A scalable solution for tumor mutational burden from formalinfixed, paraffin-embedded samples using the Oncomine Tumor Mutation Load Assay
A scalable solution for tumor mutational burden from formalinfixed, paraffin-embedded samples using the Oncomine Tumor Mutation Load Assay
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DOI：
10.21037/tlcr.2018.08.01
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发表时间：
2018-12-01
影响因子：
4
通讯作者：
Hyland, Fiona
中科院分区：
文献类型：
--
作者：
Chaudhary, Ruchi;Quagliata, Luca;Hyland, Fiona
背景：肿瘤突变负荷（TMB）是免疫检查点抑制剂越来越重要的生物标志物。最近的出版物已经描述了在几种癌症类型中高TMB与对单一和组合免疫疗法的客观应答之间的强关联。现有的方法来估计TMB需要大量的输入DNAs，这可能并不总是可用的。方法：在这项研究中，我们开发了一种方法来估计TMB使用的Oncomine肿瘤突变负荷（TML）检测与20纳克的DNA，我们的特点是这种方法的性能对各种福尔马林固定，石蜡包埋（FFPE）的研究样品的几种癌症类型。我们通过与具有已知事实的对照样品的比较来测量TML工作流程的分析性能，并且我们将性能与使用匹配的正常样品来去除种系变体的正交方法进行比较。我们对一批FFPE样品进行全外显子组测序（WES），并将WES TMB值与TML测定的TMB估计值进行比较。结果：计算机模拟分析表明Oncomine TML组具有足够的基因组覆盖率来估计体细胞突变，与WES具有强相关性（r（2）=0.986）。此外，使用来自三个单独队列的WES数据并与与TML组重叠的WES子集进行比较的计算机模拟预测证实了对免疫检查点抑制剂的应答者和非应答者进行分层的能力，具有高度统计学显著性。我们发现TML检测细胞系和对照样品的体细胞突变率与已知的事实相似。我们验证了仅使用肿瘤样本与匹配的肿瘤-正常实验设计进行比较以去除生殖系变体的生殖系过滤的性能。我们比较了TML测定法与WES法对一批FFPE研究样本的TMB估计值，发现相关性很高（r（2）=0.83）。我们在结直肠癌（CRC）、肺癌和黑色素瘤起源的FFPE研究样本中发现了生物学上有趣的肿瘤发生特征。此外，我们评估了一组FFPE研究样本（包括肺、结肠和黑色素瘤肿瘤）的TMB，以发现TMB值的生物相关范围。结论：这些结果表明，针对1.7 Mb基因组足迹的TML检测可以准确预测TMB值与WES相当。TML检测工作流程包含使用Ion GeneStudio S5系统的简单工作流程。此外，AmpliSeq化学允许使用低输入DNA来估计来自FFPE样品的突变负荷。该TMB检测试剂盒能够在样本稀缺的情况下对免疫肿瘤学生物标志物进行可扩展的稳健研究。
Background: Tumor mutational burden (TMB) is an increasingly important biomarker for immune checkpoint inhibitors. Recent publications have described strong association between high TMB and objective response to mono- and combination immunotherapies in several cancer types. Existing methods to estimate TMB require large amount of input DNA, which may not always be available.Methods: In this study, we develop a method to estimate TMB using the Oncomine Tumor Mutation Load (TML) Assay with 20 ng of DNA, and we characterize the performance of this method on various formalin-fixed, paraffin-embedded (FFPE) research samples of several cancer types. We measure the analytical performance of TML workflow through comparison with control samples with known truth, and we compare performance with an orthogonal method which uses matched normal sample to remove germline variants. We perform whole exome sequencing (WES) on a batch of FFPE samples and compare the WES TMB values with TMB estimates by the TML assay.Results: In-silico analyses demonstrated the Oncomine TML panel has sufficient genomic coverage to estimate somatic mutations with a strong correlation (r(2)=0.986) to WES. Further, in silico prediction using WES data from three separate cohorts and comparing with a subset of the WES overlapping with the TML panel, confirmed the ability to stratify responders and non-responders to immune checkpoint inhibitors with high statistical significance. We found the rate of somatic mutations with the TML assay on cell lines and control samples were similar to the known truth. We verified the performance of germline filtering using only a tumor sample in comparison to a matched tumor-normal experimental design to remove germline variants. We compared TMB estimates by the TML assay with that from WES on a batch of FFPE research samples and found high correlation (r(2)=0.83). We found biologically interesting tumorigenesis signatures on FFPE research samples of colorectal cancer (CRC), lung, and melanoma origin. Further, we assessed TMB on a cohort of FFPE research samples including lung, colon, and melanoma tumors to discover the biologically relevant range of TMB values.Conclusions: These results show that the TML assay targeting a 1.7-Mb genomic footprint can accurately predict TMB values that are comparable to the WES. The TML assay workflow incorporates a simple workflow using the Ion GeneStudio S5 System. Further, the AmpliSeq chemistry allows the use of low input DNA to estimate mutational burden from FFPE samples. This TMB assay enables scalable, robust research into immuno-oncology biomarkers with scarce samples.