Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

Molecular and immunological features associated with long-term benefits in metastatic NSCLC patients undergoing immune checkpoint blockade

INTRODUCTION

Immunotherapy is firmly established as a treatment regimen in various solid tumors, driven by its exceptional benefits in a selected group of patients. Despite widespread adoption of immune checkpoint blockade (ICB) across diverse solid tumors, the quest for a clinically informative biomarker for long-term benefit remains unmet.

METHODS

A total of 49 patients with metastatic NSCLC treated with ICB were included. Long-term (LTR) and short-term responders (STR) were defined as those with a response to ICB lasting more than 24 months or less than 6 months, respectively. Longitudinal blood specimens were collected before ICB treatment initiation and early-on treatment. Plasma ctDNA next-generation sequencing panel (NGS) and serum proteomics were performed. GeoMx DSP on baseline tumor tissue was performed in a subset of patients.

RESULTS

Our analysis revealed specific characteristics of LTR compared with STR, namely higher PD-L1 in tumor cells (p = 0.005) and higher incidence of irAEs (p = 0.001). Genomic features associated with lack of benefit from ICB included co-occurring mutations in KRAS/STK11 and TP53/KMT2D (p < 0.05). At a baseline, LTR patients exhibited higher serum levels of proteins related with apoptosis (CASP8, PRKRA), chemotaxis, immune proteasome, processing of MHC class I (S100A4, PSMD9, RNF41) and immune homeostasis (HAVCR1, ARG1) (p < 0.05). Protein spatial profiling of tumor samples showed higher levels of proteins linked with the presence of immune cells (CD45), T cells (CD8), antigen presentation (HLA-DR) and immune regulation proteins (PD-L1, IDO1) within the tumor and tumor stroma component (p < 0.05) in LTR patients. Serum longitudinal analysis identified a set of proteins that presented distinct dynamics in LTR compared to STR, making them interesting candidates to evaluate as early predictors of treatment efficacy.

CONCLUSIONS

Our multimodal analysis of patients with metastatic NSCLC treated with ICB identified clinicopathological and immunological features associated with long-term benefits. The presence of preexisting antitumor immunity emerged as a strong predictor of long-term benefits, providing insights for potential biomarkers and therapeutic strategies for enhancing ICB outcomes in metastatic NSCLC.

Immunometabolism of tumor-associated macrophages: A therapeutic perspective

Tumor-associated macrophages (TAMs) play a pivotal role in the tumor microenvironment (TME), actively contributing to the formation of an immunosuppressive niche that fosters tumor progression. Consequently, there has been a growing interest in targeting TAMs as a promising avenue for cancer therapy. Recent advances in the field of immunometabolism have shed light on the influence of metabolic adaptations on macrophage physiology in the context of cancer. Here, we discuss the key metabolic pathways that shape the phenotypic diversity of macrophages. We place special emphasis on how metabolic reprogramming impacts the activation status of TAMs and their functions within the TME. Additionally, we explore alterations in TAM metabolism and their effects on phagocytosis, production of cytokines/chemokines and interaction with cytotoxic T and NK immune cells. Moreover, we examine the application of nanomedical approaches to target TAMs and assess the clinical significance of modulating the metabolism of TAMs as a strategy to develop new anti-cancer therapies. Taken together, in this comprehensive review article focusing on TAMs, we provide invaluable insights for the development of effective immunotherapeutic strategies and the enhancement of clinical outcomes for cancer patients.

Translating premalignant biology to accelerate non-small-cell lung cancer interception

Over the past decade, substantial progress has been made in the development of targeted and immune-based therapies for patients with advanced non-small-cell lung cancer. To further improve outcomes for patients with lung cancer, identifying and intercepting disease at the earliest and most curable stages are crucial next steps. With the recent implementation of low-dose computed tomography scan screening in populations at high risk, there is an emerging unmet need for new diagnostic, prognostic and therapeutic tools to help treat patients suspected of harbouring premalignant lesions and minimally invasive non-small-cell lung cancer. Continued advances in the identification of the earliest drivers of lung carcinogenesis are poised to address these unmet needs. Employing multimodal approaches to chart the temporal and spatial maps of the molecular events driving lung premalignant lesion progression will refine our understanding of early carcinogenesis. Elucidating the molecular drivers of premalignancy is critical to the development of biomarkers to detect those incubating a premalignant lesion, to stratify risk for progression to invasive cancer and to identify novel therapeutic targets to intercept that process. In this Review, we summarize emerging insights into the earliest cellular and molecular events associated with lung squamous and adenocarcinoma carcinogenesis and highlight the growing opportunity for translating these insights into clinical tools for early detection and disease interception to transform the outcomes for those at risk for lung cancer.

Heterogeneity of the tumor immune cell microenvironment revealed by single-cell sequencing in head and neck cancer

Head and neck cancer (HNC) is the sixth most common disease in the world. The recurrence rate of patients is relatively high, and the heterogeneity of tumor immune microenvironment (TIME) cells may be an important reason for this. Single-cell sequencing (SCS) is currently the most promising and mature application in cancer research. It can identify unique genes expressed in cells and study tumor heterogeneity. According to current research, the heterogeneity of immune cells has become an important factor affecting the occurrence and development of HNC. SCSs can provide effective therapeutic targets and prognostic factors for HNC patients through analyses of gene expression levels and cell heterogeneity. Therefore, this study analyzes the basic theory of HNC and the development of SCS technology, elaborating on the application of SCS technology in HNC and its potential value in identifying HNC therapeutic targets and biomarkers.

Decoding the role of lipid metabolism in NSCLC: From macrophage subtype identification to prognostic model development

Lipid metabolism plays a pivotal role in shaping the tumor microenvironment, particularly by influencing macrophage function. This study aimed to identify lipid-associated macrophage (LAM) marker genes involved in the onset and progression of non-small cell lung cancer (NSCLC) through integrated single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) analyses. Mutation and RNA-seq data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed to explore the relationship between lipid metabolism pathways and NSCLC progression. scRNA-seq analysis revealed macrophage subtypes closely associated with lipid metabolism, with three key marker genes-S100A10, HLA-DMB, and CTSL-identified as predictive factors for patient prognosis. A prognostic risk scoring model was constructed and validated using survival analysis and ROC curves, demonstrating high accuracy in stratifying NSCLC patients by risk. Further in vivo experiments using subcutaneous tumor xenografts and lung metastasis models showed that S100A10 and CTSL promoted tumor growth and metastasis, while HLA-DMB inhibited these processes. Immune infiltration analysis highlighted the immunological relevance of the identified marker genes, providing insights into their functional roles. This study underscores the critical influence of LAMs in NSCLC progression and highlights a robust prognostic model that offers potential therapeutic targets for improving patient outcomes.

Risk Factors for Lymph Node Metastasis in Stage pT1 Invasive Lung Adenocarcinoma

OBJECTIVE

To analyze the risk factors for lymph node metastasis (LNM) in patients with stage pT1 lung adenocarcinoma to select a more appropriate surgical option.

METHODS

In this retrospective study, 294 patients with postoperative pathologically confirmed stage pT1 invasive lung adenocarcinoma were collected and divided into two groups according to whether they had mediastinal or hilar LNM. Patient tumor imaging, pathological features and gene mutations were analyzed, and risk factors that might predict LNM were derived via univariate and multivariate logistic analyses. LNM-related variables were screened by Boruta and least absolute shrinkage and selection operator regression analysis.

RESULTS

Among the 294 patients, 45 (15.3%) had positive mediastinal or hilar lymph nodes. There were no significant differences between the two groups in terms of sex, age, or underlying disease. The difference in the percentage of solidity between the two groups was significant, with the higer percentage group showing a more significant difference. The results of multivariate logistic analysis revealed that a high percentage of solid components and wild-type epidermal growth factor receptor (EGFR) were risk factors for LNM. The nomogram for predicting LNM included the consolidation tumor ratio, tumor size, micropapillary and EGFR, with an area under the curve of 93.4% (95% CI: 88.7-99.1) in the derivation cohort and 92.3% (95% CI: 84.6-99.9) in the validation cohort.

CONCLUSIONS

A high proportion of solid components and wild-type EGFR were risk factors for pT1 stage lung adenocarcinoma, suggesting that the choice of lung segmentectomy needs to be evaluated and selected more cautiously.

Immune atlas of pituitary neuroendocrine tumors highlights endocrine-driven immune signature and therapeutic implication

Whether the tumor microenvironment is shaped by endocrine hormone secretion, as well as its cellular heterogeneity and therapeutic implications in pituitary neuroendocrine tumors (pitNETs), remains poorly understood. We demonstrate that pitNETs exhibit a sparse immune infiltration. Mass cytometry of 97,418 immune cells from 56 pitNETs establishes a high-resolution atlas, with macrophages and T cells comprising the predominant populations. Hormone secretion status dictates the immune composition and cellular phenotype. Functioning pitNETs are enriched with T cells, with robust expression of immune-suppressive markers CD38, programmed death (PD)-1, and PD-L1. The lymphoid-enriched microenvironment is associated with shorter progression-free survival in patients with pitNETs. Integrating PD-1 blockade with tumor-targeted therapy in functioning pitNETs demonstrates synergistic efficacy with enhanced apoptosis, induces cell-cycle arrest, and suppresses hormone secretion using patient-derived primary cell cultures. Altogether, our findings provide an extended resource on the cellular and functional heterogeneity of the pitNET immune microenvironment and offer a conceptual framework for rational therapeutic strategies.

Development of a reliable risk prognostic model for lung adenocarcinoma based on the genes related to endotheliocyte senescence

Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, clinical information and mutation data of LUAD patients collected from the TCGA and GEO database, we obtained 102 endotheliocyte senescence-related genes. The "ConsensusClusterPlus" R package was employed for unsupervised cluster analysis, and the "limma" was used for the differentially expressed gene (DEG) analysis. A prognosis model was created by univariate and multivariate Cox regression analysis combined with Lasso regression utilizing the "survival" and "glmnet" packages. KM survival and receiver operator characteristic curve analyses were conducted applying the "survival" and "timeROC" packages. "MCPcounter" package was used for immune infiltration analysis. Immunotherapy response analysis was performed based on the IMvigor210 and GSE78220 cohort, and drug sensitivity was predicted by the "pRRophetic" package. Cell invasion and migration were tested by carrying out Transwell and wound healing assays. According to the results, a total of 32 genes related to endotheliocyte senescence were screened to assign patients into C1 and C2 subtypes. The C2 subtype showed a significantly worse prognosis and an overall higher somatic mutation frequency, which was associated with increased activation of cancer pathways, including Myc_targets2 and angiogenesis. Then, based on the DEGs between the two subtypes, we constructed a five-gene RiskScore model with a strong classification effectiveness for short- and long-term OS prediction. High- and low-risk groups of LUAD patients were classified by the RiskScore. High-risk patients, characterized by lower immune infiltration, had poorer outcomes in both training and validation datasets. The RiskScore was associated with the immunotherapy response in LUAD. Finally, we found that potential drugs such as Cisplatin can benefit high-risk LUAD patients. In-vitro experiments demonstrated that silencing of Angiopoietin-like 4 (ANGPTL4), Gap Junction Protein Beta 3 (GJB3), Family with sequence similarity 83-member A (FAM83A), and Anillin (ANLN) reduced the number of invasive cells and the wound healing rate, while silencing of solute carrier family 34 member 2 (SLC34A2) had the opposite effect. This study, collectively speaking, developed a prognosis model with senescence signature genes to facilitate the diagnosis and treatment of LUAD.

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

Dendritic cell maturation in cancer

Dendritic cells (DCs) are specialized antigen-presenting cells that are present at low abundance in the circulation and tissues; they serve as crucial immune sentinels by continually sampling their environment, migrating to secondary lymphoid organs and shaping adaptive immune responses through antigen presentation. Owing to their ability to orchestrate tolerogenic or immunogenic responses to a specific antigen, DCs have a pivotal role in antitumour immunity and the response to immune checkpoint blockade and other immunotherapeutic approaches. The multifaceted functions of DCs are acquired through a complex, multistage process called maturation. Although the role of inflammatory triggers in driving DC maturation was established decades ago, less is known about DC maturation in non-inflammatory contexts, such as during homeostasis and in cancer. The advent of single-cell technologies has enabled an unbiased, high-dimensional characterization of various DC states, including mature DCs. This approach has clarified the molecular programmes associated with DC maturation and also revealed how cancers exploit these pathways to subvert immune surveillance. In this Review, we discuss the mechanisms by which cancer disrupts DC maturation and highlight emerging therapeutic opportunities to modulate DC states. These insights could inform the development of DC-centric immunotherapies, expanding the arsenal of strategies to enhance antitumour immunity.

Recent advancements in lung cancer research: a narrative review

Background and Objective

Lung cancer remains the leading cause of cancer-related mortality worldwide, with a 5-year survival rate ranging from 10% to 20%. The majority of cases are categorized as non-small cell lung cancer (NSCLC) (80%) and small cell lung cancer (SCLC) (20%), with NSCLC being the more prevalent type. Tobacco use, particularly cigarette smoking, is a significant contributor to over 80% of lung cancer cases. Early diagnosis is challenging due to limitations in screening methods, resulting in many cases being identified only in advanced stages. Moreover, current treatment options often exhibit low efficacy, partly due to an inadequate understanding of the disease's pathogenesis. This narrative review aims to summarize recent discoveries and advancements in lung cancer research, focusing on improvements in diagnosis, treatment, and understanding of the disease.

Methods

A comprehensive literature review was performed utilizing the PubMed Central database to identify recent studies relevant to lung cancer. This review synthesizes findings from various research articles to provide a cohesive summary of advancements in the field.

Key Content and Findings

In the past decade, notable progress has been achieved in lung cancer research, particularly concerning diagnostics and treatment strategies. Novel therapeutic approaches, including immunotherapy and genomic-targeted therapies, have demonstrated promising results. Understanding the tumor microenvironment (TME) and the role of T lymphocytes has become crucial for developing effective treatments. Additionally, advancements in immune checkpoint inhibitors (ICIs) have shown potential in enhancing patient outcomes. Improvements in tumor detection technologies are also anticipated to facilitate earlier diagnosis, ultimately contributing to better survival rates.

Conclusions

Significant strides have been made in lung cancer research over the last ten years, particularly in diagnostics and treatment methodologies. Future research should prioritize exploring the TME, the function of T lymphocytes, and the efficacy of ICIs while continuing to innovate in tumor detection technologies. Such efforts are essential for enhancing treatment outcomes and improving the overall quality of life for lung cancer patients.

DNA Origami Scaffold-Based Peptide-Major Histocompatibility Complex Multimers for Spatial Imaging of T Cells

Visualizing the spatial distribution of antigen-specific T cells is essential for understanding immune responses and improving therapeutic strategies. However, detecting low-affinity antigen-specific T cells and enhancing signals from low-abundance populations remain challenging due to limitations in sensitivity. Here, we report DNA origami scaffold-based peptide-major histocompatibility complex multimers (DOS-pMHCs) with precise spatial organization of pMHC and signaling molecules on the nanoscale for enhanced in situ visualization of antigen-specific T cells. The two-dimensional triangular DNA origami precisely organizes pMHCs and signaling molecules with high valency, significantly improving binding to antigen-specific T cells and signal amplification. These DOS-pMHCs facilitate enhanced visualization of antigen-specific T cells in lymphoid tissues compared to traditional tetramers. Moreover, we show that DOS-pMHCs enable the in situ detection of autoimmune T cells with lower affinity T cell receptors (TCRs), which are difficult to identify using traditional tetramers. This in situ detection strategy provides a powerful tool for mapping the spatial distribution of antigen-specific T cells, thus holding great potential for advancing our understanding of immune responses and guiding personalized immunotherapy.

Tissue-specific properties of type 1 dendritic cells in lung cancer: implications for immunotherapy

Checkpoint inhibitors have led to remarkable benefits in non-small cell lung cancer (NSCLC), yet response rates remain below expectations. High-dimensional analysis and mechanistic experiments in clinical samples and relevant NSCLC models uncovered the immune composition of lung cancer tissues, providing invaluable insights into the functional properties of tumor-infiltrating T cells and myeloid cells. Among myeloid cells, type 1 conventional dendritic cells (cDC1s) stand out for their unique ability to induce effector CD8 T cells against neoantigens and coordinate antitumoral immunity. Notably, lung resident cDC1 are particularly abundant and long-lived and express a unique tissue-specific gene program, underscoring their central role in lung immunity. Here, we discuss recent insights on the induction and regulation of antitumoral T cell responses in lung cancer, separating it from the tissue-agnostic knowledge generated from heterogeneous tumor models. We focus on the most recent studies dissecting functional states and spatial distribution of lung cDC1 across tumor stages and their impact on T cell responses to neoantigens. Finally, we highlight relevant gaps and emerging strategies to harness lung cDC1 immunostimulatory potential.

Prediction of pathological complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer using 18F-FDG PET radiomics features of primary tumour and lymph nodes

BACKGROUND

Predicting the response to neoadjuvant chemoimmunotherapy in patients with resectable non-small cell lung cancer (NSCLC) facilitates clinical treatment decisions. Our study aimed to establish a machine learning model that accurately predicts the pathological complete response (pCR) using 18F-FDG PET radiomics features.

METHODS

We retrospectively included 210 patients with NSCLC who completed neoadjuvant chemoimmunotherapy and subsequently underwent surgery with pathological results, categorising them into a training set of 147 patients and a test set of 63 patients. Radiomic features were extracted from the primary tumour and lymph nodes. Using 10-fold cross-validation with the least absolute shrinkage and selection operator method, we identified the most impactful radiomic features. The clinical features were screened using univariate and multivariate analyses. Machine learning models were developed using the random forest method, leading to the establishment of one clinical feature model, one primary tumour radiomics model, and two fusion radiomics models. The performance of these models was evaluated based on the area under the curve (AUC).

RESULTS

In the training set, the three radiomic models showed comparable AUC values, ranging from 0.901 to 0.925. The clinical model underperformed, with an AUC of 0.677. In the test set, the Fusion_LN1LN2 model achieved the highest AUC (0.823), closely followed by the Fusion_Lnall model with an AUC of 0.729. The primary tumour model achieved a moderate AUC of 0.666, whereas the clinical model had the lowest AUC at 0.631. Additionally, the Fusion_LN1LN2 model demonstrated positive net reclassification improvement and integrated discrimination improvement values compared with the other models, and we employed the SHapley Additive exPlanations methodology to interpret the results of our optimal model.

CONCLUSIONS

Our fusion radiomics model, based on 18F-FDG-PET, will assist clinicians in predicting pCR before neoadjuvant chemoimmunotherapy for patients with resectable NSCLC.

IL-33-Induced TREM2+ Macrophages Promote Pathological New Bone Formation Through CREG1-IGF2R Axis in Ankylosing Spondylitis

Pathological new bone formation is the main cause of disability in ankylosing spondylitis (AS), and so far, it lacks a targeted therapy. Macrophages are central orchestrators of inflammation progression and tissue remodeling, but their contribution to pathological new bone formation has largely not been explored. Here, it is identified that TREM2+ macrophages predominated within the sites of new bone formation and adjacent to osteogenic precursor cells. In vivo, both depletion of macrophages and knockout of Trem2 significantly reduced pathological new bone formation in a collagen antibody-induced arthritis (CAIA) model. Specifically, TREM2+ macrophages promoted osteogenic differentiation of ligament-derived progenitor cells (LDPCs) by secreting CREG1, a secretory glycoprotein involved in cell differentiation and normal physiology. CREG1-IGF2R-PI3K-AKT signaling pathway is involved in TREM2+ macrophage-mediated pathological new bone formation. In addition, it is found that IL-33 promoted TREM2+ macrophage differentiation through phosphorylation of STAT6. Targeting the above signalings alleviated new bone formation in the CAIA model. The findings highlight the critical role of IL-33-induced TREM2+ macrophages in pathological new bone formation and provide potential therapeutic targets for halting spinal ankylosis in AS.

Targeting cGAS-STING pathway for reprogramming tumor-associated macrophages to enhance anti-tumor immunotherapy

The cyclic GMP-AMP synthase (cGAS)-stimulator interferon genes (STING) signaling pathway plays a crucial role in activating innate and specific immunity in anti-tumor immunotherapy. As the major infiltrating cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) could be polarized into either anti-tumor M1 or pro-tumor M2 types based on various stimuli. Accordingly, targeted reprogramming TAMs to restore immune balance shows promise as an effective anti-tumor strategy. In this review, we aim to target cGAS-STING pathway for reprogramming TAMs to enhance anti-tumor immunotherapy. We investigated the double-edged sword effects of cGAS-STING in regulating TME. The regulative roles of cGAS-STING pathway in TAMs and its impact on the TME were further revealed. More importantly, several strategies of targeting cGAS-STING for reprogramming TAMs were designed for enhancing anti-tumor immunotherapy. Taken together, targeting cGAS-STING pathway for reprogramming TAMs in TME might be a promising strategy to enhance anti-tumor immunotherapy.

Cross-Talk Between Cancer and Its Cellular Environment-A Role in Cancer Progression

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

Unveiling the link between chronic inflammation and cancer

The highly nuanced transition from an inflammatory process to tumorigenesis is of great scientific interest. While it is well known that environmental stimuli can cause inflammation, less is known about the oncogenic modifications that chronic inflammation in the tissue microenvironment can bring about, as well as how these modifications can set off pro-tumorigenic processes. It is clear that no matter where the environmental factors come from, maintaining an inflammatory microenvironment encourages carcinogenesis. In addition to encouraging angiogenesis and metastatic processes, sustaining the survival and proliferation of malignant transformed cells, and possibly altering the efficacy of therapeutic agents, inflammation can negatively regulate the antitumoral adaptive and innate immune responses. Because chronic inflammation has multiple pathways involved in tumorigenesis and metastasis, it has gained recognition as a marker of cancer and a desirable target for cancer therapy. Recent advances in our knowledge of the molecular mechanisms that drive cancer's progression demonstrate that inflammation promotes tumorigenesis and metastasis while suppressing anti-tumor immunity. In many solid tumor types, including breast, lung, and liver cancer, inflammation stimulates the activation of oncogenes and impairs the body's defenses against the tumor. Additionally, it alters the microenvironment of the tumor. As a tactical approach to cancer treatment, these findings have underscored the importance of targeting inflammatory pathways. This review highlights the role of inflammation in cancer development and metastasis, focusing on its impact on tumor progression, immune suppression, and therapy resistance. It examines current anti-inflammatory strategies, including NSAIDs, cytokine modulators, and STAT3 inhibitors, while addressing their potential and limitations. The review emphasizes the need for further research to unravel the complex mechanisms linking inflammation to cancer progression and identify molecular targets for specific cancer subtypes.

Intratumoral Heterogeneity and Immune Microenvironment in Hepatoblastoma Revealed by Single-Cell RNA Sequencing

Hepatoblastoma (HB) is a common paediatric liver malignancy characterised by significant intratumoral heterogeneity and a complex tumour microenvironment (TME). Using single-cell RNA sequencing (scRNA-seq), we analysed 43,592 cells from three tumour regions and adjacent normal tissue of an HB patient. Our study revealed distinct cellular compositions and varying degrees of malignancy across different tumour regions, with the T1 region showing the highest malignancy and overexpression of HMGB2 and TOP2A. Survival analysis demonstrated that high HMGB2 expression is associated with poor prognosis and increased recurrence, suggesting its potential as a prognostic marker. Additionally, we identified a diverse immune microenvironment enriched with regulatory T cells (Tregs) and CD8+ effector memory T cells (Tem), indicating potential immune evasion mechanisms. Notably, CTLA-4 and PD-1 were highly expressed in Tregs and Tem cells, highlighting their potential as immunotherapy targets. Myeloid cells, including Kupffer cells and dendritic cells, also exhibited distinct functional roles in different tumour regions. This study provides the first comprehensive single-cell atlas of HB, revealing critical insights into its intratumoral heterogeneity and immune microenvironment. Our findings not only advance the understanding of HB biology but also offer new directions for precision medicine, including the development of targeted therapies and immunotherapeutic strategies to improve patient outcomes.

Single-cell profiling and clinical characteristics analysis of lung squamous carcinoma

Lung squamous carcinoma (LUSC) is a highly heterogeneous disease. However, the tumor microenvironment (TME) landscape and clinical characteristics for LUSC have not yet been elucidated. To map the TME and clinical characteristics of LUSC, we performed single-cell RNA sequencing for 504 LUSC samples on basis of TCGA and Gene Expression Omnibus. We introduced the computational algorithms "ESTIMATE" and "CIBERSORT" to analyze immune cell infiltration and immune-checkpoint-related gene signatures in various LUSC clusters. Weighted gene co-expression network analysis was used to explore the connections between molecular characteristics and clinical traits in LUSC. A prognostic model was constructed by performing multivariate COX. Two gene clusters exhibiting disparate immune and clinical characteristics were identified. Our findings indicate that patients in cluster 2, who have a more favorable prognosis, exhibit immune characteristics such as elevated levels of immunosuppression-associated M2 macrophages, resting memory CD4 T cells, resting dendritic cells (DC), and TNFRSF4, alongside reduced infiltration of activated DC and lower expression of TNFRSF18.Whereafter, the Risk Score model was built on basis of 3-DEGs signature consisted of cystatin C (CST3), transglutaminase type 2 (TGM2), JUN, which were proved by q-PCR and immunofluorescence. Besides, high-Risk Score may be responsible for poor prognosis in LUSC patients. Our study identified that tumor-infiltrating immune cell subtypes and the Risk Score model might shed light on the heterogeneity in LUSC patients. The TME, three DEGs and Risk Score can effectively serve as biomarkers to elucidate the immune landscape and predict prognosis in LUSC patients. They may provide insights to the investigations on therapeutic strategies for LUSC.

Dynamic changes in immune repertoire profiles in patients with stage III unresectable non-small cell lung cancer during consolidation treatment with immunotherapy

BACKGROUND

One-year of immune checkpoint inhibitor (ICI) treatment after concurrent chemoradiation (CCRT) in unresectable stage III non-small cell lung cancer (NSCLC) is a standard of care. The precise predictive biomarkers are under investigations either immunological markers or clinical characteristics. Here, we explored immune repertoire of T cell receptor β-chain (TCRβ) during ICI treatment.

METHODS

During August 2019 and September 2021, stage III NSCLC, post CCRT patients from Ramathibodi Hospital was enrolled. All patients were treated by durvalumab after CCRT. Blood samples were collected together with clinical data and tumor assessment every 3-4 months until disease progression or discontinuation of treatment due to adverse events. CDR3 region and TCRΒ polymorphisms was explored by RNA sequencing using Next-Generation Sequencing (NGS) TCR beta short-read assay. Bioinformatic analysis was performed to analyze clonal diversity, TCR convergence frequency and the Shannon diversity from each timepoint. Immune repertoire and clinical correlation were explored using Spearman's correlation and Pearson's correlation. RStudio software version 2021 build 372 was used for analyses. A significance level was at P < 0.05.

RESULTS

Forty-four blood samples from 12 patients were analyzed. Mean duration of durvalumab treatment was 284 days. After durvalumab treatment, increasing of TCR convergence frequency was found compared to baseline (R = 0.36). Interestingly, it was also significantly higher in non-progressive disease (non-PD) patients compared with progressive disease (PD) patients (P = 0.011). Furthermore, Shannon diversity was higher increasing in PD patients compared with non-PD patients. Taken together, our study found that increasing of TCR convergence with less T-cell diversity in non-PD patients probably demonstrated a T cell-specific clonal expansion response to durvalumab treatment in this population.

CONCLUSIONS

TCRβ repertoire is the potential biomarker for predicting durvalumab treatment response in post CCRT stage III NSCLC patients. However, a larger cohort with long-read assay should be explored.

Characterization of immune phenotypes in peripheral blood of adult renal transplant recipients using mass cytometry (CyTOF)

Chronic immunosuppressive therapies are crucial in organ transplantation but can increase the risk of opportunistic infections and cancer over time. We investigated immune status changes in 10 kidney transplant patients and 11 age-matched healthy adults using broad in vitro stimulation of subject-derived peripheral blood mononuclear cells followed by mass cytometry by time of flight over 6 mo. Overall, the immune cells of transplant patients exhibited increased CD8+ T cell activation and differentiation compared with healthy donors, with elevated CD8+ CD57+, MIP-1β, and interferon γ production (P < 0.05, P < 0.05, and P < 0.01, respectively). CD107a and granzyme B expression were increased in CD8+ T cells and CD56bright natural killer cells (P < 0.05 and P < 0.01, respectively), while T regulatory cells had decreased interleukin-10 production (P < 0.05). These changes indicated a proinflammatory environment influenced by induction therapy and ongoing maintenance drugs. Additionally, transplant recipients displayed signs of immune modulation, including decreased tumor necrosis factor α, interferon γ, and MIP-1β expression in γδT cells (P < 0.05 and P < 0.01), and reduced interleukin-17 and granulocyte-macrophage colony-stimulating factor expression in CD8+ T memory cell subsets (P < 0.05). The diverse functional changes underscore the importance of comprehensive immune status profiling for optimizing individual treatment strategies and developing better immunosuppressants that specifically target activated cell populations.

TREM2 Depletion in Pancreatic Cancer Elicits Pathogenic Inflammation and Accelerates Tumor Progression via Enriching IL-1β+ Macrophages

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDAC) has a complex tumor microenvironment enriched with tumor-associated macrophages. Triggering receptor expressed on myeloid cells 2 (TREM2) is highly expressed by a subset of macrophages in PDAC. However, the functional role of TREM2 in PDAC progression remains elusive.

METHODS

We generated a novel transgenic mouse model (KPPC;Trem2-/-) that enables the genetic depletion of TREM2 in the context of spontaneous PDAC development. Single-cell RNA-sequencing analysis was used to identify changes in the tumor immune microenvironment on TREM2 depletion. We evaluated the impacts of TREM2 depletion on the tumor immune microenvironment to elucidate the functions of TREM2 in macrophages and PDAC development.

RESULTS

Unexpectedly, genetic depletion of TREM2 significantly accelerated spontaneous PDAC progression and shortened the survival of KPPC;Trem2-/- mice. Single-cell analysis revealed that TREM2 depletion enhanced proinflammatory macrophages and exacerbated pathogenic inflammation in PDAC. Specifically, TREM2 functions as a key braking mechanism for the NLRP3/nuclear factor-κB/interleukin (IL)-1β inflammasome pathway, opposing to microbial lipopolysaccharide as the key activator of this pathway. TREM2 deficiency orchestrated with microbial lipopolysaccharide to trigger IL-1β upregulation and pathogenic inflammation, thereby fueling PDAC development. Notably, IL-1β inhibition or microbiome ablation not only reversed the accelerated PDAC progression caused by TREM2 depletion, but also further inhibited PDAC progression in the TREM2-depleted context.

CONCLUSIONS

TREM2 depletion accelerates tumor progression by enhancing proinflammatory macrophages and IL-1β-mediated pathogenic inflammation in PDAC. The accelerated tumor progression by TREM2 depletion can be reversed by blocking IL-1β-associated pathogenic inflammation.

Orthogonally Engineered Bacteria Capture Metabolically Labeled Tumor Antigens to Improve the Systemic Immune Response in Irradiated Tumors

In situ vaccination is considered a promising cancer immunotherapy strategy to elicit a tumor-specific T cell response. Live bacteria effectively enhanced the immune response in irradiated tumors as it can activate multiple immune cells. However, the adaptive immune response remains low since bacteria lack the efficient delivery of antigen to dendritic cells (DCs). Here, we show that tumor antigens can be metabolically labeled with azido groups in situ, allowing for their specific capture by orthogonally engineered Salmonella via bioorthogonal chemistry. Subsequently, these antigens are efficiently delivered to DCs through the active movement of the bacteria. Intratumorally injected engineered bacteria captured the labeled antigens and improved their presentation by DCs. This increased the proportion of antigen-specific CD8+ T cells in tumors, further resulting in systemic antitumor effects in the bilateral melanoma mouse model. The antitumor effects were abrogated in Batf3-/- mice or after CD8+ T cell depletion, indicating that systemic antitumor effects were dependent on adaptive immune responses. Overall, our work presents a strategy combining bacterial engineering and antigen labeling, which may guide the development of in situ vaccines in the future.

Dynamic monocyte changes as prognostic indicators in operable gastric cancer: a retrospective cohort analysis

Objective

This study aims to elucidate the relationship between postoperative monocyte count and gastric cancer prognosis. We introduce a standardized monocyte ratio (MMR) to predict postoperative survival rates in gastric cancer patients effectively.

Methods

A test cohort was created to develop and evaluate the pre- and postoperative MMR as a mortality predictor in gastric cancer patients. We used Kaplan-Meier survival analysis, complemented by univariate and multivariate analyses. The predictive utility of MMR was assessed via time-dependent ROC curves and decision-curve analysis.

Results

The sample distributions in both cohorts were similar. The MMR showed high predictive value and significant clinical benefits in 1, 3, and 5-year overall survival (OS) assessments. These findings enhance understanding of prognosis and aid in developing more precise treatment plans.

Conclusions

MMR is confirmed as an independent factor in predicting overall survival in gastric cancer patients, proving to be a reliable and cost-effective prognostic indicator.

Patients With Immunoglobulin A Nephropathy Show Abnormal Frequencies of B Cell Subsets, Unconventional T Cells, and High Levels of Galactose-Deficient IgA1-Coated Gut Bacteria

Introduction

Mucosal inflammation is involved in the pathophysiology of immunoglobulin-A nephropathy (IgAN); however, peripheral immune phenotype analyses of patients with IgAN often do not include unconventional T cells, the major subset in mucosal immunity.

Methods

We measured serum total IgA, galactose-deficient IgA1 (gd-IgA1), secretory IgA (SIgA), B cell-activating factor (BAFF), and A proliferation-inducing ligand (APRIL) in 66 patients with IgAN and 30 healthy controls (HCs). We also quantified the total IgA and gd-IgA1 in stool supernatant along with the same coated on bacteria. In 35 patients and 14 controls, we performed extensive phenotyping using cytometry by Time-of-Flight (CyTOF) of circulating immune cells, including unconventional T cells (mucosal associated invariant T [MAIT] cells, γδ T, and natural killer [NK] T cells). The results were validated using RNAseq data from a larger cohort of 179 patients with IgAN, 140 patients with minimal change disease, and 91 HCs.

Results

Patients with IgAN had higher circulating levels of total IgA, gd-IgA1, and APRIL, and higher IgA and gd-IgA1-coated gut bacteria than controls, whereas serum levels of SIgA and BAFF did not differ between groups. Patients with IgAN showed more class-switched memory (CSM) and double negative (DN) B cells than controls. MAIT cells and γδ T cells were significantly lower, and CD4-CD8- NK T cells were significantly higher in patients with IgAN than in HCs. We validated the significant decrease in MAIT cells in an independent cohort of patients with IgAN.

Conclusion

The data indicate that patients with IgAN have increased circulating CSM and DN B cells associated with abnormal T cell immunity, involving defects in unconventional T cell frequency. This may suggest putative alterations at mucosal sites because of cell migration leading to altered IgA production.

Single-cell RNA-seq analysis reveals microenvironmental infiltration of myeloid cells and pancreatic prognostic markers in PDAC

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a heterogeneous make-up of myeloid cells that influences the therapeutic response and prognosis. However, understanding the myeloid cell at both a genetic and cellular level remains a significant challenge.

METHODS

Single-cell RNA sequencing (scRNA-seq) data were downloaded from t the Tumor Immune Single-cell Hub and gene expression data were retrieved from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Gene set variation analysis (GSVA) was used to estimate the relative proportions of each cell type based on the signatures identified by scRNA-seq or previous literature. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was performed to evaluate the abundance of immune infiltrating cells. For further analysis, LASSO and Cox analyses were used to construct a risk model using univariate Cox regression.

RESULTS

Using the scRNA-seq dataset, we identified 7 clusters of myeloid cells, and these clusters were assigned a cell type based on their marker genes. In addition, the results of the CellChat analysis and SCENIC analysis indicate that TAM-spp1 cells may promote the migration of pancreatic tumor cells on different levels. Moreover, the TAM-spp1 cell is most closely related to poor prognoses. An 8-gene risk model was constructed by using univariate Cox and LASSO analyses. In the GEO cohorts, this risk model demonstrated excellent predictive abilities for prognosis. Further, patients with high-risk scores had a lower likelihood of benefiting from immunotherapy.

CONCLUSION

Using bulk RNA-seq and single-cell RNA-seq, we analyzed myeloid heterogeneity at the single-cell level, and we developed an 8-gene model that predicts survival outcomes and immunotherapy response in PADC.

Tumor suppressor genotype influences the extent and mode of immunosurveillance in lung cancer

The impact of cancer driving mutations in regulating immunosurveillance throughout tumor development remains poorly understood. To better understand the contribution of tumor genotype to immunosurveillance, we generated and validated lentiviral vectors that create an epi-allelic series of increasingly immunogenic neoantigens. This vector system is compatible with autochthonous Cre-regulated cancer models, CRISPR/Cas9-mediated somatic genome editing, and tumor barcoding. Here, we show that in the context of KRAS-driven lung cancer and strong neoantigen expression, tumor suppressor genotype dictates the degree of immune cell recruitment, positive selection of tumors with neoantigen silencing, and tumor outgrowth. By quantifying the impact of 11 commonly inactivated tumor suppressor genes on tumor growth across neoantigenic contexts, we show that the growth promoting effects of tumor suppressor gene inactivation correlate with increasing sensitivity to immunosurveillance. Importantly, specific genotypes dramatically increase or decrease sensitivity to immunosurveillance independently of their growth promoting effects. We propose a model of immunoediting in which tumor suppressor gene inactivation works in tandem with neoantigen expression to shape tumor immunosurveillance and immunoediting such that the same neoantigens uniquely modulate tumor immunoediting depending on the genetic context.

One Sentence Summary

Here we uncover an under-appreciated role for tumor suppressor gene inactivation in shaping immunoediting upon neoantigen expression.

Tissue-resident immune cells: from defining characteristics to roles in diseases

Tissue-resident immune cells (TRICs) are a highly heterogeneous and plastic subpopulation of immune cells that reside in lymphoid or peripheral tissues without recirculation. These cells are endowed with notably distinct capabilities, setting them apart from their circulating leukocyte counterparts. Many studies demonstrate their complex roles in both health and disease, involving the regulation of homeostasis, protection, and destruction. The advancement of tissue-resolution technologies, such as single-cell sequencing and spatiotemporal omics, provides deeper insights into the cell morphology, characteristic markers, and dynamic transcriptional profiles of TRICs. Currently, the reported TRIC population includes tissue-resident T cells, tissue-resident memory B (BRM) cells, tissue-resident innate lymphocytes, tissue-resident macrophages, tissue-resident neutrophils (TRNs), and tissue-resident mast cells, but unignorably the existence of TRNs is controversial. Previous studies focus on one of them in specific tissues or diseases, however, the origins, developmental trajectories, and intercellular cross-talks of every TRIC type are not fully summarized. In addition, a systemic overview of TRICs in disease progression and the development of parallel therapeutic strategies is lacking. Here, we describe the development and function characteristics of all TRIC types and their major roles in health and diseases. We shed light on how to harness TRICs to offer new therapeutic targets and present burning questions in this field.

SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma

Non-small cell lung adenocarcinoma (LUAD) is a markedly heterogeneous disease, with its underlying molecular mechanisms and prognosis prediction presenting ongoing challenges. In this study, we integrated data from multiple public datasets, including TCGA, GSE31210, and GSE13213, encompassing a total of 867 tumor samples. By employing Mendelian randomization (MR) analysis, machine learning techniques, and comprehensive bioinformatics approaches, we conducted an in-depth investigation into the molecular characteristics, prognostic markers, and potential therapeutic targets of LUAD. Our analysis identified 321 genes significantly associated with LUAD, with CENP-A, MCM7, and DLGAP5 emerging as highly connected nodes in network analyses. By performing correlation analysis and Cox regression analysis, we identified 26 prognostic genes and classified LUAD samples into two molecular subtypes with significantly distinct survival outcomes. The Random Survival Forest (RSF) model exhibited robust prognostic predictive capabilities across multiple independent cohorts (AUC > 0.75). Beyond merely predicting patient outcomes, this model also captures key features of the tumor immune microenvironment and potential therapeutic responses. Functional enrichment analysis revealed the complex interplay of cell cycle regulation, DNA repair, immune response, and metabolic reprogramming in the progression of LUAD. Furthermore, we observed a strong correlation between risk scores and the expression of specific cytokines, such as CCL17, CCR2, and CCL20, suggesting novel avenues for developing cytokine network-based therapeutic strategies. This study offers fresh insights into the molecular subtyping, prognostic prediction, and personalized therapeutic decision-making in LUAD, laying a critical foundation for future clinical applications and targeted therapy research.

TLR7: A Key Prognostic Biomarker and Immunotherapeutic Target in Lung Adenocarcinoma

Background: The tumor microenvironment (TME) plays a crucial role in the progression of lung adenocarcinoma (LUAD). However, understanding its dynamic immune and stromal modulation remains a complex challenge. Methods: We utilized the ESTIMATE algorithm to evaluate the immune and stromal components of the LUAD TME from the TCGA database. Correlations between these components and clinical characteristics and patient prognosis were analyzed. Toll-like receptor 7 (TLR7) was identified as a key prognostic biomarker through PPI network and COX regression analysis. Validation of TLR7 expression was conducted using GEO data, qPCR, WB, and IHC. A prognostic model was developed using a nomogram, incorporating TLR7 expression. Enrichment analysis, the Tumor Immune Estimation Resource database, and single-sample gene set enrichment analysis were used to explore TLR7's potential function. The response of the TLR7 subgroup to immunotherapy and drug sensitivity was observed. Results: We found significant associations between the immune and stromal components of LUAD TME and clinical features and prognosis. Specifically, TLR7 was identified as a prognostic biomarker, where lower expression in tumor tissues was linked to worse outcomes. This finding was further confirmed by comparing TLR7 expression in LUAD cells to normal bronchial epithelial cells, revealing lower expression in the tumor cells. Incorporating TLR7 into a nomogram prognostic model resulted in a good predictor of patient survival. Additionally, TLR7 was associated with immune function and positively correlated with various immune cells. Importantly, patients with high TLR7 expression were more likely to benefit from anti-PD-1 checkpoint blockade therapy. We also identified four treatment candidates for patients with high TLR7 expression. Conclusion: TLR7 is a powerful clinical feature that predicts patient prognosis, immunotherapeutic response, and drug candidates, providing additional insights for the treatment of LUAD.

Molecular and cellular dynamics of squamous cell carcinomas across tissues

Squamous cell carcinomas (SCCs), arising from the skin, head and neck, lungs, esophagus, and cervix, are collectively among the most common cancers and a frequent cause of cancer morbidity and mortality. Despite distinct stratified epithelial tissues of origin, converging evidence points toward shared biologic pathways across SCCs. With recent breakthroughs in molecular technologies have come novel SCC treatment paradigms, including immunotherapies and targeted therapy. This review compares commonalities and differences across SCCs from different anatomical sites, including risk factors and genetics, as well as cellular and molecular programs driving tumorigenesis. We review landmark discoveries of the "cancer stem cells" (CSCs) that initiate and propagate SCCs and their gene and translational regulation programs. This has led to an appreciation that interactions between CSCs and the immune system play key roles in invasion and therapeutic resistance. Here, we review the unifying principles of SCCs that have emerged from these exciting advances in our understanding of these epithelial cancers.

Spatial and single-cell transcriptomics reveal cellular heterogeneity and a novel cancer-promoting Treg cell subset in human clear-cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common histologic type of RCC. However, the spatial and functional heterogeneity of immunosuppressive cells and the mechanisms by which their interactions promote immunosuppression in the ccRCC have not been thoroughly investigated.

METHODS

To further investigate the cellular and regional heterogeneity of ccRCC, we analyzed single-cell and spatial transcriptome RNA sequencing data from four patients, which were obtained from samples from multiple regions, including the tumor core, tumor-normal interface, and distal normal tissue. On the basis, the findings were investigated in vitro using tissue and blood samples from 15 patients with ccRCC and validated in the broader samples on tissue microarrays.

RESULTS

In this study, we revealed previously unreported subsets of both stromal and immune cells, as well as mapped their spatial location at finer resolution. In addition, we validated the clusters of tumor cells after removing batch effects according to six characterized gene sets, including epithelial-mesenchymal transitionhigh clusters, metastatic clusters and proximal tubulehigh clusters. Importantly, we identified a special regulatory T (Treg) cell subpopulation that has the molecular characteristics of terminal effector Treg cells but expresses multiple cytokines, such as interleukin (IL)-1β and IL-18. This group of Treg cells has stronger immunosuppressive function and was associated with a worse prognosis in ccRCC cohorts. They were colocalized with MRC1 + FOLR2 + tumor-associated macrophages (TAMs) at the tumor-normal interface to form a positive feedback loop, maintaining a synergistic procarcinogenic effect. In addition, we traced the origin of IL-1β+ Treg cells and revealed that IL-18 can induce the expression of IL-1β in Treg cells via the ERK/NF-κB pathway.

CONCLUSIONS

We demonstrated a novel cancer-promoting Treg cell subset and its interactions with MRC1 + FOLR2 +TAMs, which provides new insight into Treg cell heterogeneity and potential therapeutic targets for ccRCC.

Research progress and the prospect of using single-cell sequencing technology to explore the characteristics of the tumor microenvironment

In precision cancer therapy, addressing intra-tumor heterogeneity poses a significant obstacle. Due to the heterogeneity of each cell subtype and between cells within the tumor, the sensitivity and resistance of different patients to targeted drugs, chemotherapy, etc., are inconsistent. Concerning a specific tumor type, many feasible treatments or combinations can be used by specifically targeting the tumor microenvironment. To solve this problem, it is necessary to further study the tumor microenvironment. Single-cell sequencing techniques can dissect distinct tumor cell populations by isolating cells and using statistical computational methods. This technology may assist in the selection of targeted combination therapy, and the obtained cell subset information is crucial for the rational application of targeted therapy. In this review, we summarized the research and application advances of single-cell sequencing technology in the tumor microenvironment, including the most commonly used single-cell genomic and transcriptomic sequencing, and their future development direction was proposed. The application of single-cell sequencing technology has been expanded to include epigenomics, proteomics, metabolomics, and microbiome analysis. The integration of these different omics approaches has significantly advanced the development of single-cell multiomics sequencing technology. This innovative approach holds immense potential for various fields, such as biological research and medical investigations. Finally, we discussed the advantages and disadvantages of using single-cell sequencing to explore the tumor microenvironment.

Programmed cell death pathways in lung adenocarcinoma: illuminating tumor drug resistance and therapeutic opportunities through single-cell analysis

Lung adenocarcinoma (LUAD) is a major contributor to cancer-related deaths, distinguished by its pronounced tumor heterogeneity and persistent challenges in overcoming drug resistance. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to dissect the roles of programmed cell death (PCD) pathways, including apoptosis, necroptosis, pyroptosis, and ferroptosis, in shaping LUAD heterogeneity, immune infiltration, and prognosis. Among these, ferroptosis and pyroptosis were most significantly associated with favorable survival outcomes, highlighting their potential roles in enhancing anti-tumor immunity. Distinct PCD-related LUAD subtypes were identified, characterized by differential pathway activation and immune cell composition. Subtypes enriched with cytotoxic lymphocytes and dendritic cells demonstrated improved survival outcomes and increased potential responsiveness to immunotherapy. Drug sensitivity analysis revealed that these subtypes exhibited heightened sensitivity to targeted therapies and immune checkpoint inhibitors, suggesting opportunities for personalized treatment strategies. Our findings emphasize the interplay between PCD pathways and the tumor microenvironment, providing insights into the mechanisms underlying tumor drug resistance and immune evasion. By linking molecular and immune features to clinical outcomes, this study highlights the potential of targeting PCD pathways to enhance therapeutic efficacy and overcome resistance in LUAD. These results contribute to a growing framework for developing precise and adaptable cancer therapies tailored to specific tumor characteristics.

Plasticity and Tumor Microenvironment in Pancreatic Cancer: Genetic, Metabolic, and Immune Perspectives

Cancer has long been believed to be a genetic disease caused by the accumulation of mutations in key genes involved in cellular processes. However, recent advances in sequencing technology have demonstrated that cells with cancer driver mutations are also present in normal tissues in response to aging, environmental damage, and chronic inflammation, suggesting that not only intrinsic factors within cancer cells, but also environmental alterations are important key factors in cancer development and progression. Pancreatic cancer tissue is mostly comprised of stromal cells and immune cells. The desmoplasmic microenvironment characteristic of pancreatic cancer is hypoxic and hypotrophic. Pancreatic cancer cells may adapt to this environment by rewiring their metabolism through epigenomic changes, enhancing intrinsic plasticity, creating an acidic and immunosuppressive tumor microenvironment, and inducing noncancerous cells to become tumor-promoting. In addition, pancreatic cancer has often metastasized to local and distant sites by the time of diagnosis, suggesting that a similar mechanism is operating from the precancerous stage. Here, we review key recent findings on how pancreatic cancers acquire plasticity, undergo metabolic reprogramming, and promote immunosuppressive microenvironment formation during their evolution. Furthermore, we present the following two signaling pathways that we have identified: one based on the small G-protein ARF6 driven by KRAS/TP53 mutations, and the other based on the RNA-binding protein Arid5a mediated by inflammatory cytokines, which promote both metabolic reprogramming and immune evasion in pancreatic cancer. Finally, the striking diversity among pancreatic cancers in the relative importance of mutational burden and the tumor microenvironment, their clinical relevance, and the potential for novel therapeutic strategies will be discussed.

Biomarkers and potential therapeutic targets driving progression of non-alcoholic steatohepatitis to hepatocellular carcinoma predicted through transcriptomic analysis

Background

Non-alcoholic steatohepatitis (NASH) is the most prevalent chronic liver condition globally, with potential progression to cirrhosis, and even hepatocellular carcinoma (HCC). The increasing prevalence of NASH underscores the urgent need for advanced diagnostic and therapeutic strategies. Despite its widespread impact, effective treatments to prevent the progression of NASH remain elusive, highlighting the critical importance of innovative molecular techniques in both the diagnosis and management of this disease.

Methods

Six microarray datasets available in GEO were used to perform Robust Rank Aggregation (RRA) to identify differentially expressed genes (DEGs).We identified 62 robust upregulated genes and 24 robust downregulated genes. These genes were undergone Gene Ontology enrichment analysis and further examination for expression correlation with NAS score. Molecular subtypes were generated using "ConsensusClusterPlus" on identified genes, which were further assessed for tumor stage relevance, expression differences in adjacent and tumor tissues, and impact on survival in TCGA liver cancer patients. Single-cell analysis was then used to explore the genes across different cell types and subgroups as well as cell-type interactions. The clinical utility of predicted core genes was highlighted through decision curve analysis, with emphasis on HCC prognosis. The GDSC database was used to evaluate the relationship between the predicted core genes and drug sensitivity, while the TIDE database was used to evaluate their relationship with immunotherapy.

Results

Four core genes, TREM2, GDF15, TTC39A, and ANXA2, were identified as key to influencing HCC prognosis and therapy responsiveness, especially immune treatment efficacy in NASH-associated HCC.

Conclusion

The core genes may act as critical biomarkers driving the progression of NASH to HCC. They are potential novel targets for the diagnosis and treatment of NASH progression, offering innovative perspectives for its clinical management.

A minimalist multifunctional nano-prodrug for drug resistance reverse and integration with PD-L1 mAb for enhanced immunotherapy of hepatocellular carcinoma

Clinical treatment of hepatocellular carcinoma (HCC) with 5-fluorouracil (5-FU), the primary anticancer agent, remains unsatisfactory due to the glutathione (GSH)-associated drug resistance and immunosuppressive microenvironment of HCC. To develop a facile yet robust strategy to overcome 5-FU resistance for enhanced immunotherapy treatment of HCC via all dimensional GSH exhaustion, we report in this study construction of a minimalist prodrug consisting of 5-FU linked to an indoleamine-(2,3)-dioxygenase (IDO) inhibitor (IND) via a disulfide bridge, FU-SS-IND that can further self-assemble into stabilized nanoparticles, FU-SS-IND NPs. Specifically, besides the disulfide linker-induced GSH exhaustion, IND inhibits GSH biosynthesis and enhances the effector function of T cells for turning a "cold" tumor to a "hot" one, which synergistically achieving a tumor inhibition rate (TIR) of 92.5% in a 5-FU resistant mice model. Most importantly, FU-SS-IND NPs could upregulate programmed death ligand 1 (PD-L1) expression on the surface of tumor cells, which enables facile combination with immune checkpoint blockade (ICB) for a ultimate prolonged survival lifetime of 5-FU-resistant tumors-bearing mice. Overall, the minimalist bioreducible nano-prodrug developed herein demonstrates great translatable potential for efficiently reversing drug resistance and enhancing immunotherapy of HCC.

Integrated single-cell transcriptome and TCR profiles of hepatocellular carcinoma highlight the convergence on interferon signaling during immunotherapy

BACKGROUND

Despite the success of immune checkpoint inhibitor (ICI)-based combination therapies in hepatocellular carcinoma (HCC), its effectiveness remains confined to a subset of patients. The development of reliable, predictive markers is important for accurate patient stratification and further mechanistic understanding of therapy response.

METHODS

We comprehensively analyzed paired single-cell RNA transcriptome and T-cell repertoire profiles from 14 HCC ascites samples, collected from 7 patients before and after treatment with the combination of sintilimab (anti-PD-1) and bevacizumab (anti-VEGF).

RESULTS

We identify a widespread convergence on interferon (IFN) signaling across various immune cell lineages in treatment-responsive patients with HCC, indicating a common transcriptional state transition in the immune microenvironment linked to immunotherapy response in HCC. Strong IFN signaling marks CD8+ T cells with larger clonal expansion and enhanced cytotoxicity, macrophages toward M1-like polarization and strong T-cell recruitment ability, dendritic cells with increased antigen presentation capacity, as well as highly cytotoxic natural killer cells and activated B cells. By translating our finding to cohorts of patients with HCC, we demonstrate the specificity of IFN-signaling in the prognosis of patients with HCC and its ability to predict immunotherapy response.

CONCLUSIONS

This study provides a unique single-cell resource with clonal and longitudinal resolution during ICI therapy and reveals IFN signaling as a biomarker of immunotherapy response in HCC, suggesting a beneficial effect by combining IFN inducers with ICIs for patients with HCC.

Multifaceted Aspects of Dysfunctional Myelopoiesis in Cancer and Therapeutic Perspectives with Focus on HCC

Myelopoiesis provides for the formation and continued renewal of cells belonging primarily to the innate immune system. It is a highly plastic process that secures the response to external and internal stimuli to face acute and changing needs. Infections and chronic diseases including cancer can modulate it by producing several factors, impacting proliferation and differentiation programs. While the lymphocytic compartment has attracted major attention due to the role of adaptive immunity in anticancer immune response, in recent years, research has found convincing evidence that confirms the importance of innate immunity and the key function played by emergency myelopoiesis. Due to cancer's ability to manipulate myelopoiesis to its own advantage, the purpose of this review is to outline myelopoiesis processes within the tumor microenvironment and suggest possible therapeutic lines of research to restore the physiological functioning of the host's immune system, with a special outlook on hepatocellular carcinoma (HCC).

The JAK-STAT signaling-related signature serves as a prognostic and predictive biomarker for renal cell carcinoma immunotherapy

Renal cell carcinoma (RCC) represents a significant portion of genitourinary cancers, marked by challenging prognosis and high metastasis rates. Immunotherapy has been applied in managing advanced renal cell carcinoma, but the therapeutic outcomes are unsatisfactory. In this study, we order to construct a Janus kinase/signal transduction and activator transcriptional (JAK/STAT)-related signature linked to kidney patient outcomes for better predicting the efficacy to immune checkpoint inhibitors (ICIs) and to provide guidance for effective combination therapy. We screened 25 differentially expressed genes (DEGs) that exhibited high expression in RCC samples and were enriched in the JAK-STAT signaling pathway. Among these genes, 11 key genes were identified and correlated with the expectation of Kidney Clear Cell Carcinoma (KIRC) patients and all these genes was significantly elevated in RCC tumor tissues and cancer cells compared to para-cancer tissues and normal renal cells. Utilizing these 11 genes, we divided RCC patients into high-risk and low-risk groups. We found a clear correlation between the clinicopathologic factors of KIRC patients and the JAK-STAT-related risk score. And the IHC results shown that the JAK3 and STAT4 expression of tumor was significantly higher than normal tissue in RCC patients, the level of JAK3 and STAT4 was positively related to the T stage of RCC patients. In addition, high-risk patients had a poorer prognosis and greater protumor immune cell infiltration, and benefitted less from immunotherapy than did low-risk patients. Furthermore, the JAK-STAT-related risk score can predict disease-free survival (DFS) in RCC patients according to the nomogram, which constructed in combination with other clinical features such as age, TNM-staging and stage. Our study demonstrated the JAK-STAT signaling pathway's important regulatory function in RCC tumor immunity. This insight not only enhances our ability to accurately predict the survival rate of RCC patients, but also underscores a potential therapeutic alternative for RCC, involving the combined targeting of the JAK-STAT pathway and immune checkpoints.

Single-cell proteomics delineates murine systemic immune response to blast lung injury

Victims of explosive events frequently suffer from blast lung injuries. Immune system has been implicated in the pathogenesis of this disease. However, systemic immune responses underlying the progression and recovery of injury repair remain poorly understood. Here, we depict the systemic landscape of immune dysregulation during blast lung injury and uncover immune recovery patterns. Single-cell analyses reveal dramatic changes in neutrophils, macrophages, monocytes, dendritic cells, and eosinophils after a gas explosion, along with early involvement of CD4 T, CD8 T, and Th17 cells. We demonstrate that myeloid cells primarily exert functions during the acute phase, while the spleen serves as an alternative source of granulocytes. Granulopoiesis is initiated in the bone marrow at a later stage during blast lung injury recovery, rather than at the acute stage. These findings contribute to a better understanding of the pathogenesis and provide valuable insights for potential immune interventions in blast lung injury.

Macrophage diversity in cancer dissemination and metastasis

Invasion and metastasis are hallmarks of cancer. In addition to the well-recognized hematogenous and lymphatic pathways of metastasis, cancer cell dissemination can occur via the transcoelomic and perineural routes, which are typical of ovarian and pancreatic cancer, respectively. Macrophages are a universal major component of the tumor microenvironment and, in established tumors, promote growth and dissemination to secondary sites. Here, we review the role of tumor-associated macrophages (TAMs) in cancer cell dissemination and metastasis, emphasizing the diversity of myeloid cells in different tissue contexts (lungs, liver, brain, bone, peritoneal cavity, nerves). The generally used models of lung metastasis fail to capture the diversity of pathways and tissue microenvironments. A better understanding of TAM diversity in different tissue contexts may pave the way for tailored diagnostic and therapeutic approaches.

Circadian rhythms of macrophages are altered by the acidic tumor microenvironment

Tumor-associated macrophages (TAMs) are prime therapeutic targets due to their pro-tumorigenic functions, but varying efficacy of macrophage-targeting therapies highlights our incomplete understanding of how macrophages are regulated within the tumor microenvironment (TME). The circadian clock is a key regulator of macrophage function, but how circadian rhythms of macrophages are influenced by the TME remains unknown. Here, we show that conditions associated with the TME such as polarizing stimuli, acidic pH, and lactate can alter circadian rhythms in macrophages. While cyclic AMP (cAMP) has been reported to play a role in macrophage response to acidic pH, our results indicate pH-driven changes in circadian rhythms are not mediated solely by cAMP signaling. Remarkably, circadian disorder of TAMs was revealed by clock correlation distance analysis. Our data suggest that heterogeneity in circadian rhythms within the TAM population level may underlie this circadian disorder. Finally, we report that circadian regulation of macrophages suppresses tumor growth in a murine model of pancreatic cancer. Our work demonstrates a novel mechanism by which the TME influences macrophage biology through modulation of circadian rhythms.

The evolution of immune profiling: will there be a role for nanoparticles?

Immune profiling provides insights into the functioning of the immune system, including the distribution, abundance, and activity of immune cells. This understanding is essential for deciphering how the immune system responds to pathogens, vaccines, tumors, and other stimuli. Analyzing diverse immune cell types facilitates the development of personalized medicine approaches by characterizing individual variations in immune responses. With detailed immune profiles, clinicians can tailor treatment strategies to the specific immune status and needs of each patient, maximizing therapeutic efficacy while minimizing adverse effects. In this review, we discuss the evolution of immune profiling, from interrogating bulk cell samples in solution to evaluating the spatially-rich molecular profiles across intact preserved tissue sections. We also review various multiplexed imaging platforms recently developed, based on immunofluorescence and imaging mass spectrometry, and their impact on the field of immune profiling. Identifying and localizing various immune cell types across a patient's sample has already provided important insights into understanding disease progression, the development of novel targeted therapies, and predicting treatment response. We also offer a new perspective by highlighting the unprecedented potential of nanoparticles (NPs) that can open new horizons in immune profiling. NPs are known to provide enhanced detection sensitivity, targeting specificity, biocompatibility, stability, multimodal imaging features, and multiplexing capabilities. Therefore, we summarize the recent developments and advantages of NPs, which can contribute to advancing our understanding of immune function to facilitate precision medicine. Overall, NPs have the potential to offer a versatile and robust approach to profile the immune system with improved efficiency and multiplexed imaging power.

Cold and hot tumors: from molecular mechanisms to targeted therapy

Immunotherapy has made significant strides in cancer treatment, particularly through immune checkpoint blockade (ICB), which has shown notable clinical benefits across various tumor types. Despite the transformative impact of ICB treatment in cancer therapy, only a minority of patients exhibit a positive response to it. In patients with solid tumors, those who respond well to ICB treatment typically demonstrate an active immune profile referred to as the "hot" (immune-inflamed) phenotype. On the other hand, non-responsive patients may exhibit a distinct "cold" (immune-desert) phenotype, differing from the features of "hot" tumors. Additionally, there is a more nuanced "excluded" immune phenotype, positioned between the "cold" and "hot" categories, known as the immune "excluded" type. Effective differentiation between "cold" and "hot" tumors, and understanding tumor intrinsic factors, immune characteristics, TME, and external factors are critical for predicting tumor response and treatment results. It is widely accepted that ICB therapy exerts a more profound effect on "hot" tumors, with limited efficacy against "cold" or "altered" tumors, necessitating combinations with other therapeutic modalities to enhance immune cell infiltration into tumor tissue and convert "cold" or "altered" tumors into "hot" ones. Therefore, aligning with the traits of "cold" and "hot" tumors, this review systematically delineates the respective immune characteristics, influencing factors, and extensively discusses varied treatment approaches and drug targets based on "cold" and "hot" tumors to assess clinical efficacy.

Trial watch: anticancer vaccination with dendritic cells

Dendritic cells (DCs) are critical players at the intersection of innate and adaptive immunity, making them ideal candidates for anticancer vaccine development. DC-based immunotherapies typically involve isolating patient-derived DCs, pulsing them with tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs), and utilizing maturation cocktails to ensure their effective activation. These matured DCs are then reinfused to elicit tumor-specific T-cell responses. While this approach has demonstrated the ability to generate potent immune responses, its clinical efficacy has been limited due to the immunosuppressive tumor microenvironment. Recent efforts have focused on enhancing the immunogenicity of DC-based vaccines, particularly through combination therapies with T cell-targeting immunotherapies. This Trial Watch summarizes recent advances in DC-based cancer treatments, including the development of new preclinical and clinical strategies, and discusses the future potential of DC-based vaccines in the evolving landscape of immuno-oncology.

Immune signatures of patients with advanced non-small-cell lung cancer for efficacy prediction after immunotherapy

Background

Programmed cell death protein 1 ligand 1 (PD-L1) expression alone may not be the optimal predictor of immunotherapy (IO) efficacy in advanced non-small cell lung cancer (NSCLC). Evaluation of circulating immune signatures using mass cytometry is a promising technique for predicting IO response and prognosis. The utility of circulating immune signatures for efficacy prediction after IO in advanced NSCLC remains to be elucidated.

Objectives

To assess the feasibility of circulating immune cells and cytokines in predicting tumor response to IO in advanced NSCLC.

Design

A prospective observational study.

Methods

To investigate dynamic changes in immune signatures, blood specimens were prospectively collected from patients with NSCLC at baseline and following chemotherapy (C/T) and/or IO. Mass cytometry and enzyme-linked immunosorbent assay were used to characterize immune signatures and cytokine patterns to identify correlations between immune profiles and treatment efficacy.

Results

The study enrolled 45 patients. The proportion of circulating natural killer (NK) cells and CD8+ T cells significantly increased after IO alone treatment. Cell levels of PD-1+CD8+ T cells, PD-1+CD4+ T cells, TIM-3+CD8+ T cells, LAG-3+ NK cells, and LAG-3+CD8+ T cells significantly decreased in patients with treatment response to IO alone. Tumor necrosis factor-alpha (TNF-α) levels significantly increased after IO alone treatment. Patients with high PD-1+CD8+ T cells before IO alone treatment had lower overall survival (OS) compared to those with low levels. Patients with high LAG-3+CD8+ T cells before chemotherapy plus immunotherapy treatment had lower OS compared to those with low levels.

Conclusion

Responses to IO in NSCLC were correlated with declines in specific exhausted T cells, suggesting that IO may exert therapeutical efficacy by decreasing circulating exhausted T cells, which were associated with poorer survival, while also increasing TNF-α. These results highlight the prognostic value of monitoring changes in circulating exhausted T cells to predict IO response and survival outcomes in advanced lung cancer.

Protein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment

Lung cancer remains the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and the presence of metastases. Several countries around the world have adopted nation-wide LDCT-based lung cancer screening that will benefit patients, shifting the stage at diagnosis to earlier stages with more therapeutic options. Biomarkers can help to optimize the screening process, as well as refine the TNM stratification of lung cancer patients, providing information regarding prognostics and recommending management strategies. Moreover, novel adjuvant strategies will clearly benefit from previous knowledge of the potential aggressiveness and biological traits of a given early-stage surgically resected tumor. This review focuses on proteins as promising biomarkers in the context of lung cancer screening. Despite great efforts, there are still no successful examples of biomarkers in lung cancer that have reached the clinics to be used in early detection and early management. Thus, the field of biomarkers in early lung cancer remains an evident unmet need. A more specific objective of this review is to present an up-to-date technical assessment of the potential use of protein biomarkers in early lung cancer detection and management. We provide an overview regarding the benefits, challenges, pitfalls and constraints in the development process of protein-based biomarkers. Additionally, we examine how a number of emerging protein analytical technologies may contribute to the optimization of novel robust biomarkers for screening and effective management of lung cancer.

Focusing on CD8+ T-cell phenotypes: improving solid tumor therapy

Vigorous CD8+ T cells play a crucial role in recognizing tumor cells and combating solid tumors. How T cells efficiently recognize and target tumor antigens, and how they maintain the activity in the "rejection" of solid tumor microenvironment, are major concerns. Recent advances in understanding of the immunological trajectory and lifespan of CD8+ T cells have provided guidance for the design of more optimal anti-tumor immunotherapy regimens. Here, we review the newly discovered methods to enhance the function of CD8+ T cells against solid tumors, focusing on optimizing T cell receptor (TCR) expression, improving antigen recognition by engineered T cells, enhancing signal transduction of the TCR-CD3 complex, inducing the homing of polyclonal functional T cells to tumors, reversing T cell exhaustion under chronic antigen stimulation, and reprogramming the energy and metabolic pathways of T cells. We also discuss how to participate in the epigenetic changes of CD8+ T cells to regulate two key indicators of anti-tumor responses, namely effectiveness and persistence.