Pritchard, J. R. | bioRxiv Science

bioRxiv2019

Exploiting the 'survival of the likeliest' to enable evolution-guided drug design

Theoretical treatments of evolutionary dynamics tend to model the probability that a single "resistant" species will arise in a population. However, experimental studies have identified a diversity of mutations that can lead to genetic resistance. By quantitatively predicting mutations that occur across an entire drug target during treatment, we identify and bridge a fundamental gap in drug resistance theory: that nucleotide/codon substitution biases can dictate which resistant variants arise in the clinic. We find that the likeliest mutation can beat the most resistant mutation. This creates a new paradigm in drug resistance that we term "survival of the likeliest". We use epidemiological evidence in leukemia, isogenic experiments, stochastic dynamics, and large-scale simulations to support this theory. In addition, this work has strong implications for drug design because not all resistance liabilities are created equal. In pathogenic populations that exhibit survival of the likeliest, exploiting the least likely evolutionary path can minimize resistance across a population during widespread drug use, even when a vulnerability-free molecule or combination cannot be made. Data and Code Availabilityhttps://github.com/pritchardlabatpsu/SurvivalOfTheLikeliest/

evolutionary biology↗

bioRxiv2019

Evolution of the nonsense-mediated decay (NMD) pathway is associated with decreased cytolytic immune infiltration

BackgroundThe somatic co-evolution of tumors and the cellular immune responses that combat them drives the diversity of immune-tumor interactions. This includes tumor mutations that generate neo-antigenic epitopes that elicit cytotoxic T-cell activity and subsequent pressure to select for genetic loss of antigen presentation. Most studies have focused on how tumor missense mutations can drive tumor immunity, but frameshift mutations have the potential to create far greater antigenic diversity. However, expression of this antigenic diversity is potentially regulated by Nonsense Mediated Decay (NMD) and NMD has been shown to be of variable efficiency in cancers. MethodsUsing TCGA datasets, we derived novel patient-level metrics of NMD burden and interrogated how different mutation and most importantly NMD burdens influence cytolytic activity using machine learning models and survival outcomes. ResultsWe find that NMD is a significant and independent predictor of immune cytolytic activity. Different indications exhibited varying dependence on NMD and mutation burden features. We also observed significant co-alteration of genes in the NMD pathway, with a global increase in NMD efficiency in patients with NMD co-alterations. Finally, NMD burden also stratified patient survival in multivariate regression models. ConclusionsOur work suggests that beyond selecting for mutations that elicit NMD in tumor suppressors, tumor evolution may react to the selective pressure generated by inflammation to globally enhance NMD through coordinated amplification and/or mutation.

cancer biology↗