ArticleGenome research2023
Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models.
Article in Genome research, 2023. 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, 10 citations in OpenAlex.
- Long-read sequencing of single cell-derived melanoma sublines reveals divergent and parallel genomic and epigenomic evolutionary trajectories.Nature communications · 2026Article
- Long-read sequencing of single cell-derived melanoma subclones reveals divergent and parallel genomic and epigenomic evolutionary trajectories.bioRxiv : the preprint server for biology · 2025Article
- Fair molecular feature selection unveils universally tumor lineage-informative methylation sites in colorectal cancer.Bioinformatics (Oxford, England) · 2025Article
- Fast tumor phylogeny regression via tree-structured dual dynamic programming.Bioinformatics (Oxford, England) · 2025Article
- Single-cell lineage tracing techniques in hematology: unraveling the cellular narrative.Journal of translational medicine · 2025Review
- High-resolution, noninvasive single-cell lineage tracing in mice and humans based on DNA methylation epimutations.Nature methods · 2025Article
- Stochastic modeling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.Cell systems · 2025Article
- Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
Recent studies exploring the impact of methylation in tumor evolution suggest that although the methylation status of many of the CpG sites are preserved across distinct lineages, others are altered as the cancer progresses. Because changes in methylation status of a CpG site may be retained in mitosis, they could be used to infer the progression history of a tumor via single-cell lineage tree reconstruction. In this work, we introduce the first principled distance-based computational method, Sgootr, for inferring a tumor's single-cell methylation lineage tree and for jointly identifying lineage-informative CpG sites that harbor changes in methylation status that are retained along the lineage. We apply Sgootr on single-cell bisulfite-treated whole-genome sequencing data of multiregionally sampled tumor cells from nine metastatic colorectal cancer patients, as well as multiregionally sampled single-cell reduced-representation bisulfite sequencing data from a glioblastoma patient. We show that the tumor lineages constructed reveal a simple model underlying tumor progression and metastatic seeding. A comparison of Sgootr against alternative approaches shows that Sgootr can construct lineage trees with fewer migration events and with more in concordance with the sequential-progression model of tumor evolution, with a running time a fraction of that used in prior studies. Lineage-informative CpG sites identified by Sgootr are in inter-CpG island (CGI) regions, as opposed to intra-CGIs, which have been the main regions of interest in genomic methylation-related analyses.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.