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  • Author: Jose Viana Lima-Jr x
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Jose Viana Lima-Jr, Nilza Maria Scalissi, Kelly Cristina dr Oliveira, Susan C. Lindsey, Caroline Olivati, Elisa Napolitano Ferreira, and Claudio E. Kater

Pheochromocytoma/paraganglioma (PPGL) are rare neuroendocrine tumors carrying 25-40% pathogenic germline gene variants (PGV). We evaluated clinical, laboratory, and germline molecular profile of 115 patients with pathologic (fourteen patients were relatives from 8 different families recruited for genetic survey) confirmed PPGL followed in our institution. Patients with classic MEN2A/MEN2B phenotypes and at-risk relatives underwent direct analysis of RET proto-oncogene, and the remained had samples submitted to complete Next Generation Sequencing (NGS) aiming 23 PPGL-related genes: ATM, ATR, CDKN2A, EGLN1, FH, HRAS, KIF1B, KMT2D, MAX, MDH2, MERTK, MET, NF1, PIK3CA, RET, SDHA, SDHAF2, SDHB, SDHC, SDHD, TMEM127, TP53, and VHL. We also developed a clinical judgment score (CJS) to determine the probability of patients having a potentially hereditary disease. The resulting genetic landscape showed that 67 patients (58.3%) had variants in at least one gene: 34 (50.7%) had exclusively pathogenic or likely pathogenic variants, 13 (19.4%) pathogenic or likely pathogenic variants and VUS and 20 (29.8%) carried only VUS. PGV were found in RET (N=18; 38.3%), VHL (N=10; 21.3%), SDHB and NF1 (N=8; 17% each), and MAX, SDHD, TMEM127, and TP53 (N=1; 2.1% each). Direct genetic testing disclosed 91.3% sensitivity, 81.2% specificity, and 76.4% and 93.3% positive (PPV) and negative (NPV) predictive values, respectively. The CJS to identify patients who would not benefit from genetic testing had 75% sensitivity, 96.4% specificity, and 60% and 98.2% PPV and NPV, respectively. In summary, the landscape of PPGL germline gene variants from 115 Brazilian patients resulted in slightly higher prevalent pathogenic and likely pathogenic variants, especially in the RET gene. We suggest a CJS to identify PPGL patients who would not require initial genetic evaluation, improving test specificity and reducing costs.