Marc Lenburg, Ph.D.
|Marc Lenburg, Ph.D.
Professor of Medicine, Section of Computational Biomedicine
Professor, Bioinformatics ProgramProfessor of Pathology
Professor, Pulmonary Center
Co-Director, Microarray Resource
Deputy Director, CTSI Translational Bioinformatics Core
Ph.D. 2000, UC San Francisco
mlenburg at bu.edu
Genome-wide approaches for improving lung disease treatment
Genomic approaches to understanding lung disease. Our lab approaches lung disease from a variety of angles, but one unifying theme is our use of comprehensive genome-wide gene-expression profiling (whether using microarray-based technology or now RNAseq) together with rigorous computational data analysis methods to discover unexpected distinctions between disease states that provide us not only with clues as to how disease develops, but also sensitive and specific tools for detecting disease.
The physiologic response to tobacco smoke. As many of our research goals are aimed at improving the treatment of patients with smoking-related lung diseases, we are interested in understanding how the body responds to tobacco smoke, and using this to better understand how tobacco smoke exposure contributes to disease. Using genomic approaches, we have identified smoking-related gene expression changes that occur throughout the respiratory tract and identified a subset that remain altered in people who have quit smoking. These irreversibly changed genes are especially interesting since disease risk remains elevated after smoking cessation. That many of the gene expression changes deep in the airway are also altered in cells that line the nose has led us to explore whether we can combine a simple nose test together with genome-wide approaches to answer basic questions such as: how physiologic responses to tobacco smoke vary amongst people who are exposed to different levels of tobacco smoke (or people who are only exposed to second-hand smoke), if differences in responses between individuals might contribute to differing levels of disease susceptibility, and if other inhaled pollutants cause similar differences in gene expression. This work is supported by grants from the NIEHS.
Detecting lung cancer. Using genomic approaches that allow us to comprehensively identify gene expression differences, we have identified a number of differences between smokers who have lung cancer and others who were thought to potentially have lung cancer but turn out instead to have a benign disease. We detect these expression differences in normal-looking cells from the large airway that are collected during bronchoscopy: a routine clinical procedure that is often employed as an early step in figuring out whether someone has lung cancer. We have shown that we can use a combination of several such genes as a biomarker that is both sensitive and specific for distinguishing smokers with lung cancer from those with benign disease and that this biomarker is more sensitive than the standard workup done as part of the routine bronchoscopy procedure. This biomarker has been licensed to a company that is seeking to validate its performance and make it available for clinicians to use as an adjunct to bronchoscopy. We are now determining whether these cancer-specific signals can also be detected in samples from the nose and whether there are gene expression differences that occur prior to the development of clinically detectable cancer in the hope that such differences could be used as a biomarker for assessing lung cancer risk. Lung cancer risk assessment could be used to determine which current and former smokers might benefit from increased lung cancer screening, or those who are good candidates for drugs that might prevent lung cancer. This work is supported by grants from the NCI and the Department of Defense.
Assessing and understanding COPD and emphysema. Chronic Obstructive Pulmonary Disease (COPD) and emphysema are debilitating smoking-related lung diseases that often develop over an extended period and can be remarkably different between different patients. Using very similar approaches as our work in smoking and lung cancer, we have begun to identify gene expression differences that occur in the airway in patients with COPD and emphysema. Interestingly, the COPD-related gene-expression differences in the larger airways that we’ve studied are similar to the differences that occur in the small airways and alveolae: the tissues that are thought to be the main sites of disease. Moreover, these gene expression differences are more severe in patients with more severe disease and are diminished following treatment with anti-COPD therapy. These studies open the possibility of being able to molecularly dissect the clinical differences between patients with COPD using airway tissue readily obtained during bronchoscopy, and to develop biomarkers for monitoring a patient’s response to therapy. This work is supported by grants from the NHLBI.
Mechanisms of disease pathogenesis. In addition to developing biomarkers for assessing lung disease in clinical samples, we are also interested in using genome-wide approaches to improve our molecular understanding of lung disease pathogenesis. One strategy that we have used to model disease progression in both emphysema and lung cancer is to perform gene-expression profiling on multiple tissues from the same patient collected from regions of differing disease severity. Using this approach we have identified specific molecular processes involved in tissue remodeling that are specifically altered in regions of more severe emphysema. By combining these data with computational approaches to search databases of drugs, we have identified an existing drug as a potential emphysema therapeutic and validated that this drug reverses aspects of the emphysema gene expression signature and molecular defects in tissue remodeling pathways.
A second approach has involved identifying microRNA expression differences associated with disease. While we are exploring using microRNA (miRNA) expression differences as the basis for biomarkers similar to our gene (mRNA) expression biomarkers, the regulatory function of miRNA makes them especially attractive for understanding the regulation of disease processes. The majority of our miRNA profiling work has been performed using high throughput RNA sequencing technology that has allowed us to develop a comprehensive portrait of all the small RNA that are expressed both in airway and lung tissue and discover a number of new miRNA. We have identified specific miRNA that are important regulators of the response to smoking as well as other miRNA that contribute to airway epithelial cell differentiation and repress aspects of lung carcinogenesis.
A third approach to understanding disease pathogenesis has involved the use of high throughput RNA sequencing to provide a comprehensive genome-wide view of the lung transcriptome at single nucleotide resolution. We are mining these data to identify disease-associated differences in transcript structure, expression of non-coding RNAs, etc. in the hope that they could serve as biomarkers, but more importantly that they might also provide specific clues as to the regulation of processes that contribute to disease pathogenesis.
Our work on the molecular regulation of the response to smoking and lung disease pathogenesis is supported by grants from the NIEHS, NHLBI and the Department of Defense.
Computational tools for clinical genomics. A critical challenge with the genome-wide expression technologies that we use in our research is sifting through the large volumes of data they generate to find disease-associated differences that are informative either for use as biomarkers or for understanding the mechanisms of disease. A large portion of our activity is therefore focused on identifying the computational, statistical, and bioinformatic strategies that are most powerful for doing this. One area of research involves developing approaches to use the large volume of publicly available gene-expression data as a source of knowledge about how genes are coexpressed across diverse conditions; and to develop methods that allow this information to be incorporated into the biomarker discovery process or used to identify biologically related conditions based on their resulting in similar differences in gene expression. While these sorts of methods may have broad applicability beyond the study of lung disease, our hope is that they will enhance our ability to gain useful insights and clinically useful tools for the treatment of lung disease. This work is supported by grants from the NCRR.
1. Snyder, R.W., M. E. Lenburg, A. T. Seebaum, L. B. Grabel. 1992. Disruption of the cytoskeleton-extracellular matrix linkage promotes the accumulation of plasminogen activators in F9 derived parietal endoderm. Differentiation. 50:153-162. PMID: 1330791.
2. Lenburg, M. E., N. R. Landau. 1993. Vpu-induced degradation of CD4: requirements for specific amino acid residues in the cytoplasmic domain of CD4. Journal of Virology. 67:7238-7245. PMID: 8230446. PMC238186.
3. Aiken, C., J. Konner, N. Landau, M. Lenburg, D. Trono. 1994. Nef induces CD4 endocytosis: requirement for a critical di-leucine motif in the membrane proximal CD4 cytoplasmic domain. Cell. 76(5):853-64. PMID: 8124721.
4. Anderson S. J., M. Lenburg , N. R. Landau, J.V. Garcia. 1994. The cytoplasmic domain of CD4 is sufficient for its down-regulation from the cell surface by human immunodeficiency virus type 1 Nef. Journal of Virology. 68:3092-101. PMID: 8151774. PMC236799.
5. Lenburg, M. E. and E. K. O’Shea. 1996. Signaling phosphate starvation. Trends in Biochemical Sciences. 21: 383-7. PMID: 8918192.
7. Lenburg, M. E., L. S. Liou, N. P. Gerry, G. M. Frampton, H. T. Cohen, M. F. Christman. 2003. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data. BMC Cancer. 3:31. PMID: 14641932. PMC317310.
8. Carson, J. P., N. Zhiang, G. Frampton, N. P. Gerry, M. E. Lenburg and M. F. Christman. 2004. Pharmacogenomic identification of targets for adjuvant therapy with the topoisomerase poison camptothecin. Cancer Research. 64:2096-104. PMID: 15026349.
9. King, C., N. Guo, G. M. Frampton, N. P. Gerry, M. E. Lenburg and C. L. Rosenberg. 2005. Reliability and reproducibility of gene expression measurements using amplified RNA from laser microdissected primary breast tissue with oligonucleotide arrays. Journal of Molecular Diagnostics. 7:57-64. PMID: 15681475. PMC1867505.
10. Klings, E. S., S. Safaya, A. H. Adewoye, A. Odhiambo, G. Frampton, M. Lenburg, N. Gerry, P. Sebastiani, M. H. Steinberg, and H. W. Farber. 2005. Differential Gene Expression in Pulmonary Artery Endothelial Cells Exposed to Sickle Cell Plasma. Physiological Genomics. 21:293-8. PMID: 15741505.
11. Kanefsky, J., M. Lenburg, and C.-M. Hai. 2006. Amplitude and frequency effects of cyclic stretch-induced inflammatory gene expression in intact airway smooth muscle. American Journal of Respiratory Cell and Molecular Biology. 34:417-425. PMID: 16339998. PMC2644203.
12. Herbert, A., N. P. Gerry, M. McQueen, I. M. Heid, A. Pfeufer, T. Illig, H.-E. Wichmann, T. Meitinger, D. Hunter, F. B. Hu, G. Colditz, A. Hinney, J. Hebebrand, K. Koberwitz, X. Zhu, R. Cooper, K. Ardlie, H. Lyon, J. Hirschhorn, N. M. Laird, M. E. Lenburg, C. Lange and M. F. Christman. 2006. A common genetic variant is associated with adult and childhood obesity. Science. 5771:279-283. PMID: 16614226.
13. Tchkonia, T., M. Lenburg, T. Thomou, N. Giorgadze, G. Frampton, T. Pirtskhalava, A. Cartwright, M. Cartwright, J. Flanagan, I. Karagiannides, N. Gerry, R. Forse, Y. Tchoukalova, M. Jensen, C. Pothoulakis, J. Kirkland. 2007. Identification of Depot-Specific Human Fat Cell Progenitors through Distinct Expression Profiles and Developmental Gene Patterns. American Journal of Physiology – Endocrinology and Metabolism. 292:298-307. PMID: 16985259.
14. Herbert, A.*, M. E. Lenburg*, D. Ulrich, N. P. Gerry, K. Schlauch, M. F. Christman. 2007. Open access database for candidate quantitative-trait associations from a dense genome-wide association study of the Framingham Heart Study. Nature Genetics. 39:135-136. (* joint first authors). PMID: 17262019.
15. Lenburg, M. E., A. Sinha, D. V. Faller and G. V. Denis. 2007. Tumor-specific and proliferation-specific gene expression typifies murine transgenic B cell lymphomagenesis. Journal of Biological Chemistry. 282:4803-4811. PMID: 17166848. PMC2819333.
16. Spira, A., J. Beane, V. Shah, K. Steiling, G. Liu, F. Schembri, S. Gilman, Y.-M. Dumas, P. Calner, P. Sebastiani, S. Sridhar, J. Beamis, C. Lamb, T. Anderson, N. Gerry, J. Keane, M. E. Lenburg, J. S. Brody. 2007. Airway Epithelial Gene Expression in the Diagnostic Evaluation of Smokers with Suspect Lung Cancer. Nature Medicine. 13:361-366. PMID: 17334370.
17. Beane, J.E., P. Sebastiani, G. Liu, J.S. Brody, M.E. Lenburg, A. Spira. 2007. Reversible and Permanent effects of Tobacco Smoke Exposure on Airway Epithelial Gene Expression. Genome Biology. 8:R201. PMID: 17894889. PMC2375039.
18. Tripathi, A., C. King, A. de la Morenas, G. Antoine, E. Hirsch, M. Kavanah, J. Mendez, M. Stone, N. P. Gerry, M.E. Lenburg, C.L. Rosenberg. 2007. Gene expression differences between histologically-normal breast epithelium of breast cancer cases and controls. International Journal of Cancer. 122:1557-1566. PMID: 18058819.
19. Zhang, X., G. Liu, M.E. Lenburg, A. Spira. 2007. Comparison of smoking-induced gene expression on Affymetrix exon and 3’-based expression arrays. Genome Informatics. 18:247-257. PMID: 18546492.
20. Millien, G., J. Beane, M. Lenburg, P-N. Tsao, J. Lu, A. Spira, M.I. Ramirez. 2008. Characterization of the mid-foregut transcriptome identifies genes regulated during lung bud induction. Gene Expression Patterns. 8:124-139. PMID: 18023262. PMC2440337.
21. Sridhar, S., F. Schembri, J. Zeskind, V. Shah, A.M. Gustafson, K. Steiling, G. Liu, Y.M. Dumas, S. Zhang, J. Brody, M.E. Lenburg, A. Spira. 2008. Smoking-induced gene expression changes in the bronchial airway are reflected in nasal and buccal epithelium. BMC Genomics. 9:259. PMID: 18513428. PMC2435556.
22. Blick, T., E. Widodo, H. Hugo, M. Waltham, M.E. Lenburg, R.M. Neve, E Thompson. 2008. Epithelial mesenchymal transition traits in human breast cancer cell lines. Clinical and Experimental Metastasis. 25:629-642. PMID: 18461285.
23. Beane, J.E., P. Sebastiani, T.H. Whitfield, K. Steiling, Y-M. Dumas, M.E. Lenburg, A. Spira. 2008. A prediction model for diagnosing lung cancer that integrates genomic and clinical features. Cancer Prevention Research. 1:56-64. PMID: 19138936
24. Zeskind, J., M. E. Lenburg, A. Spira. 2008. Translating the COPD transcriptome: insights into pathogenesis and tools for clinical management. Proceedings of the American Thoracic Society. 5:834-841. PMID: 19017738. PMC2645236.
25. Merritt, W., Y. G. Lin, L. Y. Han, A. A. Kamat, W. A. Spannuth, R. Schmandt, D. Urbauer, L. A. Pennacchio, J-F Cheng, A. Zeidan, H. Wang, P. Mueller, M. E. Lenburg, J. W. Gray, S. Mok, M. J. Birrer, G. Lopez-Berestein, R. L. Coleman, M. Bar-Eli, A. K. Sood. 2008. Decreased Expression of RNA Interference Machinery, Dicer and Drosha, is Associated with Poor Outcome in Ovarian Cancer Patients. New England Journal of Medicine. 359:2641-2650. PMID: 19092150. PMC2710981.
27. Liu, P., D.M. Slater, M. Lenburg, K. Nevis, J. Cook, C. Vaziri. 2009. Replication licensing promotes Cyclin D1 expression and G1 progression in untransformed human cells. Cell Cycle. 8:125-136. PMID: 19106611.
28. Schembri, F., S. Sridhar, C. Perdomo, A. Gustafson, X. Zhang, A. Ergun, J. Lu, G. Liu, X. Zhang, J. Bowers, K. Sensinger, J.J. Collins, J. Brody, R. Getts, M.E. Lenburg, A. Spira. 2009. MicroRNAs as modulators of smoking-induced gene-expression changes in human airway epithelium. Proceedings of the National Academy of Sciences. 106:2319-24. PMID: 19168627. PMC2650144.
29. Zhu, J., J.Z. Sanborn, S. Benz, F. Hsu, C. Szeto, R.M. Kuhn, D. Karolchik, J. Archie, M.E. Lenburg, L.J. Esserman, W.J. Kent, T. Wang, D. Haussler. 2009. The UCSC Cancer Genomics Browser. Nature Methods. 6:239-240. PMID: 19333237.
30. Steiling, K., A.Y. Kadar, A. Bergerat, J. Flanigon, S. Sridhar, V. Shah, M.E. Lenburg, Q. R. Ahmad, M. Steffen, J.S. Brody, A. Spira. 2009. Proteomic differences in large-airway epithelial cells collected from never and current smokers. PLoS ONE. 4(4): e5043.s. PMID: 19357784. PMC2664466.
31. Zhou, J., W. Huang, S. Ibaragi, Y. Ido, X. Wu, Y.O. Alekseyev, M.E. Lenburg, G. Hu, Z. Luo. 2009. Inactivation of AMPK alters gene expression and promotes the growth of prostate cancer cells. Oncogene. 28(18):1993-2002. PMID: 19347029. PMC2679420.
32. Steiling, K., M.E. Lenburg, A. Spira. 2009. Airway gene expression in chronic obstructive pulmonary disease. Proceedings of the American Thoracic Society. 6:697-700. PMID: 20008878. PMC2797071.
33. Papageorgis, P., A. Lambert, S. Ozturk, F. Gao, H. Pan, U. Manne, Y. Alekseyev, A. Thiagalingam, H. Abdolmaleky, M. Lenburg, S. Thiagalingam. 2010. Smad signaling is required to maintain epigenetic silencing during breast cancer progression. Cancer Research. 70:968-978. PMID: 20086175. PMC2946209
34. Palomares, K.T.S., L.C. Gerstenfeld, N.A. Wigner, M.E. Lenburg, T.A. Einhorn, E.F. Morgan. 2010. Transcriptional profiling and biochemical analysis of mechanically induced cartilaginous tissues. Arthritis & Rheumatism. 62:1108-18. PMID: 20131271. PMC2929815
35. Cartwright, M.J, K. Schlauch, M. E. Lenburg, T. Tchkonia, T. Pirtskhalava, A. Cartwright, T. Thomou, J. L. Kirkland. 2010. Aging, Depot Origin, and Preadipocyte Gene Expression. Journal of Gerontology: Biological Sciences. 65:242-251. PMID: 20106964. PMC2904595.
36. Zhang, X., G. Liu, F. Schembri, X. Zhang, Y.-M. Dumas, E.M. Langer, Y. Alekseyev, G.T. O’Connor, D.R. Brooks, P. Sebastiani, M.E. Lenburg*, A. Spira*. 2010. Similarity and differences in effect of cigarette smoking on gene expression in nasal and bronchial epithelium. Physiological Genomics. 41:1-8. (* contributed equally). PMID: 19952278. PMC2841495
37. Gustafson, A., R. Soldi, C. Anderlind, M.B Scholand, X. Zhang, D. Walker, A. McWilliams, G. Liu, E. Szabo, M.E. Lenburg, S. Lam, A.H. Bild, A. Spira. 2010. Deregulation of the phosphatidylinositol 3-kinase pathway in the bronchial airway epithelium is an early and reversible event in the development of lung cancer. Science Translational Medicine. 2:26ra25. PMID: 20375364
38. Hu, Z., G. Huang, A. Sadanandam, M.E. Lenburg, S Gu, N Bayani, E.A. Blakely, J.W. Gray, J-H Mao and M. Pai. 2010. The expression level of HJURP has an independent prognostic impact and predicts the sensitivity to radiotherapy in breast cancer. Breast Cancer Research. 12(2):R18. PMID: 20211017. PMC2879562.
39. Blick T., H. Hugo, E. Widodo, M. Waltham, S. Mani, R.A. Weinberg, R. M. Neve, M.E. Lenburg, E.W. Thompson. 2010. Epithelial Mesenchymal Transition Traits in a Panel of Human Breast Cancer Cell Lines Parallel the CD44hi/CD24lo/- Human Breast Cancer Stem Cell Phenotype. Journal of Mammary Gland Biology and Neoplasia. 15:235-52. PMID: 20521089
40. Panchenko, M.P., D.M. Dombowski, Y.O. Alekseyev, M.E. Lenburg, T.E. MacGillvray, F.I. Preffer, J.R. Stone. 2010. Critical role of the H2O2-responsive nuclear kinase CK1αLS in vascular cell activation. American Journal of Pathology. 177:1562-72. PMID: 20696773. PMC2928985.
41. Ooi AT, V Mah, DW Nickerson, JL Gilbert, VL Ha, AE Hegab, S Horvath, MT Alavi, EL Maresh, D Chia, AC Gower, ME Lenburg, A Spira, II Wistuba, TC Walser, WD Wallace, SM Dubinett, L Goodglick and BN Gomperts. 2010. A putative tumor-initiating progenitor cell population predicts poor prognosis in smokers with non-small cell lung cancer. Cancer Research. 70:6639-48. PMID: 20710044. PMC2924777
42. Boelens, M.C., A.M. Gustafson, D.S. Postma, K. Kok, G. van der Vries, P. van der Vlies, A. Spira, M.E. Lenburg, M. Geerlings, H. Sietsma, W. Timens, A. van den Berg, H.J.M. Groen. 2011. A chronic obstructive pulmonary disease related signature in squamous cell lung cancer. Lung Cancer. 72:177-83. PMID: 20832896.
43. Campbell, J.D, A. Spira, M.E. Lenburg. 2011. Applying gene-expression microarrays to pulmonary disease. Respirology. 16:407-418. PMID: 21299687.
44. Gower, A.C., K. Steiling, J.F. Brothers II, M.E. Lenburg, A. Spira. 2011. Transcriptomic studies of the airway “field of injury” associated with smoking-related lung disease. Proceedings of the American Thoracic Society. 8:173-179. PMID: 21543797.
45. Beane, J.E., J. Vick, F. Schembri, C. Anderlind, A.C. Gower, J. Campbell, L. Luo, X. Zhang, J. Xiao, Y.O. Alekseyev, S. Wang, S. Levy, P.P. Massion, M.E. Lenburg, A. Spira. 2011. Characterizing the impact of smoking and lung cancer on the airway transcriptome using RNA-seq. Cancer Prevention Research. 4:803-817. PMID: 21636547.
46. Gower, A.C., A. Spira, M.E. Lenburg. 2011. Discovering biological connections between experimental conditions based on common patterns of differential gene expression. BMC Bioinformatics. 12:381.