title: Combined Analysis of SNP Array Data Identifies Novel CNV Candidates and Pathways in Ependymoma and Mesothelioma.
abstract: Copy number variation is a class of structural genomic modifications that includes the gain and loss of a specific genomic region, which may include an entire gene. Many studies have used low-resolution techniques to identify regions that are frequently lost or amplified in cancer. Usually, researchers choose to use proprietary or non-open-source software to detect these regions because the graphical interface tends to be easier to use. In this study, we combined two different open-source packages into an innovative strategy to identify novel copy number variations and pathways associated with cancer. We used a mesothelioma and ependymoma published datasets to assess our tool. We detected previously described and novel copy number variations that are associated with cancer chemotherapy resistance. We also identified altered pathways associated with these diseases, like cell adhesion in patients with mesothelioma and negative regulation of glutamatergic synaptic transmission in ependymoma patients. In conclusion, we present a novel strategy using open-source software to identify copy number variations and altered pathways associated with cancer.
authors.affiliation: Bioinformatics Unit, Clinical Research Coordination, National Cancer Institute of Brazil (INCA), 20231-050 Rio de Janeiro, RJ, Brazil ; Graduate Program in Systems and Computational Biology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), 21040-360 Rio de Janeiro, RJ, Brazil ; Laboratory of Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), 21040-360 Rio de Janeiro, RJ, Brazil.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Wajnberg
authors.affiliation: Department of Medical Genetics, School of Medical Sciences, State University of Campinas, 13083-887 Campinas, SP, Brazil.
authors.forename: Benilton S
authors.initials: BS
authors.lastname: Carvalho
authors.affiliation: Clinical Research Coordination, National Cancer Institute of Brazil (INCA), 20231-050 Rio de Janeiro, RJ, Brazil.
authors.forename: Carlos G
authors.initials: CG
authors.lastname: Ferreira
authors.affiliation: Bioinformatics Unit, Clinical Research Coordination, National Cancer Institute of Brazil (INCA), 20231-050 Rio de Janeiro, RJ, Brazil ; Graduate Program in Systems and Computational Biology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), 21040-360 Rio de Janeiro, RJ, Brazil ; Laboratory of Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), 21040-360 Rio de Janeiro, RJ, Brazil.
authors.forename: Fabio
authors.initials: F
authors.lastname: Passetti
mesh_terms: D001483:Base Sequence; D001932:Brain Neoplasms / Q000235:genetics*; D056915:DNA Copy Number Variations / Q000235:genetics*; D004252:DNA Mutational Analysis / Q000379:methods; D004806:Ependymoma / Q000235:genetics*; D006801:Humans; D008654:Mesothelioma / Q000235:genetics*; D008969:Molecular Sequence Data; D009154:Mutation / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015398:Signal Transduction / Q000235:genetics*