Division of Cancer Epidemiology and Genetics, NCI, NIH, Department of Health and Human Services, Bethesda, MD 20892, USA.
Cancer Prev Res (Phila). 2011 Oct;4(10):1599-608. doi: 10.1158/1940-6207.CAPR-10-0170. Epub 2011 Jul 8.
Affordable early screening in subjects with high risk of lung cancer has great potential to improve survival from this deadly disease. We measured gene expression from lung tissue and peripheral whole blood (PWB) from adenocarcinoma cases and controls to identify dysregulated lung cancer genes that could be tested in blood to improve identification of at-risk patients in the future. Genome-wide mRNA expression analysis was conducted in 153 subjects (73 adenocarcinoma cases, 80 controls) from the Environment And Genetics in Lung cancer Etiology study using PWB and paired snap-frozen tumor and noninvolved lung tissue samples. Analyses were conducted using unpaired t tests, linear mixed effects, and ANOVA models. The area under the receiver operating characteristic curve (AUC) was computed to assess the predictive accuracy of the identified biomarkers. We identified 50 dysregulated genes in stage I adenocarcinoma versus control PWB samples (false discovery rate ≤0.1, fold change ≥1.5 or ≤0.66). Among them, eight (TGFBR3, RUNX3, TRGC2, TRGV9, TARP, ACP1, VCAN, and TSTA3) differentiated paired tumor versus noninvolved lung tissue samples in stage I cases, suggesting a similar pattern of lung cancer-related changes in PWB and lung tissue. These results were confirmed in two independent gene expression analyses in a blood-based case-control study (n = 212) and a tumor-nontumor paired tissue study (n = 54). The eight genes discriminated patients with lung cancer from healthy controls with high accuracy (AUC = 0.81, 95% CI = 0.74-0.87). Our finding suggests the use of gene expression from PWB for the identification of early detection markers of lung cancer in the future.
在肺癌高危人群中进行负担得起的早期筛查,具有极大提高这种致命疾病生存率的潜力。我们从腺癌病例和对照者的肺组织和外周全血(PWB)中测量基因表达,以鉴定可能在血液中检测到的失调肺癌基因,从而在未来更好地识别高危患者。利用 PWB 和配对的冷冻肿瘤和未受累肺组织样本,对来自环境与遗传在肺癌病因学研究(Environment And Genetics in Lung cancer Etiology study)中的 153 名受试者(73 例腺癌病例,80 例对照者)进行了全基因组 mRNA 表达分析。采用非配对 t 检验、线性混合效应和 ANOVA 模型进行分析。计算了接受者操作特征曲线(receiver operating characteristic curve,ROC)下的面积(area under the receiver operating characteristic curve,AUC)以评估所鉴定生物标志物的预测准确性。我们在 I 期腺癌与对照者 PWB 样本中鉴定到 50 个失调基因(错误发现率≤0.1,倍数变化≥1.5 或≤0.66)。其中,8 个基因(TGFBR3、RUNX3、TRGC2、TRGV9、TARP、ACP1、VCAN 和 TSTA3)在 I 期病例中区分了配对肿瘤与未受累肺组织样本,表明 PWB 和肺组织中存在相似的肺癌相关变化模式。在一项基于血液的病例对照研究(n=212)和一项肿瘤-非肿瘤配对组织研究(n=54)中,两个独立的基因表达分析中证实了这些结果。这 8 个基因以较高的准确度(AUC=0.81,95%CI=0.74-0.87)区分了肺癌患者和健康对照者。我们的发现表明,未来可能会利用 PWB 中的基因表达来鉴定肺癌的早期检测标志物。