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Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA)

机译:使用循环肿瘤DNA(ctDNA)的高通量靶向DNA甲基化测序技术对早期肺癌进行非侵入性诊断

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Rational: LDCT screening can identify early-stage lung cancers yet introduces excessive false positives and it remains a great challenge to differentiate malignant tumors from benign solitary pulmonary nodules, which calls for better non-invasive diagnostic tools. Methods: We performed DNA methylation profiling by high throughput DNA bisulfite sequencing in tissue samples (nodule size 3 cm in diameter) to learn methylation patterns that differentiate cancerous tumors from benign lesions. Then we filtered out methylation patterns exhibiting high background in circulating tumor DNA (ctDNA) and built an assay for plasma sample classification. Results: We first performed methylation profiling of 230 tissue samples to learn cancer-specific methylation patterns which achieved a sensitivity of 92.7% (88.3% - 97.1%) and a specificity of 92.8% (89.3% - 96.3%). These tissue-derived DNA methylation markers were further filtered using a training set of 66 plasma samples and 9 markers were selected to build a diagnostic prediction model. From an independent validation set of additional 66 plasma samples, this model obtained a sensitivity of 79.5% (63.5% - 90.7%) and a specificity of 85.2% (66.3% - 95.8%) for differentiating patients with malignant tumor (n = 39) from patients with benign lesions (n = 27). Additionally, when tested on gender and age matched asymptomatic normal individuals (n = 118), our model achieved a specificity of 93.2% (89.0% - 98.3%). Specifically, our assay is highly sensitive towards early‐stage lung cancer, with a sensitivity of 75.0% (55.0%-90.0%) in 20 stage Ia lung cancer patients and 85.7% (57.1%-100.0%) in 7 stage Ib lung cancer patients. Conclusions: We have developed a novel sensitive blood based non‐invasive diagnostic assay for detecting early stage lung cancer as well as differentiating lung cancers from benign pulmonary nodules.
机译:合理:LDCT筛查可以识别早期肺癌,但会引入过多的假阳性,将恶性肿瘤与良性孤立性肺结节区分开来仍然是一个巨大的挑战,这需要更好的无创诊断工具。方法:我们通过高通量DNA亚硫酸氢盐测序对组织样品(结节直径<3 cm直径)进行了DNA甲基化分析,以了解区分癌性肿瘤与良性病变的甲基化模式。然后,我们滤出了循环肿瘤DNA(ctDNA)中显示高背景的甲基化模式,并建立了血浆样品分类的测定方法。结果:我们首先对230个组织样本进行了甲基化分析,以了解特定于癌症的甲基化模式,其敏感性为92.7%(88.3%-97.1%),特异性为92.8%(89.3%-96.3%)。使用66个血浆样品的训练集进一步过滤这些组织来源的DNA甲基化标记,并选择9个标记以建立诊断预测模型。通过对另外66个血浆样品进行的独立验证,该模型对区分恶性肿瘤患者的敏感性为79.5%(63.5%-90.7%),特异性为85.2%(66.3%-95.8%)(n = 39)。来自良性病变患者(n = 27)。此外,在对性别和年龄相匹配的无症状正常个体(n = 118)进行测试时,我们的模型达到了93.2%(89.0%-98.3%)的特异性。具体而言,我们的分析对早期肺癌高度敏感,在20例Ia期肺癌患者中敏感性为75.0%(55.0%-90.0%),在7例Ib期肺癌中敏感性为85.7%(57.1%-100.0%)耐心。结论:我们开发了一种新颖的基于血液的敏感非侵入性诊断检测方法,可检测早期肺癌并将肺癌与良性肺结节区分开。

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