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Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models.
Liu, Yuelin; Li, Xuan Cindy; Rashidi Mehrabadi, Farid; Schäffer, Alejandro A; Pratt, Drew; Crawford, David R; Malikic, Salem; Molloy, Erin K; Gopalan, Vishaka; Mount, Stephen M; Ruppin, Eytan; Aldape, Kenneth D; Sahinalp, S Cenk.
Afiliação
  • Liu Y; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Li XC; Department of Computer Science, University of Maryland, College Park, Maryland 20742, USA.
  • Rashidi Mehrabadi F; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA.
  • Schäffer AA; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Pratt D; Program in Computational Biology, Bioinformatics, and Genomics, University of Maryland, College Park, Maryland 20742, USA.
  • Crawford DR; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Malikic S; Department of Computer Science, Indiana University, Bloomington, Indiana 47408, USA.
  • Molloy EK; Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Gopalan V; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Mount SM; Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Ruppin E; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Aldape KD; Program in Computational Biology, Bioinformatics, and Genomics, University of Maryland, College Park, Maryland 20742, USA.
  • Sahinalp SC; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742, USA.
Genome Res ; 33(7): 1089-1100, 2023 07.
Article em En | MEDLINE | ID: mdl-37316351
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metilação de DNA / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Genome Res Assunto da revista: BIOLOGIA MOLECULAR / GENETICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metilação de DNA / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Genome Res Assunto da revista: BIOLOGIA MOLECULAR / GENETICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos