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Although this therapy is initially effective, nearly all prostate cancers become refractory to it. Approximately 15% of these castration-resistant prostate cancers harbour a genomic amplification at 10q22. The aim of this study was to explore the structure of the 10q22 amplicon and to determine the major driving genes. Application of high-resolution array-CGH using the 244k Agilent microarrays to cell lines with 10q22 amplification allowed us to narrow down the common amplified region to a region of 5.8 megabases. We silenced each of the genes of this region by an RNAi screen in the prostate cancer cell lines PC-3 and 22Rv1. We selected genes with a significant growth reduction S3I-201 in vitro in the 10q22 amplified cell line PC-3, but not in the non-amplified 22Rv1 cells, as putative target genes of this amplicon. Immunohistochemical analysis of the protein expression of these candidate genes on a tissue microarray enriched for 10q22 amplified prostate cancers revealed vinculin as the most promising target of this amplicon. We found a strong association between vinculin gene amplification and overexpression (p diglyceride cancer (p selleck chemicals lymphocyte subsets is important in understanding the microenvironment in cancer and holds promise as a prognostic parameter in invasive breast cancer. To address this, we used digital image analysis to integrate cell abundance, distance metrics, neighbourhood relationships and sample heterogeneity into comprehensive assessment of immune infiltrates. Lymphocyte and macrophage subpopulations were detected by chromogenic duplex immunohistochemistry for CD3/perforin and CD68/CD163 in samples of invasive breast cancer. The analysis workflow combined commercial and open-source software modules. We confirmed the accuracy of automated detection of cells with lymphoid morphology [concordance correlation coefficient (CCC), 0.92 for CD3+-T lymphocytes], whereas variable morphology limited automated classification of macrophages as distinct cellular objects (CCC, 0.43 for object-based detection; 0.79 for pixel-based area analysis).