Lung tissue T cells are activated in chronic obstructive pulmonary disease with non-small cell lung cancer patients

Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation of the respiratory tract and is associated with an increased risk of lung cancer. Non-small cell lung cancer (NSCLC) patients with COPD have been shown to exhibit favorable responses to anti-PD-1/PD-L1 therapy. In the present study, we investigated T cell profiles and functions in the lung tissues of NSCLC patients with or without COPD to provide the rationale for immunotherapy of NSCLC patients with COPD. Abundant PD-1<sup>+</sup> and Tim-3<sup>+</sup> T cells were detected in the lung tumor tissues of NSCLC patients with COPD. On the other hand, CD103<sup>+</sup> tissue-resident memory T (T<sub>RM</sub>) cells in non-tumor lung tissues were more abundant in NSCLC patients with than in those without COPD. Furthermore, the abundance of CD103<sup>+</sup> T<sub>RM</sub> cells in non-tumor lung tissues correlated with IFN-γ production and COPD-related clinical parameters (pack-years smoking history and the FEV1/FVC ratio). In NSCLC patients with COPD, T cells were active participants in both the non-tumor and the lung tumor tissues, suggesting the potential response to immunotherapy.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-11-21
DOI
https://doi.org/10.1038/s41598-025-25141-x
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lung tissue T cells are activated in chronic obstructive pulmonary disease with non-small cell lung cancer patients

Hisashi Wada, Mari Tone, Atsushi Kumanogoh, Yoko Yamamoto et al.
Scientific Reports
Cancer Immunotherapy and Biomarkers
article

Lung tissue T cells are activated in chronic obstructive pulmonary disease with non-small cell lung cancer patients

Hisashi Wada, Mari Tone, Atsushi Kumanogoh, Yoko Yamamoto, Kota Iwahori, Yoshito Takeda, Yasushi Shintani, Tomomi Isono
article en

Abstract

Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation of the respiratory tract and is associated with an increased risk of lung cancer. Non-small cell lung cancer (NSCLC) patients with COPD have been shown to exhibit favorable responses to anti-PD-1/PD-L1 therapy. In the present study, we investigated T cell profiles and functions in the lung tissues of NSCLC patients with or without COPD to provide the rationale for immunotherapy of NSCLC patients with COPD. Abundant PD-1<sup>+</sup> and Tim-3<sup>+</sup> T cells were detected in the lung tumor tissues of NSCLC patients with COPD. On the other hand, CD103<sup>+</sup> tissue-resident memory T (T<sub>RM</sub>) cells in non-tumor lung tissues were more abundant in NSCLC patients with than in those without COPD. Furthermore, the abundance of CD103<sup>+</sup> T<sub>RM</sub> cells in non-tumor lung tissues correlated with IFN-γ production and COPD-related clinical parameters (pack-years smoking history and the FEV1/FVC ratio). In NSCLC patients with COPD, T cells were active participants in both the non-tumor and the lung tumor tissues, suggesting the potential response to immunotherapy.

Scientific ReportsVol. 15(1)
Japan Agency for Medical Research and Development (JP), Osaka International Cancer Institute (JP), Osaka International University (JP), The University of Osaka (JP)
Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science
Openalex Percentile: Top 51%
Cancer Immunotherapy and Biomarkers
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.