Pheochromocytoma and Paraganglioma: Current Functional and Future Molecular Imaging

Paragangliomas are neural crest-derived tumors, arising either from chromaffin sympathetic tissue (in adrenal, abdominal, intra-pelvic, or thoracic paraganglia) or from parasympathetic tissue (in head and neck paraganglia). They have a specific cellular metabolism, with the ability to synthesize, store, and secrete catecholamines (although most head and neck paragangliomas do not secrete any catecholamines). This disease is rare and also very heterogeneous, with various presentations (e.g., in regards to localization, multifocality, potential to metastasize, biochemical phenotype, and genetic background). With growing knowledge, notably about the pathophysiology and genetic background, guidelines are evolving rapidly. In this context, functional imaging is a challenge for the management of paragangliomas. Nuclear imaging has been used for exploring paragangliomas for the last three decades, with MIBG historically as the first-line exam. Tracers used in paragangliomas can be grouped in three different categories. Agents that specifically target catecholamine synthesis, storage, and secretion pathways include: 123 and 131I-metaiodobenzylguanidine (123/131I-MIBG), 18F-fluorodopamine (18F-FDA), and 18F-fluorodihydroxyphenylalanine (18F-FDOPA). Agents that bind somatostatin receptors include 111In-pentetreotide and 68Ga-labeled somatostatin analog peptides (68Ga-DOTA-TOC, 68Ga-DOTA-NOC, 68Ga-DOTA-TATE). The non-specific agent most commonly used in paragangliomas is 18F-fluorodeoxyglucose (18F-FDG). This review will first describe conventional scintigraphic exams that are used for imaging paragangliomas. In the second part we will emphasize the interest in new PET approaches (specific and non-specific), considering the growing knowledge about genetic background and pathophysiology, with the aim of understanding how tumors behave, and optimally adjusting imaging technique for each tumor type

Attention Deficit Hyperactivity Disorder in Pediatric Patients with Pheochromocytoma and Paraganglioma.

The aim of the study is to evaluate if there is an association between attention deficit hyperactivity disorder (ADHD) and the diagnosis of pheochromocytoma/paraganglioma (PHEO/PGL) in pediatric patients. A case series study of 43 patients under the age of 18 with PHEO/PGL tumors who were evaluated at the National Institute of Health between January 2006 and May 2014 is reported. Prior diagnosis of ADHD and treatment course with stimulant medications was recorded. Patient symptoms, catecholamine and metanephrine levels, tumor characteristics, and genetic analyses for syndromes associated with PHEO/PGL were evaluated. A chi-squared test was used to assess the prevalence of ADHD in the PHEO/PGL patients compared to the general population. Nine out of 43 (21%) of patients diagnosed with PHEO/PGL had been diagnosed with ADHD prior to tumor identification. Four of the 9 patients had been treated with amphetamine, dextroamphetamine, and/or methylphenidate, potentially exacerbating an adrenergic crisis. In addition, 4 patients exhibited hypertension at the initial diagnosis of their PHEO/PGL. Three patients had resolution of their ADHD symptoms after successful surgical removal of PHEO/PGL. Our study found a prevalence of ADHD in 21% of our PHEO/PGL patients, significantly higher than 7.2% seen in the general pediatric population. Symptoms of anxiety and difficulty in concentration in these patients may have been related to their underlying PHEO/PGL and were not recognized as part of the constellation of symptoms in a child with PHEO/PGL. In pediatric patients with hypertension and ADHD symptomatology, an evaluation to rule out PHEO/PGL is warranted prior to treatment with stimulant medications

The role of the P1BS element containing promoter-driven genes in Pi transport and homeostasis in plants

Inorganic phosphate (Pi) is an easily accessible form of phosphorus for plants. Plant Pi uptake is usually limited by slow Pi diffusion through the soil which adsorps the Pi quite strong. That is why plants have developed mechanisms to increase Pi availability. There are abiotic (phosphate level) and biotic (mycorrhiza) factors regulating the expression of Pi-responsive genes. Transcription factors binding to the promoters of Pi-responsive genes activate different pathways of Pi transport, distribution and homeostasis maintenance. Pi metabolism involves proteins, as well as microRNAs and other noncoding RNAs

Detecting Latin-Based Medical Terminology in Croatian Texts

No matter what the main language of texts in the medical domain is, there is always an evidence of the usage of Latin-derived words and formative elements in terminology development. Generally speaking, this usage presents language-specific morpho-semantic behaviors in forming both technical-scientific and common-usage words. Nevertheless, this usage of Latin in Croatian medical texts does not seem consistent due to the fact that diferent mechanisms of word formation may be applied to the same term. In our pursuit to map all the diferent occurrences of the same concept to only one, we propose a model designed within NooJ and based on dictionaries and morphological grammars. Starting from the manual detection of nouns and their variations, we recognize some word formation mechanisms and develop grammars suitable to recognize Latinisms and Croatinized Latin medical terminology

Primary fibroblast co-culture stimulates growth and metabolism in Sdhb-impaired mouse pheochromocytoma MTT cells

Pheochromocytomas and paragangliomas (PGLs) due to mutations of succinate dehydrogenase (SDH) B, a subunit of the SDH complex with a role in the Krebs cycle and the respiratory chain, tend to be larger at diagnosis and more prone to metastatic disease than other tumors. This presentation contrasts with the behavior of some cell line models of SDHB impairment, which show reduced growth compared to wild type. We hypothesize that reduced growth of SDHB-impaired monolayer culture models might reflect lack of support from sources within the tumor microenvironment. The present study therefore investigates how the microenvironment, modeled here by fibroblast co-culture, modulates cell metabolism, growth and invasion in an Sdhb-impaired mouse pheochromocytoma cell line. We employed two different constructs of short hairpin RNA to knockdown Sdhb and compared growth in a monolayer with and without fibroblast co-culture. Sdhb-silenced cells showed functional impairment of SDH with elevated succinate to fumarate ratio and decreased oxidative capacity. Cell growth was delayed with an increase in doubling time of 2 h or 20 h. Clonogenic cell survival and viability, on the other hand, were either unchanged or increased compared to control. In standard monolayer culture, no differences in pro-metastatic features were present. Co-culture with primary mouse fibroblast reversed the difference of proliferation between control and Sdhb knockdown but was unable to significantly influence invasiveness under these culture conditions. Metabolic studies identified that lactate secreted by fibroblasts was taken up preferentially by Sdhb-silenced cells. In summary, the present study identified a potential role for the tumor microenvironment in influencing phenotypic features of SDHB-mutated PGLs, providing a basis for the use of therapies targeted towards the tumor microenvironment

Biochemical Diagnosis and Localization of Pheochromocytoma

Pheochromocytomas can have a highly variable presentation, making diagnosis challenging. To think of the tumor represents the crucial initial step, but establishing the diagnosis requires biochemical evidence of excessive catecholamine production and imaging studies to localize the source. Currently, however, there exist no generally agreed upon guidelines based on which tests and testing algorithms should be used to confirm and locate or exclude a suspected pheochromocytoma. Choice of biochemical tests and imaging studies instead usually depends on institutional experience. At the First International Symposium on Pheochromocytoma (ISP2005), held in Bethesda in October 2005, a panel of experts and patient representatives discussed current problems and available options for tumor diagnosis and localization and formulated recommendations, which were subsequently agreed upon by those in attendance at the meeting. This article summarizes the discussion and recommendations derived from that session.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72111/1/annals.1353.038.pd

Determinants of disease-specific survival in patients with and without metastatic pheochromocytoma and paraganglioma

BACKGROUND: Pheochromocytomas and paragangliomas (PPGLs) have a heterogeneous prognosis, the basis of which remains unclear. We, therefore, assessed disease-specific survival (DSS) and potential predictors of progressive disease in patients with PPGLs and head/neck paragangliomas (HNPGLs) according to the presence or absence of metastases. METHODS: This retrospective study included 582 patients with PPGLs and 57 with HNPGLs. DSS was assessed according to age, location and size of tumours, recurrent/metastatic disease, genetics, plasma metanephrines and methoxytyramine. RESULTS: Among all patients with PPGLs, multivariable analysis indicated that apart from older age (HR = 5.4, CI = 2.93-10.29, P < 0.0001) and presence of metastases (HR = 4.8, CI = 2.41-9.94, P < 0.0001), shorter DSS was also associated with extra-adrenal tumour location (HR = 2.6, CI = 1.32-5.23, P = 0.0007) and higher plasma methoxytyramine (HR = 1.8, CI = 1.11-2.85, P = 0.0170) and normetanephrine (HR = 1.8, CI = 1.12-2.91, P = 0.0160). Among patients with HNPGLs, those with metastases presented with longer DSS compared to patients with metastatic PPGLs (33.4 versus 20.2 years, P < 0.0001) and only plasma methoxytyramine (HR = 13, CI = 1.35-148, P = 0.0380) was an independent predictor of DSS. For patients with metastatic PPGLs, multivariable analysis revealed that apart from older age (HR = 6.2, CI = 3.20-12.20, P < 0.0001), shorter DSS was associated with the presence of synchronous metastases (HR = 4.9, CI = 2.78-8.80, P < 0.0001), higher plasma methoxytyramine (HR = 2.4, CI = 1.44-4.14, P = 0.0010) and extensive metastatic burden (HR = 2.1, CI = 1.07-3.79, P = 0.0290). CONCLUSIONS: DSS among patients with PPGLs/HNPGLs relates to several presentations of the disease that may provide prognostic markers. In particular, the independent associations of higher methoxytyramine with shorter DSS in patients with HNPGLs and metastatic PPGLs suggest the utility of this biomarker to guide individualized management and follow-up strategies in affected patients

Current Trends in Functional Imaging of Pheochromocytomas and Paragangliomas

Most pheochromocytomas/paragangliomas should be evaluated with anatomical imaging (computed tomography or magnetic resonance imaging) followed by functional imaging (nuclear medicine modalities). Functional imaging assures that the tumor is indeed a pheochromocytoma/paraganglioma and enables more thorough localization, especially detecting as many lesions as possible (in particular for metastatic disease). Functional imaging for pheochromocytomas/paragangliomas, can use radiolabled ligands specific for pathways of synthesis, metabolism, and inactivation of catecholamines or nonspecific ligands. In an overview of the available nuclear medicine modalities, we summarize the accumulated experience and recommend when functional imaging should be applied to patients with pheochromocytoma/paraganglioma.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74881/1/annals.1353.041.pd

Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort

BACKGROUND Pheochromocytomas and paragangliomas have up to a 20% rate of metastatic disease that cannot be reliably predicted. This study prospectively assessed whether the dopamine metabolite, methoxytyramine, might predict metastatic disease, whether predictions might be improved using machine learning models that incorporate other features, and how machine learning-based predictions compare with predictions made by specialists in the field. METHODS In this machine learning modelling study, we used cross-sectional cohort data from the PMT trial, based in Germany, Poland, and the Netherlands, to prospectively examine the utility of methoxytyramine to predict metastatic disease in 267 patients with pheochromocytoma or paraganglioma and positive biochemical test results at initial screening. Another retrospective dataset of 493 patients with these tumors enrolled under clinical protocols at National Institutes of Health (00-CH-0093) and the Netherlands (PRESCRIPT trial) was used to train and validate machine learning models according to selections of additional features. The best performing machine learning models were then externally validated using data for all patients in the PMT trial. For comparison, 12 specialists provided predictions of metastatic disease using data from the training and external validation datasets. FINDINGS Prospective predictions indicated that plasma methoxytyramine could identify metastatic disease at sensitivities of 52% and specificities of 85%. The best performing machine learning model was based on an ensemble tree classifier algorithm that used nine features: plasma methoxytyramine, metanephrine, normetanephrine, age, sex, previous history of pheochromocytoma or paraganglioma, location and size of primary tumours, and presence of multifocal disease. This model had an area under the receiver operating characteristic curve of 0·942 (95% CI 0·894-0·969) that was larger (p<0·0001) than that of the best performing specialist before (0·815, 0·778-0·853) and after (0·812, 0·781-0·854) provision of SDHB variant data. Sensitivity for prediction of metastatic disease in the external validation cohort reached 83% at a specificity of 92%. INTERPRETATION Although methoxytyramine has some utility for prediction of metastatic pheochromocytomas and paragangliomas, sensitivity is limited. Predictive value is considerably enhanced with machine learning models that incorporate our nine recommended features. Our final model provides a preoperative approach to predict metastases in patients with pheochromocytomas and paragangliomas, and thereby guide individualised patient management and follow-up. FUNDING Deutsche Forschungsgemeinschaft