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Quantification of spatial subclonal interactions enhancing the invasive phenotype of pediatric glioma.
Tari, Haider; Kessler, Ketty; Trahearn, Nick; Werner, Benjamin; Vinci, Maria; Jones, Chris; Sottoriva, Andrea.
Afiliación
  • Tari H; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK; Glioma Team, The Institute of Cancer Research, London, UK.
  • Kessler K; Glioma Team, The Institute of Cancer Research, London, UK.
  • Trahearn N; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
  • Werner B; Barts Cancer Institute, Queen Mary University of London, London, UK.
  • Vinci M; Department of Haematology/Oncology, Cell and Gene Therapy, Bambino Gesù Children's Hospital-IRCCS, Rome, Italy.
  • Jones C; Glioma Team, The Institute of Cancer Research, London, UK. Electronic address: chris.jones@icr.ac.uk.
  • Sottoriva A; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK; Research Centre for Computational Biology, Human Technopole, Milan, Italy. Electronic address: andrea.sottoriva@fht.org.
Cell Rep ; 40(9): 111283, 2022 08 30.
Article en En | MEDLINE | ID: mdl-36044867
ABSTRACT
Diffuse midline gliomas (DMGs) are highly aggressive, incurable childhood brain tumors. They present a clinical challenge due to many factors, including heterogeneity and diffuse infiltration, complicating disease management. Recent studies have described the existence of subclonal populations that may co-operate to drive pro-tumorigenic processes such as cellular invasion. However, a precise quantification of subclonal interactions is lacking, a problem that extends to other cancers. In this study, we combine spatial computational modeling of cellular interactions during invasion with co-evolution experiments of clonally disassembled patient-derived DMG cells. We design a Bayesian inference framework to quantify spatial subclonal interactions between molecular and phenotypically distinct lineages with different patterns of invasion. We show how this approach could discriminate genuine interactions, where one clone enhanced the invasive phenotype of another, from those apparently only due to the complex dynamics of spatially restricted growth. This study provides a framework for the quantification of subclonal interactions in DMG.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Rep Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Glioma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Rep Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido
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