Hypoxic Environment and Paired Hierarchical 3D and 2D Models of Pediatric
hypoxia
intra-tumor heterogeneity
models
pediatric high-grade glioma
tumor and cell metabolism
Journal
Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829
Informations de publication
Date de publication:
26 Nov 2019
26 Nov 2019
Historique:
received:
16
09
2019
revised:
07
11
2019
accepted:
15
11
2019
entrez:
30
11
2019
pubmed:
30
11
2019
medline:
30
11
2019
Statut:
epublish
Résumé
Pediatric high-grade gliomas (pHGGs) are facing a very dismal prognosis and representative pre-clinical models are needed for new treatment strategies. Here, we examined the relevance of collecting functional, genomic, and metabolomics data to validate patient-derived models in a hypoxic microenvironment. From our biobank of pediatric brain tumor-derived models, we selected 11 pHGGs driven by the histone The concurrent 2D and 3D cultures generated from the same tumor sample exhibited divergent but complementary features, recreating the patient intra-tumor complexity. Genomic and metabolomic data described the metabolic changes during pHGG progression and supported hypoxia as an important key to preserve the tumor metabolism in vitro and cell dissemination present in patients. The neurosphere features preserved tumor development and sensitivity to treatment. We proposed a novel multistep work for the development and validation of patient-derived models, considering the immature and differentiated content and the tumor microenvironment of pHGGs.
Sections du résumé
BACKGROUND
BACKGROUND
Pediatric high-grade gliomas (pHGGs) are facing a very dismal prognosis and representative pre-clinical models are needed for new treatment strategies. Here, we examined the relevance of collecting functional, genomic, and metabolomics data to validate patient-derived models in a hypoxic microenvironment.
METHODS
METHODS
From our biobank of pediatric brain tumor-derived models, we selected 11 pHGGs driven by the histone
RESULTS
RESULTS
The concurrent 2D and 3D cultures generated from the same tumor sample exhibited divergent but complementary features, recreating the patient intra-tumor complexity. Genomic and metabolomic data described the metabolic changes during pHGG progression and supported hypoxia as an important key to preserve the tumor metabolism in vitro and cell dissemination present in patients. The neurosphere features preserved tumor development and sensitivity to treatment.
CONCLUSION
CONCLUSIONS
We proposed a novel multistep work for the development and validation of patient-derived models, considering the immature and differentiated content and the tumor microenvironment of pHGGs.
Identifiants
pubmed: 31779235
pii: cancers11121875
doi: 10.3390/cancers11121875
pmc: PMC6966513
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Cancer Research UK
ID : 13982
Pays : United Kingdom
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
Références
Oncotarget. 2016 Apr 12;7(15):20486-95
pubmed: 26967252
BMC Cancer. 2017 Dec 29;17(1):905
pubmed: 29284440
Int J Cancer. 2016 Apr 1;138(7):1709-18
pubmed: 26519239
J Cell Mol Med. 2011 Jun;15(6):1239-53
pubmed: 21251211
Cancer. 2008 Oct 1;113(7 Suppl):1953-68
pubmed: 18798534
Genome Biol. 2010;11(10):R106
pubmed: 20979621
Cancer Res. 1999 Nov 1;59(21):5403-7
pubmed: 10554005
Cancer Res. 2012 Nov 15;72(22):5878-88
pubmed: 23026133
Acta Neuropathol. 2016 Jun;131(6):803-20
pubmed: 27157931
Oncotarget. 2017 Mar 23;8(42):71597-71617
pubmed: 29069732
Bioinformatics. 2015 Jan 15;31(2):166-9
pubmed: 25260700
Nat Genet. 2014 May;46(5):457-461
pubmed: 24705252
Cancer Res. 2016 Apr 15;76(8):2465-77
pubmed: 26896279
Nat Neurosci. 2016 Jan;19(1):10-9
pubmed: 26713744
Oncotarget. 2017 Feb 2;8(32):52543-52559
pubmed: 28881750
Clin Cancer Res. 2010 Jul 1;16(13):3368-77
pubmed: 20570930
Nucleic Acids Res. 2014 Jan;42(Database issue):D199-205
pubmed: 24214961
Clin Exp Metastasis. 2002;19(7):571-82
pubmed: 12498386
Genome Biol. 2014;15(12):550
pubmed: 25516281
FEBS Lett. 2007 Jul 31;581(19):3582-91
pubmed: 17586500
Exp Cell Res. 2017 Nov 15;360(2):397-403
pubmed: 28947132
J Clin Oncol. 2018 Jul 1;36(19):1963-1972
pubmed: 29746225
Cancer Lett. 2016 Jul 1;376(2):328-38
pubmed: 27063097
J Neurooncol. 2012 Jan;106(2):399-407
pubmed: 21858607
Cell Stem Cell. 2018 Apr 5;22(4):514-528.e5
pubmed: 29625067
Anat Cell Biol. 2015 Mar;48(1):25-35
pubmed: 25806119
Front Surg. 2016 Apr 15;3:21
pubmed: 27148537
J Clin Oncol. 2018 Apr 1;36(10):951-958
pubmed: 29412784
Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50
pubmed: 16199517
Neuro Oncol. 2015 Jul;17(7):965-77
pubmed: 25537021
Nat Methods. 2012 Mar 04;9(4):357-9
pubmed: 22388286
Clin Cancer Res. 2017 Oct 15;23(20):6101-6112
pubmed: 28733441
Neuro Oncol. 2017 Feb 1;19(2):229-241
pubmed: 27576873
Mult Scler. 2014 Apr;20(5):558-65
pubmed: 24080986
Nucleic Acids Res. 2018 Jan 4;46(D1):D754-D761
pubmed: 29155950
Stem Cells Int. 2018 Feb 18;2018:3292704
pubmed: 29531533
Genome Biol. 2013 Apr 25;14(4):R36
pubmed: 23618408
ACS Biomater Sci Eng. 2018 Feb 12;4(2):410-420
pubmed: 29527571
PLoS One. 2017 Jan 4;12(1):e0169485
pubmed: 28052119
AJNR Am J Neuroradiol. 2014 Jun;35(6 Suppl):S31-6
pubmed: 24481330
Nucleic Acids Res. 2000 Jan 1;28(1):27-30
pubmed: 10592173
Science. 2018 Apr 20;360(6386):331-335
pubmed: 29674595
Nat Med. 2018 May;24(5):572-579
pubmed: 29662203
Acta Neuropathol. 2016 Jun;131(6):903-10
pubmed: 26671409
Nat Med. 2015 Jun;21(6):555-9
pubmed: 25939062
Nat Med. 2018 Aug;24(8):1204-1215
pubmed: 29967352
Oncotarget. 2017 Mar 21;8(12):18626-18639
pubmed: 28148893