Prognosis of Non-small-cell Lung Cancer Patients With Lipid Metabolism Pathway Alternations to Immunotherapy.
immune checkpoint inhibitors
immune microenvironment
lipid metabolism pathway
non-small-cell lung cancer
predictive marker
Journal
Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621
Informations de publication
Date de publication:
2021
2021
Historique:
received:
26
12
2020
accepted:
08
06
2021
entrez:
2
8
2021
pubmed:
3
8
2021
medline:
3
8
2021
Statut:
epublish
Résumé
Immune checkpoint inhibitors (ICIs) significantly improve the survival of patients with non-small-cell lung cancer (NSCLC), but only some patients obtain clinical benefits. Predictive biomarkers for ICIs can accurately identify people who will benefit from immunotherapy. Lipid metabolism signaling plays a key role in the tumor microenvironment (TME) and immunotherapy. Hence, we aimed to explore the association between the mutation status of the lipid metabolism pathway and the prognosis of patients with NSCLC treated with ICIs. We downloaded the mutation data and clinical data of a cohort of patients with NSCLC who received ICIs. Univariate and multivariate Cox regression models were used to analyze the association between the mutation status of the lipid metabolism signaling and the prognosis of NSCLC receiving ICIs. Additionally, The Cancer Genome Atlas (TCGA)-NSCLC cohort was used to explore the relationships between the different mutation statuses of lipid metabolism pathways and the TME. Additionally, we found that patients with high numbers of mutations in the lipid metabolism pathway had significantly enriched macrophages (M0- and M1-type), CD4 + T cells (activated memory), CD8 + T cells, Tfh cells and gamma delta T cells, significantly increased expression of inflammatory genes [interferon-γ (IFNG), CD8A, GZMA, GZMB, CXCL9, and CXCL10] and enhanced immunogenic factors [neoantigen loads (NALs), tumor mutation burden (TMB), and DNA damage repair pathways]. In the local-NSCLC cohort, we found that the group with a high number of mutations had a significantly higher tumor mutation burden (TMB) and PD-L1 expression. High mutation status in the lipid metabolism pathway is associated with significantly prolonged progression-free survival (PFS) in NSCLC, indicating that this marker can be used as a predictive indicator for patients with NSCLC receiving ICIs.
Identifiants
pubmed: 34335679
doi: 10.3389/fgene.2021.646362
pmc: PMC8317604
doi:
Types de publication
Journal Article
Langues
eng
Pagination
646362Informations de copyright
Copyright © 2021 Cheng, Zhang, Liu, Lai and Wen.
Déclaration de conflit d'intérêts
JZ, DL, and GL were employed by the company, HaploX Biotechnology. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Références
Lancet Oncol. 2016 Dec;17(12):e542-e551
pubmed: 27924752
Nat Med. 2013 Nov;19(11):1423-37
pubmed: 24202395
Nat Methods. 2015 May;12(5):453-7
pubmed: 25822800
Cancer Lett. 2016 Sep 28;380(1):205-15
pubmed: 26272180
Front Oncol. 2017 Sep 27;7:233
pubmed: 29034210
N Engl J Med. 2015 May 21;372(21):2018-28
pubmed: 25891174
Cancer Immunol Res. 2020 Apr;8(4):479-492
pubmed: 32075801
Virchows Arch. 2016 Mar;468(3):313-9
pubmed: 26637197
Cancer Lett. 2019 Aug 10;457:168-179
pubmed: 31078738
Nat Rev Cancer. 2019 Jul;19(7):405-414
pubmed: 31101865
Nucleic Acids Res. 2016 May 5;44(8):e71
pubmed: 26704973
J Clin Oncol. 2018 Mar 1;36(7):633-641
pubmed: 29337640
Annu Rev Immunol. 2014;32:513-45
pubmed: 24555472
Lung Cancer. 2017 Oct;112:200-215
pubmed: 29191596
Nat Commun. 2017 Oct 11;8(1):864
pubmed: 29021522
Front Oncol. 2020 Jul 22;10:1197
pubmed: 32775303
Front Immunol. 2018 Dec 14;9:2927
pubmed: 30619288
Lancet. 2016 Apr 9;387(10027):1540-1550
pubmed: 26712084
Bioinformatics. 2011 Jun 15;27(12):1739-40
pubmed: 21546393
Cell. 2015 Jan 15;160(1-2):48-61
pubmed: 25594174
Cell Metab. 2008 Jan;7(1):11-20
pubmed: 18177721
CA Cancer J Clin. 2018 Jan;68(1):7-30
pubmed: 29313949
Cancer Med. 2018 Mar;7(3):746-756
pubmed: 29436178
Cell Metab. 2019 Jul 2;30(1):143-156.e5
pubmed: 31031094
J Exp Clin Cancer Res. 2019 May 14;38(1):193
pubmed: 31088500
Front Immunol. 2020 Aug 12;11:2039
pubmed: 32903444
Nature. 2018 Jan 24;553(7689):446-454
pubmed: 29364287
Nature. 2019 May;569(7755):270-274
pubmed: 31043744
Science. 2016 Mar 25;351(6280):1463-9
pubmed: 26940869
Immunity. 2018 Apr 17;48(4):812-830.e14
pubmed: 29628290
Contemp Oncol (Pozn). 2015;19(1A):A68-77
pubmed: 25691825
Lancet Oncol. 2016 Nov;17(11):1497-1508
pubmed: 27745820
Cancer Res. 2018 Nov 15;78(22):6486-6496
pubmed: 30171052
Nature. 2016 Mar 31;531(7596):651-5
pubmed: 26982734
J Clin Oncol. 2018 Jun 10;36(17):1685-1694
pubmed: 29489427
Mol Cancer. 2019 Sep 16;18(1):139
pubmed: 31526368
J Clin Oncol. 2019 Oct 1;37(28):2518-2527
pubmed: 31154919
CA Cancer J Clin. 2018 Nov;68(6):394-424
pubmed: 30207593
Lancet Oncol. 2020 Mar;21(3):387-397
pubmed: 32035514
Cancer Lett. 2017 Feb 28;387:61-68
pubmed: 26845449
Bioinformatics. 2007 Dec 1;23(23):3251-3
pubmed: 17644558
J Exp Clin Cancer Res. 2015 Oct 06;34:111
pubmed: 26445347
Science. 2018 Feb 2;359(6375):582-587
pubmed: 29217585
Nat Rev Rheumatol. 2017 May;13(5):267-279
pubmed: 28331208
Cell. 2012 May 25;149(5):1060-72
pubmed: 22632970