Journal Articles

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

(1) Pei S (2) Pan Y (3) Liang H (4) Lei L (5) Lin Q (6) Mi J (7) Ravetch JV (8) Soehnlein O (9) Karlsson MCI

Immunity

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

(1) Pei S (2) Pan Y (3) Liang H (4) Lei L (5) Lin Q (6) Mi J (7) Ravetch JV (8) Soehnlein O (9) Karlsson MCI

Immunity

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

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

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

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

Citation: Immunity 2026 Jun 15 Epub06/15/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42296966

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Tumor transcriptional state predicts survival in immune-checkpoint-blockade-treated glioblastoma Spotlight 

(1) Ghannam JY (2) Bryan J (3) Weiss J (4) Kovarsky D (5) Merrell D (6) Messer C (7) Schlueter-Kuck K (8) Fell GG (9) Lim-Fat MJ (10) Youssef G (11) Rahman R (12) Qin L (13) Young GS (14) Janes JT 3rd (15) Van Orden M (16) Pfaff KL (17) Gans A (18) Lin ES (19) Huang RY (20) Danysh BP (21) Parida L (22) Li S (23) Wen PY (24) Chiocca EA (25) Neuberg D (26) Ligon KL (27) Tirosh I (28) Reardon DA (29) Getz G (30) Wu CJ

Nature cancer

Using bulk DNA/RNA sequencing and single-nucleus RNAseq, Ghannam et al. profiled 181 ICB-treated glioblastomas, benchmarking against standard-of-care cohorts, to define genomic correlates of ICB response. At baseline, an mesenchymal (MES) transcriptional subtype with high HLA class I expression and increased T cell infiltration was predictive of improved survival after ICB, but not chemoradiation, whereas non-MES-linked lesions were associated with worse ICB outcomes. TMB was not predictive of outcomes, and a longitudinal analysis showed ICB selected for subclones with non-MES features as a trajectory of acquired ICB resistance in GBM.

Contributed by Shishir Pant

(1) Ghannam JY (2) Bryan J (3) Weiss J (4) Kovarsky D (5) Merrell D (6) Messer C (7) Schlueter-Kuck K (8) Fell GG (9) Lim-Fat MJ (10) Youssef G (11) Rahman R (12) Qin L (13) Young GS (14) Janes JT 3rd (15) Van Orden M (16) Pfaff KL (17) Gans A (18) Lin ES (19) Huang RY (20) Danysh BP (21) Parida L (22) Li S (23) Wen PY (24) Chiocca EA (25) Neuberg D (26) Ligon KL (27) Tirosh I (28) Reardon DA (29) Getz G (30) Wu CJ

Nature cancer

Using bulk DNA/RNA sequencing and single-nucleus RNAseq, Ghannam et al. profiled 181 ICB-treated glioblastomas, benchmarking against standard-of-care cohorts, to define genomic correlates of ICB response. At baseline, an mesenchymal (MES) transcriptional subtype with high HLA class I expression and increased T cell infiltration was predictive of improved survival after ICB, but not chemoradiation, whereas non-MES-linked lesions were associated with worse ICB outcomes. TMB was not predictive of outcomes, and a longitudinal analysis showed ICB selected for subclones with non-MES features as a trajectory of acquired ICB resistance in GBM.

Contributed by Shishir Pant

ABSTRACT: The determinants of immune checkpoint blockade (ICB) response in glioblastoma (GBM) with wild-type isocitrate dehydrogenase remain poorly understood. Here we profiled 181 ICB-treated GBM cases using bulk DNA sequencing, bulk RNA sequencing and single-nucleus RNA sequencing to investigate the genomic features associated with ICB outcomes. Baseline tumor transcriptional subtype was predictive of overall survival following ICB, with mesenchymal (MES) GBM associated with improved outcomes to ICB but not standard chemoradiation. Non-MES-associated genetic lesions, including those in PDGFRA and CDKN2A, were associated with worse survival following ICB but not standard therapy. Tumor mutational burden was not predictive of outcomes. Survival was associated with pre-ICB enrichment for MES-like malignant cells, marked by high human leukocyte antigen class I expression and greater T cell infiltration. Paired tumor analyses linked ICB exposure to outgrowth of subclones harboring lesions associated with non-MES subtypes, supporting MES-to-non-MES transition as a common trajectory of acquired resistance to ICB, distinct from standard chemoradiation.

Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Harvard Medical School, Boston, MA, USA. Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Author Info: (1) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Harvard Medical School, Boston, MA, USA. Broad Institute of MIT and Harvard, Cambridge, MA, USA. Harvard/MIT MD-PhD Program and Harvard Immunology PhD Program, Harvard Medical School, Boston, MA, USA. (2) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Harvard Medical School, Boston, MA, USA. Broad Institute of MIT and Harvard, Cambridge, MA, USA. Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Molecular Diagnostics Laboratory, Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (3) Broad Institute of MIT and Harvard, Cambridge, MA, USA. (4) Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel. (5) Broad Institute of MIT and Harvard, Cambridge, MA, USA. (6) Broad Institute of MIT and Harvard, Cambridge, MA, USA. (7) Broad Institute of MIT and Harvard, Cambridge, MA, USA. (8) Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. (9) Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada. (10) Harvard Medical School, Boston, MA, USA. Center for Neuro-Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (11) Department of Radiation Oncology, Brigham and Women's Hospital, Boston, MA, USA. (12) Department of Imaging, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, USA. (13) Departments of Radiology, Mass General Brigham, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, USA. (14) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA. (15) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA. (16) Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (17) Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (18) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (19) Departments of Radiology, Mass General Brigham, Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, USA. (20) Broad Institute of MIT and Harvard, Cambridge, MA, USA. (21) IBM Research, Yorktown Heights, NY, USA. (22) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Broad Institute of MIT and Harvard, Cambridge, MA, USA. Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA. (23) Center for Neuro-Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (24) Center for Tumors of the Nervous System, Mass General Brigham Cancer Institute & Department of Neurosurgery, Mass General Brigham, Boston, MA, USA. (25) Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. (26) Broad Institute of MIT and Harvard, Cambridge, MA, USA. Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Department of Pathology, Dana-Farber Cancer Institute, Boston, MA, USA. (27) Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel. (28) Center for Neuro-Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. (29) Harvard Medical School, Boston, MA, USA. Broad Institute of MIT and Harvard, Cambridge, MA, USA. Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA, USA. (30) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. catherine_wu@dfci.harvard.edu. Harvard Medical School, Boston, MA, USA. catherine_wu@dfci.harvard.edu. Broad Institute of MIT and Harvard, Cambridge, MA, USA. catherine_wu@dfci.harvard.edu.

Citation: Nat Cancer 2026 Jun 3 Epub06/03/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42237038

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Explainable machine learning-guided integrated multiomics analysis reveals macrophage-driven immune suppression in breast cancer Spotlight 

(1) Azimzade Y (2) Haugen MH (3) Kristensen VN (4) Frigessi A (5) Köhn-Luque A

Nature communications

Azimazade et al. developed an explainable machine learning (XML) pipeline to study associations between clinical outcomes and in silico estimated cell types within the TIME of over 5,000 METABRIC and TCGA samples from patients with breast cancer. In estrogen receptor-positive samples, macrophages correlated positively with pathological complete responses after neoadjuvant chemotherapy, but negatively with relapse-free survival. Imaging mass cytometry and scRNAseq data demonstrated that HLA-ABC+ macrophages accumulated in the vicinity of HLA-ABChi epithelial cells and were associated with Tregs and TEX cells.

Contributed by Ute Burkhardt

(1) Azimzade Y (2) Haugen MH (3) Kristensen VN (4) Frigessi A (5) Köhn-Luque A

Nature communications

Azimazade et al. developed an explainable machine learning (XML) pipeline to study associations between clinical outcomes and in silico estimated cell types within the TIME of over 5,000 METABRIC and TCGA samples from patients with breast cancer. In estrogen receptor-positive samples, macrophages correlated positively with pathological complete responses after neoadjuvant chemotherapy, but negatively with relapse-free survival. Imaging mass cytometry and scRNAseq data demonstrated that HLA-ABC+ macrophages accumulated in the vicinity of HLA-ABChi epithelial cells and were associated with Tregs and TEX cells.

Contributed by Ute Burkhardt

Despite thorough characterizations of cellular compositions within the breast tumor microenvironment (TME), their implications for disease progression and patient prognosis remain poorly understood. Unraveling these effects is vital for identifying potential targets to improve treatment outcomes. In this study, we devise an explainable machine learning (XML) pipeline to scrutinize the associations between TME cellular constituents and relapse-free survival (RFS). By applying this pipeline to estimated cell fractions in the METABRIC and TCGA datasets and comparing these results with associations to pathological complete response (pCR) after neoadjuvant chemotherapy (NAC), we create a comprehensive catalog of the TME's role based on 5000 patient samples. Our findings reveal an unexpected dichotomy in which macrophages correlate positively with pCR but negatively with RFS, particularly within estrogen receptor-positive (ER+) and Luminal A and B (LumA/B) cancer subtypes. We show that this pattern is driven by heterogeneity in breast tumors characterized by increasing levels of macrophage infiltration. Through imaging mass cytometry (IMC) data analysis, we find that macrophages tend to accumulate in the vicinity of HLA-ABC(hi) epithelial cells as their frequency increases in tumor tissues and that they also express elevated levels of HLA-ABC protein. In both IMC and single-cell RNA sequencing (scRNA-seq) data, we uncover a significant association between these HLA-ABC(hi) macrophages and regulatory and exhausted T cells (TReg and TEx), suggesting their involvement in immune suppression, likely by creating a chronically activated immunosuppressive TME. Subsequent cell-cell communication analysis predicts interactions between HLA-ABC(hi) macrophages and TEx cells via the ligands SIGLEC9, ALCAM, and CSF1, and with TReg cells through APP, ANGPTL4, and SIGLEC9 signaling. Considering the clinical relevance of macrophages in ER+ (LumA/B) subtypes, this work enhances the characterization of macrophage-associated immune suppression in these tumors and identifies potential targets for immunomodulatory strategies.

Author Info: (1) Oslo Center for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway. younessazimzade@gmail.com. (2) Department of Tumor Biology, Institute for Cancer Research, Div

Author Info: (1) Oslo Center for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway. younessazimzade@gmail.com. (2) Department of Tumor Biology, Institute for Cancer Research, Division of Cancer Medicine, Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway. (3) Department of Medical Genetics, Oslo University Hospital, University of Oslo, Oslo, Norway. (4) Oslo Center for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway. arnoldo.frigessi@medisin.uio.no. Oslo Center for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway. arnoldo.frigessi@medisin.uio.no. (5) Oslo Center for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway. a.k.luque@medisin.uio.no. Oslo Center for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway. a.k.luque@medisin.uio.no.

Citation: Nat Commun 2026 May 25 Epub05/25/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42185288

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Targeting CCR1 remodels the tumor microenvironment and relieves immune suppression in pancreatic cancer Featured  

(1) Zhang Y (2) Kadiyala P (3) Yan W (4) Brown K (5) Avritt FR (6) Donahue KL (7) Procario MC (8) Okoye JO (9) Giridharan T (10) Elhossiny AM (11) Espinoza CE (12) Awad D (13) Lasse Opsahl EL (14) Medina-Cabrera PI (15) Velez-Delgado A (16) Menjivar RE (17) Yang OA (18) Yang S (19) He X (20) Gupta S (21) Tariq R (22) Brandt AR (23) Wang X (24) denDekker A (25) Nwosu ZC (26) Carpenter ES (27) Courtney AH (28) Bednar F (29) Frankel TL (30) Lyssiotis CA (31) Zheng B (32) Kryczek I (33) Pasca di Magliano M

Cancer immunology research

Evaluating the role of CCR1 in pancreatic cancer, Zhang et al. used KC and KPC mouse tumor models, and found while elimination of CCR1 did not limit tumor formation, it delayed progression of active disease, resulting in prolonged survival. CCR1 was mainly expressed by macrophages and granulocytes, but its deletion induced TIME remodeling that affected fibroblasts and increased CD8+ T cell accumulation, but not activation. CCR1 inhibition showed synergy in combination with targeting of other immunosuppressive mechanisms, though there was still room to improve antitumor efficacy in this highly resistant tumor setting.

(1) Zhang Y (2) Kadiyala P (3) Yan W (4) Brown K (5) Avritt FR (6) Donahue KL (7) Procario MC (8) Okoye JO (9) Giridharan T (10) Elhossiny AM (11) Espinoza CE (12) Awad D (13) Lasse Opsahl EL (14) Medina-Cabrera PI (15) Velez-Delgado A (16) Menjivar RE (17) Yang OA (18) Yang S (19) He X (20) Gupta S (21) Tariq R (22) Brandt AR (23) Wang X (24) denDekker A (25) Nwosu ZC (26) Carpenter ES (27) Courtney AH (28) Bednar F (29) Frankel TL (30) Lyssiotis CA (31) Zheng B (32) Kryczek I (33) Pasca di Magliano M

Cancer immunology research

Evaluating the role of CCR1 in pancreatic cancer, Zhang et al. used KC and KPC mouse tumor models, and found while elimination of CCR1 did not limit tumor formation, it delayed progression of active disease, resulting in prolonged survival. CCR1 was mainly expressed by macrophages and granulocytes, but its deletion induced TIME remodeling that affected fibroblasts and increased CD8+ T cell accumulation, but not activation. CCR1 inhibition showed synergy in combination with targeting of other immunosuppressive mechanisms, though there was still room to improve antitumor efficacy in this highly resistant tumor setting.

ABSTRACT: A hallmark of pancreatic cancer is an extensive fibroinflammatory stroma. Myeloid cells, including abundant macrophages, are a prevalent cellular component of the pancreatic cancer microenvironment and a key driver of immunosuppression. Identifying mechanisms of myeloid-cell driven immunosuppression is thus key to developing therapeutic approaches. Harnessing single-cell RNA sequencing data from human and murine tumors, we determined that tumor infiltrating myeloid cells (including macrophages and granulocytes) have elevated expression of C-C motif chemokine receptor 1 (CCR1). To determine the functional role of CCR1, we generated oncogenic KRAS based genetically engineered mouse models of pancreatic cancer, with or without addition of a mutant form of the tumor suppressor Trp53 (KC and KPC, respectively), lacking CCR1 expression. CCR1 inactivation did not affect formation of early lesions, but delayed progression to cancer and resulted in prolonged survival. In these mice, macrophages lacking CCR1 had reduced expression of the immunosuppressive marker Arginase 1. Loss of CCR1 also profoundly shifted the prevalent fibroblast population, inducing a pancreatic stellate cell-like phenotype. In two independent syngeneic orthotopic models, ablation or pharmacologic inhibition of CCR1 reduced tumor growth and increased CD8+ T cell cytotoxic activity, sensitizing tumors to immunotherapy. Our data show that CCR1-expressing myeloid cells promote pancreatic cancer growth through modulation of the immune microenvironment and fibroblasts, indicating that CCR1 might be a suitable target for combination therapy.

Author Info: (1) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (2) University of Michigan-Ann Arbor Ann Arbor, MI United States. (3) University of

Author Info: (1) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (2) University of Michigan-Ann Arbor Ann Arbor, MI United States. (3) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (4) University of Michigan Medical Schooligan United States. (5) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (6) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (7) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (8) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (9) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (10) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (11) University of Michigan-Ann Arbor Ann Arbor United States. ROR: https://ror.org/00jmfr291 (12) University of Michigan-Ann Arbor United States. ROR: https://ror.org/00jmfr291 (13) University of Maryland, Baltimore Baltimore United States. ROR: https://ror.org/04rq5mt64 (14) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (15) University of Michigan-Ann Arbor Ann Arbor United States. ROR: https://ror.org/00jmfr291 (16) University of Michigan-Ann Arbor United States. ROR: https://ror.org/00jmfr291 (17) University of Michigan-Ann Arbor United States. ROR: https://ror.org/00jmfr291 (18) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (19) University of Michigan-Ann Arbor United States. ROR: https://ror.org/00jmfr291 (20) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (21) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (22) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (23) University of Michigan-Ann Arbor Ann Arbor United States. ROR: https://ror.org/00jmfr291 (24) University of Michigan-Ann Arbor United States. ROR: https://ror.org/00jmfr291 (25) Cornell University Ithaca United States. ROR: https://ror.org/05bnh6r87 (26) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (27) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (28) University of Michigan-Ann Arbor Ann Arbor, Michigan United States. ROR: https://ror.org/00jmfr291 (29) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (30) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (31) Cedars-Sinai Medical Center Los Angeles, CA United States. ROR: https://ror.org/02pammg90 (32) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291 (33) University of Michigan-Ann Arbor Ann Arbor, MI United States. ROR: https://ror.org/00jmfr291

Citation: Cancer Immunol Res 2026 May 28 Epub05/28/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42207977

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Targeting tumor-intrinsic STK40 induces immune vulnerability and drives T cell reinvigoration Spotlight 

(1) Zhu L (2) Zhang S (3) Li B (4) Liu X (5) Yang C (6) Tang X (7) Chai J (8) Yang X (9) Yu C (10) Liao H (11) Cao Z (12) Liao L (13) Wang W (14) Yuan S (15) Gao Q (16) Sun C (17) Bernards R (18) Yang Y (19) Qin W (20) Wang C

Cancer cell

Using in vivo CRISPR screens, Zhu et al. identified serine/threonine kinase 40 (STK40) as a novel regulator of immune evasion in hepatocellular carcinoma (HCC). Stk40 loss disrupted COP1-mediated IFNGR1 degradation, stabilized IFNGR1, restored tumor-intrinsic IFNγ signaling, and sensitized HCC cells to CD8+ T cell-mediated killing. Stk40 deficiency simultaneously induced tumor-derived GM-CSF, enhancing cDC1 infiltration, antigen cross-presentation, and CD8+ T cell activation. LNP-siRNA-mediated STK40 targeting synergized with PD-1 blockade in suppressing tumor growth in multiple cancer models.

Contributed by Shishir Pant

(1) Zhu L (2) Zhang S (3) Li B (4) Liu X (5) Yang C (6) Tang X (7) Chai J (8) Yang X (9) Yu C (10) Liao H (11) Cao Z (12) Liao L (13) Wang W (14) Yuan S (15) Gao Q (16) Sun C (17) Bernards R (18) Yang Y (19) Qin W (20) Wang C

Cancer cell

Using in vivo CRISPR screens, Zhu et al. identified serine/threonine kinase 40 (STK40) as a novel regulator of immune evasion in hepatocellular carcinoma (HCC). Stk40 loss disrupted COP1-mediated IFNGR1 degradation, stabilized IFNGR1, restored tumor-intrinsic IFNγ signaling, and sensitized HCC cells to CD8+ T cell-mediated killing. Stk40 deficiency simultaneously induced tumor-derived GM-CSF, enhancing cDC1 infiltration, antigen cross-presentation, and CD8+ T cell activation. LNP-siRNA-mediated STK40 targeting synergized with PD-1 blockade in suppressing tumor growth in multiple cancer models.

Contributed by Shishir Pant

ABSTRACT: Immunotherapy has revolutionized cancer treatment, yet its efficacy in hepatocellular carcinoma (HCC) remains limited and the mechanisms of resistance are poorly defined. Using in vivo CRISPR-Cas9 screens, we identify serine/threonine kinase 40 (STK40) as a previously unrecognized regulator of immune evasion. Stk40 ablation synergizes with PD-1 blockade to induce tumor regression. Hepatocyte-specific Stk40 deletion abolishes tumorigenesis in hydrodynamic plasmid-driven HCC models. Mechanistically, STK40 scaffolds the COP1 ubiquitin ligase to promote interferon gamma receptor 1 (IFNGR1) degradation. Genetic depletion of Stk40 stabilizes IFNGR1, restoring tumor cell sensitivity to T cell cytotoxicity. Concurrently, Stk40 loss triggers autonomous GM-CSF secretion, enhancing the infiltration and activation of conventional type 1 dendritic cells, which promotes antigen cross-presentation and CD8(+) T cell activation. Pharmacological inhibition of STK40 using LNP-siRNA, combined with PD-1 blockade, elicits potent anti-tumor responses across multiple cancer types. These findings establish STK40 as a dual-action therapeutic target to overcome resistance to anti-tumor immunity.

Author Info: (1) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine,

Author Info: (1) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (2) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (3) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Immune Therapy Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (4) Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (5) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (6) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (7) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (8) Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China. (9) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (10) Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (11) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (12) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (13) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. (14) The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China. (15) Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China. (16) German Cancer Research Center, Division Immune Regulation in Cancer, Heidelberg, Germany. (17) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Division of Molecular Carcinogenesis, Oncode Institute, the Netherlands Cancer Institute, Amsterdam, the Netherlands. Electronic address: r.bernards@nki.nl. (18) Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address: yuyang@shsmu.edu.cn. (19) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address: wxqin@sjtu.edu.cn. (20) State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address: cwang@shsci.org.

Citation: Cancer Cell 2026 May 28 Epub05/28/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42208540

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Immune-remodeling mRNAs expressing IRF8 or NIK generate durable antitumor immunity in multiple cancer models Spotlight 

(1) Gupta A (2) Das R (3) Reed K (4) Jeon T (5) Nguyen QTC (6) Rudra A (7) Ge X (8) Trongjit S (9) Vanrobaeys YS (10) Langer R (11) Weissleder R (12) Garris C (13) Anderson DG

Nature biotechnology

In mice, i.t. or i.v. delivery of CKK-E12-LNPs loaded with immune-remodeling mRNAs (IR-mRNAs) encoding NF-κB-inducing kinase (NIK) or IFN regulatory factor 8 (IRF8) induced (1) APC activation and maturation into cDC1s, (2) a release of immunostimulatory cytokines, (3) accumulation of NKT and γδT cells in tumors, and (4) priming of antitumor CD8+ T cells, which infiltrated and eliminated tumors and protected mice from rechallenge. In combination with mRNA encoding OVA, IR-mRNA prevented growth of OVA+ tumors. IR-mRNAs also synergized with anti-PD-1, and enhanced humoral and adaptive immune responses to infectious disease antigens.

Contributed by Lauren Hitchings

(1) Gupta A (2) Das R (3) Reed K (4) Jeon T (5) Nguyen QTC (6) Rudra A (7) Ge X (8) Trongjit S (9) Vanrobaeys YS (10) Langer R (11) Weissleder R (12) Garris C (13) Anderson DG

Nature biotechnology

In mice, i.t. or i.v. delivery of CKK-E12-LNPs loaded with immune-remodeling mRNAs (IR-mRNAs) encoding NF-κB-inducing kinase (NIK) or IFN regulatory factor 8 (IRF8) induced (1) APC activation and maturation into cDC1s, (2) a release of immunostimulatory cytokines, (3) accumulation of NKT and γδT cells in tumors, and (4) priming of antitumor CD8+ T cells, which infiltrated and eliminated tumors and protected mice from rechallenge. In combination with mRNA encoding OVA, IR-mRNA prevented growth of OVA+ tumors. IR-mRNAs also synergized with anti-PD-1, and enhanced humoral and adaptive immune responses to infectious disease antigens.

Contributed by Lauren Hitchings

ABSTRACT: Although immunotherapy has benefited a subset of persons with cancer, its broader efficacy remains limited, primarily because of an immunosuppressive tumor microenvironment characterized by insufficient numbers of functional tumor-specific T cells, antigen-presenting cells (APCs) and tumor-infiltrating lymphocytes. Here we engineer immune cells in the tumor microenvironment using lipid nanoparticles (LNPs) to deliver immune-remodeling mRNAs (IR-mRNAs) encoding NF-κB-inducing kinase or interferon regulatory factor 8. These IR-mRNAs activate APCs in tumors, significantly increasing activated type 1 conventional dendritic cells, immunostimulatory cytokines and priming antitumor CD8+ T cells. IR-mRNAs encapsulated in LNPs elicited durable antitumor responses in multiple syngeneic mouse tumor models through both intratumoral and intravenous delivery. Coadministration of IR-mRNA and ovalbumin mRNA elicited a ~10-fold increase in antigen-specific CD8+ T cell responses, sustained long-term memory and effectively prevented tumor growth in vaccinated mice. Additionally, coadministration of IR-mRNA and hemagglutinin mRNA enhanced the humoral response ~5-fold and the cellular response ~15-fold, underscoring their potential as adjuvants for boosting adaptive immunity.

Author Info: (1) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute

Author Info: (1) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (2) Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA. (3) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (4) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (5) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (6) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, MA, USA. (7) Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA. (8) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (9) Bioinformatics & Computing Core Facility of the Swanson Biotechnology Center, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. (10) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. (11) Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA. Department of Systems Biology, Harvard Medical School, Boston, MA, USA. Department of Radiology, Massachusetts General Brigham, Boston, MA, USA. (12) Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA. cgarris@mgh.harvard.edu. Department of Pathology, Massachusetts General Hospital, Boston, MA, USA. cgarris@mgh.harvard.edu. (13) David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. dgander@mit.edu. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. dgander@mit.edu.

Citation: Nat Biotechnol 2026 May 13 Epub05/13/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42129506

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Differential assembly of mouse and human tumor microenvironments Spotlight 

(1) Courau T (2) Jaszczak RG (3) Samad B (4) Flynn E (5) Chew NW (6) Reeder GC (7) Tsui J (8) Teklu S (9) Pass LF (10) Edwards AW (11) Naser M (12) Ray A (13) Wismer H (14) Bunis D (15) Lupin-Jimenez L (16) Gavil NV (17) Masopust D (18) Graham JP (19) Skelly DA (20) Vesco X (21) Liu ET (22) Fragiadakis GK (23) Combes AJ (24) Krummel MF

Nature immunology

Courau et al. profiled immune landscapes of 15 common mouse tumor models alongside human datasets. Most murine TIMEs resembled a minority subset of macrophage-rich, poorly infiltrated human tumors. Cross-species analysis showed species-specific biases in chemokine networks (including reduced CCR2/CCR5 and altered CXCL13 in mice) and altered T and myeloid cell frequencies, while conserved cell-type specific gene expression programs emerged as discriminatory. An IFN-responsive myeloid–CD8+ T cell cytotoxicity module was conserved across tumor types, and predicted clinical outcome in humans.

Contributed by Shishir Pant

(1) Courau T (2) Jaszczak RG (3) Samad B (4) Flynn E (5) Chew NW (6) Reeder GC (7) Tsui J (8) Teklu S (9) Pass LF (10) Edwards AW (11) Naser M (12) Ray A (13) Wismer H (14) Bunis D (15) Lupin-Jimenez L (16) Gavil NV (17) Masopust D (18) Graham JP (19) Skelly DA (20) Vesco X (21) Liu ET (22) Fragiadakis GK (23) Combes AJ (24) Krummel MF

Nature immunology

Courau et al. profiled immune landscapes of 15 common mouse tumor models alongside human datasets. Most murine TIMEs resembled a minority subset of macrophage-rich, poorly infiltrated human tumors. Cross-species analysis showed species-specific biases in chemokine networks (including reduced CCR2/CCR5 and altered CXCL13 in mice) and altered T and myeloid cell frequencies, while conserved cell-type specific gene expression programs emerged as discriminatory. An IFN-responsive myeloid–CD8+ T cell cytotoxicity module was conserved across tumor types, and predicted clinical outcome in humans.

Contributed by Shishir Pant

ABSTRACT: Mouse models are frequently used to develop treatments for human cancer. However, the degree to which their tumor microenvironments (TMEs) are synonymously assembled is particularly poorly characterized. Through systematic immunoprofiling of 15 commonly used mouse models, we found that most murine TMEs recapitulate the composition of poorly infiltrated human tumors, extensively biased toward high macrophage densities. We discovered substantial species-specific biases of chemokine expression networks known to drive TMEs assembly, together with discoordinated frequencies of T and myeloid cell subtypes. Even with variable alignment, conserved cell-type-specific gene expression programs emerged across species and cohorts. Dissecting the coordinated T cell-myeloid gene expression programs revealed a conserved axis between interferon-responsive myeloid states and ongoing T cell cytotoxicity that transcends tissue of origin and predicts clinical outcome. Collectively, this work provides a practical atlas outlining both the hazards and opportunities of using mice to model human cancer.

Author Info: (1) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. tristan.courau@u

Author Info: (1) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. CoLabs, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. (2) CoLabs, UCSF, San Francisco, CA, USA. (3) ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (4) CoLabs, UCSF, San Francisco, CA, USA. (5) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (6) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (7) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (8) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (9) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (10) CoLabs, UCSF, San Francisco, CA, USA. (11) CoLabs, UCSF, San Francisco, CA, USA. (12) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (13) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (14) CoLabs, UCSF, San Francisco, CA, USA. (15) CoLabs, UCSF, San Francisco, CA, USA. (16) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (17) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (18) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (19) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (20) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (21) The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. (22) CoLabs, UCSF, San Francisco, CA, USA. Department of Medicine, Division of Rheumatology, UCSF, San Francisco, CA, USA. (23) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. Department of Medicine, Division of Gastroenterology, UCSF, San Francisco, CA, USA. (24) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. max.krummel@ucsf.edu. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. max.krummel@ucsf.edu.

Citation: Nat Immunol 2026 May 19 Epub05/19/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42156893

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Loss of the autoimmune risk gene TREX1 reveals a convergence of mechanisms promoting immune tolerance loss and antitumor immunity Spotlight 

Junghyun Lim 1, Katherine Williams 1, Stephanie Mittman 1, Patricia Pacheco Sanchez 1, Ryan Rodriguez 1, Annie Ogasawara 1, Grace Barnett 1, Mayra Cruz Tleugabulova 1, Barzin Y Nabet 1, Jeffrey Hung 1, Kevin A Marroquin 1, Shari Lau 1, Serena Y Lee 1, Paul Tyler 1, Elizabeth T Carbone 1, Bridget Hough 1, Janice Corpuz 1, Haruka Murota 1, Edward Dere 1, Smadar Shiffman 1, Leah K Schutt 1, Herman Gill 1, Julia Lau 1, Marco De Simone 1, Lucinda Tam 1, Merone Roose-Girma 1, Søren Warming 1, Soyoung A Oh 1, Sascha Rutz 1, Meng Xiao He 1, Sören Müller 1, Nathaniel R West 1, Thomas F Brewer 1, Prashant Desai 1, Simon Williams 1, James Ziai 1, Yan Qu 1, Klaus Heger 1

Science advances | Free PMC Article

As certain irAEs correlate with clinical efficacy following checkpoint inhibitor therapy, Lim and Williams et al. investigated the relationship between autoimmunity and antitumor immunity. Loss of TREX1, an autoimmune risk gene and key negative regulator of the STING and type I IFN pathways promoted antitumor immunity in mice, and shared pathways with successful cancer immunotherapy. Like in PDCD1-/- and CTLA4-/- mice, constitutive TREX1 loss resulted in multiorgan CD8+ T cell influx, autoimmunity, and myocarditis. Conditional systemic TREX1 ablation was well tolerated and promoted effective CD8+ T cell-driven antitumor immunity, suggesting a new opportunity for immunotherapy.

Contributed by Katherine Turner

Junghyun Lim 1, Katherine Williams 1, Stephanie Mittman 1, Patricia Pacheco Sanchez 1, Ryan Rodriguez 1, Annie Ogasawara 1, Grace Barnett 1, Mayra Cruz Tleugabulova 1, Barzin Y Nabet 1, Jeffrey Hung 1, Kevin A Marroquin 1, Shari Lau 1, Serena Y Lee 1, Paul Tyler 1, Elizabeth T Carbone 1, Bridget Hough 1, Janice Corpuz 1, Haruka Murota 1, Edward Dere 1, Smadar Shiffman 1, Leah K Schutt 1, Herman Gill 1, Julia Lau 1, Marco De Simone 1, Lucinda Tam 1, Merone Roose-Girma 1, Søren Warming 1, Soyoung A Oh 1, Sascha Rutz 1, Meng Xiao He 1, Sören Müller 1, Nathaniel R West 1, Thomas F Brewer 1, Prashant Desai 1, Simon Williams 1, James Ziai 1, Yan Qu 1, Klaus Heger 1

Science advances | Free PMC Article

As certain irAEs correlate with clinical efficacy following checkpoint inhibitor therapy, Lim and Williams et al. investigated the relationship between autoimmunity and antitumor immunity. Loss of TREX1, an autoimmune risk gene and key negative regulator of the STING and type I IFN pathways promoted antitumor immunity in mice, and shared pathways with successful cancer immunotherapy. Like in PDCD1-/- and CTLA4-/- mice, constitutive TREX1 loss resulted in multiorgan CD8+ T cell influx, autoimmunity, and myocarditis. Conditional systemic TREX1 ablation was well tolerated and promoted effective CD8+ T cell-driven antitumor immunity, suggesting a new opportunity for immunotherapy.

Contributed by Katherine Turner

ABSTRACT: Checkpoint inhibitors targeting PD-1 and CTLA-4 have transformed cancer therapy. Both are genetically associated with autoimmune disorders. Moreover, certain immune-related adverse events and autoimmune risk variants are linked to the clinical efficacy of checkpoint inhibition. These associations suggest common principles governing successful cancer immunotherapy and autoimmune susceptibility. Here, we show that ablation of the cytosolic DNA exonuclease TREX1 predisposes mice to autoimmunity while promoting robust antitumor immunity. Constitutive TREX1 loss leads to early onset autoimmunity, characterized by multiorgan CD8+ T cell infiltration, myocarditis, and Sjgren's syndrome-like disease. In contrast, induced systemic TREX1 ablation is well tolerated and promotes effective CD8+ T cell-driven antitumor immunity. Detailed phenotypic studies revealed a notable overlap between productive antitumor and pathogenic autoimmune CD8+ T cell responses. Collectively, we provide mechanistic evidence for interrelated mechanisms underlying autoimmunity and successful cancer immunotherapy, uncover key parallels between adaptive T cell and innate immune checkpoints, and suggest that targeting autoimmune risk genes represents a promising future avenue for cancer immunotherapy.

Author Info: 1Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, USA.

Author Info: 1Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, USA.

Citation: Sci Adv 2026 May 8 12:eaea6842 Epub05/06/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42090506

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    Tumors hijack immune-privileging regulons via distinct cell types to confer T cell desertion and immunotherapy resistance across various cancers Spotlight 

    Bashir Lawal 1 2, Akshat Gupta 1 2, Renu Sharma 1 2, Huayan Ren 1 2, Rohit Bhargava 2 3, Yue Wang 1 2, Xiao-Song Wang 4 5

    Nature communications

    Lawal et al. identified an immune-privileging regulon signature (IMPREG) from tumor samples of patients who were non-responsive to ICB. IMPREG mirrors transcriptional programs of immune-privileged organs. Transcriptomics revealed that IMPREG was activated via three compartments: immature neuronal-like malignant cells, myofibroblastic CAFs, or endothelial cells, forming niches devoid of effector T cells and enriched for TGFβ3, CXCL12, and IL-34-driven suppressive circuits. High IMPREG scores predicted ICB resistance in 14 cancer types, and was associated with increased sensitivity to EGFR inhibitors and anti-angiogenic therapies.

    Contributed by Shishir Pant

    Bashir Lawal 1 2, Akshat Gupta 1 2, Renu Sharma 1 2, Huayan Ren 1 2, Rohit Bhargava 2 3, Yue Wang 1 2, Xiao-Song Wang 4 5

    Nature communications

    Lawal et al. identified an immune-privileging regulon signature (IMPREG) from tumor samples of patients who were non-responsive to ICB. IMPREG mirrors transcriptional programs of immune-privileged organs. Transcriptomics revealed that IMPREG was activated via three compartments: immature neuronal-like malignant cells, myofibroblastic CAFs, or endothelial cells, forming niches devoid of effector T cells and enriched for TGFβ3, CXCL12, and IL-34-driven suppressive circuits. High IMPREG scores predicted ICB resistance in 14 cancer types, and was associated with increased sensitivity to EGFR inhibitors and anti-angiogenic therapies.

    Contributed by Shishir Pant

    ABSTRACT: Immune checkpoint blockade (ICB) has transformed oncology, yet most patients fail to respond, suffer from hyper-progressive disease, or face severe immune-related toxicities, underscoring the urgent need for biomarkers that identify non-responders. Here we show that tumors co-opt an immune-privileging regulon signature (IMPREG) mirroring transcriptional programs of immune-privileged organs - to enforce T-cell desertion and ICB resistance across solid tumor types. Single-cell and spatial transcriptomic analyses reveal that tumors activate IMPREG through three distinct cellular routes: malignant cells adopting immature neuronal states, cancer-associated fibroblasts assuming myofibroblast identities, or endothelial cells - each creating localized niches of immune suppression and antigen-presentation collapse. Across 4 discovery and 36 validation clinical datasets, IMPREG consistently predicts immunotherapy resistance in 14 distinct cancer types, functioning as an orthogonal marker independent of established biomarkers. Crucially, IMPREG-expressing tumors show enhanced sensitivity to EGFR inhibitors or anti-angiogenic therapies in specific tumor entities. These findings suggest IMPREG as a dual-utility predictive biomarker for personalized treatment stratification.

    Author Info: 1UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA. 2Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA. 3Magee-Womens Hospital of UPMC,

    Author Info: 1UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA. 2Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA. 3Magee-Womens Hospital of UPMC, Pittsburgh, PA, USA. 4UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA. xiaosongw@pitt.edu. 5Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA. xiaosongw@pitt.edu.

    Citation: Nat Commun 2026 May 8 Epub05/08/2026

    Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42103714

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      CD39+CD49a+CD103+ cytotoxic tissue-resident natural killer cells infiltrate and control solid epithelial tumor growth in mice

      Featured  

      Nina B Horowitz 1 2, Imran A Mohammad 1, June Ho Shin 1, John W Hickey 3 4, Peter Chockley 5 6, Gail Snyder 1, Chen Chen 1, Keene Lee 1, Krishna Sharma 1, Quan Tran 1, Anahita Nejatfard 7, Sainiteesh Maddineni 1, Vasu Divi 1, Catherine A Blish 8, Garry P Nolan 4, Jennifer A Foltz 9 10, John B Sunwoo 1

      Science translational medicine

      Two recent papers phenotyped tumoral NK cell subsets. Lozada et al. detected a tissue-resident (TR) adaptive subset that was IFNG-driven, associated with better clinical outcomes and response to checkpoint blockade, while canonical NK cells expressed high TGFB1 and were suppressive. Horowitz, Mahammad, Ho Shin et al. also found that tissue-resident CD49a+CD103+ NK cells (trNK cells) can have suppressive or cytotoxic functions. A cytotoxic trNK population expressing CD39 had the highest cytolytic antitumor activity and could be differentiated and expanded ex vivo for adoptive transfer.

      Nina B Horowitz 1 2, Imran A Mohammad 1, June Ho Shin 1, John W Hickey 3 4, Peter Chockley 5 6, Gail Snyder 1, Chen Chen 1, Keene Lee 1, Krishna Sharma 1, Quan Tran 1, Anahita Nejatfard 7, Sainiteesh Maddineni 1, Vasu Divi 1, Catherine A Blish 8, Garry P Nolan 4, Jennifer A Foltz 9 10, John B Sunwoo 1

      Science translational medicine

      Two recent papers phenotyped tumoral NK cell subsets. Lozada et al. detected a tissue-resident (TR) adaptive subset that was IFNG-driven, associated with better clinical outcomes and response to checkpoint blockade, while canonical NK cells expressed high TGFB1 and were suppressive. Horowitz, Mahammad, Ho Shin et al. also found that tissue-resident CD49a+CD103+ NK cells (trNK cells) can have suppressive or cytotoxic functions. A cytotoxic trNK population expressing CD39 had the highest cytolytic antitumor activity and could be differentiated and expanded ex vivo for adoptive transfer.

      ABSTRACT: Human tissue-resident natural killer (NK) cells (trNK cells), broadly defined by markers of tissue residency, such as CD49a [integrin α1 (ITGA1)] and CD103 [integrin αE (ITGAE)], are increasingly recognized for their immunoregulatory role in host control of infection, malignancy, and autoimmunity. Although the importance of transforming growth factor-β in trNK cell differentiation has been demonstrated, the context in which the differentiation of CD49a+CD103+ trNK cells occurs can result in either an immunosuppressive phenotype (e.g., decidual NK cells) or a highly cytotoxic one (e.g., some tumor trNK subsets). To understand this dichotomy better, we used a multiomic approach to molecularly characterize these cells. We identified a cytotoxic trNK (ctrNK) cell population, characterized by the expression of CD39. These ctrNK cells exhibited superior cytolytic activity against tumor target cells, enhanced capacity to infiltrate into solid tumor microenvironments, and augmented ability to control solid tumor growth in vivo compared with conventionally activated peripheral NK cells. This heightened cytolytic and infiltrative functionality of ctrNK cells appeared to be conferred, in part, by the expression of CD103 and by avidity for tumor targets. Because adoptive immune cell therapy of solid tumor malignancies has been challenged by the inefficiency of ex vivo expanded immune cells to infiltrate immunosuppressive solid tumor microenvironments, our observations that ctrNK cells can be differentiated and expanded ex vivo present a potential platform for adoptive cell therapy of solid tumor malignancies.

      Author Info: 1Department of Otolaryngology-Head & Neck Surgery, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. 2Department of Bioengineering, Stanfo

      Author Info: 1Department of Otolaryngology-Head & Neck Surgery, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. 2Department of Bioengineering, Stanford University, Stanford, CA 94305, USA. 3Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA. 4Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA. 5Pelotonia Institute for Immuno-Oncology, Ohio State University Comprehensive Cancer Center-the James, Columbus, OH 43210, USA. 6Department of Molecular Medicine and Therapeutics, College of Medicine, Ohio State University, Columbus, OH 43210, USA. 7Department of Biochemistry, Stanford University, Stanford, CA 94305, USA. 8Division of Infectious Diseases, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA. 9Section of Computational Biology, Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA. 10Siteman Cancer Center at WashU Medicine, St. Louis, MO 63110, USA.

      Citation: Sci Transl Med 2026 May 6 18:eadw5567 Epub05/06/2026

      Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42090477

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