Metabolomics and proteomics in pheochromocytoma and paraganglioma: Translating biochemistry and biology to bedside.

The complexity of omes - the key cellular ensembles (genome and epigenome, transcriptome, proteome, and metabolome) - is becoming increasingly understood in terms of big-data analysis, the omics. Amongst these, proteomics provides a global description of quantitative and qualitative alterations of protein expression (or protein abundance in body fluids) in response to physiologic or pathologic processes while metabolomics offers a functional portrait of the physiological state by quantifying metabolite abundances in biological samples. Here, we summarize how different techniques of proteomic and metabolic analysis can be used to define key biochemical characteristics of pheochromocytomas/paragangliomas (PPGL).

Identification of potential molecular targets for the treatment of cluster 1 human pheochromocytoma and paraganglioma via comprehensive proteomic characterization.

Background: Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors. New drug targets and proteins that would assist sensitive PPGL imagining could improve therapy and quality of life of patients with PPGL, namely those with recurrent or metastatic disease. Using a combined proteomic strategy, we looked for such clinically relevant targets among integral membrane proteins (IMPs) upregulated on the surface of tumor cells and non-membrane druggable enzymes in PPGL.

FGF-23 is a biomarker of RV dysfunction and congestion in patients with HFrEF.

There is no biomarker reflecting right ventricular dysfunction in HFrEF patients used in clinical practice. We have aimed to look for a circulating marker of RV dysfunction employing a quantitative proteomic strategy. The Olink Proteomics Multiplex panels (Cardiovascular Disease II, III, Cardiometabolic, and Inflammation Target Panels) identified FGF-23 to be the most differentially abundant (more than 2.