Changes in the transcriptional profile in response to overexpression of the osteopontin-c splice isoform in ovarian (OvCar-3) and prostate (PC-3) cancer cell lines.

BACKGROUND: Especially in human tumor cells, the osteopontin (OPN) primary transcript is subject to alternative splicing, generating three isoforms termed OPNa, OPNb and OPNc. We previously demonstrated that the OPNc splice variant activates several aspects of the progression of ovarian and prostate cancers. The goal of the present study was to develop cell line models to determine the impact of OPNc overexpression on main cancer signaling pathways and thus obtain insights into the mechanisms of OPNc pro-tumorigenic roles. METHODS: Human ovarian and prostate cancer cell lines, OvCar-3 and PC-3 cells, respectively, were stably transfected to overexpress OPNc. Transcriptomic profiling was performed on these cells and compared to controls, to identify OPNc overexpression-dependent changes in gene expression levels and pathways by qRT-PCR analyses. RESULTS: Among 84 genes tested by using a multiplex real-time PCR Cancer Pathway Array approach, 34 and 16, respectively, were differentially expressed between OvCar-3 and PC-3 OPNc-overexpressing cells in relation to control clones. Differentially expressed genes are included in all main hallmarks of cancer, and several interacting proteins have been identified using an interactome network analysis. Based on marked up-regulation of Vegfa transcript in response to OPNc overexpression, we partially validated the array data by demonstrating that conditioned medium (CM) secreted from OvCar-3 and PC-3 OPNc-overexpressing cells significantly induced endothelial cell adhesion, proliferation and migration, compared to CM secreted from control cells. CONCLUSIONS: Overall, the present study elucidated transcriptional changes of OvCar-3 and PC-3 cancer cell lines in response to OPNc overexpression, which provides an assessment for predicting the molecular mechanisms by which this splice variant promotes tumor progression features

A strategy to identify housekeeping genes suitable for analysis in breast cancer diseases

Standard curve and serial dilutions for nHKGs and tHKGs. The x axis represents the dilution series (1:800, 1:400, 1:200 and 1:100) and the y axis represents the mean of CT for each gene. The correlation coefficient r is given for each gene inside parentheses. (PDF 53 kb

Validation of a network-based strategy for the optimization of combinatorial target selection in breast cancer therapy: SiRNA knockdown of network targets in MDA-MB-231 cells as an in vitro model for inhibition of tumor development

Submitted by Fabricia Pimenta ([email protected]) on 2017-09-01T17:09:45Z No. of bitstreams: 1 Tilli_etal_2016b.pdf: 5059048 bytes, checksum: 08051376c2e7d6871825b46b34fdea61 (MD5)Approved for entry into archive by Fabricia Pimenta ([email protected]) on 2017-09-12T18:57:03Z (GMT) No. of bitstreams: 1 Tilli_etal_2016b.pdf: 5059048 bytes, checksum: 08051376c2e7d6871825b46b34fdea61 (MD5)Made available in DSpace on 2017-09-12T18:57:03Z (GMT). No. of bitstreams: 1 Tilli_etal_2016b.pdf: 5059048 bytes, checksum: 08051376c2e7d6871825b46b34fdea61 (MD5) Previous issue date: 2016-09-27Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças Negligenciadas. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil.Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças Negligenciadas. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil.University of Alberta. Faculty of Medicine & Dentistry. Department of Oncology. Department of Physics. Edmonton, Alberta, Canada.University of Alberta. Faculty of Medicine & Dentistry. Department of Oncology. Edmonton, Alberta, Canada.Network-based strategies provided by systems biology are attractive tools for cancer therapy. Modulation of cancer networks by anticancer drugs may alter the response of malignant cells and/or drive network re-organization into the inhibition of cancer progression. Previously, using systems biology approach and cancer signaling networks, we identified top-5 highly expressed and connected proteins (HSP90AB1, CSNK2B, TK1, YWHAB and VIM) in the invasive MDA-MB-231 breast cancer cell line. Here, we have knocked down the expression of these proteins, individually or together using siRNAs. The transfected cell lines were assessed for in vitro cell growth, colony formation, migration and invasion relative to control transfected MDA-MB-231, the non-invasive MCF-7 breast carcinoma cell line and the non-tumoral mammary epithelial cell line MCF-10A. The knockdown of the top-5 upregulated connectivity hubs successfully inhibited the in vitro proliferation, colony formation, anchorage independence, migration and invasion in MDA-MB-231 cells; with minimal effects in the control transfected MDA-MB-231 cells or MCF-7 and MCF-10A cells. The in vitro validation of bioinformatics predictions regarding optimized multi-target selection for therapy suggests that protein expression levels together with protein-protein interaction network analysis may provide an optimized combinatorial target selection for a highly effective anti-metastatic precision therapy in triple-negative breast cancer. This approach increases the ability to identify not only druggable hubs as essential targets for cancer survival, but also interactions most susceptible to synergistic drug action. The data provided in this report constitute a preliminary step toward the personalized clinical application of our strategy to optimize the therapeutic use of anti-cancer drugs

Antitumor Activity of Lankacidin Group Antibiotics Is Due to Microtubule Stabilization via a Paclitaxel-like Mechanism

Lankacidin group antibiotics show strong antimicrobial activity against various Gram-positive bacteria. In addition, they were shown to have considerable antitumor activity against certain cell line models. For decades, the antitumor activity of lankacidin was associated with the mechanism of its antimicrobial action, which is interference with peptide bond formation during protein synthesis. This, however, was never confirmed experimentally. Due to significant similarity to paclitaxel-like hits in a previous computational virtual screening study, we suggested that the cytotoxic effect of lankacidin is due to a paclitaxel-like action. In this study, we tested this hypothesis computationally and experimentally and confirmed that lankacidin is a microtubule stabilizer that enhances tubulin assembly and displaces taxoids from their binding site. This study serves as a starting point for optimization of lankacidin derivatives for better antitumor activities. It also highlights the power of computational predictions and their aid in guiding experiments and formulating rigorous hypotheses