Journal Articles

Oncogenic Kras targeting with MRTX1133 or Daraxonrasib specifically synergize with anti-CTLA4 to promote anti-tumor immunity in pancreatic cancer

Krishnan K. Mahadevan (1), Ana S. Maldonado (1), Bingrui Li (1), Aaron A. Bickert (1), Adrian Kacperczyk-Perdyan (1,2), Shreyasee V. Kumbhar (1), Sujan Piya (3), Amari M. Sockwell (1), Sami J. Morse (1), Kent Arian (1), Hikaru Sugimoto (1), Shabnam Shalapour (1), David S. Hong (4), Timothy P. Heffernan (5), Anirban Maitra (3)& Raghu Kalluri (1,6,7,8)

Nature communications

Krishnan K. Mahadevan (1), Ana S. Maldonado (1), Bingrui Li (1), Aaron A. Bickert (1), Adrian Kacperczyk-Perdyan (1,2), Shreyasee V. Kumbhar (1), Sujan Piya (3), Amari M. Sockwell (1), Sami J. Morse (1), Kent Arian (1), Hikaru Sugimoto (1), Shabnam Shalapour (1), David S. Hong (4), Timothy P. Heffernan (5), Anirban Maitra (3)& Raghu Kalluri (1,6,7,8)

Nature communications

ABSTRACT: Lack of sustained response to oncogenic Kras (Kras*) inhibition in pancreatic ductal adenocarcinoma (PDAC) underscores the need to identify effective combination therapies. Here, we demonstrate that Kras* targeting using MRTX1133 or Daraxonrasib recruits diverse T-cell infiltrates, including regulatory (Tregs), effector and exhausted T cells into the PDAC microenvironment. Kras* inhibition induces T-cell influx and offers a therapeutic window to specifically prime PDAC to anti-CTLA4 immune checkpoint blockade efficacy, in contrast to anti-PD1, anti-Tim3, anti-Lag3, anti-Vista, and anti-4-1BB agonist combination therapy. Mechanistically, anti-CTLA4 combination therapy transcriptionally reprograms effector Tregs to a naive phenotype, reverses CD8+ T-cell exhaustion, and promotes recruitment of functional tertiary lymphoid structures to mediate anti-tumor immunity. Single-cell ATAC sequencing reveals that Treg reprogramming by anti-CTLA4 is epigenetically regulated by downregulation of AP-1 family transcription factors in the IL-35 promoter region. This study reveals an actionable vulnerability in the adaptive immune response in Kras* targeted PDAC with immediate clinical implications.

Author Info: (1) Department of Cancer Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA (2) 3P-Medicine Laboratory, Medical University of Gdansk, 80-210 Gdansk, Poland (3

Author Info: (1) Department of Cancer Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA (2) 3P-Medicine Laboratory, Medical University of Gdansk, 80-210 Gdansk, Poland (3) Departments of Anatomical Pathology and Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA (4) Department of Investigative Cancer Therapeutics, University of Texas MD Anderson Cancer Center, Houston, TX, USA (5) Institute for Applied Science and TRACTION platform, University of Texas MD Anderson Cancer Center, Houston, TX, USA (6) Department of Bioengineering, Rice University, Houston, TX, USA (7) Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA (8) Department of Pathology, University of Texas Medical Branch, Galveston, TX, USA

Citation: Nat com 2026

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Tim-3 Sustains Tumor Treg Stability and Function, Limiting Checkpoint Blockade Therapy Efficacy Spotlight 

(1) Banerjee H (2) Onyekachi OV (3) Nieves-Rosado H (4) Murter BM (5) Kulkarni A (6) Pandey SP (7) Cardona E (8) Dougherty JE (9) Li H (10) Upadhyay P (11) Hinterleitner R (12) Ferris RL (13) Kane LP

Cancer immunology research

Banerjee et al. showed that Tim3 expression on tumor-infiltrating Tregs was required for their survival and suppressive function via Akt-FOXO1 signaling. Treg-specific Tim3 deletion in an MC38 model reduced tumor-infiltrating Tregs and CD25 expression, impaired Treg survival, delayed CD8+ T cell exhaustion, enhanced CD8+ proliferation, and reduced tumor burden, without disrupting peripheral homeostasis. Delayed Tim3 deletion in Tregs was sufficient to slow tumor growth and augment CD8+ responses, and Treg-specific Tim3 loss synergized with ICB in a resistant B16F10 model. In HNSCC, low Tim3 expression correlated with response to anti-PD-1/Lag3 ICB.

Contributed by Shishir Pant

(1) Banerjee H (2) Onyekachi OV (3) Nieves-Rosado H (4) Murter BM (5) Kulkarni A (6) Pandey SP (7) Cardona E (8) Dougherty JE (9) Li H (10) Upadhyay P (11) Hinterleitner R (12) Ferris RL (13) Kane LP

Cancer immunology research

Banerjee et al. showed that Tim3 expression on tumor-infiltrating Tregs was required for their survival and suppressive function via Akt-FOXO1 signaling. Treg-specific Tim3 deletion in an MC38 model reduced tumor-infiltrating Tregs and CD25 expression, impaired Treg survival, delayed CD8+ T cell exhaustion, enhanced CD8+ proliferation, and reduced tumor burden, without disrupting peripheral homeostasis. Delayed Tim3 deletion in Tregs was sufficient to slow tumor growth and augment CD8+ responses, and Treg-specific Tim3 loss synergized with ICB in a resistant B16F10 model. In HNSCC, low Tim3 expression correlated with response to anti-PD-1/Lag3 ICB.

Contributed by Shishir Pant

ABSTRACT: Regulatory T cells (Treg) act as a powerful barrier to effective antitumor immunity. Although manipulating Treg is a promising anticancer strategy, doing so while sparing general immune tolerance has been a challenge. Identifying factors specifically expressed in tumor-infiltrating Treg is therefore important for better understanding cancer pathogenesis and identifying novel therapeutic targets that enhance antitumor immunity. We show that T cell Immunoglobulin and Mucin 3 (Tim-3) expression on tumor Treg is required for the function and survival of these cells, in part through Akt and FOXO1 signaling. Deleting Tim-3 in Treg leads to delayed tumor-specific T-cell exhaustion and lower tumor burden, without altering peripheral homeostasis. Similar effects were noted when Tim-3 was only deleted from half of the Treg or when deletion was delayed until after tumor inoculation. Moreover, Treg-specific deletion of Tim-3 cooperated with PD-1 checkpoint blockade to sensitize an immunotherapy-resistant tumor model. In addition, a decrease in Tim-3+ tumor Treg correlated with responsiveness to PD-1/LAG-3 combination checkpoint blockade in a human clinical trial. Overall, our data provide evidence that Tim3-expressing Treg are a promising target to modulate tumor-specific immune responses.

Author Info: (1) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (2) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305

Author Info: (1) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (2) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (3) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (4) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (5) University of North Carolina at Chapel Hill Chapel Hill, NC United States. ROR: https://ror.org/0130frc33 (6) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (7) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (8) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (9) University of Pittsburgh Pittsburgh, PA United States. (10) University of North Carolina at Chapel Hill Chapel Hill, NC United States. ROR: https://ror.org/0130frc33 (11) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (12) University of North Carolina Hospitals Chapel Hill, NC United States. ROR: https://ror.org/0355zfr67 (13) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305

Citation: Cancer Immunol Res 2026 Jul 15 Epub07/15/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42455126

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Mutant KRAS peptide vaccine with dual checkpoint blockade in metastatic colorectal cancer: a phase I trial Spotlight 

(1) Wang HH (2) Huff AL (3) Haldar SD (4) Berg M (5) Thoburn C (6) Heumann TR (7) Anders RA (8) Barrett B (9) Bever KM (10) Pishvaian MJ (11) Lee V (12) Le DT (13) Christenson ES (14) Baretti M (15) Yarchoan M (16) Laheru D (17) Thomas A (18) Durham JN (19) Nauroth JM (20) Lu J (21) Wang H (22) Jaffee EM (23) Azad NS (24) Zaidi N

Nature communications

Wang et al. evaluated a combination of nivolumab, ipilimumab, and mKRAS-VAX (six 21-mer synthetic long peptides targeting common KRAS mutations) in 13 heavily pretreated patients with MMRp/MSS metastatic colorectal cancer. Treatment was well tolerated, with a 15% overall response rate and a median progression-free and overall survival of 2 and 24.9 months, respectively. Direct ex vivo peptide stimulation revealed reactive T cell responses in 75% of patients, which reached 100% following in vitro expansion (mainly CD4+ and polyfunctional). Tumor infiltration by peripheral mKRAS-reactive T cells was associated with tumor regression.

Contributed by Ute Burkhardt

(1) Wang HH (2) Huff AL (3) Haldar SD (4) Berg M (5) Thoburn C (6) Heumann TR (7) Anders RA (8) Barrett B (9) Bever KM (10) Pishvaian MJ (11) Lee V (12) Le DT (13) Christenson ES (14) Baretti M (15) Yarchoan M (16) Laheru D (17) Thomas A (18) Durham JN (19) Nauroth JM (20) Lu J (21) Wang H (22) Jaffee EM (23) Azad NS (24) Zaidi N

Nature communications

Wang et al. evaluated a combination of nivolumab, ipilimumab, and mKRAS-VAX (six 21-mer synthetic long peptides targeting common KRAS mutations) in 13 heavily pretreated patients with MMRp/MSS metastatic colorectal cancer. Treatment was well tolerated, with a 15% overall response rate and a median progression-free and overall survival of 2 and 24.9 months, respectively. Direct ex vivo peptide stimulation revealed reactive T cell responses in 75% of patients, which reached 100% following in vitro expansion (mainly CD4+ and polyfunctional). Tumor infiltration by peripheral mKRAS-reactive T cells was associated with tumor regression.

Contributed by Ute Burkhardt

ABSTRACT: Immune checkpoint inhibitors (ICIs) have limited activity in mismatch repair proficient or microsatellite stable (MMRp/MSS) colorectal cancer (CRC). KRAS mutations, present in approximately 40% of these cancers, can generate neoantigens that are targets for therapeutic vaccines. In this single-arm, phase I study (NCT04117087), we evaluated mKRAS-VAX, a pooled mutant KRAS (mKRAS) peptide vaccine targeting six KRAS mutations with nivolumab and ipilimumab in 13 patients with pretreated metastatic MMRp/MSS CRC. Both primary endpoints of safety and immunogenicity (within 17 weeks post-vaccination) were met. Secondary endpoints included treatment efficacy defined by RECIST v1.1 criteria. All adverse events attributed to mKRAS-VAX were grade 1 or 2, and the addition of mKRAS-VAX did not increase the frequency of severe immune-related adverse events beyond the expected profile of dual ICIs alone. mKRAS-VAX elicited an increase in tumor-specific mKRAS-reactive T-cells in 8/12 biomarker-evaluable patients (75%) by direct ex vivo IFN_ ELISpot and in 12 patients (100%) following in vitro expansion. Our findings support further development of mKRAS vaccines with ICIs for advanced MMRp/MSS CRC.

Author Info: (1) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University S

Author Info: (1) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (2) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (3) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. (4) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (5) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (6) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. Department of Hematology/Oncology, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. (7) Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. (8) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (9) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (10) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (11) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (12) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (13) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (14) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (15) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (16) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (17) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (18) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (19) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (20) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (21) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. (22) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. (23) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. nilo.azad@jhu.edu. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. nilo.azad@jhu.edu. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. nilo.azad@jhu.edu. (24) Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA. nzaidi1@jhmi.edu. Johns Hopkins Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. nzaidi1@jhmi.edu. The Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University of Medicine, Baltimore, MD, USA. nzaidi1@jhmi.edu.

Citation: Nat Commun 2026 Jun 23 Epub06/23/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42336869

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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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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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TIGIT-targeted IL-12 fusion protein engages NK and CD8+ T cells for potent tumor immunotherapy

Spotlight 

(1) Tang M (2) Huang Y (3) Bi J (4) Meng D (5) Zheng X (6) Peng H (7) Sun R (8) Ma H (9) Tian Z (10) Sun H (11) Zheng X

Cell reports. Medicine

To mitigate systemic IL-12 activation, Tang et al. generated T-12, a fusion protein linking IL-12 to an anti-TIGIT scFv that blocks TIGIT binding to its inhibitory receptor. Compared to wild-type IL-12, T-12 selectively localized to tumor sites and activated intratumoral NK and CD8+ T cells (both highly expressing TIGIT) to promote NK cell proliferation and reprogram CD8+ T cells toward a proliferative, memory-like effector phenotype. T-12 exhibited an MTD ~100X higher than wild-type IL-12, suppressed tumor growth in multiple mouse models (including immunologically “cold”/anti-PD-1 resistant), and reduced metastatic lesions to promote survival by mechanisms requiring both NK and CD8+ T cells.

Contributed by Paula Hochman

(1) Tang M (2) Huang Y (3) Bi J (4) Meng D (5) Zheng X (6) Peng H (7) Sun R (8) Ma H (9) Tian Z (10) Sun H (11) Zheng X

Cell reports. Medicine

To mitigate systemic IL-12 activation, Tang et al. generated T-12, a fusion protein linking IL-12 to an anti-TIGIT scFv that blocks TIGIT binding to its inhibitory receptor. Compared to wild-type IL-12, T-12 selectively localized to tumor sites and activated intratumoral NK and CD8+ T cells (both highly expressing TIGIT) to promote NK cell proliferation and reprogram CD8+ T cells toward a proliferative, memory-like effector phenotype. T-12 exhibited an MTD ~100X higher than wild-type IL-12, suppressed tumor growth in multiple mouse models (including immunologically “cold”/anti-PD-1 resistant), and reduced metastatic lesions to promote survival by mechanisms requiring both NK and CD8+ T cells.

Contributed by Paula Hochman

ABSTRACT: The limitation of wild-type interleukin-12 (IL-12) in its clinical application lies in its systemic activation, which results in severe toxicities. Here, we develop a fusion protein named _TIGIT-IL12 (T-12), which fuses the 13G6 (_TIGIT) antibody scFv fragment in tandem with IL-12. T-12 can selectively localize to the tumor site and concurrently target intratumoral natural killer (NK) and CD8(+) T cells in vivo. T-12 demonstrated exceptional efficacy in reducing tumor burden across multiple tumor models in mice, dependent on NK and CD8(+) T cells. T-12 preferentially activates tumor-infiltrating NK and CD8(+) T cells over their peripheral counterparts, in contrast to wild-type IL-12. Compared with wild-type IL-12, T-12 exhibits greater safety upon systemic administration while treating tumor-bearing models, and the maximal tolerance dosage was elevated by up to about 100-fold. T-12 exhibits potent therapeutic efficacy in checkpoint-insensitive tumor models and metastatic tumor models. These findings underscore the potential of the T-12 fusion protein as a strategy in immunotherapy.

Author Info: (1) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedic

Author Info: (1) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China. (2) CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Center for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning 530021, Guangxi, China. (3) CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China. (4) CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China. (5) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China. (6) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China. (7) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; Hefei TG ImmunoPharma Corporation Limited, Hefei, China. (8) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China. Electronic address: mahongdi@ustc.edu.cn. (9) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Hefei TG ImmunoPharma Corporation Limited, Hefei, China. Electronic address: tzg@ustc.edu.cn. (10) Department of Immunology, School of Basic Medical Sciences, and Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China; Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China; Hefei TG ImmunoPharma Corporation Limited, Hefei, China. Electronic address: haoyusun@ustc.edu.cn. (11) State Key Laboratory of Immune Response and Immunotherapy, Institute of Immunology, School of Basic Medical Sciences, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Hefei TG ImmunoPharma Corporation Limited, Hefei, China. Electronic address: ustczxh@ustc.edu.cn.

Citation: Cell Rep Med 2026 Jun 16 102876 Epub06/16/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42302794

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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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FAP-CD40 and PD1-IL2v combination therapy reprograms immunologically cold tumors through de novo intratumoral T cell-dendritic cell clusters Spotlight 

(1) Nguyen TT (2) Gómez H (3) Lutge M (4) Yángüez E (5) Hüsser T (6) Nassiri S (7) Trumpfheller C (8) Colombetti S (9) Codarri Deak L (10) Umaña P (11) Tugues S (12) Grazina de Matos I (13) Kunz L

Journal for immunotherapy of cancer | Free PMC Article

In a KPC tumor model, Nguyen et al. combined a FAP-targeted CD40 agonist (FAP-CD40; localizes CD40 stimulation to the TME) and PD1–IL-2v (targets a mutated IL-2 to PD-1+ T cells and not Tregs). FAP-CD40 alone activated TME cDC1s, which migrated to tdLNs. Combination therapy expanded TME T cells and increased CD4+/CD8+/cDC1 clustering and therapeutic efficacy (dependent on both CD4+ and CD8+ T cells) compared to monotherapies. FTY720 blockade of LN egress did not preclude clustering or efficacy, suggesting activation of TME T cells. Combination therapy boosted TME T cell Th1 gene expression, TNFα/IFNγ production, and Nur77 promoter activity.

Contributed by Alex Najibi

(1) Nguyen TT (2) Gómez H (3) Lutge M (4) Yángüez E (5) Hüsser T (6) Nassiri S (7) Trumpfheller C (8) Colombetti S (9) Codarri Deak L (10) Umaña P (11) Tugues S (12) Grazina de Matos I (13) Kunz L

Journal for immunotherapy of cancer | Free PMC Article

In a KPC tumor model, Nguyen et al. combined a FAP-targeted CD40 agonist (FAP-CD40; localizes CD40 stimulation to the TME) and PD1–IL-2v (targets a mutated IL-2 to PD-1+ T cells and not Tregs). FAP-CD40 alone activated TME cDC1s, which migrated to tdLNs. Combination therapy expanded TME T cells and increased CD4+/CD8+/cDC1 clustering and therapeutic efficacy (dependent on both CD4+ and CD8+ T cells) compared to monotherapies. FTY720 blockade of LN egress did not preclude clustering or efficacy, suggesting activation of TME T cells. Combination therapy boosted TME T cell Th1 gene expression, TNFα/IFNγ production, and Nur77 promoter activity.

Contributed by Alex Najibi

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a major challenge for immunotherapy due to its immunologically cold tumor nature, characterized by poor T cell infiltration and a highly suppressive tumor microenvironment. Here, we propose a novel strategy, combining fibroblast activation protein (FAP)-CD40 to activate dendritic cells (DCs) in the tumor microenvironment and programmed cell death protein-1 (PD1)-interleukin 2v (IL2v) to promote the expansion and differentiation of tumor-infiltrating T cells. We hypothesize that this combination will synergistically enhance both T cell priming and expansion directly within pancreatic 4662 KPC tumors, which recapitulate the immunologically cold features of human PDAC. METHODS: Immune cell distribution and abundance following FAP-CD40/PD1-IL2v monotherapy or combination therapy were analyzed using multiplexed confocal imaging (3D immune phenotyping). FTY720 studies assessed the contribution of lymph node priming in treatment efficacy, while CD4+/CD8+ T cell depletion experiments identified the roles of these subsets in combination therapy. T cell functionality was further assessed through ex vivo restimulation assays and single-cell RNA sequencing. RESULTS: Combination therapy induced dense intratumoral clusters of CD4(+) and CD8(+) T cells, colocalized with type 1 conventional DCs, termed as T cell-DC clusters (TDCs). These TDCs were strongly associated with tumor regression, which required both CD4(+) and CD8(+) T cells. Furthermore, T cells from combination-treated tumors showed enhanced functionality, with increased tumor necrosis factor-alpha and interferon-gamma production compared with monotherapy groups. Single-cell RNA sequencing revealed polarization of CD4(+) T cells toward a T helper cell 1 phenotype in combination-treated tumors. CONCLUSION: The combination of FAP-CD40 and PD1-IL2v offers a promising strategy for treating poorly infiltrated, cold tumors. By driving T cell infiltration, promoting de novo TDC formation and orchestrating local antitumor immunity, this strategy provides a foundation for future therapies targeting immunotherapy-resistant tumors.

Author Info: (1) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (2) Roche Pharma Research and Early Development, Roche Innovation Center Ba

Author Info: (1) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (2) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (3) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (4) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (5) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (6) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (7) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (8) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland. (9) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (10) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (11) Institute of Experimental Immunology, UniversitŠt ZŸrich, ZŸrich, Switzerland. Department of Immunology, Heidelberg University Medical Faculty Mannheim, Mannheim, Germany. (12) Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland. (13) Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland leo.kunz@roche.com.

Citation: J Immunother Cancer 2026 May 28 14: Epub05/28/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42208978

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