Endostatin- and interleukin-2-expressing retroviral bicistronic vector for gene therapy of metastatic renal cell carcinoma

Background Metastatic renal cell carcinoma (mRCC) is one of the most treatment-resistant malignancies. Despite all new therapeutic advances, almost all patients develop resistance to treatment and cure is rarely seen. In the present study, we evaluated the antitumor effect of a bicistronic retrovirus vector encoding both endostatin (ES) and interleukin (IL)-2 using an orthotopic metastatic RCC mouse model. Methods Balb/C-bearing Renca cells were treated with NIH/3T3-LendIRES-IL-2-SN cells. In the survival studies, mice were monitored daily until they died. At the end of the in vivo experiment, serum levels of IL-2 and ES were measured, the lung was weighed, and the number of metastatic nodules, nodule area, tumor vessels and proliferation of tumor-infiltrating Renca cells were determined. Results Inoculation of NIH/3T3-LendIRES-IL-2-SN cells resulted in an increase in ES and IL-2 levels in the treated group (p < 0.05). There was a significant decrease in lung wet weight, lung nodule area and tumor vessels in the treated group compared to the control group (p < 0.001). The proliferation of Renca cells in the bicistronic-treated group was significantly reduced compared to the control group (p < 0.05). Kaplan-Meier survival curves showed that the probability of survival was significantly higher for mice submitted to bicistronic therapy (log-rank test, p = 0.0016). Bicistronic therapy caused an increase in the infiltration of CD4, CD4 interferon (IFN)gamma-producing, CD8, CD8 IFN gamma-producing and natural killer (CD49b) cells. Conclusions Retroviral bicistronic gene transfer led to the secretion of functional ES and IL-2 that was sufficiently active to: (i) inhibit tumor angiogenesis and tumor cell proliferation and (ii) increase the infiltration of immune cells (C) Copyright. 2011 John Wiley & Sons, Ltd.

Concomitant expression of epithelial-mesenchymal transition biomarkers in breast ductal carcinoma: Association with progression

Epithelial to mesenchymal transition (EMT) is a process implicated in cancer progression in which the underlying cellular changes have been identified mainly using in vitro models. We determined the expression of some putative EMT biomarkers including E-cadherin, beta-catenin, zinc finger factor Snail (Snail), transforming growth factor beta 1 (TGF beta 1), TGF beta type II receptor (TBRII) and the HGF receptor (c-met) and their possible correlation to progression and overall survival in a series of breast ductal carcinoma in situ (DCIS) and invasive ductal carcinomas (IDC). Biomarkers were immunohistochemically determined in 55 IDC specimens from which 21 had lymph node metastases and in 95 DCIS specimens, 46 of these cases associated to invasive carcinoma, in a tissue microarray (TMA). Positive cytoplasmic staining of TGF beta 1 (78.2%), c-met (43.6%), Snail (34.5%), TBRII (100%), membranous E-cadherin (74.5%) and membranous/cytoplasmic beta-catenin (71%) were detected in the IDC samples. Metastatic lymph node samples displayed similar frequencies. A significant increase of c-met and TGF beta 1 positivity along DCIS to IDC progression was noted but only TGF beta 1 positivity was associated with presence of lymph node metastases and advanced stages in IDC. The evaluation of the other EMT markers in DCIS did not show differences in positivity rate as compared to invasive carcinomas. DCIS either pure or associated to IDC showed similar expression of the analyzed biomarkers. All the carcinomas exhibited positive expression of TBRII. Associations between the markers, determined by Spearman`s correlation coefficient, showed a significant association between TGF beta 1 and respectively E-cadherin, beta-catenin and cmet in DCIS cases, but in invasive carcinomas only cadherin and catenin were positively correlated. Kaplan-Meier survival curves revealed that none of the EMT biomarkers analyzed were correlated with survival, which was significantly determined only by clinical and hormone receptor parameters.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Transfer of an autonomously replicating vector between vegetatively incompatible biotypes of Colletotrichum gloeosporioides

Previous research has indicated that biotypes A and B of Colletotrichum gloeosporioides that infect Stylosanthes spp. in Australia are asexual and vegetatively incompatible. Selectable marker genes conferring resistance either to hygromycin or phleomycin were introduced into isolates of these biotypes. Vectors conferring resistance to hygromycin and carrying telomeric sequences from Fusarium oxysporum replicated autonomously in C. gloeosporioides and gave frequencies of transformation 100-times higher than vectors that integrated into the genome. Monoconidial colonies resistant to both antibiotics were recovered when hygromycin-resistant biotype-A transformants carrying an autonomously replicating vector were paired in culture with a phleomycin-resistant biotype-B transformant carrying integrative vector sequences. Molecular analysis of double antibiotic-resistant progeny indicated that they contained the autonomous vector in a biotype-B genetic background, Results indicate that transfer of the autonomous vector had occurred from biotype A to biotype B, demonstrating the potential for transfer of genetic information between these biotypes.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

A hypothesis for explaining single outbreaks (like the Black Death in European cities) of vector-borne infections

We propose a mechanism by which single outbreaks of vector-borne infections can happen even when the value of the basic reproduction number, R(o), of the infection is below one. With this hypothesis we have shown that dynamical models simulations demonstrate that the arrival of a relatively small (with respect to the host population) number of infected vectors can trigger a short-lived epidemic but with a huge number of cases. These episodes are characterized by a sudden outbreak in a previously virgin area that last from weeks to a few months, and then disappear without leaving vestiges. The hypothesis proposed in this paper to explain those single outbreaks of vector-borne infections, even when total basic reproduction number, Ro, is less than one (which explain the fact that those infections fail to establish themselves at endemic levels), is that the vector-to-host component of Ro is greater than one and that a sufficient amount of infected vectors are imported to the vulnerable area, triggering the outbreak. We tested the hypothesis by performing numerical simulations that reproduce the observed outbreaks of chikungunya in Italy in 2007 and the plague in Florence in 1348. The theory proposed provides an explanation for isolated outbreaks of vector-borne infections, ways to calculate the size of those outbreaks from the number of infected vectors arriving in the affected areas. Given the ever-increasing worldwide transportation network, providing a high degree of mobility from endemic to virgin areas, the proposed mechanism may have important implications for public health planning. (C) 2009 Elsevier Ltd. All rights reserved.

Concurreny based transition refinement for the verification of distributed algorithms

We suggest a new notion of behaviour preserving transition refinement based on partial order semantics. This notion is called transition refinement. We introduced transition refinement for elementary (low-level) Petri Nets earlier. For modelling and verifying complex distributed algorithms, high-level (Algebraic) Petri nets are usually used. In this paper, we define transition refinement for Algebraic Petri Nets. This notion is more powerful than transition refinement for elementary Petri nets because it corresponds to the simultaneous refinement of several transitions in an elementary Petri net. Transition refinement is particularly suitable for refinement steps that increase the degree of distribution of an algorithm, e.g. when synchronous communication is replaced by asynchronous message passing. We study how to prove that a replacement of a transition is a transition refinement.

Demonstration of epithelial-mesenchymal transition in kidney - The contribution of a coupled histochemical and immunohistochemical staining with Periodic Acid-Thionin Schiff

Traditional Periodic Acid Schiff has been extensively used, coupled with immunohistochemistry for epithelia or mesenchymal cells, to highlight renal tubular basement membrane (TBM). We recently tried to perform such technique in a 5/6 nephrectomy model of progressive renal fibrosis to demonstrate TBM disruption as an evidence for epithelial-mesenchymal transdifferentiation. Despite excellent basement membrane staining with traditional fuchsin-Periodic Acid Schiff, the interface between epithelial and mesenchymal cells was frequently blurred when revealed with 3`3 diaminobenzidine tetrachloride-peroxidase. Also, it was inadequate when revealed with alkaline phosphatase-fast red. We devised a triple staining method with Periodic Acid-Thionin Schiff to highlight basement membrane in blue, after double immunostaining for epithelium and mesenchymal cells. Blue basement membrane rendered a brisk contrast and highlighted boundaries between epithelial-mesenchymal interfaces. This method was easy to perform and useful to demonstrate the TBM, yield a clear demonstration of the very focal TBM disruption found in this model of progressive renal fibrosis.

Neonatal BCG Immunization Followed by DNAhsp65 Boosters: Highly Immunogenic but not Protective Against Tuberculosis - a Paradoxical Effect of the Vector?

A new tuberculosis vaccine is urgently needed. Prime-boost strategies are considered very promising and the inclusion of BCG is highly desirable. In this investigation, we tested the protective efficacy of BCG delivered in the neonatal period followed by boosters in the adult phase with a DNA vaccine containing the hsp65 gene from Mycobacterium leprae (pVAXhsp65). Immune responses were characterized by serum anti-hsp65 antibody levels and IFN-gamma and IL-5 production by the spleen. Amounts of these cytokines were also determined in lung homogenates. Protective efficacy was established by the number of colony-forming units (CFU) and histopathological analysis of the lungs after challenge with Mycobacterium tuberculosis. Immunization with BCG alone triggered a significant reduction of CFU in the lungs and also clearly preserved the pulmonary parenchyma. BCG priming also increased the immunogenicity of pVAXhsp65. However, boosters with pVAXhsp65 or the empty vector abolished the protective efficacy of BCG. Also, higher IL-5 levels were produced by spleen and lungs after DNA boosters. These results demonstrated that neonatal BCG immunization followed by DNAhsp65 boosters is highly immunogenic but is not protective against tuberculosis.