Hypoxia-Inducible Factor 2 Alpha (HIF2α) Inhibitors: Targeting Genetically Driven Tumor Hypoxia.

Tumors driven by deficiency of the VHL gene product, which is involved in degradation of the hypoxia-inducible factor subunit 2 alpha (HIF2α), are natural candidates for targeted inhibition of this pathway. Belzutifan, a highly specific and well-tolerated HIF2α inhibitor, recently received FDA approval for the treatment of nonmetastatic renal cell carcinomas, pancreatic neuroendocrine tumors, and central nervous system hemangioblastomas from patients with von Hippel-Lindau disease, who carry VHL germline mutations. Such approval is a milestone in oncology; however, the full potential, and limitations, of HIF2α inhibition in the clinic are just starting to be explored. Here we briefly recapitulate the molecular rationale for HIF2α blockade in tumors and review available preclinical and clinical data, elaborating on mutations that might be particularly sensitive to this approach. We also outline some emerging mechanisms of intrinsic and acquired resistance to HIF2α inhibitors, including acquired mutations of the gatekeeper pocket of HIF2α and its interacting partner ARNT. Lastly, we propose that the high efficacy of belzutifan observed in tumors with genetically driven hypoxia caused by VHL mutations suggests that a focus on other mutations that similarly lead to HIF2α stabilization, such as those occurring in neuroendocrine tumors with disruptions in the tricarboxylic acid cycle (SDHA/B/C/D, FH, MDH2, IDH2), HIF hydroxylases (EGLN/PHDs), and the HIF2α-encoding gene, EPAS1, are warranted.

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BACKGROUND: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. METHODS: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. RESULTS: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. CONCLUSION: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

A technology assisted precision ketogenic diet intervention for cardio-renal-metabolic health in overweight or obese adults: Protocol for a randomized controlled trial.

BACKGROUND: The obesity epidemic is a public health concern, as it is associated with a variety of chronic conditions. The ketogenic diet has drawn much scientific and public attention. However, implementation is challenging and its effect on cardio-renal-metabolic health is inconclusive. This study will assess the feasibility, acceptability, and preliminary efficacy of a technology-assisted ketogenic diet on cardio-renal-metabolic health. METHODS: This is a single center, 6-month, stratified, randomized controlled trial. A total of 60 overweight/obese adults (18+ years old) will be enrolled, including 20 without type 2 diabetes (T2D) and without chronic kidney disease (CKD); 20 with T2D, but without CKD; and 20 with early-stage CKD. Participants will be stratified based on health conditions and randomized into a ketogenic diet (n = 30) or a low-fat diet group (n = 30). Health education involving diet and physical activity will be delivered both digitally and in-person. Mobile and connected health technologies will be used to track lifestyle behaviors and health indicators, as well as provide weekly feedback. The primary outcome (weight) and the secondary outcomes (e.g., blood pressure, glycemic control, renal health) will be assessed with traditional measurements and metabolomics. DISCUSSION: Mobile and connected health technologies provide new opportunities to improve chronic condition management, health education attendance, planned lifestyle changes and engagement, and health outcomes. The advancement of bioinformatics technology offers the possibility to profile and analyze omics data which may advance our understanding of the underlying mechanisms of intervention effects on health outcomes at the molecular level for personalized and precision lifestyle interventions.

Endocrine and Neuroendocrine Tumors Special Issue-Checkpoint Inhibitors for Adrenocortical Carcinoma and Metastatic Pheochromocytoma and Paraganglioma: Do They Work?

Adrenocortical cancers and metastatic pheochromocytomas are the most common malignancies originating in the adrenal glands. Metastatic paragangliomas are extra-adrenal tumors that share similar genetic and molecular profiles with metastatic pheochromocytomas and, subsequently, these tumors are studied together. Adrenocortical cancers and metastatic pheochromocytomas and paragangliomas are orphan diseases with limited therapeutic options worldwide. As in any other cancers, adrenocortical cancers and metastatic pheochromocytomas and paragangliomas avoid the immune system. Hypoxia-pseudohypoxia, activation of the PD-1/PD-L1 pathway, and/or microsatellite instability suggest that immunotherapy with checkpoint inhibitors could be a therapeutic option for patients with these tumors. The results of clinical trials with checkpoint inhibitors for adrenocortical carcinoma or metastatic pheochromocytoma or paraganglioma demonstrate limited benefits; nevertheless, these results also suggest interesting mechanisms that might enhance clinical responses to checkpoint inhibitors. These mechanisms include the normalization of tumor vasculature, modification of the hormonal environment, and vaccination with specific tumor antigens. Combinations of checkpoint inhibitors with classical therapies, such as chemotherapy, tyrosine kinase inhibitors, radiopharmaceuticals, and/or novel therapies, such as vaccines, should be evaluated in clinical trials.

Insights into Mechanisms of Pheochromocytomas and Paragangliomas Driven by Known or New Genetic Drivers.

Pheochromocytomas and paragangliomas are rare tumors of neural crest origin. Their remarkable genetic diversity and high heritability have enabled discoveries of bona fide cancer driver genes with an impact on diagnosis and clinical management and have consistently shed light on new paradigms in cancer. In this review, we explore unique mechanisms of pheochromocytoma and paraganglioma initiation and management by drawing from recent examples involving rare mutations of hypoxia-related genes VHL, EPAS1 and SDHB, and of a poorly known susceptibility gene, TMEM127. These models expand our ability to predict variant pathogenicity, inform new functional domains, recognize environmental-gene connections, and highlight persistent therapeutic challenges for tumors with aggressive behavior.

Genotype-Phenotype Features of Germline Variants of the TMEM127 Pheochromocytoma Susceptibility Gene: A 10-Year Update.

PURPOSE: This work aimed to evaluate genotype-phenotype associations in individuals carrying germline variants of transmembrane protein 127 gene (TMEM127), a poorly known gene that confers susceptibility to pheochromocytoma (PHEO) and paraganglioma (PGL). DESIGN: Data were collected from a registry of probands with TMEM127 variants, published reports, and public databases. MAIN OUTCOME ANALYSIS: Clinical, genetic, and functional associations were determined. RESULTS: The cohort comprised 110 index patients (111 variants) with a mean age of 45 years (range, 21-84 years). Females were predominant (76 vs 34, P < .001). Most patients had PHEO (n = 94; 85.5%), although PGL (n = 10; 9%) and renal cell carcinoma (RCC, n = 6; 5.4%) were also detected, either alone or in combination with PHEO. One-third of the cases had multiple tumors, and known family history was reported in 15.4%. Metastatic PHEO/PGL was rare (2.8%). Epinephrine alone, or combined with norepinephrine, accounted for 82% of the catecholamine profiles of PHEO/PGLs. Most variants (n = 63) occurred only once and 13 were recurrent (2-12 times). Although nontruncating variants were less frequent than truncating changes overall, they were predominant in non-PHEO clinical presentations (36% PHEO-only vs 69% other, P < .001) and clustered disproportionately within transmembrane regions (P < .01), underscoring the relevance of these domains for TMEM127 function. Integration of clinical and previous experimental data supported classification of variants into 4 groups based on mutation type, localization, and predicted disruption. CONCLUSIONS: Patients with TMEM127 variants often resemble sporadic nonmetastatic PHEOs. PGL and RCC may also co-occur, although their causal link requires further evaluation. We propose a new classification to predict variant pathogenicity and assist with carrier surveillance.