Infiltrating S100A8+ myeloid cells promote metastatic spread of human breast cancer and predict poor clinical outcome.

The mechanisms by which breast cancer (BrC) can successfully metastasize are complex and not yet fully understood. Our goal was to identify tumor-induced stromal changes that influence metastatic cell behavior, and may serve as better targets for therapy. To identify stromal changes in cancer-bearing tissue, dual-species gene expression analysis was performed for three different metastatic BrC xenograft models.

Utility of redundant combinatorial libraries in distinguishing high and low quality screening hits.

Large one-bead one-compound (OBOC) combinatorial libraries can be constructed relatively easily by solid-phase split and pool synthesis. The use of resins with hydrophilic surfaces, such as TentaGel, allows the beads to be used directly in screens for compounds that bind selectively to labeled proteins, nucleic acids, or other biomolecules. However, we have found that this method, while useful, has a high false positive rate.

A new mouse model for the study of human breast cancer metastasis.

Breast cancer is the most common cancer in women, and this prevalence has a major impact on health worldwide. Localized breast cancer has an excellent prognosis, with a 5-year relative survival rate of 85%. However, the survival rate drops to only 23% for women with distant metastases.

Whole genome in vivo RNAi screening identifies the leukemia inhibitory factor receptor as a novel breast tumor suppressor.

Cancer is caused by mutations in oncogenes and tumor suppressor genes, resulting in the deregulation of processes fundamental to the normal behavior of cells. The identification and characterization of oncogenes and tumor suppressors has led to new treatment strategies that have significantly improved cancer outcome. The advent of next generation sequencing has allowed the elucidation of the fine structure of cancer genomes, however, the identification of pathogenic changes is complicated by the inherent genomic instability of cancer cells.

Simultaneous analysis of tumor and stromal gene expression profiles from xenograft models.

Identifying the gene expression alterations that occur in both the tumor and stroma is essential to understanding tumor biology. We have developed a dual-species microarray analysis method that allows the dissection of both tumor and stromal gene expression profiles from xenograft models, based on limited interspecies cross-hybridization on Illumina gene expression beadchips. This methodology allows for simultaneous genome-wide analysis of gene expression profiles of both tumor cells and the associated stromal tissue.