Priscila Ferreira Aquino

Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from http://patternlabforproteomics.org.

a Time-Based and intratumoral Proteomic assessment of a recurrent glioblastoma Multiforme

Tumors consist of cells in different stages of transformation with molecular and cellular heterogeneity. By far, heterogeneity is the hallmark of glioblastoma multiforme (GBM), the most malignant and aggressive type of glioma. Most proteomic studies aim in comparing tumors from different patients, but here we dive into exploring the intratumoral proteome diversity of a single GBM. For this, we profiled tumor fragments from the profound region of the same patient’s GBM but obtained from two surgeries a year’s time apart. Our analysis also included GBM‘s fragments from different anatomical regions. Our quantitative proteomic strategy employed 4-plex iTRAQ peptide labeling followed by a four-step strong cation chromatographic separation; each fraction was then analyzed by reversed-phase nano-chromatography coupled on-line with an Orbitrap-Velos mass spectrometer. Unsupervised clustering grouped the proteomic profiles into four major distinct groups and showed that most changes were related to the tumor’s anatomical region. Nevertheless, we report differentially abundant proteins from GBM’s fragments of the same region but obtained 1 year apart. We discuss several key proteins (e.g., S100A9) and enriched pathways linked with GBM such as the Ras pathway, RHO GTPases activate PKNs, and those related to apoptosis, to name a few. As far as we know, this is the only report that compares GBM fragments proteomic profiles from the same patient. Ultimately, our results fuel the forefront of scientific discussion on the importance in exploring the richness of subproteomes within a single tissue sample for a better understanding of the disease, as each tumor is unique.

Proteome Analysis of Formalin-Fixed Paraffin-Embedded Tissues from a Primary Gastric Melanoma and its Meningeal Metastasis: A Case Report

Melanoma is the third most common brain metastasis cause in the United States as it has a relatively high susceptibility to metastasize to the central nervous system. Among the different origins for brain metastasis, those originating from primary gastric melanomas are extremely rare. Here, we compare protein profiles obtained from formalin-fixed paraffin- embedded (FFPE) tissues of a primary gastric melanoma with its meningeal metastasis. For this, the contents of a microscope slide were scraped and ultimately analyzed by nano-chromatography coupled online with tandem mass spectrometry using an Orbitrap XL. Our results disclose 184 proteins uniquely identified in the primary gastric melanoma, 304 in the meningeal metastasis, and 177 in common. Notably, we identified several enzymes related to changes in the metabolism that are linked to producing energy by elevated rates of glycolysis in a process called the Warburg effect. Moreover, we show that our FFPE proteomic approach allowed identification of key biological markers such as the S100 protein that we further validated by immunohistochemistry for both, the primary and metastatic tumor samples. That said, we demonstrated a powerful strategy to retrospectively mine data for aiding in the understanding of metastasis, biomarker discovery, and ultimately, diseases. To our knowledge, these results disclose for the first time a comparison of the proteomic profiles of gastric melanoma and its corresponding meningeal metastasis.

Proteomic assessment of colorectal cancers and respective resection margins from patients of the Amazon state of Brazil

Colorectal cancer (CRC) is the third most common type of cancer in the world with a low survival rate and therapeutic efficiency. Tumor surgery implies the removal of an apparently non-tumorous tissue around the tumor in an attempt to reduce recurrence chances; this tissue is referred to as the resection margin. Our analysis employed an 8-plex iTRAQ to label four adenocarcinoma biopsies and their corresponding resection margins at 5cm; our results disclose fifty-six proteins as being differentially abundant. These proteins are mainly involved in energetic metabolism (e.g. S100 calcium binding protein A11), cell migration (e.g. transgelin), formation of the cytoskeleton (e.g. profilin 1) and degradation of extracellular matrix (e.g. carbonic anhydrase 2). A gene ontology enrichment analysis revealed several proteins related to adhesion, invasion, metastasis, death, and recognition cell. Taken together, our results highlight proteins related to invasion, cell proliferation, and linked to the metastasis of colorectal cancer in tumor tissue. Finally, we argue that the expression patterns revealed in our comparison helps shed light on the development of more effective surgical strategies and add to the comprehension of this disease. BIOLOGICAL SIGNIFICANCE Colorectal cancer (CRC) is the third most common type of cancer in the world with a low survival rate and therapeutic efficiency. Tumor surgery implies the removal of an apparently non-tumorous tissue around the tumor in an attempt to reduce recurrence chances; this tissue is also referred to as the resection margin. In this regard, resection margins pose as a treasure trove for investigating the molecular characteristics of the tumorigenesis process. While most studies focus on comparing cancer versus control tissue, this study contrasts the proteomic profiles of colorectal cancer biopsies with their corresponding resection margin at 5cm apart. Our analysis employed an 8-plex iTRAQ labeling and a 4-step offline MudPIT online with a Velos. A gene ontology enrichment analysis revealed several proteins related to adhesion, invasion, metastasis, death, and recognition cell.

DiagnoProt: a tool for discovery of new molecules by mass spectrometry

Motivation: Around 75% of all mass spectra remain unidentified by widely adopted proteomic strategies. We present DiagnoProt, an integrated computational environment that can efficiently cluster millions of spectra and use machine learning to shortlist high‐quality unidentified mass spectra that are discriminative of different biological conditions. Results: We exemplify the use of DiagnoProt by shortlisting 4366 high‐quality unidentified tandem mass spectra that are discriminative of different types of the Aspergillus fungus. Availability and Implementation: DiagnoProt, a demonstration video and a user tutorial are available at http://patternlabforproteomics.org/diagnoprot. Contact: andrerfsilva@gmail.com or paulo@pcarvalho.com Supplementary information: Supplementary data are available at Bioinformatics online.

Considerations about gastric cancer proteomics.

The frequency of molecular studies aimed to analyze promoter methylation of tumor suppressor genes and global proteomics in gastric carcinogenesis is increasing. Nonetheless, only a few considered the different types of stomach cells, the tumor location and the influence of Helicobacter pylori and Epstein Barr virus infection (EBV). Molecular differences relating to anatomical and histological tumor areas were also recently described. The authors propose a molecular classification of gastric cancer, dividing it into four subtypes: tumors positive for EBV; microsatellite unstable tumors; genomically stable tumors and tumors with chromosomal instability. RESUMO A frequência de estudos moleculares visando a analisar os promotores de metilação de genes supressores de tumor e proteômica globais na carcinogênese gástrica está aumentando. No entanto, apenas alguns consideraram os diferentes tipos de células do estômago, a localização do tumor e a influência da infecção por Helicobacter pylori e pelo vírus Epstein-Barr (EBV). Diferenças moleculares relacionadas com áreas tumorais anatômicas e histológicas também foram recentemente descritas. Os autores propõem uma classificação molecular de câncer gástrico, dividindo-o em quatro subtipos: tumores positivos para o EBV; tumores microssatélite instáveis; tumores genomicamente estáveis ​​e tumores com instabilidade cromossômica.

Abstract 389: Epigenetic and proteomic analysis of gastric tumor and its histologically free proximal and distal margins

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Introduction: Gastric cancer (GC) corresponds to the fourth most common malignancy among men and sixth among women in Brazil. GC is a multifactorial disease that results from individual genetic predisposition and exposure to ambient factors such as diet, alcohol consumption, smoking, chronic Helicobacter pylori infection or Epstein-Barr virus (EBV). H. pylori and EBV are known to up-regulate DNA methyltransferases. Aim: Compare the promoter methylation profiles of E-cadherin, p16, DAPK, and Rb genes of histologically tumor free proximal and distal margins from fresh tissues and perform a quantitative proteomic comparison of the tumor, distal and proximal resection margins profiles from the same patient. Methods: 18 samples consisting of six gastric carcinomas, their corresponding proximal margins (PM), and distal margins (DM) were obtained from six patients subjected to gastric resection at the Federal University of Rio de Janeiro, Brazil. DNA was extracted from the fresh tissues by using proteinase K digestion and Phenol-chloroform isoamilic alcohol followed by ethanol precipitation. Methylation-specific PCR analysis was used to determine the methylation status of E-cadherin, p16, DAPK, and Rb genes promoter by bisulfite modification. The presence of EBV was investigated by PCR and a shotgun proteomic analysis of all tissues from the H pilory and EBV negative patient was performed using an Orbitrap Velos. Results: 3 of 6 patients were positive for EBV viz: 3 tumors plus 6 margins. The total methylation for the 4 genes in all 9 samples (p16, E-cadherin, DAPK, and Rb genes) were: 5/36 in PM (esophagus); 5/36 in tumor, and 9/36 for DM (intestinal); in the negative EBV samples: 6/36 in PM; 4/36 in tumor and 8/36 in the DM. The proteomic analysis disclosed 786 proteins identified in the tumor fragment (58 proteins uniquely identified in this tissue), 777 to histologically normal proximal margin (87 unique proteins) and 750 to histologically normal distal margin (132 unique proteins). In all three fragments analyzed, unique proteins related to tumor progression or metastasis were identified; examples are: hepatoma- derived growth (HDGF) in the tumor, Annexin 1A in the PM and Mucin 1 in the DM. Conclusion: Our results show that histologically free tumor margins are molecularly compromised by methylation and by up regulation of proteins correlated to tumor progression and metastasis even in samples not infected with EBV or H.pylori Financial support CNPq Citation Format: Paulo Costa Carvalho, Carlos Eduardo Carvalho, Guilherme Pinto Bravo Neto, Juliana Fischer Carvalho, Thais Mac Cormick, Priscila F. Aquino, Marcelo Mota Silva, Maria da Gloria da Costa Carvalho. Epigenetic and proteomic analysis of gastric tumor and its histologically free proximal and distal margins. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 389. doi:10.1158/1538-7445.AM2014-389