B.S., 1996, University of Florida, Microbiology
Ph.D., 2001, University of Colorado, Pharmacology
Post-doctoral Research, Duke University, Genomics
Understanding the biological and clinical diversity of cancer is an opportune area for the application of genomic approaches. Molecular-profiling studies, particularly DNA microarray analyses, have the potential to describe the complexity of cancer phenotypes, and provide an opportunity to link these phenotypes to clinically relevant information, such as therapeutic strategies. My lab focuses on the signal transduction pathways that contribute to the oncogenic processes such as tumor initiation or metastasis with the ultimate goal of identifying novel therapeutic strategies.
While past studies have focused on the pathway status of oncogenic/tumor suppressor pathways in primary and mostly early stage tumors, we wish to extend this work to study models of tumor progression. This approach offers the potential to provide a more powerful characterization of tumor progression. The studies of Vogelstein and colleagues established the paradigm for the sequential accumulation of genetic alterations as tumors progress from a benign to a malignant state. These studies were dependent on the ability to characterize precise gene mutations. In contrast, the analysis of gene expression signatures reflecting pathway deregulation identifies the functional consequence of gene mutations. More importantly, this approach provides the opportunity to integrate the data, through the clustering of pathway deregulation events, to identify patterns of pathway deregulation that characterize a given tumor state. As such, the analysis goes beyond the identification of the relation of a single event with a phenotype and offers the ability to examine the importance of combinations of events. This approach will be all the more powerful as additional signatures are developed that reflect other pathways as well as the sub-components of the existing pathways. The penultimate goal of these studies is to uncover the events that lead to both cancer initiation and tumor metastasis. To this end, pre-malignant and metastatic tissue will be used for prediction analyses with the compendium of signatures both previously generated, and those generated for this specific goal. By using a directed approach in predicting pathway status in tumors, we are able to isolate the signaling aberrations that are important in driving tumorigenesis. Importantly, these studies give us the opportunity to identify and further study chromosomal rearrangements common to a particular signaling pathway, as well as drugs that specifically target these pathways. It remains a challenge to discover deregulation of specific pathways that have a causal role in cancer, particularly those that initiate the process, and those that lead to systemic disease. Advances in understanding and targeting the concerted signaling driving these processes will aid in preventative intervention and more successful treatment during the course of tumor progression.
Another specific area of research includes the study of breast cancer phenotypes. In these studies, supervised analysis is used to discover the underlying biology of distinct subclasses of breast tumors. Specifically, we find unique signaling pathways are deregulated in luminal, basal, and HER2 positive breast tumor subtypes. These patterns of pathway deregulation are consistent across multiple datasets. Further, using gene expression signatures that accurately predict chemotherapeutic response in patients and cell lines, these subclasses of tumors are shown to have distinctive profiles of sensitivity to individual chemotherapeutic drugs. More in-depth analyses of these tumor subtypes identifies the unique pathway and drug resistance characteristics of patients who have tumor recurrence. A significant aspect of these studies is the identification of patterns of pathway activation in distinct breast tumor subtypes, reflecting the biological differences of these tumor phenotypes. Further, the correlation of these tumor subtypes to therapeutic responses outlines the resultant clinical diversity. The development of gene expression profiles that predict both pathway deregulation and response to targeted therapies as well as sensitivity to common cytotoxic agents provides a genomic approach with the capacity to identify therapeutic strategies most effective for the individual subtypes of breast cancer.
Other research includes investigating the aberrant biochemical changes that occur upon smoke exposure and predispose one to cancer development. Past studies have uncovered many signal transduction pathways activated upon exposure to cigarette smoke. These stress responses serve to protect cells from injury; however, long-term activation potentially contributes to the pathogenesis of COPD and lung cancer. We are focused on perturbing genes that are central to the major pathways related to smoke exposure and that we have shown to be altered in the bronchial airway epithelial cells of smokers. These pathway signatures will be applied to predict genetic changes that predispose smokers to disease as well as provide insights into novel targets for chemoprophylaxis strategies in smokers.
Dressman HK, Berchuck A, Chan G, Zhai J, Bild A, Sayer R, Cragun J, Clarke J, Whitaker RS, Li L, Gray J, Marks J, Ginsburg GS, Potti A, West M, Nevins JR, Lancaster JM. An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer. J Clin Oncol. 2007 Feb 10;25(5):517-25.
Mori S, Rempel RE, Chang JT, Yao G, Lagoo AS, Potti A, Bild A, Nevins JR. Utilization of pathway signatures to reveal distinct types of B lymphoma in the Emicro-myc model and human diffuse large B-cell lymphoma. Cancer Res. 2008 Oct 15;68(20):8525-34.
Chang JT, Carvalho C, Mori S, Bild AH, Gatza ML, Wang Q, Lucas JE, Potti A, Febbo PG, West M, Nevins JR. A genomic strategy to elucidate modules of oncogenic pathway signaling networks. Mol Cell. 2009 Apr 10;34(1):104-14.
Bild AH*, Parker JS, Gustafson AM, Acharya CR, Hoadley KA, Anders C, Marcom PK, Carey LA, Potti A, Nevins JR, Perou CM. An Integration of Complementary Strategies for Gene Expression Analysis to Reveal Novel Therapeutic Opportunities for Breast Cancer. Breast Cancer Research, 2009 Jul 28;11(4):R55.
Gustafson AM, Soldi R, Anderlind C, Scholand M, Zhang X, Walker D, McWilliams A, Liu G, Szabo E, Brody J, Lenburg M, Lam S, Bild AH*, Spira A*. Deregulation of the PI3K pathway in the bronchial airway epithelium is an early and reversible event in the development of lung cancer. In review.
Potti, A., Dressman, H.K., Bild, A. , Riedel, R.F., Chan, G., Sayer, R., Cragun, J., Cottrill, H., Kelley, M.J., Petersen, R., Harpole, D., Marks, J., Berchuck, A., Ginsburg, G.S., Febbo, P., Lancaster, J., Nevins, J.R. Genomic signatures to guide the use of chemotherapeutics. Nat Med . 2006 Nov;12(11):1294-300. Epub 2006 Oct 22.
Bild, A.H. , Potti, A., and Nevins, J.R. Linking oncogenic pathways with therapeutic opportunities. Nat Rev Cancer . 2006 Sep;6(9):735-41. Epub 2006 Aug 17. Review.
Kong, L.J., Chang, J.T., Bild, A.H ., and Nevins, J.R. Compensation and specificity of function within the E2F family. Oncogene . 2006 Aug 14 [epub].
Potti, A., Mukherjee, S., Petersen, R., Dressman, H.K., Bild, A ., Koontz, J., Kratzke, R., Watson, M., Kelley, M., Ginsburg, G.S., West, M., Harpole, D., and Nevins, J.R.. A Genomic Strategy to Refine Prognosis in Early Stage Non-Small Cell Lung Carcinoma. N Engl J Med ., 2006 Aug 10;355(6):570-80.
Dressman, H.K., Hans, C., Bild, A. , Olson, J.A., Rosen, E., Marcom, P.K., Liotcheva, V., Jones, E., Vujaskovic, Z., Marks, J., Dewhirst, M.W., West, M., Nevins, J.R., and Blackwell, K. Gene Expression Profiles of Multiple Breast Cancer Phenotypes and Response to Neoadjuvant Chemotherapy. Clinical Cancer Research , 2006 Feb 1;12(3 Pt 1):819-26.
Bild, A.H. , Yao, G., Chang, J.T., Wang, Q., Potti, A., Chasse, D., Joshi, M., Harpole, D., Lancaster, J.M., Berchuck, A., Olson, Jr., J.A., Marks, J.R., Dressman, H.K., West, M., and Nevins, J.R. Oncogenic Pathway Signatures in Human Cancers As a Guide To Targeted Therapies. Nature . 2006 Jan 19;439(7074):353-7. Epub 2005 Nov 6.
Potti, A., Bild, A.H. , Dressman, H.K., Lewis, D.A., Nevins, J.R., and Ortel, T.R. Gene Expression Patterns Predict Phenotypes of Immune-Mediated Thrombosis. Blood , November, 2005 (epub).
Bild, A. , and Febbo, P.G. Application of a priori established gene sets to discover biologically important differential expression in microarray data. Proc Natl Acad Sci USA , 2005 Oct 25; 102(43):15278-9. Epub 2005 Oct 17.
Delong, M., Yao, G., Wang, Q., Dobra, A., Black, E.P., Chang, J.T., Bild, A. , West, M., Nevins, J.R., Dressman, H.K. DIG--a system for gene annotation and functional discovery. Bioinformatics. 2005 Jul 1; 21(13):2957-9. Epub 2005 May 3.
Pittman, J., Huang, E., Dressman, H.K., Horng, C.F., Cheng, S.H., Tsu, M.H., Bild, A.H. , Iversen, E.S., Huang, A.T., Nevins, J.R., and West, M. Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes . Proc Natl Acad Sci USA. 101(22), 8431-6 (2004).
Huang, E., Cheng, S.H., Dressman, H, K., Pittman, J., Tsu, M.H., Horng, C.F., Bild, A.H. , Iversen, E.S., Liao, M., West, M., Nevins, J.R., and Huang, A.T. Prediction of Breast Cancer States and Outcomes by Incorporating Gene Expression Patterns. Lancet. 361(9369), 1590-6 (2003).
Huang, E., Ishida, S., Pittman, J., Dressman, H., Bild, A.H. , Pestell, R.G., West, M., and Nevins, J.R. Gene Expression Phenotypic Models That Predict the Activity of Oncogenic Pathways. Nature Genetics. 34(2), 226-30 (2003).
Bild, A.H. , Gibson, E.M., Onio, J., Garrington, T.P., Johnson, G.L., and Gibson, S.B. MEKK1-induced apoptosis requires TRAIL death receptor activation and is inhibited by Akt through inhibition of MEKK1 cleavage. Oncogene. 21(43), 6649-56 (2002).
Bild, A.H. , Turkson, J.K., and Jove, R. Cytoplasmic Transport of Stat3 by Receptor-mediated Endocytosis. EMBO J. 21(13), 3255-63 (2002).
Sorkina, T., Bild, A. , Tebar, F., and Sorkin, A. Clathrin, adaptors and eps15 in endosomes containing activated epidermal growth factor receptors. Journal of Cell Science. 112, 317-327 (1999).