Genotype-phenotype correlations in pheochromocytoma and paraganglioma
AffiliationDepartment of Medical Sciences, Uppsala Universitet, Uppsala, 75185, Sweden
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AbstractPheochromocytoma and paraganglioma (PPGL) can be divided into at least four molecular subgroups. Whether such categorizations are independent factors for prognosis or metastatic disease is unknown. We performed a systematic review and individual patient meta-analysis aiming to estimate if driver mutation status can predict metastatic disease and survival. Driver mutations were used to categorize patients accordingly to three different molecular systems: two subgroups (SDHB mutated or wild type), three subgroups (pseudohypoxia, kinase signaling or Wnt/unknown) and four subgroups (tricarboxylic acid cycle, VHL/EPAS1, kinase signaling or Wnt/unknown). Twenty-one studies and 703 patients were analyzed. Multivariate models for association with metastasis showed correlation with SDHB mutation (OR 5.68 [95% CI 1.79-18.06]) as well as norepinephrine (OR 3.01 [95% CI 1.02-8.79]) and dopamine (OR 6.39 [95% CI 1.62-25.24]) but not to PPGL location. Other molecular systems were not associated with metastasis. In multivariate models for association with survival, age (HR 1.04 [95% CI 1.02-1.06]) and metastases (HR 6.13 [95% CI 2.86-13.13]) but neither paraganglioma or SDHB mutation remained significant. Other molecular subgroups did not correlate with survival. We conclude that molecular categorization accordingly to SDHB provided independent information on the risk of metastasis. Driver mutations status did not correlate independently with survival. These data may ultimately be used to guide current and future risk stratification of PPGL.
CitationCrona J, Lamarca A, Ghosal S, Welin S, Skogseid B, Pacak K. Genotype-phenotype correlations in pheochromocytoma and paraganglioma. Endocr Relat Cancer. 2019.
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