Journal Articles

Innovative Methods

Methods with focus on improving cancer immunotherapy approaches

Combining DNA vaccine and AIM2 in H1 nanoparticles exert anti-renal carcinoma effects via enhancing tumor-specific multi-functional CD8+ T cell responses

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Renal carcinoma presents a rapid progression in patients with high metastasis with no effective therapeutic strategy. In this study, we designed a folate grafted PEI600-CyD (H1) nanoparticle-mediated DNA vaccine containing an adjuvant of absent in melanoma 2 (AIM2) and a tumor-specific antigen of carbonic anhydrase IX (CAIX) for renal carcinoma therapy. Mice bearing subcutaneous human CAIX (hCAIX)-Renca tumor were intramuscularly immunized with H1-pAIM2/pCAIX, H1-pCAIX, H1-pAIM2, or Mock vaccine, respectively. The tumor growth of hCAIX-Renca was significantly inhibited in H1-pAIM2/pCAIX vaccine group compared with control group. The vaccine activated CAIX-specific CD8+ T cell proliferation and cytotoxic T lymphocyte (CTL) responses, and enhanced the induction of multi-functional CD8+ T cells (expressing TNF-alpha, IL-2, and IFN-gamma). CD8+ T cell depletion resulted in the loss of anti-tumor activity of H1-pAIM2/pCAIX vaccine, suggesting that the efficacy of the vaccine was dependent on CD8+ T cell responses. Lung metastasis of renal carcinoma was also suppressed by H1-pAIM2/pCAIX vaccine treatment accompanied with the increased percentages of CAIX-specific multi-functional CD8+ T cells in the spleen, tumor, and bronchoalveolar lavage as compared with H1-pCAIX vaccine. Similarly, the vaccine enhanced CAIX-specific CD8+ T cell proliferation and CTL responses. Therefore, these results indicated that H1-pAIM2/pCAIX vaccine exhibits the therapeutic efficacy of anti-renal carcinoma by enhancing tumor-specific multi-functional CD8+ T cell responses. This vaccine strategy could be a potential and promising approach for the therapy of primary solid or metastasis tumors.

Author Info: (1) Cancer Institute, Xuzhou Medical University. (2) Department of Orthopedics, Affiliated Hospital of Xuzhou Medical University. (3) Cancer Institute, Xuzhou Medical University. (4) Cancer Institute

Author Info: (1) Cancer Institute, Xuzhou Medical University. (2) Department of Orthopedics, Affiliated Hospital of Xuzhou Medical University. (3) Cancer Institute, Xuzhou Medical University. (4) Cancer Institute, Xuzhou Medical University. (5) Cancer Institute, Xuzhou Medical University. (6) Cancer Institute, Xuzhou Medical University. (7) Cancer Institute, Xuzhou Medical University. (8) Biology college, Hunan University. (9) Cancer Institute, Xuzhou Medical University. (10) Cancer Institute, Xuzhou Medical University. (11) Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University jnzheng@xzhmu.edu.cn.

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CD33/CD3-bispecific T-cell engaging (BiTE(R)) antibody construct targets monocytic AML myeloid-derived suppressor cells

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Acute myeloid leukemia (AML) is the most common acute leukemia amongst adults with a 5-year overall survival lower than 30%. Emerging evidence suggest that immune alterations favor leukemogenesis and/or AML relapse thereby negatively impacting disease outcome. Over the last years myeloid derived suppressor cells (MDSCs) have been gaining momentum in the field of cancer research. MDSCs are a heterogeneous cell population morphologically resembling either monocytes or granulocytes and sharing some key features including myeloid origin, aberrant (immature) phenotype, and immunosuppressive activity. Increasing evidence suggests that accumulating MDSCs are involved in hampering anti-tumor immune responses and immune-based therapies. Here, we demonstrate increased frequencies of CD14(+) monocytic MDSCs in newly diagnosed AML that co-express CD33 but lack HLA-DR (HLA-DR(lo)). AML-blasts induce HLA-DR(lo) cells from healthy donor-derived monocytes in vitro that suppress T-cells and express indoleamine-2,3-dioxygenase (IDO). We investigated whether a CD33/CD3-bispecific BiTE(R) antibody construct (AMG 330) with pre-clinical activity against AML-blasts by redirection of T-cells can eradicate CD33(+) MDSCs. In fact, T-cells eliminate IDO(+)CD33(+) MDSCs in the presence of AMG 330. Depletion of total CD14(+) cells (including MDSCs) in peripheral blood mononuclear cells from AML patients did not enhance AMG 330-triggered T-cell activation and expansion, but boosted AML-blast lysis. This finding was corroborated in experiments showing that adding MDSCs into co-cultures of T- and AML-cells reduced AML-blast killing, while IDO inhibition promotes AMG 330-mediated clearance of AML-blasts. Taken together, our results suggest that AMG 330 may achieve anti-leukemic efficacy not only through T-cell-mediated cytotoxicity against AML-blasts but also against CD33(+) MDSCs, suggesting that it is worth exploring the predictive role of MDSCs for responsiveness towards an AMG 330-based therapy.

Author Info: (1) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (2) Department of Internal Medicine 5, Hematology and

Author Info: (1) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (2) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (3) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (4) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (5) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (6) Amgen Research GmbH, Munich, Germany. (7) Amgen Research GmbH, Munich, Germany. (8) Clinical Biomarkers and Diagnostics, Amgen Inc., South San Francisco, CA, USA. (9) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. (10) Department of Internal Medicine 5, Hematology and Oncology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054, Erlangen, Germany. dimitrios.mougiakakos@uk-erlangen.de.

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Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics

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Tumor ecosystems are composed of multiple cell types that communicate by ligand-receptor interactions. Targeting ligand-receptor interactions (for instance, with immune checkpoint inhibitors) can provide significant benefits for patients. However, our knowledge of which interactions occur in a tumor and how these interactions affect outcome is still limited. We present an approach to characterize communication by ligand-receptor interactions across all cell types in a microenvironment using single-cell RNA sequencing. We apply this approach to identify and compare the ligand-receptor interactions present in six syngeneic mouse tumor models. To identify interactions potentially associated with outcome, we regress interactions against phenotypic measurements of tumor growth rate. In addition, we quantify ligand-receptor interactions between T cell subsets and their relation to immune infiltration using a publicly available human melanoma dataset. Overall, this approach provides a tool for studying cell-cell interactions, their variability across tumors, and their relationship to outcome.

Author Info: (1) Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA, 02139, USA. (2) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. (3) Department of

Author Info: (1) Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA, 02139, USA. (2) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. (3) Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA, 02139, USA. (4) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. (5) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. (6) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. (7) Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA, 02139, USA. (8) Discovery, Merrimack Pharmaceuticals, Inc., Cambridge MA, 02139, USA. Electronic address: araue@merrimack.com.

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Acidic pH-responsive polymer nanoparticles as a TLR7/8 agonist delivery platform for cancer immunotherapy

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Synthetic imidazoquinoline-based toll-like receptor (TLR) 7/8 bi-specific agonists are promising vaccine adjuvants that can induce maturation of dendritic cells (DCs) and activate them to secrete pro-inflammatory cytokines. However, in vivo efficacy of these small molecule agonists is often hampered by their fast clearance from the injection site, limiting their use to topical treatments. In this study, we investigated the use of acidic pH-responsive poly(lactide-co-glycolide) (PLGA) nanoparticles for endo-lysosome specific release of 522, a novel TLR7/8 agonist. Bicarbonate salt was incorporated into the new formulation to generate carbon dioxide (CO2) gas at acidic pH, which can disrupt the polymer shell to rapidly release the payload. Compared to conventional PLGA nanoparticles, the pH responsive formulation resulted in 33-fold higher loading of 522. The new formulation demonstrated acid-responsive CO2 gas generation and drug release. The acid-responsive formulation increased the in vitro expression of co-stimulatory molecules on DCs and improved antigen-presentation via MHC I, both of which are essential for CD8 T cell priming. In vivo studies showed that the pH-responsive formulation elicited stronger antigen-specific CD8 T cell and natural killer (NK) cell responses than conventional PLGA nanoparticles, resulting in enhanced anticancer efficacy in a murine melanoma tumor model. Our results suggest that acidic-pH responsive, gas-generating nanoparticles are an efficient TLR7/8 agonist delivery platform for cancer immunotherapy.

Author Info: (1) Department of Pharmaceutics, University of Minnesota, Minneapolis, MN 55455, USA. jpanyam@umn.edu. (2) Department of Pharmaceutics, University of Minnesota, Minneapolis, MN 55455, USA. jpanyam@umn.edu. (3)

Author Info: (1) Department of Pharmaceutics, University of Minnesota, Minneapolis, MN 55455, USA. jpanyam@umn.edu. (2) Department of Pharmaceutics, University of Minnesota, Minneapolis, MN 55455, USA. jpanyam@umn.edu. (3) Department of Urology, University of Minnesota, Minneapolis, MN 55455, USA. (4) Department of Medicinal Chemistry, University of Minnesota, Minneapolis, MN 55455, USA. (5) Department of Urology, University of Minnesota, Minneapolis, MN 55455, USA and Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA and Center for Immunology, University of Minnesota, Minneapolis, MN 55455, USA and Microbiology, Immunology, and Cancer Biology Graduate Program, University of Minnesota, Minneapolis, MN 55455, USA. (6) Department of Pharmaceutics, University of Minnesota, Minneapolis, MN 55455, USA. jpanyam@umn.edu and Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA.

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Nondestructive, multiplex three-dimensional mapping of immune infiltrates in core needle biopsy

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Enumeration of tumor-infiltrating lymphocytes (TILs) in H&E stained tissue sections has demonstrated limited value in predicting immune responses to cancer immunotherapy, likely reflecting the diversity of cell types and immune activation states among tumor infiltrates. Multiparametric flow cytometry enables robust phenotypic and functional analysis to distinguish suppression from activation, but tissue dissociation eliminates spatial context. Multiplex methods for immunohistochemistry (IHC) are emerging, but these interrogate only a single tissue section at a time. Here, we report transparent tissue tomography (T3) as a tool for three-dimensional (3D) imaging cytometry in the complex architecture of the tumor microenvironment, demonstrating multiplexed immunofluorescent analysis in core needle biopsies. Using T3 imaging, image processing and machine learning to map CD3(+)CD8(+) cytotoxic T cells (CTLs) in whole core needle biopsies from Her2(+) murine mammary tumors and human head and neck surgical specimens revealed marked inhomogeneity within single needle cores, confirmed by serial section IHC. Applying T3 imaging cytometry, we discovered a strong spatial correlation between CD3(+)CD8(+) CTLs and microvasculature in the EGFR(+) parenchyma, revealing significant differences among head and neck cancer patients. These results show that T3 offers simple and rapid access to three-dimensional and quantitative maps of the tumor microenvironment and immune infiltrate, offering a new diagnostic tool for personalized cancer immunotherapy.

Author Info: (1) Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL, USA. Department of Biopharmaceutical Sciences, The University of Illinois at Chicago

Author Info: (1) Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL, USA. Department of Biopharmaceutical Sciences, The University of Illinois at Chicago, Chicago, IL, USA. (2) Integrated Light Microscopy Facility, The University of Chicago, Chicago, IL, USA. (3) Department of Pathology, The University of Chicago, Chicago, IL, USA. (4) Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL, USA. skron@uchicago.edu.

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Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition

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Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes. Most in silico methods predict only peptide-MHCII binding, resulting in significant over-prediction of CD4 T-cell epitopes. We present a method, ITCell, for prediction of T-cell epitopes within an input protein antigen sequence for given MHCII and TCR sequences. The method integrates information about three stages of the immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition. First, antigen cleavage sites are predicted based on the cleavage profiles of cathepsins S, B, and H. Second, for each 12-mer peptide in the antigen sequence we predict whether it will bind to a given MHCII, based on the scores of modeled peptide-MHCII complexes. Third, we predict whether or not any of the top scoring peptide-MHCII complexes can bind to a given TCR, based on the scores of modeled ternary peptide-MHCII-TCR complexes and the distribution of predicted cleavage sites. Our benchmarks consist of epitope predictions generated by this algorithm, checked against 20 peptide-MHCII-TCR crystal structures, as well as epitope predictions for four peptide-MHCII-TCR complexes with known epitopes and TCR sequences but without crystal structures. ITCell successfully identified the correct epitopes as one of the 20 top scoring peptides for 22 of 24 benchmark cases. To validate the method using a clinically relevant application, we utilized five factor VIII-specific TCR sequences from hemophilia A subjects who developed an immune response to factor VIII replacement therapy. The known HLA-DR1-restricted factor VIII epitope was among the six top-scoring factor VIII peptides predicted by ITCall to bind HLA-DR1 and all five TCRs. Our integrative approach is more accurate than current single-stage epitope prediction algorithms applied to the same benchmarks. It is freely available as a web server (http://salilab.org/itcell).

Author Info: (1) Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America. Department of Pharmaceutical Chemistry, University of

Author Info: (1) Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. (2) Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. Graduate Group in Biophysics, University of California at San Francisco, San Francisco, CA, United States of America. (3) Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. (4) Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. (5) Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. (6) Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. (7) Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. California Institute for Quantitative Biosciences (QB3), University of California, San Francisco, San Francisco, CA, United States of America. (8) Uniformed Services University of the Health Sciences, Bethesda, MD, United States of America. (9) Bayer HealthCare, San Francisco, CA, United States of America. (10) Bayer HealthCare, San Francisco, CA, United States of America. (11) Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States of America. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America. Graduate Group in Biophysics, University of California at San Francisco, San Francisco, CA, United States of America.

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Cancer Immunoinformatics: A Promising Era in the Development of Peptide Vaccines for Human Papillomavirus induced Cervical cancer

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Cancer immunoinformatics have new directions towards in vaccine design from predicted potential epitope candidates, able to stimulate a correct cellular or humoral immune responses have been reported. It employed to accomplish an advanced vaccine design through Reverse vaccinology by replacing the whole organisms. In this review, computational tools play an essential role in evaluating multiple proteomes to identify and select the potential targeted epitopes or combinations of distinct epitopes candidates may afford a rationale design competent towards obtaining suitable cytotoxic T lymphocytes (T cell) or B cell-mediated immune responses. This review explains a complete collection of the most beneficial online and user-friendly immunological tools, servers and databases; with the intention of the peptide vaccine's designing and development. In addition, the mechanism of major histocompatability (MHC) restricted peptide presentation and how these tools are supporting the vaccine development is also presented. Human papillomavirus (HPV) has been taken as model microbial strain for peptide vaccine design and discussed their sensitization against HPV induced cervical cancer significantly.

Author Info: (1) Center of Interdisciplinary Sciences-Computational Life Sciences, College of Food Science and Engineering, Henan University of Technology, Zhengzhou High-tech Industrial Development Zone, 100 Lianhua Street

Author Info: (1) Center of Interdisciplinary Sciences-Computational Life Sciences, College of Food Science and Engineering, Henan University of Technology, Zhengzhou High-tech Industrial Development Zone, 100 Lianhua Street, Zhengzhou, Henan 450001. China. (2) Center of Interdisciplinary Sciences-Computational Life Sciences, College of Food Science and Engineering, Henan University of Technology, Zhengzhou High-tech Industrial Development Zone, 100 Lianhua Street, Zhengzhou, Henan 450001. China. (3) The State Key Laboratory of Microbial Metabolism, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang, Shanghai, 200240. China. (4) The State Key Laboratory of Microbial Metabolism, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang, Shanghai, 200240. China. (5) Center of Interdisciplinary Sciences-Computational Life Sciences, College of Food Science and Engineering, Henan University of Technology, Zhengzhou High-tech Industrial Development Zone, 100 Lianhua Street, Zhengzhou, Henan 450001. China. (6) Center of Interdisciplinary Sciences-Computational Life Sciences, College of Food Science and Engineering, Henan University of Technology, Zhengzhou High-tech Industrial Development Zone, 100 Lianhua Street, Zhengzhou, Henan 450001. China.

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Functional TCR T cell screening using single-cell droplet microfluidics

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Adoptive T cell transfer, in particular TCR T cell therapy, holds great promise for cancer immunotherapy with encouraging clinical results. However, finding the right TCR T cell clone is a tedious, time-consuming, and costly process. Thus, there is a critical need for single cell technologies to conduct fast and multiplexed functional analyses followed by recovery of the clone of interest. Here, we use droplet microfluidics for functional screening and real-time monitoring of single TCR T cell activation upon recognition of target tumor cells. Notably, our platform includes a tracking system for each clone as well as a sorting procedure with 100% specificity validated by downstream single cell reverse-transcription PCR and sequencing of TCR chains. Our TCR screening prototype will facilitate immunotherapeutic screening and development of T cell therapies.

Author Info: (1) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite

Author Info: (1) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite 3027, Irvine, CA 92697, USA. weianz@uci.edu and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA 92697, USA and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA 92697, USA and Edwards Life Sciences Center for Advanced Cardiovascular Technology, University of California, Irvine, Irvine, CA 92697, USA and Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA and Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA. (2) Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA and Center of Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China and Suzhou Institute of Systems Medicine, Suzhou 215123, China. (3) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite 3027, Irvine, CA 92697, USA. weianz@uci.edu and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA 92697, USA and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA 92697, USA and Edwards Life Sciences Center for Advanced Cardiovascular Technology, University of California, Irvine, Irvine, CA 92697, USA and Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA and Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA. (4) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite 3027, Irvine, CA 92697, USA. weianz@uci.edu and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA 92697, USA and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA 92697, USA and Edwards Life Sciences Center for Advanced Cardiovascular Technology, University of California, Irvine, Irvine, CA 92697, USA and Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA and Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA. (5) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite 3027, Irvine, CA 92697, USA. weianz@uci.edu and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA 92697, USA and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA 92697, USA and Edwards Life Sciences Center for Advanced Cardiovascular Technology, University of California, Irvine, Irvine, CA 92697, USA and Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA and Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA. (6) Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA. (7) Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA. (8) Amberstone Biosciences LLC, 23181 Verdugo, Suite 106, Laguna Hills, CA 92653, USA. george@amberstonebio.com. (9) Sue and Bill Gross Stem Cell Research Center, Sue & Bill Gross Hall CIRM Institute, University of California, Irvine, 845 Health Sciences Road, Suite 3027, Irvine, CA 92697, USA. weianz@uci.edu and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA 92697, USA and Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA 92697, USA and Edwards Life Sciences Center for Advanced Cardiovascular Technology, University of California, Irvine, Irvine, CA 92697, USA and Department of Biomedical Engineering, University of California, Irvine, Irvine, CA 92697, USA and Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA.

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Next-generation antigen receptor sequencing of paired diagnosis and relapse samples of B-cell acute lymphoblastic leukemia: Clonal evolution and implications for minimal residual disease target selection

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Antigen receptor gene rearrangements are frequently applied as molecular targets for detection of minimal residual disease (MRD) in B-cell precursor acute lymphoblastic leukemia patients. Since such targets may be lost at relapse, appropriate selection of antigen receptor genes as MRD-PCR target is critical. Recently, next-generation sequencing (NGS) - much more sensitive and quantitative than classical PCR-heteroduplex approaches - has been introduced for identification of MRD-PCR targets. We evaluated 42 paired diagnosis-relapse samples by NGS (IGH, IGK, TRG, TRD, and TRB) to evaluate clonal evolution patterns and to design an algorithm for selection of antigen receptor gene rearrangements most likely to remain stable at relapse. Overall, only 393 out of 1446 (27%) clonal rearrangements were stable between diagnosis and relapse. If only index clones with a frequency >5% at diagnosis were taken into account, this number increased to 65%; including only index clones with an absolute read count >10,000, indicating truly major clones, further increased the stability to 84%. Over 90% of index clones at relapse were also present as index clone at diagnosis. Our data provide detailed information about the stability of antigen receptor gene rearrangements, based on which we propose an algorithm for selecting stable MRD-PCR targets, successful in >97% of patients.

Author Info: (1) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (2) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (3)

Author Info: (1) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (2) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (3) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Bioinformatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (4) Dutch Childhood Oncology Group, The Hague, The Netherlands. (5) Department of Bioinformatics, Erasmus MC, University Medical Center Rotterdam, The Netherlands. (6) Department of Immunology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. Electronic address: v.h.j.vandervelden@erasmusmc.nl.

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High FcgammaR Expression on Intratumoral Macrophages Enhances Tumor-Targeting Antibody Therapy

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Therapy with tumor-specific Abs is common in the clinic but has limited success against solid malignancies. We aimed at improving the efficacy of this therapy by combining a tumor-specific Ab with immune-activating compounds. In this study, we demonstrate in the aggressive B16F10 mouse melanoma model that concomitant application of the anti-TRP1 Ab (clone TA99) with TLR3-7/8 or -9 ligands, and IL-2 strongly enhanced tumor control in a therapeutic setting. Depletion of NK cells, macrophages, or CD8(+) T cells all mitigated the therapeutic response, showing a coordinated immune rejection by innate and adaptive immune cells. FcgammaRs were essential for the therapeutic effect, with a dominant role for FcgammaRI and a minor role for FcgammaRIII and FcgammaRIV. FcgammaR expression on NK cells and granulocytes was dispensable, indicating that other tumoricidal functions of NK cells were involved and implicating that FcgammaRI, -III, and -IV exerted their activity on macrophages. Indeed, F4/80(+)Ly-6C(+) inflammatory macrophages in the tumor microenvironment displayed high levels of these receptors. Whereas administration of the anti-TRP1 Ab alone reduced the frequency of these macrophages, the combination with a TLR agonist retained these cells in the tumor microenvironment. Thus, the addition of innate stimulatory compounds, such as TLR ligands, to tumor-specific Ab therapy could greatly enhance its efficacy in solid cancers via optimal exploitation of FcgammaRs.

Author Info: (1) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (2) Department of Human Genetics, Leiden University Medical Center, 2333 ZA

Author Info: (1) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (2) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (3) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (4) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (5) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (6) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (7) Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; and. (8) Department of Medical Oncology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. (9) Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; and. (10) Department of Medical Oncology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands j.s.verbeek@lumc.nl t.van_hall@lumc.nl. (11) Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; j.s.verbeek@lumc.nl t.van_hall@lumc.nl.

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