Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models
- Yuelin Liu1,2,3,9,
- Xuan Cindy Li1,4,9,
- Farid Rashidi Mehrabadi1,5,6,9,
- Alejandro A. Schäffer1,
- Drew Pratt7,
- David R. Crawford1,4,8,
- Salem Malikić1,
- Erin K. Molloy2,3,
- Vishaka Gopalan1,
- Stephen M. Mount8,
- Eytan Ruppin1,
- Kenneth D. Aldape7 and
- S. Cenk Sahinalp1
- 1Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA;
- 2Department of Computer Science, University of Maryland, College Park, Maryland 20742, USA;
- 3Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA;
- 4Program in Computational Biology, Bioinformatics, and Genomics, University of Maryland, College Park, Maryland 20742, USA;
- 5Department of Computer Science, Indiana University, Bloomington, Indiana 47408, USA;
- 6Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA;
- 7Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA;
- 8Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742, USA
-
↵9 These authors contributed equally to this work.
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.
Footnotes
-
[Supplemental material is available for this article.]
-
Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.277608.122.
- Received January 12, 2023.
- Accepted June 6, 2023.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see https://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
