Evidence map›Paper›PMID 37316351›Full record

ArticleGenome research2023

Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models.

Yuelin Liu, Xuan Cindy Li, Farid Rashidi Mehrabadi, Alejandro A Schäffer, Drew Pratt, David R Crawford, Salem Malikić, Erin K Molloy, Vishaka Gopalan, Stephen M Mount and 3 more

Open access · bronzeAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Yuelin Liu *Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0002-1051-7236
Xuan Cindy Li *Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
Farid Rashidi Mehrabadi *Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
Alejandro A SchäfferCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
Drew PrattLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
David R CrawfordCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
Salem MalikićCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0002-4215-5655
Erin K MolloyDepartment of Computer Science, University of Maryland, College Park, Maryland 20742, USA.ORCID 0000-0001-5553-3312
Vishaka GopalanCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0002-5582-3130
Stephen M MountDepartment of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742, USA.
Eytan RuppinCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0002-7862-3940
Kenneth D AldapeLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0001-5119-7550
S Cenk SahinalpCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA; cenk.sahinalp@nih.gov.ORCID 0000-0002-5050-0682
National Institutes of Health · USUniversity of Maryland, College Park · US

Funding

Single-cell DNA methylation analysis of human cancerZIABC011846 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ALDAPE, KENNETH · 2018 to 2025
$8.4M
6 · The paper itself

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.

Indexed as

DNA MethylationNeoplasmsCpG IslandsGenomeHumansSequence Analysis, DNASulfiteshydrogen sulfiteSulfites

Identifiers

PMID37316351
PMCPMC10538489
OpenAlexW4380590382

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.