Implementation of computational analyses to identify novel biomarkers for molecular diagnosis of pancreatic tumors using next generation sequencing data

• Grant number: 13/13350-0
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Effective date (Start): March 01, 2014
• Effective date (End): February 28, 2018
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Eduardo Moraes Rego Reis
• Grantee: Omar Julio Sosa
• Host Institution: Instituto de Química (IQ). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The application of new massive sequencing technologies (NGS) have a enormous potential to contribute to the identification of somatic and transcriptional alterations present in human neoplasias. Nevertheless, the vast volume and complexity of data generated by these techniques represent an obstacle for the extraction of information with biologic and clinic relevance. This project intend to establish a bioinformatics framework to facilitate the processing, analysis and storage of the genomic data obtained from exome and transcriptome sequencing of clinical samples of pancreatic adenocarcinoma, pre-malignant lesions and non tumor pancreatic tissues, that will be produced in our laboratory. Analytical routines will be implemented for the identification of somatic alterations in the exome (SNPs, indels, CNVs) and transcriptome, including long noncoding RNAs, in pancreatic tissue samples with different degrees of malignancy. Integrated data analysis will allow the identification of genes and functional modules affected during pancreatic adenocarcinoma progression, facilitating the prioritization of candidates for experimental validation as molecular markers for an early diagnosis of the disease or therapeutic targets. (AU)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SOSA, Omar Julio. Identification and functional annotation of novel transcripts with altered expression in pancreatic cancer. 2019. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) São Paulo.