Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer

Nat Med. 2007 Mar;13(3):361-6. doi: 10.1038/nm1556. Epub 2007 Mar 4.

Abstract

Lung cancer is the leading cause of death from cancer in the US and the world. The high mortality rate (80-85% within 5 years) results, in part, from a lack of effective tools to diagnose the disease at an early stage. Given that cigarette smoke creates a field of injury throughout the airway, we sought to determine if gene expression in histologically normal large-airway epithelial cells obtained at bronchoscopy from smokers with suspicion of lung cancer could be used as a lung cancer biomarker. Using a training set (n = 77) and gene-expression profiles from Affymetrix HG-U133A microarrays, we identified an 80-gene biomarker that distinguishes smokers with and without lung cancer. We tested the biomarker on an independent test set (n = 52), with an accuracy of 83% (80% sensitive, 84% specific), and on an additional validation set independently obtained from five medical centers (n = 35). Our biomarker had approximately 90% sensitivity for stage 1 cancer across all subjects. Combining cytopathology of lower airway cells obtained at bronchoscopy with the biomarker yielded 95% sensitivity and a 95% negative predictive value. These findings indicate that gene expression in cytologically normal large-airway epithelial cells can serve as a lung cancer biomarker, potentially owing to a cancer-specific airway-wide response to cigarette smoke.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Biomarkers / metabolism
  • Biomarkers, Tumor
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / metabolism
  • Lung Neoplasms / pathology
  • Oligonucleotide Array Sequence Analysis
  • Prospective Studies
  • Respiratory Mucosa / metabolism*
  • Respiratory Mucosa / pathology
  • Smoking / adverse effects*
  • Smoking / genetics

Substances

  • Biomarkers
  • Biomarkers, Tumor

Associated data

  • GEO/GSE4115