Journal Articles

CD4+ helper T cells endow cDC1 with cancer-impeding functions in the human tumor micro-environment

Spotlight 

Lei et al. showed that anti-CD3/CD28-stimulated CD4+ T cells induced purified human blood cDC1s and less responsive cDC2s (but not pDCs and moDCs) to express antigen presentation, costimulation, cytokine, and chemokine gene/protein signatures more strongly than PRR signaling. CD4+ T cell-signaled cDC1s were the most potent DCs in an in vitro assay of CTL priming by (tumor) cell-associated antigens, and expressed the clinically favorable DC3 and mregDC signature genes. Genes comprising the mature DC signature were associated with CD8+ and Th1 T cell and cDC1 TME infiltration and response to PD-1 blockade.

Contributed by Paula Hochman

Lei et al. showed that anti-CD3/CD28-stimulated CD4+ T cells induced purified human blood cDC1s and less responsive cDC2s (but not pDCs and moDCs) to express antigen presentation, costimulation, cytokine, and chemokine gene/protein signatures more strongly than PRR signaling. CD4+ T cell-signaled cDC1s were the most potent DCs in an in vitro assay of CTL priming by (tumor) cell-associated antigens, and expressed the clinically favorable DC3 and mregDC signature genes. Genes comprising the mature DC signature were associated with CD8+ and Th1 T cell and cDC1 TME infiltration and response to PD-1 blockade.

Contributed by Paula Hochman

ABSTRACT: Despite their low abundance in the tumor microenvironment (TME), classical type 1 dendritic cells (cDC1) play a pivotal role in anti-cancer immunity, and their abundance positively correlates with patient survival. However, their interaction with CD4(+) T-cells to potentially enable the cytotoxic T lymphocyte (CTL) response has not been elucidated. Here we show that contact with activated CD4(+) T-cells enables human ex vivo cDC1, but no other DC types, to induce a CTL response to cell-associated tumor antigens. Single cell transcriptomics reveals that CD4(+) T-cell help uniquely optimizes cDC1 in many functions that support antigen cross-presentation and T-cell priming, while these changes don't apply to other DC types. We robustly identify "helped" cDC1 in the TME of a multitude of human cancer types by the overlap in their transcriptomic signature with that of recently defined, tumor-infiltrating DC states that prove to be positively prognostic. As predicted from the functional effects of CD4(+) T-cell help, the transcriptomic signature of "helped" cDC1 correlates with tumor infiltration by CTLs and Thelper(h)-1 cells, overall survival and response to PD-1-targeting immunotherapy. These findings reveal a critical role for CD4(+) T-cell help in enabling cDC1 function in the TME and may establish the helped cDC1 transcriptomic signature as diagnostic marker in cancer.

Author Info: (1) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands. (2) Department

Author Info: (1) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands. (2) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. (3) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands. (4) Genomics Facility, The Netherlands Cancer Institute, Amsterdam, The Netherlands. (5) Genomics Facility, The Netherlands Cancer Institute, Amsterdam, The Netherlands. (6) Genomics Facility, The Netherlands Cancer Institute, Amsterdam, The Netherlands. (7) Aduro Biotech Europe B.V, Oss, The Netherlands. (8) Immune Regulation in Cancer, German Cancer Research Center, Heidelberg, Germany. (9) Laboratory of Cell Stress & Immunity, Department of Cellular & Molecular Medicine, KU Leuven, Leuven, Belgium. (10) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. j.g.borst@lumc.nl. Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands. j.g.borst@lumc.nl. (11) Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands. y.xiao@lumc.nl. Oncode Institute, Leiden University Medical Center, Leiden, The Netherlands. y.xiao@lumc.nl.

Inducing trained immunity in pro-metastatic macrophages to control tumor metastasis Spotlight 

Ding and Shrestha et al. used whole beta-glucan particles (WGP) to induce trained immunity against tumor cells in myeloid cells, a pro-tumor cell type known to be enhanced in pre-metastatic niches. One i.p. dose of WGP increased bone marrow (BM) myelopoiesis and trained lung interstitial macrophages via sphingosine-mitochondrial fission, enhancing their phagocytic and cytotoxic capacity and control of tumor metastasis in various mouse models, independent of neutrophils and T and B cells. Adoptive transfer of central trained BM-derived macrophages also reduced tumor metastasis. Human monocytes trained with WGP reduced tumor burden in NSG mice.

Contributed by Ute Burkhardt

Ding and Shrestha et al. used whole beta-glucan particles (WGP) to induce trained immunity against tumor cells in myeloid cells, a pro-tumor cell type known to be enhanced in pre-metastatic niches. One i.p. dose of WGP increased bone marrow (BM) myelopoiesis and trained lung interstitial macrophages via sphingosine-mitochondrial fission, enhancing their phagocytic and cytotoxic capacity and control of tumor metastasis in various mouse models, independent of neutrophils and T and B cells. Adoptive transfer of central trained BM-derived macrophages also reduced tumor metastasis. Human monocytes trained with WGP reduced tumor burden in NSG mice.

Contributed by Ute Burkhardt

ABSTRACT: Metastasis is the leading cause of cancer-related deaths and myeloid cells are critical in the metastatic microenvironment. Here, we explore the implications of reprogramming pre-metastatic niche myeloid cells by inducing trained immunity with whole beta-glucan particle (WGP). WGP-trained macrophages had increased responsiveness not only to lipopolysaccharide but also to tumor-derived factors. WGP in vivo treatment led to a trained immunity phenotype in lung interstitial macrophages, resulting in inhibition of tumor metastasis and survival prolongation in multiple mouse models of metastasis. WGP-induced trained immunity is mediated by the metabolite sphingosine-1-phosphate. Adoptive transfer of WGP-trained bone marrow-derived macrophages reduced tumor lung metastasis. Blockade of sphingosine-1-phosphate synthesis and mitochondrial fission abrogated WGP-induced trained immunity and its inhibition of lung metastases. WGP also induced trained immunity in human monocytes, resulting in antitumor activity. Our study identifies the metabolic sphingolipid-mitochondrial fission pathway for WGP-induced trained immunity and control over metastasis.

Author Info: (1) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisvil

Author Info: (1) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (2) Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA. (3) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (4) Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA. (5) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (6) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA. (7) Department of Chemistry, Indiana University, Bloomington, IN, USA. (8) Department of Chemistry, Lehigh University, Bethlehem, PA, USA. (9) Department of Chemistry, University of Louisville, Louisville, KY, USA. (10) Department of Chemistry, University of Louisville, Louisville, KY, USA. (11) Department of Neuroscience, KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA. (12) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (13) Functional Immunomics Core, Brown Cancer Center, University of Louisville, Louisville, KY, USA. (14) Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA. (15) Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA. (16) Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, USA. Department of Computer Science and Engineering, University of Louisville, Louisville, KY, USA. (17) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (18) Department of Pharmacology & Toxicology, University of Louisville School of Medicine, Louisville, KY, USA. (19) Department of Chemistry, University of Louisville, Louisville, KY, USA. (20) Department of Chemistry, Lehigh University, Bethlehem, PA, USA. (21) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. (22) Department of Chemistry, Indiana University, Bloomington, IN, USA. (23) Division of Immunotherapy, The Hiram C. Polk, Jr., MD Department of Surgery, Immuno-Oncology Program, Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. jun.yan@louisville.edu. Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA. jun.yan@louisville.edu.

Sustained Intratumoral Administration of Agonist CD40 Antibody Overcomes Immunosuppressive Tumor Microenvironment in Pancreatic Cancer

Agonist CD40 monoclonal antibodies (mAb) is a promising immunotherapeutic agent for cold-to-hot tumor immune microenvironment (TIME) conversion. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal cancer known as an immune desert, and therefore urgently needs more effective treatment. Conventional systemic treatment fails to effectively penetrate the characteristic dense tumor stroma. Here, it is shown that sustained low-dose intratumoral delivery of CD40 mAb via the nanofluidic drug-eluting seed (NDES) can modulate the TIME to reduce tumor burden in murine models. NDES achieves tumor reduction at a fourfold lower dosage than systemic treatment while avoiding treatment-related adverse events. Further, abscopal responses are shown where intratumoral treatment yields growth inhibition in distant untreated tumors. Overall, the NDES is presented as a viable approach to penetrate the PDAC immune barrier in a minimally invasive and effective manner, for the overarching goal of transforming treatment.

Author Info: (1) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (2) Department of Nanomedicine, Houston Methodist Research Institut

Author Info: (1) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (2) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (3) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. Texas A&M University College of Medicine, 2121 W Holcombe Blvd, Houston, TX, 77003, USA. (4) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (5) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (6) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (7) Center for Immunotherapy Research, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. ImmunoMonitoring Core, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (8) Center for Immunotherapy Research, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. ImmunoMonitoring Core, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (9) Center for Immunotherapy Research, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. ImmunoMonitoring Core, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (10) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. (11) Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, TX, 77003, USA. Department of Surgery, Houston Methodist Hospital, 6565 Fannin St., Houston, TX, 77003, USA. Department of Radiation Oncology, Houston Methodist Hospital, 6565 Fannin St., Houston, TX, 77003, USA.

Mutant and non-mutant neoantigen-based cancer vaccines: recent advances and future promises

Major advances in cancer treatment have emerged with the introduction of immunotherapies using blocking antibodies that target T-cell inhibitory receptors, such as programmed death-1 (PD-1) and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), known as immune checkpoints. However, most cancer patients do not respond to immune checkpoint blockade (ICB) therapies, suggesting the development of resistance mechanisms associated with either an insufficient number of preexisting tumor-specific T-cell precursors and/or inappropriate T-cell reactivation. To broaden clinical benefit, anti-PD-1/PD-1 ligand (PD-L1) neutralizing antibodies have been combined with therapeutic cancer vaccines based on non-mutant and/or mutant tumor antigens, to stimulate and expand tumor-specific T lymphocytes. Although these combination treatments achieve the expected goal in some patients, relapse linked to alterations in antigen presentation machinery (APM) of cancer cells often occurs leading to tumor escape from CD8 T-cell immunity. Remarkably, an alternative antigenic peptide repertoire, referred to as T-cell epitopes associated with impaired peptide processing (TEIPP), arises on these malignant cells with altered APM. TEIPP are derived from ubiquitous non-mutant self-proteins and represent a unique resource to target immune-edited tumors that have acquired resistance to cytotoxic T lymphocytes (CTLs) related to defects in transporter associated with antigen processing (TAP) and possibly also to ICB. The present review discusses tumor-associated antigens (TAAs) and mutant neoantigens and their use as targets in peptide- and RNA-based therapeutic cancer vaccines. Finally, this paper highlights TEIPP as a promising immunogenic non-mutant neoantigen candidates for active cancer immunotherapy and combination with TAA and mutant neoantigens. Combining these polyepitope cancer vaccines with ICB would broaden T-cell specificity and reinvigorate exhausted antitumor CTL, resulting in the eradication of all types of neoplastic cells, including immune-escaped subtypes.

Author Info: (1) INSERM UMR 1186, Integrative Tumor Immunology and Immunotherapy, Gustave Roussy, Fac. de MŽdecine - Univ. Paris-Sud, UniversitŽ Paris-Saclay, 94805 Villejuif, France. (2) INSER

Author Info: (1) INSERM UMR 1186, Integrative Tumor Immunology and Immunotherapy, Gustave Roussy, Fac. de MŽdecine - Univ. Paris-Sud, UniversitŽ Paris-Saclay, 94805 Villejuif, France. (2) INSERM UMR 1186, Integrative Tumor Immunology and Immunotherapy, Gustave Roussy, Fac. de MŽdecine - Univ. Paris-Sud, UniversitŽ Paris-Saclay, 94805 Villejuif, France. (3) INSERM UMR 1186, Integrative Tumor Immunology and Immunotherapy, Gustave Roussy, Fac. de MŽdecine - Univ. Paris-Sud, UniversitŽ Paris-Saclay, 94805 Villejuif, France.

Prognostic significance of tumor infiltrating lymphocytes on first-line pembrolizumab efficacy in advanced non-small cell lung cancer

AIM: Tumor-infiltrating lymphocytes (TILs) in the tumor and stroma are expected to accurately predict the efficacy of programmed death-1 (PD-1) blockade therapy. However, little is known about the prognostic significance of TILs in first-line PD-1 therapy. We assessed TILs in patients with advanced or metastatic non-small cell lung cancer (NSCLC) treated with pembrolizumab in the palliative setting. METHODS: Multiplex immunohistochemistry staining of TILs (CD4, CD8, Foxp3, and PD-1) and immunohistochemical staining of CK and PD-L1 in the tumor and stroma was performed in tumor specimens of 107 NSCLC patients and correlated with clinical outcomes, as a single-center retrospective study. TILs and programmed death ligand-1 (PD-L1) were assessed on biopsies (N_=_93) or surgical resections (N_=_14) before first-line pembrolizumab. RESULTS: A low number of stromal CD4 TILs were significantly associated with bone metastasis and poor performance status (PS). The median progression-free survival (PFS) and overall survival (OS) were significantly higher in patients with a high number of stromal CD4 TILs (336 days and 731 days, respectively) than in those with low infiltration (204 days and 333 days, respectively). Patients with a high number of intratumoral CD8 TILs (731 days) yielded significantly better OS than those with low infiltration (333 days), but not for PFS. Multivariate analysis confirmed that stromal CD4 TILs were independent predictors of PFS, but not OS. Furthermore, intratumoral CD8 TILs were independent predictors of better OS. In the survival analysis of key subgroups, stromal CD4 TILs were identified as significant predictors of survival in patients with non-adenocarcinomatous histology and PD-L1_³_50%. CONCLUSION: Stromal CD4 TILs were identified as a significant marker for predicting the PFS after pembrolizumab therapy, especially in patients with non-adenocarcinoma and high PD-L1 expression. In addition, intratumoral CD8 TILs were identified as significant predictors of OS.

Author Info: (1) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan.

Author Info: (1) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. kkaira1970@yahoo.co.jp. (2) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (3) Department of Pathology, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (4) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (5) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (6) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (7) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (8) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (9) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (10) Department of Pathology, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. (11) Department of Respiratory Medicine, Comprehensive Cancer Center, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan.

HLA and tumour immunology: immune escape, immunotherapy and immune-related adverse events

PURPOSE: As molecules responsible for presenting antigens to T lymphocytes, leukocytes antigens (HLAs) play a vital role in cancer immunology. This review aims to provide current understanding of HLAs in tumour immunology. METHODS: Perspectives on how HLA alterations may contribute to the immune escape of cancer cells and resistance to immunotherapy, and potential methods to overcome HLA defects were summarized. In addition, we discussed the potential association between HLA and immune-related adverse events (irAEs), which has not been reviewed elsewhere. RESULTS: Downregulation, loss of heterogeneity and entire loss of HLAs are responsible for the immune escape of tumour cells. The strategies to overcome the HLA defects can be effective therapies of cancer. Compared with classical HLA-I, non-classical HLA-I molecules, such as HLA-E and HLA-G, appear to be more reliable predictors of prognosis, as they tend to play immunosuppressive roles in antitumor response. Relative diversified or high expression of classical HLA-I are potential predictors of favourable response of immunotherapy. Certain HLA types may be associated to enhanced affinity to self-antigen-mimicked tumour-antigens, thus may positively correlated to irAEs triggered by checkpoint inhibitors. CONCLUSIONS: Further studies exploring the relationship between HLAs and cancer may not only lead to the development of novel therapies but also bring about better management of irAEs.

Author Info: (1) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sc

Author Info: (1) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (2) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (3) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (4) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (5) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (6) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (7) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (8) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. (9) Novogene Co., Ltd, Beijing, China. (10) Renke Beijing Biotechnology Co., Ltd, Beijing, China. (11) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. tangyu_cams@163.com. (12) Department of Clinical Trials Center, Clinical Cancer Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. ncctrials@cicams.ac.cn.

Impact of the HLA Immunopeptidome on Survival of Leukemia Patients After Unrelated Donor Transplantation

PURPOSE: Immunopeptidome divergence between mismatched HLA-DP is a determinant of T-cell alloreactivity and clinical tolerability after fully HLA-A, -B, -C, -DRB1, -DQB1 matched unrelated donor hematopoietic cell transplantation (UD-HCT). Here, we tested this concept in HLA-A, -B, and -C disparities after single class I HLA-mismatched UD-HCT. PATIENTS AND METHODS: We studied 2,391 single class I HLA-mismatched and 14,426 fully HLA-matched UD-HCT performed between 2008 and 2018 for acute leukemia or myelodysplastic syndromes. Hierarchical clustering of experimentally determined peptide-binding motifs (PBM) was used as a proxy for immunopeptidome divergence of HLA-A, -B, or -C disparities, allowing us to classify 1,629/2,391 (68.1%) of the HLA-mismatched UD-HCT as PBM-matched or PBM-mismatched. Risks associated with PBM-matching status were assessed by Cox proportional hazards models, with overall survival (OS) as the primary end point. RESULTS: Relative to full matches, bidirectional or unidirectional PBM mismatches in graft-versus-host (GVH) direction (PBM-GVH mismatches, 60.7%) were associated with significantly lower OS (hazard ratio [HR], 1.48; P < .0001), while unidirectional PBM mismatches in host-versus-graft direction or PBM matches (PBM-GVH matches, 39.3%) were not (HR, 1.13; P = .1017). PBM-GVH mismatches also had significantly lower OS than PBM-GVH matches in direct comparison (HR, 1.32; P = .0036). The hazards for transplant-related mortality and acute and chronic graft-versus-host disease but not relapse increased stepwise from full HLA matches to single PBM-GVH matches, and single PBM-GVH mismatches. A webtool for PBM-matching of single class I HLA-mismatched donor-recipient pairs was developed. CONCLUSION: PBM-GVH mismatches inform mortality risks after single class I HLA-mismatched UD-HCT, suggesting that prospective consideration of directional PBM-matching status might improve outcome. These findings highlight immunopeptidome divergence between mismatched HLA as a driver of clinical tolerability in UD-HCT.

Author Info: (1) Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germany. (2) Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germa

Author Info: (1) Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germany. (2) Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germany. German Cancer Consortium, partner site Essen/DŸsseldorf (DKTK), Heidelberg, Germany. (3) CIBMTR (Center for International Blood and Marrow Transplant Research), National Marrow Donor Program/Be The Match, Minneapolis, MN. (4) Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI. Department of Medicine, Medical College of Wisconsin, CIBMTR (Center for International Blood and Marrow Transplant Research), Milwaukee, WI. (5) CIBMTR (Center for International Blood and Marrow Transplant Research), National Marrow Donor Program/Be The Match, Minneapolis, MN. (6) Division of Cancer Epidemiology and Genetics, NIH-NCI Clinical Genetics Branch, Rockville, MD. (7) Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC. (8) Anthony Nolan Research Institute and University College London Cancer Institute, Royal Free Campus, London, United Kingdom. (9) Department of Medicine, Medical College of Wisconsin, CIBMTR (Center for International Blood and Marrow Transplant Research), Milwaukee, WI. Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA. (10) CIBMTR (Center for International Blood and Marrow Transplant Research), National Marrow Donor Program/Be The Match, Minneapolis, MN. (11) CIBMTR (Center for International Blood and Marrow Transplant Research), National Marrow Donor Program/Be The Match, Minneapolis, MN. (12) Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germany. German Cancer Consortium, partner site Essen/DŸsseldorf (DKTK), Heidelberg, Germany.

Structure-based prediction of T cell receptor:peptide-MHC interactions

The regulatory and effector functions of T cells are initiated by the binding of their cell-surface T cell receptor (TCR) to peptides presented by major histocompatibility complex (MHC) proteins on other cells. The specificity of TCR:peptide-MHC interactions, thus, underlies nearly all adaptive immune responses. Despite intense interest, generalizable predictive models of TCR:peptide-MHC specificity remain out of reach; two key barriers are the diversity of TCR recognition modes and the paucity of training data. Inspired by recent breakthroughs in protein structure prediction achieved by deep neural networks, we evaluated structural modeling as a potential avenue for prediction of TCR epitope specificity. We show that a specialized version of the neural network predictor AlphaFold can generate models of TCR:peptide-MHC interactions that can be used to discriminate correct from incorrect peptide epitopes with substantial accuracy. Although much work remains to be done for these predictions to have widespread practical utility, we are optimistic that deep learning-based structural modeling represents a path to generalizable prediction of TCR:peptide-MHC interaction specificity.

Author Info: (1) Herbold Computational Biology Program, Division of Public Health Sciences. Fred Hutchinson Cancer Center, Seattle, United States. Institute for Protein Design. University of Wa

Author Info: (1) Herbold Computational Biology Program, Division of Public Health Sciences. Fred Hutchinson Cancer Center, Seattle, United States. Institute for Protein Design. University of Washington, Seattle, United States.

Clustering by antigen-presenting genes reveals immune landscapes and predicts response to checkpoint immunotherapy

Immune checkpoint blockade (ICB) has demonstrated efficacy by reinvigorating immune cytotoxicity against tumors. However, the mechanisms underlying how ICB induces responses in a subset of patients remain unclear. Using bulk and single-cell transcriptomic cohorts of melanoma patients receiving ICB, we proposed a clustering model based on the expression of an antigen-presenting machinery (APM) signature consisting of 23 genes in a forward-selection manner. We characterized four APM clusters associated with distinct immune characteristics, cancer hallmarks, and patient prognosis in melanoma. The model predicts differential regulation of APM genes during ICB, which shaped ICB responsiveness. Surprisingly, while immunogenically hot tumors with high baseline APM expression prior to treatment are correlated with a better response to ICB than cold tumors with low APM expression, a subset of hot tumors with the highest pre-ICB APM expression fail to upregulate APM expression during treatment. In addition, they undergo immunoediting and display infiltration of exhausted T cells. In comparison, tumors associated with the best patient prognosis demonstrate significant APM upregulation and immune infiltration following ICB. They also show infiltration of tissue-resident memory T cells, shaping prolonged antitumor immunity. Using only pre-treatment transcriptomic data, our model predicts the dynamic APM-mediated tumor-immune interactions in response to ICB and provides insights into the immune escape mechanisms in hot tumors that compromise the ICB efficacy. We highlight the prognostic value of APM expression in predicting immune response in chronic diseases.

Author Info: (1) Department of Biomedical Engineering, Johns Hopkins University, 217A Hackerman Hall, 3400 N. Charles St., Baltimore, MD, 21218, USA. Institute for Computational Medicine, Johns

Author Info: (1) Department of Biomedical Engineering, Johns Hopkins University, 217A Hackerman Hall, 3400 N. Charles St., Baltimore, MD, 21218, USA. Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA. (2) Department of Biomedical Engineering, Johns Hopkins University, 217A Hackerman Hall, 3400 N. Charles St., Baltimore, MD, 21218, USA. karchin@jhu.edu. Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA. karchin@jhu.edu. Department of Oncology, Johns Hopkins Medicine, Baltimore, MD, 21287, USA. karchin@jhu.edu.

BTG1 mutation yields supercompetitive B cells primed for malignant transformation

Multicellular life requires altruistic cooperation between cells. The adaptive immune system is a notable exception, wherein germinal center B cells compete vigorously for limiting positive selection signals. Studying primary human lymphomas and developing new mouse models, we found that mutations affecting BTG1 disrupt a critical immune gatekeeper mechanism that strictly limits B cell fitness during antibody affinity maturation. This mechanism converted germinal center B cells into supercompetitors that rapidly outstrip their normal counterparts. This effect was conferred by a small shift in MYC protein induction kinetics but resulted in aggressive invasive lymphomas, which in humans are linked to dire clinical outcomes. Our findings reveal a delicate evolutionary trade-off between natural selection of B cells to provide immunity and potentially dangerous features that recall the more competitive nature of unicellular organisms.

Author Info: (1) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (2) Division of Hematology and Oncology, Departm

Author Info: (1) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (2) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (3) Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA. (4) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. Tri-Institutional PhD Program in Computational Biomedicine, New York, NY, USA. Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. (5) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (6) Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germany. (7) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (8) Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA. (9) Department of Pathology, Yale School of Medicine, New Haven, CT, USA. (10) Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. (11) Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA. (12) Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germany. (13) Department of Pharmacology and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (14) Department of Pharmacology and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (15) Molecular Pharmacology Program and Center for Cell Engineering, Center for Stem Cell Biology, Center for Experimental Therapeutics, and Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Department of Pharmacology, Weill Cornell Medicine, New York, NY, USA. (16) Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA. (17) Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA. (18) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (19) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (20) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (21) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (22) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. (23) Department of Laboratory Medicine, University of California, San Francisco, CA, USA. (24) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. Weill Cornell Medicine-Qatar, Doha, Qatar. (25) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (26) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (27) Molecular Pharmacology Program and Center for Cell Engineering, Center for Stem Cell Biology, Center for Experimental Therapeutics, and Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK. (28) Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. Caryl and Israel Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. (29) Molecular Pharmacology Program and Center for Cell Engineering, Center for Stem Cell Biology, Center for Experimental Therapeutics, and Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA. (30) Department of Pharmacology and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. (31) Centre for Lymphoid Cancer, BC Cancer, Vancouver, BC, Canada. (32) Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA. (33) Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germany. Institute for Biochemistry, Biotechnology and Bioinformatics, Technische UniversitŠt Braunschweig, Braunschweig, Germany. (34) Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA. (35) Division of Hematology and Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

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