Endoscopic Diagnosis of Epithelial Subtypes of Superficial Non-Ampullary Duodenal Epithelial Tumors using Magnifying Narrow-Band Imaging.

INTRODUCTION: Superficial non-ampullary duodenal epithelial tumors (SNADETs) include low-grade adenoma (LGA) and high-grade adenoma or carcinoma (HGA/Ca) and are classified into two different epithelial subtypes, gastric-type (G-type) and intestinal-type (I-type). We attempted to distinguish them by endoscopic characteristics including magnifying endoscopy with narrow-band imaging (M-NBI). METHODS: Various endoscopic and M-NBI findings of 286 SNADETs were retrospectively reviewed and compared between G- and I-types and histological grades. M-NBI findings were divided into four patterns based on the following vascular patterns; absent, network, intrastructural vascular (ISV), and unclassified. Lesions displaying a single pattern were classified as mono-pattern and those displaying multiple patterns as mixed-pattern. Lesions showing CDX2 positivity were categorized as I-types and those showing MUC5AC or MUC6 positivity were categorized as G-types based on immunohistochemistry. RESULTS: Among 286 lesions, 23 (8%) were G-type and 243 (85%) were I-type. More G-type lesions were located oral to papilla (91.3 vs. 45.6%, p < 0.001), and had protruding morphology compared to those of I-types (65.2 vs. 14.4%, p < 0.001). The major M-NBI pattern was ISV in G-type (78.2 vs. 26.3%, p < 0.001), and absent for I-type (0 vs. 34.5%, p = 0.003). Three endoscopic characteristics; location oral to papilla, protruding morphology, and major M-NBI pattern (ISV) were independent predictors for G-type. Mixed-pattern was more common in HGA/Ca than LGA for I-type (77.0 vs. 58.8%, p = 0.01); however, there was no difference for those in G-type. CONCLUSION: Endoscopic findings including M-NBI are useful to differentiate epithelial subtypes.

Parathyroid tumors in the 5th edition of the WHO Classification of Tumors of the Endocrine Organs.

The diagnosis of pathological conditions of the parathyroid glands is the answer to clinically more frequently detected hypercalcemic conditions, including MEN syndromes. In routine biopsy practice, enlarged bodies are also a differential diagnosis for the diagnosis of thyroid nodules. In the chapter of parathyroid tumors, the 5th edition of the WHO classification brings changes influenced similarly to other endocrine organs by the increase in genetic information. At the terminological level, the concept of hyperplasia has been narrowed down to secondary hyperplasia, most of the previously primary hyperplasias are referred to as multiglandular parathyroid disease due to evidence of multiglandular clonal proliferations. The term atypical parathyroid tumor replacing atypical adenoma is newly introduced - the uncertain biological behaviour is emphasized. The basic examination includes parafibromin immunohis- tochemistry, the deficiency of parafibromin being an indicator of an inactivating CDC73 mutation and an increased risk of familial forms, or MEN. Methodologically, refinements are introduced in the quantification of mitotic activity per 10 mm2. Oncocytic subtypes have an arbitrarily declared threshold of more than 75% oncocytes. The definition of lipoadenoma (multiplication of both components, more than 50% of adipose tissue in the tumor) is similarly specified. The diagnosis of cancer remains histopathological with unequivocal evidence of invasion, or microscopically verified metastasis.

Predicting Subtype of Growth Hormone Pituitary Adenoma based on Magnetic Resonance Imaging Characteristics.

PURPOSE: This study aimed to investigate the value of magnetic resonance (MR) characteristics in differentiating the subtypes of growth hormone pituitary adenomas. MATERIALS AND METHODS: The clinical and MR imaging data of 70 patients with growth hormone pituitary adenoma confirmed by surgery and pathology were retrospectively analyzed. The tumors were divided into dense granular (DG; 36 cases) and sparse granular subtypes (SG; 34 cases). The tumors' MR features were analyzed, including the mean and maximum diameters, T2 signal intensity, T2 relative signal intensity (rSI), homogeneity, enhancement degree, and invasiveness (Knosp grade). Mann-Whitney U test and χ2 test were used to analyze MR characteristics between the 2 groups. The independent predictors and predictive probabilities of tumor subtypes were obtained via a logistic regression model, and the efficacy was compared by receiver operating characteristic curve. RESULTS: The mean and maximum diameters of growth hormone adenoma in DG and SG were 1.77 versus 2.45 and 1.95 versus 3.00 cm (median, P < 0.05), respectively. There was a significant difference between the 2 groups in T2 signal intensity and rSI (P values were 0.02 and 0.001, respectively). Most DG adenomas (86.1%) appeared as hypointense on T2 images, and 38.2% of SG adenomas were hyperintense. There was no significant difference in tumor homogeneity (P = 0.622). A significant difference was found in the Knosp grade between the 2 subtypes (P = 0.004). In addition, the enhancement degree of SG adenomas was significantly higher than that of DG adenomas (P = 0.001). Logistic regression analysis showed that high T2 rSI value and marked contrast enhancement were independent predictors of the 2 subtypes, and the odds ratios were 4.811 and 4.649, respectively. The multivariate logistic model obtained relatively high predicting efficacy, and the area under the curve, sensitivity, and specificity were 0.765, 0.882, and 0.500, respectively. CONCLUSIONS: There are significant differences in tumor size, T2 signal intensity, T2 rSI, enhancement degree, and invasiveness between DG and SG adenomas. The logistic model based on the marked contrast enhancement and high T2 rSI value has an important value in predicting the subtype of growth hormone adenoma.

External validation of blue light imaging (BLI) criteria for the optical characterization of colorectal polyps by endoscopy experts.

BACKGROUND AND AIM: Recently, the BLI Adenoma Serrated International Classification (BASIC) system was developed by European experts to differentiate colorectal polyps. Our aim was to validate the BASIC classification system among the US-based endoscopy experts. METHODS: Participants utilized a web-based interactive learning system where the group was asked to characterize polyps using the BASIC criteria: polyp surface (presence of mucus, regular/irregular and [pseudo]depressed), pit appearance (featureless, round/non-round with/without dark spots; homogeneous/heterogeneous distribution with/without focal loss), and vessels (present/absent, lacy, peri-cryptal, irregular). The final testing consisted of reviewing BLI images/videos to determine whether the criteria accurately predicted the histology results. Confidence in adenoma identification (rated "1" to "5") and agreement in polyp (adenoma vs non-adenoma) identification and characterization per BASIC criteria were derived. Strength of interobserver agreement with kappa (k) value was reported for adenoma identification. RESULTS: Ten endoscopy experts from the United States identified conventional adenoma (vs non-adenoma) with 94.4% accuracy, 95.0% sensitivity, 93.8% specificity, 93.8% positive predictive value, and 94.9% negative predictive value using BASIC criteria. Overall strength of interobserver agreement was high: kappa 0.89 (0.82-0.96). Agreement for the individual criteria was as follows: surface mucus (93.8%), regularity (65.6%), type of pit (40.6%), pit visibility (66.9%), pit distribution (57%), vessel visibility (73%), and being lacy (46%) and peri-cryptal (61%). The confidence in diagnosis was rated at high ≥4 in 67% of the cases. CONCLUSIONS: A group of US-based endoscopy experts have validated a simple and easily reproducible BLI classification system to characterize colorectal polyps with >90% accuracy and a high level of interobserver agreement.

Association of different pathologic subtypes of growth hormone producing pituitary adenoma and remission in acromegaly patients: a retrospective cohort study.

BACKGROUND: Regarding the inconclusive results of previous investigations, this study aimed to determine the association between pathology, as a possible predictor, with remission outcomes, to know the role of pathology in the personalized decision making in acromegaly patients. METHODS: A retrospective cohort study was performed on the consecutive surgeries for growth hormone (GH) producing pituitary adenomas from February 2015 to January 2021. Seventy-one patients were assessed for granulation patterns and prolactin co-expression as dual staining adenomas. The role of pathology and some other predictors on surgical remission was evaluated using logistic regression models. RESULTS: Among 71 included patients, 34 (47.9%) patients had densely granulated (DG), 14 (19.7%) had sparsely granulated (SG), 23 (32.4%) had dual staining pituitary adenomas. The remission rate was about 62.5% in the patients with SG and DG adenomas named single staining and 52.2% in dual staining groups. Postoperative remission was 1.53-folds higher in the single staining adenomas than dual staining-one (non-significant). The remission rate was doubled in DG group compared to two other groups (non-significant). By adjusting different predictors, cavernous sinus invasion and one-day postoperative GH levels decreased remission rate by 91% (95% CI: 0.01-0.67; p = 0.015) and 64% (95% CI: 0.19-0.69; p < 0.001), respectively. Responses to the medications were not significantly different among three groups. CONCLUSION: Various pathological subtypes of pituitary adenomas do not appear to have a predictive role in estimating remission outcomes. Cavernous sinus invasion followed by one-day postoperative GH is the strongest parameter to predict biochemical remission.

Bronchiolar adenomas (BA) - A detailed radio-pathologic analysis of six cases and review of literature.

Bronchiolar adenomas (BAs)/ciliated muco-nodular papillary tumors (CMPTs), are small, peripheral lung nodules arising predominantly in the elderly that follow a benign course. They can be mistaken for adenocarcinomas on frozen section. Immunohistochemistry (IHC) for basal cell markers highlights the continuous layer of basal cells underlying the tumor cells in BAs. BAs are further subdivided into proximal-type and distal type. Six BAs were retrieved from the pathology archives. The cases were classified based on morphology into proximal and distal BAs. The clinical and radiological features were reviewed. Immunohistochemistry and special stains were performed. The most common radiological picture of BA/CMPT was of a solid nodule with SUVmax < 3 as seen in 60% cases. 40% cases showed cavitation on CT. On histological examination, four cases were morphologically classified as proximal BAs and two as distal BAs. In proximal BAs, TTF1 was focally positive only in the basal cells in three of four. The mucin stained acidic. In distal BAs, TTF1 was diffusely positive in both basal and luminal cells. There was scant intracellular neutral mucin. Both the distal BAs had concomitant neuroendocrine tumors in the same lobe. Though the number of cases evaluated in this study is too low to be statistically significant, this study provides additional evidence to the concept of BA classification based on site specific histology and supplementary immunohistochemistry and reiterates the radiological features that may help distinguish it from malignant lesions.

Invited Review: Pathology of pituitary neuroendocrine tumours: present status, modern diagnostic approach, controversies and future perspectives from a neuropathological and clinical standpoint.

Neuroendocrine tumours of the adenohypophysis have traditionally been designated as pituitary adenomas to underline their usually indolent growth and lack of metastatic potential. However, they may demonstrate a huge spectrum of growth patterns and endocrine disturbances, some of them significantly affecting health and quality of life. To predict tumour growth, risk of postoperative recurrence and response to medical therapy in patients with pituitary neuroendocrine tumours is challenging. A thorough histopathological and immunohistochemical diagnostic work-up is an obligatory part of a multidisciplinary effort to precisely define the tumour type and assess prognostic and predictive factors on an individual basis. In this review, we have summarized the current status in the pathology in pituitary neuroendocrine tumours based on the selection of references from the PubMed database. We have presented possible diagnostic approaches according to the current pituitary cell lineage-based classification. The importance of recognizing histological subtypes with potentially aggressive behaviour and identification of prognostic and predictive tissue biomarkers have been highlighted. Controversies related to particular subtypes of pituitary tumours and a still limited prognostic impact of the current classification indicate the need for further refinement. Multidisciplinary approach including clinical, pathological and molecular genetic characterization will be essential for improved personalized therapy and the search for novel therapeutic targets in patients with pituitary neuroendocrine tumours.

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.

Digital analysis of hormonal immunostaining in pituitary adenomas classified according to WHO 2017 criteria and correlation with preoperative laboratory findings.

OBJECTIVE: The authors sought to evaluate clinical and laboratory data from pituitary adenoma (PA) patients with functioning PA (associated with acromegaly [n = 10] or Cushing disease [n = 10]) or nonfunctioning PA (NFPA; n = 10) that were classified according to 2017 WHO criteria (based on the expression of the transcription factors pituitary-specific positive transcription factor 1 [Pit-1], a transcription factor member of the T-box family [Tpit], and steroidogenic factor 1 [SF-1]) and to assess the immunostaining results for growth hormone (GH) and adrenocorticotropic hormone (ACTH) in the corresponding tumors. METHODS: Clinical and laboratory data were collected retrospectively. The percentage of tumoral cells positive for Pit-1, Tpit, or SF-1 was assessed and ImageJ software was used to evaluate immunopositivity in PAs with 2 different antibodies against GH (primary antibody 1 [AbGH-1] and primary antibody 2 [AbGH-2]) and 2 different antibodies against ACTH (primary antibody 1 [AbACTH-1] and primary antibody 2 [AbACTH-2]). RESULTS: Cells with positive Pit-1 staining were more frequently observed in lesions from patients with acromegaly (acromegaly group) than in lesions from patients with Cushing disease (Cushing group; p < 0.001) and those from patients with NFPA (NFPA group; p < 0.001). The percentage of Tpit-positive cells was higher in the Cushing group than in the acromegaly (p < 0.001) and NFPA (p < 0.001) groups. No difference was detected regarding SF-1 frequency among all groups (p = 0.855). In acromegalic individuals, GH immunostaining levels varied depending on the antibody employed, and only one of the antibodies (AbGH-2) yielded higher values in comparison with the values for NFPA patients (p < 0.001). For all of the antibodies employed, no significant correlations were detected between GH tissue expression and the laboratory data (serum GH vs AbGH-1, p = 0.933; serum GH vs AbGH-2, p = 0.853; serum insulin-like growth factor-1 [IGF-1] vs AbGH-1, p = 0.407; serum IGF-1 vs AbGH-2, p = 0.881). In the Cushing group data, both antibodies showed similar ACTH tissue expression, which was higher than that obtained in the NFPA group (p < 0.001). There were no significant associations between ACTH immunohistochemical findings and ACTH serum levels (serum ACTH vs AbACTH-1, p = 0.651; serum ACTH vs AbACTH-2, p = 0.987). However, ACTH immunostaining evaluated with AbACTH-1 showed a significant correlation with 24-hour urinary cortisol (24-hour cortisol vs AbACTH-1, p = 0.047; 24-hour cortisol vs AbACTH-2, p = 0.071). CONCLUSIONS: Immunostaining for Pit-1 and Tpit accurately identified lesions associated with acromegaly and Cushing disease, respectively. Conversely, SF-1 did not differentiate NFPA from lesions of the other two groups. Regarding hormonal tissue detection, results of the current investigation indicate that different antibodies may lead not only to divergent immunohistochemical results but also to lack of correlation with laboratory findings. Finally, PA classification based on transcription factor expression (Pit-1, Tpit, and SF-1), as proposed by the 2017 WHO classification of pituitary tumors, may avoid the limitations of PA classification based solely on digital immunohistochemical detection of hormones.

Multicenter external validation of the Zurich Pituitary Score.

PURPOSE: Recently, the Zurich Pituitary Score (ZPS) has been proposed as a new quantitative preoperative classification scheme for predicting gross total resection (GTR), extent of resection (EOR), and residual tumor volume (RV) in endoscopic pituitary surgery. We evaluated the external validity of the ZPS. METHODS: In three reference centers for pituitary surgery, the ZPS was applied and correlated to GTR, EOR, and RV. Furthermore, its inter-rater agreement was assessed. RESULTS: A total of 485 patients (53% male; age, 53.8 ± 15.7) were included. ZPS grades I, II, III, and IV were observed in 110 (23%), 270 (56%), 64 (13%), and 41 (8%) patients, respectively. GTR was achieved in 358 (74%) cases, with mean EOR of 87.6% ± 20.3% and RV of 1.42 ± 2.80 cm3. With increasing ZPS grade, strongly significant decreasing trends for GTR (I, 92%; II, 77%; III, 67%; IV, 15%; p < 0.001) and EOR (I, 93.8%; II, 89.9%; III, 88.1%; IV, 75.4%; p < 0.001) were found. Similarly, RV increased steadily ([cm3] I, 0.16; II, 0.61; III, 2.01; IV, 3.84; p < 0.001). We observed intraclass correlation coefficients of 0.837 (95% CI, 0.804-0.865) for intercarotid distance and 0.964 (95% CI, 0.956-0.970) for adenoma diameter, and Cohen's kappa of 0.972 (95% CI, 0.952-0.992) for the ZPS grades. CONCLUSIONS: Application of the ZPS in three external cohorts was successful. The ZPS generalized well in terms of GTR, EOR, and RV; demonstrated excellent inter-rater agreement; and can safely and effectively be applied as a quantitative classification of adenomas with relevance to surgical outcome.

Pituitary Adenoma: A review of existing classification systems based on anatomic extension and invasion.

Pituitary adenomas are common, benign tumours, that can be classified in many ways including their functionality, size and anatomical extension. Historically, larger more invasive adenomas with extension into parasellar regions were deemd untreatable. However, with increasing operative sophistication, and more precise and effective radiation options; it is no longer the case, and therefore it becomes even more important for a comprehensive classification system for these tumours. Herein, the authors present an updated review on the available classification systems for large pituitary adenomas, based on their anatomic extension and invasion of adjacent anatomic structures.

Metabolic profiling reveals distinct metabolic alterations in different subtypes of pituitary adenomas and confers therapeutic targets.

BACKGROUND: Pituitary adenomas are common brain tumors. Although transsphenoidal surgery are able to achieve extensive tumor removal, the rate of recurrence ranges from 5 to 20% depending on the different subtype. Further understanding of these tumors is needed to develop novel strategies to improve the prognosis of patients. But their metabolic characteristics are largely unknown. METHODS: We used metabolomic, transcriptomic, and proteomic approaches to systematically investigate eight subtypes of pituitary adenomas and normal pituitary glands. By blocking IDH2, we investigate IDH2 play an inhibitory role in GH tumor cell growth and tumor secretion. RESULTS: We found that all of the pituitary adenomas displayed downregulated glucose metabolism and glycolysis compared to normal tissues. Together with the differences in amino acids and fatty acids, we categorized these tumors into three clusters. We then re-established the reprogrammed metabolic flux in pituitary adenomas based on multiomic analyses. Take growth hormone-secreting pituitary adenomas as an example, we revealed that IDH2 is a key player in the reprogrammed metabolism of such tumors. By blocking IDH2, we confirmed that IDH2 is a potential target for the inhibition of tumor cell growth and tumor secretion. CONCLUSIONS: Our study first uncovered the metabolic landscape of pituitary adenomas and demonstrated a possible way to inhibit tumor growth by regulating aberrant metabolism.

Consensus molecular subtype classification of colorectal adenomas.

Consensus molecular subtyping is an RNA expression-based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction-based methodology. DNA copy number was assessed by low-coverage DNA sequencing (n = 30) or array-comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 'metabolic subtype', which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the 'MSI immune' subtype. Eight adenomas (13%) were classified as the 'canonical' CMS2. No adenomas were classified as the 'mesenchymal' CMS4, consistent with the fact that adenomas lack invasion-associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high-risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Back to the Colorectal Cancer Consensus Molecular Subtype Future.

PURPOSE OF REVIEW: This review seeks to provide an informed prospective on the advances in molecular profiling and analysis of colorectal cancer (CRC). The goal is to provide a historical context and current summary on how advances in gene and protein sequencing technology along with computer capabilities led to our current bioinformatic advances in the field. RECENT FINDINGS: An explosion of knowledge has occurred regarding genetic, epigenetic, and biochemical alterations associated with the evolution of colorectal cancer. This has led to the realization that CRC is a heterogeneous disease with molecular alterations often dictating natural history, response to treatment, and outcome. The consensus molecular subtypes (CMS) classification classifies CRC into four molecular subtypes with distinct biological characteristics, which may form the basis for clinical stratification and subtype-based targeted intervention. This review summarizes new developments of a field moving "Back to the Future." CRC molecular subtyping will better identify key subtype specific therapeutic targets and responses to therapy.

Advances and controversies in the classification and grading of pituitary tumors.

BACKGROUND: Pituitary tumors are common lesions, and they represent the second most frequent primary brain tumor. Their classification has undergone several changes over time. The World Health Organization conducts periodic expert review/consensus meetings and publishes the results as recommendations for changes in classification, based on advances in molecular and genetic advances. This paper summarizes the results of the 2017 WHO Classification, which recommends several important changes. PURPOSE: This paper provides a review of the major changes and issues leading to an understanding of the basis for a new pituitary tumor classification. They include the rejection and modification of prior conceptual and pathological characteristics of these neoplasms. There is also considerable concern related to invasive and recurrent pituitary tumors which follow a less benign course than the typical pituitary adenoma. METHODS: A review of the outcome data for the previously designated "atypical" pituitary tumor category revealed that the former criteria were not adequate to support their ability to predict with accuracy the clinical course of a given tumor. A similar review was accomplished regarding the role of the p53 tumor suppressor mutation. Again, there was no reliable contribution of p53 status to tumor aggressiveness. Other changes have occurred regarding the cytogenetic lineage of the various subtypes of pituitary adenoma. The transcription factors Pit-1, SF-1, and TPit play a major role in determining tumor subtypes and have become part of the classification criteria. RESULTS: These advances now help provide the background for more reliable and consistent classification of pituitary adenomas. Further definition of aggressive characteristics such as cavernous sinus and dural invasion remain to be considered in the quest to make more accurate prognostic projections based on histopathological analysis. CONCLUSIONS: The 2017 WHO Classification of Pituitary Tumors provides a more solid basis for accurate and reliable prognostic assessment of these lesions. Further progress undoubtedly will be made as the recommendations of this update are incorporated in to routine use.

Next-generation sequencing identifies novel mitochondrial variants in pituitary adenomas.

PURPOSE: Disrupted mitochondrial functions and genetic variants of mitochondrial DNA (mtDNA) have been observed in different human neoplasms. Next-generation sequencing (NGS) can be used to detect even low heteroplasmy-level mtDNA variants. We aimed to investigate the mitochondrial genome in pituitary adenomas by NGS. METHODS: We analysed 11 growth hormone producing and 33 non-functioning [22 gonadotroph and 11 hormone immunonegative] pituitary adenomas using VariantPro™ Mitochondrion Panel on Illumina MiSeq instrument. Revised Cambridge Reference Sequence (rCRS) of the mtDNA was used as reference. Heteroplasmy was determined using a 3% cutoff. RESULTS: 496 variants were identified in pituitary adenomas with overall low level of heteroplasmy (7.22%). On average, 35 variants were detected per sample. Samples harbouring the highest number of variants had the highest Ki-67 indices independently of histological subtypes. We identified eight variants (A11251G, T4216C, T16126C, C15452A, T14798C, A188G, G185A, and T16093C) with different prevalences among different histological groups. T16189C was found in 40% of non-recurrent adenomas, while it was not present in the recurrent ones. T14798C and T4216C were confirmed by Sanger sequencing in all 44 samples. 100% concordance was found between NGS and Sanger method. CONCLUSIONS: NGS is a reliable method for investigating mitochondrial genome and heteroplasmy in pituitary adenomas. Out of the 496 detected variants, 414 have not been previously reported in pituitary adenoma. The high number of mtDNA variants may contribute to adenoma genesis, and some variants (i.e., T16189C) might associate with benign behaviour.

Next-generation sequencing of microRNAs reveals a unique expression pattern in different types of pituitary adenomas.

Pituitary adenomas (PAs) are considered the most common intracranial tumor to cause serious morbidity because of dysregulated pituitary hormone secretions. Aberrant expression of microRNAs (miRNAs) is correlated with the development and function of the pituitary gland as well as the tumorigenesis of hypothalamic-pituitary axis-related pituitary tumors. In this study, we showed the differential expression patterns of miRNAs in NFPAs (nonfunctioning pituitary adenomas), GHPAs (growth hormone-secreting pituitary adenomas) and PRLPAs (prolactin-secreting pituitary adenomas) compared to those in three normal pituitary glands using the HiSeq 2000 sequencing system (Illumina). We validated miRNA expression using real-time quantitative polymerase chain reaction (RT-qPCR) analyses of samples from 73 patients (13 GHPAs, 42 NFPAs, and 18 PRLPAs) and 6 normal pituitary gland. We observed that miR-34c-3p was significantly downregulated in our PRLPA samples (p < 0.01), along with miR-34b-5p, miR-378 and miR-338-5p (all p < 0.05). In NFPAs, miR-493-5p was downregulated, and miR-181b-5p was significantly upregulated (p < 0.01). In GHPAs, miR-184 was significantly upregulated (p < 0.05). We observed that the tumor suppressive miR-124-3p was downregulated in both NFPAs and GHPAs. Taken together, we showed distinctive miRNA expression patterns in these three PAs, and these miRNA signatures in PA may have therapeutic potential as novel biomarkers for each type of PA.

Ocular Iridociliary Adenoma in a Congo African Grey Parrot (Psittacus erithacus).

A 19-year-old female Congo African grey parrot (Psittacus erithacus) presented for an oval, solid, pigmented, suspected intraocular mass with extrascleral extension through the inferior cornea of the left eye. The eye was nonvisual, and intraocular portions of the mass significantly altered the posterior chamber. Neoplasia was confirmed by biopsy, and enucleation was performed because of the severity of ocular disease, loss of vision, enhancement of patient comfort, and potential metastasis. Histopathologic examination of the entire globe revealed a pigmented iridociliary adenoma. Iridociliary adenomas have been rarely reported in birds, and this case report details diagnosis and treatment. Iridociliary adenomas in other species are often benign, indicating this neoplasia can be successfully treated with no reoccurrence by complete excision.

Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation.

BACKGROUND & AIMS: Hepatocellular adenomas (HCAs) are benign liver tumors that can be assigned to molecular subtypes based on inactivating mutations in hepatocyte nuclear factor 1A, activating mutations in ß-catenin, or activation of inflammatory signaling pathways. We aimed to update the classification system for HCA and associate the subtypes with disease risk factors and complications. METHODS: We analyzed expression levels of 20 genes and sequenced exon regions of 8 genes (HNF1A, IL6ST, CTNNB1, FRK, STAT3, GNAS, JAK1, and TERT) in 607 samples of 533 HCAs from 411 patients, collected from 28 centers mainly in France from 2000 and 2014. We performed gene expression profile, RNA sequence, whole-exome and genome sequence, and immunohistochemical analyses of select samples. Molecular data were associated with risk factors, histopathology, bleeding, and malignant transformation. RESULTS: Symptomatic bleeding occurred in 14% of the patients (85% of cases were female, median age, 38 years); 7% of the nodules were borderline between HCA and hepatocellular carcinoma, and 3% of patients developed hepatocellular carcinoma from HCA. Based on molecular features, we classified HCA into 8 subgroups. One new subgroup, composed of previously unclassified HCA, represented 4% of HCAs overall and was associated with obesity and bleeding. These tumors were characterized by activation of sonic hedgehog signaling, due to focal deletions that fuse the promoter of INHBE with GLI1. Analysis of genetic heterogeneity among multiple HCAs, from different patients, revealed a molecular subtype field effect; multiple tumors had different mutations that deregulated similar pathways. Specific molecular subtypes of HCA associated with various HCA risk factors, including imbalances in estrogen or androgen hormones. Specific molecular subgroup of HCA with ß-catenin and sonic hedgehog activation associated with malignant transformation and bleeding, respectively. CONCLUSIONS: Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients' risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA.

Development and validation of the SIMPLE endoscopic classification of diminutive and small colorectal polyps.

BACKGROUND: Prediction of histology of small polyps facilitates colonoscopic treatment. The aims of this study were: 1) to develop a simplified polyp classification, 2) to evaluate its performance in predicting polyp histology, and 3) to evaluate the reproducibility of the classification by trainees using multiplatform endoscopic systems. METHODS: In phase 1, a new simplified endoscopic classification for polyps - Simplified Identification Method for Polyp Labeling during Endoscopy (SIMPLE) - was created, using the new I-SCAN OE system (Pentax, Tokyo, Japan), by eight international experts. In phase 2, the accuracy, level of confidence, and interobserver agreement to predict polyp histology before and after training, and univariable/multivariable analysis of the endoscopic features, were performed. In phase 3, the reproducibility of SIMPLE by trainees using different endoscopy platforms was evaluated. RESULTS: Using the SIMPLE classification, the accuracy of experts in predicting polyps was 83 % (95 % confidence interval [CI] 77 % - 88 %) before and 94 % (95 %CI 89 % - 97 %) after training (P â€Š= 0.002). The sensitivity, specificity, positive predictive value, and negative predictive value after training were 97 %, 88 %, 95 %, and 91 %. The interobserver agreement of polyp diagnosis improved from 0.46 (95 %CI 0.30 - 0.64) before to 0.66 (95 %CI 0.48 - 0.82) after training. The trainees demonstrated that the SIMPLE classification is applicable across endoscopy platforms, with similar post-training accuracies for narrow-band imaging NBI classification (0.69; 95 %CI 0.64 - 0.73) and SIMPLE (0.71; 95 %CI 0.67 - 0.75). CONCLUSIONS: Using the I-SCAN OE system, the new SIMPLE classification demonstrated a high degree of accuracy for adenoma diagnosis, meeting the ASGE PIVI recommendations. We demonstrated that SIMPLE may be used with either I-SCAN OE or NBI.