Project description:WWOX expression is lost during tumor progression in many human malignancies including breast cancer. To understand the effects of loss of WWOX expression we analyzed the consequences of its silencing in normal human breast cells (MCF10F). WWOX silencing led to the formation of larger cell colonies, increased cell motility and decreased cell attachment. WWOX silenced cells demonstrated deregulated expression on genes involved in cell cycle, DNA damage response and cell motility. We detected an enrichment of targets activated by the SMAD3 transcription factor. Most notably expression of ANGPTL4, FST, PTHLH and SERPINE1 were all significantly increased upon WWOX silencing. Upregulation of these genes can be reversed by re-expressing WWOX in the previously silenced cells thus suggesting an inverse correlation between WWOX protein expression and SMAD3 transcriptional activity. Importantly, we demonstrate that WWOX physically interacts with SMAD3 protein via WW domain 1, that WWOX expression dramatically decreases SMAD3 occupancy at the ANGPTL4 and SERPINE1 promoters and significantly quenches activation of a TGFM-NM-2 responsive reporter (3TP-LUX). Furthermore, WWOX expression leads to intracellular redistribution of SMAD3 protein levels redirecting protein availability from the nuclear to the cytoplasmic compartment. Interestingly, meta-analysis of gene expression breast cancer datasets indicate that WWOX and ANGPTL4 expression, encoding a secreted protein of key relevance in breast cancer lung metastatic cells, are inversely correlated and the WWOXlo/ANGPTL4hi cluster of tumors are enriched in triple-negative and basal-like sub-types. In summary, we demonstrate that WWOX modulates SMAD3 signaling in breast cells via direct WW-domain binding and potential cytoplasmic sequestration of SMAD3 protein. Since loss of WWOX expression increases with breast cancer progression and it behaves as an inhibitor of SMAD3 transcriptional activity these observations may help explain, at least in part, the paradoxical pro-tumorigenic effects of TGFM-NM-2 signaling in advanced breast cancer. We compared two independent shRNAs: shWWOX-A and shWWOX-B with 3 biological replicates each one, targeting different regions of the WWOX transcript as a means of ruling out any potential off-target effects.

Project description:Glioblastoma (GBM) is the most prevalent primary malignant brain tumor in adults and remains almost invariably lethal due to its aggressive and invasive behavior. Despite many clinical trials have been put forward, the standard treatment that stands for more than a decade consists of surgical resection, followed by temozolomide (TMZ) chemotherapy and radiation treatment. However, this strategy has improved the average survival time to 14.6 months when compared to 12,1 months only with surgery and radiation1 . Therefore, due to the low prognosis, different efforts have been employed in the search for new drugs and therapeutic protocols for this malignancy. A class of drugs that has emerged as a promising candidate for GBM is Histone Deacetylase inhibitors (iHDAC). Indeed, pre-clinical studies have demonstrated the efficiency of different iHDACs as anti-tumor agents, especially when associated with other therapies, including chemotherapy and radiation2. In fact, the use of iHDACs reduced the expression of genes involved in DNA repair, formation of mitotic spindles and homologous chromosome segregation, leading to glioma apoptosis in vitro 3. In addition, it has been reported that small iHDACs molecules, such as Trichostatin (TSA), disrupts cellular signaling networks relevant to tumorigenesis, leading to an increased interest in testing iHDACs in clinical trials against different types of tumors 4 . In agreement, a high activity of HDAC has also been associated with tumor progression, corroborating the pharmacological inhibition of HDACs as an interesting anti-cancer molecular target. Previous works from our group are in line with this reasoning showing that iHDACs negatively regulate the migratory capacity of GBM in vitro, suggesting that these inhibitors may regulate the molecular signature of GBM secretome, making the tumor's microenvironment repulsive for cell migration5. In fact, the communication between tumor cells and their microenvironment may occur directly or indirectly through a variety of secreted molecules, such as growth factors, cytokines, chemokines and microRNAs6. One relevant secreted molecule described by our group is Nodal, an important morphogen involved in several cellular processes related to tumorigenesis. In this previous study, our group brings an original approach on the mechanisms that dynamically control intra and extracellular nodal availability during GBM tumorigenesis7. Thus, the heterotypic secretome that derives from the tumor cells, may be an important source of key regulators of the tumorigenic process6 . To better understand whether iHDACs can also affect the repertoire of secreted molecules, and therefore directly modulate the surrounding micro-environment displaying deleterious effects on tumor cells, we investigated the secretome of iHDAC treated GBM cells in vitro using a high throughput methodology of protein identification and quantification couple to label free mass spectrometry. Using this strategy we were able to successfully identify secreted molecules upon HDAC activity knockdown. Interestingly, we identified proteins exclusive to the iHDAC treated secretome as well as proteins found in both control and treated groups. These proteins were classified using the Matrisome classification system corroborating that the molecular signature of tumor secreted proteins, that belong to the ECM, was disrupted. In vitro experiments using 2D and 3D cell culture systems coupled to decellularized ECM analysis by confocal microscopy confirmed that HDAC activity knockdown gave rise to a disrupted pattern of ECM protein staining. Taken together our results first describe in the literature the relevance of epigenetic remodeling HDAC dependent for the molecular signature of GBM cells shedding light on putative molecular targets to approach the malignancy.

Project description:Background ; Rheumatoid arthritis (RA) is a chronic inflammatory disease, characterized by joint destruction and perpetuated by the synovial membrane (SM). In the inflamed SM, activated synovial fibroblasts (SFB) form the major cell type promoting development and progression of the disease by an abnormal expression/secretion of pro-inflammatory cytokines, tissue-degrading enzymes resulting in a predominant degradation of the extra-cellular matrix (ECM), and collagens causing joint fibrosis. We developed a new procedure, based on human knowledge and formal concept analysis (FCA), to simulate and analyze the temporal behaviour of regulatory and signaling networks. It was applied to a regulatory network (containing 18 genes from 5 functional groups) representing ECM formation and destruction in TGFÎ² - and TNFÎ± -stimulated SFB. Results ; For the modelling of SFB-controlled ECM turnover in rheumatic diseases, Boolean network architecture was used as well as extensive literature information and revision by experimental gene expression data from stimulated SFB. In course of revision, the additional experimental information resulted in different biologically reasonable changes, yielding two Boolean networks that describe TGFÎ² and TNFÎ± effects, respectively. The final simulations were further analyzed by the attribute exploration algorithm of FCA, integrating again the observed time series in a more fine-grained and automated manner. The generated temporal rules clearly reveal subtle regulatory relationships between different genes, co-expression patterns and converse gene expression regulation in rheumatic diseases. Conclusion ; The developed Boolean network based method for the dynamical analysis of regulatory and signaling networks represents a reliable systems biological solution for the improved understanding of complex regulatory pathways and the interactions among different genes in disease. The resulting knowledge base can be used for further analysis of the ECM system in human fibroblasts and may be queried to predict the functional consequences of observed (e.g. in diseases as RA) or hypothetical (e.g. for therapeutic purposes) gene expression disturbances. Experiment Overall Design: Patients and tissue samples: Experiment Overall Design: Synovial membrane samples were obtained within 10 min following tissue excision upon joint replacement/synovectomy from RA and OA patients (n = 3 each). After removal, tissue samples were frozen and stored at -70Â°C. Informed patient consent was acquired and the study was approved by the ethics committees of the respective universities. RA patients were classified according to the American College of Rheumatology (ACR) criteria, OA patients according to the respective criteria for osteoarthritis. The preparation of primary semi-transformed synovial fibroblasts from RA and OA patients was performed as previously described (Zimmermann et al., Arthritis Res. 2001;3(1):72-6). Briefly, the tissue samples were minced and digested with trypsin/collagenase P. The resulting single cell suspension was cultured for seven days. Non-adherent cells were removed by medium exchange. SFB were then negatively purified using DynabeadsÂ® M 450 CD14 and subsequently cultured over 4 passages in DMEM containing 100 Î¼g/ml gentamycin, 100 Î¼g/ml penicillin/streptomycin, 20 mM HEPES, and 10% FCS. Experiment Overall Design: Cell stimulation and isolation of total RNA : Experiment Overall Design: At the end of the fourth passage, the SFB were stimulated by 10 ng/ml TGFÎ² or TNFÎ± in serum-free DMEM for 0, 1, 2, 4, and 12 h. At the end of each time point, medium was removed and the cells were digested with trypsin/versene (0.25%). Following centrifugation and washing with PBS, the cells were lysed with RLT buffer (Qiagen) and frozen at 70Â°C. Total RNA was isolated using the RNeasy Kit (Qiagen) according to the supplier's recommendation. Experiment Overall Design: Microarray data analysis: Experiment Overall Design: RNA probes were labelled according to the supplier's instructions (AffymetrixÂ®, Santa Clara, CA, USA). Analysis of gene expression was performed using U133 Plus 2.0 RNA microarrays. Hybridization and washing was performed according to the supplier's instructions. Microarrays were analyzed by laser scanning (Hewlett-Packard Gene Scanner). Background-corrected signal intensities were determined using the MAS 5.0 software (AffymetrixÂ®) and normalized among arrays to facilitate comparisons between different patients. For this purpose, arrays were grouped according to patient class the respective stimulus (TGFÎ² and TNFÎ±, n=6 each). The arrays in each group were normalized using quantile normalization. Experiment Overall Design: See publication for further details.

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