Education: BS in Biology, University of North Carolina at Chapel Hill, 1988-1992
MS in Molecular Biology/Biotechnology, East Carolina University, 1993-1995
PhD in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, 1995-2001 Research Interests:  My research is focused on the discovery and characterization of mechanistic and clinically useful aspects of carcinogenesis from a systems biology perspective. Using genomics technologies such as DNA microarrays, my laboratory investigates the transcriptional dynamics and genomic architectures of primary tumors and cell lines at various stages of the oncogenic process and in different clinical contexts. Integrative analysis of genome-wide expression patterns, copy number alterations, and clinicopathologic features allows us to uncover transcriptional programs of mechanistic and prognostic relevance. This strategy has led to the identification and validation of gene expression signatures in liver, breast, ovarian and lung cancers that 1) reflect the activity of specific growth-regulating pathways, 2) define known and novel tumor subtypes, and 3) predict clinical outcomes such as disease recurrence and therapeutic response. Examples include prognostic signatures in breast cancer that reflect the operational configuration of the TP53 pathway (Miller et al, PNAS, 2005) and delineate new prognostic tumor subtypes based on “genetic grade” (Ivshina et al, Cancer Res, 2006). More recently, we have discovered a copy number-related transcriptional signature of disease recurrence in stage I non-small cell lung carcinoma (NSCLC) that outperforms all conventional prognostic factors, and identifies a substantial subgroup of patients that may benefit from adjuvant chemotherapy (Broët, et al, Cancer Res, 2009).
We have also pioneered novel data mining strategies that integrate multiple forms of clinico-genomic information (expression, copy number, patient survival) and are capable of pinpointing known and novel candidate oncogenes. Using this approach, we have recently identified and validated a novel breast cancer oncogene at chromosome 8p11 that promotes transformation, anchorage-independent growth, invasion through matrigel, and tumor formation in mouse xenograft models with an ability to interact with and activate H-Ras. Other candidate genes identified by this method are currently being prioritized for functional characterization based on their potential for therapeutic targeting.
Recent Publications Broët P, Camilleri-Broët S, Zhang S, Alifano M, Bangarusamy D, Battistella M, Wu Y, Régnard J, Lim E, Tan P, Miller LD. Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts By Integrative Genomics : Implications for Chemotherapy Selection. Cancer Res. 2009 Feb 1;69(3):1055-62.
Wong CW, Lee CW, Leong WY, Soh SW, Kartasasmita CB, Simoes EA, Hibberd ML, Sung WK, Miller LD. Optimization and clinical validation of a pathogen detection microarray. Genome Biol. 2007 May 28;8(5):R93.
Ivshina AV, George J, Senko O, Mow B, Putti T, Smeds J, Lindahl T, Nordgren H, Wong JEL, Bergh J, Liu ET, Kuznetsov VA, Miller LD. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res. 2006 Nov 1;66(21):10292-301.
Liu ET, Kuznetsov VA, Miller LD. In the pursuit of complexity: systems medicine in cancer biology. Cancer Cell. 2006 Apr;9(4):245-7.
Miller LD, Smeds J, George J, Vega VB, Vergara L, Ploner A, Pawitan Y, Hall P, Klaar S, Liu ET and Bergh J. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc Natl Acad Sci U S A. 2005 Sep 20;102(38):13550-5. |