Quantification of multicellular colonization in tumor metastasis using exome-sequencing data

Genetic diversity through social heterosis can increase virulence in RNA viral infections and cancer progression

In viral infections and cancer tumours, negative health outcomes often correlate with increasing genetic diversity. Possible evolutionary processes for such relationships include mutant lineages escaping host control or diversity, per se, creating too many immune system targets. Another possibility is social heterosis where mutations and replicative errors create clonal lineages varying in intrinsic capability for successful dispersal; improved environmental buffering; resource extraction or effective defence against immune systems. Rather than these capabilities existing in one genome, social heterosis proposes complementary synergies occur across lineages in close proximity. Diverse groups overcome host defences as interacting 'social genomes' with group genetic tool kits exceeding limited individual plasticity. To assess the possibility of social heterosis in viral infections and cancer progression, we conducted extensive literature searches for examples consistent with general and specific predictions from the social heterosis hypothesis. Numerous studies found supportive patterns in cancers across multiple tissues and in several families of RNA viruses. In viruses, social heterosis mechanisms probably result from long coevolutionary histories of competition between pathogen and host. Conversely, in cancers, social heterosis is a by-product of recent mutations. Investigating how social genomes arise and function in viral quasi-species swarms and cancer tumours may lead to new therapeutic approaches.

Dataset of tugHall simulations of cell evolution for colorectal cancer

Dataset contains results of multiple parallel calculations using the tugHall simulator. Output data of simulations are variant allele frequencies for four genes (APC, KRAS, TP53, and PIK3CA) related to colorectal cancer. During each simulation tugHall stochastically reproduces Darwinian evolution for cancer cells and calculates clonal heterogeneity. The probabilities of stochastic processes depend on a correspondence matrix between genome information and cancer hallmarks. As a result, tugHall records variant allele frequencies for the final stage of evolution. The number of trials is several million to get rich statistics of stochastic processes. These data can be used for approximate Bayesian computation and other statistical methods to get personalized coefficients for patients with colorectal cancer. The procedure of usage data is explained in our paper [Bioinformatics, 36, 11 (2020) 3597] in which the part of these data was used.