AI Article Synopsis

  • Genetic diagnosis for pheochromocytoma and paraganglioma is crucial, as around 80% of cases have identifiable driver mutations, prompting the need for efficient testing methods.
  • This study focused on optimizing targeted next-generation sequencing (NGS) to analyze 18 key PPGL genes in both germline and tumor DNA, validating two customized NGS assays with a diverse group of 453 patients.
  • The NGS assays demonstrated over 99% sensitivity and identified numerous mutations, including 89 pathogenic mutations, proving to be a reliable alternative to traditional sequencing methods and useful for patients with unclear clinical histories.

Article Abstract

Genetic diagnosis is recommended for all pheochromocytoma and paraganglioma (PPGL) cases, as driver mutations are identified in approximately 80% of the cases. As the list of related genes expands, genetic diagnosis becomes more time-consuming, and targeted next-generation sequencing (NGS) has emerged as a cost-effective tool. This study aimed to optimize targeted NGS in PPGL genetic diagnostics. A workflow based on two customized targeted NGS assays was validated to study the 18 main PPGL genes in germline and frozen tumor DNA, with one of them specifically directed toward formalin-fixed paraffin-embedded tissue. The series involved 453 unrelated PPGL patients, of whom 30 had known mutations and were used as controls. Partial screening using Sanger had been performed in 275 patients. NGS results were complemented with the study of gross deletions. NGS assay showed a sensitivity ≥99.4%, regardless of DNA source. We identified 45 variants of unknown significance and 89 pathogenic mutations, the latter being germline in 29 (7.2%) and somatic in 58 (31.7%) of the 183 tumors studied. In 37 patients previously studied by Sanger sequencing, the causal mutation could be identified. We demonstrated that both assays are an efficient and accurate alternative to conventional sequencing. Their application facilitates the study of minor PPGL genes, and enables genetic diagnoses in patients with incongruent or missing clinical data, who would otherwise be missed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500830PMC
http://dx.doi.org/10.1016/j.jmoldx.2017.04.009DOI Listing

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