Journal Articles

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) CarriŽ 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

Immunity

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) CarriŽ 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

Immunity

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, ƒcole Normale SupŽrieure de Lyon, UniversitŽ 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

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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

Nature communications

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

Nature communications

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

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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) Pags F (23) Vempalli FR (24) Hendrickx W (25) Masoodi T (26) Ceccarelli M (27) Bedognetti D (28) Galon J

Science translational medicine

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) Pags F (23) Vempalli FR (24) Hendrickx W (25) Masoodi T (26) Ceccarelli M (27) Bedognetti D (28) Galon J

Science translational medicine

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 LabellisŽe 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, 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), UniversitŽ Catholique de Louvain, 1200 Brussels, Belgium. (3) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (4) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (5) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (6) Department of Pathology, Cliniques Universitaires St-Luc and Institut de Recherche Clinique et Experimentale (Pole GAEN) UniversitŽ Catholique de Louvain, 1200 Brussels, Belgium. (7) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (8) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (9) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (10) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (11) UniversitŽ Paris CitŽ, 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (13) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (14) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (15) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (16) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (17) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (18) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. (19) INSERM, Laboratory of Integrative Cancer Immunology, F-75006 Paris, France. Equipe LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. Assistance Publique-H™pitaux 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. Assistance Publique-H™pitaux 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. Assistance Publique-H™pitaux 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, F-75006 Paris, France. Assistance Publique-H™pitaux 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 LabellisŽe Ligue Contre le Cancer, F-75006 Paris, France. Centre de Recherche des Cordeliers, Sorbonne UniversitŽ, UniversitŽ Paris CitŽ, 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

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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

Science

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

Science

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

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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

Nature communications

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

Nature communications

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

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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

Cancer immunology research

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

Cancer immunology research

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

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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

Cell

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

Cell

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

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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

Nature communications

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

Nature communications

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

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Immunoediting restricts clonal neoantigens in primary, treatment-naive human tumors Spotlight 

(1) Borden ES (2) Castellano D (3) Kantzos EA (4) Hughes A (5) Leibovit-Reiben Z (6) Stockard A (7) Choudhary A (8) Ma T (9) Li X (10) Mangold AR (11) Gutenkunst RN (12) LaFleur BJ (13) Buetow KH (14) Wilson MA (15) Hastings KT

Immunity

To investigate immunoediting in human tumors, Borden et al. analyzed primary, treatment-naive cSCC tumors, which frequently arise in immunosuppressed patients following solid organ transplant, suggesting immune involvement. Compared to tumors from immunodeficient patients or just poorly infiltrated tumors, tumors from immunocompetent patients with high infiltration showed lower overall and clonal mutation burdens, and a lower frequency of variant alleles with high predicted neoantigen:MHC-I binding affinity. Further, neoantigens that shared features with validated immunogenic neoantigens were decreased in clonal versus subclonal cancer cells.

Contributed by Lauren Hitchings

(1) Borden ES (2) Castellano D (3) Kantzos EA (4) Hughes A (5) Leibovit-Reiben Z (6) Stockard A (7) Choudhary A (8) Ma T (9) Li X (10) Mangold AR (11) Gutenkunst RN (12) LaFleur BJ (13) Buetow KH (14) Wilson MA (15) Hastings KT

Immunity

To investigate immunoediting in human tumors, Borden et al. analyzed primary, treatment-naive cSCC tumors, which frequently arise in immunosuppressed patients following solid organ transplant, suggesting immune involvement. Compared to tumors from immunodeficient patients or just poorly infiltrated tumors, tumors from immunocompetent patients with high infiltration showed lower overall and clonal mutation burdens, and a lower frequency of variant alleles with high predicted neoantigen:MHC-I binding affinity. Further, neoantigens that shared features with validated immunogenic neoantigens were decreased in clonal versus subclonal cancer cells.

Contributed by Lauren Hitchings

ABSTRACT: T cell targeting of cancer cells alters the tumor antigen landscape in preclinical models. Here, we examined the impact of immunoediting on the antigenic landscape of primary, treatment-naive human tumors. Cutaneous squamous cell carcinoma tumors from immunocompetent and immunosuppressed patients revealed consistent tumor mutational signatures; however, high-immune-infiltrate tumors from immunocompetent patients had lower overall mutational burdens and lower clonal mutational burdens compared with low-infiltrate tumors from immunocompetent patients and tumors from immunosuppressed patients. The lower clonal mutational burden in high-immune-infiltrate tumors from immunocompetent patients persisted after accounting for tumor purity and growth rate. Predicted neoantigen: major histocompatibility complex (MHC) class I binding affinity decreased with increasing variant allele frequency, demonstrating restriction of mutations encoding MHC-binding neoantigens. Neoantigens with features shared with validated immunogenic neoantigens were decreased in clonal relative to subclonal cancer cell populations in high-immune-infiltrate tumors from immunocompetent patients. Thus, the immune system restricts cancer cells expressing immunogenic antigens from clonal populations in primary, treatment-naive human tumors.

Author Info: (1) Department of Dermatology, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ 85004, USA; Phoenix Veterans Affairs Health Care System, Phoenix, AZ 85012, USA. (2)

Author Info: (1) Department of Dermatology, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ 85004, USA; Phoenix Veterans Affairs Health Care System, Phoenix, AZ 85012, USA. (2) Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA. (3) Department of Dermatology, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ 85004, USA. (4) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (5) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (6) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (7) Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Champaign, IL 61801, USA. (8) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (9) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (10) Department of Dermatology, Mayo Clinic Health System, Scottsdale, AZ 85259, USA. (11) Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA. (12) BIO5 Institute, University of Arizona, Tucson, AZ 85719, USA; R. Ken Coit College of Pharmacy, University of Arizona, Tucson, AZ 85724, USA. (13) School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA. (14) School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85281, USA. (15) Department of Dermatology, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ 85004, USA; Phoenix Veterans Affairs Health Care System, Phoenix, AZ 85012, USA; University of Arizona Cancer Center, University of Arizona, Tucson, AZ 85719, USA. Electronic address: khasting@arizona.edu.

Citation: Immunity 2026 Jun 11 Epub06/11/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42276071

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

(1) Jassowicz L (2) Feng F (3) Warta R (4) Heinicke F (5) Wšllner A (6) Briesch H (7) Sor F (8) Soller J (9) Lotsch C (10) Wong JKL (11) Park CG (12) Aubert N (13) Scheer M (14) Hu Z (15) Knoll M (16) Schlegel J (17) Frank L (18) Dao Trong P (19) Jungwirth G (20) Nohman AI (21) Maa§ K (22) Grabe N (23) Barthel M (24) Butz S (25) Lulay C (26) Zucknick M (27) Bortolomeazzi M (28) Sant P (29) Thewes V (30) Michel L (31) Fremd C (32) Schneeweiss A (33) Sun C (34) Rippe K (35) Abdollahi A (36) von Deimling A (37) Unterberg A (38) Krieg SM (39) Mallm JP (40) Lichter P (41) Zapatka M (42) Seiffert M (43) Herold-Mende C

Cancer cell

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

Contributed by Shishir Pant

(1) Jassowicz L (2) Feng F (3) Warta R (4) Heinicke F (5) Wšllner A (6) Briesch H (7) Sor F (8) Soller J (9) Lotsch C (10) Wong JKL (11) Park CG (12) Aubert N (13) Scheer M (14) Hu Z (15) Knoll M (16) Schlegel J (17) Frank L (18) Dao Trong P (19) Jungwirth G (20) Nohman AI (21) Maa§ K (22) Grabe N (23) Barthel M (24) Butz S (25) Lulay C (26) Zucknick M (27) Bortolomeazzi M (28) Sant P (29) Thewes V (30) Michel L (31) Fremd C (32) Schneeweiss A (33) Sun C (34) Rippe K (35) Abdollahi A (36) von Deimling A (37) Unterberg A (38) Krieg SM (39) Mallm JP (40) Lichter P (41) Zapatka M (42) Seiffert M (43) Herold-Mende C

Cancer cell

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

Contributed by Shishir Pant

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

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

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

Citation: Cancer Cell 2026 Jun 8 44:1290-1311.e16 Epub04/27/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42049023

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