Using immunopeptidomics and exome and transcriptome sequencing, Wang et al. analyzed 22 RCC samples and identified HLA-I-presented non-canonical tumor-specific antigens (TSA) derived from human endogenous retroviruses and long non-coding RNAs, with some shared across patients. TSA-reactive T cells in the TIME primarily expressed an exhausted phenotype. T cells expressing TSA-reactive TCRs isolated using scRNA seq mediated tumor cell killing/ regression in vitro in RCC patient-derived tumor-like cell clusters cocultured with autologous peripheral lymphocytes and in mouse xenograft models, particularly combined with anti-PD-1.
Contributed by Paula Hochman
Targeting non-canonical antigens unlocks functional T-cell responses in renal cell carcinoma Spotlight
(1) Wang J (2) Zhu Y (3) He X (4) Yin S (5) He Y (6) Yao P (7) Li J (8) Li X (9) Shi P (10) Qian R (11) Xiao Z (12) Ye X (13) Xi JJ (14) Ye B
Using immunopeptidomics and exome and transcriptome sequencing, Wang et al. analyzed 22 RCC samples and identified HLA-I-presented non-canonical tumor-specific antigens (TSA) derived from human endogenous retroviruses and long non-coding RNAs, with some shared across patients. TSA-reactive T cells in the TIME primarily expressed an exhausted phenotype. T cells expressing TSA-reactive TCRs isolated using scRNA seq mediated tumor cell killing/ regression in vitro in RCC patient-derived tumor-like cell clusters cocultured with autologous peripheral lymphocytes and in mouse xenograft models, particularly combined with anti-PD-1.
Contributed by Paula Hochman
Treg cells promote immunotherapy-induced immune evasion by restraining CD4 T cell control of MHC-I-deficient metastatic pancreatic cancer
Featured(1) Schmiechen ZC (2) Cruz-Hinojoza E (3) Hilk AL (4) Ellefson MA (5) Tsai AK (6) Dres OM (7) Kang LI (8) Geuenich MJ (9) Butler JZ (10) Burrack AL (11) Larsen BM (12) Hickok GH (13) Miller EA (14) Lonetree CL (15) Gaire A (16) Pandey R (17) Nanda HA (18) Chaudhury I (19) Corbiere T (20) Dileepan T (21) Shen SS (22) Campbell KR (23) DeNardo DG (24) Stromnes IM
Schmiechen et al. found that variants of PDA that escaped following PD-L1 blockade showed epigenetic silencing of Tap1 expression, which induced loss of IFNγ-inducible MHC-I and reduced tumor cell killing mediated by CD8+ T cell. Escape variants also had an increased capacity for metastasis, which was promoted by Tregs and their suppressive effect on conventional CD4+ T cells. Combination strategies involving restoring IFNγ-inducible MHC-I, targeting Tregs, and enhancing Tconv enabled more effective cancer immunotherapy, suggesting potentially targetable mechanisms to enhance immunotherapy in PDA.
(1) Schmiechen ZC (2) Cruz-Hinojoza E (3) Hilk AL (4) Ellefson MA (5) Tsai AK (6) Dres OM (7) Kang LI (8) Geuenich MJ (9) Butler JZ (10) Burrack AL (11) Larsen BM (12) Hickok GH (13) Miller EA (14) Lonetree CL (15) Gaire A (16) Pandey R (17) Nanda HA (18) Chaudhury I (19) Corbiere T (20) Dileepan T (21) Shen SS (22) Campbell KR (23) DeNardo DG (24) Stromnes IM
Schmiechen et al. found that variants of PDA that escaped following PD-L1 blockade showed epigenetic silencing of Tap1 expression, which induced loss of IFNγ-inducible MHC-I and reduced tumor cell killing mediated by CD8+ T cell. Escape variants also had an increased capacity for metastasis, which was promoted by Tregs and their suppressive effect on conventional CD4+ T cells. Combination strategies involving restoring IFNγ-inducible MHC-I, targeting Tregs, and enhancing Tconv enabled more effective cancer immunotherapy, suggesting potentially targetable mechanisms to enhance immunotherapy in PDA.
ABSTRACT: Mechanisms driving immunotherapy resistance in pancreatic cancer are poorly defined. We demonstrate that programmed death-ligand 1 immune checkpoint blockade promoted immune evasion by epigenetic Tap1 (transporter associated with antigen processing 1) silencing, increasing selection of metastatic tumor variants with defective interferon-_ (IFN-_)-inducible class I major histocompatibility complex (MHC-I) expression. Unleashing CD4 conventional T cells by regulatory T cell (T(reg) cell) depletion, transfer of tumor-reactive CD4 T cells, or anti-CTLA-4 prevented metastasis. Tumor-specific CD4 T cells adopted a TCF-1(+)SLAMF6(+) progenitor state in lymph nodes and differentiated in tumors. Anti-CTLA-4 increased intratumoral accumulation of CD4 T cells with stemness and tissue residency features, reduced metastasis, and induced gene signatures correlated with improved patient outcomes. MHC-I restoration with anti-CTLA-4 prolonged survival in murine models. In patient tumors, T(reg) cells and CD4 T cells colocalized, and abundance correlated with survival. These findings identify targetable mechanisms of immune evasion and metastasis in immunotherapy-resistant cancer.
Author Info: (1) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapo

Author Info: (1) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (2) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (3) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (4) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (5) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (6) Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA. (7) Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA. (8) Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada. (9) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (10) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (11) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (12) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (13) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (14) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (15) Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, MN, USA. Clinical Translational Science Institute, University of Minnesota Medical School, Minneapolis, MN, USA. (16) Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, MN, USA. Clinical Translational Science Institute, University of Minnesota Medical School, Minneapolis, MN, USA. (17) Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, MN, USA. Clinical Translational Science Institute, University of Minnesota Medical School, Minneapolis, MN, USA. (18) Caris Life Sciences, Phoenix, AZ, USA. (19) Caris Life Sciences, Phoenix, AZ, USA. (20) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (21) Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, MN, USA. Clinical Translational Science Institute, University of Minnesota Medical School, Minneapolis, MN, USA. (22) Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. Division of Oncology, Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada. Ontario Institute for Cancer Research, Toronto, ON, Canada. Vector Institute, Toronto, ON, Canada. (23) Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA. (24) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Masonic Cancer Center, University of Minnesota Medical School, Minneapolis, MN, USA.

Citation: Sci Immunol 2026 Jun 26 11:eadz4302 Epub06/26/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42361199
The transcription factor Eomes drives a stemness program in CD4(+) T cells that promotes anti-tumor immunity in response to immunotherapy Featured
(1) Agesta A (2) Ferrand C (3) Le Dorze AL (4) Peillex C (5) Carri N (6) Barascud R (7) Palak A (8) Esteban L (9) Bernal T (10) Joulia E (11) Colacios C (12) Pereira TM (13) Peroceschi R (14) Pichler A (15) Chaubet A (16) Zahm M (17) Saoudi A (18) El Costa H (19) Adoue V (20) Lu BY (21) Lucca LE (22) Martinet L (23) Dejean AS
Agesta, Ferrand, et al. profiled Th antitumor responses and found that Eomes expression and 4-1BB stimulation resulted in Th subsets essential for antitumor responses. Eomes expression resulted in Th subsets: progenitor subsets that self-renew or differentiate into exhausted Th cells via an intermediate effector exhausted state. These cells expanded, infiltrated tumors, and controlled tumor growth. Further, ICB treatment resulted in expansion of Eomes-expressing Th subsets, which accumulated in the tumor, whereas Eomes deficiency limited infiltration and ICB responses.
(1) Agesta A (2) Ferrand C (3) Le Dorze AL (4) Peillex C (5) Carri N (6) Barascud R (7) Palak A (8) Esteban L (9) Bernal T (10) Joulia E (11) Colacios C (12) Pereira TM (13) Peroceschi R (14) Pichler A (15) Chaubet A (16) Zahm M (17) Saoudi A (18) El Costa H (19) Adoue V (20) Lu BY (21) Lucca LE (22) Martinet L (23) Dejean AS
Agesta, Ferrand, et al. profiled Th antitumor responses and found that Eomes expression and 4-1BB stimulation resulted in Th subsets essential for antitumor responses. Eomes expression resulted in Th subsets: progenitor subsets that self-renew or differentiate into exhausted Th cells via an intermediate effector exhausted state. These cells expanded, infiltrated tumors, and controlled tumor growth. Further, ICB treatment resulted in expansion of Eomes-expressing Th subsets, which accumulated in the tumor, whereas Eomes deficiency limited infiltration and ICB responses.
ABSTRACT: CD4(+) T helper (Th) cells contribute to tumor immunity, yet the subsets and differentiation programs involved remain unclear. Here, we show that the transcription factor Eomesodermin (Eomes) is essential for Th-mediated anti-tumor immunity. Eomes orchestrated the differentiation and maintenance of an exhausted-like Th cell lineage, transcriptionally and functionally distinct from conventional effector or memory Th subsets. This Eomes-dependent program was enhanced by 4-1BB stimulation and promoted effective Th-cell-mediated tumor control. The progenitor subset of this lineage (pTh) expressed stemness-associated transcription factors, displayed self-renewal capacity, and seeded effector subsets capable of controlling tumor growth. At the transcriptional level, Eomes supported the survival, metabolic fitness, and apoptotic resistance of this lineage. Eomes_ pTh cells exhibited conserved transcriptional features in humans across multiple tumor types. As the most expanded Th cell population upon immune checkpoint inhibitor therapy, targeting these cells has potential to improve current immunotherapies.
Author Info: (1) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (2) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (3) University Toulouse, INSERM, CRCT, Toulous

Author Info: (1) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (2) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (3) University Toulouse, INSERM, CRCT, Toulouse, France. (4) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France; ENS, cole Normale Suprieure de Lyon, Universit Claude Bernard - Lyon I, University Lyon, Lyon, France. (5) University Toulouse, INSERM, CRCT, Toulouse, France. (6) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (7) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (8) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (9) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (10) Molecular and Cell Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA. (11) University Toulouse, INSERM, CRCT, Toulouse, France. (12) University Toulouse, INSERM, CRCT, Toulouse, France. (13) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (14) University Toulouse, INSERM, CRCT, Toulouse, France. (15) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (16) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (17) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (18) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (19) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. (20) Department of Medicine (Medical Oncology) and Neurology, Yale School of Medicine, New Haven, CT, USA. (21) University Toulouse, INSERM, CRCT, Toulouse, France. (22) University Toulouse, INSERM, CRCT, Toulouse, France. (23) University Toulouse, INSERM, CNRS, Infinity, Toulouse, France. Electronic address: anne.dejean@inserm.fr.

Citation: Immunity 2026 Jun 24 Epub06/24/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42341755
Tags:
Tumor suppressor genotype influences the extent and mode of immunosurveillance in lung cancer Spotlight
(1) Adler KM (2) Xu H (3) Gladstein AC (4) Irizarry-Negron VM (5) Robertson MR (6) Doerig KR (7) Petrov DA (8) Winslow MM (9) Feldser DM
Using genetically engineered conditional mouse models and lentiviral-mediated somatic gene inactivation, Adler and Xu et al. developed models that allowed them to quantify immunoediting by evaluating fixed neoantigen expression against genotypic tumor backgrounds defined by common driver mutations and different tumor suppressor genes. While genetic features promoting tumor proliferation generally correlated with increased sensitivity to immunosurveillance, different genotypes differentially affected immune cell recruitment, selection of tumor cells with neoantigen silencing, tumor growth, and mechanisms of immune evasion.
Contributed by Lauren Hitchings
(1) Adler KM (2) Xu H (3) Gladstein AC (4) Irizarry-Negron VM (5) Robertson MR (6) Doerig KR (7) Petrov DA (8) Winslow MM (9) Feldser DM
Using genetically engineered conditional mouse models and lentiviral-mediated somatic gene inactivation, Adler and Xu et al. developed models that allowed them to quantify immunoediting by evaluating fixed neoantigen expression against genotypic tumor backgrounds defined by common driver mutations and different tumor suppressor genes. While genetic features promoting tumor proliferation generally correlated with increased sensitivity to immunosurveillance, different genotypes differentially affected immune cell recruitment, selection of tumor cells with neoantigen silencing, tumor growth, and mechanisms of immune evasion.
Contributed by Lauren Hitchings
ABSTRACT: The impact of cancer driving mutations on immunosurveillance throughout tumor development remains poorly understood. To better understand the contribution of tumor genotype to immunosurveillance, we generated and validated lentiviral-based vectors that create increasingly immunogenic neoantigens. This vector system is compatible with autochthonous Cre-regulated cancer models, CRISPR/Cas9-mediated somatic genome editing, and tumor barcoding. Here, we show that in the context of oncogenic KRAS-driven lung cancer and strong neoantigen expression, tumor suppressor genotype dictates the degree of immune cell recruitment, positive selection of tumors with neoantigen silencing, and tumor outgrowth. By quantifying the impact of 11 commonly inactivated tumor suppressor genes on tumor growth across neoantigenic contexts, we show that the growth-promoting effects of tumor suppressor gene inactivation correlate with increasing sensitivity to immunosurveillance. Importantly, some genotypes also dramatically changed sensitivity to immunosurveillance independently of their growth-promoting effects. We propose a model of immunoediting in which tumor suppressor gene inactivation works in tandem with neoantigen expression to shape tumor immunosurveillance and immunoediting such that the same neoantigens uniquely modulate tumor immunoediting depending on the genetic context.
Author Info: (1) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medi

Author Info: (1) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. (2) Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. Department of Biology, Stanford University School of Medicine, Stanford, CA, USA. (3) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. (4) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. (5) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. (6) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. (7) Department of Biology, Stanford University School of Medicine, Stanford, CA, USA. (8) Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. mwinslow@stanford.edu. Department of Biology, Stanford University School of Medicine, Stanford, CA, USA. mwinslow@stanford.edu. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA. mwinslow@stanford.edu. (9) Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. dfeldser@upenn.edu. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. dfeldser@upenn.edu. Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. dfeldser@upenn.edu.

Citation: Nat Commun 2026 Jun 15 Epub06/15/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42297823
Immune microenvironment and noncoding RNA shape early colorectal carcinogenesis in patients with premalignant lesions Spotlight
(1) Morgand E (2) Van den Eynde M (3) Nguyen H (4) Batto AF (5) Mlecnik B (6) Baldin P (7) Majdi A (8) Fredriksen T (9) Lafontaine L (10) Bindea G (11) Mezine F (12) Shararah M (13) Vasaturo A (14) Hijazi A (15) Buttard B (16) Maby P (17) Ramos RN (18) Gragera P (19) Kirilovsky A (20) El Sissy C (21) Marliot F (22) Pags F (23) Vempalli FR (24) Hendrickx W (25) Masoodi T (26) Ceccarelli M (27) Bedognetti D (28) Galon J
Morgand et al. performed a retrospective, longitudinal study characterizing 258 pre-malignant colorectal lesions across discovery and validation cohorts. Patients were stratified based on polyps per year. Sequenced lesions shared few mutations, suggesting their sporadic and independent origin. Patients with the lowest polyp development rates exhibited lesions characterized by high immune cell infiltration and mature TLSs persisting from initial polyp onset to recurrent lesions. Such lesions showed increased expression of non-coding RNAs, which were associated with higher predicted immunogenicity and increased T cell density in tumor centers.
Contributed by Paula Hochman
(1) Morgand E (2) Van den Eynde M (3) Nguyen H (4) Batto AF (5) Mlecnik B (6) Baldin P (7) Majdi A (8) Fredriksen T (9) Lafontaine L (10) Bindea G (11) Mezine F (12) Shararah M (13) Vasaturo A (14) Hijazi A (15) Buttard B (16) Maby P (17) Ramos RN (18) Gragera P (19) Kirilovsky A (20) El Sissy C (21) Marliot F (22) Pags F (23) Vempalli FR (24) Hendrickx W (25) Masoodi T (26) Ceccarelli M (27) Bedognetti D (28) Galon J
Morgand et al. performed a retrospective, longitudinal study characterizing 258 pre-malignant colorectal lesions across discovery and validation cohorts. Patients were stratified based on polyps per year. Sequenced lesions shared few mutations, suggesting their sporadic and independent origin. Patients with the lowest polyp development rates exhibited lesions characterized by high immune cell infiltration and mature TLSs persisting from initial polyp onset to recurrent lesions. Such lesions showed increased expression of non-coding RNAs, which were associated with higher predicted immunogenicity and increased T cell density in tumor centers.
Contributed by Paula Hochman
ABSTRACT: Early cancer detection and prophylactic intervention remain the primary strategies for reducing colorectal carcinoma incidence and mortality. Although the immune microenvironment and tumor-associated antigens have been shown to play a pivotal role in carcinogenesis, the factors shaping immune dynamics during the premalignant phase remain poorly understood. In this study, we performed a comprehensive multimodal characterization of the immune microenvironment in 258 longitudinal premalignant colorectal lesions. Using a discovery cohort of 135 lesions from 26 patients stratified by low versus high polyp development rate, we identified distinct immune states associated with polyp burden. These findings were validated in an independent cohort of 123 lesions from 43 patients. Lesions from patients with low polyp development rates exhibited signatures of robust immune surveillance characterized by enhanced adaptive immune infiltration, including defined T cell subsets, and a higher prevalence of mature tertiary lymphoid structures compared with lesions from patients with high polyp frequency. These immune features were accompanied by increased expression of noncoding RNAs. These transcripts were predicted to encode noncanonical antigens with high MHC-I (major histocompatibility complex class I) binding affinity, potentially increasing lesion immunogenicity. We propose that early carcinogenesis is shaped by the immune microenvironment in association with noncoding RNAs, revealing potential early biomarkers in individuals at high risk of developing colorectal cancer.
Author Info: (1) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers,

Author Info: (1) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (2) Institut Roi Albert II, Department of Medical Oncology Cliniques Universitaires St-Luc and Institut de Recherche Clinique et Experimentale (Pole MIRO), Universit Catholique de Louvain, 1200 Brussels, Belgium. (3) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (4) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (5) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (6) Department of Pathology, Cliniques Universitaires St-Luc and Institut de Recherche Clinique et Experimentale (Pole GAEN) Universit Catholique de Louvain, 1200 Brussels, Belgium. (7) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (8) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (9) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (10) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (11) Universit Paris Cit, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, 75015 Paris, France. (12) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (13) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (14) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (15) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (16) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (17) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (18) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. (19) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. Assistance Publique-Hpitaux de Paris (AP-HP), Immunomonitoring Platform, Laboratory of Immunology, Georges Pompidou European Hospital, 75015 Paris, France. (20) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. Assistance Publique-Hpitaux de Paris (AP-HP), Immunomonitoring Platform, Laboratory of Immunology, Georges Pompidou European Hospital, 75015 Paris, France. (21) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. Assistance Publique-Hpitaux de Paris (AP-HP), Immunomonitoring Platform, Laboratory of Immunology, Georges Pompidou European Hospital, 75015 Paris, France. (22) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France. Assistance Publique-Hpitaux de Paris (AP-HP), Immunomonitoring Platform, Laboratory of Immunology, Georges Pompidou European Hospital, 75015 Paris, France. (23) Sidra Medicine, P.O. Box 26999, Doha, Qatar. (24) Sidra Medicine, P.O. Box 26999, Doha, Qatar. (25) Sidra Medicine, P.O. Box 26999, Doha, Qatar. (26) Sylvester Comprehensive Cancer Center and Department of Public Health Sciences, University of Miami, Miami, FL 33136, USA. (27) Sidra Medicine, P.O. Box 26999, Doha, Qatar. Department of Internal Medicine, University of Genoa, 16132 Genoa, Italy. (28) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe Labellise Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne Universit, Universit Paris Cit, F-75006 Paris, France.

Citation: Sci Transl Med 2026 Jun 10 18:eaed2424 Epub06/10/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42268933
CD4+ T cells impair tumor growth through IL-3 and TNF-dependent vascular damage
Spotlight(1) Lian Q (2) Nie J (3) Singh J (4) Chen Q (5) Matta J (6) Chan W (7) Balmaceno-Criss M (8) Vacchio MS (9) Yu W (10) Clark AD (11) Edmondson E (12) Kelly MC (13) Germain RN (14) Bosselut R
Lian and Nie et al. showed that LCMV gp66-specific CD4+ T cells inhibited tumor growth in an MC38-GP model in an antigen-specific manner, independent of direct lymphoid cell-mediated cytotoxicity. CD4+ T cells initiated antigen-dependent perivascular, myeloid cell-dense structures in the TIME, reprogrammed myeloid transcriptomes, and leveraged recruited myeloid cells to control tumor growth. Single-cell and spatial transcriptomics showed that CD4+ T cell-derived IL-3 programmed macrophages to secrete tumor necrosis factor, which damaged intratumoral vasculature, compromised blood supply, and induced localized tumor cell death and regression.
Contributed by Shishir Pant
(1) Lian Q (2) Nie J (3) Singh J (4) Chen Q (5) Matta J (6) Chan W (7) Balmaceno-Criss M (8) Vacchio MS (9) Yu W (10) Clark AD (11) Edmondson E (12) Kelly MC (13) Germain RN (14) Bosselut R
Lian and Nie et al. showed that LCMV gp66-specific CD4+ T cells inhibited tumor growth in an MC38-GP model in an antigen-specific manner, independent of direct lymphoid cell-mediated cytotoxicity. CD4+ T cells initiated antigen-dependent perivascular, myeloid cell-dense structures in the TIME, reprogrammed myeloid transcriptomes, and leveraged recruited myeloid cells to control tumor growth. Single-cell and spatial transcriptomics showed that CD4+ T cell-derived IL-3 programmed macrophages to secrete tumor necrosis factor, which damaged intratumoral vasculature, compromised blood supply, and induced localized tumor cell death and regression.
Contributed by Shishir Pant
ABSTRACT: Most cancer immunotherapy strategies are focused on direct tumor killing by immune cells, especially T lymphocytes. Clinical and conceptual limitations of these approaches create a need for additional strategies. We identified a tumor stroma-targeting mechanism in which tumor antigen-specific CD4(+) T cells inhibit tumor growth through myeloid cell and tumor necrosis factor (TNF)-dependent vascular damage. Multiplex immunofluorescence and single-cell and tissue transcriptomics showed that CD4(+) T cells trigger the formation of perivascular myeloid cell clusters containing "classically activated" macrophages that produce TNF in response to T cell-derived interleukin-3. TNF causes intratumoral endothelial damage and blood supply disruption, which are associated with localized tumor cell death. Thus, intratumoral antigen-triggered T cell activation can mediate antitumor effects without direct recognition of living tumor cells, thereby avoiding many of the inhibitory mechanisms that limit anti-tumor immunity.
Author Info: (1) Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. (2) La

Author Info: (1) Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. (2) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (3) Single Cell Analysis Facility, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (4) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (5) Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. (6) Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. (7) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (8) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (9) Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. (10) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (11) Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA. (12) Single Cell Analysis Facility, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. (13) Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. (14) Laboratory of Immune Cell Biology and Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Citation: Science 2026 Jun 18 392:eads7910 Epub06/18/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42313973
Tags:
Tumor-resident T cells and dendritic cells form an in situ archetype during immunotherapy response in melanoma Spotlight
(1) Di Pietro A (2) Au L (3) Crock P (4) Thio N (5) Pizzolla A (6) Nguyen TN (7) Macdonald S (8) Chalmers H (9) Zhu R (10) Airaghi A (11) Molden-Hauer T (12) Bacac M (13) Schwalie P (14) Schlenker R (15) Levesque MP (16) Mailer S (17) Barnes-Cullen K (18) Winch K (19) Chan J (20) Yeung GA (21) Spain L (22) Rao AD (23) Sandhu S (24) Gyorki DE (25) McArthur GA (26) Mackay LK (27) Neeson PJ
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
(1) Di Pietro A (2) Au L (3) Crock P (4) Thio N (5) Pizzolla A (6) Nguyen TN (7) Macdonald S (8) Chalmers H (9) Zhu R (10) Airaghi A (11) Molden-Hauer T (12) Bacac M (13) Schwalie P (14) Schlenker R (15) Levesque MP (16) Mailer S (17) Barnes-Cullen K (18) Winch K (19) Chan J (20) Yeung GA (21) Spain L (22) Rao AD (23) Sandhu S (24) Gyorki DE (25) McArthur GA (26) Mackay LK (27) Neeson PJ
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.

Citation: Nat Commun 2026 Jun 11 Epub06/11/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42277002
An ICAM1-targeting chimeric costimulatory receptor mimics the immune synapse and enhances tumor-specific T cell function Spotlight
(1) Min IM (2) Yang Y (3) Stefanova D (4) Vedvyas Y (5) Babu DS (6) Lee DH (7) Alcaina Y (8) Riascos MC (9) Puc J (10) Chen KJ (11) Gonzalez-Valdivieso J (12) Thaiparambil J (13) Bilal M (14) He B (15) Burnett AC (16) Zarnegar R (17) Fahey TJ (18) Jin MM
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
(1) Min IM (2) Yang Y (3) Stefanova D (4) Vedvyas Y (5) Babu DS (6) Lee DH (7) Alcaina Y (8) Riascos MC (9) Puc J (10) Chen KJ (11) Gonzalez-Valdivieso J (12) Thaiparambil J (13) Bilal M (14) He B (15) Burnett AC (16) Zarnegar R (17) Fahey TJ (18) Jin MM
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

Citation: Cancer Immunol Res 2026 Apr 27 Epub04/27/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42043451
Cuproptosis-immunity crosstalk informs strategy to overcome immunotherapy resistance Spotlight
(1) Lei G (2) Lu Z (3) Xu Z (4) Braun C (5) Huo D (6) Gao J (7) Tan L (8) Hong T (9) Wu S (10) Sun M (11) Zhao X (12) Li Q (13) Chen X (14) Yan Y (15) Lee H (16) Mao C (17) Zhuang L (18) Ku LT (19) Puebla N (20) Barsoumian H (21) Yao J (22) Hong L (23) Zhang J (24) Tran H (25) Lee JJ (26) Gibbons D (27) Vaporciyan A (28) Heymach J (29) Lin C (30) Gottlieb E (31) You MJ (32) Welsh JW (33) Lin SH (34) Zang X (35) Li Z (36) Gan B
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
(1) Lei G (2) Lu Z (3) Xu Z (4) Braun C (5) Huo D (6) Gao J (7) Tan L (8) Hong T (9) Wu S (10) Sun M (11) Zhao X (12) Li Q (13) Chen X (14) Yan Y (15) Lee H (16) Mao C (17) Zhuang L (18) Ku LT (19) Puebla N (20) Barsoumian H (21) Yao J (22) Hong L (23) Zhang J (24) Tran H (25) Lee JJ (26) Gibbons D (27) Vaporciyan A (28) Heymach J (29) Lin C (30) Gottlieb E (31) You MJ (32) Welsh JW (33) Lin SH (34) Zang X (35) Li Z (36) Gan B
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.

Citation: Cell 2026 Jun 22 Epub06/22/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42330950
Integration of donor microbiota following FMT correlates with anti-PD-1 response in melanoma Spotlight
(1) Fessler JL (2) Olm MR (3) Engleman EG (4) Sonnenburg JL
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
(1) Fessler JL (2) Olm MR (3) Engleman EG (4) Sonnenburg JL
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.

Citation: Nat Commun 2026 May 30 Epub05/30/2026
Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42218119
