29 resultados para Biomarkers, Tumor


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Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

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BACKGROUND: Due to the heterogeneity in the biological behavior of prostate cancer, biomarkers that can reliably distinguish indolent from aggressive disease are urgently needed to inform treatment choices. METHODS: We employed 8-plex isobaric Tags for Relative and Absolute Quantitation (iTRAQ), to profile the proteomes of two distinct panels of isogenic prostate cancer cells with varying growth and metastatic potentials, in order to identify novel biomarkers associated with progression. The LNCaP, LNCaP-Pro5, and LNCaP-LN3 panel of cells represent a model of androgen-responsive prostate cancer, while the PC-3, PC-3M, and PC-3M-LN4 panel represent a model of androgen-insensitive disease. RESULTS: Of the 245 unique proteins identified and quantified (>or=95% confidence; >or=2 peptides/protein), 17 showed significant differential expression (>or=+/-1.5), in at least one of the variant LNCaP cells relative to parental cells. Similarly, comparisons within the PC-3 panel identified 45 proteins to show significant differential expression in at least one of the variant PC-3 cells compared with parental cells. Differential expression of selected candidates was verified by Western blotting or immunocytochemistry, and corresponding mRNA expression was determined by quantitative real-time PCR (qRT-PCR). Immunostaining of prostate tissue microarrays for ERp5, one of the candidates identified, showed a significant higher immunoexpression in pre-malignant lesions compared with non-malignant epithelium (P < 0.0001, Mann-Whitney U-test), and in high Gleason grade (4-5) versus low grade (2-3) cancers (P < 0.05). CONCLUSIONS: Our study provides proof of principle for the application of an 8-plex iTRAQ approach to uncover clinically relevant candidate biomarkers for prostate cancer progression.

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The accurate assessment of dietary exposure is important in investigating associations between diet and disease. Research in nutritional epidemiology, which has resulted in a large amount of information on associations between diet and chronic diseases in the last decade, relies on accurate assessment methods to identify these associations. However, most dietary assessment instruments rely to some extent on self-reporting, which is prone to systematic bias affected by factors such as age, gender, social desirability and approval. Nutritional biomarkers are not affected by these and therefore provide an additional, alternative method to estimate intake. However, there are also some limitations in their application: they are affected by inter-individual variations in metabolism and other physiological factors, and they are often limited to estimating intake of specific compounds and not entire foods. It is therefore important to validate nutritional biomarkers to determine specific strengths and limitations. In this perspective paper, criteria for the validation of nutritional markers and future developments are discussed.

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Purpose Meat and fish consumption are associated with changes in the risk of chronic diseases. Intake is mainly assessed using self-reporting, as no true quantitative nutritional biomarker is available. The measurement of plasma fatty acids, often used as an alternative, is expensive and time-consuming. As meat and fish differ in their stable isotope ratios, δ13C and δ15N have been proposed as biomarkers. However, they have never been investigated in controlled human dietary intervention studies. Objective In a short-term feeding study, we investigated the suitability of δ13C and δ15N in blood, urine and faeces as biomarkers of meat and fish intake. Methods The dietary intervention study (n = 14) followed a randomised cross-over design with three eight-day dietary periods (meat, fish and half-meat–half-fish). In addition, 4 participants completed a vegetarian control period. At the end of each period, 24-h urine, fasting venous blood and faeces were collected and their δ13C and δ15N analysed. Results There was a significant difference between diets in isotope ratios in faeces and urine samples, but not in blood samples (Kruskal–Wallis test, p < 0.0001). In pairwise comparisons, δ13C and δ15N were significantly higher in urine and faecal samples following a fish diet when compared with all other diets, and significantly lower following a vegetarian diet. There was no significant difference in isotope ratio between meat and half-meat–half-fish diets for blood, urine or faecal samples. Conclusions The results of this study show that urinary and faecal δ13C and δ15N are suitable candidate biomarkers for short-term meat and fish intake.

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Red and processed meat consumption is associated with the risk of colorectal cancer. Three hypotheses are proposed to explain this association, via heme-induced oxidation of fat, heterocyclic amines, or N-nitroso compounds. Rats have often been used to study these hypotheses, but the lack of enterosalivary cycle of nitrate in rats casts doubt on the relevance of this animal model to predict nitroso- and heme-associated human colon carcinogenesis. The present study was thus designed to clarify whether a nitrite intake that mimics the enterosalivary cycle can modulate hemeinduced nitrosation and fat peroxidation. This study shows that, in contrast with the starting hypothesis, drinking water added with nitrite to mimic the salivary nitrite content did not change the effect of hemoglobin on biochemicalmarkers linked to colon carcinogenesis, notably lipid peroxidation and cytotoxic activity in the colon of rat. However, ingested sodium nitrite increased fecal nitrosocompounds level, but their fecal concentration and their nature (iron-nitrosyl) would probably not be associated with an increased risk of cancer.We thus suggest that the rat model could be relevant for study the effect of red meat on colon carcinogenesis, in spite of the lack of nitrite in the saliva of rats.

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Antiinflammatory compounds in the diet can alleviate excessive inflammation, a factor in the pathogenesis of common diseases such as rheumatoid arthritis, atherosclerosis and diabetes. This study examined three European herbs, chamomile (Matricaria chamomilla), meadowsweet (Filipendula ulmaria L.) and willow bark (Salix alba L.), which have been traditionally used to treat inflammation and their potential for use as antiinflammatory agents. Aqueous herbal extracts and isolated polyphenolic compounds (apigenin, quercetin and salicylic acid, 0–100 μM) were incubated with THP1 macrophages, and interleukin (IL)-1β, IL-6 and tumour necrosis factor-alpha (TNF-) were measured. At concentrations of 10 μM, both apigenin and quercetin reduced IL-6 significantly ( p < 0.05). Apigenin at 10 μM and quercetin at 25 μM reduced TNF- significantly ( p < 0.05). Amongst the herbal extracts, willow bark had the greatest antiinflammatory activity at reducing IL-6 and TNF- production. This was followed by meadowsweet and then chamomile. The lowest effective antiinflammatory concentrations were noncytotoxic (MTT mitochondrial activity assay). The Comet assay, which was used to study the protective effect of the isolated phenols against oxidative damage, showed positive results for all three polyphenols. These are the first findings that demonstrate the antiinflammatory capacity of these herbal extracts.

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Background: Stable-isotope ratios of carbon (13C/12C, expressed as δ13C) and nitrogen (15N/14N, or δ15N) have been proposed as potential nutritional biomarkers to distinguish between meat, fish, and plant-based foods. Objective: The objective was to investigate dietary correlates of δ13C and δ15N and examine the association of these biomarkers with incident type 2 diabetes in a prospective study. Design: Serum δ13C and δ15N (‰) were measured by using isotope ratio mass spectrometry in a case-cohort study (n = 476 diabetes cases; n = 718 subcohort) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)–Norfolk population-based cohort. We examined dietary (food-frequency questionnaire) correlates of δ13C and δ15N in the subcohort. HRs and 95% CIs were estimated by using Prentice-weighted Cox regression. Results: Mean (±SD) δ13C and δ15N were −22.8 ± 0.4‰ and 10.2 ± 0.4‰, respectively, and δ13C (r = 0.22) and δ15N (r = 0.20) were positively correlated (P < 0.001) with fish protein intake. Animal protein was not correlated with δ13C but was significantly correlated with δ15N (dairy protein: r = 0.11; meat protein: r = 0.09; terrestrial animal protein: r = 0.12, P ≤ 0.013). δ13C was inversely associated with diabetes in adjusted analyses (HR per tertile: 0.74; 95% CI: 0.65, 0.83; P-trend < 0.001], whereas δ15N was positively associated (HR: 1.23; 95% CI: 1.09, 1.38; P-trend = 0.001). Conclusions: The isotope ratios δ13C and δ15N may both serve as potential biomarkers of fish protein intake, whereas only δ15N may reflect broader animal-source protein intake in a European population. The inverse association of δ13C but a positive association of δ15N with incident diabetes should be interpreted in the light of knowledge of dietary intake and may assist in identifying dietary components that are associated with health risks and benefits.

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Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome.

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BACKGROUND: Brain inflammation has been recognized as a complex phenomenon with numerous related aspects. In addition to the very well-described neurodegenerative effect of inflammation, several studies suggest that inflammatory signals exert a potentially positive influence on neural stem cell proliferation, migration and differentiation. Tumor necrosis factor alpha (TNF-alpha) is one of the best-characterized mediators of inflammation. To date, conclusions about the action of TNF on neural stem or progenitor cells (NSCs, NPCs) have been conflicting. TNF seems to activate NSC proliferation and to inhibit their differentiation into NPCs. The purpose of the present study was to analyze the molecular signal transduction mechanisms induced by TNF and resulting in NSC proliferation. RESULTS: Here we describe for the first time the TNF-mediated signal transduction cascade in neural stem cells (NSCs) that results in increased proliferation. Moreover, we demonstrate IKK-alpha/beta-dependent proliferation and markedly up-regulated cyclin D1 expression after TNF treatment. The significant increase in proliferation in TNF-treated cells was indicated by increased neurosphere volume, increased bromodeoxyuridin (BrdU) incorporation and a higher total cell number. Furthermore, TNF strongly activated nuclear factor-kappa B (NF-kappaB) as measured by reporter gene assays and by an activity-specific antibody. Proliferation of control and TNF-treated NSCs was strongly inhibited by expression of the NF-kappaB super-repressor IkappaB-AA1. Pharmacological blockade of IkappaB ubiquitin ligase activity led to comparable decreases in NF-kappaB activity and proliferation. In addition, IKK-beta gene product knock-down via siRNA led to diminished NF-kappaB activity, attenuated cyclin D1 expression and finally decreased proliferation. In contrast, TGFbeta-activated kinase 1 (TAK-1) is partially dispensable for TNF-mediated and endogenous proliferation. Understanding stem cell proliferation is crucial for future regenerative and anti-tumor medicine. CONCLUSION: TNF-mediated activation of IKK-beta resulted in activation of NF-kappaB and was followed by up-regulation of the bona-fide target gene cyclin D1. Activation of the canonical NF-kappaB pathway resulted in strongly increased proliferation of NSCs.

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Background: Epidemiological data suggest inverse associations between citrus flavanone intake and cardiovascular disease (CVD) risk. However, insufficient randomized controlled trial (RCT) data limit our understanding of mechanisms by which flavanones and their metabolites potentially reduce cardiovascular (CV) risk factors. Objective: We examined the effects of orange juice or a dose-matched hesperidin supplement on plasma concentrations of established and novel flavanone metabolites and their effects on CV risk biomarkers in men at moderate CVD risk. Methods: In an acute, randomized, placebo-controlled crossover trial, 16 fasted participants (aged 51-69 y) received orange juice or a hesperidin supplement (both providing 320 mg hesperidin) or control (all matched for sugar and vitamin C content). At baseline and 5 h post-intake, endothelial function (primary outcome), further CV risk biomarkers (i.e. blood pressure, arterial stiffness, cardiac autonomic function, platelet activation and NADPH oxidase gene expression) and plasma flavanone metabolites were assessed. Prior to each intervention, a diet low in flavonoids, nitrate/nitrite, alcohol and caffeine was followed and a standardized low-flavonoid evening meal was consumed. Results: Orange juice intake significantly elevated mean (± SEM) plasma concentrations of 8 flavanone (1.75 ± 0.35 µmol/L, P < 0.0001) and 15 phenolic metabolites (13.27 ± 2.22 µmol/L, P < 0.0001) compared with control at 5 h post-consumption. Despite increased plasma flavanone and phenolic metabolite concentrations, CV risk biomarkers were unaltered. Following hesperidin supplement intake, flavanone metabolites were not different to control, suggesting altered absorption/metabolism compared with the orange juice matrix. Conclusions: Following single-dose flavanone intake within orange juice, we detected circulating flavanone and phenolic metabolites collectively reaching a concentration of 15.20 ± 2.15 µmol/L but observed no effect on CV risk biomarkers. Longer-duration RCTs are required to further examine the previous associations between higher flavanone intakes and improved cardiovascular health and to ascertain the relative importance of food matrix and flavanone-derived phenolic metabolites.

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Background: Public health strategies to lower cardiovascular disease (CVD) risk involve reducing dietary saturated fatty acid (SFA) intake to ≤10% of total energy (%TE). However, the optimal type of replacement fat is unclear. Objective: We investigated the substitution of 9.5-9.6%TE dietary SFA with either monounsaturated (MUFA) or n-6 polyunsaturated fatty acids (PUFA) on vascular function and other CVD risk factors. Design: Using a randomized, controlled, single-blind, parallel group dietary intervention, 195 men and women aged 21-60 y with moderate CVD risk (≥50% above the population mean) from the United Kingdom followed one of three 16-wk isoenergetic diets (%TE target compositions, total fat:SFA:MUFA:n-6 PUFA): SFA-rich (36:17:11:4, n = 65), MUFA-rich (36:9:19:4, n = 64) or n-6 PUFA-rich (36:9:13:10, n = 66). The primary outcome measure was flow-mediated dilatation (%FMD); secondary outcome measures included fasting serum lipids, microvascular reactivity, arterial stiffness, ambulatory blood pressure, and markers of insulin resistance, inflammation and endothelial activation. Results: Replacing SFA with MUFA or n-6 PUFA did not significantly impact on %FMD (primary endpoint) or other measures of vascular reactivity. Of the secondary outcome measures, substitution of SFA with MUFA attenuated the increase in night systolic blood pressure (-4.9 mm Hg, P = 0.019) and reduced E-selectin (-7.8%, P = 0.012). Replacement with MUFA or n-6 PUFA lowered fasting serum total cholesterol (TC; -8.4% and -9.2%, respectively), low-density lipoprotein cholesterol (-11.3% and -13.6%) and TC to high-density lipoprotein cholesterol ratio (-5.6% and -8.5%) (P ≤ 0.001). These changes in low-density lipoprotein cholesterol equate to an estimated 17-20% reduction in CVD mortality. Conclusions: Substitution of 9.5-9.6%TE dietary SFA with either MUFA or n-6 PUFA did not impact significantly on %FMD or other measures of vascular function. However, the beneficial effects on serum lipid biomarkers, blood pressure and E-selectin offer a potential public health strategy for CVD risk reduction.

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The present study aims to investigate the dose dependent effects of consuming diets enriched in flavonoid-rich and flavonoid-poor fruits and vegetables on the urine metabolome of adults who had a C1.5 fold increased risk of cardiovascular diseases. A single-blind, dose-dependent, parallel randomized controlled dietary intervention was conducted where volunteers (n = 126) were randomly assigned to one of three diets: high flavonoid diet, low flavonoid diet or habitual diet as a control for 18 weeks. High resolution LC– MS untargeted metabolomics with minimal sample cleanup was performed using an Orbitrap mass spectrometer. Putative biomarkers which characterize diets with high and low flavonoid content were selected by state-of-the-art data analysis strategies and identified by HR-MS and HR-MS/MS assays. Discrimination between diets was observed by application of two linear mixedmodels: one including a diet-time interaction effect and the second containing only a time effect. Valerolactones, phenolic acids and their derivatives were among sixteen biomarkers related to the high flavonoid dietary exposure. Four biomarkers related to the low flavonoid diet belonged to the family of phenolic acids. For the first time abscisic acid glucuronide was reported as a biomarker after a dietary intake, however its origins have to be examined by future hypothesis driven experiments using a more targeted approach. This metabolomic analysis has identified a number of dose dependent urinary biomarkers (i.e. proline betaine or iberin-N-acetyl cysteine), which can be used in future observation and intervention studies to assess flavonoids and nonflavonoid phenolic intakes and compliance to fruit and vegetable intervention.

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Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.