Circulating MicroRNAs as Non-Invasive Biomarkers for Early Detection of Non-Small-Cell Lung Cancer.

Magdalena B Wozniak,David Zaridze,Ghislaine Scelo,Paul Brennan,David C Muller,Anush Mukeria,Jörg D Hoheisel

doi:10.1371/journal.pone.0125026

Abstract

BackgroundDetection of lung cancer at an early stage by sensitive screening tests could be an important strategy to improving prognosis. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.Material and MethodsPlasma samples from 100 early stage (I to IIIA) non–small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Logistic regression with a lasso penalty was used to select a panel of microRNAs that discriminate between cases and controls. Internal validation of model discrimination was conducted by calculating the bootstrap optimism-corrected AUC for the selected model.ResultsWe identified a panel of 24 microRNAs with optimum classification performance. The combination of these 24 microRNAs alone could discriminate lung cancer cases from non-cancer controls with an AUC of 0.92 (95% CI: 0.87-0.95). This classification improved to an AUC of 0.94 (95% CI: 0.90-0.97) following addition of sex, age and smoking status to the model. Internal validation of the model suggests that the discriminatory power of the panel will be high when applied to independent samples with a corrected AUC of 0.78 for the 24-miRNA panel alone.ConclusionOur 24-microRNA predictor improves lung cancer prediction beyond that of known risk factors.

Highlights

Lung cancer is the most common cause of cancer death worldwide
Detection of lung cancer at an early stage by sensitive screening tests could be an important strategy to improving prognosis
Logistic regression with a lasso penalty was used to select a panel of microRNAs that discriminate between cases and controls

Summary

Introduction

Lung cancer is the most common cause of cancer death worldwide. Detection of lung cancer at an early stage by sensitive screening tests could be an important strategy to improve lung cancer prognosis. The National Lung Screening Trial (NLST) using low-dose helical computed tomography (LDCT) in high-risk individuals demonstrates that a 20% reduction in lung cancer-specific mortality and a 6.7% reduction in all-cause mortality [3] can be achieved. High false-positive rates of NLST [4], costs, and potential harms from radiation exposure highlight the need for simpler, non-invasive and more accessible methodologies for effective early cancer detection as complementary biomarkers. Detection of lung cancer at an early stage by sensitive screening tests could be an important strategy to improving prognosis. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer

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Conclusion