Breast Cancer Genetics
Human carcinomas show great diversity in their morphologies, clinical histories and in their responsiveness to therapy. This wide tumor diversity poses the main challenge to the effective treatment of cancer patients. The focus of my lab is to characterize the biological diversity of human tumors using genomics, genetics, and cell biology, and then to use this information to develop improved regimens that are specific for each tumor subtype. Our genomic characterization of human breast tumors identified at least six biologically distinct subtypes including Luminal A, Luminal B, Basal-like, HER2-enriched, Claudin-low and Normal-like (Hu et al. 2006, Herschkowitz et al. 2007, Parker et al. 2009); these Intrinsic Subtypes are predictive of relapse-free and overall survival times, and predictive of responsiveness to chemotherapy (Carey et al. 2007, Hugh et al. 2009, Parker et al. 2009). In addition to breast carcinomas we are also studying Head and Neck Squamous Cell Carcinomas (Chung et al. 2004), Lung Carcinomas (Hayes et al., 2006), Glioblastomas (TCGA, 2009) and Ovarian Carcinomas.
Concurrent with our tumor profiling studies are animal model and cell line projects that are aimed at determining the molecular function of the genes that define the Intrinsic Subtypes (Usary et al. 2004, Moyana et al. 2006, Thorner et al. 2009). As an example, my lab has shown that GATA3 is somatically mutated in some ER-positive breast tumors (Usary et al. 2004). The conditional knock-out of GATA3 in mouse mammary tissue greatly inhibited mammary gland development and caused a complete loss of luminal/ER+ epithelial cell formation. We have also determined that there are human germline variants of GATA3 that predispose to developing breast tumors (Garcia-Closas et al., 2007).
Although numerous mouse models of human breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human tumor phenotypes. To address this need, we characterized mammary tumors from over 20 different murine models using DNA microarrays and identified many similarities to human breast tumors including proliferation and Intrinsic Subtype signatures (Herschkowitz et al., 2007). Our mouse modeling studies are an ongoing project where we are focused on further "humanizing" existing models, and then we use these models to empirically test new therapeutics in the preclinical setting; these preclinical mouse testing studies are being done through the UNC Mouse Phase I Unit, which is headed by myself, Dr. Ned Sharpless, and Dr. Bill Zamboni.
Our studies also depend upon computational biologists and the utilization of many bioinformatics tools. In addition to maintaining the UNC Microarray Database (https://genome.unc.edu/), our Lineberger Comprehensive Cancer Center Bioinformatics Group develops tools for the analysis of microarray data including Distance Weighted Discrimination (Benito et al. 2004) and LAS (Shabalin et al. 2009). DWD has allowed us to combine microarray data sets together from different groups or organisms, and to use the combined data to validate the prognostic and/or predictive importance of a given gene set (Hu et al. 2006, Herschkowitz et al., 2007). In summary, my lab utilizes a multi-disciplinary approach to characterize tumor diversity, we then use this information to understand more about tumor biology, and ultimately we design and run new clinical trials for cancer patients that are based upon our preclinical results. We are actively seeking new graduate students, medical fellows and postdocs and have opportunities available that utilize genomics, genetics, molecular and cellular biology, computational biology and human population genetics.
Hoadley KA, Weigman VJ, Fan C, Sawyer LR, He X, Troester MA, Sartor CI, Rieger-House T, Bernard PS, Carey LA, Perou CM. (2007) EGFR associated expression profiles vary with breast tumor subtype. BMC Genomics 8(1):258.
Millikan RC, Newman B, Tse CK, Moorman PG, Conway K, Smith LV, Labbok MH, Geradts J, Bensen JT, Jackson S, Nyante S, Livasy C, Carey L, Earp HS, Perou CM. (2007) Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. Jun 20; [Epub ahead of print].
Herschkowitz JI, Simin K, Weigman VJ, Mikaelian I, Usary J, Hu Z, Rasmussen KE, Jones LP, Assefnia S, Chandrasekharan S, Backlund MG, Yin Y, Khramtsov AI, Bastein R, Quackenbush J, Glazer RI, Brown PH, Green JE, Kopelovich L, Furth PA, Palazzo JP, Olopade OI, Bernard PS, Churchill GA, Van Dyke T, Perou CM. (2007) Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol. 2007;8(5):R76.
Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, Karaca G, Troester MA, Tse CK, Edmiston S, Deming SL, Geradts J, Cheang MC, Nielsen TO, Moorman PG, Earp HS, Millikan RC. (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA Jun 7;295(21):2492-502.
Troester MA, Herschkowitz JI, Oh DS, He X, Hoadley KA, Barbier CS, Perou CM. (2006) Gene expression patterns associated with p53 status in breast cancer. BMC Cancer 6:276.
Fan C, Oh DS, Wessels L, Weigelt B, Nuyten DS, Nobel AB, van't Veer LJ, Perou CM. (2006) Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 355:560-9.
Oh DS, Troester MA, Usary J, Hu Z, He X, Fan C, Wu J, Carey LA, Perou CM. (2006) Estrogen-regulated genes predict survival in hormone receptor-positive breast cancers. J Clin Oncol 24:1656-64.