Journal Articles

Rapid CAR-T manufacturing with low-intensity priming enhances CAR-T cell fitness and limits inflammatory programming in a phase 1 study

(1) Yang Z (2) Li S (3) Wang L (4) Li Y (5) Xu H (6) Li Y (7) Liu L (8) Yuan Z (9) Zhang Y (10) Zhang L (11) Chen Y (12) Zhang Q (13) Shen J (14) Wang M (15) Zhu W (16) He X (17) Wang Y (18) Dong Y (19) Wang S (20) Qian C

Cell stem cell

Yang and Li et al. developed a 2-day protocol called PrimeCAR in which T cells were primed ex vivo with low-intensity soluble anti-CD3 in combination with IL-7 and IL-21. Compared to a longer conventional CAR T cell manufacturing protocol, PrimeCAR T cell manufacturing yielded less activated, less differentiated CAR T cell products that maintained strong cytotoxicity, while limiting inflammatory cytokine signaling and associated toxicities. PrimeCAR T cells showed promising results for maintaining efficacy while limiting toxicity in two phase 1 trials in patients with either B-ALL or B-NHL.

(1) Yang Z (2) Li S (3) Wang L (4) Li Y (5) Xu H (6) Li Y (7) Liu L (8) Yuan Z (9) Zhang Y (10) Zhang L (11) Chen Y (12) Zhang Q (13) Shen J (14) Wang M (15) Zhu W (16) He X (17) Wang Y (18) Dong Y (19) Wang S (20) Qian C

Cell stem cell

Yang and Li et al. developed a 2-day protocol called PrimeCAR in which T cells were primed ex vivo with low-intensity soluble anti-CD3 in combination with IL-7 and IL-21. Compared to a longer conventional CAR T cell manufacturing protocol, PrimeCAR T cell manufacturing yielded less activated, less differentiated CAR T cell products that maintained strong cytotoxicity, while limiting inflammatory cytokine signaling and associated toxicities. PrimeCAR T cells showed promising results for maintaining efficacy while limiting toxicity in two phase 1 trials in patients with either B-ALL or B-NHL.

ABSTRACT: Conventional chimeric antigen receptor (CAR)-T manufacturing requires prolonged ex vivo activation and expansion, which may compromise T cell fitness and promote inflammatory differentiation. Here, we developed PrimeCAR, a 2-day manufacturing strategy combining low-intensity anti-CD3 priming with IL-7 and IL-21. Compared with conventionally manufactured CAR-T cells, PrimeCAR products exhibited a distinct transcriptional state characterized by preserved stemness-associated programs and a PrimeCAR-enriched primed naive T cell (Tn)-like state. Following antigen stimulation, PrimeCAR cells preferentially engaged proliferative programs while limiting exhaustion-associated regulators and inflammatory mediators. Functionally, PrimeCAR cells demonstrated enhanced expansion, persistence, and durable antitumor activity in xenograft models. In investigator-initiated phase I studies of relapsed or refractory B cell acute lymphoblastic leukemia and B cell non-Hodgkin lymphoma, PrimeCAR showed encouraging clinical activity with a favorable safety profile. Together, these findings demonstrate that rapid manufacturing with controlled early T cell priming selectively restrains inflammatory programming while preserving CAR-T cell fitness, providing a practical strategy for improving CAR-T manufacturing and therapeutic performance.

Author Info: (1) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. Electronic address: yangzhi@precisio

Author Info: (1) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. Electronic address: yangzhi@precision-biotech.com. (2) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (3) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (4) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (5) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (6) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (7) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (8) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (9) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (10) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (11) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (12) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (13) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (14) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (15) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (16) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. (17) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (18) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. (19) 920th Hospital of Joint Logistics Support Force of People's Liberationsi Army of China, Kunming 650100, Yunnan, China. Electronic address: sanbin1011@163.com. (20) Chongqing Key Laboratory of Gene and Cell Therapy, Chongqing 400039, China; Chongqing Precision Biotech Co., Ltd., Chongqing 400039, China. Electronic address: cqian8634@gmail.com.

Citation: Cell Stem Cell 2026 Oct 13 Epub10/13/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42869018

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NKG2D overexpression potentiates CAR-T cells through costimulation by tumor NKG2D ligands

(1) Li J (2) Han L (3) Zhu Q (4) Liu N (5) Ma H (6) Wu Z (7) Wang Y (8) Lin X (9) Wei J (10) Han W

Cell reports. Medicine

Li, Han, and Zhu et al. observed that T cell activation increased NKG2D ligand (NKG2DL) expression, enabling T cell depletion by NK cells. Overexpressing (OE) full-length NKG2D in CAR T cells led to its colocalization with NKG2DL on the cell surface, reducing NKG2DL detection (by cis masking) and NK killing. NKG2D-OE also improved CAR T cell cytotoxicity by binding NKG2DL on tumor cells (in trans) and increasing CAR-T activation, memory phenotype, CAR-proximal signaling, and proliferative capacity, without affecting exhaustion. NKG2D-OE improved CAR-T efficacy in heme and solid tumor models, and boosted tumor infiltration.

Contributed by Alex Najibi

(1) Li J (2) Han L (3) Zhu Q (4) Liu N (5) Ma H (6) Wu Z (7) Wang Y (8) Lin X (9) Wei J (10) Han W

Cell reports. Medicine

Li, Han, and Zhu et al. observed that T cell activation increased NKG2D ligand (NKG2DL) expression, enabling T cell depletion by NK cells. Overexpressing (OE) full-length NKG2D in CAR T cells led to its colocalization with NKG2DL on the cell surface, reducing NKG2DL detection (by cis masking) and NK killing. NKG2D-OE also improved CAR T cell cytotoxicity by binding NKG2DL on tumor cells (in trans) and increasing CAR-T activation, memory phenotype, CAR-proximal signaling, and proliferative capacity, without affecting exhaustion. NKG2D-OE improved CAR-T efficacy in heme and solid tumor models, and boosted tumor infiltration.

Contributed by Alex Najibi

ABSTRACT: Chimeric antigen receptor (CAR)-T cell therapy has achieved remarkable success in hematologic malignancies, but durable efficacy remains limited by insufficient CAR-T cell persistence. Here, we show that activated CAR-T cells upregulate multiple NKG2D ligands (NKG2DLs), increasing their susceptibility to natural killer (NK) cell-mediated CAR-T cell cytotoxicity. To address this vulnerability, we engineer CAR-T cells to overexpress full-length NKG2D (CAR-NG). NKG2D overexpression reduces the surface accessibility of endogenous NKG2DLs without decreasing their total protein abundance. In parallel, engagement of tumor-expressed NKG2DLs in trans provides additional costimulatory signals, enhancing CAR-T cell activation and proliferation while attenuating exhaustion-associated phenotypes. In hematologic and solid tumor models, CAR-NG cells exhibit reduced susceptibility to NK-cell-mediated cytotoxicity, improved tumor control, increased in vivo expansion, deeper tumor infiltration, and no evident additional toxicity compared with conventional CAR-T cells. These findings identify NKG2D overexpression as an engineering strategy that enhances CAR-T antitumor activity primarily through tumor NKG2DL-dependent trans costimulation.

Author Info: (1) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (2) Department of Biotherapy, the First Medical Center, Chinese PLA General Ho

Author Info: (1) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (2) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (3) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (4) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (5) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (6) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (7) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. (8) Beijing Changping Laboratory, Beijing, China; School of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing, China; Tsinghua-Peking Center for Life Sciences, Beijing, China. Electronic address: linxin307@tsinghua.edu.cn. (9) Beijing Changping Laboratory, Beijing, China. Electronic address: woshiwjs@hotmail.com. (10) Department of Biotherapy, the First Medical Center, Chinese PLA General Hospital, Beijing, China. Electronic address: hanwdrsw@163.com.

Citation: Cell Rep Med 2026 Oct 16 103116 Epub10/16/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42887502

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A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions Spotlight 

(1) Cao K (2) Li R (3) Stra_ar M (4) Brown EM (5) Nguyen PNU (6) Pust MM (7) Park J (8) Graham DB (9) Ashenberg O (10) Uhler C (11) Xavier RJ

Nature communications | Free PMC Article

Cao et al. developed StriMap – a prediction framework for modeling peptide–HLA presentation and TCR recognition as a coupled process based on physicochemical, sequence-context, and structure-informed representations that capture relevant constraints. StriMap was successfully used to screen bacterial peptides and identity candidates to activate TCRs associated with ankylosing spondylitis (AS), and a top candidate in AS was also confirmed in IBD, linking the two autoimmune diseases. In cancer, StriMap demonstrated efficacy for both TCR selection in adoptive cell therapy, and prioritizing potential neoepitopes for personalized cancer vaccines.

Contributed by Lauren Hitchings

(1) Cao K (2) Li R (3) Stra_ar M (4) Brown EM (5) Nguyen PNU (6) Pust MM (7) Park J (8) Graham DB (9) Ashenberg O (10) Uhler C (11) Xavier RJ

Nature communications | Free PMC Article

Cao et al. developed StriMap – a prediction framework for modeling peptide–HLA presentation and TCR recognition as a coupled process based on physicochemical, sequence-context, and structure-informed representations that capture relevant constraints. StriMap was successfully used to screen bacterial peptides and identity candidates to activate TCRs associated with ankylosing spondylitis (AS), and a top candidate in AS was also confirmed in IBD, linking the two autoimmune diseases. In cancer, StriMap demonstrated efficacy for both TCR selection in adoptive cell therapy, and prioritizing potential neoepitopes for personalized cancer vaccines.

Contributed by Lauren Hitchings

ABSTRACT: The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) underlies antigen-specific T cell immunity. Despite substantial advances in peptide-HLA presentation prediction, accurate modeling of coupled TCR-peptide-HLA recognition remains underdeveloped, limiting applications such as TCR and neoepitope prioritization in cancer and antigen identification in autoimmunity. Here we present StriMap, a unified framework for predicting TCR-peptide-HLA interactions by integrating physicochemical, sequence-context, and structural features at recognition interfaces. StriMap achieves state-of-the-art performance with improved generalizability and enables applications in both cancer and autoimmunity. As a case study in ankylosing spondylitis (AS), we screened 13 million peptides derived from 43,241 bacterial proteins and identified candidate molecular mimics that were experimentally validated to activate T cells expressing an AS-associated TCR. Notably, a top validated peptide was enriched in patients with inflammatory bowel disease (IBD), suggesting potential shared microbial triggers between AS and IBD. Overall, StriMap provides a generalizable framework for rational immunotherapy design and for dissecting antigenic drivers of autoimmunity.

Author Info: (1) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (2) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Department of Molecular Biology, Massach

Author Info: (1) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (2) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States. (3) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (4) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (5) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (6) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States. (7) Broad Institute of MIT and Harvard, Cambridge, MA, United States. (8) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States. (9) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, United States. (10) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Massachusetts Institute of Technology, Cambridge, MA, United States. (11) Broad Institute of MIT and Harvard, Cambridge, MA, United States. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States. Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, United States. Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Boston, MA, United States.

Citation: Nat com 09/25/26

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/41959488

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Peripheral Blood as the Sole Source for Cancer Neoantigen and Reactive T-Cell Discovery Spotlight 

(1) Garcia-Garijo A (2) Creus-Gonz‡lez I (3) Levy PL (4) Moreno-C‡rdenas AB (5) Prieto-Fern‡ndez E (6) Lozano-Rabella M (7) Fajardo CA (8) Pujol-Borrell R (9) Mar’n-Bayo A (10) Kusnick J (11) Gonzalez J (12) Brujas C (13) Gartner JJ (14) Yuste-Estevanez A (15) Calahorro AM (16) Louhamane A (17) Fernandez J (18) Sanz-Pamplona R (19) Watkins TBK (20) Galvao V (21) Munoz-Couselo E (22) Ros J (23) ƒlez E (24) Oliveira M (25) Saura Manich C (26) Brana I (27) Oaknin A (28) Alemany R (29) Tabernero J (30) Perez-Lopez R (31) Turcotte S (32) Frankell AM (33) Garralda E (34) Toledo RA (35) Gros A

Cancer discovery

To expand the accessibility of neoantigen-based immunotherapy, Garcia-Garijo et al. integrated circulating tumor DNA (ctDNA) whole-exome sequencing (WES) to identify non-synonymous mutations (NSMs) with the isolation of neoantigen-specific T cells from circulating CD8+PD1hiCD38+ and CD4+PD1hi populations. In 8 patients with metastatic solid cancers, this strategy identified most lesion-derived NSMs (and additional neoantigens) enriched for clonal variants. In a cohort of 69 patients with metastatic solid cancers, neoantigen discovery based only on ctDNA seemed feasible in ~50% of patients (~85% of patients with colorectal cancer).

Contributed by Ute Burkhardt

(1) Garcia-Garijo A (2) Creus-Gonz‡lez I (3) Levy PL (4) Moreno-C‡rdenas AB (5) Prieto-Fern‡ndez E (6) Lozano-Rabella M (7) Fajardo CA (8) Pujol-Borrell R (9) Mar’n-Bayo A (10) Kusnick J (11) Gonzalez J (12) Brujas C (13) Gartner JJ (14) Yuste-Estevanez A (15) Calahorro AM (16) Louhamane A (17) Fernandez J (18) Sanz-Pamplona R (19) Watkins TBK (20) Galvao V (21) Munoz-Couselo E (22) Ros J (23) ƒlez E (24) Oliveira M (25) Saura Manich C (26) Brana I (27) Oaknin A (28) Alemany R (29) Tabernero J (30) Perez-Lopez R (31) Turcotte S (32) Frankell AM (33) Garralda E (34) Toledo RA (35) Gros A

Cancer discovery

To expand the accessibility of neoantigen-based immunotherapy, Garcia-Garijo et al. integrated circulating tumor DNA (ctDNA) whole-exome sequencing (WES) to identify non-synonymous mutations (NSMs) with the isolation of neoantigen-specific T cells from circulating CD8+PD1hiCD38+ and CD4+PD1hi populations. In 8 patients with metastatic solid cancers, this strategy identified most lesion-derived NSMs (and additional neoantigens) enriched for clonal variants. In a cohort of 69 patients with metastatic solid cancers, neoantigen discovery based only on ctDNA seemed feasible in ~50% of patients (~85% of patients with colorectal cancer).

Contributed by Ute Burkhardt

ABSTRACT: Neoantigen-targeted T-cell therapies require invasive tumor biopsies to identify neoantigens and reactive T cells, limiting their applicability and potentially underestimating tumor heterogeneity. We propose a novel strategy relying solely on peripheral blood to identify non-synonymous mutations via cell-free DNA whole-exome sequencing and isolate neoantigen-specific CD4+ and CD8+ T cells based on PD-1 and CD39 co-expression. Our method identified most neoantigens and increased the number of T-cell reactivities detected by standard biopsy-based techniques in an initial cohort of eight metastatic cancer patients. Critically, our approach uncovered additional neoantigens missed by tumor biopsy analysis, highlighting the potential for broader neoantigen targeting using liquid biopsies. Analysis of a cohort of 69 metastatic cancer patients revealed that approximately half could be eligible for our blood-only approach. This proof-of-concept study demonstrates the potential of using blood as a surrogate or complement for tumor biopsies to develop neoantigen-reactive T-cell therapies against a broader spectrum of neoantigens.

Author Info: (1) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (2) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://

Author Info: (1) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (2) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (3) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (4) Vall d'Hebron Institute of Oncology Spain. ROR: https://ror.org/054xx3904 (5) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (6) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (7) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (8) Universitat Aut˜noma de Barcelona Barcelona, Barcelona Spain. ROR: https://ror.org/052g8jq94 (9) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (10) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (11) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (12) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (13) National Institutes of Health United States. ROR: https://ror.org/01cwqze88 (14) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (15) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (16) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (17) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (18) Instituto de Investigaci—n Sanitaria Arag—n Zaragoza Spain. ROR: https://ror.org/03njn4610 (19) Stanford University Stanford, CA United States. ROR: https://ror.org/00f54p054 (20) Vall d'Hebron Institute of Oncology Barcelona Spain. ROR: https://ror.org/054xx3904 (21) Vall d'Hebron Institute of Oncology barcelona, barcelona, spain Spain. ROR: https://ror.org/054xx3904 (22) Vall d'Hebron Institute of Oncology (VHIO) Barcelona Spain. (23) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (24) Vall d'Hebron Institute of Oncology Barcelona Spain. ROR: https://ror.org/054xx3904 (25) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (26) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (27) Vall d'Hebron Institute of Oncology Barcelona Spain. ROR: https://ror.org/054xx3904 (28) Institut d'Investigaci— BiomŽdica de Bellvitge L'Hospitalet de Llobregat Spain. ROR: https://ror.org/0008xqs48 (29) Vall d'Hebron Institute of Oncology Barcelona Spain. ROR: https://ror.org/054xx3904 (30) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (31) Centre Hospitalier de l'UniversitŽ de MontrŽal Montreal Canada. ROR: https://ror.org/0410a8y51 (32) The Francis Crick Institute London United Kingdom. ROR: https://ror.org/04tnbqb63 (33) Vall d'Hebron Institute of Oncology Barcelona Spain. ROR: https://ror.org/054xx3904 (34) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904 (35) Vall d'Hebron Institute of Oncology Barcelona, Barcelona Spain. ROR: https://ror.org/054xx3904

Citation: Cancer Discov 2026 Sep 29 Epub09/29/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42806482

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Spatially confined IL-12 programs CAR-NK through mTORC1 to coordinate antitumor immune networks Spotlight 

(1) Tarannum M (2) Dinh K (3) Stanojevic M (4) Nguyen M (5) Campisi M (6) Maia A (7) Liu F (8) Yang S (9) Birch GC (10) Bobilev E (11) Gillanders I (12) Sheffer M (13) Gupta S (14) Wang J (15) Ganapathy S (16) Michaud DE (17) Dalton GN (18) Chugh S (19) Nguyen QD (20) Paweletz CP (21) Gokhale PC (22) Gao Y (23) Cancelas J (24) Guerriero JL (25) Choueiri TK (26) Barbie DA (27) Aguirre AJ (28) Porter RL (29) Matulonis UA (30) Koreth J (31) Wu CJ (32) Soiffer RJ (33) Ritz J (34) Chen J (35) Romee R

Cancer discovery

Tarannum et al. engineered mesothelin-targeted CAR-NK cells secreting IL-12 tethered to a collagen-binding A3 domain to spatially restrict IL-12 activity within the collagen I/III-rich TIME. IL-12 and CAR signaling converged through Ras-ERK and PI3K pathways to sustain mTORC1 activity, enhancing CAR-NK cell activation, proliferation, and metabolic fitness. Matrix-anchored IL-12 CAR-NK cells also activated bystander NK cells, T cells, and macrophages, without expanding Tregs. In ovarian and pancreatic cancer models, IL-12 CAR-NK cells achieved potent and durable antitumor responses, with limited systemic IL-12 toxicity.

Contributed by Shishir Pant

(1) Tarannum M (2) Dinh K (3) Stanojevic M (4) Nguyen M (5) Campisi M (6) Maia A (7) Liu F (8) Yang S (9) Birch GC (10) Bobilev E (11) Gillanders I (12) Sheffer M (13) Gupta S (14) Wang J (15) Ganapathy S (16) Michaud DE (17) Dalton GN (18) Chugh S (19) Nguyen QD (20) Paweletz CP (21) Gokhale PC (22) Gao Y (23) Cancelas J (24) Guerriero JL (25) Choueiri TK (26) Barbie DA (27) Aguirre AJ (28) Porter RL (29) Matulonis UA (30) Koreth J (31) Wu CJ (32) Soiffer RJ (33) Ritz J (34) Chen J (35) Romee R

Cancer discovery

Tarannum et al. engineered mesothelin-targeted CAR-NK cells secreting IL-12 tethered to a collagen-binding A3 domain to spatially restrict IL-12 activity within the collagen I/III-rich TIME. IL-12 and CAR signaling converged through Ras-ERK and PI3K pathways to sustain mTORC1 activity, enhancing CAR-NK cell activation, proliferation, and metabolic fitness. Matrix-anchored IL-12 CAR-NK cells also activated bystander NK cells, T cells, and macrophages, without expanding Tregs. In ovarian and pancreatic cancer models, IL-12 CAR-NK cells achieved potent and durable antitumor responses, with limited systemic IL-12 toxicity.

Contributed by Shishir Pant

ABSTRACT: Solid tumors evade immunotherapy because of immunosuppressive microenvironments that limit immune cell persistence and function. Although interleukin-12 (IL-12) potently activates antitumor immunity, its clinical use has been constrained by systemic toxicity. Here we engineered a CAR natural killer (NK) cell platform that integrated IL-12 signaling to enhance antitumor immunity. IL-12 signaling synergized with CAR activation to sustain mTORC1 activity through convergent Ras-ERK and PI3K pathways, promoting metabolic fitness, autonomous expansion, and sustained effector function. IL-12 also activated bystander NK cells, T cells, and macrophages to remodel the tumor microenvironment. To improve safety, IL-12 was tethered to a collagen-binding A3-domain, restricting its activity to the extracellular matrix and limiting systemic exposure. In ovarian and pancreatic cancer models, matrix-anchored IL-12 CAR NK cells expanded without exogenous cytokines and achieved durable tumor control. These findings suggest that mTORC1-mediated integration of CAR and cytokine signaling can enhance immune fitness and overcome immunosuppressive tumor microenvironments.

Author Info: (1) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (2) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86

Author Info: (1) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (2) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (3) University of Pittsburgh Pittsburgh, PA United States. ROR: https://ror.org/01an3r305 (4) Dana-Farber Cancer Institute United States. ROR: https://ror.org/02jzgtq86 (5) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (6) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (7) Dana Farber Cancer Institute Boston United States. (8) Dana-Farber Cancer Institute United States. ROR: https://ror.org/02jzgtq86 (9) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (10) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (11) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (12) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (13) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (14) Dana-Farber Brigham Cancer Center Boston, MA United States. ROR: https://ror.org/05rgrbr06 (15) Dana-Farber Cancer Institute Boston United States. ROR: https://ror.org/02jzgtq86 (16) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (17) Dana-Farber Cancer Institute United States. (18) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (19) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (20) Dana-Farber Cancer Institute Boston, Massachusetts United States. ROR: https://ror.org/02jzgtq86 (21) Dana-Farber Cancer Institute Boston United States. ROR: https://ror.org/02jzgtq86 (22) Skyline Therapeutics Cambridge, MA United States. (23) University of Cincinnati Medical Center Cincinnati United States. ROR: https://ror.org/02p72h367 (24) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (25) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (26) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (27) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (28) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (29) Dana-Farber Cancer Institute Boston, Massachusetts United States. ROR: https://ror.org/02jzgtq86 (30) Dana-Farber Cancer Institute Boston United States. ROR: https://ror.org/02jzgtq86 (31) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (32) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (33) Dana-Farber Cancer Institute Boston, MA United States. ROR: https://ror.org/02jzgtq86 (34) Massachusetts Institute of Technology Cambridge, MA United States. ROR: https://ror.org/042nb2s44 (35) Dana-Farber Cancer Institute, Harvard University Boston, MA United States.

Citation: Cancer Discov 2026 Sep 29 Epub09/29/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42810409

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IL-2/CD25 acts within the tumor microenvironment to reprogram tumor-specific cytotoxic CD8+ T cells while restraining regulatory T-cell accumulation

Spotlight 

(1) LaPorte KM (2) Pöder J (3) Ivanova D (4) Dalzell M (5) Serafini P (6) Villarino AV (7) Malek TR

Journal for immunotherapy of cancer | Free PMC Article

LaPorte et al. show that high-dose mouse IL-2/CD25 fusion protein (mIL-2/CD25) reprograms the CT26 and MC38 tumor microenvironments to favor tumor-specific CD8+ T cells over Tregs. HD mIL-2/CD25 promoted chemokine and inflammatory programs that increased intratumoral CD8+ T cell infiltration, clonal expansion, and differentiation into effector and stem-like states. In contrast, intratumoral Tregs showed impaired IL-2R signaling and effector Treg differentiation, failed to upregulate Foxp3 and CD25, and were prone to cell death. Combination with anti-PD-1 enhanced multiple tumor-specific CD8⁺ T cell effector programs and limited Treg infiltration.

Contributed by Shishir Pant

(1) LaPorte KM (2) Pöder J (3) Ivanova D (4) Dalzell M (5) Serafini P (6) Villarino AV (7) Malek TR

Journal for immunotherapy of cancer | Free PMC Article

LaPorte et al. show that high-dose mouse IL-2/CD25 fusion protein (mIL-2/CD25) reprograms the CT26 and MC38 tumor microenvironments to favor tumor-specific CD8+ T cells over Tregs. HD mIL-2/CD25 promoted chemokine and inflammatory programs that increased intratumoral CD8+ T cell infiltration, clonal expansion, and differentiation into effector and stem-like states. In contrast, intratumoral Tregs showed impaired IL-2R signaling and effector Treg differentiation, failed to upregulate Foxp3 and CD25, and were prone to cell death. Combination with anti-PD-1 enhanced multiple tumor-specific CD8⁺ T cell effector programs and limited Treg infiltration.

Contributed by Shishir Pant

BACKGROUND: Targeting the high-affinity interleukin-2 receptor (IL-2R) on CD8(+) T effector cells elicits potent antitumor responses that are augmented when co-administered with programmed cell death protein 1 (PD-1) blockade. METHODS: Using the mouse IL-2/CD25 fusion protein (mIL-2/CD25) at a high dose (HD) and anti-PD-1 checkpoint blockade, with the CT26 and MC38 colon carcinomas as models, the current study investigated how antitumor responses occurred when regulatory T cells (Tregs) are also a target of HD mIL-2/CD25. Single-cell RNA sequencing (scRNA-seq) and T-cell receptor (TCR) repertoire analysis of tumor-associated immune cells were used to identify how combination therapy reshaped the tumor microenvironment (TME). These data were cross-referenced with published datasets to (1) corroborate TCR specificity and (2) identify how CD8(+) T-cell differentiation is affected by different IL-2/PD-1 strategies. RESULTS: Here, we show that effective antitumor immunity by the combination therapy is a result of HD mIL-2/CD25-dependent reprogramming of CD8(+) tumor-specific T cells that increases their function and supports their expansion within the TME, the latter also shaped by PD-1 blockade. This therapy supports antitumor responses by chemokines and inflammatory cytokines that selectively favor the migration of CD8(+) T cells but not Tregs deep within the tumor. After HD mIL-2/CD25 treatment, Tregs within the TME showed impaired downstream IL-2R signaling, reflected by failed upregulation of forkhead box P3 and CD25, impaired development into effector Tregs, and enhanced cell death, the latter which likely offsets Treg proliferation. Many similarities were noted after direct comparison of these scRNA-seq findings with another study where IL-2 activity was targeted to PD-1(+) CD8(+) T cells. Notably, HD mIL-2/CD25 and anti-PD-1 combination promotes effector and 'stem-like' CD8(+) T-cell subsets, perhaps even to a greater extent than the PD-1-targeted IL-2 strategy. CONCLUSIONS: The efficient differentiation of exhausted CD8(+) T cells into highly functional cells and the resulting potent antitumor responses by HD mIL-2/CD25 plus anti-PD-1 suggest that this approach may augment durable response rates more than currently achieved with checkpoint blockade monotherapy.

Author Info: (1) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. Laboratory of Allergic Diseases, National Institute of Allergy and

Author Info: (1) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. Laboratory of Allergic Diseases, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA. (2) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. (3) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. (4) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. (5) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. (6) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA. (7) Department of Microbiology & Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA tmalek@med.miami.edu.

Citation: J Immunother Cancer 2026 Sep 29 14: Epub09/29/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42810810

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Bridging innate and adaptive immunity- A bispecific SIRPαD1-αPCSK9 fusion protein reprograms macrophages for durable tumor clearance

Spotlight 

(1) Xu C (2) Zhou K (3) Hu X (4) Nan Y (5) Sun Y (6) Dou Z (7) Zhou R (8) Xue W (9) Hu Q (10) Huang X (11) Hua X (12) Ju D (13) Zhang X

Cell reports. Medicine

Focused on improving macrophage-directed immunotherapy, Xu and Zhou et al. found that blocking CD47-SIRPα upregulated tumor-expressed, secreted PCSK9, resulting in macrophage MHC-1 degradation, impaired antigen presentation, and reduced CD8+T cell activation. To overcome this resistance, a bispecific SIRPαD1–anti-PCSK9 Ab fusion co-targeting CD47 and PCSK9 enhanced phagocytosis, preserved antigen cross-presentation to CD8+ T cells, reprogrammed TIME macrophages to an M1 state, and achieved potent tumor control in preclinical models. The fusion protein exhibited superior tumor targeting (via SIRPα) and had a favorable safety profile.

Contributed by Katherine Turner

(1) Xu C (2) Zhou K (3) Hu X (4) Nan Y (5) Sun Y (6) Dou Z (7) Zhou R (8) Xue W (9) Hu Q (10) Huang X (11) Hua X (12) Ju D (13) Zhang X

Cell reports. Medicine

Focused on improving macrophage-directed immunotherapy, Xu and Zhou et al. found that blocking CD47-SIRPα upregulated tumor-expressed, secreted PCSK9, resulting in macrophage MHC-1 degradation, impaired antigen presentation, and reduced CD8+T cell activation. To overcome this resistance, a bispecific SIRPαD1–anti-PCSK9 Ab fusion co-targeting CD47 and PCSK9 enhanced phagocytosis, preserved antigen cross-presentation to CD8+ T cells, reprogrammed TIME macrophages to an M1 state, and achieved potent tumor control in preclinical models. The fusion protein exhibited superior tumor targeting (via SIRPα) and had a favorable safety profile.

Contributed by Katherine Turner

ABSTRACT: Macrophage-directed immunotherapy, exemplified by blocking the CD47-signal regulatory protein α (SIRPα) axis, can eliminate tumors by unleashing phagocytosis. However, such approaches often fail to generate durable antitumor immunity, revealing a disconnect between innate activation and effective T cell responses. Here, we identify proprotein convertase subtilisin/kexin type 9 (PCSK9) as an adaptive resistance factor induced by macrophage checkpoint blockade. Tumor-derived PCSK9 promotes lysosomal degradation of major histocompatibility complex class I (MHC-I) in macrophages, impairing antigen cross-presentation and CD8+ T cell priming-thus showing how phagocytosis-targeted therapies can paradoxically suppress adaptive immunity. To overcome this, we engineer bispecific fusion proteins co-targeting the CD47-SIRPα checkpoint and the PCSK9-MHC-I axis, among which SIRPαD1-αPCSK9 is optimal. Dual targeting synergistically enhances phagocytosis, preserves antigen cross-presentation, and reprograms tumor microenvironment toward an immunostimulatory state. Consequently, SIRPαD1-αPCSK9 activates innate and adaptive antitumor immunity, achieving potent tumor control with improved safety. These findings uncover a resistance mechanism to macrophage-centered cancer immunotherapy and establish a dual-targeting strategy bridging phagocytosis and T cell activation.

Author Info: (1) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China; Quzhou Fudan Institute, 108 Minjiang Avenue,

Author Info: (1) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China; Quzhou Fudan Institute, 108 Minjiang Avenue, Kecheng District Quzhou, Zhejiang, China. (2) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China; Quzhou Fudan Institute, 108 Minjiang Avenue, Kecheng District Quzhou, Zhejiang, China. (3) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (4) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (5) Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China. (6) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (7) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (8) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (9) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (10) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China. (11) Department of Cancer Biology, Abramson Family Cancer Research Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. Electronic address: huax@pennmedicine.upenn.edu. (12) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China; Quzhou Fudan Institute, 108 Minjiang Avenue, Kecheng District Quzhou, Zhejiang, China. Electronic address: dianwenju@fudan.edu.cn. (13) School of Pharmaceutical Sciences & Shanghai Engineering Research Center of Immunotherapeutics, Fudan University, Shanghai, China; Quzhou Fudan Institute, 108 Minjiang Avenue, Kecheng District Quzhou, Zhejiang, China. Electronic address: xuyaozhang@fudan.edu.cn.

Citation: Cell Rep Med 2026 Oct 5 103087 Epub10/05/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42833217

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Senescence-directed nanotherapy ameliorates fibrosis and overcomes immune exclusion in cancer Spotlight 

(1) Hinterleitner C (2) Barthet VJA (3) Goldberg HV (4) Vogt KC (5) Perea AM (6) Hillger LR (7) Ruiz S (8) McHugh D (9) Ho YJ (10) Chaves-Perez A (11) Skamagki M (12) Flowers S (13) Styers HC (14) Rekhtman N (15) Zhuang X (16) Dessotti Barretto G (17) Li X (18) Watson JT (19) Luan W (20) Simon J (21) Tammela T (22) Gardner R (23) Rudin CM (24) Romesser PB (25) Bott MJ (26) Filliol A (27) Heller DA (28) Lowe SW

Science

Hinterleitner, Barthet, and Goldberg et al. showed that senescent-like cells in fibrotic human and mouse tissues expressed P-selectin, and the team developed fucoidan-based senescence-modulating nanoparticles (SMNPs) to target these cells. SMNPs selectively depleted P-selectin+ senescent-like macrophages (Sen+MP) and reduced liver and lung fibrosis with limited toxicities. In fibrotic liver and lung tumor models, SMNPs remodeled stromal and myeloid barriers, increased DC and T cell infiltration, and improved response to ICB. P-selectin+ Sen+MP were enriched in immune-excluded human tumors and correlated with poor response to neoadjuvant ICB plus chemotherapy.

Contributed by Shishir Pant

(1) Hinterleitner C (2) Barthet VJA (3) Goldberg HV (4) Vogt KC (5) Perea AM (6) Hillger LR (7) Ruiz S (8) McHugh D (9) Ho YJ (10) Chaves-Perez A (11) Skamagki M (12) Flowers S (13) Styers HC (14) Rekhtman N (15) Zhuang X (16) Dessotti Barretto G (17) Li X (18) Watson JT (19) Luan W (20) Simon J (21) Tammela T (22) Gardner R (23) Rudin CM (24) Romesser PB (25) Bott MJ (26) Filliol A (27) Heller DA (28) Lowe SW

Science

Hinterleitner, Barthet, and Goldberg et al. showed that senescent-like cells in fibrotic human and mouse tissues expressed P-selectin, and the team developed fucoidan-based senescence-modulating nanoparticles (SMNPs) to target these cells. SMNPs selectively depleted P-selectin+ senescent-like macrophages (Sen+MP) and reduced liver and lung fibrosis with limited toxicities. In fibrotic liver and lung tumor models, SMNPs remodeled stromal and myeloid barriers, increased DC and T cell infiltration, and improved response to ICB. P-selectin+ Sen+MP were enriched in immune-excluded human tumors and correlated with poor response to neoadjuvant ICB plus chemotherapy.

Contributed by Shishir Pant

ABSTRACT: Fibrotic remodeling of tissues and tumors establishes immunosuppressive microenvironments that drive organ dysfunction and, in cancer, limit response to immunotherapy. Senescent-like cells are conserved drivers of fibrosis and therapeutic targets, yet their functional heterogeneity complicates therapeutic intervention. Here, we show that P-selectin is expressed by a subset of senescent-like cells in fibrotic tissues and tumors. Leveraging fucoidan-based nanoparticles that bind P-selectin, we developed senescence-modulating nanoparticles (SMNPs) to selectively target these disease-associated states. SMNPs exerted potent antifibrotic and immunomodulatory effects while improving the therapeutic index. Mechanistically, we identified a pathogenic, immunosuppressive macrophage population as a functional target in vivo. In fibrotic tumors, niche remodeling restored immune infiltration and sensitized tumors to immune checkpoint-based therapies. These findings establish SMNPs as a generalizable strategy to target pathogenic senescent cell subsets across fibrosis and cancer.

Author Info: (1) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (2) Cancer Biology and Genetics Program, Sloan Ketter

Author Info: (1) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (2) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (3) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA. (4) Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (5) Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Cancer Engineering Program, Gerstner Sloan Kettering School for Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (6) Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (7) Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA. Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (8) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (9) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (10) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (11) Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (12) Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (13) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Cancer Engineering Program, Gerstner Sloan Kettering School for Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (14) Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (15) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (16) Flow Cytometry Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (17) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (18) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (19) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (20) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (21) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (22) Flow Cytometry Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (23) Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (24) Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Early Drug Development Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (25) Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (26) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (27) Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA. Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (28) Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Citation: Science 2026 Sep 24 393:eaeg4791 Epub09/24/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42784692

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Computational design of optimized and preferentially paired human TCR constant regions for improved T cell function Spotlight 

(1) Radman M (2) Shamul-Raybi A (3) Parker J (4) Fleishman SJ (5) Cohen CJ

Science advances | Free PMC Article

Using a computational strategy, Radman et al. mutated the constant and transmembrane regions of the MART-1 DMF4 TCR α/β chains to reduce mispairing and improve expression. TCR variants were found that increased expression and TNFα production against MART-1+ cells compared to the WT TCR, and the modified α/β chains expressed better together than with their WT counterparts. Modified TCR-T cells generated by retroviral vector had superior cytokine production to WT TCR-T (in bulk T cells and CD4+ or CD8+ T cells), as well as cytotoxicity and in vivo efficacy. This same strategy was successfully applied to other antitumor and antiviral TCRs.

Contributed by Alex Najibi

(1) Radman M (2) Shamul-Raybi A (3) Parker J (4) Fleishman SJ (5) Cohen CJ

Science advances | Free PMC Article

Using a computational strategy, Radman et al. mutated the constant and transmembrane regions of the MART-1 DMF4 TCR α/β chains to reduce mispairing and improve expression. TCR variants were found that increased expression and TNFα production against MART-1+ cells compared to the WT TCR, and the modified α/β chains expressed better together than with their WT counterparts. Modified TCR-T cells generated by retroviral vector had superior cytokine production to WT TCR-T (in bulk T cells and CD4+ or CD8+ T cells), as well as cytotoxicity and in vivo efficacy. This same strategy was successfully applied to other antitumor and antiviral TCRs.

Contributed by Alex Najibi

ABSTRACT: T cell receptor (TCR) gene transfer is a promising approach for cancer immunotherapy, but its efficacy is limited by mispairing of TCR chains, which reduces surface expression and may generate off-target specificities. We applied the PROSS and FuncLib algorithms to engineer human TCR constant regions for improved stability and preferential pairing. After several screening rounds, we identified a variant, termed structurally enhanced TCR (SET), that exhibited markedly enhanced surface expression, functional avidity, and reduced mispairing. SET-expressing T cells secreted higher cytokine levels, displayed increased activation, and mediated superior cytotoxicity. Notably, SET demonstrated function in CD4(+) T cells and mediated potent tumor control in xenograft models, significantly delaying tumor growth and improving survival. SET's benefits were reproducible across six different TCRs, supporting its broad applicability. These findings highlight the potential of rational design to improve the potency of TCR-based therapies.

Author Info: (1) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (2) The Laboratory of Tumor

Author Info: (1) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (2) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel. (3) Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel. (4) Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel. (5) The Laboratory of Tumor Immunology and Immunotherapy, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel.

Citation: Sci Adv 2026 Sep 25 12:eaeb9189 Epub09/23/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42777048

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Functional evaluation of TCR-pMHC pairs at scale allows in silico TCR reactivity prediction Featured  

(1) Messemaker M (2) Kwee BPY (3) Moravec _ (4) de Paauw S (5) Urbanus J (6) çlvarez-Salmoral D (7) Geerligs J (8) Xie R (9) Voogd R (10) Morris B (11) Guislain A (12) Winkler Y (13) Richterich CA (14) Mussmann M (15) Bakker M (16) Steinmetz M (17) Iras M (18) Marcus E (19) Teuwen J (20) Perrakis A (21) Beijersbergen RL (22) Scheper W (23) Schumacher TN

Immunity

Messemaker and Kwee et al. developed a TCR rapid assembly platform (T-RAP) and used it to generate a dataset of functionally validated TCR-pMHC pairs, which enabled the assembly of diverse and standardized TCR libraries and allowed for structure-based prediction of TCR-pMHC reactivity. Pooled screening of these TCR libraries could then be used to evaluate the quality of existing reactivity prediction models, including tcrdist3 and AlphaFold3, showed strong capacities for distinguishing reactivity and could be used both to pair TCRs with cognate pMHC epitopes and to shortlist TCRs with reactivity to patient-specific neoantigens, without any task-specific training.

(1) Messemaker M (2) Kwee BPY (3) Moravec _ (4) de Paauw S (5) Urbanus J (6) çlvarez-Salmoral D (7) Geerligs J (8) Xie R (9) Voogd R (10) Morris B (11) Guislain A (12) Winkler Y (13) Richterich CA (14) Mussmann M (15) Bakker M (16) Steinmetz M (17) Iras M (18) Marcus E (19) Teuwen J (20) Perrakis A (21) Beijersbergen RL (22) Scheper W (23) Schumacher TN

Immunity

Messemaker and Kwee et al. developed a TCR rapid assembly platform (T-RAP) and used it to generate a dataset of functionally validated TCR-pMHC pairs, which enabled the assembly of diverse and standardized TCR libraries and allowed for structure-based prediction of TCR-pMHC reactivity. Pooled screening of these TCR libraries could then be used to evaluate the quality of existing reactivity prediction models, including tcrdist3 and AlphaFold3, showed strong capacities for distinguishing reactivity and could be used both to pair TCRs with cognate pMHC epitopes and to shortlist TCRs with reactivity to patient-specific neoantigens, without any task-specific training.

ABSTRACT: Accurate prediction of T cell receptor (TCR) reactivity is a long-standing goal in immunology. Here, we asked whether functional validation of TCR-peptide-major histocompatibility complex (MHC) (TCR-pMHC) pairs at scale alters performance estimates of TCR-pMHC reactivity prediction models. We developed a TCR rapid assembly platform (T-RAP) that allowed the generation of large and uniform TCR libraries. T-RAP enabled evaluation of TCR signaling or MHC multimer binding of thousands of previously reported TCR-pMHC pairs under standardized conditions. In this setting of systematic standardized evaluation, only _50% of these TCRs showed the previously reported TCR reactivity. Notably, AlphaFold3 structural predictions showed good performance in identifying reactive TCR-pMHC pairs within the set of TCRs that experimentally validated without any task-specific training. AlphaFold3 structural predictions could likewise be used to shortlist TCRs reactive to patient-specific cancer neoantigens. In silico prediction of TCR-pMHC reactivity thus has greater feasibility than previously assumed, with implications for basic research and clinical application.

Author Info: (1) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (2) Division of Molecular

Author Info: (1) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (2) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (3) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (4) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (5) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (6) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (7) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands; The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (8) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (9) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (10) The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (11) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (12) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (13) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (14) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (15) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (16) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (17) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands. (18) AI for Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (19) AI for Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (20) Oncode Institute, Utrecht, the Netherlands; Division of Biochemistry, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (21) The NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (22) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. (23) Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Oncode Institute, Utrecht, the Netherlands; Department of Hematology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: t.schumacher@nki.nl.

Citation: Immunity 2026 Oct 1 Epub10/01/2026

Link to PUBMED: http://www.ncbi.nlm.nih.gov/pubmed/42822443

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