Journal Articles

The efficacy of immunotherapy in glioma requires distal B cell responses in tumor-draining lymph nodes Spotlight 

(1) Kim Y (2) Kang I (3) Kang BH (4) Park WH (5) Kim CW (6) Kim HJ (7) La J (8) Kwon MS (9) Park SH (10) Im SH (11) Kim HC (12) Ku KB (13) Kim M (14) Oh JE (15) Lee HK

Science immunology

Kim et al. showed that anti-CTLA-4 efficacy in orthotopic murine glioblastoma (GBM) models was abolished by B cell deficiency and tdLN removal. In WT mice, anti-CTLA-4 increased B cell numbers and GC reactions in tdLNs, but not in the TIME, and therapeutic efficacy required CD4+ T cell help to B cells. While maintaining tumor-reactive CD4+ T cell function in the TIME, in tdLNs, anti-CTLA-4 therapy boosted TFH cell differentiation to support GC B cell clonal expansion and generation of antibody-secreting cells producing tumor-binding class-switched IgG1 antibodies that promoted macrophage-mediated phagocytosis of glioma cells via Fc receptor signaling.

Contributed by Paula Hochman

(1) Kim Y (2) Kang I (3) Kang BH (4) Park WH (5) Kim CW (6) Kim HJ (7) La J (8) Kwon MS (9) Park SH (10) Im SH (11) Kim HC (12) Ku KB (13) Kim M (14) Oh JE (15) Lee HK

Science immunology

Kim et al. showed that anti-CTLA-4 efficacy in orthotopic murine glioblastoma (GBM) models was abolished by B cell deficiency and tdLN removal. In WT mice, anti-CTLA-4 increased B cell numbers and GC reactions in tdLNs, but not in the TIME, and therapeutic efficacy required CD4+ T cell help to B cells. While maintaining tumor-reactive CD4+ T cell function in the TIME, in tdLNs, anti-CTLA-4 therapy boosted TFH cell differentiation to support GC B cell clonal expansion and generation of antibody-secreting cells producing tumor-binding class-switched IgG1 antibodies that promoted macrophage-mediated phagocytosis of glioma cells via Fc receptor signaling.

Contributed by Paula Hochman

ABSTRACT: Humoral immunity, mediated by B cells that mature in germinal centers in lymph nodes (LNs), is essential for adaptive immune responses, but its role in antitumor immunity and responses to immunotherapy remain unclear. Here, we show that activation of B cells in tumor-draining deep cervical LNs (dcLNs) is necessary for the efficacy of CTLA-4 (cytotoxic T lymphocyte-associated protein 4) immune checkpoint blockade in glioma in vivo. Anti-CTLA-4 therapy enhanced T follicular helper cell (T(FH) cell) expansion in dcLNs, leading to germinal center B cell responses, immunoglobulin G (IgG) class switching, and the generation of glioma-reactive antibodies. Glioma-bearing mice lacking antibody-secreting cells did not benefit from CTLA-4 blockade. Distally secreted IgG accumulated in the tumor microenvironment and promoted glioma cell phagocytosis in vivo. These findings define a B cell-dependent mechanism underlying CTLA-4-mediated control of glioma and provide a conceptual framework for future therapeutic strategies in tumor.

Author Info: (1) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (2) Laboratory of Host D

Author Info: (1) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (2) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (3) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (4) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (5) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (6) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (7) Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (8) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (9) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (10) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (11) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (12) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Department of Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology, Daejeon, Republic of Korea. (13) Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (14) Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. (15) Laboratory of Host Defenses, Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Regenerative Medical Research Institute (reMRI) for Aging-Related Diseases, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.

Citation: Sci Immunol 2026 Jul 10 11:eadz2494 Epub07/10/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42430444

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Generalizable AI predicts immunotherapy outcomes across cancers and treatments Spotlight 

(1) Shen W (2) Moon I (3) Nguyen TH (4) Li MM (5) Huang Y (6) Nair N (7) Marbach D (8) Zitnik M

Nature medicine

Shen et al. developed COMPASS, an AI model that interprets pre-treatment tumor RNAseq data in the context of tumor-immune gene expression modules and maps them to predict ICB response. Trained on TCGA and cohort data, COMPASS was applicable across cohorts, indications, ICB drugs, and targets, with superior response prediction compared to established models or correlates (TMB, PD-L1). COMPASS also generated personalized “response maps” identifying potential resistance mechanisms; unexpected nonresponders (i.e. patients with an inflammatory TME) often had gene expression associated with angiogenesis, TGFβ, and B cell deficiency.

Contributed by Alex Najibi

(1) Shen W (2) Moon I (3) Nguyen TH (4) Li MM (5) Huang Y (6) Nair N (7) Marbach D (8) Zitnik M

Nature medicine

Shen et al. developed COMPASS, an AI model that interprets pre-treatment tumor RNAseq data in the context of tumor-immune gene expression modules and maps them to predict ICB response. Trained on TCGA and cohort data, COMPASS was applicable across cohorts, indications, ICB drugs, and targets, with superior response prediction compared to established models or correlates (TMB, PD-L1). COMPASS also generated personalized “response maps” identifying potential resistance mechanisms; unexpected nonresponders (i.e. patients with an inflammatory TME) often had gene expression associated with angiogenesis, TGFβ, and B cell deficiency.

Contributed by Alex Najibi

ABSTRACT: Immune checkpoint inhibitors (ICIs) are a standard treatment across cancers, yet most patients do not respond, and existing biomarkers generalize poorly across tumor types and therapies. Here we present COMPASS, a pan-cancer foundation model that predicts immunotherapy response from bulk tumor transcriptomes using a concept bottleneck transformer. COMPASS encodes gene expression through 44 biologically grounded immune concepts representing immune cell states, tumor-microenvironment interaction and signaling pathways. Trained on 10,184 tumors across 33 cancer types, COMPASS achieves better average performance than 22 methods across 16 clinical cohorts spanning seven cancers and six ICIs, improving accuracy by 8.5% and area under the precision-recall curve by 15.7% on average across cohorts. COMPASS generalizes to cancer types and treatments not represented during fine-tuning and may inform indication selection and patient stratification. In survival analyses, patients classified by COMPASS as responders had longer overall survival (hazard ratio_=_4.7, P_<_0.0001). Personalized response maps connect gene expression to immune concepts, identifying programs associated with response and resistance; in immune-inflamed non-responders, COMPASS highlights programs including TGF_ signaling, endothelial exclusion, CD4(+) T cell dysfunction and B cell deficiency. COMPASS predicts immunotherapy response and provides hypothesis-generating mechanistic insight for trial design and translational studies.

Author Info: (1) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. (2) Department of Biome

Author Info: (1) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. (2) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. (3) Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. (4) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. (5) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. (6) Roche Pharma Research and Early Development, Oncology Early Clinical Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland. (7) Computational Sciences Center of Excellence, F. Hoffmann-La Roche Ltd., Basel, Switzerland. daniel.marbach.dm1@roche.com. (8) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. marinka@hms.harvard.edu. Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Allston, MA, USA. marinka@hms.harvard.edu. Broad Institute of MIT and Harvard, Cambridge, MA, USA. marinka@hms.harvard.edu. Harvard Data Science Initiative, Cambridge, MA, USA. marinka@hms.harvard.edu.

Citation: Nat Med 2026 Jul 3 Epub07/03/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42399673

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Single-cell transcriptomic analysis reveals tumor-immune determinants of lymph node colonization and progression in thyroid cancer Spotlight 

(1) Nguyen AT (2) Viramontes J (3) Vazquez I (4) McWilliam C (5) Devarakonda V (6) Henson R (7) Sacks WL (8) Mallen-St Clair J (9) Chen Y (10) Walgama E (11) Scher KS (12) Moyers J (13) Sandler HM (14) Jang JK (15) Zumsteg ZS (16) Shon W (17) Shiao SL (18) Ho AS

Science advances | Free PMC Article

Nguyen et al. used single-cell RNAseq and multiplex IHC on paired primary thyroid carcinomas and metastatic lymph nodes (LNs) to define immune determinants of nodal colonization. In metastatic LNs, thyrocytes and TAMs downregulated inflammatory cytokine receptors. including TNFRSF12A and CX3CR1, and were enriched for Tregs relative to matched primary tumors, which suggests suppression of T cell-mediated cytotoxicity. Tumor-infiltrating lymphocytes in metastatic LNs showed increased IL7R expression, and high IL7R levels within nodal metastases correlated with enhanced immune activation and improved progression-free survival in a validation cohort.

Contributed by Shishir Pant

(1) Nguyen AT (2) Viramontes J (3) Vazquez I (4) McWilliam C (5) Devarakonda V (6) Henson R (7) Sacks WL (8) Mallen-St Clair J (9) Chen Y (10) Walgama E (11) Scher KS (12) Moyers J (13) Sandler HM (14) Jang JK (15) Zumsteg ZS (16) Shon W (17) Shiao SL (18) Ho AS

Science advances | Free PMC Article

Nguyen et al. used single-cell RNAseq and multiplex IHC on paired primary thyroid carcinomas and metastatic lymph nodes (LNs) to define immune determinants of nodal colonization. In metastatic LNs, thyrocytes and TAMs downregulated inflammatory cytokine receptors. including TNFRSF12A and CX3CR1, and were enriched for Tregs relative to matched primary tumors, which suggests suppression of T cell-mediated cytotoxicity. Tumor-infiltrating lymphocytes in metastatic LNs showed increased IL7R expression, and high IL7R levels within nodal metastases correlated with enhanced immune activation and improved progression-free survival in a validation cohort.

Contributed by Shishir Pant

ABSTRACT: Lymph node (LN) metastases are a major driver of mortality across solid cancers, including thyroid carcinomas, which are known for high rates of nodal colonization. To elucidate the determinants of nodal spread, we isolated tumor-infiltrating leukocytes from primary thyroid tumors and matched metastatic LNs for single-cell RNA sequencing with validation by multiplex immunohistochemistry. Comparing the microenvironmental alterations between primary tumors and their LNs, we found that thyrocytes and tumor-associated macrophages down-regulate the expression of multiple inflammatory cytokine receptors, including TNFRSF12A and CX3CR1, upon LN colonization. LNs were associated with the induction of regulatory T cells to suppress T cell-mediated cytotoxicity compared to matched primary tumors. Notably, tumor-infiltrating lymphocytes within LNs demonstrated increased expression of activation markers, including interleukin-7 receptor (IL7R). High LN expression of IL7R was significantly correlated with improved outcomes and can serve as a biomarker in this heterogeneous disease. Our findings on the dynamic equilibrium within LN metastases may offer conserved mechanisms for nodal colonization across solid tumors.

Author Info: (1) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA,

Author Info: (1) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (2) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (3) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (4) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (5) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (6) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (7) Division of Endocrinology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (8) Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (9) Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (10) Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (11) Division of Medical Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (12) Division of Medical Oncology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (13) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (14) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (15) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (16) Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (17) Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. (18) Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Citation: Sci Adv 2026 Jul 3 12:eaea4727 Epub07/03/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42397917

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RIG-I-targeted immunotherapy synergizes with immune checkpoint inhibition in a hepatocellular carcinoma model Spotlight 

(1) Marx C (2) Teppert J (3) Marisch L (4) Formisano S (5) Senz A (6) Boehmer DFR (7) Metzger P (8) Kechur D (9) Delius L (10) Hoerth C (11) Lauber K (12) Mayr D (13) De Toni EN (14) Helms MW (15) Brunner B (16) Endres S (17) Schnurr M (18) Duewell P (19) Rothenfusser S (20) Koenig LM

Molecular cancer therapeutics

Marx, Teppert, and Marisch et al. showed retinoic acid-inducible gene-I (RIG-I), the cytoplasmic sensor of short dsRNA with uncapped 5’-triphosphate (3p-RNA), was expressed in human HCC samples and induced by IFN-I on cell lines. 3p-RNA treatment given i.v. reduced tumor burden in murine orthotopic tumor models and induced immune memory. Therapeutic effects depended on CD4+ and CD8+ T, but not NK cells, and on tumor-intrinsic Fas expression, but not systemic intracellular RIG-I pathway signaling. Treatment with 3p-RNA upregulated PD-L1 expression on HCC cells and synergized with anti-PD-1 to improve efficacy in HCC mouse models.

Contributed by Paula Hochman

(1) Marx C (2) Teppert J (3) Marisch L (4) Formisano S (5) Senz A (6) Boehmer DFR (7) Metzger P (8) Kechur D (9) Delius L (10) Hoerth C (11) Lauber K (12) Mayr D (13) De Toni EN (14) Helms MW (15) Brunner B (16) Endres S (17) Schnurr M (18) Duewell P (19) Rothenfusser S (20) Koenig LM

Molecular cancer therapeutics

Marx, Teppert, and Marisch et al. showed retinoic acid-inducible gene-I (RIG-I), the cytoplasmic sensor of short dsRNA with uncapped 5’-triphosphate (3p-RNA), was expressed in human HCC samples and induced by IFN-I on cell lines. 3p-RNA treatment given i.v. reduced tumor burden in murine orthotopic tumor models and induced immune memory. Therapeutic effects depended on CD4+ and CD8+ T, but not NK cells, and on tumor-intrinsic Fas expression, but not systemic intracellular RIG-I pathway signaling. Treatment with 3p-RNA upregulated PD-L1 expression on HCC cells and synergized with anti-PD-1 to improve efficacy in HCC mouse models.

Contributed by Paula Hochman

ABSTRACT: Retinoic acid-inducible gene-I (RIG-I) is a cytoplasmic pattern recognition receptor that senses short double-stranded RNA with uncapped 5'-triphosphate (3p-RNA). Upon activation, RIG-I induces type I interferons and proinflammatory cytokines, thereby promoting adaptive immunity. Thus, RIG-I activation is a promising approach for creating a proinflammatory tumor microenvironment. In this study, we investigated its therapeutic potential in hepatocellular carcinoma (HCC). We explored and confirmed RIG-I expression and signaling in human HCC samples and cell lines. The therapeutic potential of RIG-I activation by 3p-RNA for the treatment of HCC was investigated in vitro and in syngeneic murine orthotopic tumor models. In vivo, 3p-RNA treatment significantly reduced the tumor burden, delayed disease progression, and achieved partial complete remission of RIL-175 tumors with durable immune memory. However, no therapeutic effects were observed in the Hep-55.1C model. Tumor clearance depended on CD4⁺ and CD8⁺ T cells, but not NK cells. Additionally, 3p-RNA induced PD-L1 expression on HCC cells, enhancing their sensitivity to anti-PD-1 immune checkpoint therapy in vivo. RIG-I activation via 3p-RNA therapy shows promise as an immunotherapeutic strategy for hepatocellular carcinoma (HCC). Future investigations need to focus on tumor-intrinsic factors to understand heterogeneity between tumors and to overcome resistance mechanisms.

Author Info: (1) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (2) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (3) LMU Klinikum Munich Germany. ROR: https://ror.or

Author Info: (1) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (2) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (3) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (4) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (5) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (6) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (7) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (8) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (9) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (10) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (11) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (12) Ludwig-Maximilians-UniversitŠt MŸnchen Munich, Bavaria Germany. ROR: https://ror.org/05591te55 (13) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (14) Sanofi (Germany) Frankfurt Germany. ROR: https://ror.org/03ytdtb31 (15) Sanofi (Germany) Frankfurt Germany. ROR: https://ror.org/03ytdtb31 (16) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (17) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (18) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (19) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32 (20) LMU Klinikum Munich Germany. ROR: https://ror.org/02jet3w32

Citation: Mol Cancer Ther 2026 Jun 25 Epub06/25/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42345470

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Neoadjuvant stereotactic body radiation therapy with durvalumab and oleclumab in ER+HER2- breast cancer: a randomized phase 2 trial

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(1) De Caluwé A (2) Desmoulins I (3) Cao K (4) Remouchamps V (5) Baten A (6) Longton E (7) Peignaux K (8) Joaquin Garcia A (9) Venet D (10) Arecco L (11) Agostinetto E (12) Nader-Marta G (13) Denis Z (14) Dhont J (15) Kristanto P (16) Catteau X (17) Larsimont D (18) Salgado R (19) Poortmans P (20) Stagg J (21) Sotiriou C (22) Piccart M (23) Ignatiadis M (24) Romano E (25) Buisseret L

Nature medicine

De Caluwé et al. conducted a phase 2 clinical trial in patients with ER+HER2- breast cancer assessing neoadjuvant chemotherapy with immune-modulating stereotactic body radiation therapy (iSBRT) alone or combined with anti-PD-L1 and anti-CD73 ICB. The addition of single or double ICB improved residual cancer burden and complete response rates. Patients with node-positive, PD-L1-negative tumors containing stromal tumor-infiltrating lymphocytes at baseline benefited most, with treatment modulating the tumor immune microenvironment from cold to hot.

(1) De Caluwé A (2) Desmoulins I (3) Cao K (4) Remouchamps V (5) Baten A (6) Longton E (7) Peignaux K (8) Joaquin Garcia A (9) Venet D (10) Arecco L (11) Agostinetto E (12) Nader-Marta G (13) Denis Z (14) Dhont J (15) Kristanto P (16) Catteau X (17) Larsimont D (18) Salgado R (19) Poortmans P (20) Stagg J (21) Sotiriou C (22) Piccart M (23) Ignatiadis M (24) Romano E (25) Buisseret L

Nature medicine

De Caluwé et al. conducted a phase 2 clinical trial in patients with ER+HER2- breast cancer assessing neoadjuvant chemotherapy with immune-modulating stereotactic body radiation therapy (iSBRT) alone or combined with anti-PD-L1 and anti-CD73 ICB. The addition of single or double ICB improved residual cancer burden and complete response rates. Patients with node-positive, PD-L1-negative tumors containing stromal tumor-infiltrating lymphocytes at baseline benefited most, with treatment modulating the tumor immune microenvironment from cold to hot.

ABSTRACT: Patients with estrogen receptor-positive (ER+), HER2-negative, early breast cancer (BC) have low pathologic complete response (pCR) rates following neoadjuvant chemotherapy. Immune checkpoint inhibitors (ICIs) provide limited benefit in programmed death-ligand 1 (PD-L1)-negative tumors, characterized by an immune-cold tumor microenvironment. Here we hypothesized that immune-modulating stereotactic body radiation therapy (iSBRT; 3 × 8 Gy) could enhance response through tumor microenvironment reprogramming, and that CD73 blockade could further improve efficacy. We conducted a phase 2, randomized, multicenter trial (Neo-CheckRay) in 147 female patients with high-risk, ER+HER2- early BC. Patients received neoadjuvant chemotherapy plus iSBRT alone (No_ICI), with anti-PD-L1 durvalumab (Single_ICI) or with durvalumab plus anti-CD73 oleclumab (Double_ICI). In the intention-to-treat population, the primary endpoint, residual cancer burden 0/1 rate, was 35.4% with No_ICI, 45.1% with Single_ICI and 47.9% with Double_ICI, without statistically significant differences. pCR rates were 16.7%, 29.4% and 33.3%, respectively (P = 0.059). In the per-protocol population (MammaPrint High Risk, n = 131), pCR rates were 16.3%, 32.6% and 35.6%, respectively (P = 0.040). Among PD-L1-negative tumors (n = 91), pCR rates were 3.4%, 28.1% and 30.0%, respectively. No new safety signals were observed. Baseline transcriptomic analysis showed low immune signature expression in PD-L1-negative tumors. Paired baseline and on-treatment biopsies obtained 1 week after iSBRT demonstrated tumor microenvironment reprogramming toward an inflamed phenotype in the iSBRT + anti-PD-L1 arms. These findings suggest that iSBRT + anti-PD-L1 may convert immune-cold ER+HER2- BC into more inflamed tumors and improve response, particularly in PD-L1-negative disease. ClinicalTrials.gov registration: NCT03875573 .

Author Info: (1) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. alex.decaluwe@bordet.be. (2) Centre Georges-Franoi

Author Info: (1) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. alex.decaluwe@bordet.be. (2) Centre Georges-Franois Leclerc, UniversitŽ Bourgogne Europe, Dijon, France. (3) Institut Curie, Paris, France. (4) CHU St Elisabeth, Namur, Belgium. (5) Universitaire Ziekenhuizen Leuven, Leuven, Belgium. (6) H™pital Universitaire St Luc, Brussels, Belgium. (7) Centre Georges-Franois Leclerc, UniversitŽ Bourgogne Europe, Dijon, France. (8) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (9) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (10) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (11) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (12) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (13) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (14) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (15) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (16) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (17) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (18) ZAS Hospitals, Antwerp, Belgium. Peter Mac Callum Cancer Centre, Melbourne, Victoria, Australia. (19) Iridium Netwerk, Antwerp, Belgium. University of Antwerp, Antwerp, Belgium. (20) Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada. (21) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (22) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (23) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium. (24) Institut Curie, Paris, France. (25) Institut Jules Bordet, H™pitaux Universitaires de Bruxelles (H.U.B), UniversitŽ Libre de Bruxelles (ULB), Brussels, Belgium.

Citation: Nat Med 2026 Jun 25 Epub06/25/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42350643

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Addressing Biases in Analysis of Time of Infusion: NCI/SWOG Trial S1404 Among Participants With High-Risk Resectable Melanoma Who Received Adjuvant Anti-PD-1 Therapy Spotlight 

(1) Othus M (2) Truong TG (3) Sharon E (4) Kendra K (5) Grossmann K (6) Buchbinder E (7) Khushalani NI (8) Eroglu Z (9) Chandra S (10) Doolittle GC (11) Kirkwood JM (12) Ikeguchi A (13) Mihalcioiu C (14) Cowey CL (15) Reddy SA (16) Johnson DB (17) Taylor M (18) Sondak VK (19) Ribas A (20) Patel SP

JCO oncology practice | Free PMC Article

In an analysis of a multi-center trial involving 628 patients with high-risk melanoma receiving adjuvant pembrolizumab, Othus et al. identified optimal time cut-points for the first infusion of 1:18 pm for recurrence-free survival and 3:48 pm for overall survival (OS). These findings, however, did not reach statistical significance regarding patient outcomes. Furthermore, the lack of threshold robustness was demonstrated when shifting the OS cut-point 30 minutes earlier, which yielded a hazard ratio of 0.98. Average infusion times trended earlier over the year, while appointments were on average later for patients living further from the treatment center.

Contributed by Ute Burkhardt

(1) Othus M (2) Truong TG (3) Sharon E (4) Kendra K (5) Grossmann K (6) Buchbinder E (7) Khushalani NI (8) Eroglu Z (9) Chandra S (10) Doolittle GC (11) Kirkwood JM (12) Ikeguchi A (13) Mihalcioiu C (14) Cowey CL (15) Reddy SA (16) Johnson DB (17) Taylor M (18) Sondak VK (19) Ribas A (20) Patel SP

JCO oncology practice | Free PMC Article

In an analysis of a multi-center trial involving 628 patients with high-risk melanoma receiving adjuvant pembrolizumab, Othus et al. identified optimal time cut-points for the first infusion of 1:18 pm for recurrence-free survival and 3:48 pm for overall survival (OS). These findings, however, did not reach statistical significance regarding patient outcomes. Furthermore, the lack of threshold robustness was demonstrated when shifting the OS cut-point 30 minutes earlier, which yielded a hazard ratio of 0.98. Average infusion times trended earlier over the year, while appointments were on average later for patients living further from the treatment center.

Contributed by Ute Burkhardt

PURPOSE: Multiple reports have suggested that receiving immunotherapy infusions earlier in the day is associated with improved outcomes, including longer overall survival (OS) and lower toxicity rates. However, the definition of early varies between publications. Reports also fail to account for confounding factors (including distance to infusion center), are subject to survivor bias (analyzing postbaseline factors at baseline), and do not adjust P values for multiple comparisons when evaluating multiple potential thresholds for early versus late time of day of infusion. METHODS: We analyzed a previously reported multicenter clinical trial evaluating pembrolizumab as adjuvant therapy for participants with resectable high-risk melanoma. Standard statistical methodologies that account for potential biasses were used to evaluate the association between time of day of infusion and clinical outcomes. RESULTS: A total of 628 participants received pembrolizumab and had time of first infusion recorded. The median age was 55 years, range, 20-82. Odds of infusion before 11:00 hours increased by 32% over 12 months of therapy (P = .013). Participants living further from their treating institution had later infusion times on average: odds of infusion before 11:00 decreased by 9% for each additional 50 miles (P = .017). The optimal cut point for first infusion time for OS was 15:48 with hazard ratio (HR) = 1.40; changing the cut point by 30 minutes earlier to 15:18 decreased HR to 0.98, indicating lack of robustness of the threshold. No significant association was identified between proportion of early infusions and outcomes in multivariable time-dependent Cox regression models. CONCLUSION: In this multicenter trial of adjuvant pembrolizumab for participants with high-risk melanoma, analyses that account for common sources of bias found no significant association between recurrence-free or OS and time of day of infusion.

Author Info: (1) Division of Public Health, Fred Hutchinson Cancer Center, Seattle WA. (2) Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH. (3)

Author Info: (1) Division of Public Health, Fred Hutchinson Cancer Center, Seattle WA. (2) Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH. (3) Department of Medicine, Dana Farber Cancer Institute, Boston, MA. Harvard Medical School, Boston, MA. (4) Medical Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH. (5) Medical Oncology, Providence Cancer Institute, Portland, OR. (6) Medical Oncology, Mass General Brigham Cancer Institute, Boston, MA. (7) Department of Cutaneous Oncology, H Lee Moffitt Cancer Center, Tampa, FL. (8) Department of Cutaneous Oncology, H Lee Moffitt Cancer Center, Tampa, FL. (9) Division of Hematology and Oncology, Robert H Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL. (10) Division of Clinical Oncology, University of Kansas Medical Center, Kansas City, KS. (11) Melanoma Program, University of Pittsburgh Medical Center, Hillman Cancer Center, Pittsburgh, PA. (12) Melanoma Medical Oncology, University of Texas, MD Anderson Cancer Center, Houston, TX. (13) Medical Oncology, McGill University Health Centre, Montreal, Canada. (14) Melanoma, Texas Oncology-Baylor Sammons Cancer Center, Dallas, TX. (15) Department of Medical Oncology, Stanford University School of Medicine, Palo Alto, CA. (16) Department of Medicine, Vanderbilt University Medical Center, Nashville, TN. (17) Medical Oncology, Providence Cancer Institute, Portland, OR. (18) Department of Cutaneous Oncology, H Lee Moffitt Cancer Center, Tampa, FL. (19) Department of Medicine, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA. (20) Department of Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO.

Citation: JCO Oncol Pract 2026 Jun 23 OP2501413 Epub06/23/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42335437

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FLT3L-secreting cDC1 in situ vaccination enhances antitumor immunity and synergizes with PD-1 blockade in murine non-small cell lung cancer Spotlight 

(1) Abascal J (2) Dumitras C (3) Tran LM (4) Crosson W (5) Kahangi B (6) Oh M (7) Rennels A (8) Lim RJ (9) Jiang H (10) Reyimjan D (11) Coleman NJ (12) Perez-Reyes E (13) Chin S (14) Krysan K (15) Dubinett SM (16) Liu B (17) Salehi-Rad R

Journal for immunotherapy of cancer | Free PMC Article

Abascal et al. engineered FLT3L-secreting mouse cDC1s that retained APC and phagocytic ability in vitro. In situ vaccination (ISV) with the cDC1s inhibited s.c. tumor growth in multiple syngeneic murine models, including those with driver mutations common in human NSCLC, and increased trafficking of the autologous cDC1s to TdLN and tumor infiltration of T cells. TCGA analysis showed that FLT3L expression in human NSCLC correlated with profiles of B and T cells, activated DCs and HEV-enriched TLS. ISV increased immature TLS formation in the murine TIME and synergized with anti-PD-1 in a NSCLC model to enhance efficacy and induce immune memory.

Contributed by Paula Hochman

(1) Abascal J (2) Dumitras C (3) Tran LM (4) Crosson W (5) Kahangi B (6) Oh M (7) Rennels A (8) Lim RJ (9) Jiang H (10) Reyimjan D (11) Coleman NJ (12) Perez-Reyes E (13) Chin S (14) Krysan K (15) Dubinett SM (16) Liu B (17) Salehi-Rad R

Journal for immunotherapy of cancer | Free PMC Article

Abascal et al. engineered FLT3L-secreting mouse cDC1s that retained APC and phagocytic ability in vitro. In situ vaccination (ISV) with the cDC1s inhibited s.c. tumor growth in multiple syngeneic murine models, including those with driver mutations common in human NSCLC, and increased trafficking of the autologous cDC1s to TdLN and tumor infiltration of T cells. TCGA analysis showed that FLT3L expression in human NSCLC correlated with profiles of B and T cells, activated DCs and HEV-enriched TLS. ISV increased immature TLS formation in the murine TIME and synergized with anti-PD-1 in a NSCLC model to enhance efficacy and induce immune memory.

Contributed by Paula Hochman

BACKGROUND: Non-small cell lung cancer (NSCLC) frequently evades immune surveillance through defective antigen presentation and a suppressive tumor microenvironment (TME), limiting the efficacy of immune checkpoint blockade (ICB). Conventional type 1 dendritic cells (cDC1s) are essential for initiating antitumor CD8(+) T-cell responses; however, their abundance and function are often diminished in NSCLC, contributing to poor outcomes and resistance to immunotherapy. We hypothesized that in situ vaccination (ISV) using gene-modified cDC1s engineered to secrete FMS-like tyrosine kinase 3 ligand (FLT3L) would enhance cDC1 function within the TME, promote antitumor immunity, and improve responses to ICB. METHODS: Syngeneic murine models of NSCLC (Kras(G12D)/P53(-/-)/Lkb1(-/-); Kras(G12D)/P53(-/-) ; and Kras(G12D) ) with varying tumor mutational burden, along with the MC38 model, were used to assess the therapeutic efficacy of FLT3L-cDC1 ISV. Flow cytometry and multiplex immunofluorescence were used to evaluate immune mechanisms of response. To assess translational relevance, immune and tertiary lymphoid structure (TLS) signatures were analyzed in The Cancer Genome Atlas (TCGA) NSCLC datasets, with TLS signatures refined using a retrained xCell2 framework incorporating curated TLS and high endothelial venule (HEV) microdissection datasets. RESULTS: FLT3L-cDC1 ISV remodeled the TME across multiple NSCLC models, inducing T lymphocyte infiltration and expanding cytolytic CD8(+) T cells. FLT3L-cDC1 ISV was associated with increased formation of immature TLS with primary follicle-like features within the TME. TCGA analyses revealed that FLT3L expression correlates with activated DC, T cell, and B cell signatures, as well as HEV-enriched TLS-associated programs. Combination with PD-1 blockade further enhanced the antitumor immunity of FLT3L-cDC1 ISV, resulting in robust local and systemic T-cell activation and the expansion of activated CCR7(+)PD-L1(+) cDC1s and stem-like TCF1(+)PD-1(+) CD8(+) progenitors within the TME. In an LKB1-deficient NSCLC model, FLT3L-cDC1 ISV plus PD-1 blockade induced complete and durable regression in 85% of tumors, leading to long-lasting systemic tumor-specific immune memory, consistent with effective tumor vaccination. CONCLUSIONS: FLT3L-cDC1 ISV represents a rational cytokine-enhanced cellular immunotherapy designed to overcome immunosuppression and restore DC function within the TME, thereby promoting tumor-specific adaptive immune responses and enhancing responsiveness to ICB.

Author Info: (1) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (2) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA

Author Info: (1) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (2) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (3) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. VA Greater Los Angeles Healthcare System, Los Angeles, California, USA. (4) Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, Los Angeles, California, USA. (5) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (6) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. VA Greater Los Angeles Healthcare System, Los Angeles, California, USA. (7) Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, Los Angeles, California, USA. (8) Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, Los Angeles, California, USA. (9) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (10) UCLA, Los Angeles, California, USA. (11) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (12) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (13) Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, Los Angeles, California, USA. (14) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. (15) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA. VA Greater Los Angeles Healthcare System, Los Angeles, California, USA. Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, Los Angeles, California, USA. (16) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA rsalehirad@mednet.ucla.edu bliu@mednet.ucla.edu. (17) Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA rsalehirad@mednet.ucla.edu bliu@mednet.ucla.edu. VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.

Citation: J Immunother Cancer 2026 Jun 25 14: Epub06/25/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42350046

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B cell-derived type I interferon sustains T cell functionality upon strong TCR stimulation during chronic infection Spotlight 

(1) Gago da Graça C (2) Cao Y (3) Li S (4) Lindemann AF (5) Heyden L (6) Wijesinghe SKM (7) Poch A (8) Nguyen MT (9) Huynh-Anh NT (10) Daum E (11) Chen D (12) Tsui C (13) Rupasinghe E (14) Gantier MP (15) Roers A (16) Thimme R (17) Hofmann M (18) Bedoui S (19) Abdullah Z (20) Schrder J (21) Kallies A (22) Alexandre YO (23) Utzschneider DT

Immunity

Graça et al. show that B cells are essential for CD8+ T cell effector response during chronic, but not acute, LCMV infection. In chronic infection, splenic B cells sense viruses via TLR7/8-STING pathways and produce IFN-I, which promotes exhausted T cell differentiation and sustain effector function in the spleen, whereas CD8+ T cells in the LN or responding to low antigen load were B cell independent. Loss of B cells or IFN-I signaling impaired exhausted T cell cytokine production (‘tolerized-like’). IRF1 integrates IFN-I signals to promote T cell expansion. Chronic human HBV showed a similar antigen-load-dependent effect observed in the murine LCMV model.

Contributed by Shishir Pant

(1) Gago da Graça C (2) Cao Y (3) Li S (4) Lindemann AF (5) Heyden L (6) Wijesinghe SKM (7) Poch A (8) Nguyen MT (9) Huynh-Anh NT (10) Daum E (11) Chen D (12) Tsui C (13) Rupasinghe E (14) Gantier MP (15) Roers A (16) Thimme R (17) Hofmann M (18) Bedoui S (19) Abdullah Z (20) Schrder J (21) Kallies A (22) Alexandre YO (23) Utzschneider DT

Immunity

Graça et al. show that B cells are essential for CD8+ T cell effector response during chronic, but not acute, LCMV infection. In chronic infection, splenic B cells sense viruses via TLR7/8-STING pathways and produce IFN-I, which promotes exhausted T cell differentiation and sustain effector function in the spleen, whereas CD8+ T cells in the LN or responding to low antigen load were B cell independent. Loss of B cells or IFN-I signaling impaired exhausted T cell cytokine production (‘tolerized-like’). IRF1 integrates IFN-I signals to promote T cell expansion. Chronic human HBV showed a similar antigen-load-dependent effect observed in the murine LCMV model.

Contributed by Shishir Pant

ABSTRACT: B cells are highly abundant lymphocytes and central players in humoral immunity. Although T cells are well known to support humoral responses, how B cells influence T cell responses is less understood. Here, we show that B cells are critical for CD8(+) T cell responses to chronic, but not acute, viral infections. In the absence of B cells, T cells responding to chronic infection exhibited severely impaired effector differentiation. This dependency on B cell help was dictated by high antigen loads and strong T cell receptor (TCR) stimulation. Loss of either B cells or interferon-I (IFN-I) signaling led to severe functional deficits in exhausted T cells, implicating B cells as key producers of IFN-I. The IFN-I-dependent T cell response to strong TCR stimulation is mediated, in part, by the transcription factor IRF1. Therefore, during chronic infection, we uncover an important role for B cell-derived IFN-I in modulating T cell responses to strong TCR stimulation.

Author Info: (1) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (2) Department of Microbi

Author Info: (1) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (2) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (3) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (4) Institute of Molecular Medicine and Experimental Immunology, University Hospital Bonn, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany. (5) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia; Institute of Molecular Medicine and Experimental Immunology, University Hospital Bonn, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany. (6) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (7) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (8) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (9) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (10) Institute for Immunology, University Hospital Heidelberg, Heidelberg, Germany. (11) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (12) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (13) Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Clayton, VIC, Australia; Department of Molecular and Translational Science, Monash University, Clayton, VIC, Australia. (14) Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Clayton, VIC, Australia; Department of Molecular and Translational Science, Monash University, Clayton, VIC, Australia. (15) Institute for Immunology, University Hospital Heidelberg, Heidelberg, Germany. (16) Department of Medicine II (Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases), Medical Center, University of Freiburg, Baden-WŸrttemberg, Germany. (17) Department of Medicine II (Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases), Medical Center, University of Freiburg, Baden-WŸrttemberg, Germany. (18) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (19) Institute of Molecular Medicine and Experimental Immunology, University Hospital Bonn, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany. (20) Computational Sciences Initiative (CSI), the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (21) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. (22) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. Electronic address: yannick.alexandre@unimelb.edu.au. (23) Department of Microbiology and Immunology, the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia. Electronic address: daniel.utzschneider@unimelb.edu.au.

Citation: Immunity 2026 Jul 2 Epub07/02/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42392074

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Treg cells promote immunotherapy-induced immune evasion by restraining CD4 T cell control of MHC-I-deficient metastatic pancreatic cancer

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(1) Schmiechen ZC (2) Cruz-Hinojoza E (3) Hilk AL (4) Ellefson MA (5) Tsai AK (6) Dres OM (7) Kang LI (8) Geuenich MJ (9) Butler JZ (10) Burrack AL (11) Larsen BM (12) Hickok GH (13) Miller EA (14) Lonetree CL (15) Gaire A (16) Pandey R (17) Nanda HA (18) Chaudhury I (19) Corbiere T (20) Dileepan T (21) Shen SS (22) Campbell KR (23) DeNardo DG (24) Stromnes IM

Science immunology

Schmiechen et al. found that variants of PDA that escaped following PD-L1 blockade showed epigenetic silencing of Tap1 expression, which induced loss of IFNγ-inducible MHC-I and reduced tumor cell killing mediated by CD8+ T cell. Escape variants also had an increased capacity for metastasis, which was promoted by Tregs and their suppressive effect on conventional CD4+ T cells. Combination strategies involving restoring IFNγ-inducible MHC-I, targeting Tregs, and enhancing Tconv enabled more effective cancer immunotherapy, suggesting potentially targetable mechanisms to enhance immunotherapy in PDA.

(1) Schmiechen ZC (2) Cruz-Hinojoza E (3) Hilk AL (4) Ellefson MA (5) Tsai AK (6) Dres OM (7) Kang LI (8) Geuenich MJ (9) Butler JZ (10) Burrack AL (11) Larsen BM (12) Hickok GH (13) Miller EA (14) Lonetree CL (15) Gaire A (16) Pandey R (17) Nanda HA (18) Chaudhury I (19) Corbiere T (20) Dileepan T (21) Shen SS (22) Campbell KR (23) DeNardo DG (24) Stromnes IM

Science immunology

Schmiechen et al. found that variants of PDA that escaped following PD-L1 blockade showed epigenetic silencing of Tap1 expression, which induced loss of IFNγ-inducible MHC-I and reduced tumor cell killing mediated by CD8+ T cell. Escape variants also had an increased capacity for metastasis, which was promoted by Tregs and their suppressive effect on conventional CD4+ T cells. Combination strategies involving restoring IFNγ-inducible MHC-I, targeting Tregs, and enhancing Tconv enabled more effective cancer immunotherapy, suggesting potentially targetable mechanisms to enhance immunotherapy in PDA.

ABSTRACT: Mechanisms driving immunotherapy resistance in pancreatic cancer are poorly defined. We demonstrate that programmed death-ligand 1 immune checkpoint blockade promoted immune evasion by epigenetic Tap1 (transporter associated with antigen processing 1) silencing, increasing selection of metastatic tumor variants with defective interferon-_ (IFN-_)-inducible class I major histocompatibility complex (MHC-I) expression. Unleashing CD4 conventional T cells by regulatory T cell (T(reg) cell) depletion, transfer of tumor-reactive CD4 T cells, or anti-CTLA-4 prevented metastasis. Tumor-specific CD4 T cells adopted a TCF-1(+)SLAMF6(+) progenitor state in lymph nodes and differentiated in tumors. Anti-CTLA-4 increased intratumoral accumulation of CD4 T cells with stemness and tissue residency features, reduced metastasis, and induced gene signatures correlated with improved patient outcomes. MHC-I restoration with anti-CTLA-4 prolonged survival in murine models. In patient tumors, T(reg) cells and CD4 T cells colocalized, and abundance correlated with survival. These findings identify targetable mechanisms of immune evasion and metastasis in immunotherapy-resistant cancer.

Author Info: (1) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. Center for Immunology, University of Minnesota Medical School, Minneapo

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

Citation: Sci Immunol 2026 Jun 26 11:eadz4302 Epub06/26/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42361199

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Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling Spotlight 

(1) Suissa D (2) Fidelle M (3) Reich E (4) Pham TN (5) Thomas S (6) Bjšrk JR (7) Liu P (8) Zhao L (9) Kitaoka K (10) Piard E (11) Lebhar I (12) Tian AL (13) Thelemaque C (14) Alves Costa Silva C (15) Deutsch E (16) Loriot Y (17) Segata N (18) Piccinno G (19) Hospers GAP (20) Maleki Vareki S (21) Silverman MS (22) Lenehan JG (23) Bataille V (24) Boulate D (25) Kuznetsova T (26) Weersma RK (27) Messaoudene M (28) Durand S (29) van der Aalst CM (30) de Koning HJ (31) Schuler-Thurner B (32) de Vries IJM (33) Rafie E (34) Saliby RM (35) Machaalani M (36) Haferkamp S (37) Schilling B (38) Porcari S (39) Ciccarese C (40) Iacovelli R (41) Cremolini C (42) Choueiri TK (43) Elkrief A (44) Kroemer G (45) Heinzerling L (46) Chamoto K (47) Ianiro G (48) Routy B (49) Derosa L (50) Paragios N (51) Zitvogel L

Nature medicine

Suissa and Fidelle et al. performed targeted metabolomics to 4,336 plasma samples from 1,714 ICI-treated patients across 16 cohorts and trained an ML model that predicted 12‑month PFS, with histidine as a favorable marker and long-chain fatty acids and succinate associated with poor outcome. Histidine supplementation promoted mitochondrial FAO and regulated T cell exhaustion, enhancing ICI-induced antitumor immunity in fibrosarcoma and melanoma models. Histidine-rich diet was associated with favorable PFS in patients without dysbiosis-associated histidine catabolism, and fecal histidine levels inversely correlated with severe irAEs.

Contributed by Shishir Pant

(1) Suissa D (2) Fidelle M (3) Reich E (4) Pham TN (5) Thomas S (6) Bjšrk JR (7) Liu P (8) Zhao L (9) Kitaoka K (10) Piard E (11) Lebhar I (12) Tian AL (13) Thelemaque C (14) Alves Costa Silva C (15) Deutsch E (16) Loriot Y (17) Segata N (18) Piccinno G (19) Hospers GAP (20) Maleki Vareki S (21) Silverman MS (22) Lenehan JG (23) Bataille V (24) Boulate D (25) Kuznetsova T (26) Weersma RK (27) Messaoudene M (28) Durand S (29) van der Aalst CM (30) de Koning HJ (31) Schuler-Thurner B (32) de Vries IJM (33) Rafie E (34) Saliby RM (35) Machaalani M (36) Haferkamp S (37) Schilling B (38) Porcari S (39) Ciccarese C (40) Iacovelli R (41) Cremolini C (42) Choueiri TK (43) Elkrief A (44) Kroemer G (45) Heinzerling L (46) Chamoto K (47) Ianiro G (48) Routy B (49) Derosa L (50) Paragios N (51) Zitvogel L

Nature medicine

Suissa and Fidelle et al. performed targeted metabolomics to 4,336 plasma samples from 1,714 ICI-treated patients across 16 cohorts and trained an ML model that predicted 12‑month PFS, with histidine as a favorable marker and long-chain fatty acids and succinate associated with poor outcome. Histidine supplementation promoted mitochondrial FAO and regulated T cell exhaustion, enhancing ICI-induced antitumor immunity in fibrosarcoma and melanoma models. Histidine-rich diet was associated with favorable PFS in patients without dysbiosis-associated histidine catabolism, and fecal histidine levels inversely correlated with severe irAEs.

Contributed by Shishir Pant

ABSTRACT: Immune-checkpoint inhibitors benefit a subset of patients with advanced cancer, and the metabolic determinants of response remain unclear. Here, using targeted metabolomics and metagenomics, we profiled 4,336 plasma samples from 1,714 patients across five tumor types and 16 cohorts spanning Europe and North America, longitudinally sampled during five immune-checkpoint inhibitor-based treatment modalities, including fecal microbiota transplantation. A multimodal machine-learning framework integrating 154 metabolites with clinical variables identified five metabolites, age, body mass index and renal function as predictors of 12-month progression-free survival. The model achieved areas under the curve of 0.88 in training and 0.73 in validation cohorts of 105 and 30 patients, respectively and generalized across seven external cohorts. Histidine was a favorable prognostic feature of survival, whereas long-chain fatty acids and succinate were negatively associated with outcome. Histidine supplementation enhanced antitumor immunity in mice. Histidine-rich diets improved progression-free survival in patients lacking dysbiotic microbiome signatures associated with histidine catabolism.

Author Info: (1) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (2) UniversitŽ Paris-Saclay,

Author Info: (1) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (2) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (3) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (4) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (5) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (6) Department of Gastroenterology and Hepatology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands. Department of Medical Oncology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands. (7) INSERM U1138 - Metabolism, Cancer & Immunity, ƒquipe LabellisŽe par la Ligue Contre le Cancer, Centre de Recherche des Cordeliers, UniversitŽ Paris CitŽ, Sorbonne UniversitŽ, Paris, France. UniversitŽ Paris-Saclay, INSERM US23 AMMICa, Metabolomic Platform, Gustave Roussy, Villejuif, France. (8) INSERM U1138 - Metabolism, Cancer & Immunity, ƒquipe LabellisŽe par la Ligue Contre le Cancer, Centre de Recherche des Cordeliers, UniversitŽ Paris CitŽ, Sorbonne UniversitŽ, Paris, France. UniversitŽ Paris-Saclay, INSERM US23 AMMICa, Metabolomic Platform, Gustave Roussy, Villejuif, France. (9) Department of Immunology and Genomic Medicine, Center for Cancer Immunotherapy and Immunobiology (CCII), Graduate School of Medicine, Kyoto University, Kyoto, Japan. (10) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (11) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (12) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (13) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. (14) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil. Gonalo Moniz Institute, Fiocruz, Salvador, Brazil. Federal University of Bahia, Salvador, Brazil. (15) Department of Radiation Oncology, Gustave Roussy, UniversitŽ Paris-Saclay, INSERM U1355, RHU LySAIRI, Villejuif, France. (16) Department of Therapeutic Innovation and Early Trials (DITEP), INSERM U981, Gustave Roussy, Villejuif, France. (17) Department of Computational, Cellular and Integrative Biology, University of Trento, Trento, Italy. (18) Department of Computational, Cellular and Integrative Biology, University of Trento, Trento, Italy. (19) Department of Medical Oncology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands. (20) Verspeeten Family Cancer Centre, London Health Sciences Research Institute, London, Ontario, Canada. Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada. Department of Oncology, Division of Experimental Oncology, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada. (21) Lawson Health Research Institute, London, Ontario, Canada. Department of Microbiology & Immunology, Western University, London, Ontario, Canada. Department of Medicine, Division of Infectious Diseases, Western University, London, Ontario, Canada. Division of Infectious Diseases, St Joseph's Health Care, London, Ontario, Canada. (22) Verspeeten Family Cancer Centre, London Health Sciences Research Institute, London, Ontario, Canada. Department of Oncology, Western University, London, Ontario, Canada. (23) Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. Department of Dermatology, Mount Vernon Cancer Centre, Northwood, UK. Department of Dermatology, Hemel Hempstead Hospital, West Hertfordshire NHS Trust, Hemel Hempstead, UK. (24) Department of Thoracic Surgery, H™pital-Nord-APHM, Aix-Marseille University, Marseille, France. H™pital Marie Lannelongue, GHPSJ, Le Plessis-Robinson, France. (25) Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium. (26) Department of Gastroenterology and Hepatology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands. (27) Centre de Recherche du Centre Hospitalier de l'UniversitŽ de MontrŽal (CRCHUM), Axe Cancer, Montreal, Quebec, Canada. (28) INSERM U1138 - Metabolism, Cancer & Immunity, ƒquipe LabellisŽe par la Ligue Contre le Cancer, Centre de Recherche des Cordeliers, UniversitŽ Paris CitŽ, Sorbonne UniversitŽ, Paris, France. UniversitŽ Paris-Saclay, INSERM US23 AMMICa, Metabolomic Platform, Gustave Roussy, Villejuif, France. (29) Department of Public Health, Erasmus Medical Centre - University Medical Centre Rotterdam, Rotterdam, The Netherlands. (30) Department of Public Health, Erasmus Medical Centre - University Medical Centre Rotterdam, Rotterdam, The Netherlands. (31) Department of Dermatology, Friedrich-Alexander-UniversitŠt Erlangen-NŸrnberg (FAU), UniversitŠtsklinikum Erlangen, Erlangen, Germany. Bavarian Cancer Research Center (BZKF), Erlangen, Germany. (32) Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands. (33) Centre de Recherche du Centre Hospitalier de l'UniversitŽ de MontrŽal (CRCHUM), Axe Cancer, Montreal, Quebec, Canada. Hemato-Oncology Division, Centre Hospitalier de l'UniversitŽ de MontrŽal (CHUM), Montreal, Quebec, Canada. (34) Dana-Farber Cancer Institute, Boston, MA, USA. Yale School of Medicine, New Haven, CT, USA. (35) Dana-Farber Cancer Institute, Boston, MA, USA. (36) Bavarian Cancer Research Center (BZKF), Erlangen, Germany. Department of Dermatology, University Hospital Regensburg, Regensburg, Germany. (37) Department of Dermatology, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany. (38) Department of Translational Medicine and Surgery, Universitˆ Cattolica del Sacro Cuore, Facoltˆ di Medicina e Chirurgia, Rome, Italy. Department of Medical and Surgical Sciences, UOC CEMAD Centro Malattie dell'Apparato Digerente, Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario Gemelli IRCCS, Rome, Italy. (39) Department of Translational Medicine and Surgery, Universitˆ Cattolica del Sacro Cuore, Facoltˆ di Medicina e Chirurgia, Rome, Italy. Department of Medical and Surgical Sciences, UOC Oncologia Medica, Comprehensive Cancer Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy. (40) Department of Translational Medicine and Surgery, Universitˆ Cattolica del Sacro Cuore, Facoltˆ di Medicina e Chirurgia, Rome, Italy. Department of Medical and Surgical Sciences, UOC Oncologia Medica, Comprehensive Cancer Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy. (41) Unit of Medical Oncology 2, University Hospital of Pisa, Pisa, Italy. Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy. (42) Dana-Farber Cancer Institute, Boston, MA, USA. Harvard Medical School, Boston, MA, USA. (43) Centre de Recherche du Centre Hospitalier de l'UniversitŽ de MontrŽal (CRCHUM), Axe Cancer, Montreal, Quebec, Canada. Hemato-Oncology Division, Centre Hospitalier de l'UniversitŽ de MontrŽal (CHUM), Montreal, Quebec, Canada. (44) INSERM U1138 - Metabolism, Cancer & Immunity, ƒquipe LabellisŽe par la Ligue Contre le Cancer, Centre de Recherche des Cordeliers, UniversitŽ Paris CitŽ, Sorbonne UniversitŽ, Paris, France. UniversitŽ Paris-Saclay, INSERM US23 AMMICa, Metabolomic Platform, Gustave Roussy, Villejuif, France. Institut du Cancer Paris CARPEM, Department of Biology, H™pital EuropŽen Georges Pompidou, AP-HP, Paris, France. (45) Department of Dermatology, Friedrich-Alexander-UniversitŠt Erlangen-NŸrnberg (FAU), UniversitŠtsklinikum Erlangen, Erlangen, Germany. Bavarian Cancer Research Center (BZKF), Erlangen, Germany. Department of Dermatology and Allergy, LMU University Hospital LMU Munich, Munich, Germany. (46) Department of Immunology and Genomic Medicine, Center for Cancer Immunotherapy and Immunobiology (CCII), Graduate School of Medicine, Kyoto University, Kyoto, Japan. Division of Cancer Immune Regulation, Center for Cancer Immunotherapy and Immunobiology (CCII), Graduate School of Medicine, Kyoto University, Kyoto, Japan. (47) Department of Translational Medicine and Surgery, Universitˆ Cattolica del Sacro Cuore, Facoltˆ di Medicina e Chirurgia, Rome, Italy. Department of Medical and Surgical Sciences, UOC CEMAD Centro Malattie dell'Apparato Digerente, Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario Gemelli IRCCS, Rome, Italy. (48) Centre de Recherche du Centre Hospitalier de l'UniversitŽ de MontrŽal (CRCHUM), Axe Cancer, Montreal, Quebec, Canada. Hemato-Oncology Division, Centre Hospitalier de l'UniversitŽ de MontrŽal (CHUM), Montreal, Quebec, Canada. (49) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. Department of Medical Oncology, Gustave Roussy, Villejuif, France. (50) MICS Laboratory, CentraleSupŽlec, UniversitŽ Paris-Saclay, Gif-sur-Yvette, France. nikos.paragios@centralesupelec.fr. TheraPanacea, Paris, France. nikos.paragios@centralesupelec.fr. (51) UniversitŽ Paris-Saclay, Gustave Roussy, ClinicObiome, Inserm UMR1367, Microbiota and Mucosal Immunity for Cancer Immunotherapy, Villejuif, France. Laurence.zitvogel@gustaveroussy.fr.

Citation: Nat Med 2026 Jun 25 Epub06/25/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42350644

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