Quantification of spatial subclonal interactions enhancing the invasive phenotype of pediatric glioma.

CP: Cancer DIPG cancer computational cooperation heterogeneity interactions mathematical pediatric subclonal

Journal

Cell reports
ISSN: 2211-1247
Titre abrégé: Cell Rep
Pays: United States
ID NLM: 101573691

Informations de publication

Date de publication:
30 08 2022
Historique:
received: 06 09 2021
revised: 21 03 2022
accepted: 08 08 2022
entrez: 31 8 2022
pubmed: 1 9 2022
medline: 9 9 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 36044867
pii: S2211-1247(22)01103-2
doi: 10.1016/j.celrep.2022.111283
pmc: PMC9449134
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

111283

Subventions

Organisme : Wellcome Trust
ID : 105104/Z/14/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 202778/B/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A23536
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 13982
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22909
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : U54 CA217376
Pays : United States

Informations de copyright

Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

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Auteurs

Haider 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.

Ketty Kessler (K)

Glioma Team, The Institute of Cancer Research, London, UK.

Nick Trahearn (N)

Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.

Benjamin Werner (B)

Barts Cancer Institute, Queen Mary University of London, London, UK.

Maria Vinci (M)

Department of Haematology/Oncology, Cell and Gene Therapy, Bambino Gesù Children's Hospital-IRCCS, Rome, Italy.

Chris Jones (C)

Glioma Team, The Institute of Cancer Research, London, UK. Electronic address: chris.jones@icr.ac.uk.

Andrea 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.

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