SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity.

MOTIVATION: Simulations of cancer evolution are highly useful to study the effects of selection and mutation rates on cellular fitness. However, most methods are either lattice-based and cannot simulate realistically sized tumours, or they omit spatial constraints and lack the clonal dynamics of real-world tumours. RESULTS: Stochastic model of intra-tumour heterogeneity (SMITH) is an efficient and explainable model of cancer evolution that combines a branching process with a new confinement mechanism limiting clonal growth based on the size of the individual clones as well as the overall tumour population. We demonstrate how confinement is sufficient to induce the rich clonal dynamics observed in spatial models and cancer samples across tumour types, while allowing for a clear geometric interpretation and simulation of 1 billion cells within a few minutes on a desktop PC. AVAILABILITY AND IMPLEMENTATION: SMITH is implemented in C# and freely available at https://bitbucket.org/schwarzlab/smith. For visualizations, we provide the accompanying Python package PyFish at https://bitbucket.org/schwarzlab/pyfish. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity.

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient's disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase's ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.

Electrostatic and bending energies predict staggering and splaying in nonmuscle myosin II minifilaments.

Recent experiments with super-resolution live cell microscopy revealed that nonmuscle myosin II minifilaments are much more dynamic than formerly appreciated, often showing plastic processes such as splitting, concatenation and stacking. Here we combine sequence information, electrostatics and elasticity theory to demonstrate that the parallel staggers at 14.3, 43.2 and 72 nm have a strong tendency to splay their heads away from the minifilament, thus potentially initiating the diverse processes seen in live cells. In contrast, the straight antiparallel stagger with an overlap of 43 nm is very stable and likely initiates minifilament nucleation. Using stochastic dynamics in a newly defined energy landscape, we predict that the optimal parallel staggers between the myosin rods are obtained by a trial-and-error process in which two rods attach and re-attach at different staggers by rolling and zipping motion. The experimentally observed staggers emerge as the configurations with the largest contact times. We find that contact times increase from isoforms C to B to A, that A-B-heterodimers are surprisingly stable and that myosin 18A should incorporate into mixed filaments with a small stagger. Our findings suggest that nonmuscle myosin II minifilaments in the cell are first formed by isoform A and then convert to mixed A-B-filaments, as observed experimentally.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.