INTRODUÇÃO: A principal manifestação clínica da doença aterosclerótica é o infarto agudo do miocárdio, caracterizada como emergência médica, que necessita de diagnóstico correto, rápido, preciso e terapia eficaz. Os estudos de transcriptoma e proteoma possibilitam obter informações que nos permite compreender de forma mais abrangente a evolução fisiopatológica das doenças, sendo as cardiovasculares particularmente favorecidas por terem etiologia multifatorial e sem dúvida multigênica, portanto a utilização destas ferramentas num modelo de doença aguda pode auxiliar, de forma singular, na obtenção de novas informações, tais como novos marcadores precoces de injúria. OBJETIVO: Identificar novos biomarcadores de doenças cardiovasculares através da análise do perfil de expressão de RNAm de células do sangue periférico e proteínas plasmáticas de pacientes com SCA. CASUÍSTICA E MÉTODOS: É um estudo caso-controle de pacientes com SCA recrutados no Pronto-Socorro do Instituto Dante Pazzanese de Cardiologia. Foram recrutados 84 indivíduos com Síndrome Coronariana Aguda (SCA), 47 indivíduos sem doença cardiovascular (grupo controle), de ambos os sexos com idade entre 30 a 65 anos, atendidos no Instituto Dante Pazzanese do Estado de São Paulo - Brasil. A avaliação de expressão gênica global de 10 pacientes e 6 controles (pareados) durante as primeiras 48 h após o IAM foi realizada através dos microarranjos de DNA (sistema Affymetrix) e a análise de plasma por separação em sistema de microarranjos (ProteinChip®), seguida da identificação e quantificação por espectrometria de massa, em sistema SELDI-TOF/MS. Os resultados de microarranjo de DNA foram validados tecnicamente (a partir das mesmas amostras processadas por microarranjo de DNA) e, posteriormente validados biologicamente (a partir das outras amostras não processadas por microarranjo de DNA) através da PCR em tempo real. RESULTADOS: Foram observados ao total 599 genes diferentemente expressos nas primeiras 48 h após IAM. Trinta e três genes foram selecionados e submetidos à validação técnica, sendo que destes, 20 genes foram submetidos à validação biológica através da PCR em tempo real. Os validados foram: ALOX15, AREG, BCL2A1, BCL2L1, CA1, COX7B, ECDHC3,KCNE1, IL18R1, IRS2, MYL4, MMP9 e TREML4. Na análise, foram identificados 479 espectros de proteínas plasmáticas diferentemente expressos em relação ao controle, destes destacam-se 16 possíveis proteínas correspondentes ao peso molecular entre 6386.5 Da e 17807,7 Da. CONCLUSÃO: Os resultados desses estudos sugerem novos marcadores para avaliação da síndrome coronariana aguda e provavelmente com valor prognóstico importante. / BACKGROUND: The main clinical manifestation of atherosclerosis is the acute myocardial infarction (AMI), which is a medical emergency that requires prompt diagnosis and efficient therapy. The transcriptomic and proteomic approaches are both powerful tools for the study of AMI and may be instrumental to identify news biomarkers involved in the inflammatory and apoptotic process of cardiovascular diseases. OBJECTIVE: The aim of this study is to determine the gene expression of RNAm and protein in blood cells following an AMI to identify new biomarkers. PATIENTS AND METHODS: For this study eighty four patients with acute coronary syndrome (ACS) and forty seven control individuals were selected among patients of the Instituto Dante Pazzanese, São Paulo state, Brazil. A global gene expression profile by GeneChip® Exon 1.0 ST Array (Affymetrix) and proteomic plasma profile by ProteinChip® Biomarker System and SELDI-TOF/MS were evaluated for ten patients from the ACS group and six from the control group. These patients were followed up for the first 48 h following the AMI. The genes differently expressed by microarray analysis were submitted to technical (same casuistic) and biologic (new casuistic) validation by PCR real time. RESULTS: 599 genes were differentially expressed at the first 48 h after AMI. Thirty-three genes were selected and submitted to the technical validation, and 20 were subjected to biological validation by real time PCR afterwards. The validated ones were: ALOX15, Areg, BCL2A1, BCL2L1, CA1, COX7B, ECDHC3, KCNE1, IL18R1, IRS2, MYL4, MMP9 and TREML4. At proteomic analysis, 479 peaks of plasma proteins differentially expressed were identified. 16 peaks were considered as high potentially biomarkers. Their molecular weight was between 6386.5 Da and 17807.7 Da. CONCLUSION: Results from this study were able to identify changes in gene and protein profiles in the plasma, and suggest new markers for evaluation of acute coronary syndrome and probably with important prognostic value.

Un dispositif de stimulation électrique in vitro sur des lignées cellulaires a été optimisé afin de nous permettre d'étudier les mécanismes cellulaires et moléculaires de la SHF. Deux lignées cellulaires (GH3 et PC12) ont été analysées au niveau transcriptomique, protéomique et de la sécrétion hormonale et de neurotransmetteurs.Nous avons comparé les niveaux de sécrétion de PRL des GH3 traitées par SHF, SBF ou par la dopamine; ainsi que les niveaux des catécholamines (DA, AD et NA) des PC12 traitées par SHF, SBF ou par la 6-OHDA. La synthèse protéique des cellules stimulées a été analysée par les techniques d'incorporation de 35S méthionine et de SELDI-TOF-MS. Enfin nous avons recherché les modifications d'expression génique des cellules stimulées en utilisant la technique des microarray à base d'oligonucléotides longs sur nylon et détection radioactive.Les premières expériences montrent une diminution significative de la quantité de prolactine à un niveau comparable à celui obtenu avec l'inhibiteur conventionnel, la dopamine. De la même façon, la production de catécholamines dans le milieu est inhibée. Les données transcriptomiques montrent l'existence des profils d'expression caractéristique de la neurostimulation à haute fréquence, avec environ 100 gènes discriminants impliqués dans la synthèse protéique, la signalisation calcique, l'énergétique cellulaire pour les principaux. Nous avons confirmé l'impact de la neurostimulation sur la synthèse protéique en SELDI-TOF comme en incorporation de méthionine. Un mécanisme original de SHF peut donc être proposé, impliquant la neutralisation de la synthèse protéique dans l'inactivation réactionnelle des structures neuronale

<p><b>Background and aims:</b> Type 2 diabetes mellitus is connected with elevated glucose levels, which cause impaired glucose-stimulated insulin secretion (GSIS) and degeneration of β-cells. Mechanisms for such glucotoxic effects were explored in the present study.</p><p><b>Materials and methods:</b> INS-1E cells were cultured for 5 days in 5.5, 11, 20 or 27 mM glucose in the presence or absence of AMPK-agonist AICAR. GSIS was determined from INS-1E cells and islets obtained from type 2 diabetes and control donors. Human islets and INS-1E cells were functionally characterized (GSIS) and protein profiled (SELDI-TOF MS). Glucose-induced <i>de novo</i> synthesis of fatty acyls (HR-MAS NMR spectroscopy), fatty acid composition (GC-MS), triglyceride content and specific proteins (Western blotting) were determined in INS-1E cells.</p><p><b>Results:</b> Impaired GSIS was observed from INS-1E cells exposed to chronic hyperglycaemia and islets isolated from type 2 diabetics compared to INS-1E cells cultured at normal glucose levels and control islets, respectively. Several glucose-regulated proteins were found when type 2 diabetes and control islets or mitochondria from INS-1E cells cultured at different glucose concentrations were protein profiled. Glucose induced lipid <i>de novo</i> synthesis of both saturated and unsaturated fatty acids in specific proportions. Glucose-induced impairment of function and mass was reverted by inclusion of AICAR, which lowered levels of pro-apoptotic protein CHOP but left triglyceride content unaffected.</p><p><b>Conclusions:</b> Impaired GSIS and increased apoptosis observed in β-cells after prolonged exposure to elevated glucose concentrations involved accumulation of lipid species in specific proportions, AMPK-inactivation, ER-stress activation and complex, coordinated changes in expression patterns of mitochondrial and human islet proteins.</p>

<b>Background and aims:</b> Type 2 diabetes mellitus is connected with elevated glucose levels, which cause impaired glucose-stimulated insulin secretion (GSIS) and degeneration of β-cells. Mechanisms for such glucotoxic effects were explored in the present study. <b>Materials and methods:</b> INS-1E cells were cultured for 5 days in 5.5, 11, 20 or 27 mM glucose in the presence or absence of AMPK-agonist AICAR. GSIS was determined from INS-1E cells and islets obtained from type 2 diabetes and control donors. Human islets and INS-1E cells were functionally characterized (GSIS) and protein profiled (SELDI-TOF MS). Glucose-induced de novo synthesis of fatty acyls (HR-MAS NMR spectroscopy), fatty acid composition (GC-MS), triglyceride content and specific proteins (Western blotting) were determined in INS-1E cells. <b>Results:</b> Impaired GSIS was observed from INS-1E cells exposed to chronic hyperglycaemia and islets isolated from type 2 diabetics compared to INS-1E cells cultured at normal glucose levels and control islets, respectively. Several glucose-regulated proteins were found when type 2 diabetes and control islets or mitochondria from INS-1E cells cultured at different glucose concentrations were protein profiled. Glucose induced lipid de novo synthesis of both saturated and unsaturated fatty acids in specific proportions. Glucose-induced impairment of function and mass was reverted by inclusion of AICAR, which lowered levels of pro-apoptotic protein CHOP but left triglyceride content unaffected. <b>Conclusions:</b> Impaired GSIS and increased apoptosis observed in β-cells after prolonged exposure to elevated glucose concentrations involved accumulation of lipid species in specific proportions, AMPK-inactivation, ER-stress activation and complex, coordinated changes in expression patterns of mitochondrial and human islet proteins.

表面增強雷射脫附遊離/飛行時間質譜(SELDI-TOF-MS)是種屬於高維度的蛋白質質譜儀資料，主要是用來偵測蛋白質分子的表現。由於SELDI技術的限制，導致掃描出來的質譜儀資料往往存在誤差與雜訊，因此在分析前通常會先針對原始資料進行低階的事前處理，步驟包括去除基線、正規化、峰偵測(peak detection)與峰調準(peak alignment)。本文中所探討前列腺癌資料，可分成正常、良性腫瘤、癌症初期與癌症末期四種類別。我們分析及比較兩筆事前處理的蛋白質質譜資料，包括我們自行處理的以及Adam等人所處理的資料。為了解決SELDI在偵測分子質量時常出現的位移誤差以及同位素的問題，我們提出以”質荷比段落”當作新的特徵變數的想法來進行分析。本文利用「ROC曲線下面積」(AUC)當作選取的準則來挑選出重要的質荷比段落，而分類方法則採用支援向量機(SVM)。在四分類的分類結果中，我們自行處理的事前處理資可以得到訓練資料89%及測試資料63 %的正確率。而Adam等人所處理的事前處理資料，則得到訓練資料94%及測試資料86 %的正確率。本研究結果指出不同事前處理的方法對分類結果確實有影響，同時也驗證了利用”特徵變數段落”的方法來進行分析的可行性。 / The surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) is a technique for presenting the expression of molecular masses. It is obvious that every spectrum has a huge dimension of features. In order to analyze these types of spectra samples, preprocessing steps are necessary. The steps of preprocessing include baseline subtraction, normalization, peak detection, and alignment. In our study, we use a prostate cancer data for demonstration. This prostate cancer data can be classified into four categories, namely, healthy men, benign prostate hyperplasia, early stage prostate cancer, and late stage prostate cancer. We analyzed both the preprocessed data processed by ourselves and the preprocessed data done by Adam et al.. In this thesis, we use segmentations of features as “new features” in attempt to solve problems due to location shifts and isotopes. The selection of important segmentations was based on the values of AUC and the SVM was applied for classification. For four-class classification, 94 % and 86 % of accuracy were obtained for training samples and validation samples, respectively, by using Dr. Adam et al.’s preprocessed data, and 89% for training samples, and 63% for validation samples by using our preprocessed data. This study suggested that the preprocessed method does have effect on classification result and a reasonable classification result can be obtained by using segmentations of features.

藉由「早期發現，早期治療」的方式，我們可以降低癌症的死亡率。因此找出與癌症病變有關的生物標記以期及早發現與治療是一項重要的工作。本研究分析了包含正常人以及攝護腺癌症病人實際的蛋白質質譜資料，而這些蛋白質質譜資料是來自於表面強化雷射解吸電離飛行質譜技術（SELDI-TOF MS）的蛋白質晶片實驗。表面增強雷射脫附遊離飛行時間質譜技術可有效地留存生物樣本的蛋白質特徵。如果沒有經過適當的事前處理步驟以消除實驗雜訊，ㄧ 個質譜中可能包含多於數百或數千的特徵變數。為了加速對於可能的蛋白質生物標記的搜尋，我們只考慮可以區分癌症病人與正常人的特徵變數。 基因演算法是一種類似生物基因演化的總體最佳化搜尋機制，它可以有效地在高維度空間中去尋找可能的最佳解。本研究中，我們利用仿基因演算法(GAL)進行蛋白質的特徵選取以區分癌症病人與正常人。另外，我們提出兩種兩階段仿基因演算法(TSGAL)，以嘗試改善仿基因演算法的缺點。 / Early detection and diagnosis can effectively reduce the mortality of cancer. The discovery of biomarkers for the early detection and diagnosis of cancer is thus an important task. In this study, a real proteomic spectra data set of prostate cancer patients and normal patients was analyzed. The data were collected from a Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (SELDI-TOF MS) experiment. The SELDI-TOF MS technology captures protein features in a biological sample. Without suitable pre-processing steps to remove experimental noise, a mass spectrum could consists of more than hundreds or thousands of peaks. To narrow down the search for possible protein biomarkers, only those features that can distinguish between cancer and normal patients are selected. Genetic Algorithm (GA) is a global optimization procedure that uses an analogy of the genetic evolution of biological organisms. It’s shown that GA is effective in searching complex high-dimensional space. In this study, we consider GA-Like algorithm (GAL) for feature selection on proteomic spectra data in classifying prostate cancer patients from normal patients. In addition, we propose two types of Two-Stage GAL algorithm (TSGAL) to improve the GAL.