< Back to previous page
Low immunogenicity of common cancer hot spot mutations resulting in false immunogenic selection signals
Journal Contribution - Journal Article
Cancer is driven by somatic mutations that result in a cellular fitness advantage. This selective advantage is expected to be counterbalanced by the immune system when these driver mutations simultaneously lead to the generation of neoantigens, novel peptides that are presented at the cancer cell membrane via HLA molecules from the MHC complex. The presentability of these peptides is determined by a patient's MHC genotype and it has been suggested that this results in MHC genotype-specific restrictions of the oncogenic mutational landscape. Here, we generated a set of virtual patients, each with an identical and prototypical MHC genotype, and show that the earlier reported HLA affinity differences between observed and unobserved mutations are unrelated to MHC genotype variation. We demonstrate how these differences are secondary to high frequencies of 13 hot spot driver mutations in 6 different genes. Several oncogenic mechanisms were identified that lower the peptides' HLA affinity, including phospho-mimicking substitutions in BRAF, destabilizing tyrosine mutations in TP53 and glycine-rich mutational contexts in the GTP-binding KRAS domain. In line with our earlier findings, our results emphasize that HLA affinity predictions are easily misinterpreted when studying immunogenic selection processes.Author summaryThe diagnosis of a malignant tumor is preceded by a long process of tumor evolution, characterized by the gradual accumulation of driver mutations, genomic alterations that give cancer cells their typical growth advantage. This process is controlled by the immune system and understanding tumor-immune interactions is critical for the development of new anti-cancer therapies. Immune cells mainly respond to neoantigens, small mutated peptides that are presented at the cancer cell membrane by binding to the Major Histocompatibility Complex (MHC). MHC genes are highly variable between individuals and it was recently suggested that an individual's MHC genotype determines cancer susceptibility. In this study we used a computational approach and simulated a set of virtual cancer patients, based on the expected driver mutation frequencies and each with a similar prototypical MHC genotype. Using these simulations, we show that the earlier perceived signals are unrelated to the underlying MHC genotypes, but rather secondary to high frequencies of 13 driver mutations in 6 cancer genes.
Journal: PLOS Genetics
Number of pages: 1