Cargando…

Experimental models and tools to tackle glioblastoma

Glioblastoma multiforme (GBM) is one of the deadliest human cancers. Despite increasing knowledge of the genetic and epigenetic changes that underlie tumour initiation and growth, the prognosis for GBM patients remains dismal. Genome analysis has failed to lead to success in the clinic. Fresh approa...

Descripción completa

Detalles Bibliográficos
Autores principales: Robertson, Faye L., Marqués-Torrejón, Maria-Angeles, Morrison, Gillian M., Pollard, Steven M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists Ltd 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765190/
https://www.ncbi.nlm.nih.gov/pubmed/31519690
http://dx.doi.org/10.1242/dmm.040386
_version_ 1783454517845557248
author Robertson, Faye L.
Marqués-Torrejón, Maria-Angeles
Morrison, Gillian M.
Pollard, Steven M.
author_facet Robertson, Faye L.
Marqués-Torrejón, Maria-Angeles
Morrison, Gillian M.
Pollard, Steven M.
author_sort Robertson, Faye L.
collection PubMed
description Glioblastoma multiforme (GBM) is one of the deadliest human cancers. Despite increasing knowledge of the genetic and epigenetic changes that underlie tumour initiation and growth, the prognosis for GBM patients remains dismal. Genome analysis has failed to lead to success in the clinic. Fresh approaches are needed that can stimulate new discoveries across all levels: cell-intrinsic mechanisms (transcriptional/epigenetic and metabolic), cell-cell signalling, niche and microenvironment, systemic signals, immune regulation, and tissue-level physical forces. GBMs are inherently extremely challenging: tumour detection occurs too late, and cells infiltrate widely, hiding in quiescent states behind the blood-brain barrier. The complexity of the brain tissue also provides varied and complex microenvironments that direct cancer cell fates. Phenotypic heterogeneity is therefore superimposed onto pervasive genetic heterogeneity. Despite this bleak outlook, there are reasons for optimism. A myriad of complementary, and increasingly sophisticated, experimental approaches can now be used across the research pipeline, from simple reductionist models devised to delineate molecular and cellular mechanisms, to complex animal models required for preclinical testing of new therapeutic approaches. No single model can cover the breadth of unresolved questions. This Review therefore aims to guide investigators in choosing the right model for their question. We also discuss the recent convergence of two key technologies: human stem cell and cancer stem cell culture, as well as CRISPR/Cas tools for precise genome manipulations. New functional genetic approaches in tailored models will likely fuel new discoveries, new target identification and new therapeutic strategies to tackle GBM.
format Online
Article
Text
id pubmed-6765190
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher The Company of Biologists Ltd
record_format MEDLINE/PubMed
spelling pubmed-67651902019-10-03 Experimental models and tools to tackle glioblastoma Robertson, Faye L. Marqués-Torrejón, Maria-Angeles Morrison, Gillian M. Pollard, Steven M. Dis Model Mech Review Glioblastoma multiforme (GBM) is one of the deadliest human cancers. Despite increasing knowledge of the genetic and epigenetic changes that underlie tumour initiation and growth, the prognosis for GBM patients remains dismal. Genome analysis has failed to lead to success in the clinic. Fresh approaches are needed that can stimulate new discoveries across all levels: cell-intrinsic mechanisms (transcriptional/epigenetic and metabolic), cell-cell signalling, niche and microenvironment, systemic signals, immune regulation, and tissue-level physical forces. GBMs are inherently extremely challenging: tumour detection occurs too late, and cells infiltrate widely, hiding in quiescent states behind the blood-brain barrier. The complexity of the brain tissue also provides varied and complex microenvironments that direct cancer cell fates. Phenotypic heterogeneity is therefore superimposed onto pervasive genetic heterogeneity. Despite this bleak outlook, there are reasons for optimism. A myriad of complementary, and increasingly sophisticated, experimental approaches can now be used across the research pipeline, from simple reductionist models devised to delineate molecular and cellular mechanisms, to complex animal models required for preclinical testing of new therapeutic approaches. No single model can cover the breadth of unresolved questions. This Review therefore aims to guide investigators in choosing the right model for their question. We also discuss the recent convergence of two key technologies: human stem cell and cancer stem cell culture, as well as CRISPR/Cas tools for precise genome manipulations. New functional genetic approaches in tailored models will likely fuel new discoveries, new target identification and new therapeutic strategies to tackle GBM. The Company of Biologists Ltd 2019-09-01 2019-09-06 /pmc/articles/PMC6765190/ /pubmed/31519690 http://dx.doi.org/10.1242/dmm.040386 Text en © 2019. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by/4.0This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Review
Robertson, Faye L.
Marqués-Torrejón, Maria-Angeles
Morrison, Gillian M.
Pollard, Steven M.
Experimental models and tools to tackle glioblastoma
title Experimental models and tools to tackle glioblastoma
title_full Experimental models and tools to tackle glioblastoma
title_fullStr Experimental models and tools to tackle glioblastoma
title_full_unstemmed Experimental models and tools to tackle glioblastoma
title_short Experimental models and tools to tackle glioblastoma
title_sort experimental models and tools to tackle glioblastoma
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765190/
https://www.ncbi.nlm.nih.gov/pubmed/31519690
http://dx.doi.org/10.1242/dmm.040386
work_keys_str_mv AT robertsonfayel experimentalmodelsandtoolstotackleglioblastoma
AT marquestorrejonmariaangeles experimentalmodelsandtoolstotackleglioblastoma
AT morrisongillianm experimentalmodelsandtoolstotackleglioblastoma
AT pollardstevenm experimentalmodelsandtoolstotackleglioblastoma