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.

Non-blood circulating tumor DNA detection in cancer Non-blood circulating tumor DNA detection in cancer

Purpose: Low-dose CT screening can reduce lung cancer–related mortality. However, CT screening has an FDR of nearly 96%. We sought to assess whether urine samples can be a source for DNA methylation–based detection of non–small cell lung cancer (NSCLC). Experimental Design: This nested case–control study of subjects with suspicious nodules on CT imaging obtained plasma and urine samples preoperatively. Cases (n = 74) had pathologic confirmation of NSCLC. Controls (n = 27) had a noncancer diagnosis. We detected promoter methylation in plasma and urine samples using methylation on beads and quantitative methylation–specific real-time PCR for cancer-specific genes (CDO1, TAC1, HOXA7, HOXA9, SOX17, and ZFP42). Results: DNA methylation at cancer-specific loci was detected in both plasma and urine, and was more frequent in patients with cancer compared with controls for all six genes in plasma and in CDO1, TAC1, HOXA9, and SOX17 in urine. Univariate and multivariate logistic regression analysis showed that methylation detection in each one of six genes in plasma and CDO1, TAC1, HOXA9, and SOX17 in urine were significantly associated with the diagnosis of NSCLC, independent of age, race, and smoking pack-years. When methylation was detected for three or more genes in both plasma and urine, the sensitivity and specificity for lung cancer diagnosis were 73% and 92%, respectively. Conclusions: DNA methylation–based biomarkers in plasma and urine could be useful as an adjunct to CT screening to guide decision-making regarding further invasive procedures in patients with pulmonary nodules.

Purpose: Non–small cell lung cancer (NSCLC) is the leading cause of cancer mortality in the world. Novel diagnostic biomarkers may augment both existing NSCLC screening methods as well as molecular diagnostic tests of surgical specimens to more accurately stratify and stage candidates for adjuvant chemotherapy. Hypermethylation of CpG islands is a common and important alteration in the transition from normal tissue to cancer. Experimental Design: Following previously validated methods for the discovery of cancer-specific hypermethylation changes, we treated eight NSCLC cell lines with the hypomethylating agent deoxyazacitidine or trichostatin A. We validated the findings using a large publicly available database and two independent cohorts of primary samples. Results: We identified >300 candidate genes. Using The Cancer Genome Atlas (TCGA) and extensive filtering to refine our candidate genes for the greatest ability to distinguish tumor from normal, we define a three-gene panel, CDO1, HOXA9, and TAC1, which we subsequently validate in two independent cohorts of primary NSCLC samples. This three-gene panel is 100% specific, showing no methylation in 75 TCGA normal and seven primary normal samples and is 83% to 99% sensitive for NSCLC depending on the cohort. Conclusion: This degree of sensitivity and specificity may be of high value to diagnose the earliest stages of NSCLC. Addition of this three-gene panel to other previously validated methylation biomarkers holds great promise in both early diagnosis and molecular staging of NSCLC. Clin Cancer Res; 20(7); 1856–64. ©2014 AACR.

Purpose: We had previously developed highly sensitive DNA methylation detection to diagnose lung cancer in patients with pulmonary nodules. To validate this approach and determine clinical utility in Chinese patients with indeterminate pulmonary nodules, we assessed the diagnostic accuracy for early stage lung cancer in plasma samples. Experimental design: Patients with CT-detected small lung nodules (diameter ≤ 3.0 cm) were included. Cases (n = 163) had staged IA or IB non-small cell lung cancer (NSCLC), while controls (n = 83) had non-cancerous lesions. Promoter methylation of eight lung cancer-specific genes (CDO1, TAC1, SOX17, HOXA7, HOXA9, GATA4, GATA5, and PAX5) was detected using nanoparticle-based DNA extraction (MOB) followed by qMSP. Results: Methylation detection for CDO1, TAC1, SOX17, and HOXA7 in plasma was significantly higher in cases compared with the benign group (p < 0.001). The sensitivity and specificity for lung cancer diagnosis using individual gene was 41–69% and 49–82%. A three-gene combination of the best individual genes has sensitivity and specificity of 90% and 71%, with area under the receiver operating curve (AUC) of 0.88, (95% CI 0.84–0.93). Furthermore, three-gene combinations detected even the smallest lung nodules, with the combination of CDO1, SOX17, and HOXA7 having the overall best performance, while the combination of CDO1, TAC1, and SOX17 was best in tumor sizes less than 1.0 cm. Conclusions: Using modified MOB-qMSP, high sensitivity and specificity, for the detection of circulating tumor DNA was obtained for early stage NSCLC. This strategy has great potential to identify patients at high risk and improve the diagnosis of lung cancer at an earlier stage. Graphical