Andrea Bild, Ph.D., serves as professor in the Division of Molecular Pharmacology within the Department of Medical Oncology & Therapeutics Research. She comes to City of Hope from the University of Utah, where she was an associate professor and director of Genome Sciences.
Dr. Bild obtained her B.S. at the University of Florida, her Ph.D. at the University of Colorado, and carried out her postdoctoral training at Duke University.
Dr. Bild’s research program focuses on cancer, and uses large-scale translational genomic and pharmacological studies to interrogate and treat tumor heterogeneity and evolution to refractory states. She has led multiple collaborative groups with the goal of characterizing and treating cancer.
As a member of the National Cancer Institute’s Cancer Systems Biology Consortium and principal investigator of multi-institutional grants, her team focuses on the development and application of multi-omic tools in the clinic for cancer prevention and treatment. With clinician collaborators, Dr. Bild’s team has initiated and carried out multiple clinical trials that use systems biology and genomic characterization of patient tumors to prevent cancer resistance and progression.
Ph.D., Pharmacology, University of Colorado, Denver, Colorado
B.S., Microbiology and Cell Biology, University of Florida
2017-present, Professor, Division of Molecular Pharmacology, Department of Medical Oncology & Therapeutics Research, City of Hope, Duarte, CA
2014-2017, Associate Professor, Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT
2011-2017, Director, Genome Sciences Program, University of Utah, Salt Lake City, UT
2007, Adjunct Associate Professor, Department of Oncological Sciences, Huntsman Cancer Institute, Salt Lake City, UT
2012-2017, Adjunct Associate Professor, Department of Bioengineering, University of Utah, Salt Lake City, UT
2014-2017, Adjunct Associate Professor, Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
2007-2014, Assistant Professor, Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT
Bild’s research program focuses on cancer and rare diseases, and uses large-scale translational genomic, systems biology and pharmacological studies to interrogate and treat human disease.
She has led multiple collaborative groups with the goal of characterizing and treating disease, and has been successful in developing research-based clinical trial studies that positively impact patient care. By integrating broad disciplines centered on translational sciences, she promotes innovative scientific exploration and enables scientists to tether clinically impactful results to the enhancement of patient care. A subset of her key research initiatives, further detailed in her team’s publications, include:
Matching Biological Basis of Disease to Treatment Strategies for Translational Research
Bild’s focus on translational research comes from an understanding that it is necessary to bring leading-edge science techniques to the clinic immediately. New strategies are needed to better personalize drug therapies, as are better approaches to combat drug resistance. Systems biology can be the common platform for classifying disease states, biological networks and drug response. By finding the gene expression profiles for each of these features, her team is able to identify those profiles that “match” disease to biology to drug and more effectively treat patients.
Disease Prevention and Early Intervention Strategies
Despite the uptick in rates of discovery for diseases, such as rare and infectious diseases, there has been no corresponding uptick in drug discovery to treat them. Without mechanisms in place to rapidly identify compounds likely to be safe and effective for treating these novel diseases, health care systems risk suboptimal patient care. Bild’s team’s published research shows that it is possible to use genomic analysis to link the right drugs to individual patients. Her team currently utilizes novel genomic approaches to provide individualized and accurate assessments for unknown or novel diseases and high-risk populations.
Computational Tools for Genomic Studies
A significant component of Bild’s research program involves the development of novel computational and systems biology tools and resources in order to interrogate biologically relevant signaling events in human disease. Specifically, in close collaborations with her statistician and mathematician colleagues, Bild has contributed to the development of algorithms critical for distilling genomic and experimental data to biologically and therapeutically meaningful information.
Combating Tumor Subclone Heterogeneity
Breast and ovarian cancers are comprised of heterogeneous populations of tumors cells characterized by mutations that distinguish each cell subpopulation from one another. During treatment, tumor “subclones,” defined as a set of unique cells within a tumor, follow unique evolutionary and resistance trajectories. Using computational tools to organize this complex variation, Bild’s team will develop a new class of systems models that define subclone evolution and acquisition of oncogenic phenotypes during treatment in order to identify key chemoresistant cell states within patient cohorts. These mechanistic models will identify points of vulnerability for drug targeting. Bild’s clinical trials will be aimed at blocking transition of tumors to a resistant state by blocking critical resistant phenotypes.
Awards & Memberships
Cancer Systems Biology Consortium
Rahman, M, MacNeil, SM, Jenkins, DF, Shrestha, G, Wyatt, SR, McQuerry, JA et al. Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant subtypes. Genome Med. 2017;9 (1):40. DOI: 10.1186/s13073-017-0429-x. PubMed PMID:28446242 PubMed Central PMC5406893.
Lam, S, Mandrekar, SJ, Gesthalter, Y, Allen Ziegler, KL, Seisler, DK, Midthun, DE et al. A Randomized Phase IIb Trial of myo-Inositol in Smokers with Bronchial Dysplasia. Cancer Prev Res (Phila). 2016;9 (12):906-914. DOI: 10.1158/1940-6207.CAPR-15-0254. PubMed PMID:27658890 PubMed Central PMC5136333.
Shrestha, G, MacNeil, SM, McQuerry, JA, Jenkins, DF, Sharma, S, Bild, AH et al. The value of genomics in dissecting the RAS-network and in guiding therapeutics for RAS-driven cancers. Semin. Cell Dev. Biol. 2016;58 :108-17. DOI: 10.1016/j.semcdb.2016.06.012. PubMed PMID:27338857.
Piccolo, SR, Hoffman, LM, Conner, T, Shrestha, G, Cohen, AL, Marks, JR et al. Integrative analyses reveal signaling pathways underlying familial breast cancer susceptibility. Mol. Syst. Biol. 2016;12 (3):860. . PubMed PMID:26969729 PubMed Central PMC4812528.
Piccolo, SR, Andrulis, IL, Cohen, AL, Conner, T, Moos, PJ, Spira, AE et al. Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility. BMC Med Genomics. 2015;8 :72. DOI: 10.1186/s12920-015-0145-6. PubMed PMID:26538066 PubMed Central PMC4634735.
Rahman, M, Jackson, LK, Johnson, WE, Li, DY, Bild, AH, Piccolo, SR et al. Alternative preprocessing of RNA-Sequencing data in The Cancer Genome Atlas leads to improved analysis results. Bioinformatics. 2015;31 (22):3666-72. DOI: 10.1093/bioinformatics/btv377. PubMed PMID:26209429 PubMed Central PMC4804769.
MacNeil, SM, Johnson, WE, Li, DY, Piccolo, SR, Bild, AH. Inferring pathway dysregulation in cancers from multiple types of omic data. Genome Med. 2015;7 (1):61. DOI: 10.1186/s13073-015-0189-4. PubMed PMID:26170901 PubMed Central PMC4499940.
Shen, Y, Rahman, M, Piccolo, SR, Gusenleitner, D, El-Chaar, NN, Cheng, L et al. ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways. Bioinformatics. 2015;31 (11):1745-53. DOI: 10.1093/bioinformatics/btv031. PubMed PMID:25617415 PubMed Central PMC4443674.
El-Chaar, NN, Piccolo, SR, Boucher, KM, Cohen, AL, Chang, JT, Moos, PJ et al. Genomic classification of the RAS network identifies a personalized treatment strategy for lung cancer. Mol Oncol. 2014;8 (7):1339-54. DOI: 10.1016/j.molonc.2014.05.005. PubMed PMID:24908424 PubMed Central PMC4450766.
Zhang, H, Cohen, AL, Krishnakumar, S, Wapnir, IL, Veeriah, S, Deng, G et al. Patient-derived xenografts of triple-negative breast cancer reproduce molecular features of patient tumors and respond to mTOR inhibition. Breast Cancer Res. 2014;16 (2):R36. DOI: 10.1186/bcr3640. PubMed PMID:24708766 PubMed Central PMC4053092.
Piccolo, SR, Withers, MR, Francis, OE, Bild, AH, Johnson, WE. Multiplatform single-sample estimates of transcriptional activation. Proc. Natl. Acad. Sci. U.S.A. 2013;110 (44):17778-83. DOI: 10.1073/pnas.1305823110. PubMed PMID:24128763 PubMed Central PMC3816418.
Cohen, AL, Piccolo, SR, Cheng, L, Soldi, R, Han, B, Johnson, WE et al.. Genomic pathway analysis reveals that EZH2 and HDAC4 represent mutually exclusive epigenetic pathways across human cancers. BMC Med Genomics. 2013;6 :35. DOI: 10.1186/1755-8794-6-35. PubMed PMID:24079712 PubMed Central PMC3850967.
Steiling, K, van den Berge, M, Hijazi, K, Florido, R, Campbell, J, Liu, G et al. A dynamic bronchial airway gene expression signature of chronic obstructive pulmonary disease and lung function impairment. Am. J. Respir. Crit. Care Med. 2013;187 (9):933-42. DOI: 10.1164/rccm.201208-1449OC. PubMed PMID:23471465 PubMed Central PMC3707363.
Beane, J, Cheng, L, Soldi, R, Zhang, X, Liu, G, Anderlind, C et al. SIRT1 pathway dysregulation in the smoke-exposed airway epithelium and lung tumor tissue. Cancer Res. 2012;72 (22):5702-11. DOI: 10.1158/0008-5472.CAN-12-1043. PubMed PMID:22986747 PubMed Central PMC4053174.
Piccolo, SR, Sun, Y, Campbell, JD, Lenburg, ME, Bild, AH, Johnson, WE et al. A single-sample microarray normalization method to facilitate personalized-medicine workflows. Genomics. 2012;100 (6):337-44. DOI: 10.1016/j.ygeno.2012.08.003. PubMed PMID:22959562 PubMed Central PMC3508193.
Poerschke, RL, Franklin, MR, Bild, AH, Moos, PJ. Major differences among chemopreventive organoselenocompounds in the sustained elevation of cytoprotective genes. J. Biochem. Mol. Toxicol. 2012;26 (9):344-53. DOI: 10.1002/jbt.21427. PubMed PMID:22807314 PubMed Central PMC4551423.
Cohen, AL, Soldi, R, Zhang, H, Gustafson, AM, Wilcox, R, Welm, BE et al. A pharmacogenomic method for individualized prediction of drug sensitivity. Mol. Syst. Biol. 2011;7 :513. DOI: 10.1038/msb.2011.47. PubMed PMID:21772261 PubMed Central PMC3159972.
Potti, A, Mukherjee, S, Petersen, R, Dressman, HK, Bild, A, Koontz, J et al.. Retraction: A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006;355:570-80. N. Engl. J. Med. 2011;364 (12):1176. DOI: 10.1056/NEJMc1101915. PubMed PMID:21366430.
Potti, A, Dressman, HK, Bild, A, Riedel, RF, Chan, G, Sayer, R et al.. Retraction: Genomic signatures to guide the use of chemotherapeutics. Nat. Med. 2011;17 (1):135. DOI: 10.1038/nm0111-135. PubMed PMID:21217686.
Gustafson, AM, Soldi, R, Anderlind, C, Scholand, MB, Qian, J, Zhang, X et al. Airway PI3K pathway activation is an early and reversible event in lung cancer development. Sci Transl Med. 2010;2 (26):26ra25. DOI: 10.1126/scitranslmed.3000251. PubMed PMID:20375364 PubMed Central PMC3694402.
Tejpar, S, Bertagnolli, M, Bosman, F, Lenz, HJ, Garraway, L, Waldman, F et al. Prognostic and predictive biomarkers in resected colon cancer: current status and future perspectives for integrating genomics into biomarker discovery. Oncologist. 2010;15 (4):390-404. DOI: 10.1634/theoncologist.2009-0233. PubMed PMID:20350999 PubMed Central PMC3227961.
Bild, AH, Parker, JS, Gustafson, AM, Acharya, CR, Hoadley, KA, Anders, C et al. An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer. Breast Cancer Res. 2009;11 (4):R55. DOI: 10.1186/bcr2344. PubMed PMID:19638211 PubMed Central PMC2750116.
Chang, JT, Carvalho, C, Mori, S, Bild, AH, Gatza, ML, Wang, Q et al. A genomic strategy to elucidate modules of oncogenic pathway signaling networks. Mol. Cell. 2009;34 (1):104-14. DOI: 10.1016/j.molcel.2009.02.030. PubMed PMID:19362539 PubMed Central PMC2694616.
Mori, S, Rempel, RE, Chang, JT, Yao, G, Lagoo, AS, Potti, A et al. 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;68 (20):8525-34. DOI: 10.1158/0008-5472.CAN-08-1329. PubMed PMID:18922927 PubMed Central PMC3617051.
Dressman, HK, Berchuck, A, Chan, G, Zhai, J, Bild, A, Sayer, R et a.. An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer. J. Clin. Oncol. 2007;25 (5):517-25. DOI: 10.1200/JCO.2006.06.3743. PubMed PMID:17290060.
Dressman, HK, Bild, A, Garst, J, Harpole, D Jr, Potti, A. Genomic signatures in non-small-cell lung cancer: targeting the targeted therapies. Curr Oncol Rep. 2006;8 (4):252-7. PubMed PMID:17254524.
Potti, A, Dressman, HK, Bild, A, Riedel, RF, Chan, G, Sayer, R et al. Genomic signatures to guide the use of chemotherapeutics. Nat. Med. 2006;12 (11):1294-300. DOI: 10.1038/nm1491. PubMed PMID:17057710.
Bild, AH, Potti, A, Nevins, JR. Linking oncogenic pathways with therapeutic opportunities. Nat. Rev. Cancer. 2006;6 (9):735-41. DOI: 10.1038/nrc1976. PubMed PMID:16915294.
Potti, A, Mukherjee, S, Petersen, R, Dressman, HK, Bild, A, Koontz, J et al. A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N. Engl. J. Med. 2006;355 (6):570-80. DOI: 10.1056/NEJMoa060467. PubMed PMID:16899777.
Edelman, E, Porrello, A, Guinney, J, Balakumaran, B, Bild, A, Febbo, PG et al. Analysis of sample set enrichment scores: assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles. Bioinformatics. 2006;22 (14):e108-16. DOI: 10.1093/bioinformatics/btl231. PubMed PMID:16873460.
Dressman, HK, Hans, C, Bild, A, Olson, JA, Rosen, E, Marcom, PK et al. Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy. Clin. Cancer Res. 2006;12 (3 Pt 1):819-26. DOI: 10.1158/1078-0432.CCR-05-1447. PubMed PMID:16467094.
Bild, AH, Yao, G, Chang, JT, Wang, Q, Potti, A, Chasse, D et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature. 2006;439 (7074):353-7. DOI: 10.1038/nature04296. PubMed PMID:16273092.
Potti, A, Bild, A, Dressman, HK, Lewis, DA, Nevins, JR, Ortel, TL et al. Gene-expression patterns predict phenotypes of immune-mediated thrombosis. Blood. 2006;107 (4):1391-6. DOI: 10.1182/blood-2005-07-2669. PubMed PMID:16263789 PubMed Central PMC1895419.
Bild, A, Febbo, PG. Application of a priori established gene sets to discover biologically important differential expression in microarray data. Proc. Natl. Acad. Sci. U.S.A. 2005;102 (43):15278-9. DOI: 10.1073/pnas.0507477102. PubMed PMID:16230612 PubMed Central PMC1266131.
Delong, M, Yao, G, Wang, Q, Dobra, A, Black, EP, Chang, JT et al. DIG--a system for gene annotation and functional discovery. Bioinformatics. 2005;21 (13):2957-9. DOI: 10.1093/bioinformatics/bti467. PubMed PMID:15870167 .
Pittman, J, Huang, E, Dressman, H, Horng, CF, Cheng, SH, Tsou, MH et al. Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes. Proc. Natl. Acad. Sci. U.S.A. 2004;101 (22):8431-6. DOI: 10.1073/pnas.0401736101. PubMed PMID:15152076 PubMed Central PMC420411.
Huang, E, Ishida, S, Pittman, J, Dressman, H, Bild, A, Kloos, M et al. Gene expression phenotypic models that predict the activity of oncogenic pathways. Nat. Genet. 2003;34 (2):226-30. DOI: 10.1038/ng1167. PubMed PMID:12754511.
Huang, E, Cheng, SH, Dressman, H, Pittman, J, Tsou, MH, Horng, CF et al. Gene expression predictors of breast cancer outcomes. Lancet. 2003;361 (9369):1590-6. doi: 10.1016/S0140-6736(03)13308-9. PubMed PMID:12747878
Bild, AH, Mendoza, FJ, Gibson, EM, Huang, M, Villanueva, J, Garrington, TP et al. MEKK1-induced apoptosis requires TRAIL death receptor activation and is inhibited by AKT/PKB through inhibition of MEKK1 cleavage. Oncogene. 2002;21 (43):6649-56. DOI: 10.1038/sj.onc.1205819. PubMed PMID:12242663.