Characterizing MHC-I genotype predictive power for oncogenic mutation probability in cancer patients

Joan Font-Burgada, Lainie Beauchemin, Michael Slifker, David Rossell

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages185-198
Number of pages14
Volume2131
DOIs
StatePublished - 2020

Publication series

NameMethods in molecular biology (Clifton, N.J.)
PublisherHumana Press
ISSN (Print)1064-3745

Keywords

  • Computational Biology/methods
  • Databases, Genetic
  • Exome Sequencing
  • Genetic Predisposition to Disease
  • Genotyping Techniques
  • Histocompatibility Antigens Class II/genetics
  • Humans
  • Likelihood Functions
  • Mutation
  • Mutation Rate
  • Neoplasms/genetics
  • Precision Medicine
  • Tumor Escape

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