Dynamics of peripheral T cell clones during PD-1 blockade in non-small cell lung cancer

[Advancements in Single-cell RNA Sequencing Technology in the Study of the Tumor Microenvironment in Lung Cancer]

The immune microenvironment plays a key role in the development and progression of tumors. In recent years, with the rapid advancement of high-throughput sequencing technologies, researchers have gained a deeper understanding of the composition and function of immune cells in the tumor microenvironment. However, traditional bulk sequencing technologies are limited in resolving heterogeneity at the single-cell level, constraining a comprehensive understanding of the complexity of the tumor microenvironment. The advent of single-cell RNA sequencing technology has brought new opportunities to uncover the heterogeneity of the immune microenvironment in lung cancer. Currently, T-cell-centered immunotherapy in clinical settings is prone to side effects affecting prognosis, such as immunogenic drug resistance or immune-related pneumonia, with the key factor being changes in the interactions between immune cells and tumor cells in the tumor microenvironment. Single-cell RNA sequencing technology can reveal the origins and functions of different subgroups within the tumor microenvironment from perspectives such as intercellular interactions and pseudotime analysis, thereby discovering new cell subgroups or novel biomarkers, providing new avenues for uncovering resistance to immunotherapy and monitoring therapeutic efficacy. This review comprehensively discusses the newest research techniques and advancements in single-cell RNA sequencing technology for unveiling the heterogeneity of the tumor microenvironment after lung cancer immunotherapy, offering insights for enhancing the precision and personalization of immunotherapy.
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Identification of JUN gene and cellular microenvironment in response to PD-1 blockade treatment in lung cancer patients via single-cell RNA sequencing

Exploring the molecular mechanisms of PD-1/PDL-1 blockade for non-small cell lung cancer (NSCLC) would facilitate understanding for tumor microenvironment (TME) and development of individualized medicine. To date, biomarkers of response to PD-1 blockade therapy were still limited. In this study, we hypothesize that cell type in the tumor microenvironment can influence the effect of PD-1 blockade immunotherapy through specific genes. Therefore, we re-analyze the single-cell RNA sequencing data and validation in tissue from lung adenocarcinoma patients. Dynamic changes of cellular subpopulation were observed after anti-PD-1 immunotherapy among TMEs between primary/metastasis or good/poor response patients. Non-exhausted CD8 T cells and dysregulated genes were observed in responsing patients from PD-1 blockade therapy. Among all changed genes, JUN, involved in PD-1 blockade immunotherapy pathway, and could be considered as a PD-1 responsing biomarker.

How single-cell techniques help us look into lung cancer heterogeneity and immunotherapy

Lung cancer patients tend to have strong intratumoral and intertumoral heterogeneity and complex tumor microenvironment, which are major contributors to the efficacy of and drug resistance to immunotherapy. From a new perspective, single-cell techniques offer an innovative way to look at the intricate cellular interactions between tumors and the immune system and help us gain insights into lung cancer and its response to immunotherapy. This article reviews the application of single-cell techniques in lung cancer, with focuses directed on the heterogeneity of lung cancer and the efficacy of immunotherapy. This review provides both theoretical and experimental information for the future development of immunotherapy and personalized treatment for the management of lung cancer.

CD39+ conventional CD4+ T cells with exhaustion traits and cytotoxic potential infiltrate tumors and expand upon CTLA-4 blockade

Conventional CD4+ T (Tconv) lymphocytes play important roles in tumor immunity; however, their contribution to tumor elimination remains poorly understood. Here, we describe a subset of tumor-infiltrating Tconv cells characterized by the expression of CD39. In several mouse cancer models, we observed that CD39+ Tconv cells accumulated in tumors but were absent in lymphoid organs. Compared to tumor CD39- counterparts, CD39+ Tconv cells exhibited a cytotoxic and exhausted signature at the transcriptomic level, confirmed by high protein expression of inhibitory receptors and transcription factors related to the exhaustion. Additionally, CD39+ Tconv cells showed increased production of IFNγ , granzyme B, perforin and CD107a expression, but reduced production of TNF. Around 55% of OVA-specific Tconv from B16-OVA tumor-bearing mice, expressed CD39. In vivo CTLA-4 blockade induced the expansion of tumor CD39+ Tconv cells, which maintained their cytotoxic and exhausted features. In breast cancer patients, CD39+ Tconv cells were found in tumors and in metastatic lymph nodes but were less frequent in adjacent non-tumoral mammary tissue and not detected in non-metastatic lymph nodes and blood. Human tumor CD39+ Tconv cells constituted a heterogeneous cell population with features of exhaustion, high expression of inhibitory receptors and CD107a. We found that high CD4 and ENTPD1 (CD39) gene expression in human tumor tissues correlated with a higher overall survival rate in breast cancer patients. Our results identify CD39 as a biomarker of Tconv cells, with characteristics of both exhaustion and cytotoxic potential, and indicate CD39+ Tconv cells as players within the immune response against tumors.

Tumor-infiltrating lymphocytes predict efficacy of immunotherapy in advanced non-small cell lung cancer: a single-center retrospective cohort study

BACKGROUND/PURPOSE

The current study aimed to investigate the correlation between tumor-infiltrating lymphocytes (TILs) and immunotherapy efficacy in patients with advanced non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Eighty-nine patients with advanced NSCLC who received immune checkpoint inhibitors (ICIs) monotherapy were retrospectively enrolled in this study. The density of TILs in paraffin-embedded pathological tissues taken before receiving ICIs was quantitatively analyzed by immunohistochemical staining. The density of TILs was treated as a dichotomous variable using the median as the cutoff value. The Kaplan-Meier analysis was used to assess survival differences between groups. Univariate and multivariate Cox analyses were applied to screen out independent prognostic factors and further construct a nomogram prediction model to predict survival.

RESULTS

Survival analysis showed that CD8+ TILs, CD4+ TILs, and IFN-γ+ Th1 were significant positive indicators for predicting progression-free survival (PFS) and overall survival (OS) (p < 0.05), whereas Foxp3+ Treg were a significant negative predictor (p < 0.05). The predictive role of IL-4+ Th2 was not apparent in this study and requires further investigation and exploration (p > 0.05). The nomogram prediction model exhibited good discriminative ability, with C-index values of 0.723 (95% CI 0.682-0.764) and 0.793 (95% CI, 0.738-0.848) in the training cohort and validation cohort, respectively. The AUC values indicated that the nomogram prediction model had high predictive value and the calibration curve presented good prediction accuracy.

CONCLUSIONS

TILs could predict the efficacy of immunotherapy and may become a promising predictor.

Single-cell RNA sequencing reveals enhanced antitumor immunity after combined application of PD-1 inhibitor and Shenmai injection in non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have altered the clinical management of non-small cell lung cancer (NSCLC). However, the low response rate, severe immune-related adverse events (irAEs), and hyperprogressive disease following ICIs monotherapy require attention. Combination therapy may overcome these limitations and traditional Chinese medicine with immunomodulatory effects provides a promising approach. Shenmai injection (SMI) is a clinically effective adjuvant treatment for cancer with chemotherapy and radiotherapy. Therefore, the combined effects and mechanisms of SMI and programmed death-1 (PD-1) inhibitor against NSCLC was focused on this study.

METHODS

A Lewis lung carcinoma mouse model and a lung squamous cell carcinoma humanized mouse model were used to investigate the combined efficacy and safety of SMI and PD-1 inhibitor. The synergistic mechanisms of the combination therapy against NSCLC were explored using single-cell RNA sequencing. Validation experiments were performed using immunofluorescence analysis, in vitro experiment, and bulk transcriptomic datasets.

RESULTS

In both models, combination therapy alleviated tumor growth and prolonged survival without increasing irAEs. The GZMA^high and XCL1^high natural killer (NK) cell subclusters with cytotoxic and chemokine signatures increased in the combination therapy, while malignant cells from combination therapy were mainly in the apoptotic state, suggesting that mediating tumor cell apoptosis through NK cells is the main synergistic mechanisms of combination therapy. In vitro experiment confirmed that combination therapy increased secretion of Granzyme A by NK cells. Moreover, we discovered that PD-1 inhibitor and SMI combination blocked inhibitory receptors on NK and T cells and restores their antitumoral activity in NSCLC better than PD-1 inhibitor monotherapy, and immune and stromal cells exhibited a decrease of angiogenic features and attenuated cancer metabolism reprogramming in microenvironment of combination therapy.

CONCLUSIONS

This study demonstrated that SMI reprograms tumor immune microenvironment mainly by inducing NK cells infiltration and synergizes with PD-1 inhibitor against NSCLC, suggested that targeting NK cells may be an important strategy for combining with ICIs. Video Abstract.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Peripheral changes in T cells predict efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer

The application of programmed cell death protein 1 (PD-1) antibodies has brought great benefits to non-small cell lung cancer (NSCLC) patients. Nevertheless, not all patients respond to anti-PD-1 immunotherapy. This study aimed to find response markers to predict efficacy of anti-PD-1 immunotherapy in NSCLC patients. 80 patients with NSCLC who would accept anti-PD-1 immunotherapy were recruited, and peripheral blood was obtained before and after treatment. Flow cytometry was used to detect proportions of circulating cell subsets and expression of co-stimulatory molecules, co-inhibitory molecules and cytokines in T cells from pre- and post-treatment patients. Results showed that proportions of CD4⁺ and CD8⁺ T cells, NK, γδT and mucosal-associated invariant T (MAIT) cells were higher and regulatory T cells (Tregs) were lower in responders (n = 50) after treatment but no obvious difference was found in non-responders (n = 30). After treatment, responders showed an increase in the frequency of co-stimulatory and co-inhibitory molecules, as well as the production of cytokines in T cells. This study indicates that monitoring the alterations of immune markers in circulating cells from NSCLC patients may be helpful to discriminate responders and non-responders, which provides a potential novel way to assess efficacy of anti-PD-1 immunotherapy.

PD-1 blockade and CDK4/6 inhibition augment nonoverlapping features of T cell activation in cancer

We performed single-cell RNA-sequencing and T cell receptor clonotype tracking of breast and ovarian cancer patients treated with the CDK4/6 inhibitor ribociclib and PD-1 blockade. We highlight evidence of two orthogonal treatment-associated phenomena: expansion of T cell effector populations and promotion of T cell memory formation. Augmentation of the antitumor memory pool by ribociclib boosts the efficacy of subsequent PD-1 blockade in mouse models of melanoma and breast cancer, pointing toward sequential therapy as a potentially safe and synergistic strategy in patients.

Hyperprogression of cutaneous T cell lymphoma after anti-PD-1 treatment

BACKGROUNDImmune checkpoint blockade is an emerging treatment for T cell non-Hodgkin's lymphoma (T-NHL), but some patients with T-NHL have experienced hyperprogression with undetermined mechanisms upon anti-PD-1 therapy.METHODSSingle-cell RNA-Seq, whole-genome sequencing, whole-exome sequencing, and functional assays were performed on primary malignant T cells from a patient with advanced cutaneous T cell lymphoma who experienced hyperprogression upon anti-PD-1 treatment.RESULTSThe patient was enrolled in a clinical trial of anti-PD-1 therapy and experienced disease hyperprogression. Single-cell RNA-Seq revealed that PD-1 blockade elicited a remarkable activation and proliferation of the CD4+ malignant T cells, which showed functional PD-1 expression and an exhausted status. Further analyses identified somatic amplification of PRKCQ in the malignant T cells. PRKCQ encodes PKCθ; PKCθ is a key player in the T cell activation/NF-κB pathway. PRKCQ amplification led to high expressions of PKCθ and p-PKCθ (T538) on the malignant T cells, resulting in an oncogenic activation of the T cell receptor (TCR) signaling pathway. PD-1 blockade in this patient released this signaling, derepressed the proliferation of malignant T cells, and resulted in disease hyperprogression.CONCLUSIONOur study provides real-world clinical evidence that PD-1 acts as a tumor suppressor for malignant T cells with oncogenic TCR activation.TRIAL REGISTRATIONClinicalTrials.gov (NCT03809767).FUNDINGThe National Natural Science Foundation of China (81922058), the National Science Fund for Distinguished Young Scholars (T2125002), the National Science and Technology Major Project (2019YFC1315702), the National Youth Top-Notch Talent Support Program (283812), and the Peking University Clinical Medicine plus X Youth Project (PKU2019LCXQ012) supported this work.

Case Report: Partial response to single-agent pembrolizumab in a chemotherapy-resistant metastatic pancreatic cancer patient with a high tumor mutation burden

Single-agent immune checkpoint blockade has shown no clinical benefits in pancreatic cancer. Recently, the programmed cell death protein 1 (PD-1) antibody pembrolizumab has been recommended as a treatment option for high tumor mutational burden (TMB) solid tumors based on the data from a basket trial. However, no pancreatic cancer patients were enrolled in that trial. Whether pancreatic cancer patients with high TMB respond to PD-1 blockade as well remains unclear. Here, we report a case with a partial response to single-agent immunotherapy with pembrolizumab in pancreatic cancer with high TMB after the failure of several lines of chemotherapy. This result indicates that single-agent immunotherapy may be effective in pancreatic cancer patients with high TMB. In addition, in order to understand the basic immune state of our patients, we also analyzed the changes in immune cells in peripheral blood with cytometry by time-of-flight mass spectrometry (CyTOF) before and after pembrolizumab treatment.

Diversity of immune checkpoints in cancer immunotherapy

Finding effective treatments for cancer remains a challenge. Recent studies have found that the mechanisms of tumor evasion are becoming increasingly diverse, including abnormal expression of immune checkpoint molecules on different immune cells, in particular T cells, natural killer cells, macrophages and others. In this review, we discuss the checkpoint molecules with enhanced expression on these lymphocytes and their consequences on immune effector functions. Dissecting the diverse roles of immune checkpoints in different immune cells is crucial for a full understanding of immunotherapy using checkpoint inhibitors.

Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

The development of combination immunotherapy based on the mediation of regulatory mechanisms of the tumor immune microenvironment (TIME) is promising. However, a deep understanding of tumor immunology must involve the systemic tumor immune environment (STIE) which was merely illustrated previously. Here, we aim to review recent advances in single-cell transcriptomics and spatial transcriptomics for the studies of STIE, TIME, and their interactions, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect. We review the evidence from preclinical and clinical studies related to TIME, STIE, and their significance on overall survival, through different immunomodulatory pathways, such as metabolic and neuro-immunological pathways. We also evaluate the significance of the STIE, TIME, and their interactions as well as changes after local radiotherapy and systemic immunotherapy or combined immunotherapy. We focus our review on the evidence of lung cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma, aiming to reshape STIE and TIME to enhance immunotherapy efficacy.

High-throughput single-сell sequencing in cancer research

With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

Single-cell immunology: Past, present, and future

The immune system is a complex, dynamic, and plastic ecosystem composed of multiple cell types that constantly sense and interact with their local microenvironment to protect from infection and maintain homeostasis. For over a century, great efforts and ingenuity have been applied to the characterization of immune cells and their microenvironments, but traditional marker-based and bulk technologies left key questions unanswered. In the past decade, the advent of single-cell genomic approaches has revolutionized our knowledge of the cellular and molecular makeup of the immune system. In this perspective, we outline the past, present, and future applications of single-cell genomics in immunology and discuss how the integration of multiomics at the single-cell level will pave the way for future advances in immunology research and clinical translation.

Analysis of the Diagnosis Model of Peripheral Non-Small-Cell Lung Cancer under Computed Tomography Images

This study aimed to explore the effect of deep learning models on lung CT image lung parenchymal segmentation (LPS) and the application value of CT image texture features in the diagnosis of peripheral non-small-cell lung cancer (NSCLC). Data of peripheral lung cancer (PLC) patients was collected retrospectively and was divided into peripheral SCLC group and peripheral NSCLC group according to the pathological examination results, ResNet50 model and feature pyramid network (FPN) algorithm were undertaken to improve the Mask-RCNN model, and after the MaZda software extracted the texture features of the CT images of PLC patients, the Fisher coefficient was used to reduce the dimensionality, and the texture features of the CT images were analyzed and compared. The results showed that the average Dice coefficients of the 2D CH algorithm, Faster-RCNN, Mask-RCNN, and the algorithm proposed in the validation set were 0.882, 0.953, 0.961, and 0.986, respectively. The accuracy rates were 88.3%, 93.5%, 94.4%, and 97.2%. The average segmentation speeds in lung CT images were 0.289 s/sheet, 0.115 s/sheet, 0.108 s/sheet, and 0.089 s/sheet. The improved deep learning model showed higher accuracy, better robustness, and faster speed than other algorithms in the LPS of CT images. In summary, deep learning can achieve the LPS of CT images and show excellent segmentation efficiency. The texture parameters of GLCM in CT images have excellent differential diagnosis performance for NSCLC and SCLC and potential clinical application value.

Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment

The lung tumor microenvironment, which is composed of heterogeneous cell populations, plays an important role in the progression of lung cancer and is closely related to therapeutic efficacy. Increasing evidence has shown that stromal components play a key role in regulating tumor invasion, metastasis and drug resistance. Therefore, a better understanding of stromal components in the tumor microenvironment is helpful for the diagnosis and treatment of lung cancer. Rapid advances in technology have brought our understanding of disease into the genetic era, and single-cell RNA sequencing has enabled us to describe gene expression profiles with unprecedented resolution, enabling quantitative analysis of gene expression at the single-cell level to reveal the correlations among heterogeneity, signaling pathways, drug resistance and microenvironment molding in lung cancer, which is important for the treatment of this disease. In this paper, several common single-cell RNA sequencing methods and their advantages and disadvantages are briefly introduced to provide a reference for selection of suitable methods. Furthermore, we review the latest progress of single-cell RNA sequencing in the study of stromal cells in the lung tumor microenvironment.

Systemic Immune Dysregulation Correlates With Clinical Features of Early Non-Small Cell Lung Cancer

Background

Systemic immune dysregulation correlates with cancer progression. However, the clinical implications of systemic immune dysregulation in early non-small cell lung cancer (NSCLC) remain unclear.

Methods

Using a panel of 9 markers to identify 12 parameters in the peripheral blood of 326 patients (34 in the discovery group and 292 in the validation group), we investigated systemic immune dysregulation in early NSCLC. Then, we analyzed the impact of surgery on the systemic immune state of these patients. Finally, we analyzed correlations between systemic immune dysregulation and the clinical features of early NSCLC.

Results

We found striking systemic immune dysregulation in the peripheral blood of early NSCLC patients. This dysregulation was characterized by a significant decrease in total lymphocytes, T cells, quiescent T cells, CD4+ T cells, and NKT cells. We also observed increased proportions of activated lymphocytes and activated T cells. Systemic immune dysregulation was increased after surgery. Furthermore, systemic immune dysregulation was correlated with multiple clinical features, such as sex, age, smoking history, pathological type, tumor stage, surgical approach, tumor differentiation, and epidermal growth factor receptor (EGFR) mutation. Finally, we observed that systemic immune dysregulation was correlated with complications and systemic inflammatory response syndrome (SIRS) in early NSCLC patients.

Conclusions

Our results reveal systemic immune dysregulation occurring in early NSCLC and demonstrate the correlation between these dysregulations and clinical features. Our findings suggest that systemic immune dysregulation is involved in cancer development and may be a promising candidate for high-risk screening and treatment strategies for early NSCLC.

Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges

Cancer has become one of the greatest threats to human health, and new technologies are urgently needed to further clarify the mechanisms of cancer so that better detection and treatment strategies can be developed. At present, extensive genomic analysis and testing of clinical specimens shape the insights into carcinoma. Nevertheless, carcinoma of humans is a complex ecosystem of cells, including carcinoma cells and immunity-related and stroma-related subsets, with accurate characteristics obscured by extensive genome-related approaches. A growing body of research shows that sequencing of single-cell RNA (scRNA-seq) is emerging to be an effective way for dissecting human tumor tissue at single-cell resolution, presenting one prominent way for explaining carcinoma biology. This review summarizes the research progress of scRNA-seq in the field of tumors, focusing on the application of scRNA-seq in tumor circulating cells, tumor stem cells, tumor drug resistance, the tumor microenvironment, and so on, which provides a new perspective for tumor research.

Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy

Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.

Single-Cell Sequencing, an Advanced Technology in Lung Cancer Research

Single-cell sequencing (SCS) which has an unprecedentedly high resolution is an advanced technique for cancer research. Lung cancer still has a high mortality and morbidity. For further understanding the lung cancer, SCS is also been applied to lung cancer research to investigate its heterogeneity, metastasis, drug resistance, tumor microenvironment and many other issues. In this review, we summarized lung cancer research using SCS and their research achievements.

Insights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment

Understanding tumor immune microenvironments is critical for identifying immune modifiers of cancer progression and developing cancer immunotherapies. Recent applications of single-cell RNA sequencing (scRNA-seq) in dissecting tumor microenvironments have brought important insights into the biology of tumor-infiltrating immune cells, including their heterogeneity, dynamics, and potential roles in both disease progression and response to immune checkpoint inhibitors and other immunotherapies. This review focuses on the advances in knowledge of tumor immune microenvironments acquired from scRNA-seq studies across multiple types of human tumors, with a particular emphasis on the study of phenotypic plasticity and lineage dynamics of immune cells in the tumor environment. We also discuss several imminent questions emerging from scRNA-seq observations and their potential solutions on the horizon.

The progress and challenge of anti-PD-1/PD-L1 immunotherapy in treating non-small cell lung cancer

The use of programmed cell-death protein 1 (PD-1)/programmed cell-death ligand 1 (PD-L1) inhibitors is the standard therapy for the first-line or second-line treatment of patients with non-small-cell lung cancer (NSCLC). In contrast to current traditional treatments such as chemotherapy or radiotherapy, anti-PD-1 and anti-PD-L1 treatments can directly attenuate tumour-mediated exhaustion and effectively modulate the host anti-tumour immune response in vivo. In addition, compared with traditional therapy, PD-1/PD-L1 inhibitor monotherapy can significantly prolong survival without obvious side effects in the treatment of advanced NSCLC. Ideally, several biomarkers could be used to monitor the safety and effectiveness of anti-PD-1 and anti-PD-L1 treatments; however, the current lack of optimal prognostic markers remains a widespread limitation and challenge for further clinical applications, as does the possibility of immune-related adverse events and drug resistance. In this review, we aimed to summarise the latest progress in anti-PD-1/anti-PD-L1 treatment of advanced NSCLC, worldwide, including in China. An exploration of underlying biomarker identification and future challenges will be discussed in this article to facilitate translational studies in cancer immunotherapy.