Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma

Metabolic heterogeneity in tumor cells impacts immunology in lung squamous cell carcinoma

Metabolic processes are crucial in immune regulation, yet the impact of metabolic heterogeneity on immunological functions remains unclear. Integrating metabolomics into immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. To elucidate such insight in lung squamous cell carcinoma (LUSC), we analyzed 106 LUSC tumor tissues. We performed high-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain spatial metabolic profiles, and immunohistochemistry to detect tumor-infiltrating T lymphocytes (TILs). Unsupervised k-means clustering and Simpson's diversity index were employed to assess metabolic heterogeneity, identifying five distinct metabolic tumor subpopulations. Our findings revealed that TILs are specifically associated with metabolite distributions, not randomly distributed. Integrating a validation cohort, we found that heterogeneity-correlated metabolites interact with CD8+ TIL-associated genes, affecting survival. High metabolic heterogeneity was linked to worse survival and lower TIL levels. Pathway enrichment analyses highlighted distinct metabolic pathways in each subpopulation and their potential responses to chemotherapy. This study uncovers the significant impact of metabolic heterogeneity on immune functions in LUSC, providing a foundation for tailoring therapeutic strategies.

Tertiary lymphoid structures achieve 'cold' to 'hot' transition by remodeling the cold tumor microenvironment

Immune checkpoint blockade (ICB) therapies have demonstrated significant clinical efficacy in immune-infiltrated tumors such as melanoma and non-small cell lung cancer. However, "cold tumors"-including ovarian cancer, pancreatic cancer, and gliomas-exhibit insufficient immune infiltration, leading to poor therapeutic responses to ICBs and limited improvement in patient prognosis. Recent studies have shown that tumor-associated tertiary lymphoid structures (TLSs) can induce strong local immune responses within the tumor microenvironment (TME), serving as important biological markers for predicting ICB therapy efficacy. Notably, preclinical and clinical studies on cold tumors have confirmed that TLSs can potently enhance ICB efficacy through TME remodeling-a breakthrough that has attracted considerable attention. Here, we systematically examine the immunological profile of cold tumors and decipher the mechanistic basis for their impaired immune cell infiltration. We further delineate the distinctive features of tumor-associated TLSs in generating antitumor immunity and establish criteria for their identification. Significantly, we emphasize the unique capability of TLSs to reprogram the immunosuppressive tumor microenvironment characteristic of cold tumors. Based on these insights, we evaluate clinical evidence supporting TLS-mediated enhancement of ICB efficacy and discuss emerging strategies for exogenous TLSs induction.

Exploring effects of gut microbiota on tertiary lymphoid structure formation for tumor immunotherapy

Anti-tumor immunity, including innate and adaptive immunity is critical in inhibiting tumorigenesis and development of tumor. The adaptive immunity needs specific lymph organs such as tertiary lymphoid structures (TLSs), which are highly correlated with improved survival outcomes in many cancers. In recent years, with increasing attention on the TLS in tumor microenvironment, TLSs have emerged as a novel target for anti-tumor therapy. Excitingly, studies have shown the contribution of TLSs to the adaptive immune responses. However, it is unclear how TLSs to form and how to more effectively defense against tumor through TLS formation. Recent studies have shown that the inflammation plays a critical role in TLS formation. Interestingly, studies have also found that gut microbiota can regulate the occurrence and development of inflammation. Therefore, we here summarize the potential effects of gut microbiota- mediated inflammation or immunosuppression on the TLS formation in tumor environments. Meanwhile, this review also explores how to manipulate mature TLS formation through regulating gut microbiota/metabolites or gut microbiota associated signal pathways for anti-tumor immunity, which potentially lead to a next-generation cancer immunotherapy.

Analysis of single-cell and spatial transcriptomics in TNBC cell-cell interactions

Triple-negative breast cancer (TNBC) is a highly malignant tumor in women, characterized by high morbidity, mortality, and recurrence rates. Although surgical treatment, radiotherapy, and chemotherapy are the mainstays of current treatment methods, the high heterogeneity of TNBC results in unsatisfactory outcomes with low 5-year survival rates. Rapid advancements in omics technology have propelled the understanding of TNBC molecular biology. The emergence of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) has significantly enhanced knowledge of tumor heterogeneity and the distribution, functionality, and intercellular interactions of various cell types within the tumor microenvironment, including tumor cells, T cells, B cells, macrophages, and fibroblasts. The present study provides an overview of the technical characteristics of scRNA-seq and ST, highlighting their applications in exploring TNBC heterogeneity, cell spatial distribution patterns, and intercellular interactions. This review aims to enhance the comprehension of TNBC at the cellular level for the development of effective therapeutic targets.

Spatially mapping the tumour immune microenvironments of non-small cell lung cancer

Lung cancer is the leading cause of cancer-related deaths. An enhanced understanding of the immune microenvironments within these tumours may foster more precise and efficient treatment, particularly for immune-targeted therapies. The spatial architectural differences between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are relatively unexplored. Here, we applied imaging mass cytometry to a balanced cohort of LUAD and LUSC patients, matched for clinical factors such as age, sex, and smoking history, to analyze 204 histopathology images of tumours from 102 individuals with non-small cell lung cancer (NSCLC). By analyzing interactions and broader cellular networks, we interrogate the tumour microenvironment to understand how immune cells are spatially organized in clinically matched adenocarcinoma and squamous cell carcinoma subsets. This spatial analysis revealed distinct patterns of immune cell aggregation, particularly among macrophage populations, that correlated with patient prognosis differentially in adenocarcinoma and squamous cell carcinoma, suggesting potential new strategies for therapeutic intervention. Our findings underscore the importance of analyzing NSCLC histological subtypes separately when investigating the spatial immune landscape, as microenvironmental characteristics and cellular interactions differed by subtype. Recognizing these distinctions is essential for designing precision therapies tailored to each subtype's unique immune architecture, ultimately enhancing patient outcomes.

Induced B-Cell Receptor Diversity Predicts PD-1 Blockade Immunotherapy Response

Immune checkpoint inhibitors such as anti-PD-1 antibodies (aPD1) can be effective in treating advanced cancers. However, many patients do not respond and the mechanisms underlying these differences remain incompletely understood. In this study, we profile a cohort of patients with locally-advanced or metastatic basal cell carcinoma undergoing aPD-1 therapy using single-cell RNA sequencing, high-definition spatial transcriptomics in tumors and draining lymph nodes, and spatial immunoreceptor profiling, with long-term clinical follow-up. We find that successful responses to PD-1 inhibition are characterized by an induction of B-cell receptor (BCR) clonal diversity after treatment initiation. These induced BCR clones spatially co-localize with T-cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD1-induced BCR diversity as a predictor of clinical response in a larger cohort of glioblastoma, melanoma, and head and neck squamous cell carcinoma patients, suggesting that this is a generalizable predictor of treatment response across many types of cancers. We discover that pre-treatment tumors harbor a characteristic gene expression signature that portends a higher probability of inducing BCR clonal diversity after aPD-1 therapy, and we develop a machine learning model that predicts PD-1-induced BCR clonal diversity from baseline tumor RNA sequencing. These findings underscore a dynamic role of B cell diversity during immunotherapy, highlighting its importance as a prognostic marker and a potential target for intervention in non-responders.

Tertiary Lymphoid Structures in Microorganism-Related Cancer

Tertiary lymphoid structures (TLSs) are ectopic lymphoid tissues formed by the accumulation of lymphocytes and other components outside lymphoid organs. They have been shown to be widespread in cancers and have predictive effects on prognosis and immunotherapy efficacy; however, there is no standardized measurement guide. This paper provides a reference for future research. Moreover, the induction strategy for the formation mechanism of TLSs is a new direction for future cancer treatment, such as cancer vaccines for microorganisms. The effects of microorganisms on cancer are dual. The role of microorganisms, including bacteria, parasites, viruses, and fungi, in promoting cancer has been widely confirmed. However, the specific mechanism of their tumor suppressor effect, particularly the promotion of TLS formation, is currently unknown. In this review, we summarize the role of TLSs in cancer related to microbial infection and provide new ideas for further understanding their mechanisms of action in cancer.

Tertiary Lymphoid Structure in Tumor Microenvironment and Immunotherapy of Lung Cancer

Immune checkpoint inhibitors have opened an era of lung cancer therapy. However, a notable disparity exists in the efficacy of immunotherapy among individual patients. The tertiary lymphoid structure (TLS) is an ectopic lymphocyte aggregation that appears under pathological conditions and is the primary site of action for anti-tumor immunity. It is commonly reported that the presence of TLS within the tumor microenvironment (TME) relates to a favorable clinical prognosis and an excellent response to immunotherapy in lung cancer patients. A thorough understanding of TLS and its dynamic changes in TME has become an attractive focus for optimizing immunotherapy strategies for lung cancer. In this review, we comprehensively generalize the composition, formation, mechanism, detection methods of TLS, and summarize the role of TLS in lung cancer immunotherapy. Finally, induction of TLS is also discussed, which may provide more effective therapeutic strategies for lung cancer therapy.

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Analyzing the Spatial Distribution of Immune Cells in Lung Adenocarcinoma

(1) Background: This study investigates the tumor immune microenvironment, focusing on immune cell distribution in lung adenocarcinoma. (2) Methods: We evaluated fifty cases of lung adenocarcinoma, and suitable areas for further studies were annotated on the histological slides. Two tumor cores per case were obtained, one from the tumor's center and another from its periphery, and introduced into three paraffin receptor blocks for optimized processing efficiency. The 4-micrometer-thick tissue microarray sections were stained for H&E and for CD68, CD163, CD8, CD4, and PD-L1; (3) Results: Our investigation revealed significant correlations between PD-L1 expression in tumor cells and the presence of CD163+ macrophages, between CD4+ cells and CD8+, CD68+, and CD163+ cells, and also between CD8+ T cells and CD163+ cells. Additionally, while we observed some differences in cellular components and densities between the tumor center and periphery, these differences were not statistically significant. However, distinct correlations between PD-L1 and immune cells in these regions were identified, suggesting spatial heterogeneity in the immune landscape. (4) Conclusions: These results emphasize the intricate interactions between immune cells and tumor cells in lung adenocarcinoma. Understanding patient spatial immune profile could improve patient selection for immunotherapy, ensuring that those most likely to benefit are identified.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms

Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-β signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.

Increased Multiplexity in Optical Tissue Clearing-Based Three-Dimensional Immunofluorescence Microscopy of the Tumor Microenvironment by Light-Emitting Diode Photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy is transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only 3 or 4 cellular and noncellular TME components can be localized in cleared tumor tissue. Here we report a light-emitting diode (LED) photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through 3 work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Tea intake and lung diseases: a Mendelian randomization study

Background

Existing studies on the relationship between tea intake and lung diseases have yielded inconsistent results, leading to an ongoing dispute on this issue. The impact of tea consumption on the respiratory system remained elucidating.

Materials and methods

We conducted a two-sample Mendelian randomization (MR) study to evaluate the associations between five distinct tea intake phenotypes and 15 different respiratory outcomes using open Genome-wide association study (GWAS) data. The inverse variance weighted (IVW) was used for preliminary screening and a variety of complementary methods were used as sensitivity analysis to validate the robustness of MR estimates. Pathway enrichment analysis was used to explore possible mechanisms.

Results

IVW found evidence for a causal effect of standard tea intake on an increased risk of lung squamous cell cancer (LSCC) (OR = 1.004; 95% CI = 1.001-1.007; P = 0.00299). No heterogeneity or pleiotropy was detected. After adjustment for potential mediators, including smoking, educational attainment, and time spent watching television, the association was still robust in multivariable MR. KEGG and GO enrichment predicted proliferation and activation of B lymphocytes may play a role in this causal relation. No causalities were observed when evaluating the effect of other kinds of tea intake on various pulmonary diseases.

Conclusion

Our MR estimates provide causal evidence of the independent effect of standard tea intake (black tea intake) on LSCC, which may be mediated by B lymphocytes. The results implied that the population preferring black tea intake should be wary of a higher risk of LSCC.

Unveiling the impact of tertiary lymphoid structures on immunotherapeutic responses of clear cell renal cell carcinoma

Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that form under pathological conditions. However, the predictive value of TLS in clear cell renal cell carcinoma (ccRCC) for immunotherapies remains unclear. We comprehensively assessed the implications for prognosis and immunological responses of the TLS spatial and maturation heterogeneity in 655 ccRCC patients. A higher proportion of early-TLS was found in peritumoral TLS, while intratumoral TLS mainly comprised secondary follicle-like TLS (SFL-TLS), indicating markedly better survival. Notably, presence of TLS, especially intratumoral TLS and SFL-TLS, significantly correlated with better survival and objective reflection rate for ccRCC patients receiving anti-Programmed Cell Death Protein-1 (PD-1)/Programmed Cell Death-Ligand-1 (PD-L1) immunotherapies. In peritumoral TLS cluster, primary follicle-like TLS, the proportion of tumor-associated macrophages, and Treg infiltration in the peritumoral regions increased prominently, suggesting an immunosuppressive tumor microenvironment. Interestingly, spatial transcriptome annotation and multispectral fluorescence showed that an abundance of mature plasma cells within mature TLS has the capacity to produce IgA and IgG, which demonstrate significantly higher objective response rates and a superior prognosis for ccRCC patients subjected to immunotherapy. In conclusion, this study revealed the implications of TLS spatial and maturation heterogeneity on the immunological status and clinical responses, allowing the improvement of precise immunotherapies of ccRCC.

Increased multiplexity in optical tissue clearing-based 3D immunofluorescence microscopy of the tumor microenvironment by LED photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy have been transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only three or four cellular and non-cellular TME components can be localized in a cleared tumor tissue. Here we report a LED photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through three work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Identification of prognosis-related lncRNAs and cell validation in lung squamous cell carcinoma based on TCGA data

Objective

To discern long non-coding RNAs (lncRNAs) with prognostic relevance in the context of lung squamous cell carcinoma (LUSC), we intend to predict target genes by leveraging The Cancer Genome Atlas (TCGA) repository. Subsequently, we aim to investigate the proliferative potential of critical lncRNAs within the LUSC milieu.

Methods

DESeq2 was employed to identify differentially expressed genes within the TCGA database. Following this, we utilized both univariate and multivariate Cox regression analyses to identify lncRNAs with prognostic relevance. Noteworthy lncRNAs were selected for validation in cell lines. The intracellular localization of these lncRNAs was ascertained through nucleocytoplasmic isolation experiments. Additionally, the impact of these lncRNAs on cellular proliferation, invasion, and migration capabilities was investigated using an Antisense oligonucleotides (ASO) knockdown system.

Results

Multivariate Cox regression identified a total of 12 candidate genes, consisting of seven downregulated lncRNAs (BRE-AS1, CCL15-CCL14, DNMBP-AS1, LINC00482, LOC100129034, MIR22HG, PRR26) and five upregulated lncRNAs (FAM83A-AS1, LINC00628, LINC00923, LINC01341, LOC100130691). The target genes associated with these lncRNAs exhibit significant enrichment within diverse biological pathways, including metabolic processes, cancer pathways, MAPK signaling, PI3K-Akt signaling, protein binding, cellular components, cellular transformation, and other functional categories. Furthermore, nucleocytoplasmic fractionation experiments demonstrated that LINC00923 and LINC01341 are predominantly localized within the cellular nucleus. Subsequent investigations utilizing CCK-8 assays and colony formation assays revealed that the knockdown of LINC00923 and LINC01341 effectively suppressed the proliferation of H226 and H1703 cells. Additionally, transwell assays showed that knockdown of LINC00923 and LINC01341 significantly attenuated the invasive and migratory capacities of H226 and H1703 cells.

Conclusion

This study has identified 12 candidate lncRNA associated with prognostic implications, among which LINC00923 and LINC01341 exhibit potential as markers for the prediction of LUSC outcomes.

Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer

Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (αCD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict αCD40 treatment status and disease-free survival (DFS) following αCD40 therapy based upon TME features. Through downstream interpretation of the machine learning models' predictions, we found αCD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following αCD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of αCD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for αCD40-treated patients with PDAC.

Tertiary lymphoid structures and B cells: An intratumoral immunity cycle

The generation of anti-tumor immunity in the draining lymph nodes is known as the cancer immunity cycle. Accumulating evidence supports the occurrence of such a cycle at tumor sites in the context of chronic inflammation. Here, we review the role of tertiary lymphoid structures (TLS) in the generation of T and B cell immunities, focusing on the impact of B cells that undergo full maturation, resulting in the generation of plasma cells (PCs) producing high-affinity IgG and IgA antibodies. In this context, we propose that antibodies binding to tumor cells induce macrophage or natural killer (NK)-cell-dependent apoptosis. Subsequently, released antigen-antibody complexes are internalized and processed by dendritic cells (DCs), amplifying antigen presentation to T cells. Immune complexes may also be fixed by follicular DCs (FDCs) in TLS, thereby increasing memory B cell responses. This amplification loop creates an intra-tumoral immunity cycle, capable of increasing sensitivity of tumors to immunotherapy even in cancers with low mutational burden.

Promising immunotherapeutic targets in lung cancer based on single-cell RNA sequencing

Immunotherapy has made great strides in the treatment of lung cancer, but a significant proportion of patients still do not respond to treatment. Therefore, the identification of novel targets is crucial to improving the response to immunotherapy. The tumor microenvironment (TME) is a complex niche composed of diverse pro-tumor molecules and cell populations, making the function and mechanism of a unique cell subset difficult to understand. However, the advent of single-cell RNA sequencing (scRNA-seq) technology has made it possible to identify cellular markers and understand their potential functions and mechanisms in the TME. In this review, we highlight recent advances emerging from scRNA-seq studies in lung cancer, with a particular focus on stromal cells. We elucidate the cellular developmental trajectory, phenotypic remodeling, and cell interactions during tumor progression. Our review proposes predictive biomarkers and novel targets for lung cancer immunotherapy based on cellular markers identified through scRNA-seq. The identification of novel targets could help improve the response to immunotherapy. The use of scRNA-seq technology could provide new strategies to understand the TME and develop personalized immunotherapy for lung cancer patients.