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Published ahead of print on September 22, 2005, doi:10.1164/rccm.200502-274OC

Am. J. Respir. Crit. Care Med., Volume 172, Number 12, December 2005, 1556-1562

A more recent version of this article appeared on December 15, 2005
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Submitted on February 19, 2005
Accepted on September 20, 2005

Proteomic Patterns of Preinvasive Bronchial Lesions

S.M.Jamshedur Rahman1, Yu Shyr2, Pinar B Yildiz1, Adriana L Gonzalez3, Huiming Li2, Xueqiong Zhang2, Pierre Chaurand4, Kiyoshi Yanagisawa5, Bonnie S Slovis1, Robert F Miller1, Mathew Ninan6, York E Miller7, Wilbur A Franklin7, Richard M Caprioli4, David P Carbone8, and Pierre P Massion9*

1 Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 2 Department of Biostatistics, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 3 Department of Pathology, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 4 Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 5 Division of Hematology and Oncology, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 6 Department of Surgery, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 7 Department of Medicine and Pathology, University of Colorado Health Science Center, Denver, CO, USA, 8 Division of Hematology and Oncology, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA; Department of Cancer Biology, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA, 9 Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA; Department of Cancer Biology, Vanderbilt University School of Medicine, Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN, USA; Veterans Affairs Medical Center, Nashville, TN, USA

* To whom correspondence should be addressed. E-mail: pierre.massion{at}vanderbilt.edu.

Purpose: Proteomics approach is warranted to further elucidate the molecular steps involved in lung tumor development. We asked whether we could classify preinvasive lesions of airway epithelium according to their proteomic profile. Experimental Design: We obtained MALDI MS profiles from ten micron sections of fresh frozen tissue samples: 25 normal lung, 29 normal bronchial epithelium, 20 preinvasive and 36 invasive lung tumor tissue samples from a total of 53 patients. Proteomic profiles were calibrated, binned and normalized before analysis. We performed class comparison, class prediction and supervised hierarchical cluster analysis. We tested a set of discriminatory features obtained in a previously published dataset to classify this independent set of normal, preinvasive and invasive lung tissues. Results: We found a specific proteomic profile that allows an overall predictive accuracy of over 90% of normal, preinvasive and invasive lung tissues. The proteomic profiles of these tissues were distinct from each other within a disease continuum. We trained our prediction model in a previously published dataset and tested it in a new blinded test set to reach an overall 74% accuracy in classifying tumors from normal tissues. Conclusions: We found specific patterns of protein expression of the airway epithelium that accurately classify bronchial and alveolar tissue with normal histology from preinvasive bronchial lesions and from invasive lung cancer. Although further study is needed to validate this approach and to identify biomarkers of tumor development, this is a first step towards a new proteomic characterization of the human model of lung cancer tumorigenesis.
Key words: Mass spectrometry, preneoplasia, early detection, profiling




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