A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

IL-32-producing CD8+ memory T cells define immunoregulatory niches in human cutaneous leishmaniasis

Human cutaneous leishmaniasis (CL) is characterized by chronic skin pathology. Experimental and clinical data suggest that immune checkpoints (ICs) play a crucial role in disease outcome, but the cellular and molecular niches that facilitate IC molecule expression during leishmaniasis are ill defined. In Sri Lankan patients with CL, indoleamine 2,3-dioxygenase 1 (IDO1) and programmed death-ligand 1 (PD-L1) were enriched in skin lesions, and reduced PD-L1 expression early after treatment initiation was predictive of a cure rate following antimonial therapy. Here, we used spatial cell interaction mapping to identify IL-32-expressing CD8+ memory T cells and Tregs as key components of the IDO1/PD-L1 niche in Sri Lankan patients with CL and in patients with distinct forms of dermal leishmaniasis in Brazil and India. Furthermore, the abundance of IL-32+ cells and IL-32+CD8+ T cells at treatment initiation was negatively correlated with the rate of cure in Sri Lankan patients. This study provides insights into the spatial mechanisms underpinning IC expression during CL and offers a strategy for identifying additional biomarkers of treatment response.

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.

SLC35A2-mediated bisected GlcNAc-modified extracellular vesicles enhance immune regulation in breast cancer lung metastasis

This study investigates the role of SLC35A2-mediated bisected GlcNAc-modified small extracellular vesicles (sEVs) in breast cancer (BC) lung metastasis. By modulating B3GALT1 expression, these sEVs regulate the pre-metastatic immune microenvironment, enhancing CD8+ T cell infiltration and reducing immune evasion. The use of β-peptide-loaded sEVs further amplifies anti-metastatic effects, as demonstrated in vivo mouse models and molecular analyses. These findings underscore the therapeutic potential of glycosylation-modified sEVs in enhancing immune responses and controlling BC metastasis.

Understanding rheumatic disease through continuous cell state analysis

Autoimmune rheumatic diseases are a heterogeneous group of conditions, including rheumatoid arthritis (RA) and systemic lupus erythematosus. With the increasing availability of large single-cell datasets, novel disease-associated cell types continue to be identified and characterized at multiple omics layers, for example, 'T peripheral helper' (TPH) (CXCR5- PD-1hi) cells in RA and systemic lupus erythematosus and MerTK+ myeloid cells in RA. Despite efforts to define disease-relevant cell atlases, the very definition of a 'cell type' or 'lineage' has proven controversial as higher resolution assays emerge. This Review explores the cell types and states involved in disease pathogenesis, with a focus on the shifting perspectives on immune and stromal cell taxonomy. These understandings of cell identity are closely related to the computational methods adopted for analysis, with implications for the interpretation of single-cell data. Understanding the underlying cellular architecture of disease is also crucial for therapeutic research as ambiguity hinders translation to the clinical setting. We discuss the implications of different frameworks for cell identity for disease treatment and the discovery of predictive biomarkers for stratified medicine - an unmet clinical need for autoimmune rheumatic diseases.

A highly resolved integrated transcriptomic atlas of human breast cancers

In this study, we developed an integrated single cell transcriptomic (scRNAseq) atlas of human breast cancer (BC), the largest resource of its kind, totaling > 600,000 cells across 138 patients. Rigorous integration and annotation of publicly available scRNAseq data enabled a highly resolved characterization of epithelial, immune, and stromal heterogeneity within the tumor microenvironment (TME). Within the immune compartment we were able to characterize heterogeneity of CD4, CD8 T cells and macrophage subpopulations. Within the stromal compartment, subpopulations of endothelial cells (ECs) and cancer associated fibroblasts (CAFs) were resolved. Within the cancer epithelial compartment, we characterized the functional heterogeneity of cells across the axes of stemness, epithelial-mesenchymal plasticity, and canonical cancer pathways. Across all subpopulations observed in the TME, we performed a multi-resolution survival analysis to identify epithelial cell states and immune cell types which conferred a survival advantage in both The Cancer Genome Atlas (TCGA) and METABRIC. We also identified robust associations between TME composition and clinical phenotypes such as tumor subtype and grade that were not discernible when the analysis was limited to individual datasets, highlighting the need for atlas-based analyses. This atlas represents a valuable resource for further high-resolution analyses of TME heterogeneity within BC.

Nervous system-gut microbiota-immune system axis: future directions for preventing tumor

Tumor is one of the leading causes of death worldwide. The occurrence and development of tumors are related to multiple systems and factors such as the immune system, gut microbiota, and nervous system. The immune system plays a critical role in tumor development. Studies have also found that the gut microbiota can directly or indirectly affect tumorigenesis and tumor development. With increasing attention on the tumor microenvironment in recent years, the nervous system has emerged as a novel regulator of tumor development. Some tumor therapies based on the nervous system have also been tested in clinical trials. However, the nervous system can not only directly interact with tumor cells but also indirectly affect tumor development through the gut microbiota. The nervous system-mediated gut microbiota can regulate tumorigenesis, growth, invasion, and metastasis through the immune system. Here, we mainly explore the potential effects of the nervous system-gut microbiota-immune system axis on tumorigenesis and tumor development. The effects of the nervous system-gut microbiota-immune system axis on tumors involve the nervous system regulating immune cells through the gut microbiota, which can prevent tumor development. Meanwhile, the direct effects of the gut microbiota on tumors and the regulation of the immune system by the nervous system, which can affect tumor development, are also reviewed.

Single-cell RNA sequencing dissects the immunosuppressive signatures in Helicobacter pylori-infected human gastric ecosystem

Helicobacter pylori (H. pylori) manipulates the host immune system to establish a persistent colonization, posing a serious threat to human health, but the mechanisms remain poorly understood. Here we integrate single-cell RNA sequencing and TCR profiling for analyzing 187,192 cells from 11 H. pylori-negative and 12 H. pylori-positive individuals to describe the human gastric ecosystem reprogrammed by H. pylori infection, as manifested by impaired antigen presentation and phagocytosis function. We further delineate a monocyte-to-C1QC+ macrophage differentiation trajectory driven by H. pylori infection, while T cell responses exhibit broad functional impairment and hyporesponsiveness with restricted clonal expansion capacity. We also identify an HLA-DRs- and CTLA4-expressing T cell population residing in H. pylori-inhabited stomach that potentially contribute to immune evasion. Together, our findings provide single-cell resolution information into the immunosuppressive microenvironment shaped by H. pylori infection, offering critical insights for developing novel therapeutic approaches to eliminate this globally prevalent pathogen.

Molecular mechanisms and clinical significance of perineural invasion in malignancies: the pivotal role of tumor-associated Schwann cells in cancer progression and metastasis

Perineural invasion (PNI) is a pathological process wherein cancer cells invade and spread along peripheral nerves, contributing to tumor aggressiveness and poor clinical outcomes, including increased recurrence, metastasis, and reduced survival. Tumor-associated Schwann cells (SCs) play a pivotal role in facilitating PNI by promoting epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, and immune modulation. These cells actively support tumor progression through neurotrophin, cytokine, chemokine, and neurotransmitter signaling, enhancing cancer cell migration along neural pathways. Recent advances in imaging techniques, single-cell transcriptomics, and molecular profiling have provided deeper insights into the tumor microenvironment's role in PNI. Emerging therapeutic strategies targeting neurotrophin-mediated signaling and SC-tumor interactions have shown promise in preclinical models. However, significant research gaps remain, particularly in understanding the heterogeneity of SCs and their molecular subtypes in PNI across different malignancies. This review highlights the clinical significance, molecular mechanisms, and potential therapeutic targets associated with PNI. A comprehensive understanding of tumor-SC interactions is essential for developing targeted interventions to mitigate PNI-driven malignancies. Future research should focus on integrating multi-omics approaches and novel therapeutics to improve early detection and treatment, ultimately enhancing patient outcomes.

Deubiquitinase USP24 activated by IL-6/STAT3 enhances PD-1 protein stability and suppresses T cell antitumor response

Persisting programmed cell death-1 (PD-1) signaling impairs T cell effector function, which is highly associated with T cell exhaustion and immunotherapy failure. However, the mechanism responsible for PD-1 deubiquitination and T cell dysfunction remains unclear. Here, we show that ubiquitin-specific peptidase 24 (USP24) promotes PD-1 protein stability by removing K48-linked polyubiquitin. Increased interleukin-6 level transcriptionally activates the USP24 expression, which leads to PD-1 stabilization. Furthermore, USP24 deficiency reduces PD-1 levels in CD8+ T cells and attenuates EgfrL858R-driven lung tumorigenesis in Usp24C1695A catalytic deficient mice. Targeting PD-1 stability with the USP24-specific inhibitor USP24-i-101 boosts cytotoxic T cell activity, restrains lung tumor growth, and achieves superior therapeutic effects when combined with anti-CTLA4 immunotherapy. Clinically, patients with lung cancer exhibiting high USP24 expression in tumor-infiltrating CD8+ T cells display exhausted features and show unfavorable responses to immunotherapy. Our findings dissect the mechanism for regulating enhanced PD-1 stability in tumor-infiltrating CD8+ T cells and reveal USP24 as a potential target of antitumor immunotherapy.

Deciphering immune predictors of immunotherapy response: A multiomics approach at the pan-cancer level

Immune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet many patients fail to respond. Employing single-cell multiomics, we unveil T cell dynamics influencing ICB response across 480 pan-cancer and 27 normal tissue samples. We identify four immunotherapy response-associated T cells (IRATs) linked to responsiveness or resistance and analyze their pseudotemporal patterns, regulatory mechanisms, and T cell receptor clonal expansion profiles specific to each response. Notably, transforming growth factor β1 (TGF-β1)+ CD4+ and Temra CD8+ T cells negatively correlate with therapy response, in stark contrast to the positive response associated with CXCL13+ CD4+ and CD8+ T cells. Validation with a cohort of 23 colorectal cancer (CRC) samples confirms the significant impact of TGF-β1+ CD4+ and CXCL13+ CD4+ and CD8+ T cells on ICB efficacy. Our study highlights the effectiveness of single-cell multiomics in pinpointing immune markers predictive of immunotherapy outcomes, providing an important resource for crafting targeted immunotherapies for successful ICB treatment across cancers.

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data

Background

Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However, limitations of the technology such as the relatively low resolution and comparatively insufficient sequencing depth make it difficult to reliably extract real biological signals from these data. To alleviate this challenge, we propose a novel transfer learning framework, referred to as TransST, to adaptively leverage the cell-labeled information from external sources in inferring cell-level heterogeneity of a target spatial transcriptomics data.

Results

Applications in several real studies as well as a number of simulation settings show that our approach significantly improves existing techniques. For example, in the breast cancer study, TransST successfully identifies five biologically meaningful cell clusters, including the two subgroups of cancer in situ and invasive cancer; in addition, only TransST is able to separate the adipose tissues from the connective issues among all the studied methods.

Conclusions

In summary, the proposed method TransST is both effective and robust in identifying cell subclusters and detecting corresponding driving biomarkers in spatial transcriptomics data.

Uncovering gene and cellular signatures of immune checkpoint response via machine learning and single-cell RNA-seq

Immune checkpoint inhibitors have transformed cancer therapy. However, only a fraction of patients benefit from these treatments. The variability in patient responses remains a significant challenge due to the intricate nature of the tumor microenvironment. Here, we harness single-cell RNA-sequencing data and employ machine learning to predict patient responses while preserving interpretability and single-cell resolution. Using a dataset of melanoma-infiltrated immune cells, we applied XGBoost, achieving an initial AUC score of 0.84, which improved to 0.89 following Boruta feature selection. This analysis revealed an 11-gene signature predictive across various cancer types. SHAP value analysis of these genes uncovered diverse gene-pair interactions with non-linear and context-dependent effects. Finally, we developed a reinforcement learning model to identify the most informative single cells for predictivity. This approach highlights the power of advanced computational methods to deepen our understanding of cancer immunity and enhance the prediction of treatment outcomes.

CD103+CD56+ ILCs Are Associated with an Altered CD8+ T-cell Profile within the Tumor Microenvironment

Immunotherapies have had unprecedented success in the treatment of multiple cancer types, albeit with variable response rates. Unraveling the complex network of immune cells within the tumor microenvironment (TME) may provide additional insights to enhance antitumor immunity and improve clinical response. Many studies have shown that NK cells or innate lymphoid cells (ILC) have regulatory capacity. Here, we identified CD103 as a marker that was found on CD56+ cells that were associated with a poor proliferative capacity of tumor-infiltrating lymphocytes in culture. We further demonstrated that CD103+CD56+ ILCs isolated directly from tumors represented a distinct ILC population that expressed unique surface markers (such as CD49a and CD101), transcription factor networks, and transcriptomic profiles compared with CD103-CD56+ NK cells. Using single-cell multiomic and spatial approaches, we found that these CD103+CD56+ ILCs were associated with CD8+ T cells with reduced expression of granzyme B. Thus, this study identifies a population of CD103+CD56+ ILCs with potentially inhibitory functions that are associated with a TME that includes CD8+ T cells with poor antitumor activity. Further studies focusing on these cells may provide additional insights into the biology of an inhibitory TME.

Cancer-associated fibroblasts in breast cancer in the single-cell era: Opportunities and challenges

Breast cancer is a leading cause of morbidity and mortality in women, and its progression is closely linked to the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), key components of the TME, play a crucial role in promoting tumor growth by driving cancer cell proliferation, invasion, extracellular matrix (ECM) remodeling, inflammation, chemoresistance, and immunosuppression. CAFs exhibit considerable heterogeneity and are classified into subgroups based on different combinations of biomarkers. Single-cell RNA sequencing (scRNA-seq) enables high-throughput and high-resolution analysis of individual cells. Relying on this technology, it is possible to cluster complex CAFs according to different biomarkers to analyze the specific phenotypes and functions of different subpopulations. This review explores CAF clusters in breast cancer and their associated biomarkers, highlighting their roles in disease progression and potential for targeted therapies.

Deciphering T-cell exhaustion in the tumor microenvironment: paving the way for innovative solid tumor therapies

In solid tumors, the tumor microenvironment (TME) is a complex mix of tumor, immune, stromal cells, fibroblasts, and the extracellular matrix. Cytotoxic T lymphocytes (CTLs) constitute a fraction of immune cells that may infiltrate into the TME. The primary function of these T-cells is to detect and eliminate tumor cells. However, due to the immunosuppressive factors present in the TME primarily mediated by Myeloid-Derived Suppressor Cells (MDSCs), Tumor associated macrophages (TAMs), Cancer Associated Fibroblasts (CAFs) as well as the tumor cells themselves, T-cells fail to differentiate into effector cells or become dysfunctional and are unable to eliminate the tumor. In addition, chronic antigen stimulation within the TME also leads to a phenomenon, first identified in chronic lymphocytic choriomeningitis virus (LCMV) infection in mice, where the T-cells become exhausted and lose their effector functions. Exhausted T-cells (Tex) are characterized by the presence of remarkably conserved inhibitory receptors, transcription and signaling factors and the downregulation of key effector molecules. Tex cells have been identified in various malignancies, including melanoma, colorectal and hepatocellular cancers. Recent studies have indicated novel strategies to reverse T-cell exhaustion. These include checkpoint inhibitor blockade targeting programmed cell death protein 1 (PD-1), T-cell immunoglobulin and mucin-domain containing-3 (Tim-3), cytotoxic T-lymphocyte associated protein 4 (CTLA-4), or combinations of different immune checkpoint therapies (ICTs) or combination of ICTs with cytokine co-stimulation. In this review, we discuss aspects of T-cell dysfunction within the TME with a focus on T-cell exhaustion. We believe that gaining insight into the mechanisms of T-cell exhaustion within the TME of human solid tumors will pave the way for developing therapeutic strategies to target and potentially re-invigorate exhausted T-cells in cancer.

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.

Dynamics of T cell subpopulations and plasma cytokines during the first year of antineoplastic therapy in patients with breast cancer: the BEGYN-1 study

BACKGROUND

The role of T cell immunity during antineoplastic therapy is poorly understood. In the BEGYN-1 study, patients with breast cancer underwent quarterly assessments prior to and during antineoplastic therapy over a period of 12 months.

METHODS

We used flow cytometry and multiplex immunoassays to quantify 25 T cell subpopulations and seven T cell associated plasma cytokines in peripheral blood from 92 non-metastatic breast cancer patients, respectively. In addition, the association between T cell dynamics and the outcome of patients undergoing neoadjuvant chemotherapy was investigated.

RESULTS

In patients undergoing chemotherapy, a significant reduction in T helper (Th) cells, particularly naïve central and effector cells and thymus positive Th cells, was observed over time. Interestingly, Th1 immune response-associated cytokines (IL-12, TNF, IFN-γ) declined while Th2 cells and cytotoxic T cells increased over time.

CONCLUSIONS

We conclude that in breast cancer patients, chemotherapy is associated with a transition from a Th1 immune response towards Th2 and an increase in cytotoxic T cells, whereas in patients without chemotherapy, these alterations were less pronounced. Future studies should clarify whether patterns of T cell subsets or plasma cytokines can be used as biomarkers to monitor or even improve therapeutic interventions.

Spatial transcriptomics reveals tryptophan metabolism restricting maturation of intratumoral tertiary lymphoid structures

Tertiary lymphoid structures (TLSs) are ectopic lymphoid aggregates found in numerous cancers, often linked to enhanced immunotherapy responses and better clinical outcomes. However, the factors driving TLS maturation are not fully understood. Using near single-cell spatial transcriptomic mapping, we comprehensively profile TLSs under various maturation stages and their microenvironment in hepatocellular carcinoma (HCC). Based on their developmental trajectories, we classify immature TLSs into two groups: conforming and deviating TLSs. Our findings indicate that conforming TLSs, similar to mature TLSs, possess a niche function for immunotherapy responses, while deviating TLSs do not. We discover that the tryptophan-enriched metabolic microenvironment shaped by malignant cells contributes to the deviation of TLS maturation. Inhibiting tryptophan metabolism promotes intratumoral TLS maturation and enhances tumor control, synergizing with anti-PD-1 treatments. Therefore, promoting TLS maturation represents a potential strategy to improve antitumor responses and immunotherapy outcomes.

Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC

Racial disparities in the clinical outcomes of triple-negative breast cancer (TNBC) have been well-documented, but the underlying biological mechanisms remain poorly understood. To investigate these disparities, we employed a multi-omic approach integrating imaging mass cytometry and spatial transcriptomics to characterize the tumor microenvironment (TME) in self-identified Black American (BA) and White American (WA) TNBC patients. Our analysis revealed that the TME in BA patients is marked by a network of endothelial cells, macrophages, and mesenchymal-like cells, which correlates with reduced patient survival. In contrast, the WA TNBC microenvironment is enriched in T-cells and neutrophils, indicative of T-cell exhaustion and suppressed immune responses. Ligand-receptor and pathway analyses further demonstrated that BA TNBC tumors exhibit a relatively "immune-cold" profile, while WA TNBC tumors display features of an "inflamed" TME, suggesting the evolution of a unique immunosuppressive mechanism. These findings provide insight into racially distinct tumor-promoting and immunosuppressive microenvironments, which may contribute to the observed differences in clinical outcomes among BA and WA TNBC patients.

Statement of Significance

This study identifies distinct tumor microenvironment (TME) profiles in Black and White American TNBC patients, providing new insights into the biological mechanisms driving outcome disparities. Our findings highlight the role of the tumor-endothelial-macrophage niche in these disparities, offering a potential therapeutic target for race-inclusive strategies aimed at improving clinical outcomes. By revealing racial differences in treatment response profiles, this work underscores the necessity for tailored therapies in TNBC. These insights lay the groundwork for the development of inclusive, precision-driven treatment approaches that may help mitigate racial disparities and enhance patient outcomes.

Double-Multiplex Immunostainings for Immune Profiling of Invasive Breast Carcinoma: Emerging Novel Immune-Based Biomarkers

The role of tumor microenvironment in invasive breast cancer prognosis and treatment is highly appreciated. With the advent of immunotherapy, immunophenotypic characterization in primary tumors is gaining attention as it can improve patient stratification. Here, we discuss the benefits of spatial analysis employing double and multiplex immunostaining, allowing the simultaneous detection of more than one protein on the same tissue section, which in turn helps us provide functional insight into infiltrating immune cells within tumors. We focus on studies demonstrating the prognostic and predictive impact of distinct tumor-infiltrating lymphocyte subpopulations including different CD8(+) T subsets as well as CD4(+) T cells and tumor-associated macrophages in invasive breast carcinoma. The clinical value of immune cell topography is also appreciated. We further refer to how the integration of digital pathology and artificial intelligence in routine practice could enhance the accuracy of multiplex immunostainings evaluation within the tumor microenvironment, maximizing our perception of host immune response, improving in turn decision-making towards more precise immune-associated therapies.

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

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

Immunosuppressive microenvironment of liver restrains chemotherapeutic efficacy in triple-negative breast cancer

BACKGROUND

Patients with liver metastases of triple-negative breast cancer (TNBC) show poor prognosis compared with other metastases. Chemotherapy is the primary treatment for advanced TNBC. Tumor cell diversity and the tumor microenvironment could affect therapeutic effect. However, whether liver metastases of TNBC exhibit differential chemotherapy efficacy compared with the primary tumors remains inadequately understood. The specific mechanisms that modulate chemotherapy efficacy in liver metastases need further investigation.

METHODS

Single-cell RNA sequencing data from public databases were leveraged to contrast the immune profiles of liver metastases and primary tumors in TNBC. Murine models bearing liver tumors or primary tumors of TNBC were used to evaluate chemotherapy efficacy. Techniques such as immunohistochemistry, wound healing assays, and colony formation assays were employed to account for tumor heterogeneity. Intratumoral T lymphocytes and macrophages were quantified and characterized using RNA sequencing, immunohistochemistry, and flow cytometry. Antibody-mediated depletion of CD8+T cells or macrophages in mice substantiated their impact on chemotherapy responses.

RESULTS

Single-cell RNA sequencing data showed the immune microenvironments of liver metastases and primary tumors exhibited significant differences, which may critically influence chemotherapy outcomes. Mouse models confirmed that chemotherapy was less effective against liver tumors compared with subcutaneous tumors. After excluding the influence of tumor cell heterogeneity, the weaker responsiveness in liver tumors was mediated by the impeded infiltration of CD8+T cells, attributed to the decreased activation of macrophages. Augmenting macrophage activation can improve the chemotherapeutic efficacy in liver tumors. Moreover, chemotherapy drove the immune microenvironment towards increased suppression through distinct mechanisms, with neutrophil extracellular traps (NETs) accumulating in liver tumors and impaired functionality of macrophages at the primary site. The combination of NET inhibitors or macrophage activators with chemotherapy enhanced treatment effectiveness.

CONCLUSIONS

These findings disclose the compromised chemotherapeutic efficacy in liver tumors of TNBC and elucidate the underlying immune-related mechanisms within the tumor microenvironment. Targeting the specific underpinnings of immune suppression at different tumor sites with selective drugs could optimize chemotherapeutic efficacy.

Profiling Multiple CD8+ T-cell Functional Dimensions Enhances Breast Cancer Immune Assessment

CD8+ T-cell abundance is insufficient to assess antitumor immunity and shows poor performance in predicting breast cancer prognosis and immunotherapy response, presumably owing to the complexity of CD8+ T-cell functionalities. Although single-cell RNA sequencing can dissect the multifaceted functions of CD8+ T cells for better immune assessment, its clinical application is limited. In this study, we developed bulk RNA sequencing-based FuncDimen models from integrative analysis of single-cell RNA sequencing and matched bulk RNA sequencing data to evaluate CD8+ T-cell functionalities across five dimensions: tumor reactivity, cytotoxicity, IFNγ secretion, proliferation, and apoptosis. The FuncDimen models quantifying different functional dimensions of CD8+ T cells were validated in our breast cancer cohort and external databases using immunofluorescence and imaging mass cytometry. We calculated the FuncAggre score by weighted aggregation of all five FuncDimen models to encapsulate the overall antitumor immunity. In our breast cancer cohort and external databases, the FuncAggre score demonstrated superior predictive performance for breast cancer prognosis (time-dependent AUC: 0.56-0.70) and immunotherapy response (AUC: 0.71-0.83) over other immune biomarkers, regardless of the breast cancer molecular subtype. Together, the FuncDimen models offer a refined assessment of antitumor immunity mediated by CD8+ T cells in the clinic, enhancing prognostic prediction and aiding personalized immunotherapy in breast cancer.

The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer

Background: Colorectal cancer (CRC) ranks as the third most common cancer worldwide. Tertiary lymphoid structures (TLSs), organized immune cell aggregates in non-lymphoid tissues, are linked to chronic inflammation and tumorigenesis. However, the precise relationship between TLSs and CRC prognosis remains unclear. This study aimed to develop a TLS-associated genetic signature to predict CRC prognosis and support clinical applications. Methods: Utilizing the TCGA database, we analyzed TLS-related gene expression in CRC versus normal tissues. Prognostic models were constructed using Cox and Kaplan-Meier analyses. CRC samples were stratified into high and low TLS groups via ssGSEA, with validation in the GSE75500 dataset. We identified clinical characteristics associated with TLS scores, created prognostic nomograms, analyzed the top 50 differential genes, assessed tumor mutations, estimated immune infiltration using CIBERSORT, and examined correlations between TLS scores and immune checkpoints. Results: A 13-gene TLS-associated prognostic model for CRC was developed, emphasizing immune response genes. Survival analysis indicated significantly better outcomes for the TLS-high group. Cox regression identified stage IV and M1 as independent factors influencing TLS scores. Nomogram analysis demonstrated that combining TLS scores with clinical features enhances prognostic accuracy. TLS scores were closely associated with immune checkpoint genes, suggesting potential immunotherapy benefits for TLS-high patients. Conclusions: This study developed and validated a TLS-based prognostic model for CRC, exploring relevant immune cells. The model holds promise for predicting clinical prognosis and treatment responsiveness in CRC patients.

Single-cell RNA sequencing identifies molecular biomarkers predicting late progression to CDK4/6 inhibition in patients with HR+/HER2- metastatic breast cancer

BACKGROUND

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6is) in combination with endocrine therapy are the standard treatment for patients with hormone receptor-positive, HER2-negative metastatic breast cancer (mBC). Despite the efficacy of CDK4/6is, intrinsic resistance occurs in approximately one-third of patients, highlighting the need for reliable predictive biomarkers.

METHODS

Single-cell RNA sequencing analyzed metastatic tumors from HR+/HER2- mBC patients pre-CDK4/6i treatment at baseline (BL) and/or at disease progression. BL samples were from CDK4/6i responders (median progression-free survival [mPFS] = 25.5 months), while progressors were categorized as early-progressors (EP, mPFS = 3 months) and late-progressors (LP, mPFS = 11 months). Metastatic sites included liver, pleural effusions, ascites, and bone. InferCNV distinguished tumor cells, and functional analysis utilized the Molecular Signatures Database.

RESULTS

LP tumors displayed enhanced Myc, EMT, TNF-α, and inflammatory pathways compared to those EP tumors. Samples from BL and LP responders showed increased tumor-infiltrating CD8+ T cells and natural killer (NK) cells compared to EP non-responders. Notably, despite a high frequency of CD8+ T cells in responding tumors, a functional analysis revealed significant upregulation of genes associated with stress and apoptosis in proliferative CD4+ and CD8+ T cells in BL tumors compared to in EP and LP tumors. These genes, including HSP90 and HSPA8, are linked to resistance to PD1/PD-L1 immune checkpoint inhibitors. A ligand-receptor analysis showed enhanced interactions associated with inhibitory T-cell proliferation (SPP1-CD44) and suppression of immune activity (MDK-NCL) in LP tumors. Longitudinal biopsies consistently revealed dynamic NK cell expansion and enhanced cytotoxic T cell activity, alongside upregulation of immune activity inhibition, in LP tumors compared to in BL tumors. Notably, the predictive biomarker panel from BL tumor cells was validated in 2 independent cohorts, where it consistently predicted a significant improvement in mPFS duration in signature-high versus -low groups.

CONCLUSION

This study underscores the significance of molecular biomarkers in predicting clinical outcomes to CDK4/6i. Tumor-infiltration CD8+ T and NK cells may also serve as baseline predictors. These insights pave the way for optimizing therapeutic strategies based on microenvironment-specific changes, providing a personalized and effective approach for managing HR+/HER2- mBC and improving patient outcomes.

Rapamycin enhances CAR-T control of HIV replication and reservoir elimination in vivo

Chimeric antigen receptor (CAR) T cell therapy shows promise for various diseases. Our studies in humanized mice and nonhuman primates demonstrate that hematopoietic stem cells (HSCs) modified with anti-HIV CAR achieve lifelong engraftment, providing functional antiviral CAR-T cells that reduce viral rebound after antiretroviral therapy (ART) withdrawal. However, T cell exhaustion due to chronic immune activation remains a key obstacle to sustained CAR-T efficacy, necessitating additional measures to achieve functional cure. We recently showed that low-dose rapamycin treatment reduced inflammation and improved anti-HIV T cell function in HIV-infected humanized mice. Here, we report that rapamycin improved CAR-T cell function both in vitro and in vivo. In vitro treatment with rapamycin enhanced CAR-T cell mitochondrial respiration and cytotoxicity. In vivo treatment with low-dose rapamycin in HIV-infected, CAR-HSC mice decreased chronic inflammation, prevented exhaustion of CAR-T cells, and improved CAR-T control of viral replication. RNA-sequencing analysis of CAR-T cells from humanized mice showed that rapamycin downregulated multiple checkpoint inhibitors and upregulated key survival genes. Mice treated with CAR-HSCs and rapamycin had delayed viral rebound after ART and reduced HIV reservoir compared with those treated with CAR-HSCs alone. These findings suggest that HSC-based anti-HIV CAR-T cells combined with rapamycin treatment are a promising approach for treating persistent inflammation and improving immune control of HIV replication.

Bone marrow breakout lesions act as key sites for tumor-immune cell diversification in multiple myeloma

The bone marrow microenvironment plays a crucial role in the development of multiple myeloma. As the disease progresses, malignant myeloma cells can evolve to survive outside the bone marrow. However, the processes underlying bone marrow independence and their consequences for immune control remain poorly understood. Here, we conducted single-cell and spatial multiomics analyses of bone marrow-confined intramedullary disease and paired breakout lesions that disrupt the cortical bone. These analyses revealed a distinct cellular microenvironment and architectural features of breakout lesions, characterized by extensive areas of malignant plasma cells interspersed with lesion-specific solitary natural killer and macrophage populations, as well as focal accumulations of immune cell agglomerates. Within these agglomerates, spatially confined T cell clones expanded alongside various immune cells, coinciding with the local genomic evolution of tumor cells. These analyses identify breakout lesions as a hotspot for tumor-immune cell interactions and diversification, representing a key event in myeloma pathogenesis.

Spatial Profiling Reveals Equivalence-Derived Molecular Signatures of Brain Mimicry and Adaptation in Breast Cancer Brain Metastases

Brain metastases (BrMets), common for advanced-stage breast cancer patients, are associated with poor median survival and accompanied by severe neurologic decline. Halting the progression of breast cancer brain metastases (BCBMs) may require modulation of the tumor microenvironment (TME), yet little is known about the impact of the primary breast TME on brain tropism, or how, once there, metastatic breast cancer cells coexist with brain-resident cells (e.g., neurons and glia). Traditionally, studies in this space have focused on differential expression analysis, overlooking potential insights gained from investigating genes with equivalent expression between groups. This is particularly crucial in distant metastasis, where tumor cells may co-opt the transcriptional programs of the host organ (e.g., brain) to facilitate successful seeding and outgrowth. Prior to our work, no computational framework existed to determine biologically-relevant equivalent gene expression. To resolve molecular mechanisms of BCBM enabled by metastatic cancer cells and/or resident brain cells, we leveraged Nanostring GeoMx to perform spatially-resolved transcriptomic profiling on 235 patient-derived tissue cores from BCBM (including adjacent normal brain), primary invasive breast cancers, and normal (non-cancer) brain; analyzing 18,677 RNAs in 450 areas of interest (AOIs). We introduce the "Equivalent Expression Index" a highly specific and accurate algorithm that identifies statistically significant "Equivalently-Expressed Genes". This method facilitated the identification of molecular remodeling and mimicry genes within tissue-specific TMEs. By integrating differential expression analysis with the Equivalent Expression Index, we discovered multiple novel gene signatures associated with BCBM and primary tumor brain-metastatic potential. We demonstrate that the Equivalent Expression Index is a powerful tool to uncover shared gene expression programs representing the adaptation of metastatic cells and brain-resident cells to the BCBM microenvironment.

Mannose metabolism reshapes T cell differentiation to enhance anti-tumor immunity

Cellular metabolic status profoundly influences T cell differentiation, persistence, and anti-tumor efficacy. Our single-cell metabolic analyses of T cells reveal that diminished mannose metabolism is a prominent feature of T cell dysfunction. Conversely, experimental augmentation/restoration of mannose metabolism in adoptively transferred T cells via D-mannose supplementation enhances anti-tumor activity and restricts exhaustion differentiation both in vitro and in vivo. Mechanistically, D-mannose treatment induces intracellular metabolic programming and increases the O-GlcNAc transferase (OGT)-mediated O-GlcNAcylation of β-catenin, which preserves Tcf7 expression and epigenetic stemness, thereby promoting stem-like programs in T cells. Furthermore, in vitro expansion with D-mannose supplementation yields T cell products for adoptive therapy with stemness characteristics, even after extensive long-term expansion, that exhibits enhanced anti-tumor efficacy. These findings reveal cell-intrinsic mannose metabolism as a physiological regulator of CD8+ T cell fate, decoupling proliferation/expansion from differentiation, and underscoring the therapeutic potential of mannose modulation in cancer immunotherapy.

Tertiary lymphoid structures and cancer immunotherapy: From bench to bedside

Tertiary lymphoid structures (TLSs) are organized ectopic lymphoid aggregates within the tumor microenvironment that serve as crucial sites for the development of adaptive antitumor cellular and humoral immunity. TLSs have been consistently documented in numerous cancer types, correlating with improved prognosis and enhanced responses to immunotherapy, especially immune-checkpoint blockade (ICB). Given the potential role of TLSs as predictive biomarkers for the efficacy of ICB in cancer patients, the therapeutic manipulation of TLSs is gaining significant attention as a promising avenue for cancer treatment. Herein, we comprehensively review the composition, definition, and detection methods of TLSs in humans. We also discuss the contributions of TLSs to antitumor immunity, their prognostic value in cancer patients, and their association with therapeutic response to ICB-based immunotherapy. Finally, we present preclinical data supporting the potential of therapeutically manipulating TLSs as a promising approach for innovative cancer immunotherapy.

Distant Metastases of Breast Cancer Resemble Primary Tumors in Cancer Cell Composition but Differ in Immune Cell Phenotypes

Breast cancer is the most commonly diagnosed cancer in women, with distant metastasis being the main cause of breast cancer-related deaths. Elucidating the changes in the tumor and immune ecosystems that are associated with metastatic disease is essential to improve understanding and ultimately treatment of metastasis. Here, we developed an in-depth, spatially resolved single-cell atlas of the phenotypic diversity of tumor and immune cells in primary human breast tumors and matched distant metastases, using imaging mass cytometry to analyze a total of 75 unique antibody targets. Although the same tumor cell phenotypes were typically present in primary tumors and metastatic sites, suggesting a strong founder effect of the primary tumor, their proportions varied between matched samples. Notably, the metastatic site did not influence tumor phenotype composition, except for the brain. Metastatic sites exhibited a lower number of immune cells overall but had a higher proportion of myeloid cells as well as exhausted and cytotoxic T cells. Myeloid cells showed distinct tissue-specific compositional signatures and increased presence of potentially matrix remodeling phenotypes in metastatic sites. This analysis of tumor and immune cell phenotypic composition of metastatic breast cancer highlights the heterogeneity of the disease within patients and across distant metastatic sites, indicating myeloid cells as the predominant immune modulators that could potentially be targeted at these sites. Significance: Multiplex imaging analysis of matched primary and metastatic breast tumors provides a phenotypic and spatial map of tumor microenvironments, revealing similar compositions of cancer cells and divergent immunologic features between matched samples.

Disrupting EDEM3-induced M2-like macrophage trafficking by glucose restriction overcomes resistance to PD-1/PD-L1 blockade

BACKGROUND

Immunotherapy is beneficial for some colorectal cancer (CRC) patients, but immunosuppressive networks limit its effectiveness. Cancer-associatedfibroblasts (CAFs) are significant in immune escape and resistance toimmunotherapy, emphasizing the urgent need for new treatment strategies.

METHODS

Flow cytometric, Western blotting, proteomics analysis, analysis of public database data, genetically modified cell line models, T cell coculture, crystal violetstaining, ELISA, metabonomic and clinical tumour samples were conducted to assess the role of EDEM3 in immune escape and itsmolecular mechanisms. We evaluated theeffects of FMD plus 2-DG on antitumour immunity using multipleximmunofluorescence, flow cytometry, cytokine profiling, TUNEL assays, xenografttumours, and in vivo studies.

RESULTS

We show thatCAFs upregulate PD-L1 glycosylation and contribute to immune evasion byglycosyltransferase EDEM3. Additionally, EDEM3 plays a role in tumour immunityduring tumour progression. However, the EDEM3-mediated upregulation of PD-L1 expression underpins PD-1/PD-L1 blockade resistance in vivo. This finding contradictsthe previous trend that positive PD-L1 expression indicates a strong responseto PD-1/PD-L1 blockade. Mechanistically, high-EDEM3 expression facilitates M2-like This finding contradictsthe previous trend that positive PD-L1 expression indicates a strong responseto PD-1/PD-L1 blockade.Mechanistically, polarizationand chemotactic migration of macrophages, which are enriched in theperipheral region of tumours compared to thecore region, precluding access of CD8+ T cells to tumourfoci. Furthermore, we EDEM3 predominantly activates the recruited M2-like macrophagesvia a glucose metabolism-dependent mechanism. Manipulationof glucose utilization by a fasting-mimicking diet(FMD) plus 2-DG treatmentsynergistically with PD-1 antibody elicits potent antitumour activity byeffectively decreasing tumour glycosylated PD-L1 expression, augmenting the CD8+effector T cell infiltration and activation while concurrently reducing the infiltration.TheCAFs-EDEM3-M2-like macrophage axis plays a critical role in promotingimmunotherapy resistance. infiltration.TheCAFs-EDEM3-M2-like macrophage axis plays a critical role in promotingimmunotherapy resistance.

CONCLUSIONS

Our study suggests that blocking EDEM3-induced M2-like macro phage trafficking by FMD plus 2-DG is a promising and effective strategy to overcomeresistance to checkpoint blockade therapy offeringhope for improved treatment outcomes.

KEY POINTS

Cancer-associated fibroblasts (CAFs) can enhance PD-L1 glycosylation through the glycosyltransferase EDEM3, contributing to immune evasion during tumour progression. EDEM3 predominantly activates the recruit M2-like macrophages via a glucose metabolism-dependent mechanism. Blocking glucose utilization antagonizes recruiting and polarizing M2-like macrophages synergistically with PD-1 antibody to improve anticancer immunity.

Tumor microenvironment and immunotherapy for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer known for its high aggressiveness and poor prognosis. Conventional treatment of TNBC is challenging due to its heterogeneity and lack of clear targets. Recent advancements in immunotherapy have shown promise in treating TNBC, with immune checkpoint therapy playing a significant role in comprehensive treatment plans. The tumor microenvironment (TME), comprising immune cells, stromal cells, and various cytokines, plays a crucial role in TNBC progression and response to immunotherapy. The high presence of tumor-infiltrating lymphocytes and immune checkpoint proteins in TNBC indicates the potential of immunotherapeutic strategies. However, the complexity of the TME, while offering therapeutic targets, requires further exploration of its multiple roles in immunotherapy. In this review, we discuss the interaction mechanism between TME and TNBC immunotherapy based on the characteristics and composition of TME, and elaborate on and analyze the effect of TME on immunotherapy, the potential of TME as an immune target, and the ability of TME as a biomarker. Understanding these dynamics will offer new insights for enhancing therapeutic approaches and investigating stratification and prognostic markers for TNBC patients.

Unraveling of Phosphotyrosine Signaling Complexes Associated with T Cell Exhaustion Using Multiplex Co-Fractionation/Mass Spectrometry

T cell exhaustion, characterized by the upregulation of inhibitory receptors and loss of effector functions, plays a crucial role in tumor immune evasion. This study utilizes a high-throughput, reproducible, and robust integrated ion-exchange chromatography-tandem mass tag (IEC-TMT) platform, coupled with a complex-centric quantification algorithm, to thoroughly profile phosphotyrosine (pTyr) protein complex changes during T cell exhaustion. The platform's high reproducibility is evidenced by >0.94 correlation and a median coefficient of variation of 0.25 among quantified complexes in HeLa cell biological replicates. This high-throughput approach allowed analysis of 312 fractions within 2 days, identifying 268 pTyr protein complexes from the T cell exhaustion model. Robust quantification of 28 complexes revealed 12 exhibiting significant abundance alterations in exhausted T cells, notably impacting lysosomal and endoplasmic reticulum-associated complexes. RTN4, a subunit of the newly identified PPI204 protein complex, is upregulated in exhausted T cells. Its knockdown reversed T cell exhaustion, enhancing antitumor immunity. These findings provide novel insights into the molecular mechanisms of T cell exhaustion and propose RTN4 as a potential therapeutic target.

Chemotherapy induces myeloid-driven spatially confined T cell exhaustion in ovarian cancer

Anti-tumor immunity is crucial for high-grade serous ovarian cancer (HGSC) prognosis, yet its adaptation upon standard chemotherapy remains poorly understood. Here, we conduct spatial and molecular characterization of 117 HGSC samples collected before and after chemotherapy. Our single-cell and spatial analyses reveal increasingly versatile immune cell states forming spatiotemporally dynamic microcommunities. We describe Myelonets, networks of interconnected myeloid cells that contribute to CD8+ T cell exhaustion post-chemotherapy and show that M1/M2 polarization at the tumor-stroma interface is associated with CD8+ T cell exhaustion and exclusion, correlating with poor chemoresponse. Single-cell and spatial transcriptomics reveal prominent myeloid-T cell interactions via NECTIN2-TIGIT induced by chemotherapy. Targeting these interactions using a functional patient-derived immuno-oncology platform demonstrates that high NECTIN2-TIGIT signaling in matched tumors predicts responses to immune checkpoint blockade. Our discovery of clinically relevant myeloid-driven spatial T cell exhaustion unlocks immunotherapeutic strategies to unleash CD8+ T cell-mediated anti-tumor immunity in HGSC.

CD8+ T cell exhaustion in the tumor microenvironment of breast cancer

CD8+ T cells are crucial cytotoxic components of the tumor immune system. In chronic inflammation, they become low-responsive, a state known as T cell exhaustion (TEX). The aim of immune checkpoint blockade is to counteract TEX, yet its dynamics in breast cancer remain poorly understood. This review defines CD8+ TEX and outlines its features and underlying mechanisms. It also discusses the primary mechanisms of CD8+ TEX in breast cancer, covering inhibitory receptors, immunosuppressive cells, cytokines, transcriptomic and epigenetic alterations, metabolic reprogramming, and exosome pathways, offering insights into potential immunotherapy strategies for breast cancer.

Elucidating Sex-Specific Immune Profiles in a Breast Cancer Model

Breast cancer is commonly thought of as a "women's disease". However, men are increasingly diagnosed with the disease, and their mortality rates are disparately higher than those of female patients. The abundance and composition of the immune microenvironment are determinants of breast cancer progression and survival. It is well documented that there are sex-specific differences in the immune response to several diseases, including various cancers. However, the effects of these differences in the context of breast cancer remain to be explored. This study demonstrates sex differences in the hormonal and immune landscape of the MMTV-PyMT transgenic murine model of female and male ER+ breast cancer using single-cell RNA sequencing (scRNA-Seq), whole-slide immunohistochemistry, and flow cytometry. Mammary tumors of transgenic male mice had increased estrogen receptor alpha expression and enriched nuclear binding signatures compared to female tumors. In the tumor immune compartment, male mice had lower intratumoral leukocyte infiltration. Yet, scRNA-Seq analysis reveals a more immunostimulatory microenvironment and increased antitumor immune populations in the primary and metastatic lungs as compared to transgenic females. Despite a more favorable innate immune profile, the metastatic burden was increased in male mice. Our data support a sex-dependent immune response in mammary carcinoma associated with the tumor, and likely host, hormonal environment. With emerging therapeutics targeting the tumor immune microenvironment, characterizing immune profiles is critical for optimizing their use in all breast cancer patients.

Unique lymphocyte transcriptomic profiles in septic patients with chronic critical illness

Introduction

Despite continued improvement in post-sepsis survival, long term morbidity and mortality remain high. Chronic critical illness (CCI), defined as persistent inflammation and organ injury requiring prolonged intensive care, is a harbinger of poor long-term outcomes in sepsis survivors. Current dogma states that sepsis survivors are immunosuppressed, particularly in CCI. Investigation of this immune suppression in heterogeneous immune populations across distinct clinical trajectories and outcomes, along with limited sampling access, is accessible via single-cell RNA sequencing (scRNA-seq).

Methods

scRNA-seq analysis was performed on healthy subjects (n=12), acutely septic patients at day 4 ± 1 (n=4), and those defined as rapid recovery (n=4) or CCI (n=5) at day 14-21. Differential gene expression and pathway analyses were performed on peripheral blood lymphocytes at both a population and annotated cell subset level. Cellular function was assessed via enzyme-linked immunosorbent spot (ELISpot), cytokine production analysis, and T-cell proliferation assays on an additional cohort of septic patients (19 healthy, 68 acutely septic, 27 rapid recovery and 20 classified as CCI 14-21 days after sepsis onset).

Results

Sepsis survivors that developed CCI exhibited proportional shifts within lymphoid cell populations, with expanded frequency of CD8+ and NK cells. Differential expression and pathway analyses revealed continued activation in T cells and NK cells, with generalized suppression of B-cell function. Both T and NK cell subsets displayed transcriptomic profiles of exhaustion and immunosuppression in CCI, particularly in CD8+ T effector memory (TEM) cells and NK cells. Functional validation of T-cell behavior in an independent cohort demonstrated T cells maintained proliferative responses in vitro yet exhibited a marked loss of cytokine production. IFN-γ production at the acute phase (day 4 ± 1) was significantly reduced in subjects later classified as CCI.

Discussion

Sepsis patients exhibit unique T-, B-, and NK-cell transcriptional patterns that are both time- and clinical trajectory-dependent. These transcriptomic and pathway differences in sepsis patients that develop CCI are associated with exhaustion in CD8+ TEM cells and NK cells. Understanding the specific immune system patterns of different cell subsets after sepsis at a molecular level will be key to the development of personalized immunotherapy and drug-targeting intervention.

Clinical trial registration

https://clinicaltrials.gov/, identifier NCT02276417.

Engineering next-generation chimeric antigen receptor-T cells: recent breakthroughs and remaining challenges in design and screening of novel chimeric antigen receptor variants

Chimeric antigen receptor (CAR) T cells are a powerful treatment against hematologic cancers. The functional phenotype of a CAR-T cell is influenced by the domains that comprise the synthetic receptor. Typically, the potency of therapeutic CAR-T cell candidates is assessed by preclinical functional assays and mouse models (i.e. human tumor xenografts). However, to date, only a few sets of domains (e.g. CD8, CD28, 41BB) have been extensively tested in preclinical assays and human clinical studies. To characterize the efficiency of a CAR, different assays have been utilized to analyze T cell phenotypes, such as expansion, cytotoxicity, secretome, and persistence. However, each of these previous studies evaluated the importance of an assay differently, resulting in a wide range of functionally diverse CARs. In this review, we highlight recent (high-throughput) methods to analyze CAR domains and demonstrate their impact on inducing T cell phenotypes and activity. We also describe advances in computational methods and their potential for identifying CAR variants with enhanced properties. Finally, we reflect on the need for a standardized scoring system to support the clinical development of next-generation CARs.

Optimizing Adoptive Cell Therapy for Solid Tumors via Epigenetic Regulation of T-cell Destiny

Adoptive cell therapy (ACT) emerged as a promising approach for cancer treatment, yet its application in solid tumors faced challenges such as inadequate tumor infiltration and cellular dysfunction. Histone acetylation is reported to play a crucial role in restoring T-cell function within tumor tissues. Building upon previous research, a novel strategy involving the co-loading of two drugs, G3C12 and vorinostat (SAHA), into PLGA microspheres to form G3C12+SAHA@PLGA is developed for intratumoral injection. The G3C12 peptide enhances adoptive T-cell recruitment to the tumor site by modulating the binding state of IFN-γ. While SAHA, a histone deacetylase inhibitor, promotes memory phenotypes of infiltrating T-cells and prevents their transition to an exhausted state. This synergistic approach effectively augmentes the efficacy of ACT in the "cold" tumor model (4T1) or the "hot" tumor model (CT26). These findings highlight the potential of combining epigenetic regulation with recruitment signaling as a means to enhance the therapeutic impact of ACT in treating solid tumors.

Revisiting the CXCL13/CXCR5 axis in the tumor microenvironment in the era of single-cell omics: Implications for immunotherapy

As one of the important members of the family of chemokines and their receptors, the CXCL13/CXCR5 axis is involved in follicle formation in normal lymphoid tissues and the establishment of somatic cavity immunity under physiological conditions, as well as being associated with a wide range of infectious, autoimmune, and tumoral diseases. Here in this review, we focus on its role in tumors. Traditional studies have found the axis to be both pro- and anti-tumorigenic, involving a variety of immune cells, including the tumor cells themselves and those in the tumor microenvironment (TME), and the prognostic significance of this axis is clinical context-dependent. With the development of techniques at the single-cell level, we were able to explain in detail the status of the CXCL13/CXCR5 axis in the TME based on real clinical samples and found that it involves a range of crucial intrinsic anti-tumor immune processes in the TME and is therefore important in tumor immunotherapy. We summarize the cellular subsets, physiological functions, and prognostic significance associated with this axis in the most promising immune checkpoint inhibitor (ICI) therapies of the day and summarize possible therapeutic ideas based on this axis. As with any TME study, the most important takeaway is that the complexity of the CXCL13/CXCR5 axis in TME suggests the importance of personalized therapy in tumor therapy.

Bulk- and single cell-RNA sequencing reveal KIF20A as a key driver of hepatocellular carcinoma progression and immune evasion

Introduction

Kinesin family member 20A (KIF20A) is essential for cell proliferation and is implicated in promoting tumor progression, but its role in hepatocellular carcinoma (HCC) remains poorly studied.

Methods

Through the analysis of bulk RNA-sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) data, the expression of KIF20A and its relationship with diagnosis, prognosis, and the immune microenvironment were examined. The association between KIF20A and the malignant progression and metastasis of HCC was confirmed through in vitro and in vivo experiments. Furthermore, patient re-staging was performed using Recursive Partitioning Analysis (RPA) to enhance clinical benefit.

Results

In this study, we firstly found KIF20A was overexprerssed in HCC both by bulk RNA-seq and scRNA-seq, and then the overexpression of KIF20A significantly promoted the proliferation, invasion, and metastasis in vitro. In vivo, the overexpression of KIF20A promoted the growth and lung metastasis of HCC. Furthermore, gene set variation analysis of bulk RNA-seq and scRNA-seq revealed that KIF20A might be associated with cell cycle related signaling pathways of E2F and G2M, and overexpression of KIF20A inhibited the activity of p21 and bax, as well as shortened G2 phase. Importantly, we found that KIF20A could induce T cell exhaustion via the SPP1-CD44 axe using scRNA-seq. Additionally, KIF20A was also correlated with the expression of immune checkpoint inhibitors (ICIs), and KIF20Ahigh subgroup might be benefited from the ICIs therapy.

Conclusion

KIF20A emerges as a pivotal driver of HCC progression, intricately regulating cell cycle pathways and modulating immune responses, which position KIF20A as a promising target for HCC management.

Dissecting the immune infiltrate of primary luminal B-like breast carcinomas in relation to age

The impact of aging on the immune landscape of luminal breast cancer (Lum-BC) is poorly characterized. Understanding the age-related dynamics of immune editing in Lum-BC is anticipated to improve the therapeutic benefit of immunotherapy in older patients. To this end, here we applied the 'multiple iterative labeling by antibody neo-deposition' (MILAN) technique, a spatially resolved single-cell multiplex immunohistochemistry method. We created tissue microarrays by sampling both the tumor center and invasive front of luminal breast tumors collected from a cohort of treatment-naïve patients enrolled in the prospective monocentric IMAGE (IMmune system and AGEing) study. Patients were subdivided into three nonoverlapping age categories (35-45 = 'young', n = 12; 55-65 = 'middle', n = 15; ≥70 = 'old', n = 26). Additionally, depending on localization and amount of cytotoxic T lymphocytes, the tumor immune types 'desert' (n = 22), 'excluded' (n = 19), and 'inflamed' (n = 12) were identified. For the MILAN technique we used 58 markers comprising phenotypic and functional markers allowing in-depth characterization of T and B lymphocytes (T&B-lym). These were compared between age groups and tumor immune types using Wilcoxon's test and Pearson's correlation. Cytometric analysis revealed a decline of the immune cell compartment with aging. T&B-lym were numerically less abundant in tumors from middle-aged and old compared to young patients, regardless of the geographical tumor zone. Likewise, desert-type tumors showed the smallest immune-cell compartment and were not represented in the group of young patients. Analysis of immune checkpoint molecules revealed a heterogeneous geographical pattern of expression, indicating higher numbers of PD-L1 and OX40-positive T&B-lym in young compared to old patients. Despite the numerical decline of immune infiltration, old patients retained higher expression levels of OX40 in T helper cells located near cancer cells, compared to middle-aged and young patients. Aging is associated with important numerical and functional changes of the immune landscape in Lum-BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

CXCL9, CXCL10, and CCL19 synergistically recruit T lymphocytes to skin in lichen planus

Lichen planus (LP) is a chronic, debilitating, inflammatory disease of the skin and mucous membranes that affects 1%-2% of Americans. Its molecular pathogenesis remains poorly understood, and there are no FDA-approved treatments. We performed single-cell RNA sequencing on paired blood and skin samples (lesional and nonlesional tissue) from 7 patients with LP. We discovered that LP keratinocytes and fibroblasts specifically secrete a combination of CXCL9, CXCL10, and CCL19 cytokines. Using an in vitro migration assay with primary human T cells, we demonstrated that CCL19 in combination with either of the other 2 cytokines synergistically enhanced recruitment of CD8+ T cells more than any individual cytokine. Moreover, exhausted T cells in lesional LP skin secreted CXCL13, which, along with CCL19, also enhanced recruitment of T cells, suggesting a feed-forward loop in LP. Finally, LP blood revealed decreased circulating naive CD8+ T cells compared with that in healthy volunteers, consistent with recruitment to skin. Molecular analysis of LP skin and blood samples increased our understanding of disease pathogenesis and identified CCL19 as a new therapeutic target for treatment.

Enhancing spatial domain detection in spatial transcriptomics with EnSDD

Advancements in spatial transcriptomics have transformed our understanding of organ function and tissue microenvironment. However, accurately identifying spatial domains to depict genome heterogeneity and cellular interactions remains a challenge. In this study, we propose EnSDD (Ensemble-learning for Spatial Domain Detection), a method that ingeniously integrates eight state-of-the-art spatial domain detection methods to automatically identify spatial domains. A key innovation of EnSDD is its dynamic weighting mechanism within the ensemble learning process, which optimizes the contribution of each base model and provides a performance evaluation metric without the need for ground truth data. By leveraging the spatial domains identified through EnSDD, we incorporate the detection of domain-specific spatially variable genes and the spatial distribution of cell types, thereby providing deeper insights into tissue heterogeneity. We validate EnSDD across diverse spatial transcriptomics datasets from various tissue organizational structures. Our results demonstrate that EnSDD significantly enhances spatial domain identification accuracy, identifies genes with spatial expression patterns, and reveals domain-specific cell type enrichment patterns, offering invaluable insights into tissue spatial heterogeneity and regionalization.

Recovering single-cell expression profiles from spatial transcriptomics with scResolve

Many popular spatial transcriptomics techniques lack single-cell resolution. Instead, these methods measure the collective gene expression for each location from a mixture of cells, potentially containing multiple cell types. Here, we developed scResolve, a method for recovering single-cell expression profiles from spatial transcriptomics measurements at multi-cellular resolution. scResolve accurately restores expression profiles of individual cells at their locations, which is unattainable with cell type deconvolution. Applications of scResolve on human breast cancer data and human lung disease data demonstrate that scResolve enables cell-type-specific differential gene expression analysis between different tissue contexts and accurate identification of rare cell populations. The spatially resolved cellular-level expression profiles obtained through scResolve facilitate more flexible and precise spatial analysis that complements raw multi-cellular level analysis.

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.

Characterization of the Breast Cancer Liver Metastasis Microenvironment via Machine Learning Analysis of the Primary Tumor Microenvironment

Breast cancer liver metastases (BCLM) are hypovascular lesions that resist intravenously administered therapies and have grim prognosis. Immunotherapeutic strategies targeting BCLM critically depend on the tumor microenvironment (TME), including tumor-associated macrophages. However, a priori characterization of the BCLM TME to optimize therapy is challenging because BCLM tissue is rarely collected. In contrast to primary breast tumors for which tissue is usually obtained and histologic analysis performed, biopsies or resections of BCLM are generally discouraged due to potential complications. This study tested the novel hypothesis that BCLM TME characteristics could be inferred from the primary tumor tissue. Matched primary and metastatic human breast cancer samples were analyzed by imaging mass cytometry, identifying 20 shared marker clusters denoting macrophages (CD68, CD163, and CD206), monocytes (CD14), immune response (CD56, CD4, and CD8a), programmed cell death protein 1, PD-L1, tumor tissue (Ki-67 and phosphorylated ERK), cell adhesion (E-cadherin), hypoxia (hypoxia-inducible factor-1α), vascularity (CD31), and extracellular matrix (alpha smooth muscle actin, collagen, and matrix metalloproteinase 9). A machine learning workflow was implemented and trained on primary tumor clusters to classify each metastatic cluster density as being either above or below median values. The proposed approach achieved robust classification of BCLM marker data from matched primary tumor samples (AUROC ≥ 0.75, 95% confidence interval ≥ 0.7, on the validation subsets). Top clusters for prediction included CD68+, E-cad+, CD8a+PD1+, CD206+, and CD163+MMP9+. We conclude that the proposed workflow using primary breast tumor marker data offers the potential to predict BCLM TME characteristics, with the longer term goal to inform personalized immunotherapeutic strategies targeting BCLM.

SIGNIFICANCE

BCLM tissue characterization to optimize immunotherapy is difficult because biopsies or resections are rarely performed. This study shows that a machine learning approach offers the potential to infer BCLM characteristics from the primary tumor tissue.