Interactions of Age and Blood Immune Factors and Noninvasive Prediction of Glioma Survival.
Journal
Journal of the National Cancer Institute
ISSN: 1460-2105
Titre abrégé: J Natl Cancer Inst
Pays: United States
ID NLM: 7503089
Informations de publication
Date de publication:
08 03 2022
08 03 2022
Historique:
received:
19
04
2021
revised:
30
06
2021
accepted:
23
09
2021
pubmed:
2
10
2021
medline:
23
3
2022
entrez:
1
10
2021
Statut:
ppublish
Résumé
Tumor-based classification of human glioma portends patient prognosis, but considerable unexplained survival variability remains. Host factors (eg, age) also strongly influence survival times, partly reflecting a compromised immune system. How blood epigenetic measures of immune characteristics and age augment molecular classifications in glioma survival has not been investigated. We assess the prognostic impact of immune cell fractions and epigenetic age in archived blood across glioma molecular subtypes for the first time. We evaluated immune cell fractions and epigenetic age in archived blood from the University of California San Francisco Adult Glioma Study, which included a training set of 197 patients with IDH-wild type, 1p19q intact, TERT wild type (IDH/1p19q/TERT-WT) glioma, an evaluation set of 350 patients with other subtypes of glioma, and 454 patients without glioma. IDH/1p19q/TERT-WT patients had lower lymphocyte fractions (CD4+ T, CD8+ T, natural killer, and B cells) and higher neutrophil fractions than people without glioma. Recursive partitioning analysis delineated 4 statistically significantly different survival groups for patients with IDH/1p19q/TERT-WT based on an interaction between chronological age and 2 blood immune factors, CD4+ T cells, and neutrophils. Median overall survival ranged from 0.76 years (95% confidence interval = 0.55-0.99) for the worst survival group (n = 28) to 9.72 years (95% confidence interval = 6.18 to not available) for the best (n = 33). The recursive partitioning analysis also statistically significantly delineated 4 risk groups in patients with other glioma subtypes. The delineation of different survival groups in the training and evaluation sets based on an interaction between chronological age and blood immune characteristics suggests that common host immune factors among different glioma types may affect survival. The ability of DNA methylation-based markers of immune status to capture diverse, clinically relevant information may facilitate noninvasive, personalized patient evaluation in the neuro-oncology clinic.
Sections du résumé
BACKGROUND
Tumor-based classification of human glioma portends patient prognosis, but considerable unexplained survival variability remains. Host factors (eg, age) also strongly influence survival times, partly reflecting a compromised immune system. How blood epigenetic measures of immune characteristics and age augment molecular classifications in glioma survival has not been investigated. We assess the prognostic impact of immune cell fractions and epigenetic age in archived blood across glioma molecular subtypes for the first time.
METHODS
We evaluated immune cell fractions and epigenetic age in archived blood from the University of California San Francisco Adult Glioma Study, which included a training set of 197 patients with IDH-wild type, 1p19q intact, TERT wild type (IDH/1p19q/TERT-WT) glioma, an evaluation set of 350 patients with other subtypes of glioma, and 454 patients without glioma.
RESULTS
IDH/1p19q/TERT-WT patients had lower lymphocyte fractions (CD4+ T, CD8+ T, natural killer, and B cells) and higher neutrophil fractions than people without glioma. Recursive partitioning analysis delineated 4 statistically significantly different survival groups for patients with IDH/1p19q/TERT-WT based on an interaction between chronological age and 2 blood immune factors, CD4+ T cells, and neutrophils. Median overall survival ranged from 0.76 years (95% confidence interval = 0.55-0.99) for the worst survival group (n = 28) to 9.72 years (95% confidence interval = 6.18 to not available) for the best (n = 33). The recursive partitioning analysis also statistically significantly delineated 4 risk groups in patients with other glioma subtypes.
CONCLUSIONS
The delineation of different survival groups in the training and evaluation sets based on an interaction between chronological age and blood immune characteristics suggests that common host immune factors among different glioma types may affect survival. The ability of DNA methylation-based markers of immune status to capture diverse, clinically relevant information may facilitate noninvasive, personalized patient evaluation in the neuro-oncology clinic.
Identifiants
pubmed: 34597382
pii: 6379711
doi: 10.1093/jnci/djab195
pmc: PMC8902347
doi:
Substances chimiques
Immunologic Factors
0
Isocitrate Dehydrogenase
EC 1.1.1.41
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
446-457Subventions
Organisme : NCI NIH HHS
ID : R01 CA126831
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM103408
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA097257
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM130423
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM103428
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA207360
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA139020
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA168524
Pays : United States
Organisme : NCI NIH HHS
ID : R25 CA112355
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA052689
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM104416
Pays : United States
Informations de copyright
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Références
BMC Bioinformatics. 2012 May 08;13:86
pubmed: 22568884
Front Pharmacol. 2019 Mar 27;10:200
pubmed: 30971917
Mol Cell. 2013 Jan 24;49(2):359-367
pubmed: 23177740
Nat Rev Drug Discov. 2017 Apr;16(4):264-272
pubmed: 28057932
Nat Med. 2019 Mar;25(3):487-495
pubmed: 30842675
Nat Rev Neurol. 2019 Jul;15(7):405-417
pubmed: 31227792
J Neuroimmunol. 1999 Dec;100(1-2):216-32
pubmed: 10695732
Blood. 2018 Feb 1;131(5):479-487
pubmed: 29141947
Mol Cell. 2018 Sep 20;71(6):882-895
pubmed: 30241605
Front Pediatr. 2016 Oct 31;4:119
pubmed: 27843891
Curr Opin Immunol. 2005 Oct;17(5):468-75
pubmed: 16098723
J Natl Cancer Inst. 1993 May 5;85(9):704-10
pubmed: 8478956
J Natl Cancer Inst. 2014 May 29;106(6):dju124
pubmed: 24875653
Nat Med. 2019 Aug;25(8):1251-1259
pubmed: 31359002
Aging (Albany NY). 2018 Apr 18;10(4):573-591
pubmed: 29676998
Bioinformatics. 2010 May 15;26(10):1357-63
pubmed: 20375111
Sci Rep. 2019 Feb 22;9(1):2636
pubmed: 30796310
J Neurooncol. 2011 Aug;104(1):339-49
pubmed: 21181233
Nat Rev Rheumatol. 2020 Feb;16(2):87-99
pubmed: 31892734
Nat Med. 2019 Mar;25(3):477-486
pubmed: 30742122
Genome Res. 2018 Sep;28(9):1285-1295
pubmed: 30072366
BMC Bioinformatics. 2016 Mar 08;17:120
pubmed: 26956433
J Immunol. 2015 May 1;194(9):4073-80
pubmed: 25888703
N Engl J Med. 2015 Jun 25;372(26):2499-508
pubmed: 26061753
Biometrics. 2012 Dec;68(4):1146-56
pubmed: 22519965
Nat Med. 2018 Nov;24(11):1773-1775
pubmed: 29967347
Neuro Oncol. 2006 Jan;8(1):12-26
pubmed: 16443944
Nature. 2018 Mar 22;555(7697):469-474
pubmed: 29539639
Int J Radiat Oncol Biol Phys. 1998 Jan 1;40(1):51-5
pubmed: 9422557
Acta Neuropathol. 2017 Jun;133(6):1001-1016
pubmed: 28255664
Neuro Oncol. 2018 Jun 18;20(7):942-953
pubmed: 29432558
Int J Radiat Oncol Biol Phys. 2005 Aug 1;62(5):1423-6
pubmed: 16029802
J Neurooncol. 2017 May;132(3):463-471
pubmed: 28332000
J Clin Oncol. 2014 Aug 1;32(22):2380-5
pubmed: 24982461
Genome Biol. 2014 Mar 05;15(3):R50
pubmed: 24598480
Genome Biol. 2018 May 29;19(1):64
pubmed: 29843789
Clin Transl Oncol. 2016 Nov;18(11):1062-1071
pubmed: 26960561
JAMA Oncol. 2018 Oct 1;4(10):1405-1409
pubmed: 29955793
Clin Cancer Res. 2011 Aug 15;17(16):5473-80
pubmed: 21737504
Nat Rev Immunol. 2013 May;13(5):376-89
pubmed: 23584423
Genome Biol. 2013;14(10):R115
pubmed: 24138928
Acta Neuropathol. 2016 Jun;131(6):803-20
pubmed: 27157931
Cell. 2017 Jan 26;168(3):487-502.e15
pubmed: 28111070
Exp Gerontol. 2018 May;105:4-9
pubmed: 29111233
N Engl J Med. 2015 Jun 25;372(26):2481-98
pubmed: 26061751
Nat Med. 2018 Sep;24(9):1459-1468
pubmed: 30104766
Front Immunol. 2019 Sep 25;10:2247
pubmed: 31608061
JAMA Oncol. 2020 Apr 1;6(4):495-503
pubmed: 32027343
Clin Epigenetics. 2017 Feb 2;9:10
pubmed: 28184256