Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr

Colorectal cancer DNA methylation patterns from patients in Manaus, Brazil

Submitted by Luciane Willcox ([email protected]) on 2016-08-26T16:21:34Z No. of bitstreams: 1 Colorectal cancer DNA methyolation patterns from patients in Manaus, Brazil.pdf: 1058445 bytes, checksum: 309836b0a370d8ddc2ab281f81de6959 (MD5)Approved for entry into archive by Luciane Willcox ([email protected]) on 2016-08-26T16:31:19Z (GMT) No. of bitstreams: 1 Colorectal cancer DNA methyolation patterns from patients in Manaus, Brazil.pdf: 1058445 bytes, checksum: 309836b0a370d8ddc2ab281f81de6959 (MD5)Made available in DSpace on 2016-08-26T16:31:19Z (GMT). No. of bitstreams: 1 Colorectal cancer DNA methyolation patterns from patients in Manaus, Brazil.pdf: 1058445 bytes, checksum: 309836b0a370d8ddc2ab281f81de6959 (MD5) Previous issue date: 2015-09-12CAPES, CNPq, Cancer Foundation (Oncobiologia Grant), and FAPEAMFederal University of Amazonas. Institute of Exact Sciences. Laboratory of Chromatography and Mass Spectrometry. Manaus, AM, Brazil.Oswaldo Cruz Fundation. Instituto Leonidas e Maria Deane. Manaus, AM, Brazil.Amazon State University. High School of Health. Manaus, AM, Brazil.Federal University of Rio de Janeiro. Department of Pathology. Laboratory of Molecular Pathology. Rio de Janeiro, RJ, Brazil.Oncology Control Center Foundation of Amazon State. Department of Abdominal Surgery. Manaus, AM, Brazil.Oswaldo Cruz Fundation. Carlos Chagas Institute. Laboratory of Proteomics and Protein Engineering. Curitiba, PR, Brazil.Background DNA methylation is commonly linked with the silencing of the gene expression for many tumor suppressor genes. As such, determining DNA methylation patterns should aid, in times to come, in the diagnosis and personal treatment for various types of cancers. Here, we analyzed the methylation pattern from five colorectal cancer patients from the Amazon state in Brazil for four tumor suppressor genes, viz.: DAPK, CDH1, CDKN2A, and TIMP2 by employing a polymerase chain reaction (PCR) specific to methylation. Efforts in the study of colorectal cancer are fundamental as it is the third most of highest incidence in the world. Results Tumor biopsies were methylated in 1/5 (20 %), 2/5 (40 %), 4/5 (80 %), and 4/5 (80 %) for CDH1, CDKN2A, DAPK, and TIMP2 genes, respectively. The margin biopsies were methylated in 3/7 (43 %), 2/7 (28 %), 7/7 (100 %), and 6/7 (86 %) for CDH1, CDKN2A, DAPK, and TIMP2, respectively. Conclusions Our findings showed DAPK and TIMP2 to be methylated in most samples from both tumor tissues and adjacent non-neoplastic margins; thus presenting distinct methylation patterns. This emphasizes the importance of better understanding of the relation of these patterns with cancer in the context of different populations

Exploring the Proteomic Landscape of a Gastric Cancer Biopsy with the Shotgun Imaging Analyzer

Accessing localized proteomic profiles has emerged as a fundamental strategy to understand the biology of diseases, as recently demonstrated, for example, in the context of determining cancer resection margins with improved precision. Here, we analyze a gastric cancer biopsy sectioned into 10 parts, each one subjected to MudPIT analysis. We introduce a software tool, named Shotgun Imaging Analyzer and inspired in MALDI imaging, to enable the overlaying of a protein’s expression heat map on a tissue picture. The software is tightly integrated with the NeXtProt database, so it enables the browsing of identified proteins according to chromosomes, quickly listing human proteins never identified by mass spectrometry (i.e., the so-called missing proteins), and the automatic search for proteins that are more expressed over a specific region of interest on the biopsy, all of which constitute goals that are clearly well-aligned with those of the C-HPP. Our software has been able to highlight an intense expression of proteins previously known to be correlated with cancers (e.g., glutathione S-transferase Mu 3), and in particular, we draw attention to Gastrokine-2, a “missing protein” identified in this work of which we were able to clearly delineate the tumoral region from the “healthy” with our approach. Data are available via ProteomeXchange with identifier PXD000584

Are Gastric Cancer Resection Margin Proteomic Profiles More Similar to Those from Controls or Tumors?

A strategy for treating cancer is to surgically remove the tumor together with a portion of apparently healthy tissue surrounding it, the so-called “resection margin”, to minimize recurrence. Here, we investigate whether the proteomic profiles from biopsies of gastric cancer resection margins are indeed more similar to those from healthy tissue than from cancer biopsies. To this end, we analyzed biopsies using an offline MudPIT shotgun proteomic approach and performed label-free quantitation through a distributed normalized spectral abundance factor approach adapted for extracted ion chromatograms (XICs). A multidimensional scaling analysis revealed that each of those tissue-types is very distinct from each other. The resection margin presented several proteins previously correlated with cancer, but also other overexpressed proteins that may be related to tumor nourishment and metastasis, such as collagen alpha-1, ceruloplasmin, calpastatin, and E-cadherin. We argue that the resection margin plays a key role in Paget’s “soil to seed” hypothesis, that is, that cancer cells require a special microenvironment to nourish and that understanding it could ultimately lead to more effective treatments

Are Gastric Cancer Resection Margin Proteomic Profiles More Similar to Those from Controls or Tumors?

A strategy for treating cancer is to surgically remove the tumor together with a portion of apparently healthy tissue surrounding it, the so-called “resection margin”, to minimize recurrence. Here, we investigate whether the proteomic profiles from biopsies of gastric cancer resection margins are indeed more similar to those from healthy tissue than from cancer biopsies. To this end, we analyzed biopsies using an offline MudPIT shotgun proteomic approach and performed label-free quantitation through a distributed normalized spectral abundance factor approach adapted for extracted ion chromatograms (XICs). A multidimensional scaling analysis revealed that each of those tissue-types is very distinct from each other. The resection margin presented several proteins previously correlated with cancer, but also other overexpressed proteins that may be related to tumor nourishment and metastasis, such as collagen alpha-1, ceruloplasmin, calpastatin, and E-cadherin. We argue that the resection margin plays a key role in Paget’s “soil to seed” hypothesis, that is, that cancer cells require a special microenvironment to nourish and that understanding it could ultimately lead to more effective treatments

Universal Dependencies 2.7

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008)

Universal Dependencies 2.8.1

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). Version 2.8.1 fixes a bug in 2.8 where a portion of the Dutch Alpino treebank was accidentally omitted

Universal Dependencies 2.7

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008)