Journal Articles

ILT2 identifies an unexploited pool of intratumoral CD8+ bystander T cells with TCR-independent cytotoxicity in renal cell carcinoma Spotlight 

Analyzing primary ccRCC samples, Laboureur et al. identified a subset of CD8+ILT2+PD-1- TILs that were terminally differentiated and expressed high baseline levels of granzyme B, perforin, and NKG2D, but lacked tumor specificity and tissue residency markers. These “bystander” T cells, likely recruited from the periphery, exhibited CD3-driven activation and IFNγ production in response to viral antigens, as well as IL-15/NKG2D-driven, TCR-independent cytotoxicity. The innate-like cytotoxicity was inhibited by HLA-G (an ILT2 ligand expressed on tumor cells), suggestive of a checkpoint axis that could potentially be targeted for immunotherapy.

Contributed by Lauren Hitchings

Analyzing primary ccRCC samples, Laboureur et al. identified a subset of CD8+ILT2+PD-1- TILs that were terminally differentiated and expressed high baseline levels of granzyme B, perforin, and NKG2D, but lacked tumor specificity and tissue residency markers. These “bystander” T cells, likely recruited from the periphery, exhibited CD3-driven activation and IFNγ production in response to viral antigens, as well as IL-15/NKG2D-driven, TCR-independent cytotoxicity. The innate-like cytotoxicity was inhibited by HLA-G (an ILT2 ligand expressed on tumor cells), suggestive of a checkpoint axis that could potentially be targeted for immunotherapy.

Contributed by Lauren Hitchings

ABSTRACT: Immune checkpoint inhibitors (ICIs) have improved clear-cell renal cell carcinoma (ccRCC) therapy, yet many patients remain unresponsive. Alternative strategies are needed, and the HLA-G/ILT2 axis has emerged as a promising immunosuppressive pathway. Here, we deeply characterized CD8_ILT2_ tumor-infiltrating lymphocytes (TILs) as a distinct subset from CD8_PD1_ TILs in ccRCC, using high-dimensional spectral flow cytometry, single-cell transcriptomics, and TCR clonotype analysis. CD8_ILT2_ TILs were terminally differentiated, highly cytotoxic "bystander" cells, enriched for virus-specific TCRs. They phenotypically, transcriptionally and functionally mirrored their circulating counterparts, suggesting peripheral recruitment. In dynamic co-culture assays, they exhibited potent TCR-independent cytotoxicity, mediated by activating innate receptors, namely NKG2D. However, HLA-G inhibited this activity, underscoring the immune-evasive role of the HLA-G/ILT2 axis. Our study defines CD8_ILT2_ TILs as an untapped effector population with potential antitumor activity and a promising therapeutic target in ccRCC. These findings offer new insights into TIL functional diversity and pave the way for innovative immunotherapies beyond conventional ICIs.

Author Info: (1) CEA Fontenay-aux-Roses Paris France. ROR: https://ror.org/010j2gw05 (2) H™pital Saint-Louis Paris France. ROR: https://ror.org/049am9t04 (3) CEA Grenoble Grenoble France. ROR:

Author Info: (1) CEA Fontenay-aux-Roses Paris France. ROR: https://ror.org/010j2gw05 (2) H™pital Saint-Louis Paris France. ROR: https://ror.org/049am9t04 (3) CEA Grenoble Grenoble France. ROR: https://ror.org/02mg6n827 (4) CEA Fontenay-aux-Roses Paris France. ROR: https://ror.org/010j2gw05 (5) Inserm Paris France. ROR: https://ror.org/02vjkv261 (6) Inserm Paris France. ROR: https://ror.org/02vjkv261 (7) CEA Fontenay-aux-Roses Paris France. ROR: https://ror.org/010j2gw05 (8) APHP Paris France. (9) H™pital Saint-Louis, Assistance publique H™pitaux de Paris Paris France. (10) APHP Paris France. (11) Assistance Publique - H™pitaux de Paris Paris France. ROR: https://ror.org/00pg5jh14 (12) CEA Paris-Saclay - Etablissement de Fontenay-aux-roses Paris France. (13) Commissariat ˆ l'Energie Atomique et aux Energies Alternatives Paris France. (14) AP-HP, H™pital Saint-Louis Paris France. (15) Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA) Grenoble France. (16) Inserm Paris France. ROR: https://ror.org/02vjkv261 (17) CEA Fontenay-aux-Roses Paris France. ROR: https://ror.org/010j2gw05 (18) Atomic Energy and Alternative Energies Commission Paris France. ROR: https://ror.org/00jjx8s55

Tumor-resident T cells and dendritic cells form an in situ archetype during immunotherapy response in melanoma Spotlight 

Pietro and Au et al. profiled melanoma lymph node metastases from untreated, ICB-resistant, and ICB-responsive patients using flow cytometry, mIHC, and single-cell transcriptomics to dissect tumor-resident (TR) T cell niches. ICB-responsive tumors were enriched for clonally expanded, cytotoxic CD8⁺ TR cells and cytotoxic/helper CD4⁺ TR cells within an immune-activated microenvironment, whereas ICB-resistant tumors displayed chronic IFNγ signaling, exhausted T cell states, and impaired clonal diversification. Spatial analyses identified CD8⁺ TRs, CD4⁺ TRs, and DC3s forming in situ immune triads as an essential feature of ICB responders.

Contributed by Shishir Pant

Pietro and Au et al. profiled melanoma lymph node metastases from untreated, ICB-resistant, and ICB-responsive patients using flow cytometry, mIHC, and single-cell transcriptomics to dissect tumor-resident (TR) T cell niches. ICB-responsive tumors were enriched for clonally expanded, cytotoxic CD8⁺ TR cells and cytotoxic/helper CD4⁺ TR cells within an immune-activated microenvironment, whereas ICB-resistant tumors displayed chronic IFNγ signaling, exhausted T cell states, and impaired clonal diversification. Spatial analyses identified CD8⁺ TRs, CD4⁺ TRs, and DC3s forming in situ immune triads as an essential feature of ICB responders.

Contributed by Shishir Pant

ABSTRACT: Tumor-resident (TR) T cells, known as tissue-resident memory (TRM) T cells in mice, play a central role in melanoma immunosurveillance, yet their contribution to immune checkpoint inhibitor (ICI) therapy has not been comprehensively explored. We performed spatial and single-cell profiling on 32 metastatic melanoma lymph node samples, from treatment-naïve, ICI-resistant and ICI-responsive patients. Here we show that tumor areas in ICI-responders were enriched for both CD8+ and CD4+ TR. CD8+ TR cells were clonally expanded, and both CD8+ and CD4+ TR cells upregulated cytotoxicity-related gene expression, suggesting functional anti-tumor immunity. Conversely, ICI-resistant tumors displayed chronic IFN-γ response pathways, linked to T cell exhaustion. We further identified a spatially organized immune triad composed of CD8⁺ TR, CD4⁺ TR, and type-3 dendritic cells (DC3) that is exclusive to responding tumors. These findings define coordinated cellular interactions within the tumor microenvironment that underpin successful immunotherapy and provide a framework for spatial biomarkers of response.

Author Info: (1) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Austra

Author Info: (1) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (2) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (3) Bioinformatics, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (4) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Bioinformatics, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (5) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (6) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (7) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (8) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (9) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (10) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (11) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (12) Roche Innovation Center, Zurich, Switzerland. (13) Roche Innovation Center Basel, Roche Pharma Research and Early Development, Basel, Switzerland. (14) Roche Innovation Center Basel, Roche Pharma Research and Early Development, Basel, Switzerland. (15) Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. (16) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Melanoma Research Victoria, Melbourne, VIC, Australia. Division of Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (17) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Melanoma Research Victoria, Melbourne, VIC, Australia. Division of Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (18) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Melanoma Research Victoria, Melbourne, VIC, Australia. Division of Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (19) Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (20) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (21) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (22) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (23) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (24) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (25) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. Melanoma Research Victoria, Melbourne, VIC, Australia. Division of Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. Cancer Biology and Therapeutics Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. (26) Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia. (27) Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia. paul.neeson@petermac.org. Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia. paul.neeson@petermac.org.

An ICAM1-targeting chimeric costimulatory receptor mimics the immune synapse and enhances tumor-specific T cell function Spotlight 

Min et al. developed an ICAM1-specific 4-1BB fusion protein. Engagement of this chimeric costimulatory receptor (ICCR) enhanced tumor cell conjugation and force-dependent immune synapse stability, triggered NF-κB-signaling, and amplified TCR-driven functional activation of engineered T cells, particularly against targets with lower antigen density. In a patient-derived orthotropic xenograft model of aggressive, incurable thyroid cancer, autologous ICCR+ T cells showed selective expansion and prolongation of survival. ICCR+ T cells exhibited reduced TCR diversity, and upregulation of cytotoxicity, TCR signaling, costimulation, and exhaustion genes.

Contributed by Ute Burkhardt

Min et al. developed an ICAM1-specific 4-1BB fusion protein. Engagement of this chimeric costimulatory receptor (ICCR) enhanced tumor cell conjugation and force-dependent immune synapse stability, triggered NF-κB-signaling, and amplified TCR-driven functional activation of engineered T cells, particularly against targets with lower antigen density. In a patient-derived orthotropic xenograft model of aggressive, incurable thyroid cancer, autologous ICCR+ T cells showed selective expansion and prolongation of survival. ICCR+ T cells exhibited reduced TCR diversity, and upregulation of cytotoxicity, TCR signaling, costimulation, and exhaustion genes.

Contributed by Ute Burkhardt

ABSTRACT: Engineered T cell therapies, such as chimeric antigen receptor (CAR) and T cell receptor (TCR)-based approaches, have transformed outcomes in hematological malignancies, yet their efficacy in solid tumors remains limited by tumor antigen escape, immunosuppressive microenvironments, and insufficient activation of CAR or TCR signaling. To overcome these barriers, we developed an intercellular adhesion molecule 1 (ICAM1)-specific chimeric costimulatory receptor (ICCR) engineered for expression in T cells to augment their activation. ICAM1 is broadly expressed across solid tumors and is further upregulated by IFN_ released during early T cell engagement, creating a feed-forward loop that reinforces tumor recognition. ICCR engagement with ICAM1 triggered NF_B signaling independently of TCR-p/MHC engagement; however, full T cell activation and cytotoxic function remained dependent on intact TCR signaling. In primary T cells, ICCR increased proliferation, cytokine production, and cytotoxicity, resulting in improved tumor control in two anaplastic thyroid cancer xenograft models treated with allogeneic or autologous ICCR-T cells. Mechanistically, ICCR strengthened tumor cell engagement, promoted selection and expansion of tumor-specific TCR clonotypes, and amplified downstream signaling pathways. These findings identify ICCR as a strategy that leverages an immune synapse-mimetic mechanism to enhance the function of low-activity tumor-specific TCRs and improve T cell responses in solid tumor microenvironments.

Author Info: (1) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (2) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (3) Weill Corn

Author Info: (1) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (2) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (3) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (4) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (5) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (6) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (7) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (8) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (9) AffyImmune Therapeutics, Inc. Natick, MA United States. (10) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (11) Weill Cornell Medicine New York, NY United States. ROR: https://ror.org/02r109517 (12) Houston Methodist Research Institute Houston, TX United States. (13) Weill Cornell Medicine New York, New York United States. ROR: https://ror.org/02r109517 (14) Weill Cornell Medicine New York, New York United States. ROR: https://ror.org/02r109517 (15) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171 (16) New York Presbyterian Hospital - Weill Cornell Medical College New York, NY United States. (17) Weill Cornell New York, NY United States. (18) Houston Methodist Houston, TX United States. ROR: https://ror.org/027zt9171

Cuproptosis-immunity crosstalk informs strategy to overcome immunotherapy resistance Spotlight 

Lei, Lu, and Xu et al. showed that cuproptosis induced immunogenic cell death, releasing DAMPs that drove DC maturation, DC-dependent cross-priming, and M1-like TAM and effector CD8+ T cell remodeling, with enhanced tumor suppression in immunocompetent hosts. CD8+ T cell-derived IFNγ activated STAT1–IRF1 signaling to upregulate mitochondrial FDX1 in tumor cells, increasing protein lipoylation and sensitization to cuproptosis. In breast, lung, and pancreatic tumor models, combining cuproptosis inducers with anti-PD-L1 amplified tumoral cuproptosis, increased intratumoral CD8+ T cell functions, and overcame intrinsic and acquired ICB resistance.

Contributed by Shishir Pant

Lei, Lu, and Xu et al. showed that cuproptosis induced immunogenic cell death, releasing DAMPs that drove DC maturation, DC-dependent cross-priming, and M1-like TAM and effector CD8+ T cell remodeling, with enhanced tumor suppression in immunocompetent hosts. CD8+ T cell-derived IFNγ activated STAT1–IRF1 signaling to upregulate mitochondrial FDX1 in tumor cells, increasing protein lipoylation and sensitization to cuproptosis. In breast, lung, and pancreatic tumor models, combining cuproptosis inducers with anti-PD-L1 amplified tumoral cuproptosis, increased intratumoral CD8+ T cell functions, and overcame intrinsic and acquired ICB resistance.

Contributed by Shishir Pant

ABSTRACT: Cuproptosis is a recently identified form of copper-dependent cell death that depends on ferredoxin 1 (FDX1)-mediated protein lipoylation. Here, we reveal that CD8(+) T cell-mediated antitumor immunity enhances tumor cell susceptibility to cuproptosis, leading to a more potent tumor-suppressive effect of cuproptosis inducers in immunocompetent hosts compared with immunodeficient ones. Mechanistically, cuproptotic tumor cells act as a form of immunogenic cell death, releasing damage-associated molecular patterns that activate dendritic cells and enhance antitumor immunity. Reciprocally, CD8(+) T cell-derived interferon (IFN)-_ enhances FDX1 transcription in tumor cells by activating the signal transducer and activator of transcription 1 (STAT1)-IFN regulatory factor-1 (IRF1) signaling axis, resulting in heightened tumor cell sensitivity to cuproptosis. Consequently, combining a cuproptosis inducer with anti-programmed cell death ligand 1 (PD-L1) therapy amplifies tumoral cuproptosis and demonstrates efficacy in overcoming PD-L1 therapy resistance across multiple preclinical models. Our findings unveil a previously unrecognized connection between antitumor immunity and cuproptosis and highlight a potential therapeutic approach to counteract tumor immunotherapy resistance by targeting this unique cell death pathway.

Author Info: (1) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: guanglei_csu@163.com. (2) Departme

Author Info: (1) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: guanglei_csu@163.com. (2) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (3) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (4) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (5) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (6) Department of Molecular and Cellular Oncology, Division of Basic Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (7) Metabolomics Core Facility, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (8) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (9) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (10) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (11) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (12) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (13) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (14) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (15) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (16) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (17) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (18) Department of Biostatistics, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (19) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (20) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (21) Department of Molecular and Cellular Oncology, Division of Basic Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (22) Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (23) Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (24) Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (25) Department of Biostatistics, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (26) Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (27) Department of Thoracic and Cardiovascular Surgery, Division of Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (28) Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (29) Department of Molecular and Cellular Oncology, Division of Basic Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (30) Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (31) Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA. (32) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (33) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (34) Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY 10461, USA. (35) Department of Biostatistics, Division of Discovery Science, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (36) Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA. Electronic address: bgan@mdanderson.org.

Neutrophil regulation of immunotherapy for cancer is controlled by type II interferon Featured  

Pei et al. found that the IFNγ produced in tumors during treatment with various immunotherapies induced PD-L1 expression by neutrophils and drove them towards an aged/immunosuppressive phenotype, which contributed to treatment resistance. This could be alleviated by eliminating neutrophils or disrupting type II IFN signaling or PD-L1 expression, which shifted neutrophil polarization to a more pro-inflammatory state. The accumulation of aged, PD-L1+ neutrophils was also evident in data from immunotherapy-treated human tumors, suggesting possible avenues for intervention to improve immunotherapy responses.

Pei et al. found that the IFNγ produced in tumors during treatment with various immunotherapies induced PD-L1 expression by neutrophils and drove them towards an aged/immunosuppressive phenotype, which contributed to treatment resistance. This could be alleviated by eliminating neutrophils or disrupting type II IFN signaling or PD-L1 expression, which shifted neutrophil polarization to a more pro-inflammatory state. The accumulation of aged, PD-L1+ neutrophils was also evident in data from immunotherapy-treated human tumors, suggesting possible avenues for intervention to improve immunotherapy responses.

ABSTRACT: Tumor resistance to immunotherapy is driven by several mechanisms, including those imposed by myeloid populations. Neutrophils are prominent within this landscape and display functional heterogeneity. Here, we investigated the contextual role of neutrophils, and using neutropenic mice, we found that the dominating function was to block the response when targeting T cells or myeloid cells. We found that neutrophils upregulated programmed death ligand-1 (PD-L1) in response to the treatment and, using this as a target, depleted this population. The upregulation of PD-L1 was dependent on interferon-γ (IFN-γ) produced by cytotoxic lymphocytes. Specific genetic deletion of cd274 or Ifngr1 on neutrophils showed that this was cell intrinsic. Moreover, in the absence of the capacity for specific IFN-γ-driven suppression, neutrophils changed their phenotype to support immunotherapy. Thus, we find that the type II interferon, IFN-γ, is key in determining whether neutrophils will support or block immunotherapy for cancer.

Author Info: (1) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden. (2) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sto

Author Info: (1) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden. (2) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden. (3) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden. (4) Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden. (5) Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden. (6) Department of Gastroenterology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. (7) Laboratory of Molecular Genetics and Immunology, Rockefeller University, New York, NY, USA. (8) University of Munster, Institute of Experimental Pathology, Munster, Germany. (9) Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden. Electronic address: mikael.karlsson@ki.se.

Integration of donor microbiota following FMT correlates with anti-PD-1 response in melanoma Spotlight 

Using data from three trials of FMT plus anti-PD-1 in melanoma, Fessler et al. performed a strain-resolved metagenomic meta-analysis, and found that while neither microbial diversity nor acquisition of specific bacterial species were associated with response, recipient acquisition of the donor microbiome and microbiome community stability were. Further, while non-responders were enriched for pro-inflammatory and pathogen-associated secretion system genes, responders were enriched for functions of community-level metabolism and communication, highlighting the importance of the microbial ecosystem over species richness or specific species.

Contributed by Lauren Hitchings

Using data from three trials of FMT plus anti-PD-1 in melanoma, Fessler et al. performed a strain-resolved metagenomic meta-analysis, and found that while neither microbial diversity nor acquisition of specific bacterial species were associated with response, recipient acquisition of the donor microbiome and microbiome community stability were. Further, while non-responders were enriched for pro-inflammatory and pathogen-associated secretion system genes, responders were enriched for functions of community-level metabolism and communication, highlighting the importance of the microbial ecosystem over species richness or specific species.

Contributed by Lauren Hitchings

ABSTRACT: Fecal microbiota transplantation (FMT) has shown promise in improving anti-PD-1 therapy in melanoma, but the underlying microbial features remain poorly defined. We performed a strain-resolved metagenomic meta-analysis across three independent FMT plus anti-PD-1 melanoma trials (n_=_41). Across cohorts, therapeutic benefit was linked to successful integration of donor microbiota, rather than increased diversity or engraftment of specific species. Responders acquired more donor-derived strains, exhibited greater post-FMT similarity to their donor, and maintained a more stable microbiome. Following FMT, non-responders' microbiomes showed greater taxonomic instability, larger fluctuations in estimated microbial load, and increased abundance of pathogen-associated secretion system genes, whereas responders showed enrichment for microbial functions involved in community-level metabolism and communication. Finally, shifts in tumor-infiltrating immune profiles tracked with clinical outcomes and microbiome changes. Together these findings highlight that distinct patterns of microbiome restructuring, including stable community transitions and altered functional capacity, are associated with anti-PD-1 response following FMT.

Author Info: (1) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. (2) Department of Integrative Physiology, University of Colorado Boulder,

Author Info: (1) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. (2) Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA. (3) Department of Pathology, Stanford University, Stanford, CA, USA. Stanford Cancer Institute, Stanford University, Palo Alto, CA, USA. (4) Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. jsonnenburg@stanford.edu. Chan Zuckerberg Biohub, San Francisco, CA, USA. jsonnenburg@stanford.edu. Center for Human Microbiome Studies, Stanford University School of Medicine, Stanford, CA, USA. jsonnenburg@stanford.edu.

Dissecting the cellular architecture of breast cancer brain metastases reveals prognostically distinct immune landscapes Spotlight 

Jassowicz, Feng, and Warta et al. used tissue cytometry, bulk and single-nucleus RNAseq, flow cytometry, and spatial transcriptomics to profile 156 human breast cancer (BC) brain metastases (BCBM) and map functionally and clinically distinct immune landscapes. Enrichment of intratumoral CD8+ TRM-like cells expressing high activation and effector markers, and the presence of tertiary lymphoid structures (TLSs) in BCBM were identified as two favorable immune landscapes associated with improved prognosis. TRM and TLS gene signatures predicted both overall survival in independent BCBM and primary BC cohorts, and response to ICB across cohorts with various cancer types.

Contributed by Shishir Pant

Jassowicz, Feng, and Warta et al. used tissue cytometry, bulk and single-nucleus RNAseq, flow cytometry, and spatial transcriptomics to profile 156 human breast cancer (BC) brain metastases (BCBM) and map functionally and clinically distinct immune landscapes. Enrichment of intratumoral CD8+ TRM-like cells expressing high activation and effector markers, and the presence of tertiary lymphoid structures (TLSs) in BCBM were identified as two favorable immune landscapes associated with improved prognosis. TRM and TLS gene signatures predicted both overall survival in independent BCBM and primary BC cohorts, and response to ICB across cohorts with various cancer types.

Contributed by Shishir Pant

ABSTRACT: Breast cancer brain metastases (BCBM) are a severe condition with high demand for improved personalized treatment, but a comprehensive understanding of BCBM immune-microenvironment heterogeneity and susceptibility to immunotherapy is lacking. Here, we multimodally profile the immune niche in a clinically well-annotated cohort of 156 BCBM applying tissue cytometry, bulk and single nuclei RNA-sequencing, flow cytometry, and spatial transcriptomics, complemented by functional studies in patient-derived models. Integrative analyses reveal two immune landscapes predicting prolonged patient survival and that are not deducible from paired primary tumors: 1) BCBM with a high proportion of CD8(+) tissue-resident-like memory T cells as major players of tumor immune control. 2) BCBM containing tertiary lymphoid structures. Surrogate signatures of these landscapes are prognostic in independent BCBM and primary breast cancer cohorts, are associated with fewer metastases, and predict immunotherapy response. Our work provides critical insights into anti-tumor immunity in BCBM and identifies novel biomarkers with translational relevance.

Author Info: (1) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Divis

Author Info: (1) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address: lena.jassowicz@med.uni-heidelberg.de. (2) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. (3) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (4) Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway. (5) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (6) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg, Germany. (7) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (8) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (9) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (10) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. (11) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. (12) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. (13) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (14) Division Immune Regulation in Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany. (15) Division of Molecular and Translational Radiation Oncology and Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ) and Heidelberg University Hospital, Heidelberg, Germany. (16) Division of Molecular and Translational Radiation Oncology and Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ) and Heidelberg University Hospital, Heidelberg, Germany. (17) Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany. (18) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (19) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (20) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (21) Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), and Hopp Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany. (22) Hamamatsu Tissue Imaging and Analysis Center, BioQuant, University of Heidelberg, Heidelberg, Germany. (23) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (24) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (25) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (26) Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; Oslo Centre for Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway. (27) Single Cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany. (28) Single Cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany. (29) National Center for Tumor Diseases (NCT), NCT Heidelberg, a Partnership Between the German Cancer Research Center (DKFZ), the University Hospital Heidelberg (UKHD), The Heidelberg Medical Faculty of the Heidelberg University, and the Thorax Clinic Heidelberg, Heidelberg, Germany. (30) Department of Medical Oncology, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (31) National Center for Tumor Diseases (NCT), NCT Heidelberg, a Partnership Between the German Cancer Research Center (DKFZ), the University Hospital Heidelberg (UKHD), The Heidelberg Medical Faculty of the Heidelberg University, and the Thorax Clinic Heidelberg, Heidelberg, Germany. (32) National Center for Tumor Diseases (NCT), NCT Heidelberg, a Partnership Between the German Cancer Research Center (DKFZ), the University Hospital Heidelberg (UKHD), The Heidelberg Medical Faculty of the Heidelberg University, and the Thorax Clinic Heidelberg, Heidelberg, Germany; Department of Medical Oncology, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany; Department of Gynecology and Obstetrics, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (33) Division Immune Regulation in Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany. (34) Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany. (35) Division of Molecular and Translational Radiation Oncology and Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ) and Heidelberg University Hospital, Heidelberg, Germany. (36) Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (37) Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (38) Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. (39) Single Cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany. (40) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Tumor Diseases (NCT), NCT Heidelberg, a Partnership Between the German Cancer Research Center (DKFZ), the University Hospital Heidelberg (UKHD), The Heidelberg Medical Faculty of the Heidelberg University, and the Thorax Clinic Heidelberg, Heidelberg, Germany. (41) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. (42) Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address: m.seiffert@dkfz-heidelberg.de. (43) Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany. Electronic address: h.mende@med.uni-heidelberg.de.

Cytotoxic CD39+ tumor-associated NK cells respond to NKG2A blockade in lung cancer

Featured  

Serger et al. profiled NK cells in NSCLC, and identified two tumor-associated NK cell (taNK; CD103+CD49a+) populations. These cells were cytotoxic, but showed hallmarks of dysfunction. Trajectory analysis showed a transition from the CD56bright phenotype through an interferon response and GZMB induction, leading to the expression of genes related to tissue residency, dysfunction, and cytotoxicity. The CD39-expressing subset of taNK cells had the highest tumor killing capacity and responded to anti-NKG2A therapy.

Serger et al. profiled NK cells in NSCLC, and identified two tumor-associated NK cell (taNK; CD103+CD49a+) populations. These cells were cytotoxic, but showed hallmarks of dysfunction. Trajectory analysis showed a transition from the CD56bright phenotype through an interferon response and GZMB induction, leading to the expression of genes related to tissue residency, dysfunction, and cytotoxicity. The CD39-expressing subset of taNK cells had the highest tumor killing capacity and responded to anti-NKG2A therapy.

ABSTRACT: Natural killer (NK) cell-targeting immunotherapies are emerging, yet the differentiation and functional states of tumor-infiltrating NK cells remain poorly understood. Using matched single-nucleus RNA and ATAC sequencing of samples from patients with non-small cell lung cancer (NSCLC), we resolved the transcriptional and epigenetic landscape of intratumoral NK cells. We identified two tumor-associated NK (taNK) cell subsets marked by expression of ITGAE (CD103) and ITGA1 (CD49a) that display features of tissue residency and dysfunction while preserving cytotoxic function. Trajectory and regulon analyses revealed an inflammation-driven transition from early granzyme K (GZMK)(+) NK cells toward an ENTPD1(+) (CD39(+)) effector state characterized by interferon-stimulated gene (ISG) programs. Functional profiling established CD39(+) taNK cells as the dominant cytotoxic NK cell population with superior killing capacity that was further potentiated by NKG2A blockade. This study offers mechanistic insights into NK cell differentiation in NSCLC and establishes CD39(+) taNK cells as a targetable effector population for immunotherapy.

Author Info: (1) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (2) Aix Marseille UniversitŽ, CNRS, INSERM, Centre d'Immunologie de Marseille-Luminy

Author Info: (1) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (2) Aix Marseille UniversitŽ, CNRS, INSERM, Centre d'Immunologie de Marseille-Luminy, Marseille, France. (3) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (4) Institute of Transplant Immunology, Hannover Medical School, Hannover, Germany. (5) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (6) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (7) Institute of Transplant Immunology, Hannover Medical School, Hannover, Germany. (8) Institute of Transplant Immunology, Hannover Medical School, Hannover, Germany. (9) Institute of Transplant Immunology, Hannover Medical School, Hannover, Germany. (10) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (11) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (12) Institute of Pathology, University Hospital and University of Basel, Basel, Switzerland. (13) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (14) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (15) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. Roche Pharma Research and Early Development pRED, Roche Innovation Center, Basel, Switzerland. (16) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (17) Department of Thoracic Surgery, University Hospital Basel, Basel, Switzerland. (18) Department of Thoracic Surgery, University Hospital Basel, Basel, Switzerland. (19) German Centre for Lung Diseases (DZL), BREATH site, Hannover, Germany. Institute of Pathology, Hannover Medical School, Hannover, Germany. (20) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. Medical Oncology, University Hospital Basel, Basel, Switzerland. (21) Institute of Pathology, University Hospital and University of Basel, Basel, Switzerland. (22) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (23) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (24) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (25) Institute of Pathology, University Hospital and University of Basel, Basel, Switzerland. (26) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. Medical Oncology, University Hospital Basel, Basel, Switzerland. (27) Institute of Transplant Immunology, Hannover Medical School, Hannover, Germany. German Centre for Lung Diseases (DZL), BREATH site, Hannover, Germany. German Centre for Infection Research (DZIF), TTU-IICH, Hannover/Braunschweig site, Hannover, Germany. (28) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. (29) Aix Marseille UniversitŽ, CNRS, INSERM, Centre d'Immunologie de Marseille-Luminy, Marseille, France. APHM, H™pital de la Timone, Marseille-Immunop™le Profiling Platform, Marseille, France. Paris-Saclay Cancer Cluster, Villejuif, France. Ecole Polytechnique, Palaiseau, France. (30) Roche Pharma Research and Early Development pRED, Roche Innovation Center, Basel, Switzerland. (31) Department of Biomedicine, University Hospital and University of Basel, Basel, Switzerland. Medical Oncology, University Hospital Basel, Basel, Switzerland.

Pan-cancer single-cell atlases of mouse and human tumor-associated dendritic cells Spotlight 

Caro and Kancheva et al. generated comprehensive scRNAseq atlases of tumor-associated mononuclear phagocytes (monocytes, macrophages, DCs, and pDCs) across 14 mouse and 10 human cancer settings. 31 murine and 25 human lineage-defined tumor-associated DC (TADC) subsets were identified across cDC1, cDC2A, cDC2B, and DC3 subsets. In tumors, new clusters emerged early on, and as tumors progressed, TADCs adopted a more inflammatory, but eventually less mature phenotype Tumor-mediated reprogramming was also evident within lymph node DCs. In patient data, certain TADC subsets and states were associated with patient outcomes.

Contributed by Lauren Hitchings

Caro and Kancheva et al. generated comprehensive scRNAseq atlases of tumor-associated mononuclear phagocytes (monocytes, macrophages, DCs, and pDCs) across 14 mouse and 10 human cancer settings. 31 murine and 25 human lineage-defined tumor-associated DC (TADC) subsets were identified across cDC1, cDC2A, cDC2B, and DC3 subsets. In tumors, new clusters emerged early on, and as tumors progressed, TADCs adopted a more inflammatory, but eventually less mature phenotype Tumor-mediated reprogramming was also evident within lymph node DCs. In patient data, certain TADC subsets and states were associated with patient outcomes.

Contributed by Lauren Hitchings

ABSTRACT: Dendritic cells (DCs) are critical inducers of anti-tumor immunity. To achieve a comprehensive mapping of mouse and human DC subsets and states in a cancer context, here we generate pan-cancer mouse and human tumor-associated DC (TADC) scRNA-seq atlases, encompassing 14 mouse tumor models and 10 human cancer types, within which we identify several lineage-defined DC subsets along with maturation/functional states. We show that TADCs acquire an inflammatory profile with tumor progression and that tumor-mediated reprogramming occurs within the DCs from lymph nodes of tumor-bearing mice. Importantly, we demonstrate that TADCs are broadly conserved between mice and humans, although species-specific differences may exist in some subsets and states. Moreover, we present a comprehensive assessment of how different human TADC clusters associate with patient survival outcomes. Overall, we provide an in-depth characterization of the TADC compartment in mouse and human cancers, which can improve our understanding of the tumor microenvironment and contribute to the development of new anti-cancer therapies.

Author Info: (1) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for I

Author Info: (1) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. Lab of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium. (2) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. (3) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. (4) Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium. Laboratory for Translational Genetics, VIB Center for Cancer Biology, Leuven, Belgium. (5) Laboratory for ER Stress and Inflammation, VIB Center for Inflammation Research, Ghent, Belgium. Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium. Laboratory for Barriers in Inflammation, VIB Center for Inflammation Research, Ghent, Belgium. Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium. (6) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. (7) Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium. VIB Single Cell Core; VIB, Ghent-Leuven, Belgium. (8) Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology in Lausanne (EPFL), Lausanne, Switzerland. Agora Cancer Research Center, Lausanne, Switzerland. (9) Laboratory of Cancer Signaling, GIGA-Institute, University of Lige, Lige, Belgium. (10) Laboratory of Cancer Signaling, GIGA-Institute, University of Lige, Lige, Belgium. (11) Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. (12) Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium. VIB Single Cell Core; VIB, Ghent-Leuven, Belgium. (13) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. (14) Laboratory of Cancer Signaling, GIGA-Institute, University of Lige, Lige, Belgium. Laboratory of Metabolic Regulation, GIGA-Institute, University of Lige, Lige, Belgium. (15) Laboratory of Cancer Signaling, GIGA-Institute, University of Lige, Lige, Belgium. WELBIO Department, WEL Research Institute, Wavre, Belgium. (16) Laboratory for ER Stress and Inflammation, VIB Center for Inflammation Research, Ghent, Belgium. Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium. (17) Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology in Lausanne (EPFL), Lausanne, Switzerland. Agora Cancer Research Center, Lausanne, Switzerland. (18) Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium. Laboratory for Translational Genetics, VIB Center for Cancer Biology, Leuven, Belgium. (19) Lab of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium. (20) Lab of Dendritic Cell Biology and Cancer Immunotherapy, VIB Center for Inflammation Research, Brussels, Belgium. dlaoui@vub.be. Lab of Cellular and Molecular Immunology, Brussels Center for Immunology, Vrije Universiteit Brussel, Brussels, Belgium. dlaoui@vub.be.

FAP-CD40 and PD1-IL2v combination therapy reprograms immunologically cold tumors through de novo intratumoral T cell-dendritic cell clusters Spotlight 

In a KPC tumor model, Nguyen et al. combined a FAP-targeted CD40 agonist (FAP-CD40; localizes CD40 stimulation to the TME) and PD1–IL-2v (targets a mutated IL-2 to PD-1+ T cells and not Tregs). FAP-CD40 alone activated TME cDC1s, which migrated to tdLNs. Combination therapy expanded TME T cells and increased CD4+/CD8+/cDC1 clustering and therapeutic efficacy (dependent on both CD4+ and CD8+ T cells) compared to monotherapies. FTY720 blockade of LN egress did not preclude clustering or efficacy, suggesting activation of TME T cells. Combination therapy boosted TME T cell Th1 gene expression, TNFα/IFNγ production, and Nur77 promoter activity.

Contributed by Alex Najibi

In a KPC tumor model, Nguyen et al. combined a FAP-targeted CD40 agonist (FAP-CD40; localizes CD40 stimulation to the TME) and PD1–IL-2v (targets a mutated IL-2 to PD-1+ T cells and not Tregs). FAP-CD40 alone activated TME cDC1s, which migrated to tdLNs. Combination therapy expanded TME T cells and increased CD4+/CD8+/cDC1 clustering and therapeutic efficacy (dependent on both CD4+ and CD8+ T cells) compared to monotherapies. FTY720 blockade of LN egress did not preclude clustering or efficacy, suggesting activation of TME T cells. Combination therapy boosted TME T cell Th1 gene expression, TNFα/IFNγ production, and Nur77 promoter activity.

Contributed by Alex Najibi

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a major challenge for immunotherapy due to its immunologically cold tumor nature, characterized by poor T cell infiltration and a highly suppressive tumor microenvironment. Here, we propose a novel strategy, combining fibroblast activation protein (FAP)-CD40 to activate dendritic cells (DCs) in the tumor microenvironment and programmed cell death protein-1 (PD1)-interleukin 2v (IL2v) to promote the expansion and differentiation of tumor-infiltrating T cells. We hypothesize that this combination will synergistically enhance both T cell priming and expansion directly within pancreatic 4662 KPC tumors, which recapitulate the immunologically cold features of human PDAC. METHODS: Immune cell distribution and abundance following FAP-CD40/PD1-IL2v monotherapy or combination therapy were analyzed using multiplexed confocal imaging (3D immune phenotyping). FTY720 studies assessed the contribution of lymph node priming in treatment efficacy, while CD4+/CD8+ T cell depletion experiments identified the roles of these subsets in combination therapy. T cell functionality was further assessed through ex vivo restimulation assays and single-cell RNA sequencing. RESULTS: Combination therapy induced dense intratumoral clusters of CD4(+) and CD8(+) T cells, colocalized with type 1 conventional DCs, termed as T cell-DC clusters (TDCs). These TDCs were strongly associated with tumor regression, which required both CD4(+) and CD8(+) T cells. Furthermore, T cells from combination-treated tumors showed enhanced functionality, with increased tumor necrosis factor-alpha and interferon-gamma production compared with monotherapy groups. Single-cell RNA sequencing revealed polarization of CD4(+) T cells toward a T helper cell 1 phenotype in combination-treated tumors. CONCLUSION: The combination of FAP-CD40 and PD1-IL2v offers a promising strategy for treating poorly infiltrated, cold tumors. By driving T cell infiltration, promoting de novo TDC formation and orchestrating local antitumor immunity, this strategy provides a foundation for future therapies targeting immunotherapy-resistant tumors.

Author Info: (1) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (2) Roche Pharma Research and Early Development, Roche Innovation Center Ba

Author Info: (1) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (2) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (3) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (4) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (5) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (6) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (7) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (8) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (9) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (10) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (11) Institute of Experimental Immunology, UniversitŠt ZŸrich, ZŸrich, Switzerland. Department of Immunology, Heidelberg University Medical Faculty Mannheim, Mannheim, Germany. (12) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (13) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland leo.kunz@roche.com.

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