y Optimizing Genetic Workup in Pheochromocytoma and Paraganglioma by Integrating Diagnostic and Research Approaches
y Optimizing Genetic Workup in Pheochromocytoma and Paraganglioma by Integrating Diagnostic and Research Approaches
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DOI：
10.3390/cancers11060809
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发表时间：
2019-06-01
期刊：
影响因子：
5.2
通讯作者：
Klink, Barbara
中科院分区：
文献类型：
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作者：
Gieldon, Laura;William, Doreen;Klink, Barbara
嗜铬细胞瘤和副神经节瘤（PPGL）是一种罕见的神经内分泌肿瘤，具有很强的遗传背景和很大的遗传异质性。确定潜在的遗传原因对于患者及其家属的管理至关重要，因为它有助于区分遗传性和散发性病例。为了提高诊断和临床管理，我们定制了一个基于富集的综合多基因下一代测序面板，适用于肿瘤组织和血液样本的分析。我们将该面板应用于肿瘤样本，并将其性能与我们目前的常规诊断方法进行比较。在德国德累斯顿的一个中心，对65名未选择的PPGL患者的血液样本进行了11个PPGL易感基因的常规诊断测序。在19例（29.2%）患者中发现易感种系突变。使用专用PPGL小组对28例PPGL肿瘤组织进行分析，发现21例（75%）已知PPGL易感基因中存在致病性或可能致病性变异，包括IDH2、ATRX和HRAS突变。这些突变提示散发性肿瘤的发生。我们的研究结果表明，PPGLs分子肿瘤检测的扩展和患者管理的改进对诊断有好处。该方法有望用于确定支持治疗决策的预后生物标志物。
Pheochromocytomas and paragangliomas (PPGL) are rare neuroendocrine tumors with a strong hereditary background and a large genetic heterogeneity. Identification of the underlying genetic cause is crucial for the management of patients and their families as it aids differentiation between hereditary and sporadic cases. To improve diagnostics and clinical management we tailored an enrichment based comprehensive multi-gene next generation sequencing panel applicable to both analyses of tumor tissue and blood samples. We applied this panel to tumor samples and compared its performance to our current routine diagnostic approach. Routine diagnostic sequencing of 11 PPGL susceptibility genes was applied to blood samples of 65 unselected PPGL patients at a single center in Dresden, Germany. Predisposing germline mutations were identified in 19 (29.2%) patients. Analyses of 28 PPGL tumor tissues using the dedicated PPGL panel revealed pathogenic or likely pathogenic variants in known PPGL susceptibility genes in 21 (75%) cases, including mutations in IDH2, ATRX and HRAS. These mutations suggest sporadic tumor development. Our results imply a diagnostic benefit from extended molecular tumor testing of PPGLs and consequent improvement of patient management. The approach is promising for determination of prognostic biomarkers that support therapeutic decision-making.