SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection

Area of Science:

• Computational Biology
• Cancer Research
• Genomics

Background:

• Existing cancer simulation frameworks often use simplified models like neutral coalescent or basic birth-death processes.
• These models may not fully capture the complexities of somatic clonal selection and genomic alterations driving tumor evolution.

Purpose of the Study:

• To introduce SISTEM, a novel software package and mathematical framework for simulating tumor evolution and cell migration.
• To provide a high-resolution, agent-based simulation tool that incorporates somatic clonal selection and diverse genomic events.

Main Methods:

• SISTEM utilizes an agent-based modeling approach to simulate individual cancer cells.
• It incorporates customizable mutation and selection models, including single nucleotide variants, segmental aberrations, and whole-genome duplications.
• The framework supports various migration models to simulate metastatic processes.

Main Results:

• SISTEM generates realistic mutation profiles, read counts, and DNA sequencing reads.
• It provides ground truth data for cell lineages and migration graphs.
• The software allows for the simulation of complex tumor evolution driven by genomic instability and selection pressures.

Conclusions:

• SISTEM offers a powerful and flexible platform for simulating tumor evolution and metastasis at single-cell resolution.
• It enables researchers to explore the impact of various genomic events and migration patterns on cancer progression.
• This tool facilitates the evaluation of diverse mutation and selection models in a realistic computational environment.