ArticleCommunications biology2022
A phylogenetic approach to study the evolution of somatic mutational processes in cancer.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Bayesian inference of tissue-migration histories in metastatic cancer from cell-lineage tracing data.Cell genomics · 2026Article
- Evolutionary dynamics of early and late mutational signatures in metastatic cancer.Frontiers in bioinformatics · 2026Article
- Inferring active mutational processes in cancer using single cell sequencing and evolutionary constraints.bioRxiv : the preprint server for biology · 2025Article
- GenoPath: a pipeline to infer tumor clone composition, mutational history, and metastatic cell migration events from tumor DNA sequencing data.Frontiers in bioinformatics · 2025Article
- Cell-cell fusion in cancer: The next cancer hallmark?The international journal of biochemistry & cell biology · 2024Review
- Article
- Improving cellular phylogenies through the integrated use of mutation order and optimality principles.Computational and structural biotechnology journal · 2023Article
- Bootstrap confidence for molecular evolutionary estimates from tumor bulk sequencing data.Frontiers in bioinformatics · 2023Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Cancer cell genomes change continuously due to mutations, and mutational processes change over time in patients, leaving dynamic signatures in the accumulated genomic variation in tumors. Many computational methods detect the relative activities of known mutation signatures. However, these methods may produce erroneous signatures when applied to individual branches in cancer cell phylogenies. Here, we show that the inference of branch-specific mutational signatures can be improved through a joint analysis of the collections of mutations mapped on proximal branches of the cancer cell phylogeny. This approach reduces the false-positive discovery rate of branch-specific signatures and can sometimes detect faint signatures. An analysis of empirical data from 61 lung cancer patients supports trends based on computer-simulated datasets for which the correct signatures are known. In lung cancer somatic variation, we detect a decreasing trend of smoking-related mutational processes over time and an increasing influence of APOBEC mutational processes as the tumor evolution progresses. These analyses also reveal patterns of conservation and divergence of mutational processes in cell lineages within patients.
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