Incremental utility of expanded mutation panel when used in combination with microRNA classification in indeterminate thyroid nodules
Incremental utility of expanded mutation panel when used in combination with microRNA classification in indeterminate thyroid nodules
复制标题
DOI：
10.1002/dc.24328
复制
发表时间：
2019-11-01
影响因子：
1.3
通讯作者：
Finkelstein, Sydney D.
中科院分区：
文献类型：
--
作者：
Jackson, Sara;Kumar, Gyanendra;Finkelstein, Sydney D.
引言评估了集中和扩展突变组与microRNA风险分类组合使用扩展组的增量效用。方法：对接受聚焦突变面板（ThyGenX（R））或扩展突变面板（ThyGeNEXT（R））的强和弱致癌驱动突变和融合的患者的分子结果进行审查。检查了预测恶性肿瘤的microRNA结果（ThyraMIR（R）），包括对恶性肿瘤高度特异性的强阳性结果。结果回顾了12993例连续患者的结果（重点组= 8619，扩展组= 4374）。扩大的面板将强驱动程序的检测增加了8%（P < .001），其中BRAFV600E和TERT启动子是最常见的。强驱动因子与阳性microRNA结果高度相关，其中90%为强阳性。扩大的面板增加了4%（P <0.001）的共存驱动程序的检测，与TERT是最常见的合作伙伴，往往与RAS配对。它增加了对弱驱动程序的检测，其中RAS和GNAS是最常见的。49%的驱动因子较弱的结节具有阳性microRNA结果，其中33%为强阳性。扩大组还将缺乏突变和融合的结节数量减少了15%（P < .001），8%的结节具有阳性microRNA结果，其中22%为强阳性。结论：使用包括不太常见的突变和融合的扩展突变面板，当与microRNA分类结合使用时，可以提供更大的效用，这有助于在风险不确定的情况下识别恶性肿瘤的高风险，因为仅存在弱驱动程序或缺乏所有驱动程序。
INTRODUCTION Focused and expanded mutation panels were assessed for the incremental utility of using an expanded panel in combination with microRNA risk classification. METHODS Molecular results were reviewed for patients who underwent either a focused mutation panel (ThyGenX (R)) or an expanded mutation panel (ThyGeNEXT (R)) for strong and weak oncogenic driver mutations and fusions. microRNA results (ThyraMIR (R)) predictive of malignancy, including strong positive results highly specific for malignancy, were examined. RESULTS Results of 12 993 consecutive patients were reviewed (focused panel = 8619, expanded panel = 4374). The expanded panel increased detection of strong drivers by 8% (P < .001), with BRAFV600E and TERT promoters being the most common. Strong drivers were highly correlated with positive microRNA results of which 90% were strongly positive. The expanded panel increased detection of coexisting drivers by 4% (P < .001), with TERT being the most common partner often paired with RAS. It increased the detection of weak drivers, with RAS and GNAS being the most common. 49% of nodules with weak drivers had positive microRNA results of which 33% were strongly positive. The expanded panel also decreased the number of nodules lacking mutations and fusions by 15% (P < .001), with 8% of nodules having positive microRNA results of which 22% were strongly positive. CONCLUSIONS Using expanded mutation panels that include less common mutations and fusions can offer increased utility when used in combination with microRNA classification, which helps to identify high risk of malignancy in the cases where risk is otherwise uncertain due to the presence of only weak drivers or the absence of all drivers.