Journal Articles

Predicability of PD-L1 expression in cancer cells based solely on H&E-stained sections

PD-L1 expression is an important biomarker for selecting patients who are eligible for immune checkpoint inhibitor (ICI) therapy. However, evaluating PD-L1 through immunohistochemistry often faces significant interobserver variability and requires considerable time and resources. Recent advancements in artificial intelligence (AI) have transformed the field of pathology, leading to more standardized and reproducible methods for biomarker quantification. In this study, we examine the application of AI-driven models, particularly deep learning algorithms, to predict PD-L1 expression directly from hematoxylin and eosin-stained histological slides. Several AI-based approaches have been studied, demonstrating high accuracy in estimating PD-L1 expression and predicting responses to ICIs across various cancer types. AI-driven assessments of PD-L1 have been shown to reduce the subjectivity associated with manual scoring methods, such as the Tumor Proportion Score and the Combined Positive Score. Moreover, integrating AI with multimodal data, including genomics, radiomics, and real-world clinical data, can further enhance predictive accuracy and improve patient stratification for immunotherapy. Finally, AI-driven computational pathology offers a transformative approach to biomarker evaluation, providing a faster, more objective, and cost-effective alternative to traditional methods, with significant implications for personalized oncology and precision medicine. Despite these promising results, several challenges remain to be addressed, such as the need for large-scale validation, standardization of AI models, and regulatory approvals for clinical implementation. Tackling these issues will be crucial for incorporating AI-based PD-L1 assessments into routine pathology workflows.

Author Info: (1) Department of Medical Sciences and Public Health, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. Department of Biology, College of Science and Technology, Temple Un

Author Info: (1) Department of Medical Sciences and Public Health, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. Department of Biology, College of Science and Technology, Temple University, Philadelphia, PA 19122, USA. (2) Department of Electrical and Electronic Engineering, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. (3) Medical Oncology Unit, University Hospital of Cagliari, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. (4) Medical Oncology Unit, University Hospital of Cagliari, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. (5) Department of Pathology, Ospedale Oncologico A. Businco, ARNAS G. Brotzu, Cagliari, Italy. (6) Department of Medical Sciences and Public Health, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. (7) Medical Oncology Unit, University Hospital of Cagliari, Universitˆ degli Studi di Cagliari, 09123 Cagliari, Italy. (8) National Cancer Institute, Kyiv, Ukraine. Associazione "Angela Serra" per la ricerca sul cancro, Modena, Italy. (9) Department of Medicine - DIMED; General Anatomic Pathology and Cytopathology Unit, Universitˆ degli Studi di Padova, 35121 Padova, Italy.

mRNA-engineered T lymphocytes secreting bispecific T cell engagers with therapeutic potential in solid tumors

BACKGROUND: In the last decade, chimeric antigen receptor (CAR)-modified T cells have revolutionized the treatment of hematologic malignancies. However, antitumor responses in solid tumors remain poor, and the difficulty in finding truly tumor-specific target antigens leads to a high risk of on-target/off-tumor toxicity. Transient modification with mRNA is gaining momentum as an alternative approach to viral transduction in order to achieve a better safety profile. On the other hand, generation of T cells secreting bispecific T cell engagers (TCEs) has been reported to outperform the antitumor efficacy of T lymphocytes expressing membrane-anchored CARs, due to the ability of the soluble TCEs to recruit unmodified bystander T cells. METHODS: We have electroporated human primary T cells with in vitro transcribed mRNA encoding an anti-EGFR x anti-CD3 bispecific T cell engager. Such mRNA-modified T cells (STAR(EGFR)-T cells) have been analyzed for anti-EGFR bispecific TCE secretion and for their ability to drive anti-tumor responses against EGFR-expressing cells, both in vitro and in vivo. RESULTS: STAR(EGFR)-T cells transiently secrete bispecific TCEs capable of redirecting T lymphocytes to exert tumor cell-specific killing in in vitro assays. Moreover, STAR(EGFR)-T cells efficiently control tumor growth in in vivo xenograft models of solid malignancy. CONCLUSIONS: Our results strongly support mRNA-engineered TCE-secreting T cells as a promising therapeutic strategy for solid tumors.

Author Info: (1) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n San

Author Info: (1) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. (2) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. (3) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. (4) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. (5) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. (6) Animal Facility, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. (7) Department of Pathology, Hospital Universitario 12 de Octubre, Madrid, Spain. Department of Pathology, Universidad Complutense, Madrid, Spain. Cutaneous Oncology Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro de Investigaci—n BiomŽdica en Red en Oncolog’a (CIBERONC), Madrid, Spain. (8) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. Banc de Sang i Teixits, Barcelona, Spain. (9) Cancer Immunotherapy Unit, Department of Immunology, Hospital Universitario12 de Octubre, Madrid, Spain. Immuno-Oncology and Immunotherapy Group, Instituto de Investigaci—n Sanitaria 12 de Octubre (imas12), Madrid, Spain. Centro Nacional de Investigaciones Oncol—gicas-Hospital del Mar Research Institute Barcelona (CNIO-HMRIB) Cancer Immunotherapy Clinical Research Unit, Centro Nacional de Investigaciones Oncol—gicas (CNIO), Madrid, Spain. Red Espa–ola de Terapias Avanzadas (TERAV), Instituto de Salud Carlos III, Madrid, Spain.

Structural mechanism of anti-MHC-I antibody blocking of inhibitory NK cell receptors in tumor immunity

Anti-major histocompatibility complex class I (MHC-I) mAbs can stimulate immune responses to tumors and infections by blocking suppressive signals delivered via various immune inhibitory receptors. To understand such functions, we determined the structure of a highly cross-reactive anti-human MHC-I mAb, B1.23.2, in complex with the MHC-I molecule HLA-B*44:05 by both cryo-electron microscopy (cryo-EM) and X-ray crystallography. Structural models determined by the two methods were essentially identical revealing that B1.23.2 binds a conserved region on the _21 helix that overlaps the killer immunoglobulin-like receptor (KIR) binding site. Structural comparison to KIR/HLA complexes reveals a mechanism by which B1.23.2 blocks inhibitory receptor interactions, leading to natural killer (NK) cell activation. B1.23.2 treatment of the human KLM-1 pancreatic cancer model in humanized (NSG-IL15) mice provides evidence of suppression of tumor growth. Such anti-MHC-I mAb that block inhibitory KIR/HLA interactions may prove useful for tumor immunotherapy.

Author Info: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

Author Info: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

Discovery of a small molecule TLR3 agonist adjuvant

Pattern-recognition receptor (PRR) agonists are valuable agents across multiple medical applications, from vaccinology to immune-oncology. However, well-defined and potent small molecule agonists for many PRRs still await discovery and development. Screening of chemical libraries of ~200,000 small molecules for maturation of human monocytic cells by quantifying NF-_B activation and cell adherence was completed. From this screen, we selected a thiazole benzamide derivative, PVP-057, for its robust immunomodulatory properties, low toxicity profile, and concentration-dependent activity. In vitro investigation of pathway and receptor activation reveals that PVP-057 is a Toll-like receptor 3 (TLR3) agonist. As a single-component adjuvant, administered intramuscularly or intradermally to female mice, PVP-057 enhances long-term humoral immunogenicity of varicella-zoster virus glycoprotein E to levels comparable to those induced by the clinical grade standard benchmark adjuvant, AS01B, while concurrently inducing cell-mediated immunity. To demonstrate the large-scale and precise synthesis necessary for the efficient mass production of a small molecule agonist, a green chemistry approach was completed, devising a three-step, 24-hour synthesis scheme for PVP-057, with a reliable purity of ~98%. Featuring highly efficient and scalable synthesis, a distinct TLR3-dependent mechanism of action, and robust adjuvanticity, the PVP-057 pharmacophore has prophylactic and therapeutic potential.

Author Info: (1) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (2) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (3) Precision Vaccines Pro

Author Info: (1) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (2) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (3) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (4) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. Center for Green Chemistry and Department of Chemistry, University of Massachusetts Boston, Boston, MA, USA. (5) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (6) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (7) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Generate Biomedicines, Somerville, MA, USA. (8) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (9) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (10) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (11) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (12) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (13) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (14) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (15) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (16) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (17) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (18) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (19) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (20) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (21) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (22) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (23) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (24) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (25) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (26) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. (27) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (28) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. (29) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, USA. (30) Dana-Farber Cancer Institute, Boston, MA, USA. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA. (31) Dana-Farber Cancer Institute, Boston, MA, USA. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA. (32) Center for Green Chemistry and Department of Chemistry, University of Massachusetts Boston, Boston, MA, USA. (33) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. Broad Institute of MIT & Harvard, Cambridge, MA, USA. (34) Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA. David.Dowling@childrens.harvard.edu. Department of Pediatrics, Harvard Medical School, Boston, MA, USA. David.Dowling@childrens.harvard.edu.

Development of a high-affinity anti-ROR1 variable region for broad anti-cancer immunotherapy

Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is an emerging target in cancer immunotherapy, recognized for its consistent and elevated expression across several epithelial tumors, including triple-negative breast cancer (TNBC). TNBC is an aggressive and difficult-to-treat cancer, with limited effective therapeutic options currently available. Therapeutic approaches centered on targeting ROR1 have therefore become increasingly popular, with ROR1 chimeric antigen receptor (CAR) T cells currently in clinical trials to treat TNBC patients. While ROR1-targeting therapies have shown promising preclinical results, single arm treatment has often shown low efficacy as well as off-target toxicity. Natural killer (NK) cell-based immunotherapies, such as antibody-dependent cell cytotoxicity-inducing monoclonal antibodies and CAR NK cells, have also been shown to induce cancer cell cytotoxicity; however, with less toxicity compared with CAR T cells. Here, we developed and characterized a phage-derived single-chain fragment variable (scFv) against a highly specific ROR1 region and generated scFv-derived chimeric monoclonal antibodies and anti-ROR1-CAR NK cells, which show anti-cancer efficacy against TNBC cells. Additionally, we found TGF-_ inhibition using either small-molecule inhibitors or CRISPR-Cas9-edited NK cells could further enhance ROR1-targeting therapy persistence and efficacy in controlling TNBC tumor growth.

Author Info: (1) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (2) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (3)

Author Info: (1) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (2) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (3) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (4) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (5) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (6) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (7) Queensland Cyber Infrastructure Foundation Ltd (QCIF) Bioinformatics, Brisbane, QLD 4072, Australia. (8) Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia, QLD 4067, Australia; BASE Facility, University of Queensland, St Lucia, QLD 4067, Australia. (9) Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia, QLD 4067, Australia. (10) Laborat—rio de Patologia Experimental, Curitiba, Queensland 80215-901, Brazil. (11) Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia, QLD 4067, Australia; BASE Facility, University of Queensland, St Lucia, QLD 4067, Australia. (12) Mater Research Institute, The University of Queensland, Brisbane, QLD 4102, Australia. (13) Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010, Australia. (14) Olivia Newton-John Cancer Research Institute, Heidelberg, VIC 3084, Australia. (15) Olivia Newton-John Cancer Research Institute, Heidelberg, VIC 3084, Australia. (16) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (17) UQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Herston, QLD 4029, Australia. (18) UQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Herston, QLD 4029, Australia. (19) UQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Herston, QLD 4029, Australia; School of Biomedical Sciences, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Saint Lucia, QLD 4067, Australia. (20) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (21) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia; School of Science & Technology, University of New England, Armidale NSW 2351, Australia. (22) Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia, QLD 4067, Australia. (23) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. (24) Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia. Electronic address: f.guimaraes@uq.edu.au.

Structure guided analysis of KRAS G12 mutants in HLA-A*11:01 reveals a length encoded immunogenic advantage in G12D

KRAS G12 mutations are frequent oncogenic drivers, yet their differential immunogenicity complicates T cell-based therapies. Here, we integrate structural, biophysical, and functional analyses to examine how KRAS G12 variants remodel peptide-MHC-I (pMHC) architecture and T cell receptor (TCR) recognition. Using HLA-A*11:01, we show that single residue substitutions at position 12 induce distinct conformational changes in the MHC groove, with G12D uniquely destabilizing the complex through a buried aspartate side chain. Notably, G12D peptides adopt two registers, a 9-mer and a 10-mer, that diverge sharply in structure and immunogenicity. The 10-mer forms a compact, stable pMHC with a TCR-accessible surface, while the 9-mer adopts a bent conformation incompatible with recognition. Molecular dynamics and NMR titration confirm the superior stability and binding affinity of the 10-mer. These results highlight how peptide length and conformation critically shape immune visibility, offering mechanistic insight for optimizing TCR-T therapies against elusive neoantigens like KRAS G12D.

Author Info: (1) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (2) Department of Anesthesiology, Putuo People's Hospital, School

Author Info: (1) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (2) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (3) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (4) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (5) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. (6) Hangzhou Weizhi Biotechnology Co., Ltd, Hangzhou, China. (7) Tongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China. (8) Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China. (9) State key laboratory of natural and biomimetic drugs, Peking University Health Science Center, Beijing, China. (10) National Facility for Protein Science in Shanghai, ZhangJiang lab, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China. (11) Tianjin Key Laboratory of Technologies Enabling Development of Clinical Therapeutics and Diagnostics, School of Pharmacy, Tianjin Medical University, Tianjin, China. (12) Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China. kx2129@tongji.edu.cn. (13) Department of Anesthesiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China. lzhao@tongji.edu.cn.

IL-12 and GM-CSF engineered dendritic cells enhance the enrichment and selection of tumor-reactive T cells for cancer immunotherapy

The use of tumor-reactive T cells in targeted tumor elimination holds significant potential for cancer immunotherapy, such as Tumor-Infiltrating Lymphocyte (TIL) therapy and TCR-T adoptive immunotherapy. Critical aspects of the effective clinical application of these immunotherapies include the enrichment and selection of tumor antigens and their corresponding reactive T cells. However, current in vitro methods for expanding and screening tumor antigen-reactive T cells remain inefficient. One reason for this inefficiency is the dysfunctional state of tumor-reactive T cells, which limits their expansion and activation. To address this challenge, we developed an optimized dendritic cell-based culture system, in which dendritic cells simultaneously express interleukin-12 and granulocyte-macrophage colony-stimulating factor (12GM-DCs), to enhance the expansion of tumor-reactive T cells. We found that 12GM-DCs can enrich reactive T cells targeting various tumor antigens, including virus-associated tumor antigens, tumor-associated antigens, mutant tumor neoantigens, and patient-specific tumor neoantigens. Moreover, 12GM-DCs increased the proportion of antigen-specific T cells, enhanced the activation of those T cells, and promoted the maintenance of a memory phenotype. The cytotoxicity of these antigen-reactive T cells was increased after co-culture with 12GM-DCs, likely due to the increased secretion of interferon-_ and granzyme B. Importantly, these functions and phenotypic advantages of tumor antigen-reactive T cells derived from the 12GM-DC culture system could be effectively maintained and the antitumor activity was also enhanced in tumor-burden mice. Our 12GM-DC coculture system effectively enriches antigen-specific T cells and has the potential to advance the clinical application of cancer immunotherapy by targeting tumor antigens and their reactive T cells.

Author Info: (1) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (2) Depa

Author Info: (1) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (2) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China. (3) Department of Gastrointestinal Surgery, Peking University Shougang Hospital, Beijing, China. (4) School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China. (5) School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China. (6) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (7) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (8) Department of Gastrointestinal Surgery, Peking University Shougang Hospital, Beijing, China. (9) School of Life Sciences, Peking University, Beijing, China. (10) Department of Gastrointestinal Surgery, Peking University Shougang Hospital, Beijing, China. (11) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (12) School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China. (13) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. (14) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. School of Life Sciences, Peking University, Beijing, China. (15) Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, China. Department of Cell Biology and Stem Cell Research Center, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking University, Beijing, China. Changping Laboratory, MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.

Scalable Exosome Isolation Platform for Clinical-Scale Therapeutics: Bridging Gaps in Drug Delivery and Regenerative Medicine

Exosomes are essential for facilitating intercellular communication. The importance of these molecules lies in the fact that they can transport bioactive molecules across cells, influencing critical physiological processes such as immune responses, tissue repair, and cell proliferation. In addition to their physiological roles, exosomes are also involved in various pathological conditions, including carcinoma, respiratory, neurodegeneration and cardiovascular diseases. They can convey signals that may promote tumor growth, metastasis, or immune evasion in cancer. This study suggests a unique scalable platform for effective exosome isolation based on functionalised SiO(2) wafers. Gold nanoparticles (GNPs) with diameters of 20 nm and 60 nm were synthesized and deposited on SiO(2) wafers before being PEGylated and conjugated with antibodies. The platform successfully isolated exosomes employing antibodies against CD9, CD81, and CD63, with CD63-coated wafers providing the most exosomes, in accordance with their abundance on the exosomal surface. NTA revealed the presence of exosomes. A 1 cm x 1 cm SiO(2) wafers successfully isolated 3.3 x 10(8) exosomes from 100 µL serum. A 2 cm x 2 cm wafer demonstrated a significant increase in isolation efficiency, capturing 7.2 x 10(8) exosomes from 200 µL serum, highlighting the scalability and potential for high-throughput exosome isolation using this platform. The average size of isolated exosomes ranged from 40 to 150 nm. This scalable technology offers a promising alternative to ultracentrifugation for exosome isolation. It has potential uses in the delivery of drugs and other biomedical fields.Clinical Relevance- This work enables scalable exosome isolation, critical for advancing therapies in drug delivery, neurodegenerative diseases, cancer, and regenerative medicine.

Author Info: (1) (2) (3)

Author Info: (1) (2) (3)

Harnessing cuproptosis for pancreatic cancer therapy: From molecular insights to clinical prospects

Pancreatic cancer (PC) remains a high-fatality malignancy with limited clinical progress, characterized by aggressive biology, marked resistance to standard therapies, and dismal outcomes. Even with state-of-the-art resection, radiotherapy, and multidrug chemotherapy, median survival benefits are modest, highlighting an urgent need for mechanism-based interventions. Cuproptosis, a newly delineated modality of regulated cell death initiated by intracellular copper accumulation and mitochondrial stress, presents a biologically coherent therapeutic avenue. Distinct from apoptosis, necroptosis, and ferroptosis, cuproptosis is driven by the direct binding of copper to lipoylated enzymes of the tricarboxylic acid (TCA) cycle, resulting in bioenergetic failure, misfolded protein aggregation, and collapse of cytotoxic proteostasis. Converging studies suggest that copper disequilibrium and metabolic reprogramming are recurrent features of PC, potentially contributing to malignant progression, immune evasion, and chemoresistance. These insights motivate two complementary strategies: first, therapeutic manipulation of copper flux, via chelators, ionophores, or transport modulators, to selectively trigger cuproptosis in tumor cells; and second, sensitization of mitochondrial metabolism, through targeting lipoic-acid pathway components, pyruvate utilization, or TCA load, to lower the threshold for cuproptotic killing. In parallel, multi-omic interrogation of cuproptosis-associated genes, proteins, and metabolites may yield prognostic and predictive biomarkers, enabling risk-adapted treatment selection and rational combinations with cytotoxic, targeted, or immunotherapeutic modalities. This review synthesizes recent advances on cuproptosis in PC and outlines its translational potential as both a therapeutic target and a biomarker framework.

Author Info: (1) School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. (2) School of Medicine, Ardabil university of medical Sciences, Ardabil, Iran. (3) Student Res

Author Info: (1) School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. (2) School of Medicine, Ardabil university of medical Sciences, Ardabil, Iran. (3) Student Research Committee, School of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran. (4) School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran. (5) Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. (6) School of Dentistry, Islamic Azad University of Isfahan, Isfahan, Iran. (7) School of Medicine, Islamic Azad University, Najafabad Branch, Isfahan, Iran. (8) School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran. (9) School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: Mahlashokouhfarr@gmail.com.

Gut microbial metabolites in cancer immunomodulation

Gut microbiota-derived metabolites are emerging as systemic "remote immunoregulators" that shape tumor immunity across tissues. Integrating evidence across short-chain fatty acids, tryptophan derivatives, secondary bile acids, polyamines and other metabolites, we advance a metabolite-immune pathway-cancer framework that links receptor-mediated signaling, epigenetic remodeling and metabolic reprogramming to context-dependent, bidirectional immune effects. Importantly, in addition to the g protein-coupled receptor / aryl hydrocarbon receptor pathway, the selected microbial small molecule metabolites are the true T-cell receptor ligands of unconventional T cells, directly shaping the tissue resident immune and tumor microenvironment, supplementing the receptor signaling and epigenetic programs in our framework. We synthesize how these metabolites recalibrate the tumor immune microenvironment-modulating antigen presentation, T-cell effector fitness and exhaustion, regulatory T-cell activity, and myeloid polarization-and why the same metabolite can either potentiate immune surveillance or entrench immunosuppression depending on ligand-receptor pairing, dose and tissue niche. We compare tumor-type specific patterns (e.g., colorectal, liver, lung, breast and prostate cancers) to highlight common circuits and organ-restricted idiosyncrasies. Methodologically, we outline how single-cell and spatial multi-omics, imaging mass spectrometry and functional biosensors now enable co-registration of metabolite exposure with immune-cell states in human tumors, providing an actionable basis for biomarker discovery. Given ongoing debate about signals attributed to intratumoral microbiota in low-biomass tumor tissues, we foreground quantifiable, spatially mappable and pharmacologically tractable metabolite-receptor pathways, using microbe-associated molecular patterns / translocation as comparators to judge when chemical signals should be prioritized as intervention targets. Finally, we evaluate precision intervention avenues-including fecal microbiota transplantation, rational bacterial consortia, engineered microbes and nanoparticle-enabled metabolite delivery-and propose stratification rules that pair metabolite/receptor signatures with fit-for-purpose delivery. Together, mapping tissue-specific metabolite-immune circuits and embedding them in robust biomarker frameworks may convert microbial metabolites from correlative markers into therapeutic targets and tools, improving the efficacy and durability of cancer immunotherapy.

Author Info: (1) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (2) Department of Urology

Author Info: (1) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (2) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (3) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (4) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (5) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (6) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. (7) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. hangxu@wchscu.cn. (8) Department of Urology, Institute of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610041, People's Republic of China. wycleflue@scu.edu.cn.

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