BACKGROUND Lung cancer is the leading cause of cancer-related death worldwide, and the timely and serial assessment of low-dose computed tomography (LDCT) in high-risk populations remains a challenge. Furthermore, testing a single biomarker for the diagnosis of lung cancers is of relatively low effectiveness. Thus, a stronger diagnostic combination of blood biomarkers is needed to improve the diagnosis of non-small cell lung cancer (NSCLC). METHODS The blood levels of individual biomarkers [IDH1, DNA methylation of short stature homeobox 2 gene (SHOX2), and prostaglandin E receptor 4 gene (PTGER4)] were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. In total, 221 candidates were enrolled and randomly assigned into two groups for the training and validation of a diagnostic panel. Additionally, a subgroup analysis was performed in the whole cohort. RESULTS A newly combined 3-marker diagnostic model for lung cancers was established and validated with area under the receiver operating characteristic (ROC) curve (AUC) values ranging from 0.835 to 0.905 in independent groups showing significantly stronger diagnostic value compared with a single tested biomarker. The sensitivity of the diagnostic model was as high as 86.1% and 80.0% in the training and validation sets, respectively. Although no apparent differences were found between the 3-marker and 2-marker models, the high clinical T-stage and histological type specificity of IDH1 and two other methylated DNA biomarkers were demonstrated in the subgroup analysis. CONCLUSIONS The combination of single biomarkers with high stage-specificity and histological type specificity (SHOX2 and PTGER4 DNA methylation and IDH1) showed better diagnostic performance in the detection of lung cancers compared with single marker assessment. A greater clinical utility of the panel may be developed by adding demographic/epidemiologic characteristics.

中文翻译：

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IDH1和DNA甲基化生物标志物在肺癌诊断中的翻译价值：阶段和组织学特异性的新型诊断方法。

背景技术肺癌是世界范围内与癌症相关的死亡的主要原因，对高风险人群进行低剂量计算机断层扫描（LDCT）的及时和连续评估仍然是一个挑战。此外，测试单个生物标记物以诊断肺癌是相对低效的。因此，需要更强的血液生物标志物诊断组合以改善对非小细胞肺癌（NSCLC）的诊断。方法测量健康对照和肺癌患者样本中的单个生物标志物的血液水平[IDH1，矮小同源盒2基因的DNA甲基化（SHOX2）和前列腺素E受体4基因（PTGER4）]，并进行统计学分析。总共招募了221名候选人，并将他们随机分为两组，以训练和验证诊断小组。此外，在整个队列中进行了亚组分析。结果建立了一个新的肺癌三标记组合诊断模型，并通过独立工作组的受试者工作特征（ROC）曲线（AUC）值范围为0.835至0.905的面积进行了验证，与单一测试的生物标志物相比，其诊断价值明显更高。 。在训练和验证集中，诊断模型的敏感性分别高达86.1％和80.0％。尽管在3标记和2标记模型之间没有发现明显差异，但在亚组分析中证明了IDH1和其他两种甲基化DNA生物标记的高临床T期和组织学类型特异性。结论与单一标志物评估相比，具有高阶段特异性和组织学类型特异性（SHOX2和PTGER4 DNA甲基化和IDH1）的单一生物标志物的组合在肺癌的检测中显示出更好的诊断性能。通过增加人口统计学/流行病学特征，可以开发该小组的更大的临床实用性。