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Open Access Highly Accessed Review

Bridging the clinical gaps: genetic, epigenetic and transcriptomic biomarkers for the early detection of lung cancer in the post-National Lung Screening Trial era

John F Brothers12*, Kahkeshan Hijazi12, Celine Mascaux3, Randa A El-Zein4, Margaret R Spitz4 and Avrum Spira12

  • * Corresponding author: John F Brothers jb2@bu.edu

  • † Equal contributors

Author Affiliations

1 Bioinformatics Program, Boston University, Boston, MA, USA

2 Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA

3 Department of Medical Oncology, Princess Margaret Cancer Centre, University of Health Network, University of Toronto, Toronto, Ontario, Canada

4 Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA

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BMC Medicine 2013, 11:168  doi:10.1186/1741-7015-11-168

Published: 19 July 2013

Abstract

Lung cancer is the leading cause of cancer death worldwide in part due to our inability to identify which smokers are at highest risk and the lack of effective tools to detect the disease at its earliest and potentially curable stage. Recent results from the National Lung Screening Trial have shown that annual screening of high-risk smokers with low-dose helical computed tomography of the chest can reduce lung cancer mortality. However, molecular biomarkers are needed to identify which current and former smokers would benefit most from annual computed tomography scan screening in order to reduce the costs and morbidity associated with this procedure. Additionally, there is an urgent clinical need to develop biomarkers that can distinguish benign from malignant lesions found on computed tomography of the chest given its very high false positive rate. This review highlights recent genetic, transcriptomic and epigenomic biomarkers that are emerging as tools for the early detection of lung cancer both in the diagnostic and screening setting.

Keywords:
Biomarker; Diagnostics; Early detection; Epigenetics; Genetics; Lung cancer; Screening; Transcriptomics