Gene expression profiling of the breast tumour microenvironment : characterization of gene expression heterogeneity in the breast tumour microenvironment and its influence on clinical outcome

Breast cancer is a very heterogeneous disease. This heterogeneity can be observed at many levels, including gene expression, chromosomal aberrations, and disease pathology. A clear understanding of these differences is important since they impact upon treatment efficacy and clinical outcome. Recent studies have demonstrated that the tumour microenvironment also plays a critical role in cancer initiation and progression. Genomic technologies have been used to gain a better understanding of the impact of gene expression heterogeneity on breast cancer, and have identified gene expression signatures associated with clinical outcome, histopathological breast cancer subtypes, and a variety of cancer-related pathways and processes. However, little work has been done in this context to examine the role of the tumour microenvironment in determining breast cancer outcome, or in defining breast cancer heterogeneity. Additionally, little is known about gene expression in histologically normal tissue adjacent to breast tumour, if this is influenced by the tumour, and how this compares with non-tumour-bearing breast tissue. By applying laser--capture microdissection and gene expression profiling to clinical breast cancer specimens the research presented in this thesis addresses these questions.We have generated gene expression profiles of morphologically normal epithelial and stromal tissue, isolated using laser capture microdissection, from patients with breast cancer or undergoing breast reduction mammoplasty. We determined that morphologically normal epithelium and stroma exhibited distinct expression profiles, but molecular signatures that distinguished breast reduction tissue from tumour-adjacent normal tissue were absent. Stroma isolated from morphologically normal ducts adjacent to tumour tissue contained two distinct expression profiles that correlated with stromal cellularity, and shared similarities with soft tissue tumors with favourable outcome. Adjacent normal epithelium and stroma from breast cancer patients showed no significant association between expression profiles and standard clinical characteristics, but did cluster ER/PR/HER2-negative breast cancers with basal-like subtype expression profiles with poor prognosis. Our data reveal that morphologically normal tissue adjacent to breast carcinomas has not undergone significant gene expression changes when compared to breast reduction tissue, and provide an important gene expression data set for comparative studies of tumour expression profiles.We compared gene expression profiles of tumour stroma from primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumour--derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node--negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumour progression.We show that gene expression in the breast tumour microenvironment is highly heterogeneous, identifying at least six different classes of tumour stroma with distinct expression patterns and distinct biological processes. Two of these classes recapitulate the processes identified in the stroma-derived prognostic predictor, while the others are new classes of stroma associated with distinct clinical outcomes. One of these is associated with matrix remodelling and is strongly associated with the basal molecular subtype of breast cancer. The remainder are independent of the previously published molecular subtypes of breast cancer. Additionally, based on independent data from over 800 tumors, the combinations of stroma classes and breast cancer subtypes identify new subgroups of breast tumors that show better discrimination between good and poor outcome individuals than the molecular breast cancer subtypes or the stroma classes alone, suggesting a novel classification scheme for breast cancer. This research demonstrates an important role for the tumour microenvironment in defining breast cancer heterogeneity, with a consequent impact upon clinical outcome. Novel therapies could be targeted at the processes that define the stroma classes suggesting new avenues for individualized treatment