1/ We set out to study the landscape of tumours and mutations when immune-associated negative selection drives tumour evolution. We asked what happens in a growing population, where tumour eradication and immune escape are both potential paths.
2/ We used a mathematical model of tumour growth to establish a hallmark of neoantigen-associated selection. The tumours were accumulating neutral and antigenic mutations, and we parametrised immune activity by the selection strength, s.
3/ We found that negative selection led to a decline in the frequency of antigenic mutations during tumour growth - which was visible in the mutation frequency spectrum of the final tumour. Qualitatively, this signal was consistent across a large range of model parameters.
4/ However, we found that negative selection was hard to resolve due to sequencing limitations: the small number of neoantigens captured meant lack of statistical power. This led to a non-linear relationship between selection strength and detected signal.
5/ In addition, hyper-mutated tumours could reach detectable size in only one way: developing immune escape. Therefore in real cancers we face an observation bias: measuring detectable tumours means an enrichment for immune escape.
6/ We then analysed neoantigens and immune escape in >800 cancers from TCGA. We found that the majority of cancers were indeed immune escaped, especially hyper-mutated and highly immune infiltrated ones. The mechanisms of escape were very diverse though.
7/ In cancers with no escape, and medium levels of immune infiltration, we did find the characteristic deviation between the total mutation spectrum and antigenic mutations. No signal in other groups though - like our simulations suggested, negative selection is hard to capture.
8/ Overall, we identified genomic hallmarks of immune selection and explored avenues to evaluate this selection. For more info check out the paper and this blogpost:

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