Co-expression of KLK6 and KLK10 as prognostic factors for survival in pancreatic ductal adenocarcinoma

Kallikreins play an important role in tumour microenvironment and as cancer biomarkers in different cancer entities. Previous studies suggested an upregulation of KLK10 and KLK6 in pancreatic ductal adenocarcinoma (PDAC). Therefore, we evaluated the clinicopathological role of these kallikreins and their value as biomarkers in PDAC

Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of cancer death. Changes in apoptosis signaling in pancreatic cancer result in chemotherapy resistance and aggressive growth and metastasizing. The aim of this study was to characterize the apoptosis pathway in pancreatic cancer computationally by evaluation of experimental data from high-throughput technologies and public data bases. Therefore, gene expression analysis of microdissected pancreatic tumor tissue was implemented in a model of the apoptosis pathway obtained by computational protein interaction prediction. METHODOLOGY/PRINCIPAL FINDINGS: Apoptosis pathway related genes were assembled from electronic databases. To assess expression of these genes we constructed a virtual subarray from a whole genome analysis from microdissected native tumor tissue. To obtain a model of the apoptosis pathway, interactions of members of the apoptosis pathway were analysed using public databases and computational prediction of protein interactions. Gene expression data were implemented in the apoptosis pathway model. 19 genes were found differentially expressed and 12 genes had an already known pathophysiological role in PDAC, such as Survivin/BIRC5, BNIP3 and TNF-R1. Furthermore we validated differential expression of IL1R2 and Livin/BIRC7 by RT-PCR and immunohistochemistry. Implementation of the gene expression data in the apoptosis pathway map suggested two higher level defects of the pathway at the level of cell death receptors and within the intrinsic signaling cascade consistent with references on apoptosis in PDAC. Protein interaction prediction further showed possible new interactions between the single pathway members, which demonstrate the complexity of the apoptosis pathway. CONCLUSIONS/SIGNIFICANCE: Our data shows that by computational evaluation of public accessible data an acceptable virtual image of the apoptosis pathway might be given. By this approach we could identify two higher level defects of the apoptosis pathway in PDAC. We could further for the first time identify IL1R2 as possible candidate gene in PDAC

Human Cancer Protein-Protein Interaction Network: A Structural Perspective

Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network). The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%). We illustrate the interface related affinity properties of two cancer-related hub proteins: Erbb3, a multi interface, and Raf1, a single interface hub. The results reveal that affinity of interactions of the multi-interface hub tends to be higher than that of the single-interface hub. These findings might be important in obtaining new targets in cancer as well as finding the details of specific binding regions of putative cancer drug candidates

Monitoring desertification in a Savannah region in Sudan using Landsat imagesand spectral mixture analysis

Two Landsat images, acquired in 1987 and 2008, were analyzed to evaluate desertification processes in central North Kurdufan State (Sudan). Spectral Mixture Analysis (SMA) and multitemporal comparison techniques (change vector analysis) were applied to estimate the long-term desertification/re-growing of vegetation cover over time and in space. Site-specific interactions between natural processes and human activity played a pivotal role in desertification. Over the last 21 years, desertification significantly prevailed over vegetation re-growth, particularly in areas around rural villages. Changes in land use and mismanagement of natural resources were the main driving factors affecting degradation. More than 120,000 km2 were estimated as being subjected to a medium-high desertification rate. Conversely, the reforestation measures, adopted by the Government in the last decade and sustained by higher rainfall, resulted in low-medium regrowth conditions over an area of about 20,000 km2. Site-specific strategies which take into account the interactions of the driving factors at local scale are thus necessary to combat desertification, avoiding any implementation of untargeted measures. In order to identify the soundest strategies, high-resolution tools must be applied. In this study the application of spectral mixture analysis to Landsat data appeared to be a consistent, accurate and low-cost technique to identify risk areas

Desertification Risks in Agricultural Projects in Northern State in Sudan

none2- ISSN:noneDAWELBAIT M; MORARI F.Dawelbait, M; Morari, Francesc

Limits and Potentialities of Studying Dryland Vegetation Using the Optical Remote Sensing

In optical remote sensing studies, the reflectance of the vegetation canopy in arid and semiarid areas is affected by the optical properties of the vegetation elements, their arrangement in the vegetation canopy and the optical properties of the surrounding environment. The study of vegetation and surrounding environment parameters presents significant peculiarities in arid areas. Low vegetation cover leads to a small contribution of vegetation reflectance in the total pixel reflectance relative to the other materials. Most types of dry ecosystem shrubs do not differ enough from one another to allow discernment of vegetation type. Vegetation in arid and semiarid areas adapts its structure and phenology to the harsh environment, which affects the overall brightness and temporal and spatial interspecies spectral variability. Moreover, the surrounding environment in dry ecosystem influences the reflectance of the vegetation by multiple scattering and nonlinear mixing and variable spectral composition of soil surface. Many remote sensing techniques are insensitive to nonphotosynthetic vegetation, which can be a major component of total cover in dry ecosystem areas. Spectral mixture analysis (SMA) appears to be the most promising technique to obtain information on vegetation cover, soil surface type and vegetation canopy characteristics. The empirical signature libraries of the world’s dominant vegetation types could be upgraded for use with SMA

Relationship Between Vegetation Coverage and Rural Settlements and Anti-desertification Strategies in Horqin Left Back Banner, Inner Mongolia, China

International audienceThis paper investigated the relationship between vegetation coverage and rural settlements in Horqin Left Back Banner. There are 4 spatial patterns about the relationship between vegetation coverage and rural settlements, including high region-low region, high region-low region-high region, high region-low region-high region-low region, and high region. Around rural settlements, land is used as cultivated land and vegetation coverage is high. The overlap effect of overgrazing and extensive cultivation creates the first low region of vegetation coverage. With increasing distance from rural settlements, human disturbance to vegetation growth decreases, vegetation coverage increases, and the high region appears again. The second low region of vegetation coverage is caused by the overgrazing of another rural settlement. At the border region of 2 adjacent villages, 3 different conditions are presented with the vegetation coverage and rural settlements. In the first condition, vegetation coverage is low and is located at the intersection of both low regions of the 2 rural settlements. In the second condition, the vegetation coverage is high and is located at the intersection of both high regions of the 2 rural settlements. In the third condition, vegetation coverage is low and is located at the intersection of both low regions of the 2 rural settlements. According to the changing patterns and reasons for such patterns, we present strategies for anti-desertification, including banning grazing, stopping extensive cultivation, promoting optimal choice of sand-fixation plant, and clarifying land property rights

Sand Dune Encroachment and Desertification Processes of the Rigboland Sand Sea, Central Iran

Early studies on sand dune movement and desertification in Iran have not always been convincingly demonstrated because of problems with the field-based measurements. In some areas where various land uses have been engulfed by aeolian sand dunes, desertification is clear, but in other less settled areas, it may not be so obvious. The objective of this study is to demonstrate encroachments of the Rigboland sand sea, central Iran, in its different directions and variable magnitude rates. Determining the rate and direction of the sand sea movements is critical for specifying which lands should be prioritized and quickly protected. The study has trialed a change detection technique which uses a Cross-Tabulation module to compare two available LandsatTM images over the Rigboland sand sea. This indicates that within a ten-year span (from 1988 to 1998) more than 200 ha/yr were added to the Rigboland sand sea, from the alluvial fan landforms in the eastern upstream, outer margins of the Rigboland sand sea. Coupled with GIS techniques, this type of analysis of the remote sensing (RS) images provides an effective tool for the monitoring and prognostication of sand dune movement and sand sea change.</p