Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 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 tumor-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 tumor progression.

Understanding the tumor immune microenvironment (TIME) promises to be key for optimal cancer therapy, especially in triple-negative breast cancer (TNBC). Integrating spatial resolution of immune cells with laser capture microdissection gene expression profiles, we defined distinct TIME stratification in TNBC, with implications for current therapies including immune checkpoint blockade. TNBCs with an immunoreactive microenvironment exhibited tumoral infiltration of granzyme B + CD8 + T cells (GzmB + CD8 + T cells), a type 1 IFN signature, and elevated expression of multiple immune inhibitory molecules including indoleamine 2,3-dioxygenase (IDO) and programmed cell death ligand 1 (PD-L1), and resulted in good outcomes. An "immune-cold" microenvironment with an absence of tumoral CD8 + T cells was defined by elevated expression of the immunosuppressive marker B7-H4, signatures of fibrotic stroma, and poor outcomes. A distinct poor-outcome immunomodulatory microenvironment, hitherto poorly characterized, exhibited stromal restriction of CD8 + T cells, stromal expression of PD-L1, and enrichment for signatures of cholesterol biosynthesis. Metasignatures defining these TIME subtypes allowed us to stratify TNBCs, predict outcomes, and identify potential therapeutic targets for TNBC.

Elevated MET receptor tyrosine kinase correlates with poor outcome in breast cancer, yet the reasons for this are poorly understood. We thus generated a transgenic mouse model targeting expression of an oncogenic Met receptor (Met mt ) to the mammary epithelium. We show that Met mt induces mammary tumors with multiple phenotypes. These reflect tumor subtypes with gene expression and immunostaining profiles sharing similarities to human basal and luminal breast cancers. Within the basal subtype, Met mt induces tumors with signatures of WNT and epithelial to mesenchymal transition (EMT). Among human breast cancers, MET is primarily elevated in basal and ERBB2-positive subtypes with poor prognosis, and we show that MET, together with EMT marker, SNAIL, are highly predictive of poor prognosis in lymph nodenegative patients. By generating a unique mouse model in which the Met receptor tyrosine kinase is expressed in the mammary epithelium, along with the examination of MET expression in human breast cancer, we have established a specific link between MET and basal breast cancer. This work identifies basal breast cancers and, additionally, poor-outcome breast cancers, as those that may benefit from anti-MET receptor therapies.gene expression profiling ͉ mouse models ͉ epithelial to mesenchymal transition B reast cancer is a heterogeneous disease that comprises distinct biological entities that are correlated with diverse clinical outcomes and responses to treatment. Gene expression profiling and molecular pathology have revealed that breast cancers naturally divide into the luminal, ERBB2-positive, and basal-like subtypes (1, 2). These subtypes were named to reflect gene expression patterns of the 2 principal cell types of the differentiated breast, luminal epithelial cells lining the duct and lobule, and myoepithelial cells that form a single layer surrounding the luminal cells. The luminal subtype comprises ϳ60% of breast cancers, is estrogen receptor (ESR1)-positive, and expresses ESR1-responsive genes and luminal markers such as keratin 8/18. Up to 25% of breast cancers are identified with overexpression/amplification of the ERBB2 receptor tyrosine kinase, and these tumors are generally ESR1/ progesterone receptor (PGR)-negative. The basal group is characterized as ESR1/PGR/ERBB2-negative and is frequently positive for basal keratins 5/6 (3, 4). Breast cancers within the luminal subtype receive antiestrogen therapies and tend to have a good prognosis. Because of the lack of treatment options, patients within the basal subtype historically have a poor prognosis (1). Hence, an understanding of the signaling pathways active in these tumors is crucial for the generation of targeted therapies.The MET receptor tyrosine kinase, which is the receptor for hepatocyte growth factor/scatter factor (HGF/SF), is expressed at elevated levels in 15-20% of human breast cancers (5), and is a prognostic factor for poor outcome (6, 7). High levels of the MET receptor ligand HGF/SF in the serum of breast cancer patients is also correl...