Research special interests include:
-Genomics of smoking-related lung diseases
-Lung cancer diagnostic/prognostic tools
-Genomics and the pathogenesis of COPD
-Developmental biology of the lung
-Relation of lung cancer to lung development
Cigarette smoking is the major cause of the two most costly and lethal pulmonary diseases, lung cancer and COPD. However, only 10-20% of smokers develop lung cancer; an equal number develop COPD. Thus, the majority of smokers develop neither disease. Our laboratory is using a variety of genomic tools to determine: 1) how the lung protects itself from the toxic effects of cigarette smoke; 2) why some smokers develop COPD and/or lung cancer while others are disease-free; 3) how we can use these new tools to define molecular pathways leading to each disease; 4) develop tests for the early diagnosis of lung cancer and for assessing a smokers’ risk of developing lung cancer; 5) and develop new approaches to therapy.
Our growing knowledge of the human genome and of the mechanisms regulating the transcription and translation of human genes coupled with the statistical and computational sciences that form the basis of bioinformatics provides an opportunity to develop new insights into the biologic and molecular processes associated with cigarette smoke-related lung disease.
Our present studies are based on the premise that smoking affects all of the epithelial cells of the respiratory tract and that measuring expression levels and mechanisms of regulating the levels of most of the genes in the human genome in easily accessible airway epithelial cells will provide new diagnostic and risk- assessment tools for the lung cancer as well as information about pathways leading to disease that might identify new pharmacologic targets for treating and preventing lung cancer and COPD. Most of our studies have utilized airway epithelial cells obtained by brushing a major bronchus during bronchoscopy. However, we are in the process of determining whether the airway field of smoking-induced injury extends to more accessible airway epithelial cells in the mouth or nose.
Our data shows the surprising power of this approach. It shows the relative expression levels of over 600 genes that are affected by smoking (current and past) and by the presence of lung cancer. While smoking affects gene expression in airway epithelial cells, there clearly are genes that signal the presence of lung cancer, independent of the current smoking status of the subject.
Our data demonstrates the potential value of the gene expression class prediction model we have built. Relying on bronchoscopy alone we are able to diagnose about 50% of lung cancers. Our class prediction model correctly diagnoses lung cancer 78% of the time. The combination of bronchoscopy and gene expression correctly diagnoses lung cancer 98% of the time. Class prediction in contrast to bronchoscopy, is particularly accurate (>95%) in diagnosing Stage I and II disease.
Preliminary studies of airway epithelial cell gene expression in smokers with COPD suggest that these cells reflect a different type of injury in smokers with COPD than is the case with lung cancer. In COPD, genes associated with inflammation predominate and genes associated with oxidant stress and NF?B pathways are altered.
Our interest in cancer intersects with a long-standing interest in lung development. This is based on the concept that the very processes that are involved in controlling lung cell proliferation and differentiation during development are deregulated in lung cancer. Thus information about the mechanisms regulating lung development may provide insights into pathogenesis and treatment of lung cancer.
- Graduate Faculty (Primary Mentor of Grad Students), Boston University School of Medicine, Division of Graduate Medical Sciences
- Boston Medical Center
- University of Illinois, MD
- University of Illinois, BS
- Published on 5/17/2015
Silvestri GA, Vachani A, Whitney D, Elashoff M, Porta Smith K, Ferguson JS, Parsons E, Mitra N, Brody J, Lenburg ME, Spira A. A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer. N Engl J Med. 2015 Jul 16; 373(3):243-51. PMID: 25981554.
- Published on 5/6/2015
Whitney DH, Elashoff MR, Porta-Smith K, Gower AC, Vachani A, Ferguson JS, Silvestri GA, Brody JS, Lenburg ME, Spira A. Derivation of a bronchial genomic classifier for lung cancer in a prospective study of patients undergoing diagnostic bronchoscopy. BMC Med Genomics. 2015; 8:18. PMID: 25944280.
- Published on 5/16/2014
Kathuria H, Gesthalter Y, Spira A, Brody JS, Steiling K. Updates and controversies in the rapidly evolving field of lung cancer screening, early detection, and chemoprevention. Cancers (Basel). 2014; 6(2):1157-79. PMID: 24840047.
- Published on 5/1/2014
Senior RM, Brody JS, Williams MC. The Red journal at 25. A perspective from the founding editors. Am J Respir Cell Mol Biol. 2014 May; 50(5):840-1. PMID: 24783953.
- Published on 2/15/2014
Brody JS. The promise and problems of e-cigarettes. Am J Respir Crit Care Med. 2014 Feb 15; 189(4):379-80. PMID: 24528311.
- Published on 10/5/2012
Brody JS. Transcriptome alterations induced by cigarette smoke. Int J Cancer. 2012 Dec 15; 131(12):2754-62. PMID: 22961494.
- Published on 1/1/2011
Brody JS, Steiling K. Interaction of cigarette exposure and airway epithelial cell gene expression. Annu Rev Physiol. 2011; 73:437-56. PMID: 21090967.
- Published on 4/7/2010
Gustafson AM, Soldi R, Anderlind C, Scholand MB, Qian J, Zhang X, Cooper K, Walker D, McWilliams A, Liu G, Szabo E, Brody J, Massion PP, Lenburg ME, Lam S, Bild AH, Spira A. Airway PI3K pathway activation is an early and reversible event in lung cancer development. Sci Transl Med. 2010 Apr 7; 2(26):26ra25. PMID: 20375364.
- Published on 4/9/2009
Steiling K, Kadar AY, Bergerat A, Flanigon J, Sridhar S, Shah V, Ahmad QR, Brody JS, Lenburg ME, Steffen M, Spira A. Comparison of proteomic and transcriptomic profiles in the bronchial airway epithelium of current and never smokers. PLoS One. 2009; 4(4):e5043. PMID: 19357784.
- Published on 1/23/2009
Schembri F, Sridhar S, Perdomo C, Gustafson AM, Zhang X, Ergun A, Lu J, Liu G, Zhang X, Bowers J, Vaziri C, Ott K, Sensinger K, Collins JJ, Brody JS, Getts R, Lenburg ME, Spira A. MicroRNAs as modulators of smoking-induced gene expression changes in human airway epithelium. Proc Natl Acad Sci U S A. 2009 Feb 17; 106(7):2319-24. PMID: 19168627.
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