DNA methylation biomarkers offer improved diagnostic efficiency in lung cancer

Abstract

The exceptional high mortality of lung cancer can be instigated to a high degree by late diagnosis. Despite the plethora of studies on potential molecular biomarkers for lung cancer diagnosis, very few have reached clinical implementation. In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency in bronchial washings from a large retrospective cohort. Candidate targets from previous high-throughput approaches were examined by pyrosequencing in an independent set of 48 lung tumor/normal paired. Ten promoters were selected and quantitative methylation-specific PCR (qMSP) assays were developed and used to screen 655 bronchial washings from the Liverpool Lung Project (LLP) subjects divided into training (194 cases and 214 controls) and validation (139 cases and 109 controls) sets. Three statistical models were used to select the optimal panel of markers and to evaluate the performance of the discriminatory algorithms. The final logit regression model incorporated hypermethylation at p16, TERT, WT1, and RASSF1. The performance of this 4-gene methylation signature in the validation set showed 82% sensitivity and 91% specificity. In comparison, cytology alone in this set provided 43% sensitivity at 100% specificity. The diagnostic efficiency of the panel did not show any biases with age, gender, smoking, and the presence of a nonlung neoplasm. However, sensitivity was predictably higher in central (squamous and small cell) than peripheral (adenocarcinomas) tumors, as well as in stage 2 or greater tumors. These findings clearly show the impact of DNA methylation-based assays in the diagnosis of cytologically occult lung neoplasms. A prospective trial is currently imminent in the LLP study to provide data on the enhancement of diagnostic accuracy in a clinical setting, including by additional markers.

Figure 1

Outline of the study progress phases. The distribution of candidate biomarker (BM) targets is validated for by Pyrosequencing Methylation analysis (PMA) in an independent set of lung cancer tissues. Quantitative methylation-specific PCR (qMSP) assays are developed and evaluated for their robustness in clinical samples. These are used to screen the training bronchial washings (BW) set from lung cancer patients and age/sex matched controls. Samples were excluded if extracted DNA failed in quality control. Statistical modeling demonstrates six markers with higher discriminating efficiency and these are used to screen the validation BW set. Further statistical modeling is applied to test the derived algorithms in the validation set. The qualifying 4-marker panel incorporates cytological data in order to construct the final algorithm. UAT: Univariate Association Test, BSR: Best Subset Regression, MDR: Multifactor Dimensionality Reduction.

Figure 2

Sensitivities of cytology and DNA methylation in different pathological stages of lung cancer. DNA methylation demonstrates superior sensitivity across all stages. D: DNA methylation panel, C: cytology.