Holding our breath: the promise of tissue-resident memory T cells in lung cancer

Dendritic cell-based immunotherapy in non-small cell lung cancer: a comprehensive critical review

Despite treatment advances through immunotherapies, including anti-PD-1/PD-L1 therapies, the overall prognosis of non-small cell lung cancer (NSCLC) patients remains poor, underscoring the need for novel approaches that offer long-term clinical benefit. This review examined the literature on the subject over the past 20 years to provide an update on the evolving landscape of dendritic cell-based immunotherapy to treat NSCLC, highlighting the crucial role of dendritic cells (DCs) in immune response initiation and regulation. These cells encompass heterogeneous subsets like cDC1s, cDC2s, and pDCs, capable of shaping antigen presentation and influencing T cell activation through the balance between the Th1, Th2, and Th17 profiles and the activation of regulatory T lymphocytes (Treg). The intricate interaction between DC subsets and the high density of intratumoral mature DCs shapes tumor-specific immune responses and impacts therapeutic outcomes. DC-based immunotherapy shows promise in overcoming immune resistance in NSCLC treatment. This article review provides an update on key clinical trial results, forming the basis for future studies to characterize the role of different types of DCs in situ and in combination with different therapies, including DC vaccines.

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

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.

Monocyte-to-lymphocyte ratio is a prognostic predictor for patients with non-small cell lung cancer treated with stereotactic body radiation therapy

Background

The monocyte-to-lymphocyte ratio (MLR), a systemic inflammation biomarker, has been shown to predict patient outcomes in several types of cancer. This study aimed to determine the association between MLR and local control (LC) and cause-specific survival (CSS) rates in patients with non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT).

Materials and methods

The median age of the 194 included participants (144 men, 50 women) was 80 (range, 50-96) years. The median follow-up period was 19 (range, 1-108) months. The LC and CSS rates were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazard regression models were used to estimate the LC and CSS rates.

Results

Local recurrence was observed in 25 patients during the follow-up. Univariate Cox proportional hazards regression analysis revealed that MLR, performance status, and tumor diameter were significant factors for LC. Multivariate analysis showed MLR and tumor diameter as significant factors (p = 0.041 and 0.031, respectively). The 1- and 2-year LC rates for the lower and higher MLR groups were 97.5% and 97.5%, and 89.7% and 81.2%, respectively. During the follow-up period, 14 patients died due to NSCLC. Although MLR tended to predict CSS in univariate analysis (p = 0.086), none of the parameters was significant in predicting CSS. However, MLR as a continuous variable was a significant factor for CSS in the univariate analysis (p = 0.004).

Conclusions

Our data suggest that MLR is correlated with LC and CSS rates in NSCLC patients treated with SBRT.

Early immune pressure initiated by tissue-resident memory T cells sculpts tumor evolution in non-small cell lung cancer

Tissue-resident memory T (TRM) cells provide immune defense against local infection and can inhibit cancer progression. However, it is unclear to what extent chronic inflammation impacts TRM activation and whether TRM cells existing in tissues before tumor onset influence cancer evolution in humans. We performed deep profiling of healthy lungs and lung cancers in never-smokers (NSs) and ever-smokers (ESs), finding evidence of enhanced immunosurveillance by cells with a TRM-like phenotype in ES lungs. In preclinical models, tumor-specific or bystander TRM-like cells present prior to tumor onset boosted immune cell recruitment, causing tumor immune evasion through loss of MHC class I protein expression and resistance to immune checkpoint inhibitors. In humans, only tumors arising in ES patients underwent clonal immune evasion, unrelated to tobacco-associated mutagenic signatures or oncogenic drivers. These data demonstrate that enhanced TRM-like activity prior to tumor development shapes the evolution of tumor immunogenicity and can impact immunotherapy outcomes.

The soldiers needed to be awakened: Tumor-infiltrating immune cells

In the tumor microenvironment, tumor-infiltrating immune cells (TIICs) are a key component. Different types of TIICs play distinct roles. CD8+ T cells and natural killer (NK) cells could secrete soluble factors to hinder tumor cell growth, whereas regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) release inhibitory factors to promote tumor growth and progression. In the meantime, a growing body of evidence illustrates that the balance between pro- and anti-tumor responses of TIICs is associated with the prognosis in the tumor microenvironment. Therefore, in order to boost anti-tumor response and improve the clinical outcome of tumor patients, a variety of anti-tumor strategies for targeting TIICs based on their respective functions have been developed and obtained good treatment benefits, including mainly immune checkpoint blockade (ICB), adoptive cell therapies (ACT), chimeric antigen receptor (CAR) T cells, and various monoclonal antibodies. In recent years, the tumor-specific features of immune cells are further investigated by various methods, such as using single-cell RNA sequencing (scRNA-seq), and the results indicate that these cells have diverse phenotypes in different types of tumors and emerge inconsistent therapeutic responses. Hence, we concluded the recent advances in tumor-infiltrating immune cells, including functions, prognostic values, and various immunotherapy strategies for each immune cell in different tumors.