Journal Articles

Tumor-targeted IL-10 synergizes with IL-2 to enhance antitumor immunity while minimizing immune-related adverse events

Spotlight 

Zhichen Sun (1), Yifei Hu (2), Casey Moore (1,3), Baran D. Sumer (4,5), Tao Wang (6) & Jian Qiao (1,3,5).

Nature communications

By analyzing TGCA data and performing tumor modeling in IL-10R KO mice, Sun et al. showed that concurrent IL-10 and high IL-2 signaling correlated with improved tumor control. Combining intratumoral injections of EGFR+ tumor-targeted Cetuximab-based IL-10 and IL-2 immunocytokines boosted efficacy. Antigen-specific intratumoral CD8+ T cells were reactivated, expanded, less exhausted, and dependent on tumor cell MHC-I expression and intratumoral IL-10R+ DCs. IL-10 signaling in macrophages suppressed high-dose IL-2-induced toxicities. Combination therapy enhanced antitumor responses in ex vivo PDTF models.

Contributed by Paula Hochman

Zhichen Sun (1), Yifei Hu (2), Casey Moore (1,3), Baran D. Sumer (4,5), Tao Wang (6) & Jian Qiao (1,3,5).

Nature communications

By analyzing TGCA data and performing tumor modeling in IL-10R KO mice, Sun et al. showed that concurrent IL-10 and high IL-2 signaling correlated with improved tumor control. Combining intratumoral injections of EGFR+ tumor-targeted Cetuximab-based IL-10 and IL-2 immunocytokines boosted efficacy. Antigen-specific intratumoral CD8+ T cells were reactivated, expanded, less exhausted, and dependent on tumor cell MHC-I expression and intratumoral IL-10R+ DCs. IL-10 signaling in macrophages suppressed high-dose IL-2-induced toxicities. Combination therapy enhanced antitumor responses in ex vivo PDTF models.

Contributed by Paula Hochman

ABSTRACT: Tumor-targeting cytokines have emerged as a promising strategy for cancer immunotherapy, although their mechanisms of action often remain complex. In this study, we develop an approach by combining tumor-targeted IL-10 (CmAb-(IL10)2) with IL-2 (CmAb-IL2) to enhance antitumor immunity while minimizing immune-related adverse events (irAEs). We demonstrate that endogenous IL-10 plays a critical role in IL-2-mediated antitumor effects, and that the combination of CmAb-(IL10)2 and CmAb-IL2 preferentially expands less-exhausted CD8+ T cells within tumors. Mechanistically, we identify that the IL-10/IL-10 receptor (IL-10R) axis in dendritic cells (DCs) is critical for mediating the efficacy of this combination therapy by promoting intratumoral DC function. Furthermore, we show that this combination enhances antitumor immune responses in humanized female mice and ex vivo patient-derived tumor fragments models. Our findings reveal that tumor-targeted IL-10 synergizes with IL-2 to enhance antitumor immunity through the IL-10/IL-10R/DC axis within tumors, while mitigating IL-2-associated irAEs through the IL-10/IL-10R/macrophage axis. This approach offers an IL-10 based strategy to improve the efficacy of immunotherapy while reducing irAEs.

Author Info: 1 - Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 2 - Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Hea

Author Info: 1 - Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 2 - Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA. 3 - Immunology Graduate Program, University of Texas Southwestern Medical Center, Dallas, TX, USA. 4 - Department of Otolaryngology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 5 - Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA. 6 - Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. e-mail: Jian.Qiao@UTSouthwestern.edu

Citation: Nat com 2026

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    Computational design of optimized and preferentially paired human TCR constant regions for improved T cell function Spotlight 

    (1) Radman M (2) Shamul-Raybi A (3) Parker J (4) Fleishman SJ (5) Cohen CJ

    Science advances | Free PMC Article

    Using a computational strategy, Radman et al. mutated the constant and transmembrane regions of the MART-1 DMF4 TCR α/β chains to reduce mispairing and improve expression. TCR variants were found that increased expression and TNFα production against MART-1+ cells compared to the WT TCR, and the modified α/β chains expressed better together than with their WT counterparts. Modified TCR-T cells generated by retroviral vector had superior cytokine production to WT TCR-T (in bulk T cells and CD4+ or CD8+ T cells), as well as cytotoxicity and in vivo efficacy. This same strategy was successfully applied to other antitumor and antiviral TCRs.

    Contributed by Alex Najibi

    (1) Radman M (2) Shamul-Raybi A (3) Parker J (4) Fleishman SJ (5) Cohen CJ

    Science advances | Free PMC Article

    Using a computational strategy, Radman et al. mutated the constant and transmembrane regions of the MART-1 DMF4 TCR α/β chains to reduce mispairing and improve expression. TCR variants were found that increased expression and TNFα production against MART-1+ cells compared to the WT TCR, and the modified α/β chains expressed better together than with their WT counterparts. Modified TCR-T cells generated by retroviral vector had superior cytokine production to WT TCR-T (in bulk T cells and CD4+ or CD8+ T cells), as well as cytotoxicity and in vivo efficacy. This same strategy was successfully applied to other antitumor and antiviral TCRs.

    Contributed by Alex Najibi

    ABSTRACT: T cell receptor (TCR) gene transfer is a promising approach for cancer immunotherapy, but its efficacy is limited by mispairing of TCR chains, which reduces surface expression and may generate off-target specificities. We applied the PROSS and FuncLib algorithms to engineer human TCR constant regions for improved stability and preferential pairing. After several screening rounds, we identified a variant, termed structurally enhanced TCR (SET), that exhibited markedly enhanced surface expression, functional avidity, and reduced mispairing. SET-expressing T cells secreted higher cytokine levels, displayed increased activation, and mediated superior cytotoxicity. Notably, SET demonstrated function in CD4(+) T cells and mediated potent tumor control in xenograft models, significantly delaying tumor growth and improving survival. SET's benefits were reproducible across six different TCRs, supporting its broad applicability. These findings highlight the potential of rational design to improve the potency of TCR-based therapies.

    Author Info: (1) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (2) The Laboratory of Tumor

    Author Info: (1) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (2) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (3) Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel. (4) Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel. (5) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel.

    Citation: Sci Adv 2026 Sep 25 12:eaeb9189 Epub09/23/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42777048

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    Functional evaluation of TCR-pMHC pairs at scale allows in silico TCR reactivity prediction Featured  

    (1) Messemaker M (2) Kwee BPY (3) Moravec _ (4) de Paauw S (5) Urbanus J (6) çlvarez-Salmoral D (7) Geerligs J (8) Xie R (9) Voogd R (10) Morris B (11) Guislain A (12) Winkler Y (13) Richterich CA (14) Mussmann M (15) Bakker M (16) Steinmetz M (17) Iras M (18) Marcus E (19) Teuwen J (20) Perrakis A (21) Beijersbergen RL (22) Scheper W (23) Schumacher TN

    Immunity

    Messemaker and Kwee et al. developed a TCR rapid assembly platform (T-RAP) and used it to generate a dataset of functionally validated TCR-pMHC pairs, which enabled the assembly of diverse and standardized TCR libraries and allowed for structure-based prediction of TCR-pMHC reactivity. Pooled screening of these TCR libraries could then be used to evaluate the quality of existing reactivity prediction models, including tcrdist3 and AlphaFold3, showed strong capacities for distinguishing reactivity and could be used both to pair TCRs with cognate pMHC epitopes and to shortlist TCRs with reactivity to patient-specific neoantigens, without any task-specific training.

    (1) Messemaker M (2) Kwee BPY (3) Moravec _ (4) de Paauw S (5) Urbanus J (6) çlvarez-Salmoral D (7) Geerligs J (8) Xie R (9) Voogd R (10) Morris B (11) Guislain A (12) Winkler Y (13) Richterich CA (14) Mussmann M (15) Bakker M (16) Steinmetz M (17) Iras M (18) Marcus E (19) Teuwen J (20) Perrakis A (21) Beijersbergen RL (22) Scheper W (23) Schumacher TN

    Immunity

    Messemaker and Kwee et al. developed a TCR rapid assembly platform (T-RAP) and used it to generate a dataset of functionally validated TCR-pMHC pairs, which enabled the assembly of diverse and standardized TCR libraries and allowed for structure-based prediction of TCR-pMHC reactivity. Pooled screening of these TCR libraries could then be used to evaluate the quality of existing reactivity prediction models, including tcrdist3 and AlphaFold3, showed strong capacities for distinguishing reactivity and could be used both to pair TCRs with cognate pMHC epitopes and to shortlist TCRs with reactivity to patient-specific neoantigens, without any task-specific training.

    ABSTRACT: Accurate prediction of T cell receptor (TCR) reactivity is a long-standing goal in immunology. Here, we asked whether functional validation of TCR-peptide-major histocompatibility complex (MHC) (TCR-pMHC) pairs at scale alters performance estimates of TCR-pMHC reactivity prediction models. We developed a TCR rapid assembly platform (T-RAP) that allowed the generation of large and uniform TCR libraries. T-RAP enabled evaluation of TCR signaling or MHC multimer binding of thousands of previously reported TCR-pMHC pairs under standardized conditions. In this setting of systematic standardized evaluation, only _50% of these TCRs showed the previously reported TCR reactivity. Notably, AlphaFold3 structural predictions showed good performance in identifying reactive TCR-pMHC pairs within the set of TCRs that experimentally validated without any task-specific training. AlphaFold3 structural predictions could likewise be used to shortlist TCRs reactive to patient-specific cancer neoantigens. In silico prediction of TCR-pMHC reactivity thus has greater feasibility than previously assumed, with implications for basic research and clinical application.

    Author Info: (1) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (2) Division of Molecular

    Author Info: (1) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (2) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (3) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (4) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (5) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (6) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (7) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands; The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (8) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (9) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (10) The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (11) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (12) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (13) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (14) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (15) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (16) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (17) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (18) AI for Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (19) AI for Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (20) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (21) The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (22) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (23) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands; Department of Hematology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: t.schumacher@nki.nl.

    Citation: Immunity 2026 Oct 1 Epub10/01/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42822443

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    Antibodies against HLA-E-VL9 enhance NK cell and CD8+ T cell cytotoxicity against tumor cells and HIV-infected CD4+ T cells

    Spotlight 

    (1) Hwang JK (2) Tuyishime M (3) Marston DJ (4) Yang H (5) Wrapp D (6) Li D (7) Brackenridge S (8) Frazier M (9) Levering NP (10) Scearce R (11) Rhodes B (12) Harris C (13) Quastel M (14) Kapingidza AB (15) Kliszczak AE (16) Gater J (17) Borrow P (18) Ferrari G (19) Gillespie GM (20) McMichael AJ (21) Haynes BF (22) Azoitei ML

    Science translational medicine

    Hwang et al. engineered high-affinity antibodies against HLA-E–VL9 using structure-based design and high-throughput library screening to block inhibitory NKG2A/CD94 interactions. HLA-E–VL9 mAbs enhanced direct NK cell killing and NK-mediated ADCC against HLA-E–VL9+ tumors in vitro and K562HLA-E–VL9 tumors in vivo. HIV-infected primary CD4+ T cells expressed HLA-E–VL9, and HLA-E–VL9 mAbs mediated NK cell ADCC that selectively eliminated activated or infected CD4+ T cells over resting CD4+ T cells. HLA-E–VL9 blockade also enhanced NKG2A+CD8+ T cell-mediated HIV-specific cytotoxicity.

    Contributed by Shishir Pant

    (1) Hwang JK (2) Tuyishime M (3) Marston DJ (4) Yang H (5) Wrapp D (6) Li D (7) Brackenridge S (8) Frazier M (9) Levering NP (10) Scearce R (11) Rhodes B (12) Harris C (13) Quastel M (14) Kapingidza AB (15) Kliszczak AE (16) Gater J (17) Borrow P (18) Ferrari G (19) Gillespie GM (20) McMichael AJ (21) Haynes BF (22) Azoitei ML

    Science translational medicine

    Hwang et al. engineered high-affinity antibodies against HLA-E–VL9 using structure-based design and high-throughput library screening to block inhibitory NKG2A/CD94 interactions. HLA-E–VL9 mAbs enhanced direct NK cell killing and NK-mediated ADCC against HLA-E–VL9+ tumors in vitro and K562HLA-E–VL9 tumors in vivo. HIV-infected primary CD4+ T cells expressed HLA-E–VL9, and HLA-E–VL9 mAbs mediated NK cell ADCC that selectively eliminated activated or infected CD4+ T cells over resting CD4+ T cells. HLA-E–VL9 blockade also enhanced NKG2A+CD8+ T cell-mediated HIV-specific cytotoxicity.

    Contributed by Shishir Pant

    ABSTRACT: A major natural killer (NK) cell and CD8(+) T cell checkpoint is mediated by the inhibitory receptor NKG2A/CD94 and its ligand, human leukocyte antigen E (HLA-E) complexed with nine-amino acid HLA-Ia leader sequence-derived peptides termed VL9 (HLA-E-VL9). Here, we used structure-based design and high-throughput library screening to generate high-affinity antibodies that block NKG2A/CD94 interactions. These antibodies enabled direct NK and CD8(+) T cell cytotoxicity and mediated NK cell antibody-dependent cellular cytotoxicity (ADCC). Anti-HLA-E-VL9 antibodies enhanced human NK cell line NK-92 killing of HLA-E-VL9(+) human tumors in mice, demonstrating checkpoint inhibition activity in vivo. Moreover, HLA-E-VL9 was found to be expressed on primary human CD4(+) T cells infected with HIV in vitro, and its engagement by HLA-E-VL9 antibodies drove elimination of infected cells by NK cell-mediated ADCC. HLA-E-VL9 antibodies also enhanced the killing of HIV-infected cells by NKG2A/CD94(+) CD8(+) T cells targeting an HIV Rev-derived epitope that complexes with HLA-E. Therefore, anti-HLA-E-VL9 antibodies represent a candidate therapeutic approach to eliminating pathogenic target cells by enhancing both NK cell and CD8(+) T cell function and by promoting ADCC.

    Author Info: (1) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (2) Department o

    Author Info: (1) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (2) Department of Surgery, Duke University School of Medicine, Durham, NC, USA. (3) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA. (4) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. Chinese Academy of Medical Sciences Oxford Institute, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (5) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (6) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (7) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (8) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA. (9) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (10) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (11) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA. (12) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA. (13) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (14) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. (15) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (16) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. (17) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (18) Department of Surgery, Duke University School of Medicine, Durham, NC, USA. (19) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (20) Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (21) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Medicine, Duke University School of Medicine, Durham, NC, USA. Department of Integrative Immunobiology, Duke University School of Medicine, Durham, NC, USA. (22) Duke Human Vaccine Institute, Duke University School of Medicine, Durham, NC, USA. Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA.

    Citation: Sci Transl Med 2026 Sep 16 18:eaea3879 Epub09/16/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42748220

    Tags:

    Identification of broadly tumour-reactive γδ TCRs from multiple myeloma

    Spotlight 

    (1) St Paul M (2) Hendrikse LD (3) Ying F (4) Snow BE (5) Luo P (6) Helke S (7) Smith LK (8) Hilal A (9) Abelman DD (10) Ramamurthy N (11) Nault H (12) Wei EN (13) Gold MJ (14) Tobin C (15) Lien SC (16) Liu Y (17) Zhou W (18) Zhang X (19) Nguyen D (20) Agbede O (21) Pedersen S (22) Eagles J (23) Saunders ME (24) Berger T (25) Wakeham A (26) Scott DS (27) Ly D (28) de Campos CB (29) Liang G (30) Zheng C (31) Wilson WV (32) Masih-Khan E (33) White D (34) McCurdy A (35) Louzada ML (36) Kotb R (37) Chu MP (38) Parkin S (39) Reece D (40) Gul E (41) Tiedemann R (42) Pugh TJ (43) Hirano N (44) Ohashi PS (45) Stewart AK (46) Trudel S (47) Mak TW

    Nature

    St. Paul and Hendrikse et al. used single-cell sequencing and developed a machine-learning algorithm (PreGame) to distinguish the enigmatic tumor-reactive γδ T cells (TRγδ T cells) from bystander cells and confirm their specificity. From MM patient bone marrow, PreGame identified TRγδ T cells that recognized broadly expressed tumor antigens in a TCR-dependent manner. Responsive patients treated with a BCMA-targeted ADC exhibited significant expansion of TRγδ T cells and of γδ TCRs in cfDNA, which correlated with favorable responses and served as an early response biomarker. A γδ TCR epitope in the ubiquitously expressed HLA-C protein was identified.

    Contributed by Katherine Turner

    (1) St Paul M (2) Hendrikse LD (3) Ying F (4) Snow BE (5) Luo P (6) Helke S (7) Smith LK (8) Hilal A (9) Abelman DD (10) Ramamurthy N (11) Nault H (12) Wei EN (13) Gold MJ (14) Tobin C (15) Lien SC (16) Liu Y (17) Zhou W (18) Zhang X (19) Nguyen D (20) Agbede O (21) Pedersen S (22) Eagles J (23) Saunders ME (24) Berger T (25) Wakeham A (26) Scott DS (27) Ly D (28) de Campos CB (29) Liang G (30) Zheng C (31) Wilson WV (32) Masih-Khan E (33) White D (34) McCurdy A (35) Louzada ML (36) Kotb R (37) Chu MP (38) Parkin S (39) Reece D (40) Gul E (41) Tiedemann R (42) Pugh TJ (43) Hirano N (44) Ohashi PS (45) Stewart AK (46) Trudel S (47) Mak TW

    Nature

    St. Paul and Hendrikse et al. used single-cell sequencing and developed a machine-learning algorithm (PreGame) to distinguish the enigmatic tumor-reactive γδ T cells (TRγδ T cells) from bystander cells and confirm their specificity. From MM patient bone marrow, PreGame identified TRγδ T cells that recognized broadly expressed tumor antigens in a TCR-dependent manner. Responsive patients treated with a BCMA-targeted ADC exhibited significant expansion of TRγδ T cells and of γδ TCRs in cfDNA, which correlated with favorable responses and served as an early response biomarker. A γδ TCR epitope in the ubiquitously expressed HLA-C protein was identified.

    Contributed by Katherine Turner

    ABSTRACT: γδ T cells are becoming increasingly appreciated for their antitumour capacity and role in mediating responses to immune checkpoint blockade1-3. Unlike classical αβ T cells, the degree to which γδ T cells rely on their T cell receptors (TCRs) to induce antitumour responses remains unclear. The challenge of distinguishing γδ T cells with tumour-reactive TCRs from bystander γδ T cells limits our understanding of tumour-reactive γδ T cell biology and the translation of their TCRs into immunotherapeutics. Here we present PreGame, a machine-learning algorithm capable of identifying tumour-reactive γδ T cells from single-cell CITE sequencing data. We use PreGame to identify tumour-reactive γδ T cells from patients with multiple myeloma or other solid cancers, and confirm the specificity of their TCRs to tumour cells. Clinically, we demonstrate that expansion of tumour-reactive γδ T cells is an early biomarker of response in patients with multiple myeloma receiving combination therapy with belantamab mafodotin. We also identify a γδ TCR epitope in the ubiquitously expressed HLA-C protein and a logic gate that enables tumour immunosurveillance. Thus, PreGame is a versatile tool that can accelerate our understanding of γδ T cell biology and facilitate the translation of γδ TCRs into universal therapeutics.

    Author Info: (1) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. michael.stpaul@uhn.ca. (2) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. liam.hendrikse@uhn.ca. (3) Prin

    Author Info: (1) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. michael.stpaul@uhn.ca. (2) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. liam.hendrikse@uhn.ca. (3) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (4) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (5) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Department of Computer Science and Mathematics, Faculty of Computer Science and Technology, Algoma University, Brampton, Ontario, Canada. (6) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (7) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (8) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (9) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (10) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (11) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (12) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (13) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (14) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (15) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (16) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (17) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (18) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (19) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (20) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (21) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (22) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (23) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (24) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (25) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (26) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (27) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (28) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (29) Centre for Oncology and Immunology, Hong Kong Science Park, Hong Kong SAR, China. (30) Centre for Oncology and Immunology, Hong Kong Science Park, Hong Kong SAR, China. (31) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (32) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (33) Queen Elizabeth II Health Sciences Centre, Dalhousie University, Halifax, Nova Scotia, Canada. (34) Ottawa Hospital Research Institute, Ottawa, Ontario, Canada. (35) London Health Sciences Centre, London, Ontario, Canada. (36) CancerCare Manitoba, Winnipeg, Manitoba, Canada. (37) Cross Cancer Institute, Edmonton, Alberta, Canada. (38) Vancouver General Hospital, Vancouver, British Columbia, Canada. (39) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (40) Canadian Myeloma Research Group (CMRG), Vaughan, Ontario, Canada. (41) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (42) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. Ontario Institute for Cancer Research, Toronto, Ontario, Canada. (43) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (44) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. (45) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. (46) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. suzanne.trudel@uhn.ca. (47) Princess Margaret Cancer Centre, Toronto, Ontario, Canada. tak.mak@uhn.ca. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. tak.mak@uhn.ca. Centre for Oncology and Immunology, Hong Kong Science Park, Hong Kong SAR, China. tak.mak@uhn.ca.

    Citation: Nature 2026 Sep 16 Epub09/16/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42749802

    Tags:

    Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages Spotlight 

    (1) Lin C (2) Li S (3) Lou R (4) Teng W (5) Tian Y (6) Feng C (7) Wang N (8) Rao Y (9) Qin Y (10) Li L (11) Huang X (12) Lin Y (13) Zhang J (14) Xia N (15) Huang C

    Science advances | Free PMC Article

    Lin et al. engineered an oncolytic herpesvirus (oHSV) with a PD-L1 nanobody attached to gD on the viral envelope surface (gDαPD- L1), targeting the virus to both tumors and TAMs expressing PD-L1. In addition to its oncolytic activity, this CAR-oHSV also resulted in the presentation of anti-PD-L1 CARs on infected cells, blocking PD-L1 in cis. In TAMs, CAR-oHSV killed a subset of TAMs, while remaining TAMs were reprogrammed via STING activation towards a CXCL9+ antigen-presenting phenotype that supported CD8+ T cell-mediated antitumor immunity. CAR-oHSV was well tolerated and showed synergy with checkpoint blockade and adoptive cell therapy.

    Contributed by Lauren Hitchings

    (1) Lin C (2) Li S (3) Lou R (4) Teng W (5) Tian Y (6) Feng C (7) Wang N (8) Rao Y (9) Qin Y (10) Li L (11) Huang X (12) Lin Y (13) Zhang J (14) Xia N (15) Huang C

    Science advances | Free PMC Article

    Lin et al. engineered an oncolytic herpesvirus (oHSV) with a PD-L1 nanobody attached to gD on the viral envelope surface (gDαPD- L1), targeting the virus to both tumors and TAMs expressing PD-L1. In addition to its oncolytic activity, this CAR-oHSV also resulted in the presentation of anti-PD-L1 CARs on infected cells, blocking PD-L1 in cis. In TAMs, CAR-oHSV killed a subset of TAMs, while remaining TAMs were reprogrammed via STING activation towards a CXCL9+ antigen-presenting phenotype that supported CD8+ T cell-mediated antitumor immunity. CAR-oHSV was well tolerated and showed synergy with checkpoint blockade and adoptive cell therapy.

    Contributed by Lauren Hitchings

    ABSTRACT: Immunosuppressive tumor-associated macrophages (TAMs) create a barrier to effective antitumor immunity and promote therapeutic resistance. Reeducating TAMs to enhance their antitumor capabilities through phenotypic remodeling remains challenging. Here, we report a modular oncolytic herpesvirus platform, engineered with a PD-L1-specific chimeric receptor integrated into the viral envelope protein (CAR-oHSV). This design endows the virus with dual tropism, enabling it to target both tumor cells and TAMs within the tumor microenvironment. In virus-resistant tumor models, CAR-oHSV preferentially targets PD-L1(+) TAMs and triggers a STING-dependent reprogramming into a CXCL9(+) phenotype, enhancing their tumor antigen cross-presentation capability and inducing an endogenous antitumor T cell response. Furthermore, this platform can synergize with adoptive T cell therapy and immune checkpoint blockade therapy to overcome immunotherapy resistance. Collectively, our findings define a precision-oncolytic platform that dismantles TAM-mediated immunosuppression while amplifying adaptive immunity, offering a promising translational avenue for cancer immunotherapy.

    Author Info: (1) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institu

    Author Info: (1) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (2) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (3) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (4) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (5) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (6) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (7) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (8) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (9) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (10) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (11) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (12) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (13) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. (14) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China. School of Life Sciences, Xiamen University, Xiamen, 361102, China. (15) State Key Laboratory of Vaccines for Infectious Diseases, Department of Laboratory Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China. National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, 361102, China.

    Citation: Sci Adv 2026 Sep 18 12:eaef6767 Epub09/18/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42758830

    Tags:

    Characterization of circulating neoantigen-specific T cell responses and public T cell receptors shaping immune memory in Lynch syndrome carriers Spotlight 

    (1) Duzagac F (2) Deng N (3) Wang J (4) Nagaraju S (5) Steinberger P (6) Reuben A (7) Sinha KM (8) Vilar E

    Cell reports. Medicine

    Duzagac et al. characterized circulating neoantigen-specific T cells in Lynch syndrome (LS) carriers using functional assays, single-cell RNA/TCR sequencing, and integration with existing TCR datasets. Cancer-free LS carriers retained polyfunctional effector and tissue-surveillance states, whereas cancer survivors showed glycolytic, stress-associated, and exhausted T cell states. Recurrent frameshift neoantigens elicited strong T cell responses and tumor organoid killing. Public neoantigen-specific TCRs showed clonal expansion and were shared across blood, pre-cancer, and tumor tissues. Reconstructed TCRs mediated HLA-restricted tumor recognition.

    Contributed by Shishir Pant

    (1) Duzagac F (2) Deng N (3) Wang J (4) Nagaraju S (5) Steinberger P (6) Reuben A (7) Sinha KM (8) Vilar E

    Cell reports. Medicine

    Duzagac et al. characterized circulating neoantigen-specific T cells in Lynch syndrome (LS) carriers using functional assays, single-cell RNA/TCR sequencing, and integration with existing TCR datasets. Cancer-free LS carriers retained polyfunctional effector and tissue-surveillance states, whereas cancer survivors showed glycolytic, stress-associated, and exhausted T cell states. Recurrent frameshift neoantigens elicited strong T cell responses and tumor organoid killing. Public neoantigen-specific TCRs showed clonal expansion and were shared across blood, pre-cancer, and tumor tissues. Reconstructed TCRs mediated HLA-restricted tumor recognition.

    Contributed by Shishir Pant

    ABSTRACT: Lynch syndrome (LS), a common inherited genetic condition predisposing to cancer, provides a unique model to study immune surveillance at the earliest stages of tumorigenesis. A hallmark of LS carcinogenesis is the generation of highly immunogenic neoantigens, yet the transcriptomic states of the T cells that recognize them remain poorly understood. Here, we characterize neoantigen-specific T cells from LS carriers using functional assays, single-cell RNA/T cell receptor (TCR) sequencing, and repertoire integration with existing large datasets. Recurrent neoantigens elicit strong immune responses, with neoantigen-specific T cells mediating cytotoxicity against tumor organoids. Single-cell analysis reveals oligoclonal expansions spanning effector and memory states with enrichment for exhausted subsets among cancer survivors and retention of polyfunctional effectors in cancer-free carriers. Cross-cohort analysis identifies public TCR clonotypes in circulation that overlap with pre-cancer and tumor tissue repertoires. Together, these findings define the architecture of circulating neoantigen-specific immune memory in LS and highlight public TCRs as candidates for immune monitoring and immunoprevention.

    Author Info: (1) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (2) Department of Clinical Cancer Prevention, The University of T

    Author Info: (1) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (2) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (3) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (4) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (5) Institute of Immunology, Medical University of Vienna, Vienna, Austria. (6) Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (7) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (8) Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: evilar@mdanderson.org.

    Citation: Cell Rep Med 2026 Sep 18 103057 Epub09/18/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42759506

    Tags:

    Inducible IL-12 or IL-18 secreting CAR T cells targeting the glyco-antigen CD176 exhibit potent activity against non-small cell lung cancer in preclinical models Spotlight 

    (1) Malinconico C (2) Weber J (3) Polzien AJ (4) Bonifacius A (5) Umland M (6) Deveuve Q (7) Bargmann T (8) Zimmermann K (9) Gellert J (10) Neubert L (11) DŸbel S (12) Schambach A (13) Braun A (14) Blasczyk R (15) Abken H (16) Hudecek M (17) Dragon AC (18) Eiz-Vesper B

    Cancer immunology research

    Malinconico et al. engineered T cells with both a CAR targeting CD176 (expressed in NSCLC and other tumors), and an inducible cassette encoding either IL-18 or IL-12 that would be expressed following CAR activation of NF-κB. The resulting CD176-iIL18 or CD176-iIL12 TRUCKs showed antigen-dependent secretion of IL-18/IL-12, increased effector molecules, and heightened THP-1 monocyte chemoattraction. They also showed increased cytotoxicity and antitumor activity in vitro, against patient explants, and in vivo, and performed best when both CD4+ and CD8+ T cells were included. TRUCKs producing IL-12 outperformed those producing IL-18, but with more toxicity.

    Contributed by Lauren Hitchings

    (1) Malinconico C (2) Weber J (3) Polzien AJ (4) Bonifacius A (5) Umland M (6) Deveuve Q (7) Bargmann T (8) Zimmermann K (9) Gellert J (10) Neubert L (11) DŸbel S (12) Schambach A (13) Braun A (14) Blasczyk R (15) Abken H (16) Hudecek M (17) Dragon AC (18) Eiz-Vesper B

    Cancer immunology research

    Malinconico et al. engineered T cells with both a CAR targeting CD176 (expressed in NSCLC and other tumors), and an inducible cassette encoding either IL-18 or IL-12 that would be expressed following CAR activation of NF-κB. The resulting CD176-iIL18 or CD176-iIL12 TRUCKs showed antigen-dependent secretion of IL-18/IL-12, increased effector molecules, and heightened THP-1 monocyte chemoattraction. They also showed increased cytotoxicity and antitumor activity in vitro, against patient explants, and in vivo, and performed best when both CD4+ and CD8+ T cells were included. TRUCKs producing IL-12 outperformed those producing IL-18, but with more toxicity.

    Contributed by Lauren Hitchings

    ABSTRACT: To date, non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide, underscoring the urgent need for new treatment options. The oncofetal carbohydrate CD176 is masked on healthy tissues but is present on a variety of cancer entities and is associated with cancer invasiveness and metastasis. In this study, we employed chimeric antigen receptor T cells (CAR-Ts) directed against CD176 for treatment of NSCLC. CD176-CAR-Ts were optimized with an additional inducible cassette encoding IL-18 (CD176-iIL18-TRUCKs) or IL-12 (CD176-iIL12-TRUCKs) to augment antitumor reactivity through autocrine and paracrine signaling. CD176-iIL18- and CD176-iIL12-TRUCKs eradicate NSCLC cells in a 3D tumor spheroid model and tissue slices derived from lung adenocarcinoma patients more potently than CD176-CAR-Ts. Administration of TRUCKs in a lung carcinoma xenograft mouse model results in partial or complete tumor eradication in all mice treated with CD176-iIL12-TRUCKs and in 50% of mice treated with CD176-iIL18-TRUCKs. This study highlights the potential of CD176 as a CAR-T-cell target and suggest CD176-CAR-Ts armored with IL-18 or IL-12 as promising new therapeutic approach for the treatment of NSCLC and several other CD176-positive cancer entities.

    Author Info: (1) Italian Institute of Technology Napoli Italy. ROR: https://ror.org/042t93s57 (2) University Hospital WŸrzburg WŸrzburg Germany. (3) Hannover Medical School Hannover Germany. (4

    Author Info: (1) Italian Institute of Technology Napoli Italy. ROR: https://ror.org/042t93s57 (2) University Hospital WŸrzburg WŸrzburg Germany. (3) Hannover Medical School Hannover Germany. (4) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98 (5) Hannover Medical School Hannover Germany. (6) UniversitŠtsklinikum WŸrzburg WŸrzburg Germany. (7) Fraunhofer Institute for Toxicology and Experimental Medicine Hannover, Lower Saxony Germany. ROR: https://ror.org/02byjcr11 (8) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98 (9) Glycotope GmbH Berlin Germany. (10) Medizinische Hochschule Hannover Hannover, Low Saxony Germany. ROR: https://ror.org/00f2yqf98 (11) Technische UniversitŠt Braunschweig Braunschweig Germany. ROR: https://ror.org/010nsgg66 (12) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98 (13) Fraunhofer Institute for Toxicology and Experimental Medicine Hannover, Lower Saxony Germany. ROR: https://ror.org/02byjcr11 (14) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98 (15) Leibniz Institute for Immunotherapy and Univ Regensberg Regensburg Germany. (16) UniversitŠtsklinikum WŸrzburg WŸrzburg Germany. ROR: https://ror.org/03pvr2g57 (17) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98 (18) Medizinische Hochschule Hannover Hannover Germany. ROR: https://ror.org/00f2yqf98

    Citation: Cancer Immunol Res 2026 Sep 22 Epub09/22/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42770707

    Tags:

    CD4 T cells convert transient responses to KRAS inhibition to durable remissions in pancreatic cancer Featured  

    (1) Qiang L (2) Hoffman MT (3) Chun JH (4) Parent B (5) Hambitzer F (6) Peprah F (7) Kureshi CTS (8) Lim BS (9) Chang E (10) Walsh MJ (11) Tello JG (12) Atajanova T (13) Shin H (14) Perkins C (15) Kureshi R (16) Molina-Aponte Y (17) Dougan JM (18) Zuo C (19) Brais L (20) Clancy TE (21) Cleary JM (22) Hornick JL (23) Huffman BM (24) Mancias JD (25) Molina G (26) Fairweather M (27) Nowak JA (28) Perez KJ (29) Rubinson DA (30) Slater S (31) van Dams R (32) Wang J (33) Wolpin BM (34) Wong KK (35) Singh H (36) Aguirre AJ (37) Baker D (38) Dougan M (39) Dougan SK

    Cell

    Qiang, Hoffman, Chun, et al. investigated immunotherapy combinations with KRAS inhibition in PDAC models. An IL-21 mimic synergized with a KRAS inhibitor, inducing durable antitumor efficacy. Therapy induced responses from IFNγ-producing CD4+ Th1 cells, decreased Tregs, and stimulated macrophage tumor phagocytosis.

    (1) Qiang L (2) Hoffman MT (3) Chun JH (4) Parent B (5) Hambitzer F (6) Peprah F (7) Kureshi CTS (8) Lim BS (9) Chang E (10) Walsh MJ (11) Tello JG (12) Atajanova T (13) Shin H (14) Perkins C (15) Kureshi R (16) Molina-Aponte Y (17) Dougan JM (18) Zuo C (19) Brais L (20) Clancy TE (21) Cleary JM (22) Hornick JL (23) Huffman BM (24) Mancias JD (25) Molina G (26) Fairweather M (27) Nowak JA (28) Perez KJ (29) Rubinson DA (30) Slater S (31) van Dams R (32) Wang J (33) Wolpin BM (34) Wong KK (35) Singh H (36) Aguirre AJ (37) Baker D (38) Dougan M (39) Dougan SK

    Cell

    Qiang, Hoffman, Chun, et al. investigated immunotherapy combinations with KRAS inhibition in PDAC models. An IL-21 mimic synergized with a KRAS inhibitor, inducing durable antitumor efficacy. Therapy induced responses from IFNγ-producing CD4+ Th1 cells, decreased Tregs, and stimulated macrophage tumor phagocytosis.

    ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is refractory to most therapies, including immunotherapies, for which reinvigoration of CD8 T cells through immune checkpoint blockade is insufficient to induce long-term, durable remissions. Direct KRAS inhibitors (KRASi) have shown clinical promise, although acquired resistance is common. We modeled KRASi response and relapse in mice and demonstrated that, unlike chemotherapy or combinations with checkpoint blockade, an interleukin (IL)-21 cytokine mimic (21h10) induced long-term, durable remissions. Its efficacy depends on T helper 1 (Th1)-polarized CD4 T cells, but not on CD8 T cells or tumor cell expression of major histocompatibility complex class I (MHC class I). Specifically, CD4 T cells primed by type 2 conventional dendritic cells (cDC2s) produce interferon _ (IFN-_), which promotes macrophage-mediated phagocytosis of tumor cells. Ex vivo treatment of human PDAC specimens with 21h10 induces IFN-_ production by infiltrating T cells. Thus, IL-21-elicited CD4 T cells exert antitumor activity in mice and potentially in humans, converting transient responses to KRAS inhibition into durable remissions.

    Author Info: (1) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (2)

    Author Info: (1) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (2) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (3) Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Department of Biochemistry, University of Washington School of Medicine, Seattle, WA 98195, USA. (4) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (5) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (6) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. (7) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (8) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. (9) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (10) Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. (11) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. (12) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. (13) Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Department of Biochemistry, University of Washington School of Medicine, Seattle, WA 98195, USA. (14) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (15) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (16) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (17) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (18) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. (19) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. (20) Department of Surgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (21) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (22) Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (23) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (24) Department of Radiation Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA. (25) Department of Surgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (26) Department of Surgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (27) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (28) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (29) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (30) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (31) Department of Radiation Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA. (32) Department of Surgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. (33) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (34) Laura and Isaac Perlmutter Cancer Center, New York University Langone Medical Center, New York, NY 10016, USA. (35) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (36) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (37) Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Department of Biochemistry, University of Washington School of Medicine, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA. (38) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. (39) Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Immunology, Harvard Medical School, Boston, MA 02115, USA. Electronic address: stephanie_dougan@dfci.harvard.edu.

    Citation: Cell 2026 Sep 23 Epub09/23/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42777708

    Tags:

    Cancers modulate processing and presentation of p53 neoantigens to evade T cell detection Spotlight 

    (1) Haratani K (2) Reinhold B (3) Duke-Cohan JS (4) Fahey CG (5) Tan K (6) Mallis RJ (7) Gusev A (8) Kehl KL (9) Luo J (10) Karmazyn A (11) Holliday EL (12) Masi DJ (13) Zienkiewicz KJ (14) Hennessey CJ (15) Blasco RB (16) Thai TC (17) Gibbons GM (18) Kivlehan S (19) Lizotte P (20) Paweletz CP (21) Aguirre AJ (22) Ligon KL (23) Chiarle R (24) Lang MJ (25) Barbie DA (26) Reinherz EL

    Immunity

    Haratani et al. found that most neoantigens arising from truncal mutations in TP53 were not presented, either because they arose from processing-resistant regions of p53 or because the required HLA allele was absent. Presentable antigens that were immunologically distinct could also be masked in tumors via increased activity of the aminopeptidase ERAP1, which prevented the display of a high-affinity HLA-A*02:01 complex containing a strongly immunogenic 11-mer. Instead, tumors favored the display of low-affinity complexes with a poorly immunogenic 9-mer, resulting in only weak T cell-mediated antitumor immunity, despite high-quality TCRs.

    Contributed by Lauren Hitchings

    (1) Haratani K (2) Reinhold B (3) Duke-Cohan JS (4) Fahey CG (5) Tan K (6) Mallis RJ (7) Gusev A (8) Kehl KL (9) Luo J (10) Karmazyn A (11) Holliday EL (12) Masi DJ (13) Zienkiewicz KJ (14) Hennessey CJ (15) Blasco RB (16) Thai TC (17) Gibbons GM (18) Kivlehan S (19) Lizotte P (20) Paweletz CP (21) Aguirre AJ (22) Ligon KL (23) Chiarle R (24) Lang MJ (25) Barbie DA (26) Reinherz EL

    Immunity

    Haratani et al. found that most neoantigens arising from truncal mutations in TP53 were not presented, either because they arose from processing-resistant regions of p53 or because the required HLA allele was absent. Presentable antigens that were immunologically distinct could also be masked in tumors via increased activity of the aminopeptidase ERAP1, which prevented the display of a high-affinity HLA-A*02:01 complex containing a strongly immunogenic 11-mer. Instead, tumors favored the display of low-affinity complexes with a poorly immunogenic 9-mer, resulting in only weak T cell-mediated antitumor immunity, despite high-quality TCRs.

    Contributed by Lauren Hitchings

    ABSTRACT: TP53 mutations occur early in malignant transformation as truncal events in tumor evolution and are therefore generally present in all descendant tumor cells, creating an immunological vulnerability. Here, we examined the immunogenicity and antigenicity of p53 neoantigens emerging from these truncal mutations. Comprehensive immunopeptidomics revealed that hotspot mutations in human tumors preferentially localize to p53 regions resistant to antigen processing, thereby avoiding display altogether. Moreover, for neoantigens presentable by HLA-A∗02:01 or HLA-B∗07:02 and structurally divergent from corresponding wild-type p53 peptide-HLA complexes, clinical tumors commonly lacked the relevant presenting HLA allele. Tumor cells further resisted T cell killing through increased activity of the aminopeptidase ERAP1, preventing display of high-affinity HLA-A∗02:01 complexes containing an immunogenic p53I195F-derived 11-mer, or by expressing low-affinity HLA-A∗02:01 complexes containing a p53R175H-derived 9-mer with poor antigenicity despite high-quality human TCRs. These findings define mechanisms by which tumors restrict targetable truncal neoantigen display and suggest immunopeptidome shift strategies to circumvent immune escape.

    Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. (2) Department of Medical Oncolo

    Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. (2) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, MA, USA. (3) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, MA, USA. (4) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. (5) Structural Biology Center, X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL 60439, USA. (6) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Dermatology, Harvard Medical School, Boston, MA, USA. (7) Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA. (8) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. (9) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (10) Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA. (11) Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA. (12) Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA. (13) Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA. (14) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (15) Department of Pathology, Boston Children's Hospital, Boston, MA, USA. (16) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (17) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (18) Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, Boston, MA, USA. (19) Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, Boston, MA, USA. (20) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, Boston, MA, USA. (21) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (22) Department of Pathology, Dana-Farber Cancer Institute, Boston, MA, USA. (23) Department of Pathology, Boston Children's Hospital, Boston, MA, USA; Department of Molecular Biotechnology and Health Sciences, University of Torino, 10125 Torino, Italy; Division of Hematopathology, IEO European Institute of Oncology IRCCS, Milan, Italy. (24) Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA. (25) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. Electronic address: david_barbie@dfci.harvard.edu. (26) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. Electronic address: ellis_reinherz@dfci.harvard.edu.

    Citation: Immunity 2026 Sep 17 Epub09/17/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42753739

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