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


Lung cancer is the leading cause of death from cancer in the US and the world1. 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 stage2,3,4. Given that cigarette smoke creates a field of injury throughout the airway5,6,7,8,9,10,11, 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 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.

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Figure 1: Development and performance of an airway biomarker for lung cancer.
Figure 2: Hierarchical clustering of biomarker probeset expression in two independent test sets.
Figure 3: Principal component analysis (PCA) of airway biomarker gene expression in lung tissue samples.
Figure 4: Diagnostic utility of bronchoscopy and the gene-expression biomarker.

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Gene Expression Omnibus


  1. Parkin, D.M., Bray, F., Ferlay, J. & Pisani, P. Global cancer statistics, 2002. CA Cancer J. Clin. 55, 74–108 (2005).

    Article  Google Scholar 

  2. Hirsch, F.R., Merrick, D.T. & Franklin, W.A. Role of biomarkers for early detection of lung cancer and chemoprevention. Eur. Respir. J. 19, 1151–1158 (2002).

    Article  CAS  Google Scholar 

  3. Jett, J.R. Limitations of screening for lung cancer with low-dose spiral computed tomography. Clin. Cancer Res. 11, 4988s–4992s (2005).

    Article  Google Scholar 

  4. Macredmond, R. et al. Screening for lung cancer using low dose CT scanning: results of 2 year follow up. Thorax 61, 54–56 (2006).

    Article  CAS  Google Scholar 

  5. Auerbach, O., Hammond, E.C., Kirman, D. & Garfinkel, L. Effects of cigarette smoking on dogs. II. Pulmonary neoplasms. Arch. Environ. Health 21, 754–768 (1970).

    Article  CAS  Google Scholar 

  6. Powell, C.A., Klares, S., O'Connor, G. & Brody, J.S. Loss of heterozygosity in epithelial cells obtained by bronchial brushing: clinical utility in lung cancer. Clin. Cancer Res. 5, 2025–2034 (1999).

    CAS  PubMed  Google Scholar 

  7. Wistuba, I.I. et al. Molecular damage in the bronchial epithelium of current and former smokers. J. Natl. Cancer Inst. 89, 1366–1373 (1997).

    Article  CAS  Google Scholar 

  8. Franklin, W.A. et al. Widely dispersed p53 mutation in respiratory epithelium. A novel mechanism for field carcinogenesis. J. Clin. Invest. 100, 2133–2137 (1997).

    Article  CAS  Google Scholar 

  9. Guo, M. et al. Promoter hypermethylation of resected bronchial margins: a field defect of changes? Clin. Cancer Res. 10, 5131–5136 (2004).

    Article  CAS  Google Scholar 

  10. Miyazu, Y.M. et al. Telomerase expression in noncancerous bronchial epithelia is a possible marker of early development of lung cancer. Cancer Res. 65, 9623–9627 (2005).

    Article  CAS  Google Scholar 

  11. Spira, A. et al. Effects of cigarette smoke on the human airway epithelial cell transcriptome. Proc. Natl. Acad. Sci. USA 101, 10143–10148 (2004).

    Article  CAS  Google Scholar 

  12. Postmus, P.E. Bronchoscopy for lung cancer. Chest 128, 16–18 (2005).

    Article  Google Scholar 

  13. Mazzone, P., Jain, P., Arroliga, A.C. & Matthay, R.A. Bronchoscopy and needle biopsy techniques for diagnosis and staging of lung cancer. Clin. Chest Med. 23, 137–158 (2002).

    Article  Google Scholar 

  14. Schreiber, G. & McCrory, D.C. Performance characteristics of different modalities for diagnosis of suspected lung cancer: summary of published evidence. Chest 123, 115S–128S (2003).

    Article  Google Scholar 

  15. Salomaa, E.R., Sallinen, S., Hiekkanen, H. & Liippo, K. Delays in the diagnosis and treatment of lung cancer. Chest 128, 2282–2288 (2005).

    Article  Google Scholar 

  16. Golub, T.R. et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999).

    Article  CAS  Google Scholar 

  17. Tibshirani, R., Hastie, T., Narasimhan, B. & Chu, G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567–6572 (2002).

    Article  CAS  Google Scholar 

  18. Bhattacharjee, A. et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. USA 98, 13790–13795 (2001).

    Article  CAS  Google Scholar 

  19. Wachi, S., Yoneda, K. & Wu, R. Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues. Bioinformatics 21, 4205–4208 (2005).

    Article  CAS  Google Scholar 

  20. Raponi, M. et al. Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res. 66, 7466–7472 (2006).

    Article  CAS  Google Scholar 

  21. Potti, A. et al. A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N. Engl. J. Med. 355, 570–580 (2006).

    Article  CAS  Google Scholar 

  22. Cheng, K.W., Lahad, J.P., Gray, J.W. & Mills, G.B. Emerging role of RAB GTPases in cancer and human disease. Cancer Res. 65, 2516–2519 (2005).

    Article  CAS  Google Scholar 

  23. Shimada, K. et al. Aberrant expression of RAB1A in human tongue cancer. Br. J. Cancer 92, 1915–1921 (2005).

    Article  CAS  Google Scholar 

  24. Kamio, T. et al. B-cell-specific transcription factor BACH2 modifies the cytotoxic effects of anticancer drugs. Blood 102, 3317–3322 (2003).

    Article  CAS  Google Scholar 

  25. Xie, K. Interleukin-8 and human cancer biology. Cytokine Growth Factor Rev. 12, 375–391 (2001).

    Article  CAS  Google Scholar 

  26. Arimura, Y. et al. Elevated serum beta-defensins concentrations in patients with lung cancer. Anticancer Res. 24, 4051–4057 (2004).

    CAS  PubMed  Google Scholar 

  27. Coussens, L.M. & Werb, Z. Inflammation and cancer. Nature 420, 860–867 (2002).

    Article  CAS  Google Scholar 

  28. Gudmundsson, G. & Hunninghake, G.W. Respiratory epithelial cells release interleukin-8 in response to a thermophilic bacteria that causes hypersensitivity pneumonitis. Exp. Lung Res. 25, 217–228 (1999).

    Article  CAS  Google Scholar 

  29. Su, A.I. et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc. Natl. Acad. Sci. USA 101, 6062–6067 (2004).

    Article  CAS  Google Scholar 

  30. Bolstad, B.M., Irizarry, R.A., Astrand, M. & Speed, T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–193 (2003).

    Article  CAS  Google Scholar 

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We thank C. O'Hara for histologic review of our airway epithelial cell samples; J. Warrington, J. Palma and R. Lipshutz for their support in designing and implementing this study; M. Klempner and D. Center for their review of the manuscript; F. O'Connell, J. Lundebye and the Lung Cancer Multi-Disciplinary Team at St. James's Hospital; and the doctors and nurses of the bronchoscopy service at Boston Medical Center, St. James's Hospital and Lahey Clinic. Affymetrix Inc. provided the HG-U133A arrays for these studies. This work was supported by the Doris Duke Charitable Foundation (A.S.), US National Institutes of Health/National Institute of Environmental Health Sciences (ES10377 to J.S.B.) and National Institutes of Health/ National Cancer Institute (R21CA10650 to A.S.).

Author information

Authors and Affiliations



A.S. was responsible for the conception and design of this study and oversaw all aspects of the study including patient recruitment, experimental protocols and data analysis. J.E.B. contributed to the design of the analytic strategy and was responsible for the computational analysis of gene-expression data including preprocessing, class prediction and the connection to tumor tissue. V.S. contributed to the analysis of gene-expression and clinical data and optimization of the class prediction algorithm. K.S. was responsible for patient recruitment and for collection and analysis of clinical data on all subjects in this study. G.L. performed the microarray experiments and real-time PCR studies and was responsible for QRTPCR data analysis. F.S. performed the histologic studies of airway samples and the immunofluorescence studies. S.G. recruited subjects, collected samples and contributed to the analysis of clinical data on all subjects. Y.-M.D. was responsible for coordinating all patient recruitment and sample collection. P.C., J.B., C.L. and T.A. recruited subjects and collected samples at their respective institutions. P.S. contributed to the statistical analysis of the data. S.S. contributed to the development of the relational database. N.G. performed all microarray hybridizations. J.K. recruited subjects, collected samples and provided support in the design of the study. M.E.L. was responsible for conceptualizing many aspects of the analytic strategy and directed the computational analysis. J.S.B. was responsible for the conception and design of the study and oversaw the experimental studies and biological interpretation of the data. A.S., J.E.B., V.S., M.E.L. and J.S.B. were responsible for the writing of the manuscript and for the supplementary information.

Corresponding author

Correspondence to Avrum Spira.

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Competing interests

Affymetrix Inc. provided the HG-U133A arrays and some of the reagents for these studies.

Supplementary information

Supplementary Fig. 1

Confirmation of expression differences for selected biomarker genes by RT-PCR. (PDF 18 kb)

Supplementary Fig. 2

Inflammatory gene expression in bronchial epithelial cells. (PDF 39 kb)

Supplementary Fig. 3

Biomarker accuracy is independent of the composition of the training set. (PDF 19 kb)

Supplementary Fig. 4

Comparison of bronchoscopy cytopathology and biomarker prediction accuracies in our primary dataset by (a) cancer stage or (b) cancer subtype. (PDF 24 kb)

Supplementary Table 1

Patient demographics by dataset and cancer status. (PDF 17 kb)

Supplementary Table 2

Cell type and staging information for the 60 lung cancer patients in the n = 129 primary dataset. (PDF 11 kb)

Supplementary Table 3

Functional classification of biomarker genes. (PDF 17 kb)

Supplementary Table 4

Comparing the airway biomarker to randomized biomarkers. (PDF 16 kb)

Supplementary Table 5

Primers used for real time PCR. (PDF 14 kb)

Supplementary Methods (PDF 258 kb)

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Spira, A., Beane, J., Shah, V. et al. Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med 13, 361–366 (2007).

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