Comprehensive analyses of the heterogeneity and prognostic significance of tumor-infiltrating immune cells in non-small-cell lung cancer: Development and validation of an individualized prognostic model.
Agammaglobulinaemia Tyrosine Kinase
/ genetics
B-Lymphocytes
/ immunology
Biomarkers, Tumor
Carcinoma, Non-Small-Cell Lung
/ diagnosis
Cohort Studies
Humans
Immune Checkpoint Proteins
/ genetics
Lectins, C-Type
/ genetics
Lung Neoplasms
/ diagnosis
Lymphocytes, Tumor-Infiltrating
/ immunology
Mast Cells
/ immunology
Models, Biological
Neoplasm Staging
Precision Medicine
Prognosis
Receptors, CCR2
/ genetics
Survival Analysis
T-Lymphocytes
/ immunology
Heterogeneity
Immune-related differentially expressed genes
Nomogram
Non-small-cell lung cancer
Tumor-infiltrating immune cells
Journal
International immunopharmacology
ISSN: 1878-1705
Titre abrégé: Int Immunopharmacol
Pays: Netherlands
ID NLM: 100965259
Informations de publication
Date de publication:
Sep 2020
Sep 2020
Historique:
received:
05
05
2020
revised:
21
06
2020
accepted:
24
06
2020
pubmed:
6
7
2020
medline:
28
5
2021
entrez:
6
7
2020
Statut:
ppublish
Résumé
Understanding the role of tumor-infiltrating immune cells (TIICs) in non-small cell lung cancer (NSCLC) is critical to finding new prognostic biomarkers and improving prognostic evaluation. Herein, we aimed to comprehensively analyze tumor-infiltrating pattern of TIICs in NSCLC and build a TIICs-associated, risk-stratification prognostic model for clinical practice. We applied CIBERSORT and ESTIMATE computational methods to analyze RNA-seq samples of 852 NSCLC patients from The Cancer Genome Atlas (TCGA). Prognotic factors were identified by univariate and multivariate Cox regression analyses for overall survival (OS). A novel model was developed to predict the 1-, 3- and 5-year OS of NSCLC based on the TCGA cohort, validated by external validation cohorts (GSE31210, GSE37745), and then evaluated by C-indexes and calibration plots. Significant heterogeneity in the infiltrating patterns of TIICs was shown among various pathological subtypes of NSCLC and between different genders. Further analyses showed that abundances of naive B cells (NBCs), T cells and mast cells (MCs) were positively correlated with prognosis. Tumor samples with high T cells abundances tended to have higher expression levels of immune checkpoint genes (PD-1, PD-L1, CTLA-4). A new immune-gene related index (IGRI) was built by five immune-related differentially expressed genes (DEGs) including BTK, CCR2, CLEC10A, NCR3 and PRKCB, which were closely correlated with TIICs abundances and prognosis. Tumor stage, IGRI, abundances of NBCs, T cells, MCs and NK cells were significant independent prognostic factors and were included in the nomogram as predictors. The internal and external calibration plots of the nomogram were in excellent agreement. This study reveals that TIICs are significantly correlated with clinicopathological features and prognosis in NSCLC and thus can be potential prognostic biomarker or therapeutic target. The remarkable heterogeneity of TIICs suggests that specific infiltrating patterns of TIICs should also be taken into consideration when determining individualized immunotherapy strategies for NSCLC patients.
Identifiants
pubmed: 32623229
pii: S1567-5769(20)31427-2
doi: 10.1016/j.intimp.2020.106744
pii:
doi:
Substances chimiques
Biomarkers, Tumor
0
CCR2 protein, human
0
CLEC10A protein, human
0
Immune Checkpoint Proteins
0
Lectins, C-Type
0
Receptors, CCR2
0
Agammaglobulinaemia Tyrosine Kinase
EC 2.7.10.2
BTK protein, human
EC 2.7.10.2
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
106744Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declared that there is no conflict of interest.