Data Mining Approaches to Diffuse Large B–Cell Lymphoma Gene Expression Data Interpretation

This paper presents a comprehensive study of gene expression patterns originating from a diffuse large B–cell lymphoma (DLBCL) database. It focuses on the implementation of feature selection and classification techniques. Thus, it firstly tackles the identification of relevant genes for the prediction of DLBCL types. It also allows the determination of key biomarkers to differentiate two subtypes of DLBCL samples: Activated B–Like and Germinal Centre B–Like DLBCL. Decision trees provide knowledge–based models to predict types and subtypes of DLBCL. This research suggests that the data may be insufficient to accurately predict DLBCL types or even detect functionally relevant genes. However, these methods represent reliable and understandable tools to start thinking about possible interesting non–linear interdependencies

The Public Repository of Xenografts enables discovery and randomized phase II-like trials in mice

More than 90% of drugs with preclinical activity fail in human trials, largely due to insufficient efficacy. We hypothesized that adequately powered trials of patient-derived xenografts (PDX) in mice could efficiently define therapeutic activity across heterogeneous tumors. To address this hypothesis, we established a large, publicly available repository of well-characterized leukemia and lymphoma PDXs that undergo orthotopic engraftment, called the Public Repository of Xenografts (PRoXe). PRoXe includes all de-identified information relevant to the primary specimens and the PDXs derived from them. Using this repository, we demonstrate that large studies of acute leukemia PDXs that mimic human randomized clinical trials can characterize drug efficacy and generate transcriptional, functional, and proteomic biomarkers in both treatment-naive and relapsed/refractory disease

Tumor cell-mediated induction of the stromal factor stromelysin-3 requires heterotypic cell contact-dependent activation of specific protein kinase C isoforms

Stromelysin-3 (ST3, MMP-11) has been shown to be strongly overexpressed in stromal fibroblasts of most invasive human carcinomas. However, the molecular mechanisms leading to ST3 expression in nonmalignant fibroblasts remain unknown. The aim of the present study was to analyze the signaling pathways activated in normal pulmonary fibroblasts after their interaction with non-small cell lung cancer (NSCLC) cells and leading to ST3 expression. The use of selective signaling pathway inhibitors showed that conventional and novel protein kinase Cs (PKC) were required for ST3 induction, whereas Src kinases exerted a negative control. We observed by both conventional and real time confocal microscopy that green fluorescent protein-tagged PKCalpha and PKCepsilon, but not PKCdelta, transfected in fibroblasts, accumulate selectively at the cell-cell contacts between fibroblasts and tumor cells. In agreement, RNAi-mediated depletion of PKCalpha and PKCepsilon, but not PKCdelta significantly decreased co-culture-dependent ST3 production. Finally, a tetracycline-inducible expression model allowed us to confirm the central role of these PKC isoforms and the negative regulatory function of c-Src in the control of ST3 expression. Altogether, our data emphasize signaling changes occurring in the tumor microenvironment that may define new stromal targets for therapeutic intervention