PRAME expression and clinical outcome of breast cancer

The tumour antigen PReferentially expressed Antigen of MElanoma (PRAME) is expressed in a variety of malignancies, including breast cancer. We have analysed PRAME gene expression in relation to clinical outcome for 295 primary breast cancer patients. Kaplan–Meier survival curves show a correlation of PRAME expression levels with increased rates of distant metastases and decreased overall patient survival. This correlation existed both for the entire patient group (n=295) and for the subgroup of patients (n=185) who did not receive adjuvant chemotherapy. Multivariable analysis indicated that PRAME is an independent marker of shortened metastasis-free interval in patients who did not receive adjuvant chemotherapy. PRAME expression was associated with tumour grade and negative oestrogen receptor status. We conclude that PRAME expression is a prognostic marker for clinical outcome of breast cancer, independent of traditional clinicopathological markers

Understanding pharmacokinetics using realistic computational models of fluid dynamics: biosimulation of drug distribution within the CSF space for intrathecal drugs

We introduce how biophysical modeling in pharmaceutical research and development, combining physiological observations at the tissue, organ and system level with selected drug physiochemical properties, may contribute to a greater and non-intuitive understanding of drug pharmacokinetics and therapeutic design. Based on rich first-principle knowledge combined with experimental data at both conception and calibration stages, and leveraging our insights on disease processes and drug pharmacology, biophysical modeling may provide a novel and unique opportunity to interactively characterize detailed drug transport, distribution, and subsequent therapeutic effects. This innovative approach is exemplified through a three-dimensional (3D) computational fluid dynamics model of the spinal canal motivated by questions arising during pharmaceutical development of one molecular therapy for spinal cord injury. The model was based on actual geometry reconstructed from magnetic resonance imaging data subsequently transformed in a parametric 3D geometry and a corresponding finite-volume representation. With dynamics controlled by transient Navier–Stokes equations, the model was implemented in a commercial multi-physics software environment established in the automotive and aerospace industries. While predictions were performed in silico, the underlying biophysical models relied on multiple sources of experimental data and knowledge from scientific literature. The results have provided insights into the primary factors that can influence the intrathecal distribution of drug after lumbar administration. This example illustrates how the approach connects the causal chain underlying drug distribution, starting with the technical aspect of drug delivery systems, through physiology-driven drug transport, then eventually linking to tissue penetration, binding, residence, and ultimately clearance. Currently supporting our drug development projects with an improved understanding of systems physiology, biophysical models are being increasingly used to characterize drug transport and distribution in human tissues where pharmacokinetic measurements are difficult or impossible to perform. Importantly, biophysical models can describe emergent properties of a system, i.e. properties not identifiable through the study of the system’s components taken in isolation

In Vivo Gene Knockdown in Rat Dorsal Root Ganglia Mediated by Self-Complementary Adeno-Associated Virus Serotype 5 Following Intrathecal Delivery

We report here in adult rat viral vector mediate-gene knockdown in the primary sensory neurons and the associated cellular and behavior consequences. Self-complementary adeno-associated virus serotype 5 (AAV5) was constructed to express green fluorescent protein (GFP) and a small interfering RNA (siRNA) targeting mammalian target of rapamycin (mTOR). The AAV vectors were injected via an intrathecal catheter. We observed profound GFP expression in lumbar DRG neurons beginning at 2-week post-injection. Of those neurons, over 85% were large to medium-diameter and co-labeled with NF200, a marker for myelinated fibers. Western blotting of mTOR revealed an 80% reduction in the lumbar DRGs (L4–L6) of rats treated with the active siRNA vectors compared to the control siRNA vector. Gene knockdown became apparent as early as 7-day post-injection and lasted for at least 5 weeks. Importantly, mTOR knockdown occurred in large (NF200) and small-diameter neurons (nociceptors). The viral administration induced an increase of Iba1 immunoreactivity in the DRGs, which was likely attributed to the expression of GFP but not siRNA. Rats with mTOR knockdown in DRG neurons showed normal general behavior and unaltered responses to noxious stimuli. In conclusion, intrathecal AAV5 is a highly efficient vehicle to deliver siRNA and generate gene knockdown in DRG neurons. This will be valuable for both basic research and clinic intervention of diseases involving primary sensory neurons

CD44(+)/CD24(- )breast cancer cells exhibit enhanced invasive properties: an early step necessary for metastasis

INTRODUCTION: A subpopulation (CD44(+)/CD24(-)) of breast cancer cells has been reported to have stem/progenitor cell properties. The aim of this study was to investigate whether this subpopulation of cancer cells has the unique ability to invade, home, and proliferate at sites of metastasis. METHODS: CD44 and CD24 expression was determined by flow cytometry. Northern blotting was used to determine the expression of proinvasive and 'bone and lung metastasis signature' genes. A matrigel invasion assay and intracardiac inoculation into nude mice were used to evaluate invasion, and homing and proliferation at sites of metastasis, respectively. RESULTS: Five among 13 breast cancer cell lines examined (MDA-MB-231, MDA-MB-436, Hs578T, SUM1315, and HBL-100) contained a higher percentage (>30%) of CD44(+)/CD24(- )cells. Cell lines with high CD44(+)/CD24(- )cell numbers express basal/mesenchymal or myoepithelial but not luminal markers. Expression levels of proinvasive genes (IL-1α, IL-6, IL-8, and urokinase plasminogen activator [UPA]) were higher in cell lines with a significant CD44(+)/CD24(- )population than in other cell lines. Among the CD44(+)/CD24(-)-positive cell lines, MDA-MB-231 has the unique property of expressing a broad range of genes that favor bone and lung metastasis. Consistent with previous studies in nude mice, cell lines with CD44(+)/CD24(- )subpopulation were more invasive than other cell lines. However, only a subset of CD44(+)/CD24(-)-positive cell lines was able to home and proliferate in lungs. CONCLUSION: Breast cancer cells with CD44(+)/CD24(- )subpopulation express higher levels of proinvasive genes and have highly invasive properties. However, this phenotype is not sufficient to predict capacity for pulmonary metastasis

Signaling pathways in breast cancer metastasis - novel insights from functional genomics

The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases

Patterns of microRNA Expression in Non-Human Primate Cells Correlate with Neoplastic Development In Vitro

MicroRNAs (miRNAs) are small noncoding RNAs that negatively regulate gene expression post-transcriptionally. They play a critical role in developmental and physiological processes and have been implicated in the pathogenesis of several diseases including cancer. To identify miRNA signatures associated with different stages of neoplastic development, we examined the expression profile of 776 primate miRNAs in VERO cells (a neoplastically transformed cell line being used for the manufacture of viral vaccines), progenitor primary African green monkey kidney (pAGMK) cells, and VERO cell derivatives: spontaneously immortalized, non-tumorigenic, low-passage VERO cells (10-87 LP); tumorigenic, high-passage VERO cells (10-87 HP); and a cell line (10-87 T) derived from a 10-87 HP cell tumor xenograft in athymic nude mice. When compared with pAGMK cells, the majority of miRNAs were expressed at lower levels in 10-87 LP, 10-87 HP, and 10-87 T cells. We identified 10 up-regulated miRNAs whose level of expression correlated with VERO cell evolution from a non-tumorigenic phenotype to a tumorigenic phenotype. The overexpression of miR-376a and the polycistronic cluster of miR-376a, miR-376b and miR-376c conferred phenotypic changes to the non-tumorigenic 10-87 LP cells that mimic the tumorigenic 10-87 HP cells. Thirty percent of miRNAs that were components of the identified miRNAs in our spontaneously transformed AGMK cell model are also dysregulated in a variety of human tumors. These results may prove to be relevant to the biology of neoplastic development. In addition, one or more of these miRNAs could be biomarkers for the expression of a tumorigenic phenotype

The non-coding transcriptome as a dynamic regulator of cancer metastasis.

Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered "housekeeping" genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients' prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms

The Drosophila melanogaster host model

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed