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Iñigo Landa and Mercedes Robledo

It is widely accepted that thyroid cancer is strongly determined by the individual genetic background. In this regard, it is expected that sporadic thyroid cancer is the result of multiple low- to moderate-penetrance genes interacting with each other and with the environment, thus modulating individual susceptibility. In the last years, an important number of association studies on thyroid cancer have been published, trying to determine this genetic contribution. The aim of this review is to provide a comprehensive and critical evaluation of the associations reported so far in thyroid cancer susceptibility in case–control studies performed in both non-medullary (papillary and follicular) and medullary thyroid cancers, including their potential strengths and pitfalls. We summarize the genetic variants reported to date, and stress the importance of validating the results in independent series and assessing the functional role of the associated loci.

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Alberto Cascón, Bruna Calsina, María Monteagudo, Sara Mellid, Alberto Díaz-Talavera, Maria Currás-Freixes, and Mercedes Robledo

The genetics of pheochromocytoma and paraganglioma (PPGL) has become increasingly complex over the last two decades. The list of genes involved in the development of these tumors has grown steadily, and there are currently more than 20 driver genes implicated in either the hereditary or the sporadic nature of the disease. Although genetic diagnosis is achieved in about 75–80% of patients, genetic etiology remains unexplained in a significant percentage of cases. Patients lacking a genetic diagnosis include not only those with apparently sporadic PPGL but also patients with a family history of the disease or with multiple tumors, that meet the criteria to be considered as candidates for carrying germline mutations in yet undiscovered genes. Mutations in known PPGL genes deregulate three main signaling pathways (hypoxia, kinase signaling, and Wnt-signaling pathways), which could be the starting point for the development of personalized treatment for PPGL patients. Furthermore, the integration of results from several genomic high-throughput platforms enables the discovery of regulatory mechanisms that cannot be identified by analyzing each piece of information separately. These strategies are powerful tools for elucidating optimal therapeutic options based on molecular biomarkers in PPGL and represent an important step toward the achievement of precision medicine for patients with metastatic PPGL.