BACKGROUND:Immune checkpoint inhibitors are effective in some cases of lung adenocarcinoma (LUAD). Whole-exome sequencing has revealed that the tumour mutation burden (TMB) is associated with clinical benefits among patients from immune checkpoint inhibitors. Several commercial mutation panels have been developed for estimating the TMB regardless of the cancer type. However, different cancer types have different mutational landscapes; hence, this study aimed to develop a small cancer-type-specific mutation panel for high-accuracy estimation of the TMB of LUAD patients.
METHODS:We developed a small cancer-type-specific mutation panel based on coding sequences (CDSs) rather than genes, for LUAD patients. Using somatic CDSs mutation data from 486 LUAD patients in The Cancer Genome Atlas (TCGA) database, we pre-selected a set of CDSs with mutation states significantly correlated with the TMB, from which we selected a CDS mutation panel with a panel-score most significantly correlated with the TMB, using a genetic algorithm.
RESULTS:A mutation panel containing 106 CDSs of 100 genes with only 0.34 Mb was developed, whose length was much shorter than current commercial mutation panels of 0.80-0.92 Mb. The correlation of this panel with the TMB was validated in two independent LUAD datasets with progression-free survival data for patients treated with nivolumab plus ipilimumab and pembrolizumab immunotherapies, respectively. In both test datasets, survival analyses revealed that patients with a high TMB predicted via the 106-CDS mutation panel with a cut-point of 6.20 mutations per megabase, median panel score in the training dataset, had a significantly longer progression-free survival than those with a low predicted TMB (log-rank p = 0.0018, HR = 3.35, 95% CI 1.51-7.42; log-rank p = 0.0020, HR = 5.06, 95% CI 1.63-15.69). This small panel better predicted the efficacy of immunotherapy than current commercial mutation panels.
CONCLUSIONS:The small-CDS mutation panel of only 0.34 Mb is superior to current commercial mutation panels and can better predict the efficacy of immunotherapy for LUAD patients, and its low cost and time-intensiveness make it more suitable for clinical applications.
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【Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung adenocarcinoma.].
【鉴定编码序列的小突变组以预测免疫疗法对肺腺癌的疗效。】
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DOI：10.1186/s12967-019-02199-6文章类型：杂志文章
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背景：免疫检查点抑制剂在某些肺腺癌（LUAD）病例中有效。全外显子组测序显示，肿瘤突变负担（TMB）与免疫检查点抑制剂对患者的临床益处相关。已经开发了几种商业突变专家组来估计TMB，而与癌症类型无关。然而，不同类型的癌症具有不同的突变态势。因此，本研究旨在开发一种小型的癌症类型特异性突变检测板，用于对LUAD患者的TMB进行高精度估算。
方法：我们为LUAD患者开发了一个基于编码序列（CDS）而非基因的小型癌症类型特异性突变组。利用癌症基因组图谱（TCGA）数据库中486位LUAD患者的体细胞CDS突变数据，我们预先选择了一组突变状态与TMB显着相关的CDS，我们从中选择了得分最高的CDS突变专家组使用遗传算法，与TMB显着相关。
结果：开发了一个包含100个基因的106个CDS的突变小组，仅0.34 Mb，其长度比目前的商业突变小组0.80-0.92 Mb短得多。在两个独立的LUAD数据集中验证了该面板与TMB的相关性，分别针对了用nivolumab联合ipilimumab和pembrolizumab免疫疗法治疗的患者提供无进展生存数据。在这两个测试数据集中，生存分析表明，通过106-CDS突变小组预测的TMB高的患者，每百万碱基的切入点为6.20突变，训练数据集中的中位小组得分，其无进展生存期显着长于无进展生存期。那些预测的TMB较低的人（对数排名p = 0.0018，HR ^ = 3.35，95％CI 1.51-7.42; log-rank p = 0.0020，HR = 5.06，95％CI 1.63-15.69）。这个小小组比目前的商业突变小组更好地预测了免疫疗法的功效。
结论：仅0.34 Mb的小CDS突变面板优于当前的商业突变面板，并且可以更好地预测LUAD患者的免疫疗法的疗效，其低成本和费时的特性使其更适合于临床应用。
方法：我们为LUAD患者开发了一个基于编码序列（CDS）而非基因的小型癌症类型特异性突变组。利用癌症基因组图谱（TCGA）数据库中486位LUAD患者的体细胞CDS突变数据，我们预先选择了一组突变状态与TMB显着相关的CDS，我们从中选择了得分最高的CDS突变专家组使用遗传算法，与TMB显着相关。
结果：开发了一个包含100个基因的106个CDS的突变小组，仅0.34 Mb，其长度比目前的商业突变小组0.80-0.92 Mb短得多。在两个独立的LUAD数据集中验证了该面板与TMB的相关性，分别针对了用nivolumab联合ipilimumab和pembrolizumab免疫疗法治疗的患者提供无进展生存数据。在这两个测试数据集中，生存分析表明，通过106-CDS突变小组预测的TMB高的患者，每百万碱基的切入点为6.20突变，训练数据集中的中位小组得分，其无进展生存期显着长于无进展生存期。那些预测的TMB较低的人（对数排名p = 0.0018，HR ^ = 3.35，95％CI 1.51-7.42; log-rank p = 0.0020，HR = 5.06，95％CI 1.63-15.69）。这个小小组比目前的商业突变小组更好地预测了免疫疗法的功效。
结论：仅0.34 Mb的小CDS突变面板优于当前的商业突变面板，并且可以更好地预测LUAD患者的免疫疗法的疗效，其低成本和费时的特性使其更适合于临床应用。
