DeCiFering the elusive cancer cell fraction in tumor heterogeneity and evolution
| Autor: | Simone Zaccaria, Mohammed El-Kebir, Benjamin J. Raphael, Gryte Satas |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Histology Phylogenetic tree viruses Cell Biology Computational biology Sequence Analysis DNA Biology Tumor heterogeneity Polymorphism Single Nucleotide DNA sequencing Pathology and Forensic Medicine Neoplasms Cancer cell Mutation (genetic algorithm) Humans Fraction (mathematics) Copy number aberration Estimation methods Algorithms Phylogeny |
| Zdroj: | Cell systems. 12(10) |
| ISSN: | 2405-4720 |
| Popis: | Summary The cancer cell fraction (CCF), or proportion of cancerous cells in a tumor containing a single-nucleotide variant (SNV), is a fundamental statistic used to quantify tumor heterogeneity and evolution. Existing CCF estimation methods from bulk DNA sequencing data assume that every cell with an SNV contains the same number of copies of the SNV. This assumption is unrealistic in tumors with copy-number aberrations that alter SNV multiplicities. Furthermore, the CCF does not account for SNV losses due to copy-number aberrations, confounding downstream phylogenetic analyses. We introduce DeCiFer, an algorithm that overcomes these limitations by clustering SNVs using a novel statistic, the descendant cell fraction (DCF). The DCF quantifies both the prevalence of an SNV at the present time and its past evolutionary history using an evolutionary model that allows mutation losses. We show that DeCiFer yields more parsimonious reconstructions of tumor evolution than previously reported for 49 prostate cancer samples. |
| Databáze: | OpenAIRE |
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