Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators.

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

Molecular, functional, and histopathological classification of the pituitary neuroendocrine neoplasms.

In 2017, WHO published an updated classification of the pituitary adenomas according to the lineages defined by the transcription factors, PIT1, SF1 and TPIT. Nomenclature of the pituitary tumors follows the mature cell types such as somatotroph (GH), lactotroph (LH), thyrotroph, corticotroph, and gonadotroph (FSH, LH). Null cell adenomas are defined by the absence of expression of any hormones and transcription factors. Not infrequently, the pituitary adenomas are invasive to the adjacent structures and are designated as aggressive adenomas. Knosp grading is often used to define the aggressiveness of the tumor. Sparsely granulated somatotroph adenomas and Crooke cell corticotroph adenomas are representative aggressive adenomas. Recently, genomics regarding various adenomas have been clarified, such as GNAS for somatotrophs and USP8 for corticotrophs. Familial pituitary adenomas are another aspect which has been clarified such as MEN1, Carney's complex, familial isolated pituitary adenoma and McCune-Albright syndrome. The pituitary adenomas often produce GH or PRL, hormones of PIT1 transcription factor. It has been agreed that the pituitary adenomas share the characteristics of neuroendocrine neoplasms. The terminology of pituitary neuroendocrine tumor has been discussed. This review article covers various aspects of pituitary adenomas.

Comparison of Survival and Patterns of Recurrence in Gastric Neuroendocrine Carcinoma, Mixed Adenoneuroendocrine Carcinoma, and Adenocarcinoma.

Importance: Gastric neuroendocrine carcinoma and mixed adenoneuroendocrine carcinoma are rare pathological types of gastric cancer, and there is a lack of multicenter studies comparing the prognosis and recurrence patterns of gastric neuroendocrine carcinoma, gastric mixed adenoneuroendocrine carcinoma, and gastric adenocarcinoma. Objective: To compare the differences in long-term survival and patterns of recurrence among gastric neuroendocrine carcinoma, gastric mixed adenoneuroendocrine carcinoma, and gastric adenocarcinoma. Design, Setting, and Participants: This cohort study included patients with resectable gastric neuroendocrine carcinoma and gastric mixed adenoneuroendocrine carcinoma at 23 hospitals in China from January 2006 to December 2016. In addition, patients with gastric adenocarcinoma were selected as controls. Propensity score-matched analysis was used to match pathological stage among the different pathological types, and disease-free survival (DFS), postrecurrence survival (PRS), and patterns of recurrence were examined. Data analysis was conducted from July 15, 2020, to October 21, 2020. Exposures: Curative resection for gastric neuroendocrine carcinoma, gastric mixed adenoneuroendocrine carcinoma, and gastric adenocarcinoma. Main Outcomes and Measures: The main outcomes were DFS and patterns of recurrence. Results: A total of 3689 patients were analyzed (median [interquartile range] age, 62 [55-69] years; 2748 [74.5%] men), including 503 patients (13.6%) with gastric neuroendocrine carcinoma, 401 patients (10.9%) with gastric mixed adenoneuroendocrine carcinoma, and 2785 patients (75.5%) with gastric adenocarcinoma. After propensity score matching, 5-year DFS was 47.6% (95% CI, 42.7%-52.5%) for patients with gastric neuroendocrine carcinoma, compared with 57.6% (95% CI, 55.1%-60.1%) with gastric adenocarcinoma (P < .001) and 51.1% (95% CI, 46.0%-56.2%) for patients with gastric mixed adenoneuroendocrine carcinoma, compared with 57.8% (95% CI, 55.1%-60.5%) patients with gastric adenocarcinoma (P = .02). Multivariable analyses found that, compared with gastric adenocarcinoma, gastric neuroendocrine carcinoma (hazard ratio [HR], 1.64; 95% CI, 1.40-1.93) and gastric mixed adenoneuroendocrine carcinoma (HR, 1.25; 95% CI, 1.05-1.49) were independent risk factors associated with worse DFS. Compared with matched patients with gastric adenocarcinoma, patients with gastric neuroendocrine carcinoma were more likely to have distant recurrence (268 patients [17.2%] vs 101 patients [23.7%]; P = .002), as were patients with gastric mixed adenoneuroendocrine carcinoma (232 patients [17.3%] vs 76 patients [22.8%]; P = .02). In multivariate analysis, gastric neuroendocrine carcinoma (HR, 2.22; 95% CI, 1.66-2.98) and gastric mixed adenoneuroendocrine carcinoma (HR, 1.70; 95% CI, 1.24-2.34) were independent risk factors associated with distant recurrence. Additionally, T3 to T4 stage (odds ratio, 2.84; 95% CI, 1.57-5.14; P = .001) and lymph node metastasis (odds ratio, 2.01; 95% CI, 1.31-3.10; P = .002) were independent risk factors associated with distant recurrence of gastric neuroendocrine carcinoma and gastric mixed adenoneuroendocrine carcinoma. Conclusions and Relevance: This cohort study found that patients with gastric neuroendocrine carcinoma or gastric mixed adenoneuroendocrine carcinoma had worse prognoses and were more prone to distant recurrence than those with gastric adenocarcinoma. Thus, different follow-up and treatment strategies should be developed to improve the long-term survival of patients with gastric neuroendocrine carcinoma or gastric mixed adenoneuroendocrine carcinoma, especially patients with tumors penetrating into the subserosa or deeper layers or with lymph node metastasis.

Systemic Treatment of Gastroenteropancreatic Neuroendocrine Carcinoma.

OPINION STATEMENT: Treatment recommendations for advanced gastroenteropancreatic neuroendocrine carcinomas (GEP-NEC) are based on uncontrolled, mainly retrospective data. Chemotherapy can offer palliative relief, but long-lasting complete responses or cures are rare. The European Neuroendocrine Tumour Society (ENETS) and European Society for Medical Oncology (ESMO) recommend platinum-based chemotherapy as first-line treatment. This has been the golden standard since the late 1980s and has been evaluated in mostly retrospective clinical studies. However, progression is inevitable for most patients. Unfortunately, data on effective second-line treatment options are scant, and ENETS and ESMO recommendations propose fluorouracil- or temozolomide-based chemotherapy schedules. As such, there is a huge unmet need for improved care. Improved knowledge on GEP-NEC biology may provide a pathway towards more effective interventions including chemotherapy, targeted gene therapy, peptide receptor radionuclide therapy, as well as immune checkpoint inhibitors. The review summarises this current state of the art as well as the most promising developments for systemic therapy in GEP-NEC patients.

Recent advances and conceptual changes in the classification of neuroendocrine tumors of the thymus.

Neuroendocrine tumors of the thymus (TNET) are exceedingly rare neoplasms. Their histomorphology is identical to neuroendocrine tumors elsewhere in the body (in particular the lungs) and bears no similarity with thymomas and thymic carcinomas. Recent molecular findings have profoundly changed our perception of these tumors and may impact future histological classification systems.

The 3-Dimensional-Computed Tomography Texture Is Useful to Predict Pancreatic Neuroendocrine Tumor Grading.

OBJECTIVES: The aim of this study is to evaluate the computed tomography texture parameters in predicting grading. METHODS: This study analyzed 68 nonfunctioning pancreatic neuroendocrine neoplasms (Pan-NENs). Clinical and radiological parameters were studied. Four model models were built, including clinical and standard radiologic parameters (model 1), first- and second-order computed tomography features (models 2 and 3), all parameters (model 4). The diagnostic accuracy was reported as area under the curve. A score was computed using the best model and validated to predict progression-free survival. RESULTS: The size of tumors and heterogeneous enhancement were related to the risk of "non-G1" Pan-NENs (coefficients 0.471, P = 0.012, and 1.508, P = 0.027). Four second-order parameters were significantly related to the presence of "non-G1" Pan-NENs: the gray level co-occurrence matrix correlation (6.771; P = 0.011), gray level co-occurrence matrix contrast variance (0.349; P = 0.009), the neighborhood gray-level different matrix contrast (-63.129; P = 0.001), and the gray-level zone length matrix with the low gray-level zone emphasis (-0.151; P = 0.049). Model 4 was the best, with a higher area under the curve (0.912; P = 0.005). The score obtained predicted the progression-free survival. CONCLUSIONS: Computed tomography radiomics signature can be useful in preoperative workup.

Clinical implications of lung neuroendocrine neoplasm classification.

INTRODUCTION: Neuroendocrine neoplasms of the lung (Lung NENs) encompass NE tumors (NETs), which are in turn split into typical and atypical carcinoids, and NE carcinomas (NECs), which group together small-cell carcinoma and large-cell NE carcinoma. This classification is the current basis for orienting the daily practice of these patients, with diagnostic, prognostic, and predictive inferences. AREAS COVERED: The clinical implications of lung NEN classification are addressed according to three converging perspectives, which were dissected through an extensive literature overview: (1) how to put intratumor heterogeneity into the context of the current classification; (2) how to contextualize immunohistochemistry markers to improve diagnosis, prognosis, and therapy prediction; and (3) how to use immuno-oncology strategies for life-threatening NECs, which still account for 90% or more of lung NENs. EXPERT OPINION: We provide practical insights to account for intratumor heterogeneity, practice the choice of immunohistochemistry markers, and emphasize once again the added value of immuno-oncology in the setting of personalized medicine of lung NENs.

Atypical course of typical lung carcinoid.

Carcinoids have been classified according to their embryonic origin in the past and are now categorized and classified as neuroendocrine tumors, including low malignant typical carcinoids, moderate malignant atypical carcinoids, and highly malignant large cell neuroendocrine and small cell carcinomas. A typical carcinoid is a previously used term for the current designation of a grade I neuroendocrine tumor, well differentiated, belonging to a group of rare tumors with a good prognosis with metastasis of less than 15% with a five-year survival of more than 90%, rarely producing serotonin. Even this bio-logically favorable tumor with a relatively low degree of metastasis cannot be underestimated. Case: The following section summarizes the classification of neuroendocrine tumors, their dia-gnosis and treatment, and the second section presents a specific case of a patient with multiple metastases of an original lung carcinoid (histology at the time of surgery 2012, at the time of using this older version of neuroendocrine tumors) describing its further treatment. Conclusion: In well differentiated neuroendocrine tumors, there is a significant risk of metastasis despite their radical surgery; their dispensarization is therefore necessary. The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.

Pancreatic neuroendocrine carcinoma G3 may be heterogeneous and could be classified into two distinct groups.

BACKGROUND/OBJECTIVES: Pancreatic neuroendocrine carcinoma (PanNEC)-G3 often presents along with genetic abnormalities such as KRAS, RB1, and TP53 mutations. However, the association between these genetic findings and response to chemotherapy and prognosis has not been clarified. This study aimed to clarify the clinicopathological features of PanNEC-G3. METHODS: We performed a subgroup analysis of the Japanese PanNEN-G3 study (multicenter, retrospective study), which revealed that Rb loss and KRAS mutation were predictors of the response to platinum-based regimen in PanNEN-G3. We re-classified WHO grades of PanNENs using the 2017 WHO classification and then analyzed the clinicopathological features and prognostic factors in 49 patients with PanNEC-G3. RESULTS: The rates of Rb loss and KRAS mutation in PanNEC-G3 were 54.5% and 48.7%, respectively. Patients with Rb loss and/or KRAS mutation showed a higher response rate to first-line platinum-based regimen than those without Rb loss or KRAS mutation (object response rate 70.0% vs 33.3%, odds ratio 9.22; 95% CI 1.26-67.3, P = 0.029), but tended to have shorter overall survival rates than those without Rb loss or KRAS mutation (median 239 vs 473 days, hazard ratio 2.11; 95% CI 0.92-4.86, P = 0.077). CONCLUSIONS: Patients with PanNEC-G3 have varied clinical outcomes for platinum-based regimen. When grouped based on Rb loss and KRAS mutation, there seemed to be two groups with distinct prognoses and responses to the platinum-based regimen. PanNEC-G3 could, therefore, be classified into two distinct groups based on immunohistochemical and genetic findings.

Ensemble Deep Learning Model for Multicenter Classification of Thyroid Nodules on Ultrasound Images.

BACKGROUND Thyroid nodules are extremely common and typically diagnosed with ultrasound whether benign or malignant. Imaging diagnosis assisted by Artificial Intelligence has attracted much attention in recent years. The aim of our study was to build an ensemble deep learning classification model to accurately differentiate benign and malignant thyroid nodules. MATERIAL AND METHODS Based on current advanced methods of image segmentation and classification algorithms, we proposed an ensemble deep learning classification model for thyroid nodules (EDLC-TN) after precise localization. We compared diagnostic performance with four other state-of-the-art deep learning algorithms and three ultrasound radiologists according to ACR TI-RADS criteria. Finally, we demonstrated the general applicability of EDLC-TN for diagnosing thyroid cancer using ultrasound images from multi medical centers. RESULTS The method proposed in this paper has been trained and tested on a thyroid ultrasound image dataset containing 26 541 images and the accuracy of this method could reach 98.51%. EDLC-TN demonstrated the highest value for area under the curve, sensitivity, specificity, and accuracy among five state-of-the-art algorithms. Combining EDLC-TN with models and radiologists could improve diagnostic accuracy. EDLC-TN achieved excellent diagnostic performance when applied to ultrasound images from another independent hospital. CONCLUSIONS Based on ensemble deep learning, the proposed approach in this paper is superior to other similar existing methods of thyroid classification, as well as ultrasound radiologists. Moreover, our network represents a generalized platform that potentially can be applied to medical images from multiple medical centers.

Immunohistochemistry in the diagnosis and classification of neuroendocrine neoplasms: what can brown do for you?

This review is based on a presentation given at the Hans Popper Hepatopathology Society companion meeting at the 2019 United States and Canadian Academy of Pathology Annual Meeting. It presents updates on the diagnosis and classification of neuroendocrine neoplasms, with an emphasis on the role of immunohistochemistry. Neuroendocrine neoplasms often present in liver biopsies as metastases of occult origin. Specific topics covered include 1. general features of neuroendocrine neoplasms, 2. general neuroendocrine marker immunohistochemistry, with discussion of the emerging marker INSM1, 3. non-small cell carcinoma with (occult) neuroendocrine differentiation, 4. the WHO Classification of neuroendocrine neoplasms, with discussion of the 2019 classification of gastroenteropancreatic neoplasms, 5. use of Ki-67 immunohistochemistry, 6. immunohistochemistry to assign site of origin in neuroendocrine metastasis of occult origin, 7. immunohistochemistry to distinguish well-differentiated neuroendocrine tumor G3 from poorly differentiated neuroendocrine carcinoma, 8. lesions frequently misdiagnosed as well-differentiated neuroendocrine tumor, and 9. required and recommended data elements for biopsies and resections with associated immunohistochemical stains. Next-generation immunohistochemistry, including lineage-restricted transcription factors (e.g., CDX2, islet 1, OTP, SATB2) and protein correlates of molecular genetic events (e.g., p53, Rb), is indispensable for the accurate diagnosis and classification of these neoplasms.

[Mixed Neuroendocrine-non-neuroendocrine Neoplasm of the Stomach that is Distributed in Depth on the Same Tumor: Inconsistent with the Definition of Mixed Adenoneuroendocrine Carcinoma in the 2010 World Health Organization Classification of Tumors of the Digestive System].

A mixed adenoneuroendocrine carcinoma (MANEC) of the stomach is a rare disease entity that was first defined by the World Health Organization (WHO) classification (2010) for tumors of the digestive system. According to the WHO classification (2010), MANEC is referred to as a tumor with both neuroendocrine and non-neuroendocrine neoplasms; each component of the tumor should be at least 30%. On the other hand, this cut-off value lacks clinical evidence and does not explain the characteristics and heterogeneity of this tumor. A 66-year-old male diagnosed with early gastric cancer (EGC) at a community hospital was referred to the Kosin University Gospel Hospital for further evaluation of gastric cancer. Esophagogastroduodenoscopy and EUS performed at the Kosin University Gospel Hospital revealed a sub-mucosal tumor-like component. In addition, a re-biopsy revealed a neuroendorine tumor at different depths of the same tumor. The final pathologic-diagnosis through surgery revealed a mixed neuroendocrine- non-neuroendocrine neoplasm, which is inconsistent with the definition of MANEC. Clinicians should consider EUS when a tumor has atypical endoscopic findings, even if EGC has already been diagnosed.

Update on Neuroendocrine Carcinomas of the Larynx.

OBJECTIVES: Laryngeal neuroendocrine carcinomas are heterogeneous neoplasms characterized by neuroendocrine differentiation. Their prognoses are dependent on tumor type, therefore different classifications have been developed. Moreover, other tumors have overlapping pathologic features posing a range of diagnostic possibilities. METHODS: A review of the literature was performed to comprehensively understand the classification and diagnosis of these tumors. RESULTS: We review the past and present classification systems, with emphasis to the latest 2017 World Health Organization Classification of Head and Neck Tumors. We highlight salient clinicopathologic features and discuss the presumptive etiologic role of human papilloma virus. We share a practical algorithmic approach to the diagnosis of suspected neuroendocrine neoplasms of the larynx including a novel marker for neuroendocrine differentiation, insulinoma-associated protein 1. CONCLUSIONS: Accurate diagnosis and grading of laryngeal neuroendocrine carcinomas is critical for prognostication and therapeutic decision making. The use of an algorithm is instrumental in assuring the exclusion of mimickers.

UV Signature Mutations Reclassify Salivary High-grade Neuroendocrine Carcinomas as Occult Metastatic Cutaneous Merkel Cell Carcinomas.

Salivary high-grade neuroendocrine carcinomas (NECs) are rare, occur predominantly in the parotid gland, and are difficult to differentiate from metastatic cutaneous Merkel cell carcinomas (MCCs), which have overlapping morphologic, immunophenotypic, and molecular profiles. Oncogenic Merkel cell polyomavirus (MCPyV), found in 70% to 80% of MCCs, has also been reported in a few salivary NECs, but this is controversial. A promising biomarker to distinguish the 2 tumor types are UV signature mutations. UV signature mutations indicate a sun damage-induced mechanism of pathogenesis and recently have been found to be highly prevalent in MCPyV-negative MCCs but would be inconsistent with salivary origin. Here, we examine UV signature mutations as a molecular marker to distinguish primary salivary high-grade NEC from MCC. Whole exome DNA sequencing was performed on matched tumor-normal tissue from 4 MCPyV-negative high-grade salivary NECs with no other primary source identified, as well as 3 melanomas and 3 lung NECs as positive and negative controls, respectively. UV signature mutations were found in all salivary NECs, when defined as ≥60% of total mutations being C-to-T transitions at dipyrimidine sites, and when compared with known human cancer-related mutational signatures. The presence of UV signature mutations in salivary high-grade NECs strongly favors these to be occult metastatic MCCs. True salivary primary NECs are likely exceedingly rare. When a high-grade NEC is encountered in the salivary gland, the presence of UV signature mutations or MCPyV may be useful to exclude occult unknown primary MCC.

[Diagnosis of lung biopsy employing the 2015 WHO criteria and detection of related oncogenic driver mutations].

Objective: The diagnostic criteria of lung biopsy specimens by 2015 WHO lung tumor classification were used to evaluate lung biopsy specimens along with detection of genetic alterations of major tumor driving genes including epidermal growth factor receptor (EGFR). Methods: The clinical data, histological slides, immunohistochemical stains and special stains of 806 lung biopsy specimens at Beijing Hospital from July 2015 to July 2018 were retrospectively analyzed. Diagnosis of lung cancer was reclassified according to the 2015 WHO lung tumor classification and related gene mutation data were analyzed. Results: During a three-year period, the total number of lung cancer diagnosis was 483 cases, including 221 female and 262 male patients with age ranging from 37 to 85 years (median age of 65 years). There were 40 cases(8.28%) of small cell carcinoma,11 cases (2.28%) of large cell neuroendocrine carcinoma, 3 cases (0.62%) of combined neuroendocrine carcinoma, 2 cases(0.41%) of atypical carcinoid, 208 cases (43.06%) of adenocarcinoma, 92 cases(19.05%) of non-small cell carcinoma, favor adenocarcinoma, 66 cases (13.66%) of squamous cell carcinoma, 42 cases(8.70%) of non-small cell carcinoma, favor squamous cell carcinoma, 16 cases(3.31%) of non-small cell carcinoma, not otherwise specified, and 3 cases (0.62%) of non-small cell carcinoma, possible adenosquamous carcinoma. Among 202 cases tested, 107 cases (52.97%) showed EGFR mutations, including 86 of 133 cases (64.66%) of adenocarcinoma and 18 of 52 cases (34.62%) of non-small cell carcinoma, favor adenocarcinoma. Twenty two cases were found to have T790M mutation among 27 patients after EGFR TKI targeted drug therapy. Immunohistochemical staining of ALK (D5F3) was positive in 3 of 354 cases of non-small cell lung cancer, confirmed by EML4-ALK fusion gene fluorescence PCR. ROS1 gene fusion was found in 1 of 38 cases. Splicing mutations in exon 14 of MET gene were seen in one case of non-small cell carcinoma with spindle cell differentiation. Conclusion: The new diagnostic criteria by the 2015 WHO lung tumor classification is better suited for diagnosing lung biopsy specimens and providing accurate treatment guidance and improving the patient outcome.

A functional gene expression analysis in epithelial sinonasal cancer: Biology and clinical relevance behind three histological subtypes.

Epithelial sinonasal cancers (SNCs) are rare diseases with overlapping morphological features and a dismal prognosis. We aimed to investigate the expression differences among the histological subtypes for discerning their molecular characteristics. We selected 47 SNCs: (i) 21 nonkeratinizing squamous cell carcinomas (NKSCCs), (ii) 13 sinonasal neuroendocrine cancers (SNECs), and (iii) 13 sinonasal undifferentiated cancers (SNUCs). Gene expression profiling was performed by DASL (cDNA-mediated annealing, selection, extension, and ligation) microarray analysis with internal validation by quantitative RT-PCR (RT-qPCR). Relevant molecular patterns were uncovered by sparse partial-least squares discriminant analysis (sPLS-DA), microenvironment cell type (xCell), CIBERSORT, and gene set enrichment (GSEA) analyses. The first two sPLS-DA components stratified samples by histological subtypes. xCell highlighted increased expression of immune components (CD8+ effector memory cells, in SNUC) and "other cells": keratinocytes and neurons in NKSCC and SNEC, respectively. Pathway enrichment was observed in NKSCC (six gene sets, proliferation related), SNEC (one gene set, pancreatic ß-cells), and SNUC (twenty gene sets, some of them immune-system related). Major neuroendocrine involvement was observed in all the SNEC samples. Our high-throughput analysis revealed a good diagnostic ability to differentiate NKSCC, SNEC, and SNUC, but indicated that the neuroendocrine pathway, typical and pathognomonic of SNEC is also present at lower expression levels in the other two histological subtypes. The different and specific profiles may be exploited for elucidating their biology and could help to identify prognostic and therapeutic opportunities.

Distinct genome-wide methylation patterns in sporadic and hereditary nonfunctioning pancreatic neuroendocrine tumors.

BACKGROUND: Aberrant methylation is a known cause of cancer initiation and/or progression. There are scant data on the genome-wide methylation pattern of nonfunctioning pancreatic neuroendocrine tumors (NFPanNETs) and sporadic and hereditary NFPanNETs. METHODS: Thirty-three tissue samples were analyzed: they included samples from sporadic (n = 9), von Hippel-Lindau (VHL)-related (n = 10), and multiple endocrine neoplasia type 1 (MEN1)-related NFPanNETs (n = 10) as well as normal islet cells (n = 4) for comparison. Genome-wide CpG methylation profiling was performed with the Infinium MethylationEPIC BeadChip assay and was analyzed with R-based tools. RESULTS: In unsupervised hierarchical clustering, sporadic and MEN1-related NFPanNETs clustered together, and the VHL group was in a separate cluster. MEN1-related NFPanNETs had a higher rate of hypermethylated CpG sites in comparison with sporadic and VHL-related tumor groups. Differentially methylated region analysis confirmed the higher rate of hypermethylation in MEN1-related tumors. Moreover, in an integrated analysis of gene expression data for the same tumor samples, downregulated gene expression was found in most genes that were hypermethylated. In a CpG island methylator phenotype analysis, 3 genes were identified and confirmed to have downregulated gene expression: secreted frizzle-related protein 5 (SFRP5) in sporadic NFPanNETs and cell division cycle-associated 7-like (CDCA7L) and RNA binding motif 47 (RBM47) in MEN1-related NFPanNETs. CONCLUSIONS: MEN1 NFPanNETs have a higher rate of geno me-wide hypermethylation than other NFPanNET subtypes. The similarity between the pathways enriched in a methylation analysis of known genes involved in NFPanNET tumorigenesis suggests a key role for aberrant methylation in the pathogenesis of NFPanNETs.

Metabolomics signatures of a subset of RET variants according to their oncogenic risk level.

Thirty percent of medullary thyroid carcinomas (MTCs) are related to dominant germline pathogenic variants in the RET proto-oncogene. According to their aggressiveness, these pathogenic variants are classified in three risk levels: 'moderate', 'high' and 'highest'. The present study compares the metabolomics profiles of five pathogenic variants, whether already classified or not. We have generated six stable murine fibroblast cell lines (NIH3T3) expressing the WT allele or variants of the human RET gene, with different levels of pathogenicity, including the M918V variant that is yet to be accurately classified. We carried out a targeted metabolomics study of the cell extracts with a QTRAP mass spectrometer, using the Biocrates Absolute IDQ p180 kit, which allows the quantification of 188 endogenous molecules. The data were then subjected to multivariate statistical analysis. One hundred seventy three metabolites were accurately measured. The metabolic profiles of the cells expressing the RET variants were found to be correlated with their oncogenic risk. In addition, the statistical model we constructed for predicting the oncogenic risk attributed a moderate risk to the M918V variant. Our results indicate that metabolomics may be useful for characterizing the pathogenicity of the RET gene variants and their levels of aggressiveness.