Early Detection of Lung Cancer Using DNA Promoter Hypermethylation in Plasma and Sputum

Abstract

Purpose: CT screening can reduce death from lung cancer. We sought to improve the diagnostic accuracy of lung cancer screening using ultrasensitive methods and a lung cancer-specific gene panel to detect DNA methylation in sputum and plasma.Experimental Design: This is a case-control study of subjects with suspicious nodules on CT imaging. Plasma and sputum were obtained preoperatively. Cases (n = 150) had pathologic confirmation of node-negative (stages I and IIA) non-small cell lung cancer. Controls (n = 60) had non-cancer diagnoses. We detected promoter methylation using quantitative methylation-specific real-time PCR and methylation-on-beads for cancer-specific genes (SOX17, TAC1, HOXA7, CDO1, HOXA9, and ZFP42).Results: DNA methylation was detected in plasma and sputum more frequently in people with cancer compared with controls (P < 0.001) for five of six genes. The sensitivity and specificity for lung cancer diagnosis using the best individual genes was 63% to 86% and 75% to 92% in sputum, respectively, and 65% to 76% and 74% to 84% in plasma, respectively. A three-gene combination of the best individual genes has sensitivity and specificity of 98% and 71% using sputum and 93% and 62% using plasma. Area under the receiver operating curve for this panel was 0.89 [95% confidence interval (CI), 0.80-0.98] in sputum and 0.77 (95% CI, 0.68-0.86) in plasma. Independent blinded random forest prediction models combining gene methylation with clinical information correctly predicted lung cancer in 91% of subjects using sputum detection and 85% of subjects using plasma detection.Conclusions: High diagnostic accuracy for early-stage lung cancer can be obtained using methylated promoter detection in sputum or plasma. Clin Cancer Res; 23(8); 1998-2005. ©2016 AACR.

Figure 1.. Methylation detection values of the studied genes.

This scatter plot shows the converted ΔCT methylation values in a logarithmic scale. These values show a bimodal distribution with the lower group the values corresponding to those samples with no detectable amplification (ND). The majority of lung tumor samples have high levels of methylation, as expected from the previous study. Plasma and sputum samples from cancer patients have detectable methylation which varies from levels nearing that of tumor samples to those at the limits of detection (10⁻⁵-10⁻⁶), while some patients are undetectable. The majority of controls have undetectable methylation at these loci, although some patients do have detectable methylation that is quantitatively similar to cancer patients. HOXA9 methylation is detectable in most control patients, especially in the sputum, suggesting this change is present in the lung epithelium and not as specific for the detection of cancer.

Figure 2.. Receiver operator classification curves for lung cancer detection.

A. ROC curves comparing the 3 genes with the largest areas under the curve for sputum. B. ROC curves comparing the 3 genes with the largest areas under the curve for Plasma. C. ROC of the combined methylation status of the genes from sputum with the largest area under the curve. D. ROC of the combined methylation status of the genes from Plasma with the largest area under the curve. Abbreviations: area under the curve: AUC, 95 % confidence interval: 95% CI.

Figure 3.. Receiver operator classification curves for cancer predictions.

ROC curves assessing the accuracy of the predictions for lung cancer performed on the testing subset by using as predictors the ΔC_t values for all six genes, age, pack-year, COPD status and FVC values. The left plot is obtained using sputum samples, the middle one, using plasma samples and the right one, the ROC curve for the clinical predictors alone.