Erich S. Huang, MD, PhD

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• Breast Cancer

Department / Division:
Surgery / General Surgery

Address:
DUMC 2945
Durham, NC 27710

Office Telephone:
919-684-6849

Fax Telephone:
919-668-4777

• MD, Duke University School of Medicine, 2003

• General Surgery, Duke University Medical Center, 2003-2008

• PhD, Genetics, Duke University Medical Center, 2002

Clinical Interests:
Breast cancer, research interest in solid tumor gene expression analysis, oncogenic pathway analysis, computational and systems biology

Research Interests:
My interest is in developing and testing quantitative models of oncogenic pathway activation. This extends previous work where I demonstrated that ectopic Myc and Ras activity in cell culture generated transcriptional changes that allow one to model their activity in in vivo. Gene expression-based models accurately recapitulate the activity of Myc-activated and Ras-activated pathways in the cell cycle, demonstrating kinetics that match their known biochemical activity and, more importantly, accurately predict the activity of Myc and Ras in tumor tissues from MMTV transgenic mouse models. This work has subsequently led to gene expression-based pathway models that appropriately predict pathway-specific drug sensitivity.

As a next step I am investigating methods to develop pathway predictors that are representative of components or "modules" of pathway activity. The advantage of looking at components is that we can tailor our understanding of pathway activation in tumors to variations in their componentry allowing us to better understand the heterogeneous behaviors of tumors.

This will require training datasets that are of sufficient complexity to encompass the range of perturbations that are seen in both physiologic and pathologic settings; therefore the complex pathway structure within these datasets can be discovered by our computational methods. With a comprehensive "library" of pathways and pathway components one can go about discovering how interacting pathways and sub-pathways can lead from regulated cell-proliferation to the dysregulated processes of premalignant lesions and malignancy. A key component to this will be developing computational approaches to linking pathways and their components together to a particular clinical or biologic phenotype. Part of my research effort will be investigating stochastic search and tree-modeling methodologies to accomplish this.

We will test our models in the setting of solid tumors such as colon cancer that have a well-established paradigm of progression from normal tissue to malignant tissue. It has been long accepted that colon cancer arises out of initial, followed by successive mutational events causing perturbations in growth regulatory and tumor suppressor programs. Our hope is to model these very events by quantitatively evaluating the pathways and sub-pathways with our models. These models differ from identifying single gene mutations because the information from genome-scale transcriptional data allow one to add a quantitative understanding of pathway activity. In other words, we seek to understand not only whether a pathway is active or not, but how active it is.

Bringing these computational techniques back to experimental biology is an important component of this research. We will take advantage of new technologies that allow us to create customized assays of pathway activity in a multiplex fashion and use tools such as genome-wide RNAi libraries to directly interrogate pathway interactions, allowing us to identify pathway synergies in the setting of neoplasia.

Representative Publications:
Cheng SH, Horng CF, West M, Huang E, Pittman J, Tsou MH, Dressman H, Chen CM, Tsai SY, Jian JJ, Liu MC, Nevins JR, Huang AT. Genomic prediction of locoregional recurrence after mastectomy in breast cancer. J Clin Oncol. 2006 Oct 1;24(28):4594-602. (2006) Abstract

Pittman J, Huang E, Nevins J, Wang Q, West M. Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes. Biostatistics. 2004 Oct;5(4):587-601. (2004) Abstract

Huang ES, Nevins JR, West M, Kuo PC. An overview of genomic data analysis. Surgery. 2004 Sep;136(3):497-9. (2004) Abstract

Nevins JR, Huang ES, Dressman H, Pittman J, Huang AT, West M. Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction. Hum Mol Genet. 2003 Oct 15;12 Spec No 2:R153-7. (2003) Abstract

Huang E, West M, Nevins JR. Gene expression profiling for prediction of clinical characteristics of breast cancer. Recent Prog Horm Res. 2003;58:55-73. (2003) Abstract

Huang E, Ishida S, Pittman J, Dressman H, Bild A, Kloos M, D'Amico M, Pestell RG, West M, Nevins JR. Gene expression phenotypic models that predict the activity of oncogenic pathways. Nat Genet. 2003 Jun;34(2):226-30. (2003) Abstract

Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF, Bild A, Iversen ES, Liao M, Chen CM, West M, Nevins JR, Huang AT. Gene expression predictors of breast cancer outcomes. Lancet. 2003 May 10;361(9369):1590-6. (2003) Abstract

Black EP, Huang E, Dressman H, Rempel R, Laakso N, Asa SL, Ishida S, West M, Nevins JR. Distinct gene expression phenotypes of cells lacking Rb and Rb family members. Cancer Res. 2003 Jul 1;63(13):3716-23. (2003) Abstract

West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson JA Jr, Marks JR, Nevins JR. Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11462-7. (2001) Abstract

Leone G, Sears R, Huang E, Rempel R, Nuckolls F, Park CH, Giangrande P, Wu L, Saavedra HI, Field SJ, Thompson MA, Yang H, Fujiwara Y, Greenberg ME, Orkin S, Smith C, Nevins JR. Myc requires distinct E2F activities to induce S phase and apoptosis. Mol Cell. 2001 Jul;8(1):105-13. (2001) Abstract

Ishida S, Huang E, Zuzan H, Spang R, Leone G, West M, Nevins JR. Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis. Mol Cell Biol. 2001 Jul;21(14):4684-99. (2001) Abstract