNAs) take part in the formation of various tumors. Multiple endocrine neoplasia syndrome type 1 (MEN1) is a rare autosomal dominant disease caused by mutations of the MEN1 gene encoding the menin protein. This syndrome is characterized by the occurrence of parathyroid tumors, gastroenteropancreatic neuroendocrine tumors, pituitary adenomas, as well as other endocrine and non-endocrine tumors. The pathogenesis of MEN-1 associated tumors due to MEN1 mutations remains unclear. In the absence of mutations of the MEN1 gene in patients with phenotypically similar features, this condition is regarded as a phenocopy of this syndrome. The cause of the combination of several MEN-1-related tumors in these patients remains unknown. The possible cause is that changes in the expression of ncRNAs affect the regulation of signaling pathways in which menin participates and may contribute to the development of MEN-1-related tumors. The identification of even a small number of agents interacting with menin makes a significant contribution to the improvement of knowledge about its pathophysiological influence and ways of developing tumors within the MEN-1 syndrome and its phenocopies.

A MEN1 pancreatic neuroendocrine tumour mouse model under temporal control.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterised by occurrence of parathyroid tumours and neuroendocrine tumours (NETs) of the pancreatic islets and anterior pituitary. The MEN1 gene, encoding menin, is a tumour suppressor, but its precise role in initiating in vivo tumourigenesis remains to be elucidated. The availability of a temporally controlled conditional MEN1 mouse model would greatly facilitate the study of such early tumourigenic events, and overcome the limitations of other MEN1 knockout models, in which menin is lost from conception or tumour development occurs asynchronously. To generate a temporally controlled conditional mouse model, we crossbred mice with the MEN1 gene floxed by LoxP sites (Men1L/L), and mice expressing tamoxifen-inducible Cre recombinase under the control of the rat insulin promoter (RIP2-CreER), to establish a pancreatic β-cell-specific NET model under temporal control (Men1L/L/RIP2-CreER). Men1L/L/RIP2-CreER mice aged ~3 months were given tamoxifen in the diet for 5 days, and pancreata harvested 2–2.5, 2.9–3.5 and 4.5–5.5 months later. Control mice did not express Cre and did not receive tamoxifen. Immunostaining of pancreata from tamoxifen-treated Men1L/L/RIP2-CreER mice, compared to control mice, showed at all ages: loss of menin in all islets; increased islet area (>4.2-fold); increased proliferation of insulin immunostaining β-cells (>2.3-fold) and decreased proliferation of glucagon immunostaining α-cells (>1.7-fold). There were no gender and apoptotic or proliferation differences, and extra-pancreatic tumours were not detected. Thus, we have established a mouse model (Men1L/L/RIP2-CreER) to study early events in the development of pancreatic β-cell NETs.

Mice deleted for cell division cycle 73 gene develop parathyroid and uterine tumours: model for the hyperparathyroidism-jaw tumour syndrome

The hyperparathyroidism-jaw tumour (HPT-JT) syndrome is an autosomal dominant disorder characterized by occurrence of parathyroid tumours, often atypical adenomas and carcinomas, ossifying jaw fibromas, renal tumours and uterine benign and malignant neoplasms. HPT-JT is caused by mutations of the cell division cycle 73 (CDC73) gene, located on chromosome 1q31.2 and encodes a 531 amino acid protein, parafibromin. To facilitate in vivo studies of Cdc73 in tumourigenesis we generated conventional (Cdc73+/−) and conditional parathyroid-specific (Cdc73+/L/PTH-Cre and Cdc73L/L/PTH-Cre) mouse models. Mice were aged to 18-21 months and studied for survival, tumour development and proliferation, and serum biochemistry, and compared to age-matched wild-type (Cdc73+/+ and Cdc73+/+/PTH-Cre) littermates. Survival of Cdc73+/− mice, when compared to Cdc73+/+ mice was reduced (Cdc73+/−=80%; Cdc73+/+=90% at 18 months of age, P<0.05). Cdc73+/−, Cdc73+/L/PTH-Cre and Cdc73L/L/PTH-Cre mice developed parathyroid tumours, which had nuclear pleomorphism, fibrous septation and increased galectin-3 expression, consistent with atypical parathyroid adenomas, from 9 months of age. Parathyroid tumours in Cdc73+/−, Cdc73+/L/PTH-Cre and Cdc73L/L/PTH-Cre mice had significantly increased proliferation, with rates >fourfold higher than that in parathyroid glands of wild-type littermates (P<0.0001). Cdc73+/−, Cdc73+/L/PTH-Cre and Cdc73L/L/PTH-Cre mice had higher mean serum calcium concentrations than wild-type littermates, and Cdc73+/− mice also had increased mean serum parathyroid hormone (PTH) concentrations. Parathyroid tumour development, and elevations in serum calcium and PTH, were similar in males and females. Cdc73+/− mice did not develop bone or renal tumours but female Cdc73+/− mice, at 18 months of age, had uterine neoplasms comprising squamous metaplasia, adenofibroma and adenomyoma. Uterine neoplasms, myometria and jaw bones of Cdc73+/− mice had increased proliferation rates that were 2-fold higher than in Cdc73+/+ mice (P<0.05). Thus, our studies, which have established mouse models for parathyroid tumours and uterine neoplasms that develop in the HPT-JT syndrome, provide in vivo models for future studies of these tumours.

HYPERPARATHYROIDISM - JAW TUMOUR: A CASE REPORT

The hyperparathyroidism-jaw tumor (HPT-JT) syndrome is an autosomal dominant disorder characterized by the occurrence of parathyroid tumors and ossifying jaw fibromas. Hyperparathyroidism is due to increased activity of the parathyroid glands, either from an intrinsic abnormal change altering excretion of parathyroid hormone (primary or tertiary hyperparathyroidism) or from an extrinsic abnormal change affecting calcium homoeostasis stimulating production of parathyroid hormone (secondary hyperparathyroidism). Primary hyperparathyroidism is the third most common endocrine disorder, with the highest incidence in postmenopausal women. Here we present an intresting case of hyperparathyroidism - jaw tumour where the patient had reduced serum calcium and serum alkaline phosphate level.

Cell division cycle protein 73 homolog (CDC73) mutations in the hyperparathyroidism-jaw tumor syndrome (HPT-JT) and parathyroid tumors

The hyperparathyroidism-jaw tumor (HPT-JT) syndrome is an autosomal dominant disorder characterized by the occurrence of parathyroid tumors in association with ossifying fibromas of the maxilla and/or mandible. The gene responsible for HPT-JT, known as CDC73, was identified in 2002 and encodes a 531 amino acid protein known as parafibromin. Parafibromin is predominantly a nuclear protein that interacts directly with beta-catenin and also forms part of the RNA polymerase associated factor-1 complex (Paf1C) that regulates transcription. Heterozygous germline CDC73 mutations are detected in the majority of patients with HPT-JT, and the demonstration of loss of heterozygosity (LOH) at the CDC73 locus in tumors from affected individuals is consistent with a tumor suppressor role. Somatic CDC73 mutations are a frequent finding in nonfamilial (i.e., sporadic) parathyroid carcinomas and have also been reported in benign sporadic parathyroid tumors as well as sporadic renal and fibro-osseous jaw tumors. To date, 111 independent CDC73 mutations have been identified (68 germline; 38 somatic; 5 undefined), and these occur throughout the coding region and splice sites of the CDC73 gene, with the majority (>80%) predicting premature truncation of the parafibromin protein. These CDC73 mutations, together with their clinical and biological relevance, are reviewed.

Hyperparathyroidism-jaw tumor syndrome in Roma families from Portugal is due to a founder mutation of the HRPT2 gene.

The hyperparathyroidism-jaw tumor (HPT-JT) syndrome is an autosomal dominant disorder characterized by the occurrence of parathyroid tumors and ossifying jaw fibromas. The gene causing HPT-JT, HRPT2, is located on chromosome 1q31.2 and consists of 17 exons that encode a 531-amino acid protein, designated parafibromin. We recently identified six Roma families in Portugal with 56 members (11 affected and 45 asymptomatic), who had the HPT-JT syndrome. We postulated that they may have a common ancestor and that the HPT-JT syndrome may be due to a mutation of the HRPT2 gene. Haplotype analysis using 14 chromosome 1q24-q32 polymorphic markers showed that the 11 affected individuals shared a common haplotype defined by seven markers that spanned an approximately 12.5-cM region, flanked centromerically by D1S202 and telomerically by D1S306. DNA sequence analysis identified a 2-bp (TG or GT) frameshift deletion in exon 8, which predicts a truncated parafibromin protein, in all 11 affected individuals. This mutation was also found in 19 unaffected individuals (age range, 12-74 yr) who shared the affected haplotype, suggesting a low age-related penetrance for HPT-JT in these families. Thus, the HPT-JT syndrome in six Roma families from Portugal is due to a novel founder mutation in the HRPT2 gene.

The hyperparathyroidism-jaw tumour syndrome in a Portuguese kindred

The hyperparathyroidism-jaw tumour (HPT-JT) syndrome is an autosomal dominant disease characterized by the occurrence of parathyroid tumours and fibro-osseous tumours of the jaw bones. Some HPT-JT patients may also develop renal abnormalities, which include Wilms' tumours, hamartomas and polycystic disease. The HPT-JT gene has been mapped to chromosome 1q25-q31, and we report the clinical and genetic findings in a kindred from central Portugal. HPT-JT was observed in six members from three generations; all had primary hyperparathyroidism (five had parathyroid adenomas, one a parathyroid carcinoma). Ossifying jaw fibromas affecting the maxilla and/or mandible were observed in 5/6. Renal cysts (<2.5 cm) were observed in four. Genetic studies using 18 polymorphic loci from chromosome 1q25-q31, together with leukocyte DNA from 11 family members and tumour DNA from three parathyroids (two adenomas and one carcinoma), revealed loss of tumour heterozygosity in the parathyroid carcinoma only, and the retained haplotype was found to cosegregate with the disease in the six affected members. A new Portuguese kindred with the HPT-JT syndrome that maps to chromosome 1q25-q31 has been identified, and these findings will help in the further characterization of this inherited disorder.