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Kozak Similarity Score Algorithm Identifies Alternative Translation Initiation Codons Implicated in Cancers.
Gleason, Alec C; Ghadge, Ghanashyam; Sonobe, Yoshifumi; Roos, Raymond P.
Afiliação
  • Gleason AC; Department of Neurology, University of Chicago Medical Center, Chicago, IL 60637, USA.
  • Ghadge G; Department of Neurology, University of Chicago Medical Center, Chicago, IL 60637, USA.
  • Sonobe Y; Department of Neurology, University of Chicago Medical Center, Chicago, IL 60637, USA.
  • Roos RP; Department of Neurology, University of Chicago Medical Center, Chicago, IL 60637, USA.
Int J Mol Sci ; 23(18)2022 Sep 12.
Article em En | MEDLINE | ID: mdl-36142475
Ribosome profiling and mass spectroscopy have identified canonical and noncanonical translation initiation codons (TICs) that are upstream of the main translation initiation site and used to translate oncogenic proteins. There have previously been conflicting reports about the patterns of nucleotides that surround noncanonical TICs. Here, we use a Kozak Similarity Score algorithm to find that nearly all of these TICs have flanking nucleotides closely matching the Kozak sequence. Remarkably, the nucleotides flanking alternative noncanonical TICs are frequently closer to the Kozak sequence than the nucleotides flanking TICs used to translate the gene's main protein. Of note, the 5' untranslated region (5'UTR) of cancer-associated genes with an upstream TIC tend to be significantly longer than the same region in genes not associated with cancer. The presence of a longer-than-typical 5'UTR increases the likelihood of ribosome binding to upstream noncanonical TICs, and may be a distinguishing feature of a number of genes overexpressed in cancer. Noncanonical TICs that are located in the 5'UTR, although thought by some to be disadvantageous and suppressed by evolution, may translate oncogenic proteins because of their flanking nucleotides.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Idioma: En Ano de publicação: 2022 Tipo de documento: Article