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Master's Dissertation
DOI
10.11606/D.95.2018.tde-14032018-150144
Document
Author
Full name
Ester Risério Matos Bertoldi
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2017
Supervisor
Committee
Reis, Eduardo Moraes Rego (President)
Marie, Suely Kazue Nagahashi
Oikawa, Márcio Katsumi
Title in Portuguese
Modelagem e implementação de banco de dados clínicos e moleculares de pacientes com câncer e seu uso para identificação de marcadores em câncer de pâncreas
Keywords in Portuguese
Banco de dados
Câncer de pâncreas
CaRDIGAn
Ensembl
ICGC
Modelo entidade-relacionamento
NGS
TCGA
Abstract in Portuguese
O adenocarcinoma pancreático (PDAC) é uma neoplasia de difícil diagnóstico precoce e cujo tratamento não tem apresentado avanços expressivos desde a última década. As tecnologias de sequenciamento de nova geração (next generation sequencing - NGS) podem trazer importantes avanços para a busca de novos marcadores para diagnóstico de PDACs, podendo também contribuir para o desenvolvimento de terapias individualizadas. Bancos de dados são ferramentas poderosas para integração, padronização e armazenamento de grandes volumes de informação. O objetivo do presente estudo foi modelar e implementar um banco de dados relacional (CaRDIGAn - Cancer Relational Database for Integration and Genomic Analysis) que integra dados disponíveis publicamente, provenientes de experimentos de NGS de amostras de diferentes tipos histopatológicos de PDAC, com dados gerados por nosso grupo no IQ-USP, facilitando a comparação entre os mesmos. A funcionalidade do CaRDIGAn foi demonstrada através da recuperação de dados clínicos e dados de expressão gênica de pacientes a partir de listas de genes candidatos, associados com mutação no oncogene KRAS ou diferencialmente expressos em tumores identificados em dados de RNAseq gerados em nosso grupo. Os dados recuperados foram utilizados para a análise de curvas de sobrevida que resultou na identificação de 11 genes com potencial prognóstico no câncer de pâncreas, ilustrando o potencial da ferramenta para facilitar a análise, organização e priorização de novos alvos biomarcadores para o diagnóstico molecular do PDAC.
Title in English
Database design and implementation of clinical and molecular data of cancer patients and its application for biomarker discovery in pancreatic cancer
Keywords in English
Cancer
CaRDIGAn
Database
Database design
Pancreatic ductal adenocarcinoma
Relational database
Abstract in English
Pancreatic Ductal Adenocarcinoma (PDAC) is a type of cancer difficult to diagnose early on and treatment has not improved over the last decade. Next Generation Sequencing (NGS) technology may contribute to discover new biomarkers, develop diagnose strategies and personalised therapy applications. Databases are powerfull tools for data integration, normalization and storage of large data volumes. The main objective of this study was the design and implementation of a relational database to integrate publicly available data of NGS experiments of PDAC pacients with data generated in by our group at IQ-USP, alowing comparisson between both data sources. The database was called CaRDIGAn (Cancer Relational Database for Integration and Genomic Analysis) and its funcionalities were tested by retrieving clinical and expression data of public data of genes differencially expressed genes in our samples or genes associated with KRAS mutation. The output of those queries were used to fit survival curves of patients, which led to the identification of 11 genes potencially usefull for PDAC prognosis. Thus, CaRDIGAn is a tool for data storage and analysis, with promissing applications to identification and priorization of new biomarkers for molecular diagnosis in PDAC.
 
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Publishing Date
2018-04-24
 
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