CancerTracer: a curated database for intrapatient tumor heterogeneity

Area of Science:

• Genomics
• Cancer Research
• Bioinformatics

Background:

• Intrapatient cancer heterogeneity contributes to drug resistance and treatment failure.
• Understanding tumor evolution is crucial for identifying therapeutic targets.

Purpose of the Study:

• To present CancerTracer, a manually curated database for tracking tumor evolutionary trajectories.
• To characterize tumor growth and heterogeneity in individual patients across various cancer types.

Main Methods:

• Collected over 6000 tumor samples from 1548 patients across 45 cancer types.
• Constructed patient-specific tumor phylogenetic trees using somatic mutations and copy number alterations from multi-region biopsies.
• Utilized multi-region and single-cell sequencing data to capture intratumor heterogeneity.

Main Results:

• CancerTracer enables identification of common and heterogeneous driver events within tumors.
• The database facilitates investigation of phylogenetic relationships between primary and metastatic tumors.
• Structured heterogeneity data provides insights into tumor evolutionary histories.

Conclusions:

• CancerTracer is a valuable resource for studying cancer evolution and intratumor heterogeneity.
• The database can potentially accelerate the identification of predictive biomarkers for personalized cancer therapies.