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Comprehensive profiling and quantitation of oncogenic mutations in non small-cell lung carcinoma using single molecule amplification and re-sequencing technology

机译:使用单分子扩增和重测序技术对非小细胞肺癌的致癌突变进行全面的分析和定量

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摘要

Activating and resistance mutations in the tyrosine kinase domain of several oncogenes are frequently associated with non-small cell lung carcinoma (NSCLC). In this study we assessed the frequency, type and abundance of EGFR, KRAS, BRAF, TP53 and ALK mutations in tumour specimens from 184 patients with early and late stage disease using single molecule amplification and re-sequencing technology (SMART). Based on modelling of EGFR mutations, the detection sensitivity of the SMART assay was at least 0.1%. Benchmarking EGFR mutation detection against the gold standard ARMS-PCR assay, SMART assay had a sensitivity and specificity of 98.7% and 99.0%. Amongst the 184 samples, EGFR mutations were the most prevalent (59.9%), followed by KRAS (16.9%), TP53 (12.7%), EML4-ALK fusions (6.3%) and BRAF (4.2%) mutations. The abundance and types of mutations in tumour specimens were extremely heterogeneous, involving either monoclonal (51.6%) or polyclonal (12.6%) mutation events. At the clinical level, although the spectrum of tumour mutation(s) was unique to each patient, the overall patterns in early or advanced stage disease were relatively similar. Based on these findings, we propose that personalized profiling and quantitation of clinically significant oncogenic mutations will allow better classification of patients according to tumour characteristics and provide clinicians with important ancillary information for treatment decision-making.
机译:几种癌基因的酪氨酸激酶结构域中的激活和耐药突变通常与非小细胞肺癌(NSCLC)相关。在这项研究中,我们使用单分子扩增和重测序技术(SMART)评估了184例早期和晚期疾病患者的肿瘤标本中EGFR,KRAS,BRAF,TP53和ALK突变的频率,类型和丰度。根据EGFR突变的模型,SMART分析的检测灵敏度至少为0.1%。相对于金标准ARMS-PCR分析,对EGFR突变检测进行基准测试,SMART分析的灵敏度和特异性分别为98.7%和99.0%。在这184个样本中,EGFR突变最为普遍(59.9%),其次是KRAS(16.9%),TP53(12.7%),EML4-ALK融合蛋白(6.3%)和BRAF(4.2%)突变。肿瘤标本中突变的丰度和类型非常不同,涉及单克隆(51.6%)或多克隆(12.6%)突变事件。在临床水平上,尽管每个患者的肿瘤突变谱都是唯一的,但早期或晚期疾病的总体模式相对相似。基于这些发现,我们建议对具有临床意义的致癌突变进行个性化分析和定量分析,可以根据肿瘤特征更好地对患者进行分类,并为临床医生提供重要的辅助信息,以进行治疗决策。

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