Integrating model systems and genomic insights to decipher mechanisms of cancer metastasis

Deciphering metastatic processes is crucial for understanding cancer progression and potential treatment options. Genetic studies of model systems engineered to mimic metastatic disease, including organoids, genetically engineered mice and human cell lines, have had an important role in shaping our understanding of the metastatic cascade and how it can be manipulated. More recently, advances in high-throughput sequencing have enabled human metastases to be studied at single-cell and single-nucleotide resolution, providing insights into metastatic evolution and phenotypes of both cancer cells and immune cells. However, human tissue studies are often correlative and descriptive, whereas experimental models are reductionistic by nature, meaning that individual results should be interpreted with caution. Crucially, these seemingly disparate branches of metastasis research can and should complement each other to strengthen and validate findings. Here we explore the synergies between model systems and sequencing studies and outline key areas that must be explored to improve our understanding of the metastatic process. This Review explores how experimental models of metastasis, such as mouse models and cell cultures, can complement the (multi)omics analysis of human metastasis samples, thereby filling knowledge gaps left by model studies and validating the findings from human sequencing data.