956 resultados para Biomarkers


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Immunohistochemistry (IHC) is an essential tool in diagnostic surgical pathology, allowing analysis of protein subcellular localization The use of IHC by different laboratories has lead to inconsistencies in published literature for several antibodies, due to either interpretative (inter-observer venation) or technical reasons These disparities have major implications in both clinical and research settings In this study, we report our experience conducting an IHC optimization of antibodies against five proteins previously identified by proteomic analysis to be breast cancer biomarkers, namely 6PGL (PGLS), CAZ2 (CAPZA2), PA2G4 (EBP1) PSD2 and TKT Large variations in the immunolocalizations and intensities were observed when manipulating the antigen retrieval method and primary antibody incubation concentration However, the use of an independent molecular analysis method provided a clear indication in choosing the appropriate biologically and functionally relevant

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Formalin fixed and paraffin embedded tissue (FFPE) collections in pathology departments are the largest resource for retrospective biomedical research studies. Based on the literature analysis of FFPE related research, as well as our own technical validation, we present the Translational Research Arrays (TRARESA), a tissue microarray centred, hospital based, translational research conceptual framework for both validation and/or discovery of novel biomarkers. TRARESA incorporates the analysis of protein, DNA and RNA in the same samples, correlating with clinical and pathological parameters from each case, and allowing (a) the confirmation of new biomarkers, disease hypotheses and drug targets, and (b) the postulation of novel hypotheses on disease mechanisms and drug targets based on known biomarkers. While presenting TRARESA, we illustrate the use of such a comprehensive approach. The conceptualisation of the role of FFPE-based studies in translational research allows the utilisation of this commodity, and adds to the hypothesis-generating armamentarium of existing high-throughput technologies.

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Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erb132 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors. (C) 2003 Elsevier Inc. All rights reserved.

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Tissue microarrays allow high throughput molecular profiling of diagnostic or predictive markers in cancer specimens and rapid validation of novel potential candidates identified from genomic and proteomic analyses in a large number of tumor samples. To validate the use of tissue microarray technology for all the main biomarkers routinely used to decide breast cancer prognostication and postsurgical adjuvant therapy, we constructed a tissue microarray from 97 breast tumors, with a single 0.6 mm core per specimen. Inummostaining; of tissue microarray sections and conventional full sections of each tumor were performed using well-characterized prognostic markers (estrogen receptor ER, progesterone receptor PR and c-erbB2). The full section versus tissue microarray concordance for these stains was 97% for ER, 98% for PR, and 97% for c-erbB2, respectively, with a strong statistical association (kappa value more than 0.90). Fluorescence in situ hybridization analysis for HER-2/neu gene amplification from the single-core tissue microarray was technically successful in about 90% (87/97) of the cases, with a concordance of 95% compared with parallel analyses with the full sections. The correlation with other pathological parameters was not significantly different between full-section and array-based results. It is concluded that the constructed tissue microarray with a single core per specimen ensures full biological representativeness to identify the associations between biomarkers and clinicopathological parameters, with no significant associated sampling bias.

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BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

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Background— Observational evidence has consistently linked increased fruit and vegetable consumption with reduced cardiovascular morbidity; however, there is little direct trial evidence to support the concept that fruit and vegetable consumption improves vascular function. This study assessed the dose-dependent effects of a fruit and vegetable intervention on arterial health in subjects with hypertension.

Methods and Results— After a 4-week run-in period during which fruit and vegetable intake was limited to 1 portion per day, participants were randomized to consume either 1, 3, or 6 portions daily for the next 8 weeks. Endothelium-dependent and -independent arterial vasodilator responses were assessed by venous occlusion plethysmography in the brachial circulation before and after intervention. Compliance was monitored with serial contemporaneous 4-day food records and by measuring concentrations of circulating dietary biomarkers. A total of 117 volunteers completed the 12-week study. Participants in the 1-, 3-, and 6-portions/d groups reported consuming on average 1.1, 3.2, and 5.6 portions of fruit and vegetables, respectively, and serum concentrations of lutein and ß-cryptoxanthin increased across the groups in a dose-dependent manner. For each 1-portion increase in reported fruit and vegetable consumption, there was a 6.2% improvement in forearm blood flow responses to intra-arterial administration of the endothelium-dependent vasodilator acetylcholine (P=0.03). There was no association between increased fruit and vegetable consumption and vasodilator responses to sodium nitroprusside, an endothelium-independent vasodilator.

Conclusions— The present study illustrates that among hypertensive volunteers, increased fruit and vegetable consumption produces significant improvements in an established marker of endothelial function and cardiovascular prognosis.

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Purpose: We previously found that cellular FLICE-inhibitory protein (c-FLIP), caspase 8, and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) receptor 2 (DR5) are major regulators of cell viability and chemotherapy-induced apoptosis in colorectal cancer. In this study, we determined the prognostic significance of c-FLIP, caspase 8, TRAIL and DR5 expression in tissues from patients with stage II and III colorectal cancer.

Experimental Design: Tissue microarrays were constructed from matched normal and tumor tissue derived from patients (n = 253) enrolled in a phase III trial of adjuvant 5-fluorouracil–based chemotherapy versus postoperative observation alone. TRAIL, DR5, caspase 8, and c-FLIP expression levels were determined by immunohistochemistry.

Results: Colorectal tumors displayed significantly higher expression levels of c-FLIP (P < 0.001), caspase 8 (P = 0.01), and DR5 (P < 0.001), but lower levels of TRAIL (P < 0.001) compared with matched normal tissue. In univariate analysis, higher TRAIL expression in the tumor was associated with worse overall survival (P = 0.026), with a trend to decreased relapse-free survival (RFS; P = 0.06), and higher tumor c-FLIP expression was associated with a significantly decreased RFS (P = 0.015). Using multivariate predictive modeling for RFS in all patients and including all biomarkers, age, treatment, and stage, we found that the model was significant when the mean tumor c-FLIP expression score and disease stage were included (P < 0.001). As regards overall survival, the overall model was predictive when both TRAIL expression and disease stage were included (P < 0.001).

Conclusions: High c-FLIP and TRAIL expression may be independent adverse prognostic markers in stage II and III colorectal cancer and might identify patients most at risk of relapse.

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Current clinical, laboratory or radiological parameters cannot accurately diagnose or predict disease outcomes in a range of autoimmune disorders. Biomarkers which can diagnose at an earlier time point, predict outcome or help guide therapeutic strategies in autoimmune diseases could improve clinical management of this broad group of debilitating disorders. Additionally, there is a growing need for a deeper understanding of multi-factorial autoimmune disorders. Proteomic platforms offering a multiplex approach are more likely to reflect the complexity of autoimmune disease processes. Findings from proteomic based studies of three distinct autoimmune diseases are presented and strategies compared. It is the authors' view that such approaches are likely to be fruitful in the movement of autoimmune disease treatment away from reactive decisions and towards a preventative stand point.

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Epidemiological evidence supports a positive relationship between fruit and vegetable (FV) intake, lung function and chronic obstructive pulmonary disease (COPD). Increasing FV intake may attenuate the oxidative stress and inflammation associated with COPD.

An exploratory randomised controlled trial to examine the effect of increased consumption of FV on oxidative stress and inflammation in moderate-to-severe COPD was conducted. 81 symptomatically stable patients with a habitually low FV intake (two or fewer portions of FV per day) were randomised to the intervention group (five or more portions of FV per day) or the control group (two or fewer portions of FV per day). Each participant received self-selected weekly home deliveries of FV for 12 weeks.

75 participants completed the intervention. There was a significant between-group change in self-reported FV intake and biomarkers of FV intake (zeaxanthin (p=0.034) and ß-cryptoxanthin (p=0.015)), indicating good compliance; post-intervention intakes in intervention and control groups were 6.1 and 1.9 portions of FV per day, respectively. There were no significant changes in biomarkers of airway inflammation (interleukin-8 and myeloperoxidase) and systemic inflammation (C-reactive protein) or airway and systemic oxidative stress (8-isoprostane).

This exploratory study demonstrated that patients with moderate-to-severe COPD were able to comply with an intervention to increase FV intake; however, this had no significant effect on airway or systemic oxidative stress and inflammation.

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Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

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The Dry Valleys of Antarctica are one of the coldest and driest environments on Earth with paleosols in selected areas that date to the emplacement of tills by warm-based ice during the Early Miocene. Cited as an analogue to the martian surface, the ability of the Antarctic environment to support microbial life-forms is a matter of special interest, particularly with the upcoming NASA/ESA 2018 ExoMars mission. Lipid biomarkers were extracted and analyzed by gas chromatography-mass spectrometry to assess sources of organic carbon and evaluate the contribution of microbial species to the organic matter of the paleosols. Paleosol samples from the ice-free Dry Valleys were also subsampled and cultivated in a growth medium from which DNA was extracted with the explicit purpose of the positive identification of bacteria. Several species of bacteria were grown in solution and the genus identified. A similar match of the data to sequenced DNA showed that Alphaproteobacteria, Gamma-proteobacteria, Bacteriodetes, and Actinobacteridae species were cultivated. The results confirm the presence of bacteria within some paleosols, but no assumptions have been made with regard to in situ activity at present. These results underscore the need not only to further investigate Dry Valley cryosols but also to develop reconnaissance strategies to determine whether such likely Earth-like environments on the Red Planet also contain life.

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The potential use of biochemical and physiological responses as biomarkers of organophosphate exposure and/or effect were assessed in the shore crab (Carcinus maenas). Male crabs were assigned to one of four dimethoate treatments (0, 0.5, 1.0 or 2.0 mg 1(-1)). Cardiac activity was measured non-invasively before and during dimethoate exposure using automated interpulse duration assessment. Heart rates decreased significantly in a concentration-dependent manner (p

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Endothelial progenitor cells (EPCs) have great clinical value because they can be used as diagnostic biomarkers and as a cellular therapy for promoting vascular repair of ischaemic tissues. However, EPCs also have an additional research value in vascular disease modelling to interrogate human disease mechanisms. The term EPC is used to describe a diverse variety of cells, and we have identified a specific EPC subtype called outgrowth endothelial cell (OEC) as the best candidate for vascular disease modelling because of its high-proliferative potential and unambiguous endothelial commitment. OECs are isolated from human blood and can be exposed to pathologic conditions (forward approach) or be isolated from patients (reverse approach) in order to study vascular human disease. The use of OECs for modelling vascular disease will contribute greatly to improving our understanding of endothelial pathogenesis, which will potentially lead to the discovery of novel therapeutic strategies for vascular diseases.

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BACKGROUND & AIMS: The risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) is low and difficult to calculate. Accurate tools to determine risk are needed to optimize surveillance and intervention. We assessed the ability of candidate biomarkers to predict which cases of BE will progress to EAC or high-grade dysplasia and identified those that can be measured in formalin-fixed tissues. METHODS: We analyzed data from a nested case-control study performed using the population-based Northern Ireland BE Register (1993-2005). Cases who progressed to EAC (n = 89) or high-grade dysplasia =6 months after diagnosis with BE were matched to controls (nonprogressors, n = 291), for age, sex, and year of BE diagnosis. Established biomarkers (abnormal DNA content, p53, and cyclin A expression) and new biomarkers (levels of sialyl Lewis(a), Lewis(x), and Aspergillus oryzae lectin [AOL] and binding of wheat germ agglutinin) were assessed in paraffin-embedded tissue samples from patients with a first diagnosis of BE. Conditional logistic regression analysis was applied to assess odds of progression for patients with dysplastic and nondysplastic BE, based on biomarker status. RESULTS: Low-grade dysplasia and all biomarkers tested, other than Lewis(x), were associated with risk of EAC or high-grade dysplasia. In backward selection, a panel comprising low-grade dysplasia, abnormal DNA ploidy, and AOL most accurately identified progressors and nonprogressors. The adjusted odds ratio for progression of patients with BE with low-grade dysplasia was 3.74 (95% confidence interval, 2.43-5.79) for each additional biomarker and the risk increased by 2.99 for each additional factor (95% confidence interval, 1.72-5.20) in patients without dysplasia. CONCLUSIONS: Low-grade dysplasia, abnormal DNA ploidy, and AOL can be used to identify patients with BE most likely to develop EAC or high-grade dysplasia.