Exposure to Tobacco Smoking Induces a subset of Activated Tumor-resident Tregs in Non-Small Cell Lung Cancer

Regulatory T cells in the blood of patients with chronic obstructive pulmonary disease (COPD): A systematic review and meta-analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) ranks among the leading causes of mortality and morbidity worldwide. Due to the lack of effective treatments for COPD, targeting regulatory T-cells (Treg) has recently attracted considerable attention. Therefore, we conducted a systematic review and meta-analysis to review all of the existing data about the percentage of Treg cells in peripheral blood samples of COPD patients to discover the potential role of these cells in finding new treatments for these patients.

METHODS

We explored SCOPUS, PubMed, and Web of Science databases using search terms like "Chronic obstructive pulmonary disease", "Emphysema", "suppressive lymphocyte", and "Regulatory T Cell". Data regarding the number of COPD patients and healthy subjects, Treg cell identification, definition of Treg cell markers, and the percentage of Tregs in COPD patients and controls, in addition to smoking, and clinical status of COPD patients were extracted.

RESULTS

The overall assessment showed no significant difference in the frequency of Treg cells between COPD patients and healthy subjects. No remarkable difference in Treg frequencies was observed in subgroup analysis based on the markers used to define Tregs, the clinical state of COPD patients, and the patient's smoking history. Based on our results, smoking reduces the level of Treg cells in the body. The frequency of CD4+CD25+FoxP3+ Tregs was considerably lower in the blood of smokers than in non-smoking healthy individuals.

CONCLUSION

The overall result of this meta-analysis points out the importance of smoking in the prevalence of peripheral blood Treg cells.

Easily applicable predictive score for MPR based on parameters before neoadjuvant chemoimmunotherapy in operable NSCLC: a single-center, ambispective, observational study

BACKGROUND

Neoadjuvant chemoimmunotherapy (NACI) is promising for resectable nonsmall cell lung cancer (NSCLC), but predictive biomarkers are still lacking. The authors aimed to develop a model based on pretreatment parameters to predict major pathological response (MPR) for such an approach.

METHODS

The authors enrolled operable NSCLC treated with NACI between March 2020 and May 2023 and then collected baseline clinical-pathology data and routine laboratory examinations before treatment. The efficacy and safety data of this cohort was reported and variables were screened by Logistic and Lasso regression and nomogram was developed. In addition, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to assess its power. Finally, internal cross-validation and external validation was performed to assess the power of the model.

RESULTS

In total, 206 eligible patients were recruited in this study and 53.4% (110/206) patients achieved MPR. Using multivariate analysis, the predictive model was constructed by seven variables, prothrombin time (PT), neutrophil percentage (NEUT%), large platelet ratio (P-LCR), eosinophil percentage (EOS%), smoking, pathological type, and programmed death ligand-1 (PD-L1) expression finally. The model had good discrimination, with area under the receiver operating characteristic curve (AUC) of 0.775, 0.746, and 0.835 for all datasets, cross-validation, and external validation, respectively. The calibration curves showed good consistency, and decision curve analysis indicated its potential value in clinical practice.

CONCLUSION

This real world study revealed favorable efficacy in operable NSCLC treated with NACI. The proposed model based on multiple clinically accessible parameters could effectively predict MPR probability and could be a powerful tool in personalized medication.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Tobacco exposure primes the secretion of CCL21 positively associated with tertiary lymphoid structure and response to immunotherapy

BACKGROUND

It has been reported that smoking history as a predictor of immunotherapy efficacy in patients with advanced lung cancer, however, the underlying mechanisms of this phenomenon remain largely unknown.

METHODS

The patients with lung adenocarcinoma's (LUAD) cohort and the orthotopical transplanted mouse model were used to explore the correlation between smoking status and tertiary lymphoid structure (TLS) and chemokine CCL21, respectively. Cell adhesion and co-immunoprecipitation assays were performed to explore the interaction between CD4+T cells and CD20+B cells under tobacco exposure. Chromatin immunoprecipitation-PCR was used to dissect the mechanism of upregulated CCL21 secretion in tobacco treatment. Serum CCL21 level was recorded in patients with LUAD treated with immunotherapy.

RESULTS

Here we observed that individuals with a smoking history exhibit an increased quantity and maturation level of TLS compared with non-smokers, along with higher levels of CCL21 secretion. Tobacco exposure promoted CCL21 expression in an epithelial cell-intrinsic manner, of which BaP, the main component of tobacco, facilitated the nuclear retention of the aryl hydrocarbon receptor that occupied the promoter of CCL21. Additionally, the activated CCL21/CCR7 axis increased the CD11a expression of CD4+T cells, boosting the interaction with CD20+B cells dependent on ICAM1, which potentially induced the TLSs formation. Patients with elevated serum levels of CCL21 benefited more from immunotherapy.

CONCLUSIONS

Patients with a smoking history exhibited higher levels of TLS via the CCL21-dependent mechanism, serum CCL21 was identified as a reliable biomarker for predicting the efficacy of immunotherapy.

Liver X receptors and estrogen receptor β, two players in a rare subtype of NSCLC

Liver X receptors (LXRαβ) play essential roles in the maintenance of the normal functions of macrophages, in modulation of immune system responses and cholesterol homeostasis. We have reported that LXRαβ^-/- mice develop squamous cell lung cancer. We now report that those LXRαβ^-/- mice, which live to 18-months of age, spontaneously develop a second type of lung cancer resembling a rare subtype of NSCLC (TTF-1 and P63-positive). The lesions are characterized as follows: a high proliferation rate; a marked accumulation of abnormal macrophages; an increase in the number of regulatory T cells; a remarkably low level of CD8⁺ cytotoxic T lymphocytes; enhanced TGFβ signaling; an increased expression of matrix metalloproteinases accompanied by degradation of lung collagen; and a loss of estrogen receptor β (ERβ). Because NSCLC is associated with cigarette smoking, we investigated the possible links between loss of LXRαβ and CS. A Kaplan-Meier Plotter database revealed reduced expression of LXRαβ and ERβ was correlated with low overall survival (OS). Thus, reduction of LXRαβ expression by cigarette smoking may be one mechanism through which CS causes lung cancer. The possibility that maintenance of LXRαβ and ERβ signaling could be used in the treatment of NSCLC needs further investigation.