Service de Biopathologie, Institut de Cancérologie de Lorraine, F-54519, Vandœuvre-lès-Nancy, France.
Data Biostatistics Unit, Institut de Cancérologie de Lorraine, F-54519, Vandœuvre-lès-Nancy, France.
Sci Rep. 2019 Oct 10;9(1):14561. doi: 10.1038/s41598-019-51155-3.
Diagnosis of lung cancer can sometimes be challenging and is of major interest since effective molecular-guided therapies are available. Compounds of tobacco smoke may generate a specific substitutional signature in lung, which is the most exposed organ. To predict whether a tumor is of lung origin or not, we developed and validated the EASILUNG (Exome And SIgnature LUNG) test based on the relative frequencies of somatic substitutions on coding non-transcribed DNA strands from whole-exome sequenced tumors. Data from 7,796 frozen tumor samples (prior to any treatment) from 32 TCGA solid cancer groups were used for its development. External validation was carried out on a local dataset of 196 consecutive routine exome results. Eight out of the 12 classes of substitutions were required to compute the EASILUNG signature that demonstrated good calibration and good discriminative power with a sensitivity of 83% and a specificity of 72% after recalibration on the external validation dataset. This innovative test may be helpful in medical decision-making in patients with unknown primary tumors potentially of lung origin and in the diagnosis of lung cancer in smokers.
肺癌的诊断有时具有挑战性,并且非常重要,因为目前已有有效的分子靶向治疗方法。烟草烟雾中的化合物可能会在肺部产生特定的取代特征,而肺部是最易受影响的器官。为了预测肿瘤是否源自肺部,我们基于全外显子组测序肿瘤中非转录编码 DNA 链上体细胞取代的相对频率,开发并验证了 EASILUNG(外显子和特征性肺)测试。该测试的数据来自 32 个 TCGA 实体瘤组的 7796 个冷冻肿瘤样本(在任何治疗之前)。我们还在一个本地的 196 例连续常规外显子组结果数据集上进行了外部验证。该测试需要计算 EASILUNG 特征的 12 类取代中的 8 类,该特征具有良好的校准和区分能力,在对外部验证数据集进行重新校准后,敏感性为 83%,特异性为 72%。这项创新的测试可能有助于患有潜在肺部起源不明原发肿瘤的患者的医疗决策,以及对吸烟者肺癌的诊断。