Mutation divergence over space in tumour expansion

Area of Science:

• Oncology
• Computational Biology
• Genetics

Background:

• Intra-tumour heterogeneity (ITH) arises from mutation accumulation during tumour evolution, frequently causing drug resistance.
• Multi-region sequencing studies highlight mutation divergence and the necessity of spatial sampling for comprehensive tumour analysis.
• Quantitative data linking mutation heterogeneity to tumour expansion modes, sampling distances, and methods remain limited.

Purpose of the Study:

• To investigate how spatial sampling distance and tumour expansion modes influence mutation divergence.
• To quantify the relationship between intra-tumour heterogeneity, sampling strategies, and inferred mutation rates.
• To compare mutation rate inference accuracy across different tumour growth models and sampling sizes.

Main Methods:

• Utilized individual-based simulations to model tumour evolution with varied sampling distances and expansion modes.
• Quantified intra-tumour heterogeneity using the Jaccard index between simulated samples.
• Analyzed variant allele frequency distributions to infer mutation rates under different simulation parameters.

Main Results:

• Intra-tumour heterogeneity increases with sampling distance, irrespective of sampling methods or sizes.
• Mutation rates can be inferred in exponentially expanding tumours, but accuracy decreases with smaller sample sizes.
• Inference of mutation rates becomes unreliable in slow-growing tumours, such as those exhibiting surface growth.

Conclusions:

• Spatial sampling distance is a critical factor influencing intra-tumour heterogeneity.
• Accurate mutation rate inference is dependent on tumour expansion dynamics and adequate sampling size.
• Simulation models provide valuable insights into the complex interplay of factors driving tumour evolution and heterogeneity.