Germline immunomodulatory expression quantitative trait loci (ieQTLs) associated with immune-related toxicity from checkpoint inhibition.

BACKGROUND: Immune checkpoint inhibition (ICI) has improved clinical outcomes for metastatic melanoma patients; however, 65-80% of patients treated with ICI experience immune-related adverse events (irAEs). Given the plausible link of irAEs with underlying host immunity, we explored whether germline genetic variants controlling the expression of 42 immunomodulatory genes were associated with the risk of irAEs in melanoma patients treated with the single-agent anti-CTLA-4 antibody ipilimumab (IPI). METHODS: We identified 42 immunomodulatory expression quantitative trait loci (ieQTLs) most significantly associated with the expression of 382 immune-related genes. These germline variants were genotyped in IPI-treated melanoma patients, collected as part of a multi-institutional collaboration. We tested the association of ieQTLs with irAEs in a discovery cohort of 95 patients, followed by validation in an additional 97 patients. RESULTS: We found that the alternate allele of rs7036417, a variant linked to increased expression of SYK, was strongly associated with an increased risk of grade 3-4 toxicity [odds ratio (OR) = 7.46; 95% confidence interval (CI) = 2.65-21.03; p = 1.43E-04]. This variant was not associated with response (OR = 0.90; 95% CI = 0.37-2.21; p = 0.82). CONCLUSION: We report that rs7036417 is associated with increased risk of severe irAEs, independent of IPI efficacy. SYK plays an important role in B-cell/T-cell expansion, and increased pSYK has been reported in patients with autoimmune disease. The association between rs7036417 and IPI irAEs in our data suggests a role of SYK overexpression in irAE development. These findings support the hypothesis that inherited variation in immune-related pathways modulates ICI toxicity and suggests SYK as a possible future target for therapies to reduce irAEs.

Analytic approach to the evolutionary effects of genetic exchange.

We present an approximate analytic study of our previously introduced model of evolution including the effects of genetic exchange. This model is motivated by the process of bacterial transformation. We solve for the velocity, the rate of increase of fitness, as a function of the fixed population size, N. We find the velocity increases with ln N, eventually saturating at an N which depends on the strength of the recombination process. The analytical treatment is seen to agree well with direct numerical simulations of our model equations.

Equilibrium state of molecular breeding.

We investigate the equilibrium state of the model of Peng, et al. for molecular breeding. In the model, a population of DNA sequences is successively culled by removing the sequences with the lowest binding affinity to a particular target sequence. The remaining sequences are then amplified to restore the original population size, undergoing some degree of point-substitution of nucleotides in the process. Working in the infinite population size limit, we derive an equation for the equilibrium distribution of binding affinity, here modeled by the number of matches to the target sequence. The equation is then solved approximately in the limit of large sequence length, in the three regimes of strong, intermediate and weak selection. The approximate solutions are verified via comparison to exact numerical results.

Fluctuation-regularized front propagation dynamics in reaction-diffusion systems.

We introduce and study a new class of fronts in finite particle-number reaction-diffusion systems, corresponding to propagating up a reaction-rate gradient. We show that these systems have no traditional mean-field limit, as the nature of the long-time front solution in the stochastic process differs essentially from that obtained by solving the mean-field deterministic reaction-diffusion equations. Instead, one can incorporate some aspects of the fluctuations via introducing a density cutoff. Using this method, we derive analytic expressions for the front velocity dependence on bulk particle density and show self-consistently why this cutoff approach can get the correct leading-order physics.

Recombination dramatically speeds up evolution of finite populations.

We study the role of recombination, in the form of bacterial transformation, in speeding up Darwinian evolution. This is done by adding a new process to a previously studied Markov model of evolution on a smooth fitness landscape; this new process allows alleles to be exchanged with those in the surrounding medium. Our results, both numerical and analytic, indicate that, for a wide range of intermediate population sizes, recombination dramatically speeds up the rate of evolutionary advance.

Front propagation up a reaction rate gradient.

We expand on a previous study of fronts in finite particle number reaction-diffusion systems in the presence of a reaction rate gradient in the direction of motion of the front. We study the system via reaction-diffusion equations, using the expedient of a cutoff in the reaction rate below some critical density to capture the essential role of fluctuations in the system. For large density, the velocity is large, which allows for an approximate analytic treatment. We derive an analytic approximation for the dependence of the front velocity on bulk particle density, showing that the velocity indeed diverges in the infinite density limit. The form in which diffusion is implemented, namely nearest-neighbor hopping on a lattice, is seen to have an essential impact on the nature of the divergence.