Abstract
Genomic heterogeneity in tumors results from mutations and selection of high-fitness single cells, the operational components of evolution. Precise knowledge about mutational heterogeneity and evolutionary trajectory of a tumor can provide useful insights into predicting cancer progression and designing personalized treatment. The rapidly advancing field of single-cell genomics provides an opportunity to study tumor heterogeneity and evolution at the ultimate level of resolution. In this review, we present an overview of the state-of-the-art single-cell DNA sequencing methods, technical errors that are inherent in the resulting large-scale datasets, and computational methods to overcome these errors. Finally, we discuss the computational and mathematical approaches for understanding intratumor heterogeneity and cancer evolution at the resolution of a single cell.
Original language | English (US) |
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Article number | 1865 |
Journal | Current Opinion in Systems Biology |
Volume | 7 |
DOIs | |
State | Published - Feb 1 2018 |
Keywords
- DNA sequencing
- Genomics
- Intra-tumor heterogeneity
- Phylogenetics
- Single-cell
- Tumor evolution
- Variant detection
ASJC Scopus subject areas
- Modeling and Simulation
- General Biochemistry, Genetics and Molecular Biology
- Drug Discovery
- Computer Science Applications
- Applied Mathematics