Lumican is overexpressed in lung adenocarcinoma pleural effusions.

Adenocarcinoma (AdC) is the most common lung cancer subtype and is often associated with pleural effusion (PE). Its poor prognosis is attributable to diagnostic delay and lack of effective treatments and there is a pressing need in discovering new biomarkers for early diagnosis or targeted therapies. To date, little is known about lung AdC proteome. We investigated protein expression of lung AdC in PE using the isobaric Tags for Relative and Absolute Quantification (iTRAQ) approach to identify possible novel diagnostic/prognostic biomarkers. This provided the identification of 109 of lung AdC-related proteins. We further analyzed lumican, one of the overexpressed proteins, in 88 resected lung AdCs and in 23 malignant PE cell-blocks (13 lung AdCs and 10 non-lung cancers) using immunohistochemistry. In AdC surgical samples, lumican expression was low in cancer cells, whereas it was strong and diffuse in the stroma surrounding the tumor. However, lumican expression was not associated with tumor grade, stage, and vascular/pleural invasion. None of the lung cancer cell-blocks showed lumican immunoreaction, whereas those of all the other tumors were strongly positive. Finally, immunoblotting analysis showed lumican expression in both cell lysate and conditioned medium of a fibroblast culture but not in those of A549 lung cancer cell line. PE is a valid source of information for proteomic analysis without many of the restrictions of plasma. The high lumican levels characterizing AdC PEs are probably due to its release by the fibroblasts surrounding the tumor. Despite the role of lumican in lung AdC is still elusive, it could be of diagnostic value

Polar Electrophoresis: Shape of Two-Dimensional Maps Is as Important as Size

The performance of two-dimensional electrophoresis in conventional gels in Cartesian coordinates (2-DE) vs. polar coordinates (2-PE) is here evaluated. Although 2-DE is performed in much longer Immobiline gels in the first dimension (17 cm) vs. barely 7-cm in 2-PE, an equivalent resolving power is found. Moreover, due to the possibility of running up to seven Immobiline strips in the radial gel format, the reproducibility of spot position is seen to be higher, this resulting in a 20% higher matching efficiency. As an extra bonus, strings of “isobaric” spots (i.e. polypeptides of identical mass with different pI values) are more resolved in the radial gel format, especially in the 10 to 30 kDa region, where the gel area fans out leaving extra space for spot resolution. In conclusion, this novel gel format in the second dimension of 2D gels is seen as an important improvement of this technique, still one of the most popular in proteome analysis

A Novel Gaussian Extrapolation Approach for 2D Gel Electrophoresis Saturated Protein Spots

Analysis of images obtained from two-dimensional gel electrophoresis (2D-GE) is a topic of utmost importance in bioinformatics research, since commercial and academic software available currently has proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this work, we present an effective technique for the detection and the reconstruction of over-saturated protein spots. Firstly, the algorithm reveals overexposed areas, where spots may be truncated, and plateau regions caused by smeared and overlapping spots. Next, it reconstructs the correct distribution of pixel values in these overexposed areas and plateau regions, using a two-dimensional least-squares fitting based on a generalized Gaussian distribution. Pixel correction in saturated and smeared spots allows more accurate quantification, providing more reliable image analysis results. The method is validated for processing highly exposed 2D-GE images, comparing reconstructed spots with the corresponding non-saturated image, demonstrating that the algorithm enables correct spot quantificatio

High Abundance Proteins Depletion vs Low Abundance Proteins Enrichment: Comparison of Methods to Reduce the Plasma Proteome Complexity

BACKGROUND: To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration. CONCLUSIONS/SIGNIFICANCE: Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol

Texture classification of proteins using support vector machines and bio-inspired metaheuristics

6th International Joint Conference, BIOSTEC 2013, Barcelona, Spain, February 11-14, 2013[Abstract] In this paper, a novel classification method of two-dimensional polyacrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for whose implementation we compare Genetic Algorithms and Particle Swarm Optimization. Then, the selected features, among which the most decisive and representative ones appear to be those related to the second order co-occurrence matrix, are used as inputs for a Support Vector Machine. The accuracy of the proposed method is around 94 %, a statistically better performance than the classification based on the entire feature set. This classification step can be very useful for discarding over-segmented areas after a protein segmentation or identification process

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker

Aims/hypothesis Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Methods Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Results Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with alpha 1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. Conclusions/interpretation We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patient

Quarta impressione del primo, secondo, et terzo libro d'intavolaturo, di Pietro Millioni, sopra il quale ciascuno da se medesimo puo l'imparare di Chitarra Spagnola, accordare fare, il trillo, il repicco, e anco trasmutar sonate da una lettera all' altra corrispondenti, nuovamente dato in luce dal medesimo

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Proteomica di fibroblasti cutanei coltivati in vitro, ottenuti da biopsie di soggetti normali e di pazienti diabetici di tipo 1, caratterizzati dalla presenza o assenza di complicanze microvascolari renali

The target of this research project was to identify protein markers of diabetic nephropathy (DN), a microvascular complication which develops in about 30% of subject with type 1 diabetes and which is often associated with an increase risk of developing cardiovascular diseases and premature death in comparison with non nephropatic subjects. Many studies indicate that hyperglycemia is a necessary although not sufficient condition to determine the diabetes associated renal damage. Indeed, the incidence of nephropathy reaches a maximum after 15-20 years of disease and thereafter it decreases. Such a behaviour is compatible with the existence of an individual susceptibility (genetic) to renal damage, induced by factors other than hyperglycaemia, thus highlighting the need for an early detection of the type 1 diabetic subjects with high risk of developing DN, and to clarify the pathophysiological mechanisms Human fibroblasts represent an ideal experimental model, also because easily accessible, for an ample investigation on the genetic predisposition to diabetic disease, as well as to study of the mechanisms leading to cellular and metabolic damages occurring in diabetic complications. We have established an experimental protocol for the extraction of proteins from cultured cells and we have defined the optimal experimental conditions to obtain reproducible 2-D gels. So we compared protein profiles of cultured fibroblasts, harvested from skin biopsies of type 1 diabetic patients with long disease duration and with or without DN, and normal healthy subjects. This research has allowed, firstly, a more and deeper knowledge about human fibloblast proteome, useful data as a reference for subsequent investigations applied to the study of various diseases including non-diabetic. Secondly, the comparison among groups showed significant changes in the amounts of some proteins including cytoskeletal proteins and proteins involved in energy metabolism and protein turnover. Some of these results have been validated with more depth analysis as western blot and enzymatic activity test. These data, entirely original at the international level, represent a starting point for further investigations for the early identification of subjects with a genetic predisposition to DN and revealed new clues to understand physiopathological mechanisms that lead to the development of this pathology. Finally we made the comparison of protein levels after exposure to high levels of glucose, within each group and among the three groups, obtaining information about proteins involved in cellular response to hyperglycemia