Oncology · 2 h ago
Review surveys methods for reconstructing tumour evolution from single cells
This review examines statistical and computational approaches for reconstructing tumour phylogenies from single-cell sequencing data. It discusses modelling assumptions, recent algorithmic developments and potential applications in cancer research and clinical oncology; no new patient cohort or clinical trial is reported.
- Reviews models for single-cell tumour phylogeny reconstruction
- Highlights challenges beyond classical phylogenetic methods
- Discusses research applications and future directions
Single-cell sequencing can reveal somatic evolution and genomic heterogeneity within tumours. This review surveys methods for using such data to reconstruct tumour phylogenies, which represent the evolutionary relationships among cancer cell populations. The authors describe the models and assumptions used by methods developed specifically for single-cell tumour data, noting that tumour evolution and sequencing characteristics pose challenges not addressed by classical phylogenetic approaches.
The article also reviews computational and algorithmic advances and discusses how phylogenetic inference can inform research into individual cancers and patient cohorts. It outlines outstanding challenges and possible future applications. As a methods-focused review, it reports no new patient sample, comparative clinical endpoint or treatment effect, and the supplied text does not establish a specific change to clinical practice.
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Nature Reviews Cancer: Single-cell tumour phylogenetics ↗This is an automated AI-condensed summary that has not yet been reviewed by an editor. Always consult the full item at the original source.