Jellyfish: integrative visualization of spatio-temporal tumor evolution and clonal dynamics

Area of Science:

• Oncology
• Bioinformatics
• Computational Biology

Background:

• Intra-tumor heterogeneity is a key driver of tumor evolution and therapy resistance.
• Current visualization tools struggle to simultaneously represent spatial and temporal dimensions of tumor heterogeneity.
• Understanding these dynamics is crucial for developing effective cancer treatments.

Purpose of the Study:

• To introduce Jellyfish, a novel visualization tool designed to capture both spatial and temporal aspects of tumor evolution.
• To provide a holistic view of tumor evolutionary processes and subclonal dynamics.
• To facilitate the analysis of complex cancer data.

Main Methods:

• Jellyfish integrates phylogenetic and sample trees into a unified plot.
• The tool generates interactive visualizations from tumor phylogeny and clonal composition data.
• It is available as a JavaScript library and an R package.

Main Results:

• Jellyfish successfully visualizes complex subclonal dynamics.
• The tool provides a comprehensive view of tumor evolution, integrating spatial and temporal data.
• Demonstrated utility using data from ovarian high-grade serous carcinoma.

Conclusions:

• Jellyfish addresses the limitations of existing tools by simultaneously visualizing spatial and temporal tumor evolution.
• This integrated approach offers a powerful method for studying tumor heterogeneity and its implications for therapy resistance.
• The tool enhances our ability to analyze and understand complex cancer evolutionary trajectories.