The tumor microenvironment (TME) represents a heterogeneous, complicated ecosystem characterized by intricate interactions between tumor cells and immune cells. During the past decade, immune cells especially T cells were found to play an important role in the progression of tumor and many related immune checkpoints drugs were created. In recent years, more and more scientists revealed the critical role of B-cells within the TME, particularly various populations of non-malignant B cells. Some studies indicated that non-malignant B cells may exert a 'double-edged sword' role in solid tumors. However, there has been comparatively less focus on the role of non-malignant B cells in hematologic malignancies. In this review, we characterized the development of B cells and summarized its functions of antitumor immunity within TME, with an emphasis on elucidating the roles and potential mechanisms of non-malignant B cells in the progression of hematologic diseases including classical Hodgkin's lymphoma, non-Hodgkin's B-cell lymphoma, non-Hodgkin's T-cell lymphoma, leukemia and multiple myeloma.

Pancreatic ductal adenocarcinoma (PDAC) is a "cold" solid tumor with frequent Major Histocompatibility Complex I (MHC-I) deficiency, thereby making it resistant to type-1-conventional dendritic cell (cDC1)-CD8+T cell mediated anti-tumor immunity. Current studies have demonstrated the emerging compensatory role of MHC-II-mediated antigen presentation and CD4+T cell activation in anti-tumor immunity against MHC-I-deficient tumors. However, the underlying mechanism of the compensatory immune response by CD4+T cells in cancer ablation therapy remains to be elucidate. In clinical samples and murine models, we observed that irreversible electroporation (IRE) ablation therapy promoted immune infiltration and the conversion of CD4+T cells into anti-tumor IFN-γ+Th1 cells and Th17 cells in MHC-I low-expressed PDAC using scRNA-seq and flow-cytometry analyses. Furthermore, we found that PD-L1 blockade predominantly enhanced the activation of CD11b+CD103-type-2 conventional dendritic cells (cDC2s) and their antigen presentation to CD4+T cells after ablation, stimulating the anti-tumor immune response through the tumor antigen-specific IFN-γ+Th1-NK cell axis. Elevated plasma levels of IL-6 in pancreatic cancer patients receiving ablation therapy are significant indicators for impaired prognosis. IL-6 and PD-L1 dual blockade could significantly augment the ratio of IFN-γ+Th1 in CD4+T cells to boost the anti-tumor immunity of NK cells, leading to prolonged survival of mouse bearing pancreatic cancer. Collectively, we have elucidated that PD-L1 blockade activates the cDC2-CD4+T cell axis after IRE therapy, thereby playing a pivotal compensatory anti-tumor role in MHC-I low-expressed pancreatic cancer. Moreover, a combination strategy involving dual-target blockade of PD-L1/IL-6 along with ablation therapy could emerge as a novel therapeutic approach for MHC-I deficient tumors.

The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.

The tumor microenvironment (TME) plays a crucial role in the limited efficacy of existing treatments for hepatocellular carcinoma (HCC), with tumor-associated endothelial cells (TECs) serving as fundamental TME components that substantially influence tumor progression and treatment efficacy. However, the precise roles and mechanisms of TECs in HCC remain inadequately understood.

We employed a multi-omics profiling strategy to investigate the single-cell and spatiotemporal evolution of TECs within the microenvironment of HCC tumors, showcasing varied responses to immunotherapy. Through an analysis of a clinical cohort of patients with HCC, we explored the correlation between TEC subpopulations and immunotherapy outcomes. The influence of TEC subsets on the immune microenvironment was confirmed through comprehensive in vitro and in vivo studies. To further explore the mechanisms of distinct TEC subpopulations in microenvironmental modulation and their impact on immunotherapy, we utilized TEC subset-specific knockout mouse models as well as humanized mouse models.

In this study, we identified a new subset of CXCL12+ TECs that exert a crucial role in immune suppression within the HCC TME. Functionally, CXCL12+ TECs impede the differentiation of CD8+ naïve T cells into CD8+ cytotoxic T cells by secreting CXCL12. Furthermore, they attract myeloid-derived suppressor cells (MDSCs). A bispecific antibody was developed to target both CXCL12 and PD1 specifically, showing significant promise in bolstering anti-tumor immune responses and advancing HCC therapy.

CXCL12+ TECs are pivotal in mediating immunosuppression within the HCC microenvironment and targeting CXCL12+ TECs presents a promising approach to augment the efficacy of immunotherapies in patients with HCC.

This investigation reveals a pivotal mechanism wherein CXCL12+ tumor-associated endothelial cells (TECs) emerge as crucial modulators of immune suppression in the tumor microenvironment of hepatocellular carcinoma (HCC). The discovery of CXCL12+ TECs as inhibitors of CD8+ naïve T cell activation and recruiters of myeloid-derived suppressor cells significantly advances our grasp of the dynamic between HCC and immune regulation. Moreover, the development and application of a bispecific antibody precisely targeting CXCL12 and PD1 has proven to enhance immune responses in a humanized mouse HCC model. This finding underscores a promising therapeutic direction for HCC, offering the potential to amplify the impact of current immunotherapies.

Colorectal cancer (CRC) is the world's third most frequent cancer, and both its incidence and fatality rates are rising. Despite various therapeutic approaches, neither its mortality rate nor its recurrence frequency has decreased significantly. Additionally, conventional treatment approaches, such as chemotherapy and radiotherapy, have several side effects and risks for patients with CRC. Accordingly, the need for alternative and effective treatments for CRC patients is critical. Immunotherapy that utilizes dendritic cells (DCs) harnesses the patient's immune system to combat cancer cells effectively. DCs are the most potent antigen-presenting cells (APCs), which play a vital role in generating anti-cancer T cell responses. A significant barrier to the immune system's ability to eliminate CRC is the establishment of a potent immunosuppressive tumor milieu by malignant cells. Since DCs are frequently defective in this milieu, the tumor setting significantly reduces the effectiveness of DC-based therapy. Determining central mechanisms contributing to tumor growth by unraveling and comprehending the interaction between CRC tumor milieu and DCs may lead to new therapeutic approaches. This study aims to review DC biology and discuss its role in T-cell-mediated anti-tumor immunity, as well as to highlight the immunosuppressive effects of the CRC tumor milieu on the function of DCs. We will also highlight the tumor microenvironment (TME)-related factors that interfere with DC function as a possible therapeutic target to enhance DC-based cell therapy efficacy.

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment but remains effective in only a subset of patients. Emerging evidence suggests that the gut microbiome and its metabolites critically influence ICB efficacy. In this study, we performed a multi-omics analysis of fecal microbiomes and metabolomes from 165 patients undergoing anti-programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) therapy, identifying microbial and metabolic entities associated with treatment response. Integration of data from four public metagenomic datasets (n = 568) uncovered cross-cohort microbial and metabolic signatures, validated in an independent cohort (n = 138). An integrated predictive model incorporating these features demonstrated robust performance. Notably, we characterized five response-associated enterotypes, each linked to specific bacterial taxa and metabolites. Among these, the metabolite phenylacetylglutamine (PAGln) was negatively correlated with response and shown to attenuate anti-PD-1 efficacy in vivo. This study sheds light on the interplay among the gut microbiome, the gut metabolome, and immunotherapy response, identifying potential biomarkers to improve treatment outcomes.

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.

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.

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.

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

Colorectal cancer (CRC) is one of the most common malignancies. Hypoxia can promote the occurrence and development of CRC. However, how hypoxia regulates the CRC immune microenvironment needs to be further explored. The bulk RNA sequencing data and clinicopathological information of CRC patients were enrolled from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The single-cell RNA sequencing (scRNA-seq) datasets of CRC were collected from and analyzed from the GEO database and the ArrayExpress database. The score of the hypoxia gene set was estimated using the "ssGSEA" algorithm in the "GSVA" R package. The functional characteristics of CAF subtypes were studied by bioinformatics analysis and in vitro experiments, and a prognostic model was constructed based on machine learning correlation. Hypoxia is associated with poor prognosis in CRC patients. Periostin (POSTN) + Fib is a cancer-associated fibroblast (CAF) closely associated with hypoxia, and high infiltration of POSTN + Fib is associated with adverse outcomes in overall survival (OS) and relapse-free survival (RFS) in CRC patients. Hypoxia can induce POSTN expression and secretion in CAFs. Hypoxia-induced increase of POSTN expression in CAFs can significantly promote the migration and proliferation of CRC cells. Hypoxia-induced increase of POSTN expression in CAFs can significantly promote the proliferation and migration of CRC cells. The POSTN+Fib Hypoxia-Related Risk Model (PFHRM) can predict the survival and immunotherapy response of CRC patients. Our study identified a POSTN+Fib cell subpopulation closely associated with hypoxia, which promotes the malignant progression of CRC. The development of PFHRM provides a theoretical basis for improving patient survival and prognosis.

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.

While highlighting the complexity and heterogeneity of tumor immune microenvironments, the application of single-cell analyses in human cancers has identified recurrent subsets of tumor-associated macrophages (TAMs). Among these, interleukin (IL)-1β+ TAMs - cells with high levels of expression of inflammatory response and tissue repair genes, but with limited capacity to stimulate cytotoxic immunity - are emerging as key drivers of pathogenic inflammation in cancer. In this review we discuss recent literature defining the phenotypical, molecular, and functional properties of IL-1β+ TAMs, as well as their temporal dynamics and spatial organization. Elucidating the biology of these cells across tumor initiation, progression, metastasis, and therapy could inform the design and interpretation of clinical trials targeting IL-1β and/or other inflammatory factors in cancer immunotherapy.

Batch effect correction (BEC) is fundamental to integrate multiple single-cell RNA sequencing datasets, and its success is critical to empower in-depth interrogation for biological insights. However, no simple metric is available to evaluate BEC performance with sensitivity to data overcorrection, which erases true biological variations and leads to false biological discoveries. Here, we propose RBET, a reference-informed statistical framework for evaluating the success of BEC. Using extensive simulations and six real data examples including scRNA-seq and scATAC-seq datasets with different numbers of batches, batch effect sizes and numbers of cell types, we demonstrate that RBET evaluates the performance of BEC methods more fairly with biologically meaningful insights from data, while other methods may lead to false results. Moreover, RBET is computationally efficient, sensitive to overcorrection and robust to large batch effect sizes. Thus, RBET provides a robust guideline on selecting case-specific BEC method, and the concept of RBET is extendable to other modalities.

A sustained blood supply is critical for tumor growth, as it delivers the nutrients and oxygen required for development. Targeting of blood vessel formation via immunotherapies is an area of great importance. Knowing that certain embryonic genes, such as carcinoembryonic antigens (CEA) and oncofetal fibronectin, become reexpressed in malignant transformation, we hypothesized that a similar phenomenon holds true for tumor endothelial cells (TECs) as well. An approach for identification of highly selective tumor endothelial markers was conducted to develop targeted antiangiogenic immunotherapies. We first queried the transcriptome that is present during embryo development. We then performed a systematic search for genes selectively expressed in the mouse embryo at days E11 and E18, as compared to the transcriptome of the adult mouse. Subsequently, we queried for expression of these embryonic genes in sorted murine TECs. This approach identified among others the tumor endothelial antigens fibrillin-2 (Fbn2), elastin microfibril interface-located protein 2 (Emilin2) as well as the tumor endothelial antigens lysyl oxidase (Lox) and serine/cysteine protease inhibitor, clade E, member 1 (Serpine1; Pai-1). For these selected genes, functional involvement in angiogenesis was confirmed in in vitro bioassays. We subsequently used iBoost conjugate vaccine technology to develop vaccines against the selected targets. For all four targets, vaccination readily induced target-specific antibody responses in mice, resulting in inhibition of tumor growth. Access to highly specific tumor endothelial markers provides opportunities for direct targeting of the tumor vasculature with high specificity, without affecting healthy vasculature.

Gastric cancer (GC) is one of the most common malignancies and is a highly heterogeneous disease; it is also a leading cause of cancer-related death. Owing to the complexity and late-stage diagnosis of GC, the prognosis remains poor. To explore potential biomarkers for GC, GC patient transcriptome data were subjected to a comprehensive approach involving machine learning, binary nomogram prediction model construction, the topological algorithm of CytoHubba, and Kaplan-Meier and Mendelian randomization (MR) analyses. First, gene expression data for normal and GC tissues were assessed via machine learning and the topological algorithm of CytoHubba, and a total of 792 differentially expressed genes (DEGs) and nine core genes were identified. Kaplan-Meier analysis and analysis of a nomogram binary prediction model for the core genes revealed that the expression level of BRCA1 was closely and significantly correlated with the survival time of GC patients, suggesting that BRCA1 may be considered a valuable biomarker for GC diagnosis. Furthermore, MR analysis revealed that BRCA1 promotes the transformation of normal cells into GC cells by regulating NADPH levels, leading to a continuous increase in oxidative stress. This is one of the initial comprehensive analysis involving MR and multidimensional approaches; it revealed the significant role of BRCA1 in GC, providing new ideas on drugs and targets for GC clinical treatment.

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.

Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract, with increasing incidence and mortality rates, posing a significant burden on human health. Its progression relies on various mechanisms, among which the tumor microenvironment and tumor-associated macrophages (TAMs) have garnered increasing attention. Macrophage infiltration in various solid tumors is associated with poor prognosis and is linked to chemotherapy resistance in many cancers. These significant biological behaviors depend on the heterogeneity of macrophages. Tumor-promoting TAMs comprise subpopulations characterized by distinct markers and unique transcriptional profiles, rendering them potential targets for anticancer therapies through either depletion or reprogramming from a pro-tumoral to an anti-tumoral state. Single-cell RNA sequencing technology has significantly enhanced our research resolution, breaking the traditional simplistic definitions of macrophage subtypes and deepening our understanding of the diversity within TAMs. However, a unified elucidation of the nomenclature and molecular characteristics associated with this diversity remains lacking. In this review, we assess the application of conventional macrophage polarization subtypes in colorectal malignancies and explore several unique subtypes defined from a single-cell omics perspective in recent years, categorizing them based on their potential functions.

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.

Understanding the intricate tumor microenvironment (TME) is crucial for elucidating the mechanisms underlying the progression of cervical squamous cell carcinoma (CSCC) and its response to anti-PD-1 therapy.

In this study, we characterized 50,649 cells obtained from the CSCC for single-cell RNA sequencing and integrated bulk sequencing data from The Cancer Genome Atlas (TCGA) and clinical samples to explore their cell composition, metabolic processes, signaling pathways, specific transcription factors, lineage tracking and response to immunotherapy. In vivo experiments were performed to validate the function of key cell subsets.

We identified ten major cell type and 35 subsets of stromal and immune cells in TME and observed distinct patterns in the metabolic processes and signaling pathways of these cells between tumor and normal tissues. Furthermore, PCNA clamp-associated factor (PCLAF)+ tumor-associated epithelial cell (TAEpis) was negatively correlated with the number of C-X-C motif chemokine ligand 13 (CXCL13)+ CD8+ T cells, overall survival, and response to anti-programmed cell death-1(PD-1) therapy in patients with CSCC. Both in vivo and in vitro experiments demonstrated that PCLAF+ TAEpis promotes the apoptosis of CD8+ T and tumor growth, while also inhibiting T cell infiltration and function.

Our findings illuminate the heterogeneity of the complex TME in CSCC and offer evidence supporting PCLAF+ TAEpis as a promising therapeutic target.

Indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors are promising for treating tumors but have limited efficacy due to the immunosuppressive tumor microenvironment. In this study, we develop an orchestrated nanoparticle system using modular peptide assemblies, where the co-assembled sequences are designed for the specific binding to the hydrophobic and hydrophilic domains, guiding the assembly process and enabling the customization of nanoparticle properties. We exploit the modularity of this platform to integrate a hydrophobic ferroptosis precursor, an IDO1 inhibitor, and a hydrophilic peptidic PD-L1 antagonist for optimizing therapeutic outcomes through ferroptosis-enhanced tumor immunotherapy. The resulting nanoparticles induce immunogenic ferroptosis, enhance the intratumoral function of T lymphocytes, suppress regulatory T cells, and effectively modulate the immunosuppressive tumor microenvironment, thereby facilitating regression of tumor growth. This work provides a modular peptide-based nanoparticle engineering strategy and holds significant potential for advancing cancer treatment.

Prior studies have demonstrated the association between immune cells and colorectal cancer (CRC). However, the causal link to specific immunophenotypes is limited. This study intends to elucidate the causal relationship of immune cell signatures on CRC.

We performed a bi-directional and two-sample mendelian randomization (MR) study, utilizing GWAS summary data of 731 immune cell traits (n = 3,757) and CRC statistics (n = 470,002). The primary MR methodology was inverse-variance weighted (IVW) method. Furthermore, heterogeneity was evaluated by Cochran's Q test. MR-PRESSO and MR-Egger were employed to assess horizontal and vertical pleiotropy respectively. Sensitivity analysis and FDR correction were conducted in our results. These results were validated in both the UK Biobank and FinnGen cohorts. We also extracted transcriptomic data of CRC and adjacent non-tumor tissues from TCGA, and used CIBERSORT to compare the infiltration patterns of 22 immune cell panels between normal tissues and the tumor microenvironment (TME).

Our study indicated nine immune cell signatures had significant causality with the risk of CRC after sensitivity analysis and FDR correction. The positive results covered four panels: B cell, CD8 + T cell, Treg, and monocyte. IgD- CD38br and IgD + CD38br B cell, CD8dim and CD28 + CD45RA- CD8dim T cell, and CD14 on CD14 + CD16- monocyte were the protective factors of CRC. However, CD39 + resting Treg, CX3CR1 on CD14- CD16 + monocyte, FSC-A on HLA DR + T cell, and BAFF-R on B cell increased the risk of CRC. The results were validated in the UK Biobank data and FinnGen cohorts. The data from the TCGA database also confirmed the infiltration of B cell, CD8 + T cell, Treg, and monocyte panels in the TME.

This study highlights the causal link between specific immune cell phenotypes and CRC, providing valuable insights into the immune microenvironment's role in CRC. The validation of our findings using large-scale datasets (UK Biobank, FinnGen) and TCGA underscores the robustness of our results, offering new potential therapeutic targets for CRC treatment.

The gene-regulatory dynamics governing drug responses in cancer are yet to be fully understood. Here, we report a pipeline capable of producing high-throughput pharmacotranscriptomic profiling through live-cell barcoding using antibody-oligonucleotide conjugates. This pipeline combines drug screening with 96-plex single-cell RNA sequencing. We show the potential of this approach by exploring the heterogeneous transcriptional landscape of primary high-grade serous ovarian cancer (HGSOC) cells after treatment with 45 drugs, with 13 distinct classes of mechanisms of action. A subset of phosphatidylinositol 3-OH kinase (PI3K), protein kinase B (AKT) and mammalian target of rapamycin (mTOR) inhibitors induced the activation of receptor tyrosine kinases, such as the epithelial growth factor receptor (EGFR), and this was mediated by the upregulation of caveolin 1 (CAV1). This drug resistance feedback loop could be mitigated by the synergistic action of agents targeting PI3K-AKT-mTOR and EGFR for HGSOC with CAV1 and EGFR expression. Using this workflow could enable the personalized testing of patient-derived tumor samples at single-cell resolution.

Tumour-associated microbiota are integral components of the tumour microenvironment (TME). However, previous studies on intratumoral microbiota primarily rely on bulk tissue analysis, which may obscure their spatial distribution and localized effects. In this study, we applied in situ spatial-profiling technology to investigate the spatial distribution of intratumoral microbiota in breast cancer and their interactions with the local TME. Using 5R 16S rRNA gene sequencing and RNAscope FISH/CISH on patients' tissue, we identified significant spatial heterogeneity in intratumoral microbiota, with Fusobacterium nucleatum (F. nucleatum) predominantly localized in tumour cell-rich areas. GeoMx digital spatial profiling (DSP) revealed that regions colonized by F. nucleatum exhibit significant influence on the expression of RNAs and proteins involved in proliferation, migration and invasion. In vitro studies indicated that co-culture with F. nucleatum significantly stimulates the proliferation and migration of breast cancer cells. Integrative spatial multi-omics and co-culture transcriptomic analyses highlighted the MAPK signalling pathways as key altered pathways. By intersecting these datasets, VEGFD and PAK1 emerged as critical upregulated proteins in F. nucleatum-positive regions, showing strong positive correlations with MAPK pathway proteins. Moreover, the upregulation of VEGFD and PAK1 by F. nucleatum was confirmed in co-culture experiments, and their knockdown significantly reduced F. nucleatum-induced proliferation and migration. In conclusion, intratumoral microbiota in breast cancer exhibit significant spatial heterogeneity, with F. nucleatum colonization markedly altering tumour cell protein expression to promote progression and migration. These findings provide novel perspectives on the role of microbiota in breast cancer, identify potential therapeutic targets, and lay the foundation for future cancer treatments. KEY POINTS: Intratumoral Fusobacterium nucleatum exhibits significant spatial heterogeneity within breast cancer tissues. F. nucleatum colonization alters the expression of key proteins involved in tumour progression and migration. The MAPK signalling pathway is a critical mediator of F. nucleatum-induced breast cancer cell proliferation and migration. VEGFD and PAK1 are potential therapeutic targets to mitigate F. nucleatum-induced tumour progression.

With the growth of clinical cancer single-cell RNA sequencing studies, robust differential expression methods for case/control analyses (e.g., treatment responders vs. non-responders) using gene signatures are pivotal to nominate hypotheses for further investigation. However, many commonly used methods produce a large number of false positives, do not adequately represent the patient-specific hierarchical structure of clinical single-cell RNA sequencing data, or account for sample-driven confounders. Here, we present a nonparametric statistical method, BEANIE, for differential expression of gene signatures between clinically relevant groups that addresses these issues. We demonstrate its use in simulated and real-world clinical datasets in breast cancer, lung cancer and melanoma. BEANIE outperforms existing methods in specificity while maintaining sensitivity, as demonstrated in simulations. Overall, BEANIE provides a methodological strategy to inform biological insights into unique and shared differentially expressed gene signatures across different tumor states, with utility in single-study, meta-analysis, and cross-validation across cell types.

A major characteristic of ovarian cancer (OC) is its unique route of metastasis via ascites. The immune microenvironment in ascites remains understudied, leaving the mechanism of ascites-mediated abdominal metastasis obscure. Here, a single-cell transcriptomic landscape of CD45+ immune cells across multiple anatomical sites is depicted, including primary tumors, metastatic lesions, and ascites, from patients diagnosed with high-grade serous ovarian carcinoma (HGSOC). A novel subset of perilipin 2 high (PLIN2hi) macrophages are identified that are enriched in ascites and positively correlated with OC progression, hence being designated as "ascites-associated macrophages (AAMs)". AAMs are lipid-loaded with overexpression of the lipid droplet protein PLIN2. Overexpression or suppression of PLIN2 can enhance or inhibit tumor cell migration, invasion, and vascular permeability in vitro, which is also confirmed in vivo. Mechanistically, it is demonstrated that PLIN2 boosts HIF1α/SPP1 signaling in macrophages, thereby exerting pro-tumor functions. Finally, a PLIN2-targeting liposome is designed to efficiently suppress ascites production and tumor metastasis. Taken together, this work provides a comprehensive characterization of the cancer-promoting function and lipid-rich property of ascites-enriched PLIN2hi macrophages, establishes a link between lipid metabolism and hypoxia within the context of the ascites microenvironment, and elucidates the pivotal role of ascites in trans-coelomic metastasis of OC.

We aimed to analyze the sensitivity of patients to chemotherapy drugs and actively explore potential new intervention targets, providing an essential reference for personalized treatment.

Candidate markers with significant differential expression in macrophages were identified by analyzing gene expression at the single-cell level. A weighted gene co-expression network (WGCN) was constructed on the GSE26712 dataset to explore the modules most relevant to macrophages. Differentially expressed genes for specific markers were identified. A multi-factor regulatory network was constructed based on single-cell dataset markers screening, differentially expressed genes, and genes commonly present in WGCNA modules. Different macrophage subtypes were identified using this network. Machine learning was used to filter and predict the markers' drug sensitivity, and the potential therapeutic compounds for specific markers were screened.

We identified 14 and 17 of M1 and M2 macrophage candidate markers, respectively. In the multi-factor regulatory network of M1 macrophages, 6 out of 14 markers recognized 159 transcription factors (TFs) and 48 micro RNAs (miRNAs), whereas 13 of 17 markers recognized 191 TFs and 182 miRNAs in the multi-factor regulatory network of M2 macrophages. Filtering of the identified differentially expressed genes using random forests yielded 15 M1 and M2 macrophage-specific markers. Drug sensitivity prediction analysis and in vitro experiments revealed the close association of these markers with common chemotherapy drug sensitivity.

We identified specific M1 and M2 macrophage markers and found potential therapeutic compounds (dasatinib and afatinib) in these specific markers. These potential therapeutic compounds provide insight into the underlying mechanisms of serous ovarian cancer (OC) and inspire more effective treatment methods.

This article reviews the impact of single-cell sequencing (SCS) on cancer biology research. SCS has revolutionized our understanding of cancer and tumor heterogeneity, clonal evolution, and the complex interplay between cancer cells and tumor microenvironment. SCS provides high-resolution profiling of individual cells in genomic, transcriptomic, and epigenomic landscapes, facilitating the detection of rare mutations, the characterization of cellular diversity, and the integration of molecular data with phenotypic traits. The integration of SCS with multi-omics has provided a multidimensional view of cellular states and regulatory mechanisms in cancer, uncovering novel regulatory mechanisms and therapeutic targets. Advances in computational tools, artificial intelligence (AI), and machine learning have been crucial in interpreting the vast amounts of data generated, leading to the identification of new biomarkers and the development of predictive models for patient stratification. Furthermore, there have been emerging technologies such as spatial transcriptomics and in situ sequencing, which promise to further enhance our understanding of tumor microenvironment organization and cellular interactions. As SCS and its related technologies continue to advance, they are expected to drive significant advances in personalized cancer diagnostics, prognosis, and therapy, ultimately improving patient outcomes in the era of precision oncology.

Recent oncological research has intensely focused on the tumor immune microenvironment (TME), particularly the functions of CD4 + T lymphocytes. CD4+ T lymphocytes have been implicated in antigen presentation, cytokine release, and cytotoxicity, suggesting their contribution to the dynamics of the TME. Furthermore, the application of single-cell sequencing has yielded profound insights into the phenotypic diversity and functional specificity of CD4+ T cells in the TME. In this review, we discuss the current findings from single-cell analyses, emphasizing the heterogeneity of CD4+ T cell subsets and their implications in tumor immunology. In addition, we review the critical signaling pathways and molecular networks underpinning CD4+ T cell activities, thereby offering novel perspectives on therapeutic targets and strategies for cancer treatment and prognosis.

A gene regulatory network (GRN) intricately encodes the interconnectedness of identities and functionalities of genes within cells, ultimately shaping cellular specificity. Despite decades of endeavors, reverse engineering of GRNs from gene expression profiling data remains a profound challenge, particularly when it comes to reconstructing cell-specific GRNs that are tailored to precise cellular and genetic contexts. Here, we propose a discrete diffusion generation model, called DigNet, capable of generating corresponding GRNs from high-throughput single-cell RNA sequencing (scRNA-seq) data. DigNet embeds the network generation process into a multistep recovery procedure with Markov properties. Each intermediate step has a specific model to recover a portion of the gene regulatory architectures. It thus can ensure compatibility between global network structures and regulatory modules through the unique multistep diffusion procedure. Furthermore, through iMetacell integration and non-Euclidean discrete space modeling, DigNet is robust to the presence of noise in scRNA-seq data and the sparsity of GRNs. Benchmark evaluation results against more than a dozen state-of-the-art network inference methods demonstrate that DigNet achieves superior performance across various single-cell GRN reconstruction experiments. Furthermore, DigNet provides unique insights into the immune response in breast cancer, derived from differential gene regulation identified in T cells. As an open-source software, DigNet offers a powerful and effective tool for generating cell-specific GRNs from scRNA-seq data.

The influence of tertiary lymphoid structures (TLSs) on disease progression and the response to immunotherapy in head and neck squamous cell carcinoma (HNSCC) is well established, yet the heterogeneity among these structures remains largely unexplored. We utilized digital spatial profiling technology to perform in situ transcriptomic sequencing of TLSs across varying levels of maturation and distinct tumor regions within HNSCC. We assessed the prognostic significance of TLS maturation and spatial distribution in 260 patients with HNSCC through hematoxylin and eosin staining and multiplex immunohistochemistry. Furthermore, we established a TLS scoring system to predict survival in patients with HNSCC. Our study revealed that mature TLSs in the intratumor region (Intra-TLSs) of HNSCC, enriched with memory B cells, plasma cells, and CD4+ T cells, presented increased B-cell activity gene expression. Conversely, early TLSs (E-TLSs), abundant in endothelial cells, fibroblasts, and regulatory T cells, express epithelial‒mesenchymal transition (EMT)-related genes, potentially fostering tumor growth. Compared with mature TLSs within the peritumoral region (Peri-TLSs), mature Intra-TLSs have greater memory B-cell and macrophage densities and upregulate genes involved in B-cell receptor signaling and immune effector processes. Mature Peri-TLSs, characterized by endothelial cell enrichment and EMT receptor interaction genes, may contribute to tumor progression and immune evasion. Patients with mature Intra-TLSs or invasive margin TLSs (Invas-TLSs) have improved 5-year survival, whereas those with mature Peri-TLSs have poorer prognoses. By integrating TLS maturity and distribution in HNSCC, we developed a TLS scoring system to guide personalized treatments, which is crucial for predicting outcomes.

B cells have long been understood to be drivers of both humoral and cellular immunity. Recent advances underscore this importance but also indicate that in infection, inflammatory disease and cancer, B cells function directly at sites of inflammation and form tissue-resident memory populations. The spatial organization and cellular niches of tissue B cells have profound effects on their function and on disease outcome, as well as on patient response to therapy. Here we review the role of B cells in peripheral tissues in homeostasis and disease, and discuss the newly identified cellular and molecular signals that are involved in regulating their activity. We integrate emerging data from multi-omic human studies with experimental models to propose a framework for B cell function in tissue inflammation and homeostasis.

Tumor heterogeneity plays a pivotal role in tumor progression and resistance to clinical treatment. Single-cell RNA sequencing (scRNA-seq) enables us to explore heterogeneity within a cell population and identify rare cell types, thereby improving our design of targeted therapeutic strategies. Here, we use a pan-cancer and pan-tissue single-cell transcriptional landscape to reveal heterogeneous expression patterns within malignant cells, precancerous cells, as well as cancer-associated stromal and endothelial cells. We introduce a deep learning framework named Shennong for in silico screening of anticancer drugs for targeting each of the landscape cell clusters. Utilizing Shennong, we could predict individual cell responses to pharmacologic compounds, evaluate drug candidates' tissue damaging effects, and investigate their corresponding action mechanisms. Prioritized compounds in Shennong's prediction results include FDA-approved drugs currently undergoing clinical trials for new indications, as well as drug candidates reporting anti-tumor activity. Furthermore, the tissue damaging effect prediction aligns with documented injuries and terminated discovery events. This robust and explainable framework has the potential to accelerate the drug discovery process and enhance the accuracy and efficiency of drug screening.

Stereotactic ablative radiotherapy (SABR) is thought to activate T cell responses in patients with cancer, leading to its combination with immunotherapy and chemotherapy for treatment of non-small-cell lung cancer (NSCLC). Here, we aimed to provide a high-resolution transcriptomic profiling of the systemic T cell response following SABR, with or without preceding immunotherapy/chemotherapy.

We conducted single-cell RNA and T cell receptor (TCR) sequencing of T cells from peripheral blood of seven patients with early-stage NSCLC taken pre- and post-SABR without or with prior immunotherapy and chemotherapy (icSABR). Other flow cytometry, single-cell RNA-seq data and bulk RNA-seq data were used to validate the results.

We uncovered distinct T cell response patterns induced by these treatments: while terminal effector CD8+ T cells showed increased cytotoxic and inhibitory scores, and upregulated immune-activated pathways post-SABR, the reverse responses occurred post-icSABR. Furthermore, the proportion of large T cell clones increased and single clone decreased post-SABR, while the opposite was seen post-icSABR. Of note, both SABR and icSABR largely changed TCR clonotypes, which were mainly large clones post-SABR but single clone post-icSABR, and predominantly from terminal effector CD8+ T cells and T helper cells, respectively.

These findings reveal a complex interplay between SABR and immunotherapy, with potentially valuable implications for treatment strategies involving SABR and immunotherapy to induce systemic T cell responses for tumor eradication in patients with NSCLC.

Neoadjuvant chemotherapy is the foundation treatment for triple-negative breast cancer (TNBC) and frequently results in pathological complete response (pCR). However, there are large differences in clinical response and survival after neoadjuvant chemotherapy of TNBC patients. The aim was to identify genes whose expression significantly associates with the efficacy of neoadjuvant chemotherapy in patients with TNBC. Transcriptomes of 46 formalin-fixed paraffin-embedded (FFPE) tumor samples from TNBC patients were analyzed by RNA-seq by comparing 26 TNBCs with pCR versus 20 TNBCs with pathological partial remission (pPR). Subsequently, we narrowed down the list of genes to those that strongly correlated with drug sensitivity of 63 breast cancer cell lines based on Dependency Map Consortium data re-analysis. Furthermore, the list of genes was limited to those presenting specific expression in breast tumor cells as revealed in three large published single-cell RNA-seq breast cancer datasets. Finally, we analyzed which of the selected genes were significantly associated with overall survival (OS) in TNBC TCGA dataset. A total of 105 genes were significantly differentially expressed in comparison between pPR versus pCR. As revealed by PLSR analysis in breast cancer cell lines, out of 105 deregulated genes, 42 were associated with sensitivity to docetaxel, doxorubicin, paclitaxel, and/or cyclophosphamide. We found that 24 out of 42 sensitivity-associated genes displayed intermediate or strong expression in breast malignant cells using single-cell RNAseq re-analysis. Finally, 10 out of 24 genes were significantly associated with overall survival in TNBC TCGA dataset. Our RNA-seq-based findings suggest that there might be transcriptomic signature consisted of 24 genes specifically expressed in tumor malignant cells for predicting neoadjuvant response in FFPE samples from TNBC patients prior to treatment initiation. Additionally, nine out of 24 genes were potential survival predictors in TNBC. This group of 24 genes should be further investigated for its potential to be translated into a predictive test(s).

Maturation of conventional dendritic cells (cDCs) is crucial for maintaining tolerogenic safeguards against auto-immunity and for promoting immunogenic responses to pathogens and cancer. The subcellular mechanism for cDC maturation remains poorly defined. We show that cDCs mature by leveraging an internal reservoir of cholesterol (harnessed from extracellular cell debris and generated by de novo synthesis) to assemble lipid nanodomains on cell surfaces of maturing cDCs, enhance expression of maturation markers and stabilize immune receptor signaling. This process is dependent on cholesterol transport through Niemann-Pick disease type C1 (NPC1) and mediates homeostatic and Toll-like receptor (TLR)-induced maturation. Importantly, we identified the receptor tyrosine kinase AXL as a regulator of the NPC1-dependent construction of lipid nanodomains. Deleting AXL from cDCs enhances their maturation, thus improving anti-tumor immunity. Altogether, our study presents new insights into cholesterol mobilization as a fundamental basis for cDC maturation and highlights AXL as a therapeutic target for modulating cDCs.