TY - JOUR
T1 - A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer
AU - Shen, Aidan
AU - Garrett, Aliesha
AU - Chao, Cheng Chi
AU - Liu, Dongliang
AU - Cheng, Chao
AU - Wang, Zhaohui
AU - Qian, Chen
AU - Zhu, Yangzhi
AU - Mai, Junhua
AU - Jiang, Chongming
N1 - Publisher Copyright:
Copyright © 2024 Shen, Garrett, Chao, Liu, Cheng, Wang, Qian, Zhu, Mai and Jiang.
PY - 2024
Y1 - 2024
N2 - Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.
AB - Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.
KW - machine learning
KW - non-small-cell lung cancer
KW - prognosis
KW - tissue resident memory T cell
KW - tumor immune microenvironment
KW - Carcinoma, Non-Small-Cell Lung/immunology
KW - Prognosis
KW - Lung Neoplasms/immunology
KW - Humans
KW - Memory T Cells/immunology
KW - Lymphocytes, Tumor-Infiltrating/immunology
KW - Tumor Microenvironment/immunology
KW - Immunologic Memory
UR - http://www.scopus.com/inward/record.url?scp=85199216430&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85199216430&partnerID=8YFLogxK
U2 - 10.3389/fimmu.2024.1416751
DO - 10.3389/fimmu.2024.1416751
M3 - Article
C2 - 39040095
AN - SCOPUS:85199216430
SN - 1664-3224
VL - 15
SP - 1416751
JO - Frontiers in immunology
JF - Frontiers in immunology
M1 - 1416751
ER -