Personalized Management of Pheochromocytoma and Paraganglioma

Pheochromocytomas/paragangliomas are characterized by a unique molecular landscape that allows their assignment to clusters based on underlying genetic alterations. With around 30% to 35% of Caucasian patients (a lower percentage in the Chinese population) showing germline mutations in susceptibility genes, pheochromocytomas/paragangliomas have the highest rate of heritability among all tumors. A further 35% to 40% of Caucasian patients (a higher percentage in the Chinese population) are affected by somatic driver mutations. Thus, around 70% of all patients with pheochromocytoma/paraganglioma can be assigned to 1 of 3 main molecular clusters with different phenotypes and clinical behavior. Krebs cycle/VHL/EPAS1-related cluster 1 tumors tend to a noradrenergic biochemical phenotype and require very close follow-up due to the risk of metastasis and recurrence. In contrast, kinase signaling-related cluster 2 tumors are characterized by an adrenergic phenotype and episodic symptoms, with generally a less aggressive course. The clinical correlates of patients with Wnt signaling-related cluster 3 tumors are currently poorly described, but aggressive behavior seems likely. In this review, we explore and explain why cluster-specific (personalized) management of pheochromocytoma/paraganglioma is essential to ascertain clinical behavior and prognosis, guide individual diagnostic procedures (biochemical interpretation, choice of the most sensitive imaging modalities), and provide personalized management and follow-up. Although cluster-specific therapy of inoperable/metastatic disease has not yet entered routine clinical practice, we suggest that informed personalized genetic-driven treatment should be implemented as a logical next step. This review amalgamates published guidelines and expert views within each cluster for a coherent individualized patient management plan.

Automated summary

Pheochromocytomas/paragangliomas have high heritability, with 70% of patients falling into 3 main molecular clusters with distinct phenotypes and clinical behaviors. Personalized management strategies are essential for accurate diagnosis and effective treatment in different clusters.