1 Ocak 2010 Dergi makalesi Açık Erişim

Kavak, Ersen; Unlu, Mustafa; Nister, Monica; Koman, Ahmet

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        "name": "Kavak, Ersen"
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        "affiliation": "Bogazici Univ, Dept Mol Biol & Genet, Istanbul, Turkey", 
        "name": "Unlu, Mustafa"
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      {
        "affiliation": "Karolinska Inst, Dept Oncol Pathol, S-17177 Stockholm, Sweden", 
        "name": "Nister, Monica"
      }, 
      {
        "affiliation": "Bogazici Univ, Dept Mol Biol & Genet, Istanbul, Turkey", 
        "name": "Koman, Ahmet"
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    "description": "Cancer is among the major causes of human death and its mechanism(s) are not fully understood. We applied a novel meta-analysis approach to multiple sets of merged serial analysis of gene expression and microarray cancer data in order to analyze transcriptome alterations in human cancer. Our methodology, which we denote 'COgnate Gene Expression patterNing in tumours' (COGENT), unmasked numerous genes that were differentially expressed in multiple cancers. COGENT detected well-known tumor-associated (TA) genes such as TP53, EGFR and VEGF, as well as many multi-cancer, but not-yet-tumor-associated genes. In addition, we identified 81 co-regulated regions on the human genome (RIDGEs) by using expression data from all cancers. Some RIDGEs (28%) consist of paralog genes while another subset (30%) are specifically dysregulated in tumors but not in normal tissues. Furthermore, a significant number of RIDGEs are associated with GC-rich regions on the genome. All assembled data is freely available online (www.oncoreveal.org) as a tool implementing COGENT analysis of multi-cancer genes and RIDGEs. These findings engender a deeper understanding of cancer biology by demonstrating the existence of a pool of under-studied multi-cancer genes and by highlighting the cancer-specificity of some TA-RIDGEs.", 
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    "journal": {
      "issue": "20", 
      "pages": "7008-7021", 
      "title": "NUCLEIC ACIDS RESEARCH", 
      "volume": "38"
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    "publication_date": "2010-01-01", 
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    "title": "Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation"
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