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Characterizing MHC-I Genotype Predictive Power for Oncogenic Mutation Probability in Cancer Patients.
Beauchemin, Lainie; Slifker, Michael; Rossell, David; Font-Burgada, Joan.
Afiliação
  • Beauchemin L; Cancer Biology Program, Fox Chase Cancer Center, Philadelphia, PA, USA.
  • Slifker M; Cancer Biology Program, Fox Chase Cancer Center, Philadelphia, PA, USA.
  • Rossell D; Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain.
  • Font-Burgada J; Cancer Biology Program, Fox Chase Cancer Center, Philadelphia, PA, USA. joan.font-burgada@fccc.edu.
Methods Mol Biol ; 2131: 185-198, 2020.
Article em En | MEDLINE | ID: mdl-32162254
ABSTRACT
MHC class I proteins present intracellular peptides on the cell's surface, enabling the immune system to recognize tumor-specific neoantigens of early neoplastic cells and eliminate them before the tumor develops further. However, variability in peptide-MHC-I affinity results in variable presentation of oncogenic peptides, leading to variable likelihood of immune evasion across both individuals and mutations. Since the major determinant of peptide-MHC-I affinity in patients is individual MHC-I genotype, we developed a residue-centric presentation score taking both mutated residues and MHC-I genotype into account and hypothesized that high scores (which correspond to poor presentation) would correlate to high mutation frequencies within tumors. We applied our scoring system to 9176 tumor samples from TCGA across 1018 recurrent mutations and found that, indeed, presentation scores predicted mutation probability. These findings open the door to more personalized treatment plans based on simple genotyping. Here, we outline the computational tools and statistical methods used to arrive at this conclusion.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Antígenos de Histocompatibilidade Classe II / Biologia Computacional / Mutação / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Antígenos de Histocompatibilidade Classe II / Biologia Computacional / Mutação / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article