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Aberrant epigenomic alterations that are defined by distinct genomic signatures associated with gliomas: methods and development

Grant number: 15/02844-7
Support type:Scholarships in Brazil - Master
Effective date (Start): August 01, 2015
Effective date (End): April 30, 2016
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Houtan Noushmehr
Grantee:Tiago Chedraoui Silva
Home Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Cancer, which is one of the major causes of mortality worldwide, is a complex disease orchestrated by aberrant genomic and epigenomic changes that can modify gene regulatory circuits and cellular identity. Emerging evidence obtained through high-throughput genomic data deposited within the public TCGA international consortium suggests that one in ten cancer patients would be more accurately classified by molecular taxonomy versus histology. Therefore, we have hypothesized that the establishment of genome-wide maps of the de novo DNA binding motifs localization coupled with differentially methylated regions and gene expression changes might help to characterize and exploit cancer phenotypes at the molecular level. Technological advances and public databases like The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap) have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high resolution. Markedly however, biological information is stored in different formats and there is no current tool to integrate the data, highlighting an urgent need to develop bioinformatic tools and/or computational softwares to overcome this challenge. In this context, the main purpose of this study is to implement the development of biOMICs, a package coded in the GNU GPL (General Public License) R programming language that will be submitted to the larger open-source Bioconductor community project. Our expectation is that biOMICs can effectively automate search, retrieve, and analyze the vast (epi)genomic data currently available from TCGA, ENCODE, and Roadmap, and integrate genomics and epigenomics features with researchers own high-throughput data. Finally, we will also navigate through these data manually in order to validate the capacity of biOMICs in discovering epigenomic signatures able to redefine subtypes of gliomas, one of the most aggressive primary brain cancer. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
COLAPRICO, ANTONIO; SILVA, TIAGO C.; OLSEN, CATHARINA; GAROFANO, LUCIANO; CAVA, CLAUDIA; GAROLINI, DAVIDE; SABEDOT, THAIS S.; MALTA, TATHIANE M.; PAGNOTTA, STEFANO M.; CASTIGLIONI, ISABELLA; CECCARELLI, MICHELE; BONTEMPI, GIANLUCA; NOUSHMEHR, HOUTAN. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Research, v. 44, n. 8 MAY 5 2016. Web of Science Citations: 151.
CECCARELLI, MICHELE; BARTHEL, FLORIS P.; MALTA, TATHIANE M.; SABEDOT, THAIS S.; SALAMA, SOFIE R.; MURRAY, BRADLEY A.; MOROZOVA, OLENA; NEWTON, YULIA; RADENBAUGH, AMIE; PAGNOTTA, STEFANO M.; ANJUM, SAMREEN; WANG, JIGUANG; MANYAM, GANIRAJU; ZOPPOLI, PIETRO; LING, SHIYUN; RAO, ARJUN A.; GRIFFORD, MIA; CHERNIACK, ANDREW D.; ZHANG, HAILEI; POISSON, LAILA; CARLOTTI, JR., CARLOS GILBERTO; TIRAPELLI, DANIELA PRETTI DA CUNHA; RAO, ARVIND; MIKKELSEN, TOM; LAU, CHING C.; YUNG, W. K. ALFRED; RABADAN, RAUL; HUSE, JASON; BRAT, DANIEL J.; LEHMAN, NORMAN L.; BARNHOLTZ-SLOAN, JILL S.; ZHENG, SIYUAN; HESS, KENNETH; RAO, GANESH; MEYERSON, MATTHEW; BEROUKHIM, RAMEEN; COOPER, LEE; AKBANI, REHAN; WRENSCH, MARGARET; HAUSSLER, DAVID; ALDAPE, KENNETH D.; LAIRD, PETER W.; GUTMANN, DAVID H.; NOUSHMEHR, HOUTAN; IAVARONE, ANTONIO; VERHAAK, ROEL G. W.; NETWORK, TCGA RES. Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma. Cell, v. 164, n. 3, p. 550-563, JAN 28 2016. Web of Science Citations: 464.

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