Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice.
Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice.
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全面的癌症基因面板可用于估计突变负荷，并在临床实践中预测PD-1阻滞的临床益处。
DOI：
10.18632/oncotarget.5950
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发表时间：
2015-10-27
期刊：
影响因子：
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通讯作者：
Camargo AA
中科院分区：
文献类型：
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作者：
Campesato LF;Barroso-Sousa R;Jimenez L;Correa BR;Sabbaga J;Hoff PM;Reis LF;Galante PA;Camargo AA
癌症基因组（CGP）已经用于临床实践，以将肿瘤的遗传特征与现有的靶向治疗相匹配。我们的目的是确定CGP是否也可以用于估计肿瘤突变负荷并预测PD-1和CTLA-4检查点阻断治疗的临床益处。Snyder et al. 2014和Rizvi et al. 2015分别发表的从黑色素瘤和非小细胞肺癌（NSCLC）患者中获得的全外显子组测序（WES）突变数据用于选择基础医学小组（FM-CGP）和我们自己的机构小组（HSL-CGP）中包含的基因中发生的非同义体细胞突变。使用两个组计算每例患者的CGRP突变负荷，并与原始文章中定义和报告的临床结局相关。在表现出对PD-1阻断的持久临床获益（DCB）的NSCLC患者中观察到更高的CGP突变负荷（FM-CGP P=0.03，HSL-CGP P=0.01）。我们还观察到，69%的高CGP突变负荷患者经历了DCB对PD-1的阻断，而20%的低CGP突变负荷患者（FM-CGP和HSL-CGP P=0.01）。值得注意的是，DCB的CGRP突变负荷的预测准确性与WES测序估计的准确性无统计学差异（P=0.73）。此外，高CGP突变负荷与接受PD-1阻断治疗的患者的无进展生存期（PFS）显著相关（FM-CGP P=0.005，HR 0.27，95%IC 0.105至0.669; HSL-CGP P=0.008，HR 0.29，95%IC 0.116至0.719）。没有观察到CGRP突变负荷与CTLA-4阻断的临床益处之间的类似关联。总之，我们的数据表明，CGP可用于估计突变负荷并预测PD-1阻断的临床益处，其准确性与使用WES报告的准确性相似。
Cancer gene panels (CGPs) are already used in clinical practice to match tumor's genetic profile with available targeted therapies. We aimed to determine if CGPs could also be applied to estimate tumor mutational load and predict clinical benefit to PD-1 and CTLA-4 checkpoint blockade therapy. Whole-exome sequencing (WES) mutation data obtained from melanoma and non-small cell lung cancer (NSCLC) patients published by Snyder et al. 2014 and Rizvi et al. 2015, respectively, were used to select nonsynonymous somatic mutations occurring in genes included in the Foundation Medicine Panel (FM-CGP) and in our own Institutional Panel (HSL-CGP). CGP-mutational load was calculated for each patient using both panels and was associated with clinical outcomes as defined and reported in the original articles. Higher CGP-mutational load was observed in NSCLC patients presenting durable clinical benefit (DCB) to PD-1 blockade (FM-CGP P=0.03, HSL-CGP P=0.01). We also observed that 69% of patients with high CGP-mutational load experienced DCB to PD-1 blockade, as compared to 20% of patients with low CGP-mutational load (FM-CGP and HSL-CGP P=0.01). Noteworthy, predictive accuracy of CGP-mutational load for DCB was not statistically different from that estimated by WES sequencing (P=0.73). Moreover, a high CGP-mutational load was significantly associated with progression-free survival (PFS) in patients treated with PD-1 blockade (FM-CGP P=0.005, HR 0.27, 95% IC 0.105 to 0.669; HSL-CGP P=0.008, HR 0.29, 95% IC 0.116 to 0.719). Similar associations between CGP-mutational load and clinical benefit to CTLA-4 blockade were not observed. In summary, our data reveals that CGPs can be used to estimate mutational load and to predict clinical benefit to PD-1 blockade, with similar accuracy to that reported using WES.