bims-spamet Biomed News
on Spatial metabolomics of T cells
Issue of 2026–08–30
nine papers selected by
Peio Azcoaga, Katholieke Universiteit te Leuven
  1. Post-translational modifications in CD8+ T cell exhaustion: mechanisms, networks, and epigenetic locking.
  2. Multiscale modeling of T cell exhaustion: A mathematical framework integrating continuous dynamics with spatial heterogeneity.
  3. Spatial Immune Coding in Tumor-Draining Lymph Nodes: Functional Compartmentalization of Immune Activation and Immunosuppression.
  4. RNF180 loss stabilizes BCAS4 to enhance PD-L1 expression and immune evasion in hepatocellular carcinoma.
  5. A predictive model for immunotherapy efficacy in cancer based on dynamic changes of CD8+ T cells: a pan-cancer retrospective study.
  6. A spatially resolved implantable microdevice for multiplexed in situ screening of engineered cellular therapies in solid tumors.
  7. The heterogeneous and dynamic immune-tumor interface in breast cancer.
  8. Reprogramming the immunosuppressive microenvironment in glioblastoma: the microglia-MDSC-Treg axis and translational therapeutic strategies.
  9. Metabolic heterogeneity and functional diversity of cancer-associated fibroblasts in gastric cancer (Review).
  1. Front Immunol. 2026 ;17 1913598
    Post-translational modifications in CD8+ T cell exhaustion: mechanisms, networks, and epigenetic locking.
    Ting Yu, Mengjuan Xia, Yuxia Wu, Qiongshi Wu, Jing Xie, Haocheng Gao, Shengfeng Hu.
      CD8+ T cells are core effector cells of adaptive immunity. However, in chronic infection and tumor microenvironments, they often lose their effector functions. Under persistent antigenic and metabolic stress, CD8+ T cells may progressively acquire a stable dysfunctional state termed T cell exhaustion. Post-translational modifications (PTMs) constitute a rapid and dynamic regulatory system that targets four core functional modules: membrane receptor signaling, transcription factors, metabolic enzymes, and epigenetic regulators. These modules are interconnected through a multi-layered PTM network. Within this network, PTMs orchestrate a stepwise cascade that proceeds from signal initiation through metabolic reprogramming to transcriptional and epigenetic remodeling. Ultimately, this cascade consolidates the exhaustion program via stable epigenetic memory. Accordingly, we propose a "PTM-driven signal-metabolism-epigenetic locking model" as the central framework of this review. Focusing on five key PTMs, namely phosphorylation, ubiquitination, glycosylation, acetylation, and lactylation, we elucidate how these modifications cooperatively regulate CD8+ T cell exhaustion. Critically, the PTM network drives progressive locking of the exhausted state through three epigenetic layers: DNA methylation, chromatin remodeling, and histone modifications. These layers collectively contribute to the progressive stabilization of the exhausted state over time. This framework integrates transient environmental signals, metabolic fluctuations, and transcriptional changes into permanent cell fate decisions. Building upon this mechanistic understanding, the review further explores novel strategies targeting the PTM network to reverse exhaustion and enhance immunotherapeutic efficacy. This review provides a clear and comprehensive framework for understanding how PTMs govern CD8+ T cell exhaustion and lays a solid foundation for the development of next-generation immunotherapies.
    Keywords:  CD8+ T cells; cancer immunotherapy; epigenetic locking; post-translational modifications; t cell exhaustion
    DOI:  https://doi.org/10.3389/fimmu.2026.1913598
  2. PLoS Comput Biol. 2026 Aug 26. 22(8): e1014690
    Multiscale modeling of T cell exhaustion: A mathematical framework integrating continuous dynamics with spatial heterogeneity.
    Chenghang Li, Yuhong Zhang, Xue Liu, Yipu Qu, Xiulan Lai, Jinzhi Lei.
      Continuous antigen exposure drives T cells into a progressive state of dysfunction known as exhaustion, enabling tumors to evade immune surveillance and promoting disease progression. Despite its importance, predictive modeling of T cell exhaustion remains a major challenge due to the complexity of its regulatory dynamics. To address this challenge, we developed a mathematical framework that characterizes the dynamic regulation of T cell exhaustion and its impact on tumor-immune interactions. Here, we integrate multi-source data, population dynamics modeling, and agent-based modeling to track the progressive stages of CD8+ T cell exhaustion. Our model demonstrates that immune checkpoint blockade significantly delays exhaustion and promotes the expansion of tumor-reactive T cells compared to untreated conditions. From a pseudo-potential energy perspective, we show that the core mechanism of immunotherapy lies in expanding the tumor-reactive T cell pool, which consequently reduces the overall state of exhaustion within the system. We find that T cell activation and exhaustion signals jointly govern tumor-immune dynamics. Enhancing activation alone without restricting exhaustion can inadvertently accelerate the loss of T cell function. In contrast, combining enhanced activation (via anti-CTLA-4) with suppressed exhaustion (via anti-PD-1) is essential for achieving a sustained antitumor response. Furthermore, spatial simulations confirm that a high-activation and low-exhaustion state effectively restricts tumor spread, maintaining substantially lower tumor densities compared to low-activation, high-exhaustion scenarios. Our framework provides quantitative insights into T cell exhaustion and a theoretical foundation for optimizing combination immunotherapies.
    DOI:  https://doi.org/10.1371/journal.pcbi.1014690
  3. Int J Mol Sci. 2026 Aug 08. pii: 7113. [Epub ahead of print]27(16):
    Spatial Immune Coding in Tumor-Draining Lymph Nodes: Functional Compartmentalization of Immune Activation and Immunosuppression.
    Jinjie Li, Wei Ping, Ruijie Zhang, Lin Peng, Yujie Zhang, Li Zhang.
      Tumor-draining lymph nodes (TDLNs) are important immune organs linking primary tumors with systemic immune responses. They support tumor antigen presentation, T-cell priming, and effector immune responses, but under sustained tumor influence they can also be remodeled into microenvironments that promote immune escape and metastatic colonization. Conventional methods, including flow cytometry, bulk RNA sequencing, and routine immunohistochemistry, have advanced our understanding of TDLN immunity but cannot simultaneously preserve tissue architecture, cell identity, and spatial cell-cell relationships. Recent advances in spatial transcriptomics, spatial proteomics, and multiplexed imaging enable in situ analysis of immune cells, stromal cells, vascular structures, and their interactions within TDLNs. Emerging evidence suggests that TDLNs are not immunologically homogeneous organs, but gradually develop spatially distinct immune-activation and immunosuppressive regions during tumor progression. Activation regions are associated with HEV-mediated lymphocyte entry, DC-T-cell priming, B-cell follicles, and germinal-center reactions, whereas suppressive regions are enriched in Treg cells, exhausted T cells, suppressive myeloid cells, tumor-reprogrammed FRCs, and myeloid-CAF niches. This review summarizes spatial multi-omics studies of TDLN functional compartmentalization and discusses the potential value of TDLN spatial immune states in predicting immunotherapy response, assessing metastatic risk, and guiding precision treatment, thereby providing a reference for future spatial multi-omics studies of TDLNs.
    Keywords:  functional compartmentalization; immune activation; immunosuppressive niche; spatial multi-omics; spatial proteomics; spatial transcriptomics; tertiary lymphoid structures; tumor-draining lymph nodes
    DOI:  https://doi.org/10.3390/ijms27167113
  4. iScience. 2026 Sep 18. 29(9): 117249
    RNF180 loss stabilizes BCAS4 to enhance PD-L1 expression and immune evasion in hepatocellular carcinoma.
    Ke Ye, Xiupeng Cai, Xuefan Dong.
      Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, and the regulation of immune evasion within the tumor microenvironment remains poorly understood. This study shows that breast carcinoma susceptibility protein 4 (BCAS4), not previously studied in HCC, is markedly upregulated in HCC tissues and associated with T cell exhaustion signatures and poor prognosis. BCAS4 enhances PD-L1 expression through NF-κB signaling, driving CD8+ T cell dysfunction and immune evasion. We identify RNF180 as an E3 ligase that binds BCAS4 and mediates its degradation via K48-linked ubiquitination; loss of RNF180 stabilizes BCAS4, amplifying NF-κB activation and PD-L1 upregulation. In vitro and in vivo experiments using a human peripheral blood mononuclear cell (PBMC)-reconstituted xenograft model confirmed that the RNF180-BCAS4 axis modulates CD8+ T cell infiltration and function and promotes tumor progression. Our findings uncover a previously unrecognized RNF180-BCAS4-PD-L1 axis driving immune evasion in HCC, establishing BCAS4 as a potential prognostic biomarker and therapeutic target for improving immunotherapy responses in HCC patients.
    Keywords:  BCAS4; PD-L1; RNF180; hepatocellular carcinoma
    DOI:  https://doi.org/10.1016/j.isci.2026.117249
  5. Front Immunol. 2026 ;17 1870840
    A predictive model for immunotherapy efficacy in cancer based on dynamic changes of CD8+ T cells: a pan-cancer retrospective study.
    Mengyan Xie, Chao Wang, Jun Zhang, Xinming Jing, Pei Ma, Yongqian Shu.
       Objective: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, but reliable peripheral blood biomarkers for monitoring treatment response and predicting prognosis remain limited. This study aimed to analyze the dynamic changes of lymphocyte subsets in patients receiving ICI therapy, evaluate their role in treatment response monitoring and prognosis assessment, and develop a practical clinical risk stratification tool.
    Methods: A total of 121 patients with malignancies who received ICI therapy and had available lymphocyte subset data were retrospectively enrolled. Peripheral blood lymphocyte subsets and routine blood test data were collected before and after treatment. The associations between changes in these parameters and treatment response as well as progression-free survival (PFS) were analyzed using univariate and multivariate Cox regression models. A risk score model and a simplified clinical scoring system were constructed and validated using time-dependent receiver operating characteristic (ROC) curves and Kaplan-Meier analysis.
    Results: Pan-cancer analysis showed that a decrease in CD8+ T cell count after treatment was significantly associated with progressive disease (PD) and inversely correlated with PFS (HR = 0.2308, 95% CI: 0.0875-0.5636). A non-immunotherapy validation cohort further confirmed the immunotherapy-specific nature of CD8+ T cell dynamics. Multivariate Cox analysis identified decreased CD8+ T cell count, elevated neutrophil-to-lymphocyte ratio (NLR), multiple lines of therapy, and specific cancer types (hepatopancreatobiliary malignancies) as independent unfavorable prognostic factors. Time-dependent area under the curve (AUC) values at 2.5, 3.5, and 5.7 months were 0.727, 0.827, and 0.853, respectively, indicating good predictive performance. The risk score based on these variables stratified patients into low-, medium-, and high-risk groups (median PFS: not reached, not reached, and 4.5 months, respectively; p<0.001). A simplified clinical scoring system also effectively distinguished different prognostic groups (median PFS: not reached, 6.2 months, and 4.3 months, respectively; p<0.001).
    Conclusions: The dynamic change in CD8+ T cell count before and after treatment is an independent predictor of PFS in patients receiving ICI therapy and exhibits immunotherapy specificity. The proposed risk stratification tool, incorporating CD8+ T cell dynamics, NLR change, and key clinical variables, provides a simple and effective approach for prognostic assessment and may facilitate individualized treatment decision-making in clinical practice.
    Keywords:  CD8+ T cells; cancer immunotherapy; immune checkpoint inhibitors; lymphocyte subsets; risk stratification
    DOI:  https://doi.org/10.3389/fimmu.2026.1870840
  6. Sci Adv. 2026 Aug 28. 12(35): eaee6195
    A spatially resolved implantable microdevice for multiplexed in situ screening of engineered cellular therapies in solid tumors.
    Sajanlal R Panikkanvalappil, Ellen Maloney, Sebastian W Ahn, Samantha Martin, Courtney Marlin, Sharath K Bhagavatula, Oliver Jonas.
      The clinical translation of cellular immunotherapies for solid tumors remains limited by the lack of adequate tools to evaluate therapeutic function within the native tumor microenvironment. Here, we demonstrate a miniaturized implantable microdevice (IMD) capable of spatially resolving and multiplexing the delivery and screening of multiple T cell therapies directly within live tumors. This customizable IMD is comprised of discrete fibrin-filled reservoirs that can be independently loaded with distinct immune cell formulations, which enables spatially confined release and region-specific immune-tumor interactions within the same tumor mass. Using this platform in glioblastoma xenografts, we simultaneously delivered EGFR-targeting CAR-T cells and control T cells and analyzed adjacent tissues via IHC-based quantitative image analysis and multiplexed immunofluorescence. The perireservoir region adjacent to CAR-T cell reservoirs exhibited dense CD8+ infiltration, cleaved caspase-3-mediated apoptosis, and suppressed Ki67 expression, in contrast to minimal activity in control regions. We believe our IMD platform facilitates the parallel in vivo evaluation of multiple immune cell therapies, providing a translational tool to accelerate the development of successful personalized adoptive cell therapies.
    DOI:  https://doi.org/10.1126/sciadv.aee6195
  7. Front Oncol. 2026 ;16 1906555
    The heterogeneous and dynamic immune-tumor interface in breast cancer.
    Constantin N Baxevanis, Maria Goulielmaki, Angelos D Gritzapis, Ourania E Tsitsilonis.
      Breast cancer (BCa) progression is driven by ongoing interactions between evolving tumor cells and the host immune system. Antitumor immunity is not the same across all BCa subtypes and depends on the quality, localization, and functional state of immune cells within the tumor microenvironment (TME). Highly immunogenic subtypes, such as triple-negative and HER2-positive (+) BCa, generally show stronger immune infiltration and inflammatory signaling, whereas estrogen receptor-positive tumors more often display immune-desert or immune-excluded phenotypes with limited immune cell infiltration and effector activity. Effective immune surveillance requires not only the presence of immune cells, but also their suitable spatial localization and functional capacity. Cytotoxic CD8+ T cells mediate tumor control when they infiltrate tumor areas, whereas stromal-related limitations or functional exhaustion reduces their efficacy. This dysfunction is reinforced by regulatory populations, including FoxP3+ regulatory T cells and CD163+ tumor-associated macrophages, which establish suppressive networks that inhibit effector responses. Within this framework, T-cell immunity is organized into distinct functional states, including stem-like progenitor exhausted T cells, which maintain their immune potential, and effector T cells responsible for cytotoxicity, which support local surveillance. Tertiary lymphoid structures further enhance coordinated immune activation by serving as intratumoral sites of antigen presentation and lymphocyte priming. Immune escape arises through T-cell exhaustion, impaired antigen presentation, tumor-intrinsic signaling changes, and stromal barriers that restrict infiltration. Collectively, these mechanisms generate a regulated, but often tumor-supporting immune environment. BCa progression therefore, reflects a balance between immune activation and suppression, governed by spatial organization and cellular stratification within the TME.
    Keywords:  breast cancer; cancer progression; immune checkpoint blockade; immune escape; immune exhaustion; suppression; tertiary lymphoid structures; tumor microenvironment
    DOI:  https://doi.org/10.3389/fonc.2026.1906555
  8. Front Oncol. 2026 ;16 1782775
    Reprogramming the immunosuppressive microenvironment in glioblastoma: the microglia-MDSC-Treg axis and translational therapeutic strategies.
    Hasan Ali Aydın, Emrah Keskin, Murat Kalaycı.
      Glioblastoma (GBM) remains one of the most lethal primary brain tumors despite maximal surgical resection, radiotherapy, and temozolomide. Immune checkpoint inhibitors have failed to demonstrate durable benefit in three large phase III trials (CheckMate 143, 498, and 548), underscoring profound, multilayered immune resistance. This narrative review synthesizes the immunosuppressive GBM microenvironment, situating the microglia-myeloid-derived suppressor cell (MDSC)-regulatory T cell (Treg) axis within the broader immune landscape, including dendritic cells, natural killer cells, exhausted CD8+ T cells, neutrophils, and B cells. We distinguish ontogenetically distinct resident microglia from bone marrow-derived macrophages, separate monocytic (M-MDSC) from polymorphonuclear (PMN-MDSC) subsets, and examine how radiotherapy reshapes immunity. We extend the immunometabolic discussion beyond indoleamine 2,3-dioxygenase (IDO) to the adenosine (CD39/CD73/A2A), arginine, hypoxia, lactate, and glutamine pathways, and critically analyze why checkpoint blockade has failed. We summarize emerging strategies, including CSF1R, CCR2, CXCR2, CD47-SIRPα, STING, CD40, TGF-β, and IL-1β targeting, together with candidate biomarkers such as circulating MDSCs, CSF1, IL-1β, multiplex immunofluorescence, spatial transcriptomics, and single-cell RNA sequencing, for rational patient selection. We frame these mechanisms as a single, self-reinforcing circuit integrating myeloid-driven immune regulation, metabolic reprogramming, and treatment-induced immune remodeling. We argue that future progress depends on biomarker-driven combinations that reprogram the myeloid compartment, relieve metabolic suppression, and actively inflame the tumor, integrated with radiotherapy and tailored to molecular context (IDH and MGMT status).
    Keywords:  cancer immunotherapy; glioblastoma; immunometabolism; microglia; myeloid immunity; myeloid-derived suppressor cells; regulatory T cells; tumor microenvironment
    DOI:  https://doi.org/10.3389/fonc.2026.1782775
  9. Oncol Lett. 2026 Oct;32(4): 462
    Metabolic heterogeneity and functional diversity of cancer-associated fibroblasts in gastric cancer (Review).
    Qilu Fang, Neng Lv, Shuwei Yu, Jia Wang, Wenxiu Xin.
      Gastric cancer (GC) remains a major global health challenge characterized by poor prognosis and high mortality rates, despite advances in anticancer therapies. Increasing evidence indicates that GC is a highly stromal-rich tumor, with cancer-associated fibroblasts (CAFs) serving as key stromal components of the tumor microenvironment (TME). CAFs exhibit substantial metabolic heterogeneity, such that distinct CAF subtypes demonstrate intrinsic differences and dynamic remodeling in glucose, lipid and amino acid metabolism. This metabolic reprogramming represents not only functional diversity but also an adaptive response to microenvironmental stressors, including tumor-derived signals, hypoxia, nutrient fluctuations and oxidative stress. Through these adaptations, CAFs engage in extensive crosstalk with tumor and immune cells, thereby contributing to microenvironmental remodeling. Due to their critical role and abundance in GC, CAFs have emerged as promising therapeutic targets. The present review summarizes the origins, characteristics and heterogeneity of CAFs in GC and discusses their interactions with the TME. In addition, it summarizes the metabolic heterogeneity of CAFs, explores potential metabolism-targeted therapeutic strategies and outlines the broader impact of CAFs on the TME.
    Keywords:  CAFs; TME; functional diversity; gastric cancer; metabolic heterogeneity
    DOI:  https://doi.org/10.3892/ol.2026.15817
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