Triple-Negative Pleomorphic Lobular Carcinoma in a BRCA1 Mutation Carrier: A Case of Complete Pathological Response.

BACKGROUND Hereditary breast cancer arising in BRCA1-deficient patients is commonly diagnosed as invasive carcinoma of no special type (NST) with medullary features, while invasive lobular carcinoma (ILC) appears to be significantly under-represented in BRCA1 mutation carriers. We report a case of pleomorphic ILC arising in a 28-year-old woman harboring a germline BRCA1 c.3756_3759delGTCT p.(Ser1253Argfs*10) pathogenic variant. CASE REPORT A nulliparous 28-year-old woman with a family history of BRCA1 mutation presented to the symptomatic breast clinic with a several-week history of a left 80-mm breast lump. Core biopsy established a diagnosis of a poorly differentiated triple-negative breast cancer (TNBC) of pleomorphic lobular phenotype. Her clinical diagnosis was cT3, N0, M0, cStageIIB. The MDT recommended CT staging, MRI breast imaging and neoadjuvant chemotherapy (NACT). PET CT imaging showed no evidence of distant metastatic disease. The patient had a good radiological response to NACT with a FEC-T carboplatin regimen. Post-NACT imaging showed a residual cystic mass and the patient underwent a mastectomy and sentinel lymph node biopsy with plans for a delayed latissimus dorsi reconstruction following her adjuvant radiotherapy treatment. A complete pathological response was subsequently demonstrated without any evidence of metastatic disease. CONCLUSIONS This case is the first report of pleomorphic ILC with a triple-negative receptor status and a complete pathological response in a BRCA1 mutation carrier. Our study expands the heterogeneous spectrum of TNBC and contributes to a better understanding of the molecular genetic landscape that characterizes invasive pleomorphic lobular neoplasia.

Convolutional neural networks for the differentiation between benign and malignant renal tumors with a multicenter international computed tomography dataset.

OBJECTIVES: To use convolutional neural networks (CNNs) for the differentiation between benign and malignant renal tumors using contrast-enhanced CT images of a multi-institutional, multi-vendor, and multicenter CT dataset. METHODS: A total of 264 histologically confirmed renal tumors were included, from US and Swedish centers. Images were augmented and divided randomly 70%:30% for algorithm training and testing. Three CNNs (InceptionV3, Inception-ResNetV2, VGG-16) were pretrained with transfer learning and fine-tuned with our dataset to distinguish between malignant and benign tumors. The ensemble consensus decision of the three networks was also recorded. Performance of each network was assessed with receiver operating characteristics (ROC) curves and their area under the curve (AUC-ROC). Saliency maps were created to demonstrate the attention of the highest performing CNN. RESULTS: Inception-ResNetV2 achieved the highest AUC of 0.918 (95% CI 0.873-0.963), whereas VGG-16 achieved an AUC of 0.813 (95% CI 0.752-0.874). InceptionV3 and ensemble achieved the same performance with an AUC of 0.894 (95% CI 0.844-0.943). Saliency maps indicated that Inception-ResNetV2 decisions are based on the characteristics of the tumor while in most tumors considering the characteristics of the interface between the tumor and the surrounding renal parenchyma. CONCLUSION: Deep learning based on a diverse multicenter international dataset can enable accurate differentiation between benign and malignant renal tumors. CRITICAL RELEVANCE STATEMENT: Convolutional neural networks trained on a diverse CT dataset can accurately differentiate between benign and malignant renal tumors. KEY POINTS: • Differentiation between benign and malignant tumors based on CT is extremely challenging. • Inception-ResNetV2 trained on a diverse dataset achieved excellent differentiation between tumor types. • Deep learning can be used to distinguish between benign and malignant renal tumors.

A pilot radiometabolomics integration study for the characterization of renal oncocytic neoplasia.

Differentiating benign renal oncocytic tumors and malignant renal cell carcinoma (RCC) on imaging and histopathology is a critical problem that presents an everyday clinical challenge. This manuscript aims to demonstrate a novel methodology integrating metabolomics with radiomics features (RF) to differentiate between benign oncocytic neoplasia and malignant renal tumors. For this purpose, thirty-three renal tumors (14 renal oncocytic tumors and 19 RCC) were prospectively collected and histopathologically characterised. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) was used to extract metabolomics data, while RF were extracted from CT scans of the same tumors. Statistical integration was used to generate multilevel network communities of -omics features. Metabolites and RF critical for the differentiation between the two groups (delta centrality > 0.1) were used for pathway enrichment analysis and machine learning classifier (XGboost) development. Receiver operating characteristics (ROC) curves and areas under the curve (AUC) were used to assess classifier performance. Radiometabolomics analysis demonstrated differential network node configuration between benign and malignant renal tumors. Fourteen nodes (6 RF and 8 metabolites) were crucial in distinguishing between the two groups. The combined radiometabolomics model achieved an AUC of 86.4%, whereas metabolomics-only and radiomics-only classifiers achieved AUC of 72.7% and 68.2%, respectively. Analysis of significant metabolite nodes identified three distinct tumour clusters (malignant, benign, and mixed) and differentially enriched metabolic pathways. In conclusion, radiometabolomics integration has been presented as an approach to evaluate disease entities. In our case study, the method identified RF and metabolites important in differentiating between benign oncocytic neoplasia and malignant renal tumors, highlighting pathways differentially expressed between the two groups. Key metabolites and RF identified by radiometabolomics can be used to improve the identification and differentiation between renal neoplasms.

Machine Learning Integrating 99mTc Sestamibi SPECT/CT and Radiomics Data Achieves Optimal Characterization of Renal Oncocytic Tumors.

The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7-100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7-100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5-99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

99mTc-Sestamibi SPECT/CT and histopathological features of oncocytic renal neoplasia.

BACKGROUND: 99mTc-Sestamibi Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) contributes to the non-invasive differentiation of renal oncocytoma (RO) from renal cell carcinoma (RCC) by characterising renal tumours as Sestamibi positive or Sestamibi negative regarding their 99mTc-Sestamibi uptake compared to the non-tumoral renal parenchyma. PURPOSE: To determine whether 99mTc- Sestamibi uptake in renal tumour and the non-tumoral renal parenchyma measured using Standard Uptake Value (SUV) SPECT, has a beneficial role in differentiating RO from RCC. MATERIAL AND METHODS: Fifty-seven renal tumours from 52 patients were evaluated. In addition to visual evaluation of 99mTc-Sestamibi uptake, SUVmax measurements were performed in the renal tumour and the ipsilateral non-tumoral renal parenchyma. Analysis of the area under the receiver operating characteristic curve identified an optimal cut-off value for detecting RO, based on the relative ratio of 99mTc- Sestamibi uptake. RESULTS: Semiquantitative evaluation of 99mTc-Sestamibi uptake did not improve the performance of 99mTc- Sestamibi SPECT/CT in detecting RO. 99mTc- Sestamibi SPECT/CT identifies a group of mostly indolent Sestamibi-positive tumours with low malignant potential containing RO, Low-Grade Oncocytic Tumours, Hybrid Oncocytic Tumours, and a subset of chromophobe RCCs. CONCLUSION: The imaging limitations for accurate differentiation of Sestamibi-positive renal tumours mirror the recognised diagnostic complexities of the histopathologic evaluation of oncocytic neoplasia. Patients with Sestamibi-positive renal tumours could be better suited for biopsy and follow-up, according to the current active surveillance protocols.

Mass spectrometry imaging identifies metabolic patterns associated with malignant potential in pheochromocytoma and paraganglioma.

OBJECTIVE: Within the past decade, important genetic drivers of pheochromocytoma and paraganglioma (PPGLs) development have been identified. The pathophysiological mechanism that translates these alterations into functional autonomy and potentially malignant behavior has not been elucidated in detail. Here we used MALDI-mass spectrometry imaging (MALDI-MSI) of formalin-fixed paraffin-embedded tissue specimens to comprehensively characterize the metabolic profiles of PPGLs. DESIGN AND METHODS: MALDI-MSI was conducted in 344 PPGLs and results correlated with genetic and phenotypic information. We experimentally silenced genetic drivers by siRNA in PC12 cells to confirm their metabolic impact in vitro. RESULTS: Tissue abundance of kynurenine pathway metabolites such as xanthurenic acid was significantly lower (P = 2.35E-09) in the pseudohypoxia pathway cluster 1 compared to PPGLs of the kinase-driven PPGLs cluster 2. Lower abundance of xanthurenic acid was associated with shorter metastasis-free survival (log-rank tests P = 7.96E-06) and identified as a risk factor for metastasis independent of the genetic status (hazard ratio, 32.6, P = 0.002). Knockdown of Sdhb and Vhl in an in vitro model demonstrated that inositol metabolism and sialic acids were similarly modulated as in tumors of the respective cluster. CONCLUSIONS: The present study has identified distinct tissue metabolomic profiles of PPGLs in relation to tumor genotypes. In addition, we revealed significantly altered metabolites in the kynurenine pathway in metastatic PPGLs, which can aid in the prediction of its malignant potential. However, further validation studies will be required to confirm our findings.

What Have We Learned from Molecular Biology of Paragangliomas and Pheochromocytomas?

Recent advances in molecular genetics and genomics have led to increased understanding of the aetiopathogenesis of pheochromocytomas and paragangliomas (PPGLs). Thus, pan-genomic studies now provide a comprehensive integrated genomic analysis of PPGLs into distinct molecularly defined subtypes concordant with tumour genotypes. In addition, new embryological discoveries have refined the concept of how normal paraganglia develop, potentially establishing a developmental basis for genotype-phenotype correlations for PPGLs. The challenge for modern pathology is to translate these scientific discoveries into routine practice, which will be based largely on histopathology for the foreseeable future. Here, we review recent progress concerning the cell of origin and molecular pathogenesis of PPGLs, including pathogenetic mechanisms, genetic susceptibility and molecular classification. The current roles and tools of pathologists are considered from a histopathological perspective, including differential diagnoses, genotype-phenotype correlations and the use of immunohistochemistry in identifying hereditary predisposition and validating genetic variants of unknown significance. Current and potential molecular prognosticators are also presented with the hope that predictive molecular biomarkers will be integrated into risk stratification scoring systems to assess the metastatic potential of these intriguing neoplasms and identify potential drug targets.

Data set for the reporting of pheochromocytoma and paraganglioma: explanations and recommendations of the guidelines from the International Collaboration on Cancer Reporting.

BACKGROUND AND OBJECTIVES: The International Collaboration on Cancer Reporting (ICCR) is a not-for-profit to develop evidence-based, internationally agreed-upon standardized data sets for each anatomic site, to be used throughout the world. Providing global standardization of pathology tumor classification, staging, and other reporting elements will lead to improved patient management and enhanced epidemiological research. METHODS: Pheochromocytoma and paraganglioma are uncommon and are frequently overlooked in registry data sets. Malignant criteria have previously been defined only when there was metastatic disease. RESULTS: With recent recognition of a significant inheritance association and the development of risk stratification tools, this data set was created in order to obtain more meaningful outcomes and management data, using similar criteria across the global pathology community. Issues related to key core and non-core elements, especially clinical hormonal status, familial history, tumor focality, proliferative fraction, adverse or risk stratification features, and ancillary techniques, are discussed in the context of daily application to these types of specimens. CONCLUSIONS: The ICCR data set, developed by an international panel of endocrine organ specialists, establishes a pathology-standardized reporting guide for pheochromocytoma and paraganglioma.

Data set for reporting of carcinoma of the adrenal cortex: explanations and recommendations of the guidelines from the International Collaboration on Cancer Reporting.

Complete resection of adrenal cortical carcinoma (ACC) with or without adjuvant therapy offers the best outcome. Recurrence is common, and in individual cases, the long-term outcome is difficult to predict, making it challenging to personalize treatment options. Current risk stratification approaches are based on clinical and conventional surgical pathology assessment. Rigorous and uniform pathological assessment may improve care for individual patients and facilitate multi-institutional collaborative studies. The International Collaboration on Cancer Reporting (ICCR) convened an expert panel to review ACC pathology reporting. Consensus recommendations were made based on the most recent literature and expert opinion. The data set comprises 23 core (required) items. The core pathological features include the following: diagnosis as per the current World Health Organization classification, specimen integrity, greatest dimension, weight, extent of invasion, architecture, percentage of lipid-rich cells, capsular invasion, lymphatic invasion, vascular invasion, atypical mitotic figures, coagulative necrosis, nuclear grade, mitotic count, Ki-67 proliferative index, margin status, lymph node status, and pathological stage. Tumors were dichotomized into low-grade (<20 mitoses per 10 mm2) and high-grade (>20 mitoses per 10 mm2) ones. Additional noncore elements that may be useful in individual cases included several multifactorial risk assessment systems (Weiss, modified Weiss, Lin-Weiss-Bisceglia, reticulin, Helsinki, and Armed Forces Institute of Pathology scores/algorithms). This data set is now available through the ICCR website with the hope of better standardizing pathological assessment of these relatively rare but important malignancies.

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.

BACKGROUND: Cross-sectional imaging regularly results in incidental discovery of adrenal tumours, requiring exclusion of adrenocortical carcinoma (ACC). However, differentiation is hampered by poor specificity of imaging characteristics. We aimed to validate a urine steroid metabolomics approach, using steroid profiling as the diagnostic basis for ACC. METHODS: We did a prospective multicentre study in adult participants (age ≥18 years) with newly diagnosed adrenal masses. We assessed the accuracy of diagnostic imaging strategies based on maximum tumour diameter (≥4 cm vs <4 cm), imaging characteristics (positive vs negative), and urine steroid metabolomics (low, medium, or high risk of ACC), separately and in combination, using a reference standard of histopathology and follow-up investigations. With respect to imaging characteristics, we also assessed the diagnostic utility of increasing the unenhanced CT tumour attenuation threshold from the recommended 10 Hounsfield units (HU) to 20 HU. FINDINGS: Of 2169 participants recruited between Jan 17, 2011, and July 15, 2016, we included 2017 from 14 specialist centres in 11 countries in the final analysis. 98 (4·9%) had histopathologically or clinically and biochemically confirmed ACC. Tumours with diameters of 4 cm or larger were identified in 488 participants (24·2%), including 96 of the 98 with ACC (positive predictive value [PPV] 19·7%, 95% CI 16·2-23·5). For imaging characteristics, increasing the unenhanced CT tumour attenuation threshold to 20 HU from the recommended 10 HU increased specificity for ACC (80·0% [95% CI 77·9-82·0] vs 64·0% [61·4-66.4]) while maintaining sensitivity (99·0% [94·4-100·0] vs 100·0% [96·3-100·0]; PPV 19·7%, 16·3-23·5). A urine steroid metabolomics result indicating high risk of ACC had a PPV of 34·6% (95% CI 28·6-41·0). When the three tests were combined, in the order of tumour diameter, positive imaging characteristics, and urine steroid metabolomics, 106 (5·3%) participants had the result maximum tumour diameter of 4 cm or larger, positive imaging characteristics (with the 20 HU cutoff), and urine steroid metabolomics indicating high risk of ACC, for which the PPV was 76·4% (95% CI 67·2-84·1). 70 (3·5%) were classified as being at moderate risk of ACC and 1841 (91·3%) at low risk (negative predictive value 99·7%, 99·4-100·0). INTERPRETATION: An unenhanced CT tumour attenuation cutoff of 20 HU should replace that of 10 HU for exclusion of ACC. A triple test strategy of tumour diameter, imaging characteristics, and urine steroid metabolomics improves detection of ACC, which could shorten time to surgery for patients with ACC and help to avoid unnecessary surgery in patients with benign tumours. FUNDING: European Commission, UK Medical Research Council, Wellcome Trust, and UK National Institute for Health Research, US National Institutes of Health, the Claire Khan Trust Fund at University Hospitals Birmingham Charities, and the Mayo Clinic Foundation for Medical Education and Research.

Management of Full-Thickness Macular Hole in A Genetically Confirmed Case with Usher Syndrome.

INTRODUCTION: Full-thickness macular hole (FTMH) formation is rarely seen in patients with retinitis pigmentosa (RP) and can have an adverse impact on their residual visual function. The underlying mechanisms are unknown, and clinical experience is limited regarding surgical outcomes. Here, we describe the surgical management of FTMH in a young patient with genetically confirmed Usher syndrome, the most common form of syndromic RP. CASE REPORT: A 28-year-old woman presented with blurred vision in her right eye (RE). She had a history of RP and bilateral hearing impairment since childhood. Fundoscopy and spectral-domain optical coherence tomography revealed a FTMH in the RE along with typical RP features bilaterally. After pars plana vitrectomy (PPV) with internal limiting membrane peel and gas tamponade, the FTMH closed. Six months after PPV the patient underwent cataract surgery in the affected eye, and the visual acuity remained stable compared to baseline. The clinical diagnosis of Usher syndrome was genetically confirmed by whole exome sequencing (WES), which revealed the presence of two pathogenic nucleotide variants in trans (compound heterozygosity) in the gene USH2A. CONCLUSION: We report a rare case of successful closure of a FTMH in a patient with Usher syndrome. Surgical treatment of FTMH can help preserve the central vision in RP patients, whose peripheral vision is severely affected.

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background in over one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and several other tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlighting the importance of identifying SDHx mutations for patient management. Genetic variants of unknown significance, where implications for the patient and family members are unclear, are a problem for interpretation. For such cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB (SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatography-mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions provide an alternative method. Here, we compare SDHB-IHC with metabolite profiling in 189 tumours from 187 PPGL patients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to establish predictive models for interpreting metabolite data. Metabolite profiling showed higher diagnostic specificity compared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite profiles improved predictive ability over that of the SFR, in particular for hard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, the combination of metabolite profiling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classified all but one of the false negatives from metabolite profiling strategies, while metabolite profiling correctly classified all but one of the false negatives/positives from SDHB-IHC. From 186 tumours with confirmed status of SDHx variant pathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benefits of both strategies for patient management. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

In Situ Metabolomics Expands the Spectrum of Renal Tumours Positive on 99mTc-sestamibi Single Photon Emission Computed Tomography/Computed Tomography Examination.

BACKGROUND: Definite noninvasive characterisation of renal tumours positive on 99mTc-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) examination including renal oncocytomas (ROs), hybrid oncocytic chromophobe tumours (HOCTs), and chromophobe renal cell carcinoma (chRCC) is currently not feasible. OBJECTIVE: To investigate whether combined 99mTc-sestamibi SPECT/CT and in situ metabolomic profiling can accurately characterise renal tumours exhibiting 99mTc-sestamibi uptake. DESIGN SETTING AND PARTICIPANTS: A tissue microarray analysis of 33 tumour samples from 28 patients was used to investigate whether their in situ metabolomic status correlates with their features on 99mTc-sestamibi SPECT/CT examination. In order to validate emerging data, an independent cohort comprising 117 tumours was subjected to matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: MALDI MSI data analysis and image generation were facilitated by FlexImaging v. 4.2, while k-means analysis by SCiLS Lab software followed by R-package CARRoT analysis was used for assessing the highest predictive power in the differential of RO versus chRCC. Heatmap-based clustering, sparse partial least-squares discriminant analysis, and volcano plots were created with MetaboAnalyst 3.0. RESULTS AND LIMITATIONS: We identified a discriminatory metabolomic signature for 99mTc-sestamibi SPECT/CT-positive Birt-Hogg-Dubè-associated HOCTs versus other renal oncocytic tumours. Metabolomic differences were also evident between 99mTc-sestamibi-positive and 99mTc-sestamibi-negative chRCCs, prompting additional expert review; two of three 99mTc-sestamibi-positive chRCCs were reclassified as low-grade oncocytic tumours (LOTs). Differences were identified between distal-derived tumours from those of proximal tubule origin, including differences between ROs and chRCCs. CONCLUSIONS: The current study expands the spectrum of 99mTc-sestamibi SPECT/CT-positive renal tumours, encompassing ROs, HOCTs, LOTs, and chRCCs, and supports the feasibility of in situ metabolomic profiling in the diagnostics and classification of renal tumours. PATIENT SUMMARY: For preoperative evaluation of solid renal tumours, 99mTc-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) is a novel examination method. To increase diagnostic accuracy, we propose that 99mTc-sestamibi-positive renal tumours should be biopsied and followed by a combined histometabolomic analysis.

Novel methods in adrenal research: a metabolomics approach.

Metabolic alterations have implications in a spectrum of tissue functions and disease. Aided by novel molecular biological and computational tools, our understanding of physiological and pathological processes underpinning endocrine and endocrine-related disease has significantly expanded over the last decade. Herein, we focus on novel metabolomics-related methodologies in adrenal research: in situ metabolomics by mass spectrometry imaging, steroid metabolomics by gas and liquid chromatography-mass spectrometry, energy pathway metabologenomics by liquid chromatography-mass spectrometry-based metabolomics of Krebs cycle intermediates, and cellular reprogramming to generate functional steroidogenic cells and hence to modulate the steroid metabolome. All four techniques to assess and/or modulate the metabolome in biological systems provide tremendous opportunities to manage neoplastic and non-neoplastic disease of the adrenal glands in the era of precision medicine. In this context, we discuss emerging clinical applications and/or promising metabolic-driven research towards diagnostic, prognostic, predictive and therapeutic biomarkers in tumours arising from the adrenal gland and extra-adrenal paraganglia as well as modern approaches to delineate and reprogram adrenal metabolism.

New and Emerging Biomarkers in Endocrine Pathology.

Significant advances in genomics and molecular genetics in recent years have reshaped the practice of endocrine pathology. Pan-genomic studies, including the pioneering ones on papillary thyroid carcinoma, phaeochromocytoma/paraganglioma, and adrenal cortical carcinoma from the Cancer Genome Atlas (TCGA) project, provided a comprehensive integrated genomic analysis of endocrine tumors into distinct molecularly defined subtypes. Better understanding of the molecular landscape and more accurate definition of biological behavior has been accordingly achieved. Nevertheless, how any of these advances are translated into routine practice still remains a challenge in the era of precision medicine. The challenge for modern pathology is to keep up the pace with scientific discoveries by integrating novel concepts in tumor classification, molecular genetics, prognostication, and theranostics. As an example, pathology plays a role in the identification of hereditary disease, while it offers the tools for complementing molecular genetics, for example, validation of variants of unknown significance deriving from targeted sequencing or whole exome/genome sequencing approach. Immunohistochemistry has arisen as a cost-effective strategy in the evaluation either of somatic mutations in tumors and/or germline mutations in patients with familial cancer syndromes. Herein, a comprehensive review focusing on novel and emerging biomarkers is presented in order pathologists and other endocrine-related specialists to remain updated and become aware of potential pitfalls and limitations in the field of endocrine pathology.

Expression of Contactin 4 Is Associated With Malignant Behavior in Pheochromocytomas and Paragangliomas.

Context: Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine, usually benign, tumors. Currently, the only reliable criterion of malignancy is the presence of metastases. Objective: The aim of this study was to identify genes associated with malignancy in PPGLs. Design: Transcriptomic profiling was performed on 40 benign and 11 malignant PPGLs. Genes showing a significantly different expression between benign and malignant PPGLs with a ratio ≥4 were confirmed and tested in an independent series by quantitative real-time polymerase chain reaction (qRT-PCR). Immunohistochemistry was performed for the validated genes on 109 benign and 32 malignant PPGLs. Functional assays were performed with hPheo1 cells. Setting: This study was conducted at the Department of Pathology of the Erasmus MC University Medical Center Rotterdam Human Molecular Genetics laboratory of the de Duve Institute, University of Louvain. Patients: PPGL samples from 179 patients, diagnosed between 1972 and 2015, were included. Main outcome measures: Associations between gene expression and malignancy were tested using supervised clustering approaches. Results: Ten differentially expressed genes were selected based on messenger RNA (mRNA) expression array data. Contactin 4 (CNTN4) was overexpressed in malignant vs benign tumors [4.62-fold; false discovery rate (FDR), 0.001]. Overexpression at the mRNA level was confirmed using qRT-PCR (2.90-fold, P = 0.02; validation set: 4.26-fold, P = 0.005). Consistent findings were obtained in The Cancer Genome Atlas cohort (2.7-fold; FDR, 0.02). CNTN4 protein was more frequently expressed in malignant than in benign PPGLs by immunohistochemistry (58% vs 17%; P = 0.002). Survival after 7 days of culture under starvation conditions was significantly enhanced in hPheo1 cells transfected with CNTN4 complementary DNA. Conclusion: CNTN4 expression is consistently associated with malignant behavior in PPGLs.

SDHA related tumorigenesis: a new case series and literature review for variant interpretation and pathogenicity.

PURPOSE: To evaluate the role of germline SDHA mutation analysis by (1) comprehensive literature review, (2) description of novel germline SDHA mutations and (3) in silico structural prediction analysis of missense substitutions in SDHA. PATIENTS AND METHODS: A systematic literature review and a retrospective review of the molecular and clinical features of patients identified with putative germline variants in UK molecular genetic laboratories was performed. To evaluate the molecular consequences of SDHA missense variants, a novel model of the SDHA/B/C/D complex was generated and the structural effects of missense substitutions identified in the literature, our UK novel cohort and a further 32 "control missense variants" were predicted by the mCSM computational platform. These structural predictions were correlated with the results of tumor studies and other bioinformatic predictions. RESULTS: Literature review revealed reports of 17 different germline SDHA variants in 47 affected individuals from 45 kindreds. A further 10 different variants in 15 previously unreported cases (seven novel variants in eight patients) were added from our UK series. In silico structural prediction studies of 11 candidate missense germline mutations suggested that most (63.7%) would destabilize the SDHA protomer, and that most (78.1%) rare SDHA missense variants present in a control data set (ESP6500) were also associated with impaired protein stability. CONCLUSION: The clinical spectrum of SDHA-associated neoplasia differs from that of germline mutations in other SDH-subunits. The interpretation of the significance of novel SDHA missense substitutions is challenging. We recommend that multiple investigations (e.g. tumor studies, metabolomic profiling) should be performed to aid classification of rare missense variants before genetic testing results are used to influence clinical management.