Aug 2026· Signal Transduction and Targeted Therapy· Vol 11· 0 citations· 35 references
Medicine
TL;DR
A comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes.
Abstract
Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1⁺/PD-L1⁺ Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in γδ T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific γδ TCR clonotypes and 30 unique αβ TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.
Tumor cell heterogeneity and interactions with the immune microenvironment play a key role in the progression and therapeutic efficacy of natural killer/T-cell lymphoma (NKTCL). We perform single-cell RNA sequencing analysis of 63 samples, integrating spatial transcriptomics, bulk transcriptomics, proteomics, and metabolomics to dissect inter- and intra-tumoral heterogeneity. Four meta-programs (MP) are identified, including MP1 (immune-responsive), MP2 (proliferative), MP3 (inflammatory), and MP4 (metabolic), each linked to distinct molecular and immune features. MP1 exhibits an immune-exhausted tumor microenvironment and high programmed death-ligand 1 expression, suggesting a potential response to immune checkpoint blockade. MP2 shows an immune-desert phenotype with elevated HDAC2 and MKI67 expression, indicating epigenetic regulation in tumor proliferation. MP3 is characterized by a myeloid-dominant tumor microenvironment, JAK/STAT pathway activation, and an aggressive clinical course. MP4 exhibits a distinct amino acid metabolic profile and enriched tertiary lymphoid structures. Collectively, our study provides a high-resolution molecular atlas of NKTCL heterogeneity, offering insights into patient stratification and potential avenues for future therapeutic development. Tumor cell heterogeneity and interactions with the immune microenvironment play a key role in natural killer/T-cell lymphoma (NKTCL). Here, the authors characterize 63 NKTCL samples using single-cell, spatial, and bulk multiomics; they identify four gene expression meta-programs that are associated with tumor proliferation and response to therapy.
Yi Cao, Jun Cai, Danling Dai et al.· Nature Communications· 0 citations
Background Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid proliferation, early dissemination, and limited durable benefit from current chemoimmunotherapy. Although immune checkpoint blockade has modestly improved clinical outcomes, the regulatory logic linking malignant cell states to the tumor immune microenvironment remains incompletely understood. Here, we applied an integrative single-nucleus transcriptomic framework to dissect tumor cell heterogeneity, regulatory programs, and immune-stromal communication networks in SCLC. Methods Publicly available Single-nucleus RNA sequencing data from primary and metastatic SCLC samples were analyzed using Seurat-based clustering, inferCNV-based malignant cell identification, differential expression analysis, pathway enrichment, metabolic and stemness scoring, pseudotime trajectory reconstruction, CellChat-mediated cell-cell communication inference, and transcription factor regulatory module analysis. A UBE2C-enriched proliferative tumor cell subpopulation was prioritized for functional validation. siRNA-mediated UBE2C knockdown was performed in DMS114 and NCI-H446 SCLC cell lines, followed by qRT-PCR, CCK-8, colony formation, transwell migration, and Annexin V/PI apoptosis assays. Results Using snRNA-seq, we identified multiple cell types and resolved a UBE2C+ subpopulation with marked proliferative features. UBE2C+ subpopulation displayed strong G2/M-phase enrichment, elevated mitotic and cell cycle programs. And pseudotime analysis positioned C3 UBE2C+ tumor cells at a proliferative state during tumor cell state evolution. Cell-cell communication analysis suggested that this subpopulation might interact with macrophages and fibroblasts through GRN-SORT1 and THBS1-CD47/CD36 signaling axes, indicating a potential link between proliferative tumor states and candidate communication axes. Transcription factor module analysis further revealed enrichment of cell cycle-associated regulators, including MYBL2, NFYB, E2F2, TGIF1, and RXRG, in the C3 subpopulation. Functionally, UBE2C knockdown significantly suppressed proliferation, clonogenic growth, and migration while increasing apoptosis in SCLC cells. Conclusions This study identified UBE2C+ proliferative tumor cells as a functionally relevant malignant subpopulation in SCLC and links this state to immune-stromal communication networks within the tumor microenvironment. By integrating single-nucleus transcriptomics, regulatory network inference, intercellular communication analysis, and in vitro validation, our findings nominate UBE2C as a potential candidate functional regulator and provide a systems-level framework for investigating the cancer-immunity regulome in SCLC.
Hong-Ling Jia, Yongxuan An, Bing Chen et al.· Frontiers in Immunology· 0 citations
Background/Objectives: Immune checkpoint blockade targeting the PD-1/PD-L1 axis is a standard treatment for urothelial carcinoma (UC), but 20–30% of patients develop resistance. The underlying mechanisms, particularly regarding tumor microenvironment metabolic reprogramming, remain unclear. Methods: We performed single-cell RNA sequencing on pre-treatment tumors from eight pembrolizumab-treated UC patients (three responders, five non-responders). Bioinformatic analyses included cell clustering, pathway enrichment, and cell–cell communication, validated using public datasets. Functional experiments involved SGPL1 knockdown in MB49 cells and a syngeneic PD-1-resistant murine model (MB49-R5). Results: Responders exhibited a higher proportion of infiltrating T-cells. Unexpectedly, CD4+ subsets, rather than CD8+ cells, were numerically enriched in responders. However, all T-cell subsets in responders demonstrated enhanced oxidative phosphorylation-dominant metabolic activity. Enhanced macrophage–T-cell crosstalk was observed, with macrophages exhibiting M1-like polarization driven by CD4+ T-cell-derived IFN-γ and CD40L signaling. In contrast, non-responders displayed dominant tumor-derived MIF–CD74 signaling and M2 polarization. Integration of public datasets identified SGPL1 as a key metabolic regulator associated with poor prognosis and reduced immune activation. Functional experiments demonstrated that SGPL1 knockdown inhibited tumor proliferation and restored anti-PD-1 sensitivity, accompanied by increased T-cell infiltration. Conclusions: T-cell metabolic activation drives anti-PD-1 responses in UC, and CD4+ T-cell-mediated M1 polarization and tumor-intrinsic SGPL1 crucially shape therapeutic outcomes, highlighting SGPL1 as a candidate metabolic target to overcome PD-1 resistance.
Immune checkpoint blockade elicits durable responses in a subset of patients with gastric cancer, yet the cellular programs underlying therapeutic divergence remain unclear. Using integrative single-cell transcriptomics of tumors from Immune Checkpoint Inhibitor (ICI)-treated patients, we resolved the CD8 + T-cell landscape associated with response. Therapeutic outcome reflected not only differences in state abundance but also functional reprogramming within shared states. Trajectory analysis revealed bifurcation of naïve CD8 + T cells into effector and exhaustion-prone branches that were differentially enriched between responders and non-responders. Inference of transcription factor activity revealed lineage-specific modules associated with these divergent fates. Further modeling of ligand-receptor pairs uncovered how signaling between myeloid and T cells changes during different responses. Together, these findings delineate a regulatory and intercellular framework characterizing CD8 + T-cell differentiation in gastric cancer and illuminate mechanisms of immune-state divergence during immunotherapy.
Ming-De Zang, Yi-Sa Xuan, Guanlin Li et al.· Biochemical and Biophysical...· 0 citations
These findings identify a tumor-adapted MC state that orchestrates immune evasion and tissue remodeling during CRC progression, supporting the notion that MC are reprogrammed toward an immune-suppressive and pro-tumorigenic phenotype.
E. Putro, Alessia Carnevale, Caterina Marangio et al.· Cell Death & Disease· 0 citations
Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.
Zi-Xuan Gou, Xiao-Jun Huang, Xiang-Yu Zhao· Cancer Letters· 0 citations
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