Pheochromocytomas (PHEOs) and paragangliomas (PGLs) are rare neuroendocrine tumors that arise from chromaffin cells. PHEOs arise from the adrenal medulla, whereas PGLs arise from the neural crest localized outside the adrenal gland. Approximately 40% of all cases of PPGLs (pheochromocytomas/paragangliomas) are associated with germline mutations and 30–40% display somatic driver mutations. The mutations associated with PPGLs can be classified into three groups. The pseudohypoxic group or cluster I includes the following genes: SDHA, SDHB, SDHC, SDHD, SDHAF2, FH, VHL, IDH1/2, MHD2, EGLN1/2 and HIF2/EPAS; the kinase group or cluster II includes RET, NF1, TMEM127, MAX and HRAS; and the Wnt signaling group or cluster III includes CSDE1 and MAML3. Underlying mutations can help understand the clinical presentation, overall prognosis and surveillance follow-up. Here we are discussing the new genetic insights of PPGLs.

Studies involving two methods for measuring a continuous response are regularly conducted in health sciences to evaluate agreement of a method with itself and agreement between methods. Notwithstanding their wide usage, the design of such studies, in particular, the sample size determination, has not been addressed in the literature when the goal is the simultaneous evaluation of intra- and inter-method agreement. We fill this need by developing a simulation-based Bayesian methodology for determining sample sizes in a hierarchical model framework. Unlike a frequentist approach, it takes into account uncertainty in parameter estimates. This methodology can be used with any scalar measure of agreement available in the literature. We demonstrate this for four currently used measures. The proposed method is applied to an ongoing proteomics project, where we use pilot data to determine the number of individuals and the number of replications needed to evaluate the agreement between two methods for measuring protein ratios. We also apply our method to determine the sample size for an experiment involving measurement of blood pressure.

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy of the adrenal gland with an unfavorable prognosis. It is rare in the pediatric population, with an incidence of 0.2-0.3 patients per million in patients under 20 years old. It is primarily associated with Li-Fraumeni and Beckwith-Wiedemann tumor predisposition syndromes in children. The incidence of pediatric ACC is 10-15fold higher in southern Brazil due to a higher prevalence of TP53 mutation associated with Li-Fraumeni syndrome in that population. Current treatment protocols are derived from adult ACC and consist of surgery and/or chemotherapy with etoposide, doxorubicin, and cisplatin (EDP) with mitotane. Limited research has been reported on other treatment modalities for pediatric ACC, including mitotane, pembrolizumab, cabozantinib, and chimeric antigen receptor autologous cell (CAR-T) therapy.

Gastroenteropancreatic neuroendocrine neoplasms (NENs) are a heterogenous group of tumors that are incurable when metastatic, regardless of grade. The aim of this article is to understand tumor heterogeneity and grade progression as possible contributors to drug resistance in gastroentropancreatic neuroendocrine tumors (GEP-NETs). Heterogeneity has been observed in the genetic, pathological, and imaging features of these tumors at baseline. Diagnostic challenges related to tumor sampling and the potential for changes in grade over time further confound our ability to optimize therapy for patients. A better understanding of NEN biology and tumor heterogeneity at baseline and over time could lead to the development of new therapeutic avenues.