A pan-cancer single-cell panorama of human natural killer cells

Avelumab induces greater Fc-Fc receptor-dependent natural killer cell activation and dendritic cell crosstalk compared to durvalumab

Several FDA-approved anti-PD-L1 (programmed cell death ligand-1) monoclonal antibodies (mAbs) are used to treat cancer. While these mAbs primarily target and intercept PD-L1:PD-1 inhibitory signaling in T-cells, the Fc-domains of these mAbs are distinct, and the unique cellular cascades triggered by differing Fc-domains of PD-L1 mAbs have not been directly investigated. In this study, we compared the innate immune effects of two widely used anti-PD-L1 IgG1 mAbs which bear distinct Fc-domains, avelumab (native-Fc) and durvalumab (mutated-Fc), using two-cell and three-cell co-culture systems containing Natural Killer cells (NK-cells), dendritic cells (DCs) and various tumor cell lines of multiple cancer origins. We show a robust enhancement in NK-cell effector function, DC maturation, reciprocal NK:DC crosstalk and DC editing that is unique to avelumab treatment using multiple functional immune assays. By transcriptomic analysis, we show for the first time pivotal differences in gene sets involved in NK-cell effector function, DC maturation, immunoregulatory interactions, and cytokine production between innate immune cells treated with avelumab versus durvalumab. Furthermore, we report several previously unknown Fc-receptor-associated biological pathways uniquely triggered by avelumab. Our findings elucidate novel mechanisms of Fc-dependent actions of PD-L1 mAbs which may inform their use in future clinical trials.

The landscape of malignant transition: Unraveling cancer cell-of-origin and heterogeneous tissue microenvironment

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.

Paracrine Orchestration of Tumor Microenvironment Remodeling Induced by GLO1 Potentiates Lymph Node Metastasis in Breast Cancer

Breast cancer is the most prevalent form of malignant tumor that frequently metastasizes to axillary lymph nodes (LNs). Nonetheless, the precise mechanisms underlying alterations in the tumor microenvironment (TME) in LN metastasis in breast cancer remain poorly understood. Single-cell RNA sequencing of 28 LN samples from 23 patients is performed, and a comprehensive landscape of the entire ecosystem is generated. Ten major cell types are identified, with the subclusters of each major cell type exhibiting diverse characteristics. Furthermore, multiple signatures are collected to evaluate the key components of the subclusters using multi-omics methodologies. This study finds that myCAFs may hasten LN metastasis, and observed a notable increase in APOE+ macrophages and a higher proportion of exhausted CD8+ T cells, contributing to the immunosuppressive TME. Moreover, cancer cells in metastatic lesions exhibited diverse expression patterns linked to proliferation, metastasis, oxidative phosphorylation, hypoxia, and interferon responses. Using multi-omics approaches and experimental validations, it determines that GLO1 can promote lymphatic angiogenesis, metastasis, and inhibit the proteasomal degradation of GSS, thereby maintaining intracellular glutathione (GSH) and reactive oxygen species (ROS) balance. Collectively, the study offers novel perspectives on the microenvironment remodeling of breast cancer LN metastases, suggesting that GLO1 may be a promising therapeutic target.

Influenza A virus dissemination and infection leads to tissue resident cell injury and dysfunction in viral sepsis

BACKGROUND

Severe respiratory viral infections can lead to viral sepsis (VS), a life-threatening condition characterized by lung and extrapulmonary organ dysfunction. However, the pathology of VS is not clear. Specifically, it is unknown how the cytokine storm and direct virus infection contribute to the damage of extrapulmonary organs.

METHODS

In this study, we established survival and lethal mouse models of VS by intranasally administering different doses of PR8/H1N1 influenza virus in C57BL/6J male mice, as well as model of bacterial sepsis (BS) caused by Streptococcus pneumoniae as references. Viraemia and extrapulmonary dissemination and infection of the virus were examined. Single-cell sequencing of the lungs and livers was performed at different days post-infection (dpi) in three groups.

FINDINGS

While bacteria can spread and colonize extensively in extrapulmonary organs, causing multiple organ injuries, IAVs mainly replicate and cause damage in pulmonary cells. Live virus can be isolated in the blood and extrapulmonary organs. Disseminating via the bloodstream, IAVs transiently infect the liver and spleen, causing liver dysfunction and spleen atrophy, without affecting kidney function, despite systematically elevated cytokine levels. Compared to BS, a more significant decrease in the proportion of alveolar macrophages, epithelial cells, endothelial cells, and fibroblasts in the lungs, as well as endothelial cells and Kupffer cells in the liver, was observed in VS. This was accompanied by a longer activated PANoptosis pathway and downregulated genes responsible for barrier function and antigen presentation in the epithelial and endothelial cells.

INTERPRETATION

Our study suggests that H1N1 influenza virus disseminates through the bloodstream and infects extrapulmonary organs to varying extents, which may lead to differential cell death, organ dysfunction, and trigger VS.

FUNDING

This research was supported by the National Natural Science Foundation of China (82241056, 82170015, 82030002, 82470007, 824B2001), the National Key R&D Program of China (2023YFC2306300), Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2021-I2M-1-048), the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD-D-202208), New Cornerstone Science Foundation, National High Level Hospital Clinical Research Funding (2024-NHLHCRF-LX-01-0101, 2024-NHLHCRF-LX-01-0102), Beijing Research Ward Excellence Program (BRWEP2024W114060103), Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0506200, 2023ZD0506203) and Special Research Fund for Central Universities, Peking Union Medical College (3332024193).

Targeting Lineage-Specific Functions of NR4A1 for Cancer Immunotherapy

Orphan nuclear receptor 4A1 (NR4A1, Nur77) plays a crucial role in regulating immune cell metabolism and function within the tumor microenvironment (TME), thus influencing cancer progression and serving as a potential therapeutic target for cancer immunotherapy. A comprehensive review discussing the multifaceted roles of NR4A1 in immune cells and the exploitation of that knowledge for therapeutic development is lacking in the field. This review explores diverse functions of NR4A1 in tumor-associated immune cells, including T cells, monocytes, natural killer cells, B cells, dendritic cells, macrophages, and neutrophils. NR4A1 contributes to immune regulation by impacting cytokine production, cell differentiation, and immune cell exhaustion. We highlight how NR4A1 in immune cells within the TME may be either a positive (e.g., macrophages in colon cancer) or negative prognostic factor (e.g., T cells in melanoma), depending on the cancer and immune cell context. Additionally, this review also highlights potential therapeutic strategies targeting NR4A1, leading to its inhibition, activation, or degradation to restore immune cell function and enhance anti-tumor immunity. Such therapies could potentially improve patient outcomes by altering immune cell behaviors, blocking intrinsic tumor growth pathways, or via both mechanisms. However, the development of NR4A1-targeted therapies will be dependent on further research to better understand lineage-specific roles of NR4A1 and the underlying mechanisms across different cancer types and immune cells.

A single-cell atlas reveals immune heterogeneity in anti-PD-1-treated non-small cell lung cancer

Anti-PD-(L)1 treatment is standard for non-small cell lung cancer (NSCLC), but patients show variable responses to the same regimen. The tumor immune microenvironment (TIME) is associated with immunotherapy response, yet the heterogeneous underlying therapeutic outcomes remain underexplored. We applied single-cell RNA and TCR sequencing (scRNA/TCR-seq) to analyze surgical tumor samples from 234 NSCLC patients post-neoadjuvant chemo-immunotherapy. Analyses revealed five distinct TIME subtypes with varying major pathological response (MPR) rates. MPR patients had elevated levels of FGFBP2+ NK/NK-like T cells, memory B cells, or effector T cells, while non-MPR patients showed higher CCR8+ Tregs. T cell clonal expansion analyses unveiled heterogeneity in non-MPR patients, marked by varying expansions of Tex-relevant cells and CCR8+ Tregs. Precursor exhausted T cells (Texp cells) correlated with recurrence-free survival, identifying a patient subgroup with reduced recurrence risk despite lack of MPR. Our study dissects TIME heterogeneity in response to chemoimmunotherapy, offering insights for NSCLC management.

Application of mass cytometry in the immune microenvironment of breast cancer

The rapid development of immunotherapy has shown preliminary clinical efficacy and significant anti-tumor effects in some cancer patients. Although immunotherapy has been approved for breast cancer, some breast cancer patients still do not benefit from it due to issues such as immunotherapy insensitivity and resistance. Mass cytometry, as a mature single-cell proteomic analysis method, with its high-throughput capabilities, has been widely used in the analysis of tumor immune microenvironments and immune cell subpopulations. Using mass cytometry to analyze the immune microenvironment of breast cancer and explore new immunotherapy targets can help improve the current status of breast cancer immunotherapy and develop personalized treatment plans for more patients. This review surveys the recent advancements in analyzing the single-cell components of breast cancer using mass cytometry technology and reviews the immune microenvironment of breast cancer as well as potential targets for immunotherapy. These results provide new insights for the subsequent research of the immune microenvironment of breast cancer and targeted immunotherapy.

Single cell atlas of canine natural killer cells identifies distinct circulating and tissue resident gene profiles

Introduction

Natural killer (NK) cells in mice and humans are key effectors of the innate immune system with complex immunoregulatory functions, and diverse subsets have been identified with distinct characteristics and roles. Companion dogs with spontaneous cancer have been validated as models of human disease, including cancer immunology and immunotherapy, and greater understanding of NK cell heterogeneity in dogs can inform NK biology across species and optimize NK immunotherapy for both dogs and people.

Methods

Here, we assessed canine NK cell populations by single-cell RNA sequencing (scRNAseq) across blood, lung, liver, spleen, and placenta with comparison to human NK cells from blood and the same tissues to better characterize the differential gene expression of canine and human NK cells regarding ontogeny, heterogeneity, patterns of activation, inhibition, and tissue residence.

Results

Overall, we observed tissue-specific NK cell signatures consistent with immature NK cells in the placenta, mature and activated NK cells in the lung, and NK cells with a mixed activated and inhibited signature in the liver with significant cross-species homology.

Discussion

Together, our results point to heterogeneous canine NK populations highly comparable to human NK cells, and we provide a comprehensive atlas of canine NK cells across organs which will inform future cross-species NK studies and further substantiate the spontaneous canine model to optimize NK immunotherapy across species.

Single-cell meta-analysis of T cells reveals clonal dynamics of response to checkpoint immunotherapy

Despite the crucial role of T cell clones in anti-tumor activity, their characterization and association with clinical outcomes following immune checkpoint inhibitors are lacking. Here, we analyzed paired single-cell RNA sequencing/T cell receptor sequencing of 767,606 T cells across 460 samples spanning 6 cancer types. We found a robust signature of response based on expanded CD8+ clones that differentiates responders from non-responders. Analysis of persistent clones showed transcriptional changes that are differentially induced by therapy in the different response groups, suggesting an improved reinvigoration capacity in responding patients. Moreover, a gene trajectory analysis revealed changes in the pseudo-temporal state of de novo clones that are associated with clinical outcomes. Lastly, we found that clones shared between tumor and blood are more abundant in non-responders and execute distinct transcriptional programs. Overall, our results highlight differences in clonal transcriptional states that are linked to patient response, offering valuable insights into the mechanisms driving effective anti-tumor immunity.

The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution

Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.

RAC2 inhibition enhances tumor sensitivity to NK cell-mediated cytotoxicity

BACKGROUND

Natural killer (NK) cells are recognized for their ability to kill tumor cells for tumor control, but tumor cells often develop resistance to evade NK cell-mediated cytotoxicity. Identification of molecular mechanisms by which tumor cells evade from NK cell-mediated killing may offer novel therapeutic strategies for potentiating NK-based cancer immunotherapy.

METHODS

An in vitro tumor-NK cell co-culture system was employed to identify the most significantly altered genes in tumor cells following NK cell interaction. The cell death rate of tumor cells by NK cell exposure was quantified using flow cytometry. EL4 and HCT116 tumor models in C57BL/6, BALB/c-nu, and NOD/SCID mice were used for evaluating tumor growth differences induced by Rac2 knockdown or knockout. The cellular and molecular impact of Rac2 knockdown or knockout on the sensitivity of tumor cells to NK cell-mediated cytotoxicity was assessed using quantitative PCR, immunofluorescence, and mutation analysis.

RESULTS

By screening expression levels of the Ras homology (Rho) GTPase family genes in tumor cells after co-culture with NK cells, we identified RAC2 as a key regulator of tumor cell resistance to NK cell-mediated cytotoxicity among the Rho GTPase family members. Furthermore, knockout of RAC2 in human colorectal cancer cells leads to increased tumor susceptibility to NK cell-mediated cytotoxicity in a xenograft tumor model. Mechanistically, the absence of RAC2 enhances tumor cell sensitivity to NK cell-mediated killing by facilitating cell-cell contact.

CONCLUSIONS

These findings indicate that the inhibition of RAC2 in tumor cells substantially enhances their susceptibility to NK cell-mediated cytotoxicity, thereby providing a potential therapeutic target for optimizing NK cell therapy.

Robust differentiation of NK cells from MSLN.CAR-IL-15-engineered human iPSCs with enhanced antitumor efficacy against solid tumors

Human induced pluripotent stem cells (iPSCs) offer a promising source for chimeric antigen receptor (CAR)-engineered natural killer (NK) products. However, complex iPSC-NK (iNK) manufacturing challenges clinical use. Here, we identified LiPSC-GR1.1 as a superior iPSC line for iNK production. By engineering LiPSC-GR1.1 with a mesothelin (MSLN)-targeting CAR and interleukin-15 (IL-15), we achieved robust differentiation of iPSCs into mature activated iNK cells with enhanced tumor killing efficacy, superior tumor homing, and vigorous proliferation. Single-cell transcriptomic analysis revealed that transforming growth factor-β (TGF-β)-producing tumor cells up-regulated major histocompatibility complex molecules and down-regulated MSLN post-CAR-IL-15 iNK treatment. Tumor-infiltrating CAR-IL-15 iNK cells exhibited high levels of CAR, IL-15, and NK-activating receptors, negligible checkpoint exhaustion markers, and extremely low levels of NK suppressive factors CISH, TGFBR2, and BATF, enabling them to sustain activation, metabolic fitness, and effective tumor killing within TGF-β-rich hypoxic tumor microenvironment. Overall, we developed MSLN.CAR-IL-15-engineered GR1.1-iNK therapy with enhanced antitumor efficacy for solid tumor treatment.

Targeting HMGB2 acts as dual immunomodulator by bolstering CD8+ T cell function and inhibiting tumor growth in hepatocellular carcinoma

T cell exhaustion is a critical obstacle for durable treatment response in hepatocellular carcinoma (HCC). Developing drugs that control tumor growth and simultaneously bolster immune function is of great significance. Although high-mobility group box 2 (HMGB2) has been reported to be crucial to HCC prognosis, its role in the tumor microenvironment remains unclear. Here, we found HMGB2+ CD8+ T cells as being associated with immune exhaustion and resistance to anti-PD-1 treatment through single-cell RNA sequencing. Mechanistically, HMGB2 impaired the oxidative phosphorylation in CD8+ T cells and inactivated the interferon-γ response in tumor cells, reducing the antitumor effector function. Tannic acid, a specific inhibitor of HMGB2, synergized with PD-1 antibody to attenuate tumor growth and reverse T cell exhaustion. Our findings highlight the unique role of HMGB2 as an immune exhaustion associated molecule. Targeting HMGB2 on both CD8+ T cells and tumor cells contributed to promising treatment strategies for HCC.

Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies

BACKGROUND

Lung adenocarcinoma (LUAD) presents a considerable danger to human health and has evolved into a major public health concern. Ribosome biogenesis (RiboSis) is a critical process for synthesizing ribosomes, closely associated with cancer initiation, progression, and treatment resistance, potentially serving as a target for future cancer therapies.

METHODS

Utilizing single-cell RNA sequencing (scRNA-seq) technology, a single-cell atlas of LUAD was delineated, focusing on the analysis of T cell subpopulations. Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4+ T cells. Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. The relationship between RBS risk scores and various factors in LUAD patients, including prognosis, the tumor immune microenvironment (TIME), responsiveness to immunotherapy, and sensitivity to pharmacological treatments was specifically analyzed. Immunohistochemistry was utilized to validate the expression levels of immune markers in the high- and low- RBS groups, and in vitro experiments were performed to validate the functional role of the pivotal gene KIF23 in the progression of LUAD.

RESULTS

Using single-cell analysis, two distinct T cell subtypes were identified: CD8+ interferon (IFN) response T cells and CD4+ stress response T cells. It was observed that CD4+ naive-like T cells exhibit high expression of RiboSis-related genes, with a gradual decrease in RiboSis activity as CD4+ T cells develop. Compared to other prognostic models, RBS demonstrated superior performance in prognosis prediction. The low-RBS group exhibited a tumor microenvironment (TME) more favorable for efficient immune monitoring and reaction, higher responsiveness to immunotherapy, and a better prognosis. Immunohistochemistry confirmed higher expression levels of immune markers in the low-RBS group, while in vitro experiments validated the promoting role of KIF23 in LUAD cell proliferation, migration and invasion.

CONCLUSION

This study delves into the relationship between RiboSis and LUAD cell subpopulations, identifying a potent prognostic biomarker for LUAD. This biomarker aids in assessing immunotherapy efficacy in LUAD patients, ultimately enhancing their prognosis and guiding clinical decision-making.

Comprehensive characterization of T cell subtypes in lung adenocarcinoma: Prognostic, predictive, and therapeutic implications

BACKGROUND

T cells are crucial for immunosurveillance and tumor eradication, with their dysregulation or absence in the tumor microenvironment linked to immunotherapy resistance. In lung adenocarcinoma (LUAD), this resistance is a significant barrier to effective treatment, highlighting the need for robust biomarkers and therapeutic targets to improve clinical outcomes.

METHODS

T cell-related markers were identified through single-cell RNA sequencing analysis. The TCGA dataset was used for consensus clustering to define molecular subtypes associated with distinct survival outcomes and immune profiles. A T cell-related prognostic signature was developed by integrating LUAD datasets from TCGA, GSE31210, GSE50081, and GSE68465 using 10 machine learning algorithms. Further analysis linked risk scores to immune infiltration and drug sensitivity. The role of a hub gene in CD4+ T cell function and its involvement in tumor immunity was explored through in vitro experiments and molecular biology techniques.

RESULTS

Cluster analysis identified three LUAD subtypes, with cluster1 showing the best prognosis and immune characteristics. A Lasso + PLSRcox-based signature was a significant risk factor for predicting LUAD patient outcomes, outperforming traditional clinicopathological factors. The risk score correlated with immune microenvironment features, immune cell infiltration, and sensitivity to immunotherapy and chemotherapy. CPA3 expression was elevated in activated CD4+ T cells, particularly in Th1 cells, promoting differentiation and IFN-γ secretion. Overexpression of CPA3 enhanced tumor cell apoptosis and increased Granzyme B and IFN-γ levels, highlighting its role in immune responses.

CONCLUSION

We developed a powerful prognostic signature in LUAD that accurately predicts clinical outcomes and can guide immunotherapy and chemotherapy responses.

Understanding the cellular and molecular heterogeneity in colorectal cancer through the use of single-cell RNA sequencing

The very prevalent nature, genetic variability, and intricate tumor microenvironment (TUME) of colorectal cancer (COREC) are its defining features. In order to better understand the molecular and cellular make-up of COREC, this work used single-cell RNA sequencing (SRNAS) to isolate and characterize important cell types as well as their interactions within the TUME. Our analysis of 51,204 cells yielded six distinct types: epithelial, fibroblast, endothelial, T&NK, B, and myeloid. C3 B cells were shown to be the most active in immunological regulation, according to chemokine signaling study, which was one of seven clusters of B cells that were thoroughly subtyped. The examination of copy number variation (CONUV) revealed a great deal of genetic variability, especially in epithelial cells. We traced the activity of three key transcription factor clusters (M1, M2, and M3) across all B cell subtypes using transcription factor analysis. We created a predictive model that correctly sorts patients according to survival results by using marker genes from C3 B cells. In addition, the relationship between genetic changes and the immune system was better understood by tumor mutational burden (TUMUB) and immune infiltration studies. Our research sheds light on the genetic complexity and cellular variety of COREC, which in turn opens up new possibilities for targeted treatments and individualized approaches to patient care.

KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics

KanCell is a deep learning model based on Kolmogorov-Arnold networks (KAN) designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics (ST) data. ST technologies provide insights into gene expression within tissue context, revealing cellular interactions and microenvironments. To fully leverage this potential, effective computational models are crucial. We evaluate KanCell on both simulated and real datasets from technologies such as STARmap, Slide-seq, Visium, and Spatial Transcriptomics. Our results demonstrate that KanCell outperforms existing methods across metrics like PCC, SSIM, COSSIM, RMSE, JSD, ARS, and ROC, with robust performance under varying cell numbers and background noise. Real-world applications on human lymph nodes, hearts, melanoma, breast cancer, dorsolateral prefrontal cortex, and mouse embryo brains confirmed its reliability. Compared with traditional approaches, KanCell effectively captures non-linear relationships and optimizes computational efficiency through KAN, providing an accurate and efficient tool for ST. By improving data accuracy and resolving cell type composition, KanCell reveals cellular heterogeneity, clarifies disease microenvironments, and identifies therapeutic targets, addressing complex biological challenges.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

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.

Nuclear mitochondrial acetyl-CoA acetyltransferase 1 orchestrates natural killer cell-dependent antitumor immunity in colorectal cancer

Tumor metabolism often interferes with the immune microenvironment. Although natural killer (NK) cells play pivotal roles in antitumor immunity, the connection between NK cells and tumor metabolism remains unclear. Our systematic analysis of multiomics data and survival data from colorectal cancer (CRC) patients uncovered a novel association between mitochondrial acetyl-CoA acetyltransferase 1 (ACAT1) and NK cell infiltration that influences disease progression. ACAT1, a metabolic enzyme involved in reversible conversion of acetoacetyl-CoA to two molecules of acetyl-CoA, exhibits nuclear protein acetylation activity through its translocation. Under immune stimulation, mitochondrial ACAT1 can be phosphorylated at serine 60 (S60) and enters the nucleus; however, this process is hindered in nutrient-poor tumor microenvironments. Nuclear ACAT1 directly acetylates lysine 146 of p50 (NFKB1), attenuating its DNA binding and transcriptional repression activity and thereby increasing the expression of immune-related factors, which in turn promotes NK cell recruitment and activation to suppress colorectal cancer growth. Furthermore, significant associations are found among low nuclear ACAT1 levels, decreased S60 phosphorylation, and reduced NK cell infiltration, as well as poor prognosis in CRC. Our findings reveal an unexpected function of ACAT1 as a nuclear acetyltransferase and elucidate its role in NK cell-dependent antitumor immunity through p50 acetylation.

CLN-619, a MICA/B monoclonal antibody that promotes innate immune cell-mediated antitumor activity

BACKGROUND

Major histocompatibility complex class I-related protein A and B (MICA/B) are ligands for the natural killer group 2 member D (NKG2D) receptor and are broadly expressed on tumor cells but minimally on normal tissues. When cytotoxic NKG2D-expressing immune cells engage MICA/B, the ligand-expressing cells are targeted for lysis. Cancer cells can evade NKG2D-mediated destruction by shedding MICA/B from their cell surface via proteases present in the tumor microenvironment. CLN-619 is a humanized IgG1 monoclonal antibody (mAb) which binds MICA/B and inhibits shedding resulting in accumulation of MICA/B on the tumor cell surface. CLN-619 may thereby have therapeutic effects in a broad range of malignancies by re-establishing the MICA/B-NKG2D axis to enable NKG2D-mediated, as well as Fc-gamma receptor-mediated, tumor cell lysis.

METHODS

CLN-619 was characterized for binding epitope and affinity, effects on surface and soluble levels of MICA/B, and in vitro tumor cell killing. In mouse models, the mAb was tested for tumor growth inhibition. The contribution of the Fc-gamma (Fcγ) 1 domain to CLN-619 activity was also assessed.

RESULTS

CLN-619 bound with high affinity to the alpha-3 domain of MICA/B without encumbering the interaction with NKG2D on natural killer cells. CLN-619 increased the level of cell surface expression of MICA/B and concomitantly decreased the levels of soluble MICA/B in cell culture assays. Treatment of cancer cell lines with CLN-619 induced antibody-dependent cellular cytotoxicity and antibody-dependent cellular phagocytosis. CLN-619 resulted in potent inhibition of tumor growth in multiple xenograft models and increased survival of mice in a disseminated cancer model.

CONCLUSIONS

CLN-619 inhibited the shedding of MICA/B to effectively restore cytotoxic signaling pathways in immune cells. Potent antitumor activity of CLN-619 as a monotherapy was observed in several preclinical models. Activity of CLN-619 required a functional Fcγ1 domain, suggesting the requirement of simultaneous engagement of NKG2D and cluster of differentiation 16A (CD16A) on immune cells for optimal cytotoxicity. The preclinical data reported here support the assessment of CLN-619 in patients with cancer.

Tissue-resident immune cells in cervical cancer: emerging roles and therapeutic implications

The favorable prognosis of "hot" tumors is widely acknowledged in oncology. Recently, the concept of tertiary lymphoid structures (TLS) has renewed appreciation for local immune cells within tumor tissues. Tissue-resident immune cells, a newly identified subset of tumor-infiltrating lymphocytes, are emerging as potential key players in tumor infiltration and TLS formation, due to their ability to reside indefinitely within tissues and mount effective responses to local antigens. Cervical cancer (CC), the fourth most common cause of cancer-related mortality among women globally, has experienced comparatively limited progress in delineating its tumor immune microenvironment compared to other malignancies. Notably, the role of tissue-resident immune cells within the CC milieu remains inadequately characterized. This comprehensive review aims to synthesize current knowledge and critically evaluate the putative roles of these cells in CC pathogenesis, providing new insights on the intricate dynamics of the local tumor microenvironment.

Identification and validation of poor prognosis immunoevasive subtype of esophageal cancer with tumor-infiltrating SAMD3 + NK cell abundance

INTRODUCTION

Esophageal cancer (EC) remains highly lethal due to tumor microenvironment (TME)-mediated immune evasion. While natural killer (NK) cells are central to antitumor immunity, their functional states in EC are poorly characterized.

METHODS

We integrated bulk RNA-seq (TCGA/GEO) and single-cell data to construct an NK cell-derived prognostic signature (NK score) via LASSO-Cox regression. Immunofluorescence was applied to assess the clinical relevance of SAMD3 + NK cells in EC. Using both xenograft mouse models and in vitro co-culture procedures, the impact of SAMD3 on NK cell function was confirmed.

RESULTS

In EC patients, the prognostic NK score-which is generated from important NK cell markers including SAMD3-was substantially correlated with a worse chance of survival. NK cells within the TME had significant levels of SAMD3 expression, as seen by immunofluorescence labeling. Moreover, NK cells with SAMD3 knockdown exhibited enhanced antitumor activity, leading to decreased tumor development in the xenograft model.

DISCUSSION

Our results demonstrate the predictive significance of NK cell markers in EC and pinpoint SAMD3 as a critical modulator of NK cell activity. We pioneer SAMD3 + NK cells as architects of TME immunosuppression in EC. Our findings nominate SAMD3 inhibition as a combinatorial strategy to overcome immune checkpoint blockade resistance.

Immunocytes in the tumor microenvironment: recent updates and interconnections

The tumor microenvironment (TME) is a complex, dynamic ecosystem where tumor cells interact with diverse immune and stromal cell types. This review provides an overview of the TME's evolving composition, emphasizing its transition from an early pro-inflammatory, immune-promoting state to a later immunosuppressive milieu characterized by metabolic reprogramming and hypoxia. It highlights the dual roles of key immunocytes-including T lymphocytes, natural killer cells, macrophages, dendritic cells, and myeloid-derived suppressor cells-which can either inhibit or support tumor progression based on their phenotypic polarization and local metabolic conditions. The article further elucidates mechanisms of immune cell plasticity, such as the M1/M2 macrophage switch and the balance between effector T cells and regulatory T cells, underscoring their impact on tumor growth and metastasis. Additionally, emerging therapeutic strategies, including checkpoint inhibitors and chimeric antigen receptor (CAR) T and NK cell therapies, as well as approaches targeting metabolic pathways, are discussed as promising avenues to reinvigorate antitumor immunity. By integrating recent molecular insights and clinical advancements, the review underscores the importance of deciphering the interplay between immunocytes and the TME to develop more effective cancer immunotherapies.

Comprehensive Integrated Analysis Reveals the Spatiotemporal Microevolution of Cancer Cells in Patients with Bone-Metastatic Prostate Cancer

Background/Objectives: Bone metastasis is a frequent and life-threatening event in advanced cancers, affecting up to 70-85% of prostate cancer patients. Understanding the cellular and molecular mechanisms underlying bone metastasis is essential for developing targeted therapies. This study aimed to systematically characterize the heterogeneity and microenvironmental adaptation of prostate cancer bone metastases using single-cell transcriptomics. Methods: We integrated the largest single-cell transcriptome dataset to date, encompassing 124 samples from primary prostate tumors, various bone metastatic sites, and non-malignant tissues (e.g., benign prostatic hyperplasia, normal bone marrow). After quality control, 602,497 high-quality single-cell transcriptomes were analyzed. We employed unsupervised clustering, gene expression profiling, mutation analysis, and metabolic pathway reconstruction to characterize cancer cell subtypes and tumor microenvironmental remodeling. Results: Cancer epithelial cells dominated the tumor microenvironment but exhibited pronounced heterogeneity, posing challenges for conventional clustering methods. By integrating genetic and metabolic features, we revealed key evolutionary trajectories of epithelial cancer cells during metastasis. Notably, we identified a novel epithelial subpopulation, NEndoCs, characterized by unique differentiation patterns and distinct spatial distribution across metastatic niches. We also observed significant metabolic reprogramming and recurrent mutations linked to prostate-to-bone microenvironmental transitions. Conclusions: This study comprehensively elucidates the mutation patterns, metabolic reprogramming, and microenvironment adaptation mechanisms of bone metastasis in prostate cancer, providing key molecular targets and clinical strategies for the precise treatment of bone metastatic prostate cancer.

Single-cell transcriptomics reveals immunosuppressive microenvironment and highlights tumor-promoting macrophage cells in Glioblastoma

Glioblastoma (GBM) is the most prevalent and aggressive primary brain malignancy in adults. Nevertheless, the cellular heterogeneity and complexity within the GBM microenvironment (TME) are still not fully understood, posing a significant obstacle in the advancement of more efficient immunotherapies for GBM. In this study, we conducted an integrated analysis of 48 tumor fragments from 24 GBM patients at the single-cell level, uncovering substantial molecular diversity within immune infiltrates. We characterized molecular signatures for five distinct tumor-associated macrophages (TAMs) subtypes. Notably, the TAM_MRC1 subtype displayed a pronounced M2 polarization signature. Additionally, we identified a subtype of natural killer (NK) cells, designated CD56dim_DNAJB1. This subtype is characterized by an exhausted phenotype, evidenced by an elevated stress signature and enrichment in the PD-L1/PD-1 checkpoint pathway. Our findings also highlight significant cell-cell interactions among malignant glioma cells, TAM, and NK cells within the TME. Overall, this research sheds light on the functional heterogeneity of glioma and immune cells in the TME, providing potential targets for therapeutic intervention in this immunologically cold cancer.

Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFA+ neutrophil prognostic model

BACKGROUND

Neutrophils play a key role in the tumor microenvironment (TME); however, their functions in glioblastoma (GBM) are overlooked and insufficiently studied. A detailed analysis of GBM-associated neutrophil (GBMAN) subpopulations may offer new insights and opportunities for GBM immunotherapy.

METHODS

We analyzed single-cell RNA sequencing (scRNA-seq) data from 127 isocitrate dehydrogenase (IDH) wild-type GBM samples to characterize the GBMAN subgroups, emphasizing developmental trajectories, cellular communication, and transcriptional networks. We implemented 117 machine learning combinations to develop a novel risk model and compared its performance to existing glioma models. Furthermore, we assessed the biological and molecular features of the GBMAN subgroups in patients.

RESULTS

From integrated large-scale scRNA-seq data (498,747 cells), we identified 5,032 neutrophils and classified them into four distinct subtypes. VEGFA+GBMAN exhibited reduced inflammatory response characteristics and a tendency to interact with stromal cells. Furthermore, these subpopulations exhibited significant differences in transcriptional regulation. We also developed a risk model termed the "VEGFA+neutrophil-related signature" (VNRS) using machine learning methods. The VNRS model showed higher accuracy than previously published risk models and was an independent prognostic factor. Additionally, we observed significant differences in immunotherapy responses, TME interactions, and chemotherapy efficacy between high-risk and low-risk VNRS score groups.

CONCLUSION

Our study highlights the critical role of neutrophils in the TME of GBM, allowing for a better understanding of the composition and characteristics of GBMAN. The developed VNRS model serves as an effective tool for evaluating the risk and guiding clinical treatment strategies for GBM.

CLINICAL TRIAL NUMBER

Not applicable.

MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis

Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune function research. Here, we introduce a deep learning framework for single-T cell transcriptome and receptor analysis, MIST (Multi-insight for T cell). MIST features three latent spaces: gene expression, TCR, and a joint latent space. Through analyses of antigen-specific T cells, and T cell datasets related to lung cancer immunotherapy and COVID19, we demonstrate MIST's interpretability and flexibility. MIST easily and accurately resolves cell function and antigen specificity by vectorizing and integrating transcriptome and TCR data of T cells. In addition, using MIST, we identified the heterogeneity of CXCL13+ subsets in lung cancer infiltrating CD8+ T cells and their association with immunotherapy, providing additional insights into the functional transition of CXCL13+ T cells related to anti-PD-1 therapy that were not reported in the original study.

Emerging Role of the p53 Pathway in Modulating NK Cell-Mediated Immunity

The p53 pathway plays an important role in role in cancer immunity. Mutation or downregulation of the proteins in the p53 pathway are prevalent in many cancers, contributing to tumor progression and immune dysregulation. Recent findings suggest that the activity of p53 within tumor cells, immune cells, and the tumor microenvironment can play an important role in modulating NK cell-mediated immunity. Consequently, efforts to restore p53 pathway activity are being actively pursued to modulate this form of immunity. This review focuses on p53 activity regulating the infiltration and activation of NK cells in the tumor immune microenvironment. Furthermore, the impact of p53 and its regulation of NK cells on immunogenic cell death within solid tumors and the abscopal effect are reviewed. Finally, future avenues for therapeutically restoring p53 activity to improve NK cell-mediated antitumor immunity and optimize the effectiveness of cancer therapies are discussed.

The Problem with Syngeneic Mouse Tumor Models

The advent of syngeneic mouse tumor models provided the scientific foundation for cancer immunotherapies now in widespread use. However, in many respects, these models do not faithfully recapitulate the interactions between cancer cells and the immune systems of human patients who have solid tumors because they represent a very early stage in the immune response to the newly transplanted cancer cells compared with the relatively mature stage found in human patients at the time of treatment. The lack of translatability of syngeneic models is probably responsible for many failed clinical trials conducted at considerable expense, involving far too many patients with cancer who received no benefit. Better mouse models would substantially accelerate the pace of discovery of new immunotherapies. Until these models emerge, a better understanding of the differences between the existing syngeneic models and human cancers may provide a more efficient path for moving experimental drugs into clinical development. To accomplish this, we must consider mice transplanted with syngeneic tumor cells to be in vivo assays, potentially useful for understanding the mechanism of action of immunotherapies rather than disease models.

The Spatial Organization of cDC1 with CD8+ T Cells is Critical for the Response to Immune Checkpoint Inhibitors in Patients with Melanoma

Dendritic cells (DC) are promising targets for cancer immunotherapies because of their central role in the initiation and control of immune responses. The type 1 conventional DC (cDC1) population is of particular interest because of its ability to cross-present antigens to CD8+ T cells. cDC1s also secrete cytokines that allow Th1 cell polarization and NK cell activation and recruitment. However, the spatial organization and specific functions of cDC1s in response to immunotherapy remain to be clearly characterized in human tumors. In this study, we used a multiplexed immunofluorescence analysis pipeline coupled with computational image analysis to determine the spatial organization of cDC1s in skin lesions from a cohort of patients with advanced melanoma treated with immune checkpoint inhibitors (ICI). For this, we performed a whole-slide image analysis of cDC1 infiltration, distribution, and spatial interaction with key immune partners such as CD8+ T cells and plasmacytoid DCs. We also analyzed LAMP3+ DCs, which correspond to a mature subset of tumor-infiltrating DCs. Distance and cell network analyses demonstrated that cDC1s exhibited a scattered distribution compared with tumor-infiltrating plasmacytoid DCs and LAMP3+ DCs, which were preferentially organized in dense areas with high homotypic connections. The proximity and interactions between CD8+ T cells and cDC1s were positively associated with the response to ICIs. In conclusion, our study unravels the complex spatial organization of cDC1s and their interactions with CD8+ T cells in lesions of patients with melanoma, shedding light on the pivotal role of these cells in shaping the response to ICIs.

TMEM115 as an Oncogenic and Immunological Biomarker in Hepatocellular Carcinoma

BACKGROUND

Transmembrane (TMEM) proteins are involved in fundamental biological processes such as material transport and signal transduction. TMEM115 is a member of the TMEM protein family, but its significance in hepatocellular carcinoma (HCC) remains unclear. In this study, we investigate the clinical predictive significance and potential functions of TMEM115 in HCC.

METHODS

Bioinformatics was used to investigate TMEM115 mRNA expression and immune infiltration score. Through multiplex immunohistochemistry analysis, we assessed its protein expression and association with HCC patient clinical features, prognosis and immune cell infiltration in HCC. Through in vitro and in vivo experiments, we evaluated the biological functions of TMEM115 in HCC cells and its impact on the immune microenvironment.

RESULTS

TMEM115 mRNA and protein levels were significantly higher in HCC tissues compared to paracancerous liver tissues. Its protein expression correlated with clinical characteristics and overall survival in HCC patients. In HCC tissues, higher TMEM115 protein expression corresponded to lower proportions of CD66b+ neutrophils and CD8+ T cells and a higher proportion of CD4+ T cells. Furthermore, patients with low TMEM115 expression displayed higher programmed cell death ligand-1 and lower lymphocyte activation gene 3 protein expression. Functionally, TMEM115 knockdown inhibited the proliferation, migration and invasion of HCC cells. In orthotopic models, TMEM115 knockdown inhibited the growth of HCC and affected the infiltration of immune cells.

CONCLUSIONS

Our findings show TMEM115 as a promising prognostic indicator for HCC and hold promise in predicting responses to immune therapy, emphasising its potential clinical relevance and intricate involvement in the immune microenvironment of HCC.

Immunoregulatory mechanisms of the arachidonic acid pathway in cancer

The arachidonic acid (AA) pathway promotes tumor progression by modulating the complex interactions between cancer and immune cells within the microenvironment. In this Review, we summarize the knowledge acquired thus far concerning the intricate mechanisms through which eicosanoids either promote or suppress the antitumor immune response. In addition, we will discuss the impact of eicosanoids on immune cells and how they affect responsiveness to immunotherapy, as well as potential strategies for manipulating the AA pathway to improve anticancer immunotherapy. Understanding the molecular pathways and mechanisms underlying the role played by AA and its metabolites in tumor progression may contribute to the development of more effective anticancer immunotherapies.

The role of TIGIT-CD226-PVR axis in mediating T cell exhaustion and apoptosis in NSCLC

The treatment of non-small cell lung cancer (NSCLC) remains a critical challenge in oncology, primarily due to the dysfunction and exhaustion of T cells within the tumor microenvironment, which greatly limits the effectiveness of immunotherapy. This study investigates the regulatory role of the T cell immunoglobulin and ITIM domain (TIGIT)-CD226-PVR signaling axis in the exhaustion and apoptosis of cluster of differentiation (CD)27+/CD127+T cells in NSCLC. Utilizing single-cell sequencing technology, we conducted a comprehensive gene expression analysis of T cells in a mouse model of NSCLC. Bioinformatics analysis revealed that the TIGIT-CD226-PVR signaling axis is highly active in the CD27+/CD127+T cell subset and is closely associated with their functional decline and exhaustion. In vitro experiments further demonstrated that inhibiting the TIGIT-PVR pathway while activating the CD226-PVR pathway significantly restored T cell proliferation and effector function. Importantly, in vivo studies showed that targeting this axis can significantly alleviate T cell exhaustion, enhance their cytotoxicity against NSCLC cells, and promote apoptosis, thereby improving the efficacy of immunotherapy.

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.

scPANDA: PAN-Blood Data Annotator with a 10-Million Single-Cell Atlas

OBJECTIVES

Recent advancements in single-cell RNA sequencing (scRNA-seq) have revolutionized the study of cellular heterogeneity, particularly within the hematological system. However, accurately annotating cell types remains challenging due to the complexity of immune cells. To address this challenge, we develop a PAN-blood single-cell Data Annotator (scPANDA), which leverages a comprehensive 10-million-cell atlas to provide precise cell type annotation.

METHODS

The atlas, constructed from data collected in 16 studies, incorporated rigorous quality control, preprocessing, and integration steps to ensure a high-quality reference for annotation. scPANDA utilizes a three-layer inference approach, progressively refining cell types from broad compartments to specific clusters. Iterative clustering and harmonization processes were employed to maintain cell type purity throughout the analysis. Furthermore, the performance of scPANDA was evaluated in three external datasets.

RESULTS

The atlas was structured hierarchically, consisting of 16 compartments, 54 classes, 4,‍460 low-level clusters (pd_cc_cl_tfs), and 611 high-level clusters (pmid_cts). Robust performance of the tool was demonstrated in annotating diverse immune scRNA-seq datasets, analyzing immune-tumor coexisting clusters in renal cell carcinoma, and identifying conserved cell clusters across species.

CONCLUSIONS

scPANDA exemplifies effective reference mapping with a large-scale atlas, enhancing the accuracy and reliability of blood cell type identification.

Retinoid X receptor γ predicts the prognosis and is associated with immune infiltration in kidney renal clear cell carcinoma: a qRT-PCR, TCGA and in silico research

BACKGROUND

Kidney clear cell carcinoma (KIRC) stands as one of the most prevalent primary malignant tumors, showcasing significant heterogeneity within the urological system. However, the precise molecular mechanisms underpinning tumorigenesis in KIRC remain elusive. While Retinoid X receptor γ (RXRG) has been implicated in various diseases and human cancers, its specific role in KIRC remains undetermined. This research aimed to investigate the involvement of RXRG in KIRC pathogenesis.

METHODS

Quantitative real-time polymerase chain reaction was performed to evaluate the expression levels of RXRG in KIRC. Utilizing RNA-seq data and corresponding clinicopathological information from The Cancer Genome Atlas (TCGA) database, we embarked on an analysis to ascertain the prognostic significance of RXRG in KIRC. Furthermore, bioinformatics analyses were employed to delineate the preliminary molecular mechanisms through which RXRG operates in KIRC tumorigenesis.

RESULTS

Our findings revealed a significant downregulation of RXRG in KIRC tumor tissues compared to normal kidney tissues, as evidenced in local and TCGA cohorts. Diminished RXRG expression correlated with adverse clinicopathological characteristics, including larger tumor size, higher clinical stage, and advanced histologic grade. Cox regression analyses unveiled that reduced RXRG expression was associated with poorer overall survival (OS) and disease-free survival (DFS) rates in KIRC patients. Bioinformatics analyses indicated that the RXRG-related differentially expressed genes (DEGs) were involved in tumorigenesis and metabolism by regulating a series of signaling pathways. Using ssGSEA, we found that RXRG expression was significantly associated with NK cells and macrophages.

CONCLUSION

Our study provides new insights and evidence that RXRG is involved in the tumorigenesis of KIRC and may be a suitable target for immunotherapy in KIRC.

Study on Heparanase Promoting Breast Cancer Cell Proliferation and Inhibiting NK Cell Cytolytic Activity Via the PD-1/PD-L1 Pathway

OBJECTIVE

To explore the mechanism of action of heparanase (HPSE) in breast cancer (BC), particularly its impact on BC cell proliferation and natural killer (NK) cell cytolytic activity through the programmed cell death protein 1 (PD-1)/PD ligand 1 (PD-L1) pathway.

METHODS

HPSE expression levels were analyzed in BC cells. MDA-MB-231 cells, a widely used triple-negative BC model, were treated and assessed using RT-qPCR and Western blotting for gene and protein expression. CCK-8, Transwell assays, and flow cytometry were used to evaluate cell proliferation, migration, invasion, and apoptosis. NK cells isolated from healthy donors were treated with HPSE and co-cultured with BC cells to assess cytolytic activity through interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) release measurements. A nude mouse xenograft model was established to examine the in vivo effects of HPSE on tumor growth and NK cell function.

RESULTS

HPSE overexpression enhanced BC cell proliferation, migration, and invasion, while reducing apoptosis. It also upregulated PD-1 and PD-L1 expression, leading to impaired NK cell cytolytic activity and decreased secretion of TNF-α and IFN-γ. Inhibition of the PD-1/PD-L1 pathway partially reversed the pro-tumor effects of HPSE and restored NK cell cytolytic function. In vivo, HPSE overexpression promoted tumor growth and reduced NK cell activity within tumor tissues.

CONCLUSION

These findings reveal HPSE as a key regulator of BC immune evasion, likely via modulation of the PD-1/PD-L1 axis. Targeting HPSE, particularly in combination with PD-1/PD-L1 inhibitors, may offer a novel therapeutic strategy for BC treatment.

Pan-cancer analysis shapes the understanding of cancer biology and medicine

Advances in multi-omics datasets and analytical methods have revolutionized cancer research, offering a comprehensive, pan-cancer perspective. Pan-cancer studies identify shared mechanisms and unique traits across different cancer types, which are reshaping diagnostic and treatment strategies. However, continued innovation is required to refine these approaches and deepen our understanding of cancer biology and medicine. This review summarized key findings from pan-cancer research and  explored their potential to drive future advancements in oncology.

Circadian rhythm related genes identified through tumorigenesis and immune infiltration-guided strategies as predictors of prognosis, immunotherapy response, and candidate drugs in skin cutaneous malignant melanoma

Background

Skin cutaneous malignant melanoma (SKCM) is among the most aggressive forms of skin cancer, notorious for its rapid progression and poor prognosis under late diagnosis. This study investigates the role of circadian rhythm-related genes (CRGs) in SKCM addressing a gap in understanding how CRGs affect tumor progression and patient outcomes.

Methods

An analysis of CRGs expression was conducted on SKCM samples derived from The Cancer Genome Atlas datasets(TCGA). Moreover, a correlation between various subtypes and their clinical features was identified. The study employed various bioinformatics methods, including differential expression analysis, consensus clustering, and survival analysis, to investigate the role of CRGs. The functional consequences of various CRG expression patterns were further investigated using immune infiltration analysis and gene set variation analysis (GSVA). A scoring system based on CRGs was developed to predict overall survival (OS) and treatment responses in SKCM patients. The predictive accuracy of this score system was then tested, and a nomogram was used to improve its clinical usefulness.

Results

Key findings from this study include significant genetic alterations in circadian rhythm-related genes (CRGs) in skin cutaneous melanoma (SKCM), such as mutations and CNVs. Two molecular subtypes with distinct clinical outcomes and immune profiles were identified. A prognostic model based on six CRGs (CMTM, TNPO1, CTBS, UTRN, HK2, and LIF) was developed and validated with TCGA and GEO datasets, showing high predictive accuracy for overall survival (OS). A high CRGs score correlated with poor OS, immune checkpoint expression, and reduced sensitivity to several chemotherapeutics, including AKT inhibitor VIII and Camptothecin.

Conclusions

This work provides valuable insights into the circadian regulation of SKCM and underscores the potential of CRGs as biomarkers for prognosis and targets for therapeutic interventions. The novel molecular subtypes and CRGs prognostic scoring model introduced in this study offer significant contributions to the understanding and management of SKCM.

Immune cell infiltration as a prognostic factor in endometrial cancer: a meta-analysis

The immune system's role in cancer development and progression is receiving increasing attention. Endometrial cancer, common gynecological malignancy, has exhibited promising responses to immunotherapies. This study aims to assess the prognostic significance of various immune cell subsets in endometrial cancer, focusing on potential novel biomarkers and therapeutic targets. A systematic literature review and meta-analysis were conducted. Eleven eligible studies, comprising 2,319 patients with endometrial cancer, were included. The primary outcome was the association between levels of immune cell types, particularly CD8+ T cells, and overall prognosis. The meta-analysis found that high levels of tumor-infiltrating lymphocytes (TILs), particularly CD8+ T cells, were significantly associated with better overall prognosis in endometrial cancer patients. These findings suggest that the tumor immune microenvironment plays a crucial role in endometrial cancer prognosis. This meta-analysis indicates that higher levels of CD8+ T cells in the tumor microenvironment are linked to improved prognosis in endometrial cancer, underscoring the immune system's potential in prognostication and therapy.

NLRP4 unlocks an NK/macrophages-centered ecosystem to suppress non-small cell lung cancer

BACKGROUND

Tumor immune evasion extends beyond T cells, affecting innate immune elements like natural killer cells (NK) and macrophages within the tumor-immune microenvironment (TIME). Nevertheless, translational strategies to trigger collaboration of NK cells and macrophages to initiate sufficient anti-tumor cytoxicity remain scarce and are urgently needed.

METHODS

In this study, TCGA datasets was used to confirm the prognosis value of the expression level of NLR family pyrin domain containing 4 (NLRP4) in NSCLC and the tumor tissues microarray was used to further check its clinical-relevance at protein-level. Subsequently, a tumor cell line with stable NLRP4 overexpression was established and subcutaneous tumor models in C57BL/6J mice were used to validate the anti-tumor characteristics of NLRP4. After analyzing the tumor microenvironment using flow cytometry and multiplex immunofluorescence, we further validated our findings through co-culture transwell assays and TCGA analysis. Utilizing bulk-RNA sequencing, proteomics, and mass spectrometry of mouse tumor tissues, we innovatively identified the downstream pathways of NLRP4 and verified them through co-immunoprecipitation (co-IP) and Western blot (WB) experiments.

RESULTS

NLRP4 could trigger a distinct anti-tumor ecosystem organized by TIGIT+TNFA+ NK and iNOS+ M1 in lung cancer, discovered in TCGA analysis and verified in murine model. NLRP4-eco exerted tumor-suppression capacity through chemokine reprogramming including CCL5 and CXCL2. Meanwhile, the cytoxicity of NK could be facilitated by iNOS+M1. Mechanistically, NLRP4 stimulated PI3K/Akt-NF-kB axis through suppression of the activity of PP2A. Besides, knockdown of CCL5 and blockade of CXCL2-CXCR2 axis abolished chemotaxis of TIGIT+TNFA+ NK and iNOS+ M1 respectively, as well as for LB-100, a PP2A inhibitor.

CONCLUSION

Altogether, we delineated NLRP4's unexplored facets and discovered an NLRP4-driven anti-tumor ecosystem composed of TIGIT+TNFA+ NK and iNOS+ M1. Finally, targeting PP2A by its inhibitor successfully mimicked the anti-tumor capacity of the overexpression of NLRP4.

Single-cell RNA sequencing revealed changes in the tumor microenvironment induced by radiotherapy for cervical cancer and the molecular mechanism of mast cells in immunosuppression

Radiotherapy (RT) is an important treatment for cervical cancer (CC), effectively controlling tumor growth and improving survival rates. However, radiotherapy-induced cell heterogeneity and its underlying mechanisms remain unclear, which may potentially impact treatment efficacy. This study aims to investigate tumor microenvironment changes following radiotherapy for CC, hoping to provide evidence to improve the therapeutic effects of radiotherapy. For the first time, we applied single-cell RNA sequencing (scRNA-seq) to analyze tissue samples from three CC patients pre- and post-radiotherapy. We obtained gene expression data from 52,506 cells to identify the cellular changes and molecular mechanisms induced by radiotherapy. Radiotherapy significantly alters cellular composition and gene expression within the tumor microenvironment (TME), notably upregulating mast cell expression. Mast cells are involved in multiple cell axes in the CC ecosystem after radiotherapy, and play a pivotal role in tumor immunosuppression and matrix remodeling. scRNA-seq revealed gene expression variations among cell types after radiotherapy, underscoring the importance of specific cell types in modulating the TME post-treatment. This study revealed the molecular mechanism of radiotherapy for CC and the role of mast cells, providing a foundation for optimizing the personalized treatment of CC.

An intraepithelial ILC1-like natural killer cell subset produces IL-13

Natural killer (NK) cells are innate immune effectors with considerable heterogeneity and potent antitumor capabilities. Intraepithelial ILC1 (ieILC1)-like NK cells, a population of cytotoxic tissue-resident innate lymphoid cells, have recently been documented in the microenvironment of head and neck squamous cell carcinomas (HNSCC) and other solid tumors. These cells have antitumor cytolytic potential and are potent producers of type 1 cytokines, including IFNγ. Here, we identify a subpopulation of ex vivo differentiated ieILC1-like NK cells that produce IL-13 upon stimulation. Functional characterization revealed that these cells co-expressed IFNγ and IL-13 while maintaining an ILC1 transcriptional signature. IL-13 was induced either upon co-culture with tumor cell lines, or in response to TGF-β and IL-15. IL-13-expressing ieILC1-like NK cells were identified among tumor infiltrating lymphocytes expanded from patient HNSCC tumors, in support of their in vivoexistence in primary tumors. These data demonstrate additional heterogeneity within the ieILC1-like NK cell population than previously appreciated and highlight a unique form of ILC plasticity in which cells with clear ILC1 transcriptional profiles express a type 2 cytokine. With the known roles of IL-13 in cancer cell growth dynamics and immunoregulation, the identification of this subset within tumor microenvironments presents a potential target for therapeutic manipulation.

STING in cancer immunoediting: Modeling tumor-immune dynamics throughout cancer development

Cancer immunoediting is a dynamic process of tumor-immune system interaction that plays a critical role in cancer development and progression. Recent studies have highlighted the importance of innate signaling pathways possessed by both cancer cells and immune cells in this process. The STING molecule, a pivotal innate immune signaling molecule, mediates DNA-triggered immune responses in both cancer cells and immune cells, modulating the anti-tumor immune response and shaping the efficacy of immunotherapy. Emerging evidence has shown that the activation of STING signaling has dual opposing effects in cancer progression, simultaneously provoking and restricting anti-tumor immunity, and participating in every phase of cancer immunoediting, including immune elimination, equilibrium, and escape. In this review, we elucidate the roles of STING in the process of cancer immunoediting and discuss the dichotomous effects of STING agonists in the cancer immunotherapy response or resistance. A profound understanding of the sophisticated roles of STING signaling pathway in cancer immunoediting would potentially inspire the development of novel cancer therapeutic approaches and overcome the undesirable protumor effects of STING activation.

Lymphocytes-Associated Extracellular Vesicles Activate Natural Killer Cells in HNSCC

Small extracellular vesicles (sEVs) facilitate intercellular communication and play a pivotal role in tumor progression. Accumulated evidence has indicated the diversity of sEVs but with limited results revealing the landscape of heterogeneity of sEVs. The heterogeneity of cargo RNA in sEVs presents the different cell origins and indicates different functions. Here, we analyzed the heterogeneity of sEVs at droplet levels from single-cell RNA sequencing results of head and neck squamous cell carcinoma (HNSCC) with the previously reported algorithm SEVtras. With the sEVs secretion activity calculated by SEVtras, we also found that the T cells held the major role of sEVs secretion. In addition, we found these sEVs secreted by T cells increased the cytotoxic ability of natural killer cells (NK cells), which illustrated an indirect manner for the anti-tumor function of T cells. These results revealed the heterogeneity of cargo RNA of sEVs in HNSCC and underlined a sEVs-dependent manner in which T cells act on NK cells and anti-tumor immunity.

High-dimensional deconstruction of HNSC reveals clinically distinct cellular states and ecosystems that are associated with prognosis and therapy response

BACKGROUND

Characterizing the variety of cell types in the tumor microenvironment (TME) and their organization into cellular communities is vital for elucidating the biological diversity of cancer and informing therapeutic strategies.

METHODS

Here, we employed a machine learning-based algorithm framework, EcoTyper, to analyze single-cell transcriptomes from 139 patients with head and neck squamous cell carcinoma (HNSC)and gene expression profiles from 983 additional HNSC patients, aiming to delineate the fundamental cell states and ecosystems integral to HNSC.

RESULTS

A diverse landscape of 66 cell states and 9 ecosystems within the HNSC microenvironment was identified, revealing classical cell types while also expanding upon previous immune classifications. Survival analysis revealed that specific cell states and ecotypes (ecosystems) are associated with patient prognosis, underscoring their potential as indicators of clinical outcomes. Moreover, distinct cell states and ecotypes exhibited varying responses to immunotherapy and chemotherapy, with several showing promise as predictive biomarkers for treatment efficacy.

CONCLUSION

Our large-scale integrative transcriptome analysis provides high-resolution insights into the cellular states and ecosystems of HNSC, facilitating the discovery of novel biomarkers and supporting the development of precision therapies.

The spatial landscape of cancer hallmarks reveals patterns of tumor ecological dynamics and drug sensitivity

Tumors are complex ecosystems of interacting cell types. The concept of cancer hallmarks distills this complexity into underlying principles that govern tumor growth. Here, we explore the spatial distribution of cancer hallmarks across 63 primary untreated tumors from 10 cancer types using spatial transcriptomics. We show that hallmark activity is spatially organized, with the cancer compartment contributing to the activity of seven out of 13 hallmarks, while the tumor microenvironment (TME) contributes to the activity of the rest. Additionally, we discover that genomic distance between tumor subclones correlates with differences in hallmark activity, even leading to clone-hallmark specialization. Finally, we demonstrate interdependent relationships between hallmarks at the junctions of TME and cancer compartments and how they relate to sensitivity to different neoadjuvant treatments in 33 bladder cancer patients from the DUTRENEO trial. In conclusion, our findings may improve our understanding of tumor ecology and help identify new drug biomarkers.

Comprehensive analysis of lipid metabolic signatures identified CEBPD promotes breast cancer cell proliferation

Breast cancer (BRCA) remains the leading cause of cancer-related mortality worldwide, with lipid metabolism emerging as a critical factor in tumor progression that influences cell proliferation, migration, and immune response. Insights into lipid metabolism signatures and associated genes may offer new prognostic and therapeutic avenues. In this study, we leveraged scRNA-seq and bulk transcriptome data to assess the expression patterns and prognostic significance of lipid metabolism-related genes in BRCA. Through single-cell transcriptomic analysis of primary BRCA samples, we identified a specific set of lipid metabolism signature genes and constructed a prognostic risk model based on these signatures. This model enables patient stratification by risk scores, supporting an integrated analysis of lipid metabolism, immune landscape, and clinical outcomes. Importantly, we identified CEBPD, ABCA1, and CYP27A1 as independent prognostic genes linked to lipid metabolism, with functional assays revealing an inhibitory role for CEBPD in BRCA cell proliferation. Our findings underscore the influence of adipocytes in BRCA progression and propose CEBPD as a potential target for therapeutic intervention. This study provides a foundation for further exploration of metabolism-based strategies to enhance BRCA outcomes.

The comprehensive potential of AQP1 as a tumor biomarker: evidence from kidney neoplasm cohorts, cell experiments and pan-cancer analysis

Aquaporin1 (AQP1) facilitates water transport. Its ability to be a biomarker at the pan-cancer level remains uninvestigated. We performed immunohistochemical staining on tissues from 370 individuals with kidney neoplasms to measure AQP1 expression. We utilized Kaplan-Meier survival analysis, Chi-square tests, and multivariate Cox regression analyses to assess the prognostic relevance of AQP1 expression. In the pan-cancer context, we explored AQP1's competing endogenous RNAs network, protein-protein interactions, genomic changes, gene set enrichment analysis (GSEA), the correlation of AQP1 expression with survival outcomes, drug sensitivity, drug molecular docking, tumor purity and immunity. AQP1 shRNA expressing 786-O cells were established. Cell proliferation was assessed by Cell Counting Kit-8 and colony formation. Transwell migration, invasion, and cell scratch assays were conducted. In our study, AQP1 expression was an independent protective factor for OS and PFS in renal cancer patients. AQP1 expression significantly correlated with survival outcomes in renal cancers, LGG, SARC, HNSC and UVM. PI-103 sensitivity was related to AQP1 expression and had potential binding cite with AQP1 protein. Knockdown of AQP1 reduced cell proliferation, migration and invasion. Our study uncovered AQP1 as a biomarker for favorable survival outcomes in renal cancers. Furthermore, the bioinformatic analysis promoted its implication in pan-cancer scope.