Colon cancer cell-derived 12(S)-HETE induces the retraction of cancer-associated fibroblast via MLC2, RHO/ROCK and Ca2+ signalling

Retraction of mesenchymal stromal cells supports the invasion of colorectal cancer cells (CRC) into the adjacent compartment. CRC-secreted 12(S)-HETE enhances the retraction of cancer-associated fibroblasts (CAFs) and therefore, 12(S)-HETE may enforce invasivity of CRC. Understanding the mechanisms of metastatic CRC is crucial for successful intervention. Therefore, we studied pro-invasive contributions of stromal cells in physiologically relevant three-dimensional in vitro assays consisting of CRC spheroids, CAFs, extracellular matrix and endothelial cells, as well as in reductionist models. In order to elucidate how CAFs support CRC invasion, tumour spheroid-induced CAF retraction and free intracellular Ca2+ levels were measured and pharmacological-or siRNA-based inhibition of selected signalling cascades was performed. CRC spheroids caused the retraction of CAFs, generating entry gates in the adjacent surrogate stroma. The responsible trigger factor 12(S)-HETE provoked a signal, which was transduced by PLC, IP3, free intracellular Ca2+, Ca(2+)calmodulin-kinase-II, RHO/ROCK and MYLK which led to the activation of myosin light chain 2, and subsequent CAF mobility. RHO activity was observed downstream as well as upstream of Ca2+ release. Thus, Ca2+ signalling served as central signal amplifier. Treatment with the FDA-approved drugs carbamazepine, cinnarizine, nifedipine and bepridil HCl, which reportedly interfere with cellular calcium availability, inhibited CAF-retraction. The elucidation of signalling pathways and identification of approved inhibitory drugs warrant development of intervention strategies targeting tumour-stroma interaction

Gene and protein expression of glucose transporter 1 and glucose transporter 3 in human laryngeal cancer—the relationship with regulatory hypoxia-inducible factor-1α expression, tumor invasiveness, and patient prognosis

Increased glucose uptake mediated by glucose transporters and reliance on glycolysis are common features of malignant cells. Hypoxia-inducible factor-1α supports the adaptation of hypoxic cells by inducing genes related to glucose metabolism. The contribution of glucose transporter (GLUT) and hypoxia-inducible factor-1α (HIF-1α) activity to tumor behavior and their prognostic value in head and neck cancers remains unclear. The aim of this study was to examine the predictive value of GLUT1, GLUT3, and HIF-1α messenger RNA (mRNA)/protein expression as markers of tumor aggressiveness and prognosis in laryngeal cancer. The level of hypoxia/metabolic marker genes was determined in 106 squamous cell laryngeal cancer (SCC) and 73 noncancerous matched mucosa (NCM) controls using quantitative realtime PCR. The related protein levels were analyzed by Western blot. Positive expression of SLC2A1, SLC2A3, and HIF-1α genes was noted in 83.9, 82.1, and 71.7 % of SCC specimens and in 34.4, 59.4, and 62.5 % of laryngeal cancer samples. Higher levels of mRNA/protein for GLUT1 and HIF-1α were noted in SCC compared to NCM (p<0.05). SLC2A1 was found to have a positive relationship with grade, tumor front grading (TFG) score, and depth and mode of invasion (p<0.05). SLC2A3 was related to grade and invasion type (p<0.05). There were also relationships of HIF-1α with pTNM, TFG scale, invasion depth and mode, tumor recurrences, and overall survival (p<0.05). In addition, more advanced tumors were found to be more likely to demonstrate positive expression of these proteins. In conclusion, the hypoxia/metabolic markers studied could be used as molecular markers of tumor invasiveness in laryngeal cancer.This work was supported, in part, by the statutory fund of the Department of Cytobiochemistry, University of Łódź, Poland (506/811), and by grant fromtheNational Science Council, Poland (N403 043 32/2326)

Identification of SERPINA1 as single marker for papillary thyroid carcinoma through microarray meta analysis and quantification of its discriminatory power in independent validation

<p>Abstract</p> <p>Background</p> <p>Several DNA microarray based expression signatures for the different clinically relevant thyroid tumor entities have been described over the past few years. However, reproducibility of these signatures is generally low, mainly due to study biases, small sample sizes and the highly multivariate nature of microarrays. While there are new technologies available for a more accurate high throughput expression analysis, we show that there is still a lot of information to be gained from data deposited in public microarray databases. In this study we were aiming (1) to identify potential markers for papillary thyroid carcinomas through meta analysis of public microarray data and (2) to confirm these markers in an independent dataset using an independent technology.</p> <p>Methods</p> <p>We adopted a meta analysis approach for four publicly available microarray datasets on papillary thyroid carcinoma (PTC) nodules versus nodular goitre (NG) from N2-frozen tissue. The methodology included merging of datasets, bias removal using distance weighted discrimination (DWD), feature selection/inference statistics, classification/crossvalidation and gene set enrichment analysis (GSEA). External Validation was performed on an independent dataset using an independent technology, quantitative RT-PCR (RT-qPCR) in our laboratory.</p> <p>Results</p> <p>From meta analysis we identified one gene (SERPINA1) which identifies papillary thyroid carcinoma against benign nodules with 99% accuracy (n = 99, sensitivity = 0.98, specificity = 1, PPV = 1, NPV = 0.98). In the independent validation data, which included not only PTC and NG, but all major histological thyroid entities plus a few variants, SERPINA1 was again markedly up regulated (36-fold, p = 1:3*10^-10) in PTC and identification of papillary carcinoma was possible with 93% accuracy (n = 82, sensitivity = 1, specificity = 0.90, PPV = 0.76, NPV = 1). We also show that the extracellular matrix pathway is strongly activated in the meta analysis data, suggesting an important role of tumor-stroma interaction in the carcinogenesis of papillary thyroid carcinoma.</p> <p>Conclusions</p> <p>We show that valuable new information can be gained from meta analysis of existing microarray data deposited in public repositories. While single microarray studies rarely exhibit a sample number which allows robust feature selection, this can be achieved by combining published data using DWD. This approach is not only efficient, but also very cost-effective. Independent validation shows the validity of the results from this meta analysis and confirms SERPINA1 as a potent mRNA marker for PTC in a total (meta analysis plus validation) of 181 samples.</p

W kierunku autonomicznego, opierającego się na opisie semantycznym, systemu zarządzania aplikacjami rozproszonymi

In this paper we present our approach to the management of distributed systems based on semantic description of available resources. We use ontologies for a semantic description of the monitored system and other aspects of monitoring and management (such as metrics) and introduce a feedback loop on underlying infrastructure. Such an approach allows to automate monitoring and the ease the work of administrator. We introduce concepts behind a novel automatic management system, SAMM, developed within our research. We discuss the core mechanisms used in the system - the estimation of future measurements, approach to knowledge gathering, and the process of decision making. Then we provide some details on the architecture and implementation of SAMM.Publikacja ta przedstawia nowe podejście do zagadnień monitorowania i zarządzania systemami rozproszonymi, wykorzystujące ontologiczny opis zasobów przez nie udostępnianych. Podejście to wykorzystuje ontologie do opisu semantycznego monitorowanego systemu, a także innych aspektów monitorowania i zarządzania nim (np. dostępne metryki) oraz wprowadza sprzężenie zwrotne na monitorowanej infrastrukturze. Pozwala to na automatyzację procesu monitorowania i zarządzania w celu ułatwienia pracy administratora. Publikacja opisuje także działanie nowatorskiego systemu SAMM, który powstał w wyniku badań. Przedstawione zostały również koncepcje dotyczące estymacji pomiarów, tworzenia baz wiedzy oraz procesu podejmowania decyzji. Artykuł opisuje zarówno architekturę SAMM-a, jak i szczegóły implementacyjne

Neuroendocrine tumors and fibrosis: An unsolved mystery?

Neuroendocrine tumors are a heterogeneous group of slow-growing neoplasms arising mainly from the enterochromaffin cells of thedigestive and respiratory tract. Although they are relatively rare, their incidence is rising. It has long been observed that they oftenare associated with the development of fibrosis, both local and distant. Fibrotic complications, such as carcinoid heart disease andmesenteric desmoplasia, may lead to considerable morbidity or even affect prognosis. The elucidation of the pathophysiology offibrosis would be of critical importance for the development of targeted therapeutic strategies. In this article, the authors review theavailable evidence regarding the biological basis of fibrosis in neuroendocrine tumors. They explore the role of the tumor microenvi-ronment and the interplay between tumor cells and fibroblasts as a key factor in fibrogenesis and tumor development/progression.They also review the role of serotonin, growth factors, and other peptides in the development of carcinoid-related fibrotic reactions

A system-level approach for deciphering the transcriptional response to prion infection

Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here, we investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection. RESULTS: To this end, we analyze previously published gene expression data, from which we extrapolate a putative full-scale model of transcriptional gene-gene dependencies in the mouse central nervous system. Then, we use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily influenced by this perturbation. Our method sheds light on the mode of action of prions by identifying key transcripts that are the most likely to be responsible for the overall transcriptional rearrangement from a nominal regulatory network. As a first result of our inference, we have been able to predict known targets of prions (i.e. PrP(C)) and to unveil the potential role of previously unsuspected gene