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Combined Analysis of SNP Array Data Identifies Novel CNV Candidates and Pathways in Ependymoma and Mesothelioma.

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, research...

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Published in:BioMed Research International Vol. 2015; pp. 1 - 11
Main Authors: Wajnberg, Gabriel, Carvalho, Benilton S., Ferreira, Carlos G., Passetti, Fabio
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Wiley-Blackwell 6/22/2015
Online Access:View this record in EBSCOhost
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      dt: 6/22/2015
      vid: 2015
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        109274658
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        109274658
        10.1155/2015/902419
        109274658
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        atl: Combined Analysis of SNP Array Data Identifies Novel CNV Candidates and Pathways in Ependymoma and Mesothelioma.
      aug:
        au:
          Wajnberg, Gabriel
          Carvalho, Benilton S.
          Ferreira, Carlos G.
          Passetti, Fabio
        affil: Bioinformatics Unit, Clinical Research Coordination, National Cancer Institute of Brazil (INCA), 20231-050 Rio de Janeiro, RJ, Brazil
      sug:
        subj:
          Software Utilization
          Polymorphism, Genetic Evaluation
          Chromosome Aberrations
          DNA
          Mesothelioma, Malignant Physiopathology
          Glioma Physiopathology
          Research Methodology
          Databases, Health
          Sequence Analysis
          Data Collection Methods
          Data Analysis, Statistical Methods
          Descriptive Statistics
          Data Analysis Software
          Algorithms
          Gene Amplification
          Oligonucleotide Array Sequence Analysis
          Human
          Secondary Analysis
          Funding Source
      ab: 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.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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