Estrogen receptor dependent genetic and epigenetic factors of tamoxifen resistance

Resumo: A decisão da terapêutica hormonal no tratamento do cancro da mama baseiase na determinação do receptor de estrogénio alfa por imunohistoquímica (IHC). Contudo, a presença deste receptor não prediz a resposta em todas as situações, em parte devido a limitações do método IHC. Investigámos se a expressão dos genes ESR1 e ESR2, bem como a metilação dos respectivos promotores, pode estar relacionada com a evolução desfavorável de uma proporção de doentes tratados com tamoxifeno assim como com a perda dos receptores de estrogénio alfa (ERα) e beta (ERß). Amostras de 211 doentes com cancro da mama diagnosticado entre 1988 e 2004, fixadas em formalina e preservadas em parafina, foram utilizadas para a determinação por IHC da presença dos receptores ERα e ERß. O mRNA total do gene ESR1 e os níveis específicos do transcrito derivado do promotor C (ESR1_C), bem como dos transcritos ESR2_ß1, ESR2_ß2/cx, and ESR2_ß5 foram avaliados por Real-time PCR. Os promotores A e C do gene ESR1 e os promotores 0K e 0N do gene ESR2 foram investigados por análise de metilação dos dinucleotidos CpG usando bisulfite-PCR para análise com enzimas de restrição, ou para methylation specific PCR. Atendendo aos resultados promissores relacionados com a metilação do promotor do gene ESR1, complementamos o estudo com um método quantitativo por matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) suportado pelo software Epityper para a medição da metilação nos promotores A e C. Fez-se a avaliação da estabilidade do mRNA nas linhas celulares de cancro da mama MCF-7 e MDA-MB-231 tratadas com actinomicina D. Baixos níveis do transcrito ESR1_C associaram-se a uma melhor sobrevivência global (p = 0.017). Níveis elevados do transcrito ESR1_C associaram-se a uma resposta inferior ao tamoxifeno (HR = 2.48; CI 95% 1.24-4.99), um efeito mais pronunciado em doentes com tumores de fenótipo ERα/PgR duplamente positivo (HR = 3.41; CI 95% 1.45-8.04). A isoforma ESR1_C mostrou ter uma semi-vida prolongada, bem como uma estrutura secundária da região 5’UTR muito mais relaxada em comparação com a isoforma ESR1_A. A análise por Western-blot mostrou que ao nível da 21 proteína, a selectividade de promotores é indistinguivel. Não se detectou qualquer correlação entre os níveis das isoformas do gene ESR2 ou entre a metilação dos promotores do gene ESR2, e a detecção da proteína ERß. A metilação do promotor C do gene ESR1, e não do promotor A, foi responsável pela perda do receptor ERα. Estes resultados sugerem que os níveis do transcrito ESR1_C sejam usados como um novo potencial marcador para o prognóstico e predição de resposta ao tratamento com tamoxifeno em doentes com cancro da mama. Abstract: The decision of endocrine breast cancer treatment relies on ERα IHC-based assessment. However, ER positivity does not predict response in all cases in part due to IHC methodological limitations. We investigated whether ESR1 and ESR2 gene expression and respective promoter methylation may be related to non-favorable outcome of a proportion of tamoxifen treated patients as well as to ERα and ERß loss. Formalin-fixed paraffin-embedded breast cancer samples from 211 patients diagnosed between 1988 and 2004 were submitted to IHC-based ERα and ERß protein determination. ESR1 whole mRNA and promoter C specific transcript levels, as well as ESR2_ß1, ESR2_ß2/cx, and ESR2_ß5 transcripts were assessed by real-time PCR. ESR1 promoters A and C, and ESR2 promoters 0N and 0K were investigated by CpG methylation analysis using bisulfite-PCR for restriction analysis, or methylation specific PCR. Due to the promising results related to ESR1 promoter methylation, we have used a quantification method by matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDITOF MS) together with Epityper software to measure methylation at promoters A and C. mRNA stability was assessed in actinomycin D treated MCF-7 and MDA-MB-231 cells. ERα protein was quantified using transiently transfected breast cancer cells. Low ESR1_C transcript levels were associated with better overall survival (p = 0.017). High levels of ESR1_C transcript were associated with non-favorable response in tamoxifen treated patients (HR = 2.48; CI 95% 1.24-4.99), an effect that was more pronounced in patients with ERα/PgR double-positive tumors (HR = 3.41; CI 95% 1.45-8.04). The ESR1_C isoform had a prolonged mRNA half-life and a more relaxed 5’UTR structure compared to ESR1_A isoform. Western-blot analysis showed that at protein level, the promoter selectivity is undistinguishable. There was no correlation between levels of ESR2 isoforms or ESR2 promoter methylation and ERß protein staining. ESR1 promoter C CpG methylation and not promoter A was responsible for ERα loss. We propose ESR1_C levels as a putative novel marker for breast cancer prognosis and prediction of tamoxifen response.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Hyperspectral unmixing algorithm via dependent component analysis

This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component analysis (DECA). This method decomposes a hyperspectral images into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding abundance fractions at each pixel. DECA assumes that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abudances are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. This method overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

Effect of skin colour and selected physical characteristics on Schistosoma mansoni dependent morbidity

The effect of the colour group on the morbidity due to Schistosoma mansoni was examined in two endemic areas situated in the State of Minas Gerais, Brazil. Of the 2773 eligible inhabitants, 1971 (71.1%) participated in the study: 545 (27.6%) were classified as white, 719 (36.5%) as intermediate and 707 (35.9%) as black. For each colour group, signs and symptoms of individuals who eliminated S.mansoni eggs (cases) were compared to those who did not present eggs in the faeces (controls). The odds ratios were adjusted by age, gender, previous treatment for schistosomiasis, endemic area and quality of the household. There was no evidence of a modifier effect of colour on diarrhea, bloody faeces or abdominal pain. A modifier effect of colour on hepatomegaly was evident among those heaviest infected (> 400 epg): the adjusted odds ratios for palpable liver at the middle clavicular and the middle sternal lines were smaller among blacks (5.4 and 6.5, respectively) and higher among whites (10.6 and 12.9) and intermediates (10.4 and 10.1, respectively). These results point out the existence of some degree of protection against hepatomegaly among blacks heaviest infected in the studied areas.

Lettuce (Lactuca sativa L.) leaf-proteome profiles after exposure to cylindrospermopsin and a microcystin-LR/cylindrospermopsin mixture: A concentration-dependent response

The intensification of agricultural productivity is an important challenge worldwide. However, environmental stressors can provide challenges to this intensification. The progressive occurrence of the cyanotoxins cylindrospermopsin (CYN) and microcystin-LR (MC-LR) as a potential consequence of eutrophication and climate change is of increasing concern in the agricultural sector because it has been reported that these cyanotoxins exert harmful effects in crop plants. A proteomic-based approach has been shown to be a suitable tool for the detection and identification of the primary responses of organisms exposed to cyanotoxins. The aim of this study was to compare the leaf-proteome profiles of lettuce plants exposed to environmentally relevant concentrations of CYN and a MC-LR/CYN mixture. Lettuce plants were exposed to 1, 10, and 100 lg/l CYN and a MC-LR/CYN mixture for five days. The proteins of lettuce leaves were separated by twodimensional electrophoresis (2-DE), and those that were differentially abundant were then identified by matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF/TOF MS). The biological functions of the proteins that were most represented in both experiments were photosynthesis and carbon metabolism and stress/defense response. Proteins involved in protein synthesis and signal transduction were also highly observed in the MC-LR/CYN experiment. Although distinct protein abundance patterns were observed in both experiments, the effects appear to be concentration-dependent, and the effects of the mixture were clearly stronger than those of CYN alone. The obtained results highlight the putative tolerance of lettuce to CYN at concentrations up to 100 lg/l. Furthermore, the combination of CYN with MC-LR at low concentrations (1 lg/l) stimulated a significant increase in the fresh weight (fr. wt) of lettuce leaves and at the proteomic level resulted in the increase in abundance of a high number of proteins. In contrast, many proteins exhibited a decrease in abundance or were absent in the gels of the simultaneous exposure to 10 and 100 lg/l MC-LR/CYN. In the latter, also a significant decrease in the fr. wt of lettuce leaves was obtained. These findings provide important insights into the molecular mechanisms of the lettuce response to CYN and MC-LR/CYN and may contribute to the identification of potential protein markers of exposure and proteins that may confer tolerance to CYN and MC-LR/CYN. Furthermore, because lettuce is an important crop worldwide, this study may improve our understanding of the potential impact of these cyanotoxins on its quality traits (e.g., presence of allergenic proteins).

Culture-dependent characterization of cyanobacterial diversity in the intertidal zones of the Portuguese coast: A polyphasic study

Cyanobacteria are important primary producers, and many are able to fix atmospheric nitrogen playing a key role in the marine environment. However, not much is known about the diversity of cyanobacteria in Portuguese marine waters. This paper describes the diversity of 60 strains isolated from benthic habitats in 9 sites (intertidal zones) on the Portuguese South and West coasts. The strains were characterized by a morphological study (light and electron microscopy) and by a molecular characterization (partial 16S rRNA, nifH, nifK, mcyA, mcyE/ndaF, sxtI genes). The morphological analyses revealed 35 morphotypes (15 genera and 16 species) belonging to 4 cyanobacterial Orders/Subsections. The dominant groups among the isolates were the Oscillatoriales. There is a broad congruence between morphological and molecular assignments. The 16S rRNA gene sequences of 9 strains have less than 97% similarity compared to the sequences in the databases, revealing novel cyanobacterial diversity. Phylogenetic analysis, based on partial 16S rRNA gene sequences showed at least 12 clusters. One-third of the isolates are potential N2-fixers, as they exhibit heterocysts or the presence of nif genes was demonstrated by PCR. Additionally, no conventional freshwater toxins genes were detected by PCR screening.

Crystallographic studies on molybdopterin-dependent enzymes

Dissertação para obtenção do Grau de Doutor em Bioquímica, Especialidade Bioquímica Estrutural

Activity-Dependent Neurorehabilitation Beyond Physical Trainings: "Mental Exercise" Through Mirror Neuron Activation

The activity dependent brain repair mechanism has been widely adopted in many types of neurorehabilitation. The activity leads to target specific and non-specific beneficial effects in different brain regions, such as the releasing of neurotrophic factors, modulation of the cytokines and generation of new neurons in adult hood. However physical exercise program clinically are limited to some of the patients with preserved motor functions; while many patients suffered from paralysis cannot make such efforts. Here the authors proposed the employment of mirror neurons system in promoting brain rehabilitation by "observation based stimulation". Mirror neuron system has been considered as an important basis for action understanding and learning by mimicking others. During the action observation, mirror neuron system mediated the direct activation of the same group of motor neurons that are responsible for the observed action. The effect is clear, direct, specific and evolutionarily conserved. Moreover, recent evidences hinted for the beneficial effects on stroke patients after mirror neuron system activation therapy. Finally some music-relevant therapies were proposed to be related with mirror neuron system.

Deletions within COL11A1 in Type 2 Stickler Syndrome Detected by Multiplex Ligation - Syndrome Detected by Multiplex Ligation Dependent Probe Amplification (MLPA)

Background: COL11A1 is a large complex gene around 250 kb in length and consisting of 68 exons. Pathogenic mutations in the gene can result in Stickler syndrome, Marshall syndrome or Fibrochondrogenesis. Many of the mutations resulting in either Stickler or Marshall syndrome alter splice sites and result in exon skipping, which because of the exon structure of collagen genes usually leaves the message in-frame. The mutant protein then exerts a dominant negative effect as it co-assembles with other collagen gene products. To date only one large deletion of 40 kb in the COL11A1, which was detected by RT-PCR, has been characterized. However, commonly used screening protocols, utilizing genomic amplification and exon sequencing, are unlikely to detect such large deletions. Consequently the frequency of this type of mutation is unknown. Case presentations: We have used Multiplex Ligation-Dependent Probe Amplification (MLPA) in conjunction with exon amplification and sequencing, to analyze patients with clinical features of Stickler syndrome, and have detected six novel deletions that were not found by exon sequencing alone. Conclusion: Exon deletions appear to represent a significant proportion of type 2 Stickler syndrome. This observation was previously unknown and so diagnostic screening of COL11A1 should include assays capable of detecting both large and small deletions, in addition to exon sequencing.

Information flow analysis using data-dependent logical propositions

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Long-Term and Concentration-Dependent Beneficial Effect of Efavirenz on HDL-Cholesterol in HIV-Infected Patients

AIMS: To investigate the long-term effects of efavirenz on cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C) and triglycerides (TG). METHODS: Thirty-four HIV-infected patients who commenced efavirenz therapy were monitored for 36 months. RESULTS: In patients with baseline HDL-C<40 mg.dL-1 an increase in HDL-C from 31+/-1 mg.dL-1 to 44+/-2 mg.dL-1 (95% confidence interval 5.9, 21.9, P<0.01) was observed and remained throughout the follow-up period. Median efavirenz plasma concentration was 1.98 mg.L-1 and a direct correlation between percentage of HDL-C variation or TC/HDL-C ratio and efavirenz plasma concentrations was found. CONCLUSIONS: There is evidence of a long-term and concentration-dependent beneficial effect of efavirenz on HDL-C in HIV-infected patients.

The mechanism of formate oxidation by metal-dependent formate dehydrogenases

J Biol Inorg Chem (2011) 16:1255–1268 DOI 10.1007/s00775-011-0813-8

Low-Spin Heme b3 in the Catalytic Center of Nitric Oxide Reductase from Pseudomonas nautica

Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605p

Triple Regimen with Rituximab, Plasmapheresis and Intravenous Immunoglobulin in the Treatment of Dialysis Dependent Acute Humoral-Mediated Rejection in Kidney Grafts

Introduction: The clinical importance of humoral-mediated acute rejection has been progressively recognised. Early recognition and treatment with plasmapheresis and intravenous immunoglobulin have recently improved short term prognosis. Case report: In this report we describe the clinical features of three 2nd transplant patients developing severe acute humoral rejection during the first week post-transplant while on anti-thymocyte globulin therapy. Treatment with plasmapheresis/ intravenous immunoglobulin/rituximab resulted in rapid reversal of oliguria,and recovery of renal function within the 1st week of treatment in 2/3 patients. Diagnosis was confirmed by graft biopsies revealing peritubular neutrophiles and C4d deposits. Sequential graft biopsies in all three patients revealed complete histological recovery within two weeks. One patient never recovered renal function, and one patient lost his graft at three months following hemorrhagic shock. After 2 years follow up, the remaining patient maintains a serum creatinine of 1.1mg/dl. Conclusion: The regimen using plasmapheresis plus intravenous immunoglobulin and rituximab was effective in rapidly reversing severe acute humoral rejection.

Differences in Nevirapine Biotransformation as a Factor for its Sex-Dependent Dimorphic Profile of Adverse Drug Reactions

OBJECTIVES: Nevirapine is widely used for the treatment of HIV-1 infection; however, its chronic use has been associated with severe liver and skin toxicity. Women are at increased risk for these toxic events, but the reasons for the sex-related differences are unclear. Disparities in the biotransformation of nevirapine and the generation of toxic metabolites between men and women might be the underlying cause. The present work aimed to explore sex differences in nevirapine biotransformation as a potential factor in nevirapine-induced toxicity. METHODS: All included subjects were adults who had been receiving 400 mg of nevirapine once daily for at least 1 month. Blood samples were collected and the levels of nevirapine and its phase I metabolites were quantified by HPLC. Anthropometric and clinical data, and nevirapine metabolite profiles, were assessed for sex-related differences. RESULTS: A total of 52 patients were included (63% were men). Body weight was lower in women (P = 0.028) and female sex was associated with higher alkaline phosphatase (P = 0.036) and lactate dehydrogenase (P = 0.037) levels. The plasma concentrations of nevirapine (P = 0.030) and the metabolite 3-hydroxy-nevirapine (P = 0.035), as well as the proportions of the metabolites 12-hydroxy-nevirapine (P = 0.037) and 3-hydroxy-nevirapine (P = 0.001), were higher in women, when adjusted for body weight. CONCLUSIONS: There was a sex-dependent variation in nevirapine biotransformation, particularly in the generation of the 12-hydroxy-nevirapine and 3-hydroxy-nevirapine metabolites. These data are consistent with the sex-dependent formation of toxic reactive metabolites, which may contribute to the sex-dependent dimorphic profile of nevirapine toxicity.