Mechanical behaviour and rupture of normal and pathological human ascending aortic wall

The mechanical properties of aortic wall, both healthy and pathological, are needed in order to develop and improve diagnostic and interventional criteria, and for the development of mechanical models to assess arterial integrity. This study focuses on the mechanical behaviour and rupture conditions of the human ascending aorta and its relationship with age and pathologies. Fresh ascending aortic specimens harvested from 23 healthy donors, 12 patients with bicuspid aortic valve (BAV) and 14 with aneurysm were tensile-tested in vitro under physiological conditions. Tensile strength, stretch at failure and elbow stress were measured. The obtained results showed that age causes a major reduction in the mechanical parameters of healthy ascending aortic tissue, and that no significant differences are found between the mechanical strength of aneurysmal or BAV aortic specimens and the corresponding age-matched control group. The physiological level of the stress in the circumferential direction was also computed to assess the physiological operation range of healthy and diseased ascending aortas. The mean physiological wall stress acting on pathologic aortas was found to be far from rupture, with factors of safety (defined as the ratio of tensile strength to the mean wall stress) larger than six. In contrast, the physiological operation of pathologic vessels lays in the stiff part of the response curve, losing part of its function of damping the pressure waves from the heart

Resistance of Renal Cell Carcinoma to Sorafenib Is Mediated by Potentially Reversible Gene Expression

Purpose: Resistance to antiangiogenic therapy is an important clinical problem. We examined whether resistance occurs at least in part via reversible, physiologic changes in the tumor, or results solely from stable genetic changes in resistant tumor cells. Experimental Design: Mice bearing two human RCC xenografts were treated with sorafenib until they acquired resistance. Resistant 786-O cells were harvested and reimplanted into naïve mice. Mice bearing resistant A498 cells were subjected to a 1 week treatment break. Sorafenib was then again administered to both sets of mice. Tumor growth patterns, gene expression, viability, blood vessel density, and perfusion were serially assessed in treated vs control mice. Results: Despite prior resistance, reimplanted 786-O tumors maintained their ability to stabilize on sorafenib in sequential reimplantation steps. A transcriptome profile of the tumors revealed that the gene expression profile of tumors upon reimplantation reapproximated that of the untreated tumors and was distinct from tumors exhibiting resistance to sorafenib. In A498 tumors, revascularization was noted with resistance and cessation of sorafenib therapy and tumor perfusion was reduced and tumor cell necrosis enhanced with re-exposure to sorafenib. Conclusions: In two RCC cell lines, resistance to sorafenib appears to be reversible. These results support the hypothesis that resistance to VEGF pathway therapy is not solely the result of a permanent genetic change in the tumor or selection of resistant clones, but rather is due to a great extent to reversible changes that likely occur in the tumor and/or its microenvironment

Critical dynamics in the evolution of stochastic strategies for the iterated Prisoner's Dilemma

The observed cooperation on the level of genes, cells, tissues, and individuals has been the object of intense study by evolutionary biologists, mainly because cooperation often flourishes in biological systems in apparent contradiction to the selfish goal of survival inherent in Darwinian evolution. In order to resolve this paradox, evolutionary game theory has focused on the Prisoner's Dilemma (PD), which incorporates the essence of this conflict. Here, we encode strategies for the iterated Prisoner's Dilemma (IPD) in terms of conditional probabilities that represent the response of decision pathways given previous plays. We find that if these stochastic strategies are encoded as genes that undergo Darwinian evolution, the environmental conditions that the strategies are adapting to determine the fixed point of the evolutionary trajectory, which could be either cooperation or defection. A transition between cooperative and defective attractors occurs as a function of different parameters such a mutation rate, replacement rate, and memory, all of which affect a player's ability to predict an opponent's behavior.Comment: 27 pages, including supplementary information. 5 figures, 4 suppl. figures. Version accepted for publication in PLoS Comp. Bio

Reduced Expression of Fumarate Hydratase in Clear Cell Renal Cancer Mediates HIF-2α Accumulation and Promotes Migration and Invasion

Germline mutations of FH, the gene that encodes for the tricarboxylic acid TCA (TCA) cycle enzyme fumarate hydratase, are associated with an inherited form of cancer referred to as Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC). Individuals with HLRCC are predisposed to the development of highly malignant and lethal renal cell carcinoma (RCC). The mechanisms of tumorigenesis proposed have largely focused on the biochemical consequences of loss of FH enzymatic activity. While loss of the tumor suppressor gene von Hippel Lindau (VHL) is thought to be an initiating event for the majority of RCCs, a role for FH in sporadic renal cancer has not been explored. Here we report that FH mRNA and protein expression are reduced in clear cell renal cancer, the most common histologic variant of kidney cancer. Moreover, we demonstrate that reduced FH leads to the accumulation of hypoxia inducible factor- 2α (HIF-2α), a transcription factor known to promote renal carcinogenesis. Finally, we demonstrate that overexpression of FH in renal cancer cells inhibits cellular migration and invasion. These data provide novel insights into the tumor suppressor functions of FH in sporadic kidney cancer

Nck2 promotes human melanoma cell proliferation, migration and invasion in vitro and primary melanoma-derived tumor growth in vivo

<p>Abstract</p> <p>Background</p> <p>Nck1 and Nck2 adaptor proteins are involved in signaling pathways mediating proliferation, cytoskeleton organization and integrated stress response. Overexpression of Nck1 in fibroblasts has been shown to be oncogenic. Through the years this concept has been challenged and the consensus is now that overexpression of either Nck cooperates with strong oncogenes to transform cells. Therefore, variations in Nck expression levels in transformed cells could endorse cancer progression.</p> <p>Methods</p> <p>Expression of Nck1 and Nck2 proteins in various cancer cell lines at different stages of progression were analyzed by western blots. We created human primary melanoma cell lines overexpressing GFP-Nck2 and investigated their ability to proliferate along with metastatic characteristics such as migration and invasion. By western blot analysis, we compared levels of proteins phosphorylated on tyrosine as well as cadherins and integrins in human melanoma cells overexpressing or not Nck2. Finally, in mice we assessed tumor growth rate of human melanoma cells expressing increasing levels of Nck2.</p> <p>Results</p> <p>We found that expression of Nck2 is consistently increased in various metastatic cancer cell lines compared with primary counterparts. Particularly, we observed significant higher levels of Nck2 protein and mRNA, as opposed to no change in Nck1, in human metastatic melanoma cell lines compared with non-metastatic melanoma and normal melanocytes. We demonstrated the involvement of Nck2 in proliferation, migration and invasion in human melanoma cells. Moreover, we discovered that Nck2 overexpression in human primary melanoma cells correlates with higher levels of proteins phosphorylated on tyrosine residues, assembly of Nck2-dependent pY-proteins-containing molecular complexes and downregulation of cadherins and integrins. Importantly, we uncovered that injection of Nck2-overexpressing human primary melanoma cells into mice increases melanoma-derived tumor growth rate.</p> <p>Conclusions</p> <p>Collectively, our data indicate that Nck2 effectively influences human melanoma phenotype progression. At the molecular level, we propose that Nck2 in human primary melanoma promotes the formation of molecular complexes regulating proliferation and actin cytoskeleton dynamics by modulating kinases or phosphatases activities that results in increased levels of proteins phosphorylated on tyrosine residues. This study provides new insights regarding cancer progression that could impact on the therapeutic strategies targeting cancer.</p

ProteoSign: an end-user online differential proteomics statistical analysis platform

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign