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Novais EJ, Ottone OK, Brown EV, Madhu V, Tran VA, Ramteke P, Dighe AS, Solga MD, Manchel A, Lepore AC, Risbud MV. Genetics- and age-driven neuroimmune and disc changes underscore herniation susceptibility and pain-associated behaviors in SM/J mice. SCIENCE ADVANCES 2025; 11:eado6847. [PMID: 40267183 PMCID: PMC12017323 DOI: 10.1126/sciadv.ado6847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 03/19/2025] [Indexed: 04/25/2025]
Abstract
There are no appropriate mouse models to study the pathophysiology of spontaneous disc herniations in a wild-type setting. SM/J mice, a poor healer inbred strain, presented a high incidence of age-associated lumbar disc herniations with neurovascular innervations. Transcriptomic comparisons of the SM/J annulus fibrosus with human tissues showed shared pathways related to immune cell activation and inflammation. Notably, aged SM/J mice showed increased pain sensitization and neuroinflammation with altered extracellular matrix regulation in the dorsal root ganglia and spinal cord. There were increased T cells in the vertebral marrow, and cytometry by time-of-flight analysis showed increased splenic CD8+ T cells, nonspecific activation of CD8+ memory T cells, and enhanced interferon-γ production in the myeloid compartment. Single-cell RNA sequencing of peripheral blood mononuclear cells showed more B cells, with lower proportions of T cells, monocytes, and granulocytes. This study highlights the contribution of genetic background and aging to increased susceptibility of spontaneous intervertebral disc herniations in a clinically relevant murine model.
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Affiliation(s)
- Emanuel J. Novais
- Orthopaedic Department, Local Health Unit of the Litoral Alentejano, Santiago do Cacém, Portugal
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Faculty of Medicine, Universidade Católica Portuguesa, Lisbon, Portugal
- Center for Interdisciplinary Research in Health, Universidade Católica Portuguesa, Lisbon, Portugal
| | - Olivia K. Ottone
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Graduate Program in Cell Biology and Regenerative Medicine, Jefferson College of Life Sciences, Thomas Jefferson University, Philadelphia, PA, USA
| | - Eric V. Brown
- Department of Neuroscience, Vickie and Jack Farber Institute for Neuroscience·, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA
| | - Vedavathi Madhu
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Victoria A. Tran
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Pranay Ramteke
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Abhijit S. Dighe
- Department of Orthopedic Surgery, University of Virginia Health System, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Michael D. Solga
- Flow Cytometry Core Facility, University of Virginia, Charlottesville, VA, USA
| | - Alexandra Manchel
- Graduate Program in Cell Biology and Regenerative Medicine, Jefferson College of Life Sciences, Thomas Jefferson University, Philadelphia, PA, USA
| | - Angelo C. Lepore
- Department of Neuroscience, Vickie and Jack Farber Institute for Neuroscience·, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA
| | - Makarand V. Risbud
- Department of Orthopaedic Surgery, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Graduate Program in Cell Biology and Regenerative Medicine, Jefferson College of Life Sciences, Thomas Jefferson University, Philadelphia, PA, USA
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Morse MA, Crosby EJ, Halperin DM, Uronis HE, Hsu SD, Hurwitz HI, Rushing C, Bolch EK, Warren DA, Moyer AN, Lowe ME, Niedzwiecki D. Phase Ib/II study of Pembrolizumab with Lanreotide depot for advanced, progressive Gastroenteropancreatic neuroendocrine tumors (PLANET). J Neuroendocrinol 2025; 37:e13496. [PMID: 39933708 DOI: 10.1111/jne.13496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 11/28/2024] [Accepted: 01/25/2025] [Indexed: 02/13/2025]
Abstract
While performing a study of immune checkpoint blockade with the anti-PD-1 antibody pembrolizumab combined with the somatostatin analogue (SSA) lanreotide in patients with low- and intermediate-grade gastroenteropancreatic neuroendocrine tumors (GEP-NETs), we studied whether there were any immune correlates of response to the anti-PD-1 therapy that could guide future attempts to integrate immunotherapy into the treatment of NETs. Patients with grade 1 and 2 GEP-NETs who had progressed on a prior SSA received lanreotide 90 mg subcutaneously and pembrolizumab 200 mg intravenously every 3 weeks until progression or intolerable toxicity. Objective response rate (ORR) at any time in the study, clinical benefit rate (CBR, defined as stable disease or better), progression-free survival (PFS), and overall survival (OS) were measured. Changes in T cell subsets in peripheral blood before and during therapy were analyzed by multiparameter mass cytometry (CyTOF). Archived tissue samples were analyzed for PD-L1 expression and TIL infiltration. Twenty-two (22) patients (GI/pancreatic 14/8, median Ki67 7% [IQR 4, 10%], median 1.5 prior systemic therapies [range 1-4]) were enrolled. Among the GI-NETs, there was one partial response, the CBR was 50%, the median PFS was 8.5 months, and the median OS was 32.7 months. No responses were seen in pancreatic NETs, which had 0% CBR, a PFS of 2.7 months, and an OS of 23.9 months. Of the 16 analyzable tumors, 6 had detectable PD-L1 expression and 15 had detectable TILs. Neither TILs nor PD-L1 expression correlated with ORR or CBR. However, clinical benefit (SD or better) was associated with peripheral blood on-treatment effector memory T cell activation and progressive disease was associated with baseline peripheral blood regulatory T cell (Treg) activation. We conclude that immune checkpoint blockade had low activity in unselected patients with grade 1 and 2 GEP-NETs. Further study of strategies to reduce Treg activation or enhance effector memory activation during immunotherapy is warranted.
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Affiliation(s)
- Michael A Morse
- Division of Medical Oncology, Duke University Department of Medicine, Durham, North Carolina, USA
| | - Erika J Crosby
- Department of Surgery, Duke University Medical Center, Durham, North Carolina, USA
| | - Daniel M Halperin
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Hope E Uronis
- Division of Medical Oncology, Duke University Department of Medicine, Durham, North Carolina, USA
| | - S David Hsu
- Division of Medical Oncology, Duke University Department of Medicine, Durham, North Carolina, USA
| | - Herbert I Hurwitz
- Division of Medical Oncology, Duke University Department of Medicine, Durham, North Carolina, USA
| | - Christel Rushing
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Emily K Bolch
- Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Dana A Warren
- Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Ashley N Moyer
- Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Melissa E Lowe
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Donna Niedzwiecki
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
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3
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Coffey DG, Osman K, Aleman A, Bekri S, Kats S, Dhadwal A, Catamero D, Kim-Schulze S, Gnjatic S, Chari A, Parekh S, Jagannath S, Cho HJ. Phase 1 study combining elotuzumab with autologous stem cell transplant and lenalidomide for multiple myeloma. J Immunother Cancer 2024; 12:e008110. [PMID: 38609316 PMCID: PMC11029259 DOI: 10.1136/jitc-2023-008110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/04/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND Autologous stem cell transplantation (ASCT) after induction therapy improves disease-free survival for patients with multiple myeloma (MM). While the goal of ASCT is to render a minimal disease state, it is also associated with eradication of immunosuppressive cells, and we hypothesize that early introduction of immunotherapy post-ASCT may provide a window of opportunity to boost treatment efficacy. METHODS We conducted a phase 1 clinical trial to investigate the application of autologous lymphocyte infusion and anti-SLAMF7 monoclonal antibody, elotuzumab, after ASCT in patients with newly diagnosed MM previously treated with induction therapy. In addition to CD34+ stem cells, peripheral blood mononuclear cells were harvested prior to transplant and infused on day 3 after stem cell infusion to accelerate immune reconstitution and provide autologous natural killer (NK) cells that are essential to the mechanism of elotuzumab. Elotuzumab was administered starting on day 4 and then every 28 days after until 1 year post-ASCT. Cycles 4-12 were administered with standard-of-care lenalidomide maintenance. RESULTS All subjects were evaluated for safety, and 13 of 15 subjects completed the treatment protocol. At 1 year post-ASCT, the disease status of enrolled subjects was as follows: five stringent complete responses, one complete response, six very good partial responses, one partial response, and two progressive diseases. The treatment plan was well tolerated, with most grade 3 and 4 AEs being expected hematologic toxicities associated with ASCT. Correlative analysis of the immune microenvironment demonstrated a trend toward reduced regulatory T cells during the first 3 months post-transplant followed by an increase in NK cells and monocytes in patients achieving a complete remission. CONCLUSIONS This phase 1 clinical trial demonstrates that early introduction of immunotherapy after ASCT is well tolerated and shows promising disease control in patients with MM, accompanied by favorable changes in the immune microenvironment. TRIAL REGISTRATION NUMBER NCT02655458.
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Affiliation(s)
- David G Coffey
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida, USA
| | - Keren Osman
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Adolfo Aleman
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Selma Bekri
- Hematology/Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Simone Kats
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Amishi Dhadwal
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Donna Catamero
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Seunghee Kim-Schulze
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Sacha Gnjatic
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
- Hematology/Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ajai Chari
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Samir Parekh
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Sundar Jagannath
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
| | - Hearn Jay Cho
- Icahn School of Medicine at Mount Sinai Tisch Cancer Institute, New York, New York, USA
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Subramanian K, Varghese R, Pochedly M, Muralidaran V, Yazigi N, Kaufman S, Khan K, Vitola B, Kroemer A, Fishbein T, Ressom H, Ekong UD. Non-fatal outcomes of COVID-19 disease in pediatric organ transplantation associates with down-regulation of senescence pathways. Sci Rep 2024; 14:1877. [PMID: 38253675 PMCID: PMC10803774 DOI: 10.1038/s41598-024-52456-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/18/2024] [Indexed: 01/24/2024] Open
Abstract
This is a cross-sectional study examining kinetics and durability of immune response in children with solid organ transplants (SOTs) who had COVID-19 disease between November 2020 through June 2022, who were followed for 60-days at a single transplant center. Blood was collected between 1-14 (acute infection), and 15-60 days of a positive PCR (convalescence). SOT children with peripheral blood mononuclear cells (PBMC) cryopreserved before 2019 were non-infected controls (ctrls). PBMCs stimulated with 15-mer peptides from spike protein and anti-CD49d/anti-CD28. Testing done included mass cytometry, mi-RNA sequencing with confirmatory qPCR. 38 children formed the study cohort, 10 in the acute phase and 8 in the convalescence phase. 20 subjects were non-infected controls. Two subjects had severe disease. Subjects in the acute and convalescent phases were different subjects. The median age and tacrolimus level at blood draw was not significantly different. There was no death, and no subject was lost to follow-up. During acute infection CD57 expression was low in NKT, Th17 effector memory, memory Treg, CD4-CD8-, and γδT cells (p = 0.01, p = 0.04, p = 0.03, p = 0.03, p = 0.004 respectively). The frequencies of NK and Th2 effector memory cells increased (p = 0.01, p = 0.02) during acute infection. Non-switched memory B and CD8 central memory cell frequencies were decreased during acute infection (p = 0.02; p = 0.02), but the decrease in CD8 central memory cells did not persist. CD4-CD8- and CD14 monocyte frequencies increased during recovery (p = 0.03; p = 0.007). Our observations suggest down regulation of CD57 with absence of NK cell contraction protect against death from COVID-19 disease in children with SOTs.
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Affiliation(s)
- Kumar Subramanian
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Rency Varghese
- Department of Oncology, Genomics, and Epigenomics Shared Resource, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Molly Pochedly
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Vinona Muralidaran
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Nada Yazigi
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Stuart Kaufman
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Khalid Khan
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Bernadette Vitola
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Alexander Kroemer
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Thomas Fishbein
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA
| | - Habtom Ressom
- Department of Oncology, Genomics, and Epigenomics Shared Resource, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
| | - Udeme D Ekong
- Medstar Georgetown Transplant Institute, Medstar Georgetown University Hospital, 3800 Reservoir Rd, NW, Washington, DC, USA.
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5
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Rybakowska P, Alarcón-Riquelme ME, Marañón C. Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings. Methods Mol Biol 2024; 2779:369-394. [PMID: 38526795 DOI: 10.1007/978-1-0716-3738-8_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.
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Affiliation(s)
- Paulina Rybakowska
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
| | - Marta E Alarcón-Riquelme
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
- Institute for Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Concepción Marañón
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain.
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6
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Spurgeon BEJ, Frelinger AL. OMIP-097: High-parameter phenotyping of human platelets by spectral flow cytometry. Cytometry A 2023; 103:935-940. [PMID: 37786346 DOI: 10.1002/cyto.a.24797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/24/2023] [Accepted: 09/12/2023] [Indexed: 10/04/2023]
Abstract
Using spectral flow cytometry, we developed a 16-color panel for analysis of platelet phenotype and function in human whole blood. The panel contains markers of clinical relevance and follows an optimized protocol for the high-parameter phenotyping of (phosphatidylserine positive) procoagulant platelets. Inclusion of established markers, such as CD62P and PAC-1, allows the subsetting of classic (proinflammatory and proaggregatory) phenotypes, while addition of novel markers, such as TLR9, allows the resolution of platelets with nonclassic functions. Multiple inducible (C3b, CD63, CD107a, CD154, and TLT-1) and constitutive (CD29, CD31, CD32, CD36, CD42a, CD61, and GPVI) markers are also measurable, and we demonstrate the use of automatic gating for platelet analysis. The panel is widely applicable to research and clinical settings and can be readily modified, should users wish to tailor the panel to more specific needs.
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Affiliation(s)
- Benjamin E J Spurgeon
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew L Frelinger
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts, USA
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7
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Kare AJ, Nichols L, Zermeno R, Raie MN, Tumbale SK, Ferrara KW. OMIP-095: 40-Color spectral flow cytometry delineates all major leukocyte populations in murine lymphoid tissues. Cytometry A 2023; 103:839-850. [PMID: 37768325 PMCID: PMC10843696 DOI: 10.1002/cyto.a.24788] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 07/26/2023] [Accepted: 08/18/2023] [Indexed: 09/29/2023]
Abstract
High-dimensional immunoprofiling is essential for studying host response to immunotherapy, infection, and disease in murine model systems. However, the difficulty of multiparameter panel design combined with a lack of existing murine tools has prevented the comprehensive study of all major leukocyte phenotypes in a single assay. Herein, we present a 40-color flow cytometry panel for deep immunophenotyping of murine lymphoid tissues, including the spleen, blood, Peyer's patches, inguinal lymph nodes, bone marrow, and thymus. This panel uses a robust set of surface markers capable of differentiating leukocyte subsets without the use of intracellular staining, thus allowing for the use of cells in downstream functional experiments or multiomic analyses. Our panel classifies T cells, B cells, natural killer cells, innate lymphoid cells, monocytes, macrophages, dendritic cells, basophils, neutrophils, eosinophils, progenitors, and their functional subsets by using a series of co-stimulatory, checkpoint, activation, migration, and maturation markers. This tool has a multitude of systems immunology applications ranging from serial monitoring of circulating blood signatures to complex endpoint analysis, especially in pre-clinical settings where treatments can modulate leukocyte abundance and/or function. Ultimately, this 40-color panel resolves a diverse array of immune cells on the axes of time, tissue, and treatment, filling the niche for a modern tool dedicated to murine immunophenotyping.
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Affiliation(s)
- Aris J. Kare
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Lisa Nichols
- Stanford Shared FACS Facility, Stanford University, Stanford, CA 94305, USA
| | - Ricardo Zermeno
- Stanford Shared FACS Facility, Stanford University, Stanford, CA 94305, USA
| | - Marina N. Raie
- Department of Radiology, Stanford University, Stanford, CA 94305, USA
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Thomsen LCV, Kleinmanns K, Anandan S, Gullaksen SE, Abdelaal T, Iversen GA, Akslen LA, McCormack E, Bjørge L. Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study. Cancers (Basel) 2023; 15:5106. [PMID: 37894472 PMCID: PMC10605295 DOI: 10.3390/cancers15205106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/06/2023] [Accepted: 10/17/2023] [Indexed: 10/29/2023] Open
Abstract
The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.
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Affiliation(s)
- Liv Cecilie Vestrheim Thomsen
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, 5021 Bergen, Norway
- Norwegian Institute of Public Health, 5015 Bergen, Norway
| | - Katrin Kleinmanns
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
| | - Shamundeeswari Anandan
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, 5021 Bergen, Norway
| | - Stein-Erik Gullaksen
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
| | - Tamim Abdelaal
- Delft Bioinformatics Laboratory, Delft University of Technology, 2628XE Delft, The Netherlands
- Department of Radiology, Leiden University Medical Center, 2333ZA Leiden, The Netherlands
| | - Grete Alrek Iversen
- Department of Obstetrics and Gynecology, Haukeland University Hospital, 5021 Bergen, Norway
| | - Lars Andreas Akslen
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, 5021 Bergen, Norway
- Department of Pathology, Haukeland University Hospital, 5021 Bergen, Norway
| | - Emmet McCormack
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Centre for Pharmacy, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
| | - Line Bjørge
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, 5021 Bergen, Norway
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9
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Sanz M, Weideman AMK, Ward AR, Clohosey ML, Garcia-Recio S, Selitsky SR, Mann BT, Iannone MA, Whitworth CP, Chitrakar A, Garrido C, Kirchherr J, Coffey AR, Tsai YH, Samir S, Xu Y, Copertino D, Bosque A, Jones BR, Parker JS, Hudgens MG, Goonetilleke N, Soriano-Sarabia N. Aminobisphosphonates reactivate the latent reservoir in people living with HIV-1. Front Immunol 2023; 14:1219250. [PMID: 37744358 PMCID: PMC10516574 DOI: 10.3389/fimmu.2023.1219250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023] Open
Abstract
Antiretroviral therapy (ART) is not curative due to the existence of cellular reservoirs of latent HIV-1 that persist during therapy. Current research efforts to cure HIV-1 infection include "shock and kill" strategies to disrupt latency using small molecules or latency-reversing agents (LRAs) to induce expression of HIV-1 enabling cytotoxic immune cells to eliminate infected cells. The modest success of current LRAs urges the field to identify novel drugs with increased clinical efficacy. Aminobisphosphonates (N-BPs) that include pamidronate, zoledronate, or alendronate, are the first-line treatment of bone-related diseases including osteoporosis and bone malignancies. Here, we show the use of N-BPs as a novel class of LRA: we found in ex vivo assays using primary cells from ART-suppressed people living with HIV-1 that N-BPs induce HIV-1 from latency to levels that are comparable to the T cell activator phytohemagglutinin (PHA). RNA sequencing and mechanistic data suggested that reactivation may occur through activation of the activator protein 1 signaling pathway. Stored samples from a prior clinical trial aimed at analyzing the effect of alendronate on bone mineral density, provided further evidence of alendronate-mediated latency reversal and activation of immune effector cells. Decay of the reservoir measured by IPDA was however not detected. Our results demonstrate the novel use of N-BPs to reverse HIV-1 latency while inducing immune effector functions. This preliminary evidence merits further investigation in a controlled clinical setting possibly in combination with therapeutic vaccination.
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Affiliation(s)
- Marta Sanz
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
| | - Ann Marie K. Weideman
- Biostatistics Core, Center for AIDS Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Adam R. Ward
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
- Department of Infectious Diseases, Weill Cornell Medicine, New York, NY, United States
| | - Matthew L. Clohosey
- UNC HIV Cure Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Susana Garcia-Recio
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sara R. Selitsky
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Brendan T. Mann
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
| | - Marie Anne Iannone
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Chloe P. Whitworth
- UNC HIV Cure Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Alisha Chitrakar
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
| | - Carolina Garrido
- UNC HIV Cure Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jennifer Kirchherr
- UNC HIV Cure Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Alisha R. Coffey
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yi- Hsuan Tsai
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Shahryar Samir
- Microbiology & Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yinyan Xu
- Microbiology & Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Dennis Copertino
- Department of Infectious Diseases, Weill Cornell Medicine, New York, NY, United States
| | - Alberto Bosque
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
| | - Brad R. Jones
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
- Department of Infectious Diseases, Weill Cornell Medicine, New York, NY, United States
| | - Joel S. Parker
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Michael G. Hudgens
- Biostatistics Core, Center for AIDS Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Nilu Goonetilleke
- Microbiology & Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Natalia Soriano-Sarabia
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington, DC, United States
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10
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Coffey DG, Maura F, Gonzalez-Kozlova E, Diaz-Mejia JJ, Luo P, Zhang Y, Xu Y, Warren EH, Dawson T, Lee B, Xie H, Smith E, Ciardiello A, Cho HJ, Rahman A, Kim-Schulze S, Diamond B, Lesokhin A, Kazandjian D, Pugh TJ, Green DJ, Gnjatic S, Landgren O. Immunophenotypic correlates of sustained MRD negativity in patients with multiple myeloma. Nat Commun 2023; 14:5335. [PMID: 37660077 PMCID: PMC10475030 DOI: 10.1038/s41467-023-40966-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/18/2023] [Indexed: 09/04/2023] Open
Abstract
The role of the immune microenvironment in maintaining disease remission in patients with multiple myeloma (MM) is not well understood. In this study, we comprehensively profile the immune system in patients with newly diagnosed MM receiving continuous lenalidomide maintenance therapy with the aim of discovering correlates of long-term treatment response. Leveraging single-cell RNA sequencing and T cell receptor β sequencing of the peripheral blood and CyTOF mass cytometry of the bone marrow, we longitudinally characterize the immune landscape in 23 patients before and one year after lenalidomide exposure. We compare patients achieving sustained minimal residual disease (MRD) negativity to patients who never achieved or were unable to maintain MRD negativity. We observe that the composition of the immune microenvironment in both the blood and the marrow varied substantially according to both MRD negative status and history of autologous stem cell transplant, supporting the hypothesis that the immune microenvironment influences the depth and duration of treatment response.
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Affiliation(s)
- David G Coffey
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA.
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Francesco Maura
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | | | - J Javier Diaz-Mejia
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Ping Luo
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Yong Zhang
- Office of Oncologic Diseases, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Yuexin Xu
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Edus H Warren
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Travis Dawson
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Lee
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hui Xie
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eric Smith
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Amanda Ciardiello
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hearn J Cho
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Multiple Myeloma Research Foundation, Norwalk, USA
| | - Adeeb Rahman
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Benjamin Diamond
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | - Alexander Lesokhin
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dickran Kazandjian
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | - Trevor J Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Damian J Green
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sacha Gnjatic
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ola Landgren
- Division of Myeloma, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA.
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11
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Simon Davis DA, Ritchie M, Hammill D, Garrett J, Slater RO, Otoo N, Orlov A, Gosling K, Price J, Yip D, Jung K, Syed FM, Atmosukarto II, Quah BJC. Identifying cancer-associated leukocyte profiles using high-resolution flow cytometry screening and machine learning. Front Immunol 2023; 14:1211064. [PMID: 37600768 PMCID: PMC10435879 DOI: 10.3389/fimmu.2023.1211064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/26/2023] [Indexed: 08/22/2023] Open
Abstract
BACKGROUND Machine learning (ML) is a valuable tool with the potential to aid clinical decision making. Adoption of ML to this end requires data that reliably correlates with the clinical outcome of interest; the advantage of ML is that it can model these correlations from complex multiparameter data sets that can be difficult to interpret conventionally. While currently available clinical data can be used in ML for this purpose, there exists the potential to discover new "biomarkers" that will enhance the effectiveness of ML in clinical decision making. Since the interaction of the immune system and cancer is a hallmark of tumor establishment and progression, one potential area for cancer biomarker discovery is through the investigation of cancer-related immune cell signatures. Hence, we hypothesize that blood immune cell signatures can act as a biomarker for cancer progression. METHODS To probe this, we have developed and tested a multiparameter cell-surface marker screening pipeline, using flow cytometry to obtain high-resolution systemic leukocyte population profiles that correlate with detection and characterization of several cancers in murine syngeneic tumor models. RESULTS We discovered a signature of several blood leukocyte subsets, the most notable of which were monocyte subsets, that could be used to train CATboost ML models to predict the presence and type of cancer present in the animals. CONCLUSIONS Our findings highlight the potential utility of a screening approach to identify robust leukocyte biomarkers for cancer detection and characterization. This pipeline can easily be adapted to screen for cancer specific leukocyte markers from the blood of cancer patient.
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Affiliation(s)
- David A. Simon Davis
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
| | - Melissa Ritchie
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
| | - Dillon Hammill
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Jessica Garrett
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Robert O. Slater
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Naomi Otoo
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Anna Orlov
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Katharine Gosling
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
| | - Jason Price
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Desmond Yip
- Australian National University, Canberra, ACT, Australia
- Department of Medical Oncology, Canberra Hospital & Health Services, Canberra, ACT, Australia
| | - Kylie Jung
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
- Radiation Oncology Department, Canberra Hospital & Health Services, Canberra, ACT, Australia
| | - Farhan M. Syed
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
- Radiation Oncology Department, Canberra Hospital & Health Services, Canberra, ACT, Australia
| | - Ines I. Atmosukarto
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
- Division of Genome Sciences & Cancer, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Ben J. C. Quah
- Irradiation Immunity Interaction Lab, Australian National University, Canberra, ACT, Australia
- Radiation Oncology Department, Canberra Hospital & Health Services, Canberra, ACT, Australia
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12
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Mas G, Man N, Nakata Y, Martinez-Caja C, Karl D, Beckedorff F, Tamiro F, Chen C, Duffort S, Itonaga H, Mookhtiar AK, Kunkalla K, Valencia AM, Collings CK, Kadoch C, Vega F, Kogan SC, Shiekhattar R, Morey L, Bilbao D, Nimer SD. The SWI/SNF chromatin-remodeling subunit DPF2 facilitates NRF2-dependent antiinflammatory and antioxidant gene expression. J Clin Invest 2023; 133:e158419. [PMID: 37200093 PMCID: PMC10313367 DOI: 10.1172/jci158419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/16/2023] [Indexed: 05/20/2023] Open
Abstract
During emergency hematopoiesis, hematopoietic stem cells (HSCs) rapidly proliferate to produce myeloid and lymphoid effector cells, a response that is critical against infection or tissue injury. If unresolved, this process leads to sustained inflammation, which can cause life-threatening diseases and cancer. Here, we identify a role of double PHD fingers 2 (DPF2) in modulating inflammation. DPF2 is a defining subunit of the hematopoiesis-specific BAF (SWI/SNF) chromatin-remodeling complex, and it is mutated in multiple cancers and neurological disorders. We uncovered that hematopoiesis-specific Dpf2-KO mice developed leukopenia, severe anemia, and lethal systemic inflammation characterized by histiocytic and fibrotic tissue infiltration resembling a clinical hyperinflammatory state. Dpf2 loss impaired the polarization of macrophages responsible for tissue repair, induced the unrestrained activation of Th cells, and generated an emergency-like state of HSC hyperproliferation and myeloid cell-biased differentiation. Mechanistically, Dpf2 deficiency resulted in the loss of the BAF catalytic subunit BRG1 from nuclear factor erythroid 2-like 2-controlled (NRF2-controlled) enhancers, impairing the antioxidant and antiinflammatory transcriptional response needed to modulate inflammation. Finally, pharmacological reactivation of NRF2 suppressed the inflammation-mediated phenotypes and lethality of Dpf2Δ/Δ mice. Our work establishes an essential role of the DPF2-BAF complex in licensing NRF2-dependent gene expression in HSCs and immune effector cells to prevent chronic inflammation.
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Affiliation(s)
- Gloria Mas
- Sylvester Comprehensive Cancer Center and
| | - Na Man
- Sylvester Comprehensive Cancer Center and
| | - Yuichiro Nakata
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | | | | | - Felipe Beckedorff
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | | | - Chuan Chen
- Sylvester Comprehensive Cancer Center and
| | | | | | | | | | - Alfredo M. Valencia
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Chemical Biology Program, Harvard University, Cambridge, Massachusetts, USA
| | - Clayton K. Collings
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Cigall Kadoch
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Francisco Vega
- Sylvester Comprehensive Cancer Center and
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Scott C. Kogan
- Helen Diller Family Comprehensive Cancer Center and
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - Ramin Shiekhattar
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Lluis Morey
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Daniel Bilbao
- Sylvester Comprehensive Cancer Center and
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Stephen D. Nimer
- Sylvester Comprehensive Cancer Center and
- Department of Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
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13
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Farooqui N, Zaidi M, Vaughan L, McKee TD, Ahsan E, Pavelko KD, Villasboas JC, Markovic S, Taner T, Leung N, Dong H, Alexander MP, Herrmann SM. Cytokines and Immune Cell Phenotype in Acute Kidney Injury Associated With Immune Checkpoint Inhibitors. Kidney Int Rep 2023; 8:628-641. [PMID: 36938084 PMCID: PMC10014345 DOI: 10.1016/j.ekir.2022.11.020] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/25/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022] Open
Abstract
Introduction Immune checkpoint inhibitors (ICIs) induce impressive antitumor responses but may lead to acute kidney injury (AKI) associated with ICI therapy (AKI-ICI). Biomarkers distinguishing AKI-ICI from AKI because of other causes (AKI-other) are currently lacking. Because ICIs block immunoregulatory pathways, we hypothesized that biomarkers related to immune cell dysregulation, including tumor necrosis factor alpha (TNF-α) and other markers of B and T cell activation in the systemic circulation and kidney tissue, may aid with the diagnosis of AKI-ICI. Methods This is a prospective study consisting of 24 participants who presented with AKI during ICI therapy, adjudicated to either have AKI-ICI (n = 14) or AKI-other (n = 10). We compared markers of kidney inflammation and injury (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1) as well as plasma and urine levels of T cell-associated cytokines (TNF-α, interferon-γ, interleukin (IL)-2, IL-4, IL-6, IL-8, IL-9, and IL-10) between groups. We also compared T-cell responses in the systemic circulation and in kidney tissue across groups, using mass cytometry systems. Results We observed increase in several specific immune cells, including CD4 memory, T helper cells, and dendritic cells in the kidney tissue, as well as in the urine cytokines IL-2, IL-10, and TNF-α, in patients who developed AKI-ICI compared to patients with AKI-other (P < 0.05 for all). The discriminatory ability of TNF-α on AKI cause was strong (area under the curve = 0.814, 95% confidence interval: 0.623-1.00. The CD4+ T cells with memory phenotype formed the dominant subset. Conclusion These results suggest that specific T-cell responses and their respective cytokines may be indicative of AKI associated with ICI therapy and may help to differentiate AKI-ICI from AKI-other. Urine TNF-α is a promising biomarker for AKI-ICI, which is most often caused by acute interstitial nephritis (AIN), and TNF-α pathway may serve as a potential target for therapeutic intervention.
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Affiliation(s)
- Naba Farooqui
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark Zaidi
- Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Lisa Vaughan
- Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Trevor D. McKee
- Department of Medical Biophysics, University of Toronto, Ontario, Canada
- Deciphex Inc., Chicago, Illinois, USA
| | - Eram Ahsan
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Kevin D. Pavelko
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | | | | | - Timucin Taner
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Nelson Leung
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Haidong Dong
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Mariam P. Alexander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Sandra M. Herrmann
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
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14
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Parker S, McDowall C, Sanchez-Perez L, Osorio C, Duncker PC, Briley A, Swartz AM, Herndon JE, Yu YRA, McLendon RE, Tedder TF, Desjardins A, Ashley DM, Gunn MD, Enterline DS, Knorr DA, Pastan IH, Nair SK, Bigner DD, Chandramohan V. Immunotoxin-αCD40 therapy activates innate and adaptive immunity and generates a durable antitumor response in glioblastoma models. Sci Transl Med 2023; 15:eabn5649. [PMID: 36753564 PMCID: PMC10440725 DOI: 10.1126/scitranslmed.abn5649] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 01/17/2023] [Indexed: 02/10/2023]
Abstract
D2C7-immunotoxin (IT), a dual-specific IT targeting wild-type epidermal growth factor receptor (EGFR) and mutant EGFR variant III (EGFRvIII) proteins, demonstrates encouraging survival outcomes in a subset of patients with glioblastoma. We hypothesized that immunosuppression in glioblastoma limits D2C7-IT efficacy. To improve the response rate and reverse immunosuppression, we combined D2C7-IT tumor cell killing with αCD40 costimulation of antigen-presenting cells. In murine glioma models, a single intratumoral injection of D2C7-IT+αCD40 treatment activated a proinflammatory phenotype in microglia and macrophages, promoted long-term tumor-specific CD8+ T cell immunity, and generated cures. D2C7-IT+αCD40 treatment increased intratumoral Slamf6+CD8+ T cells with a progenitor phenotype and decreased terminally exhausted CD8+ T cells. D2C7-IT+αCD40 treatment stimulated intratumoral CD8+ T cell proliferation and generated cures in glioma-bearing mice despite FTY720-induced peripheral T cell sequestration. Tumor transcriptome profiling established CD40 up-regulation, pattern recognition receptor, cell senescence, and immune response pathway activation as the drivers of D2C7-IT+αCD40 antitumor responses. To determine potential translation, immunohistochemistry staining confirmed CD40 expression in human GBM tissue sections. These promising preclinical data allowed us to initiate a phase 1 study with D2C7-IT+αhCD40 in patients with malignant glioma (NCT04547777) to further evaluate this treatment in humans.
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Affiliation(s)
- Scott Parker
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Charlotte McDowall
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Luis Sanchez-Perez
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Cristina Osorio
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | | | - Aaron Briley
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Adam M Swartz
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
| | - James E Herndon
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA
| | - Yen-Rei A Yu
- Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Roger E McLendon
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
| | - Thomas F Tedder
- Department of Immunology, Duke University Medical Center, Durham, NC 27710, USA
| | - Annick Desjardins
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - David M Ashley
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
| | - Michael Dee Gunn
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
- Department of Immunology, Duke University Medical Center, Durham, NC 27710, USA
- Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - David S Enterline
- Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - David A Knorr
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Ira H Pastan
- Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Smita K Nair
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
| | - Darell D Bigner
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
| | - Vidyalakshmi Chandramohan
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
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15
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Sanz M, Weideman AMK, Ward AR, Clohosey ML, Garcia-Recio S, Selitsky SR, Mann BT, Iannone MA, Whitworth CP, Chitrakar A, Garrido C, Kirchherr J, Coffey AR, Tsai YH, Samir S, Xu Y, Copertino D, Bosque A, Jones BR, Parker JS, Hudgens MG, Goonetilleke N, Soriano-Sarabia N. Aminobisphosphonates reactivate the latent reservoir in people living with HIV-1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.07.527421. [PMID: 36798291 PMCID: PMC9934553 DOI: 10.1101/2023.02.07.527421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Antiretroviral therapy (ART) is not curative due to the existence of cellular reservoirs of latent HIV-1 that persist during therapy. Current research efforts to cure HIV-1 infection include "shock and kill" strategies to disrupt latency using small molecules or latency-reversing agents (LRAs) to induce expression of HIV-1 enabling cytotoxic immune cells to eliminate infected cells. The modest success of current LRAs urges the field to identify novel drugs with increased clinical efficacy. Aminobisphosphonates (N-BPs) that include pamidronate, zoledronate, or alendronate, are the first-line treatment of bone-related diseases including osteoporosis and bone malignancies. Here, we show the use of N-BPs as a novel class of LRA: we found in ex vivo assays using primary cells from ART-suppressed people living with HIV-1 that N-BPs induce HIV-1 from latency to levels that are comparable to the T cell activator phytohemagglutinin (PHA). RNA sequencing and mechanistic data suggested that reactivation may occur through activation of the activator protein 1 signaling pathway. Stored samples from a prior clinical trial aimed at analyzing the effect of alendronate on bone mineral density, provided further evidence of alendronate-mediated latency reversal and activation of immune effector cells. Decay of the reservoir measured by IPDA was however not detected. Our results demonstrate the novel use of N-BPs to reverse HIV-1 latency while inducing immune effector functions. This preliminary evidence merits further investigation in a controlled clinical setting possibly in combination with therapeutic vaccination.
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Affiliation(s)
- Marta Sanz
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
| | - Ann Marie K. Weideman
- Department of Biostatistics, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Adam R. Ward
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
- Department of Infectious Diseases, Weill Cornell Medicine, New York, USA
| | - Matthew L. Clohosey
- UNC HIV-1 Cure Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Susana Garcia-Recio
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Sara R. Selitsky
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Brendan T. Mann
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
| | - Marie Anne Iannone
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Chloe P. Whitworth
- UNC HIV-1 Cure Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Alisha Chitrakar
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
| | - Carolina Garrido
- UNC HIV-1 Cure Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Jennifer Kirchherr
- UNC HIV-1 Cure Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Alisha R. Coffey
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Yi-Hsuan Tsai
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Shahryar Samir
- Microbiology & Immunology, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Yinyan Xu
- Microbiology & Immunology, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Dennis Copertino
- Department of Infectious Diseases, Weill Cornell Medicine, New York, USA
| | - Alberto Bosque
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
| | - Brad R. Jones
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
- Department of Infectious Diseases, Weill Cornell Medicine, New York, USA
| | - Joel S. Parker
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Michael G. Hudgens
- Department of Biostatistics, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Nilu Goonetilleke
- Microbiology & Immunology, University of North Carolina at Chapel Hill, North Carolina, USA
| | - Natalia Soriano-Sarabia
- Department of Microbiology Immunology and Tropical Medicine, the George Washington University, Washington DC, USA
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16
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Spurgeon BEJ, Frelinger AL. Platelet Phenotyping by Full Spectrum Flow Cytometry. Curr Protoc 2023; 3:e687. [PMID: 36779850 DOI: 10.1002/cpz1.687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Platelets play key roles in hemostasis, immunity, and inflammation, and tests of platelet phenotype and function are useful in studies of disease biology and pathology. Full spectrum flow cytometry offers distinct advantages over standard tests and enables the sensitive and simultaneous detection of many biomarkers. A typical assay provides a wealth of information on platelet biology and allows the assessment of in vivo activation and in vitro reactivity, as well as the discovery of novel phenotypes. Here, we describe the analysis of platelets by full spectrum flow cytometry and discuss a range of controls and methods for interpreting results. © 2023 Wiley Periodicals LLC. Basic Protocol: Platelet phenotyping by full spectrum flow cytometry Support Protocol 1: Spectral unmixing Support Protocol 2: Data preprocessing.
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Affiliation(s)
- Benjamin E J Spurgeon
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts
| | - Andrew L Frelinger
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts
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17
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Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers. Semin Immunopathol 2023; 45:61-69. [PMID: 36625902 DOI: 10.1007/s00281-022-00981-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 12/11/2022] [Indexed: 01/11/2023]
Abstract
Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.
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18
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Rybakowska P, Van Gassen S, Martorell Marugán J, Quintelier K, Saeys Y, Alarcón-Riquelme ME, Marañón C. Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline. STAR Protoc 2022; 3:101697. [PMID: 36353363 PMCID: PMC9637821 DOI: 10.1016/j.xpro.2022.101697] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Mass cytometry (MC) is a powerful large-scale immune monitoring technology. To maximize MC data quality, we present a protocol for whole blood analysis together with an R package, Cyto Quality Pipeline (CytoQP), which minimizes the experimental artifacts and batch effects to ensure data reproducibility. We describe the steps to stimulate, fix, and freeze blood samples before acquisition to make them suitable for retrospective studies. We then detail the use of barcoding and reference samples to facilitate multicenter and multi-batch experiments. For complete details on the use and execution of this protocol, please refer to Rybakowska et al. (2021a) and (2021b).
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Affiliation(s)
- Paulina Rybakowska
- GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain.
| | - Sofie Van Gassen
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium
| | - Jordi Martorell Marugán
- GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain; Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain; Data Science for Health Research Unit, Fondazione Bruno Kessler, 38123 Trento, Italy
| | - Katrien Quintelier
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium; Department of Pulmonary Diseases, Erasmus MC, 3015 Rotterdam, the Netherlands
| | - Yvan Saeys
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium
| | - Marta E Alarcón-Riquelme
- GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain; Institute for Environmental Medicine, Karolinska Institute, 17177 Stockholm, Sweden
| | - Concepción Marañón
- GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain.
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19
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Imanishi M, Cheng H, Kotla S, Deswal A, Le NT, Chini E, Ko KA, Samanthapudi VSK, Lee LL, Herrmann J, Xu X, Reyes-Gibby C, Yeung SCJ, Schadler KL, Yusuf SW, Liao Z, Nurieva R, Amir EAD, Burks JK, Palaskas NL, Cooke JP, Lin SH, Kobayashi M, Yoshimoto M, Abe JI. Radiation therapy induces immunosenescence mediated by p90RSK. Front Cardiovasc Med 2022; 9:988713. [PMID: 36426217 PMCID: PMC9680092 DOI: 10.3389/fcvm.2022.988713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
Radiation therapy (RT) to the chest increases the patients' risk of cardiovascular disease (CVD). A complete understanding of the mechanisms by which RT induces CVD could lead to specific preventive, therapeutic approaches. It is becoming evident that both genotoxic chemotherapy agents and radiation induce mitochondrial dysfunction and cellular senescence. Notably, one of the common phenotypes observed in cancer survivors is accelerated senescence, and immunosenescence is closely related to both cancer risk and CVD development. Therefore, suppression of immunosenescence can be an ideal target to prevent cancer treatment-induced CVD. However, the mechanism(s) by which cancer treatments induce immunosenescence are incompletely characterized. We isolated peripheral blood mononuclear cells (PBMCs) before and 3 months after RT from 16 thoracic cancer patients. We characterized human immune cell lineages and markers of senescence, DNA damage response (DDR), efferocytosis, and determinants of clonal hematopoiesis of indeterminant potential (CHIP), using mass cytometry (CyTOF). We found that the frequency of the B cell subtype was decreased after RT. Unsupervised clustering of the CyTOF data identified 138 functional subsets of PBMCs. Compared with baseline, RT increased TBX21 (T-bet) expression in the largest B cell subset of Ki67-/DNMT3a+naïve B cells, and T-bet expression was correlated with phosphorylation of p90RSK expression. CD38 expression was also increased in naïve B cells (CD27-) and CD8+ effector memory CD45RA T cells (TEMRA). In vitro, we found the critical role of p90RSK activation in upregulating (1) CD38+/T-bet+ memory and naïve B, and myeloid cells, (2) senescence-associated β-gal staining, and (3) mitochondrial reactive oxygen species (ROS) after ionizing radiation (IR). These data suggest the crucial role of p90RSK activation in immunosenescence. The critical role of p90RSK activation in immune cells and T-bet induction in upregulating atherosclerosis formation has been reported. Furthermore, T-bet directly binds to the CD38 promoter region and upregulates CD38 expression. Since both T-bet and CD38 play a significant role in the process of immunosenescence, our data provide a cellular and molecular mechanism that links RT-induced p90RSK activation and the immunosenescence with T-bet and CD38 induction observed in thoracic cancer patients treated by RT and suggests that targeting the p90RSK/T-bet/CD38 pathway could play a role in preventing the radiation-associated CVD and improving cancer prognosis by inhibiting immunosenescence.
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Affiliation(s)
- Masaki Imanishi
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Haizi Cheng
- Center for Stem Cell and Regenerative Medicine, Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Sivareddy Kotla
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Anita Deswal
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Nhat-Tu Le
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, United States
| | - Eduardo Chini
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Jacksonville, FL, United States
| | - Kyung Ae Ko
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | | | - Ling-Ling Lee
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Joerg Herrmann
- Division of Preventive Cardiology, Cardio Oncology Clinic, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Xiaolei Xu
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, United States
| | - Cielito Reyes-Gibby
- Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sai-Ching J. Yeung
- Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Keri L. Schadler
- Department of Pediatric Research, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Syed Wamique Yusuf
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Zhongxing Liao
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Roza Nurieva
- Division of Basic Science, Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | | | - Jared K. Burks
- Division of Center Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Nicolas L. Palaskas
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - John P. Cooke
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, United States
| | - Steven H. Lin
- Department of Pediatric Research, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Michihiro Kobayashi
- Center for Stem Cell and Regenerative Medicine, Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Momoko Yoshimoto
- Center for Stem Cell and Regenerative Medicine, Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Jun-ichi Abe
- Department of Cardiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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20
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Jaimes MC, Leipold M, Kraker G, Amir E, Maecker H, Lannigan J. Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison. Cytometry A 2022; 101:942-959. [PMID: 35593221 PMCID: PMC9790709 DOI: 10.1002/cyto.a.24565] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 02/23/2022] [Accepted: 04/25/2022] [Indexed: 01/27/2023]
Abstract
High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.
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Affiliation(s)
| | - Michael Leipold
- Department of Microbiology/ImmunologyStanford UniversityStanfordCaliforniaUSA
| | - Geoffrey Kraker
- Technical Applications SupportCytek Biosciences Inc.FremontCaliforniaUSA
| | - El‐ad Amir
- Astrolabe DiagnosticsFort LeeNew JerseyUSA
| | - Holden Maecker
- Department of Microbiology/ImmunologyStanford UniversityStanfordCaliforniaUSA
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21
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Sarkar I, Davies R, Aarebrot AK, Solberg SM, Petrovic A, Joshi AM, Bergum B, Brun JG, Hammenfors D, Jonsson R, Appel S. Aberrant signaling of immune cells in Sjögren’s syndrome patient subgroups upon interferon stimulation. Front Immunol 2022; 13:854183. [PMID: 36072585 PMCID: PMC9441756 DOI: 10.3389/fimmu.2022.854183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundPrimary Sjögren’s syndrome (pSS) is a systemic autoimmune disease, characterized by mononuclear cell infiltrates in the salivary and lacrimal glands, leading to glandular atrophy and dryness. Patient heterogeneity and lack of knowledge regarding its pathogenesis makes pSS a difficult disease to manage.MethodsAn exploratory analysis using mass cytometry was conducted of MAPK/ERK and JAK/STAT signaling pathways in peripheral blood mononuclear cells (PBMC) from 16 female medication free pSS patients (8 anti-Sjögren’s syndrome-related antigen A negative/SSA- and 8 SSA+) and 8 female age-matched healthy donors after stimulation with interferons (IFNs).ResultsWe found significant differences in the frequencies of memory B cells, CD8+ T central and effector memory cells and terminally differentiated CD4+ T cells among the healthy donors and patient subgroups. In addition, we observed an upregulation of HLA-DR and CD38 in many cell subsets in the patients. Upon IFNα2b stimulation, slightly increased signaling through pSTAT1 Y701 was observed in most cell types in pSS patients compared to controls, while phosphorylation of STAT3 Y705 and STAT5 Y694 were slightly reduced. IFNγ stimulation resulted in significantly increased pSTAT1 Y701 induction in conventional dendritic cells (cDCs) and classical and non-classical monocytes in the patients. Most of the observed differences were more prominent in the SSA+ subgroup, indicating greater disease severity in them.ConclusionsAugmented activation status of certain cell types along with potentiated pSTAT1 Y701 signaling and reduced pSTAT3 Y705 and pSTAT5 Y694 induction may predispose pSS patients, especially the SSA+ subgroup, to upregulated expression of IFN-induced genes and production of autoantibodies. These patients may benefit from therapies targeting these pathways.
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Affiliation(s)
- Irene Sarkar
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
- *Correspondence: Irene Sarkar, ; Silke Appel,
| | - Richard Davies
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders K. Aarebrot
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Silje M. Solberg
- Department of Dermatology, Haukeland University Hospital, Bergen, Norway
| | - Aleksandra Petrovic
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anagha M. Joshi
- Computational Biology Unit, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Brith Bergum
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
- Core Facility for Flow Cytometry, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Johan G. Brun
- Department of Rheumatology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Daniel Hammenfors
- Department of Rheumatology, Haukeland University Hospital, Bergen, Norway
| | - Roland Jonsson
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Silke Appel
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
- Core Facility for Flow Cytometry, Department of Clinical Science, University of Bergen, Bergen, Norway
- *Correspondence: Irene Sarkar, ; Silke Appel,
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22
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Serra V, Orrù V, Lai S, Lobina M, Steri M, Cucca F, Fiorillo E. Comparison of Whole Blood Cryopreservation Methods for Extensive Flow Cytometry Immunophenotyping. Cells 2022; 11:cells11091527. [PMID: 35563832 PMCID: PMC9103885 DOI: 10.3390/cells11091527] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/24/2022] Open
Abstract
Fresh blood immunophenotyping by flow cytometry, based on the reliable simultaneous detection of several markers in a cell, is the method of choice to study the circulating human immune system. Especially in large and multicenter studies, high sample quality is difficult to achieve, and adequate collection and storage of samples with fine-tuned whole blood cryopreservation is mandatory. Here, we compared the quality of immunophenotypic data obtained from fresh blood with those obtained after five cryopreservation methods by quantifying the levels of 41 immune cell populations. They comprised B and T lymphocyte subsets and their maturation stages, as well as monocytes and granulocytes. Three methods used fixative solutions and two other methods used dimethyl sulfoxide solutions to preserve cell viability. The fixative methods prevented detection of markers critical for identification of B and T cell subsets, including CD27, CXCR3, and CCR6. The other two methods permitted reliable discrimination of most immune-cell populations in thawed samples, though some cell frequencies varied compared to the corresponding fresh sample. Of those two methods, the one preserving blood in media containing dimethyl sulfoxide produced results that were most similar to those with fresh samples.
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Affiliation(s)
- Valentina Serra
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
- Correspondence:
| | - Valeria Orrù
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
| | - Sandra Lai
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
| | - Monia Lobina
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
| | - Maristella Steri
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
| | - Francesco Cucca
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
| | - Edoardo Fiorillo
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Cittadella Universitaria di Monserrato, 09042 Cagliari, Italy; (V.O.); (S.L.); (M.L.); (M.S.); (F.C.); (E.F.)
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23
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Abstract
Mass cytometry has revolutionized immunophenotyping, particularly in exploratory settings where simultaneous breadth and depth of characterization of immune populations is needed with limited samples such as in preclinical and clinical tumor immunotherapy. Mass cytometry is also a powerful tool for single-cell immunological assays, especially for complex and simultaneous characterization of diverse intratumoral immune subsets or immunotherapeutic cell populations. Through the elimination of spectral overlap seen in optical flow cytometry by replacement of fluorescent labels with metal isotopes, mass cytometry allows, on average, robust analysis of 60 individual parameters simultaneously. This is, however, associated with significantly increased complexity in the design, execution, and interpretation of mass cytometry experiments. To address the key pitfalls associated with the fragmentation, complexity, and analysis of data in mass cytometry for immunologists who are novices to these techniques, we have developed a comprehensive resource guide. Included in this review are experiment and panel design, antibody conjugations, sample staining, sample acquisition, and data pre-processing and analysis. Where feasible multiple resources for the same process are compared, allowing researchers experienced in flow cytometry but with minimal mass cytometry expertise to develop a data-driven and streamlined project workflow. It is our hope that this manuscript will prove a useful resource for both beginning and advanced users of mass cytometry.
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Affiliation(s)
- Akshay Iyer
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, United States
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Anouk A. J. Hamers
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, United States
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, United States
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Asha B. Pillai
- Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, United States
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, United States
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, United States
- Sheila and David Fuente Program in Cancer Biology, University of Miami Miller School of Medicine, Miami, FL, United States
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24
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Michelozzi IM, Sufi J, Adejumo TA, Amrolia PJ, Tape CJ, Giustacchini A. High-dimensional functional phenotyping of preclinical human CAR T cells using mass cytometry. STAR Protoc 2022; 3:101174. [PMID: 35199038 PMCID: PMC8844283 DOI: 10.1016/j.xpro.2022.101174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Here, we present a comprehensive protocol for the generation and functional characterization of chimeric antigen receptor (CAR) T cells and their products by mass cytometry in a reproducible and scalable manner. We describe the production of CAR T cells from human peripheral blood mononuclear cells. We then detail a three-step staining protocol with metal-labeled antibodies and the subsequent mass cytometry analysis. This protocol allows simultaneous characterization of CAR T cell intracellular signaling, activation, proliferation, cytokine production, and phenotype in a single assay.
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Affiliation(s)
- Ilaria M. Michelozzi
- Molecular and Cellular Immunology Section, UCL Great Ormond Street Institute of Child Health, Zayed Centre For Research into Rare Disease in Children, WC1N 1DZ London, UK
| | - Jahangir Sufi
- Cell Communication Lab, Department of Oncology, University College London Cancer Institute, WC1E 6DD London, UK
| | | | - Persis J. Amrolia
- Molecular and Cellular Immunology Section, UCL Great Ormond Street Institute of Child Health, Zayed Centre For Research into Rare Disease in Children, WC1N 1DZ London, UK
- Department of Bone Marrow Transplant, Great Ormond Street Hospital for Children, WC1N 3JH London, UK
| | - Christopher J. Tape
- Cell Communication Lab, Department of Oncology, University College London Cancer Institute, WC1E 6DD London, UK
| | - Alice Giustacchini
- Molecular and Cellular Immunology Section, UCL Great Ormond Street Institute of Child Health, Zayed Centre For Research into Rare Disease in Children, WC1N 1DZ London, UK
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25
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Chalabi Hajkarim M, Karjalainen E, Osipovitch M, Dimopoulos K, Gordon SL, Ambri F, Rasmussen KD, Grønbæk K, Helin K, Wennerberg K, Won KJ. Comprehensive and unbiased multiparameter high-throughput screening by compaRe finds effective and subtle drug responses in AML models. eLife 2022; 11:e73760. [PMID: 35166670 PMCID: PMC9020823 DOI: 10.7554/elife.73760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 02/14/2022] [Indexed: 12/01/2022] Open
Abstract
Large-scale multiparameter screening has become increasingly feasible and straightforward to perform thanks to developments in technologies such as high-content microscopy and high-throughput flow cytometry. The automated toolkits for analyzing similarities and differences between large numbers of tested conditions have not kept pace with these technological developments. Thus, effective analysis of multiparameter screening datasets becomes a bottleneck and a limiting factor in unbiased interpretation of results. Here we introduce compaRe, a toolkit for large-scale multiparameter data analysis, which integrates quality control, data bias correction, and data visualization methods with a mass-aware gridding algorithm-based similarity analysis providing a much faster and more robust analyses than existing methods. Using mass and flow cytometry data from acute myeloid leukemia and myelodysplastic syndrome patients, we show that compaRe can reveal interpatient heterogeneity and recognizable phenotypic profiles. By applying compaRe to high-throughput flow cytometry drug response data in AML models, we robustly identified multiple types of both deep and subtle phenotypic response patterns, highlighting how this analysis could be used for therapeutic discoveries. In conclusion, compaRe is a toolkit that uniquely allows for automated, rapid, and precise comparisons of large-scale multiparameter datasets, including high-throughput screens.
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Affiliation(s)
- Morteza Chalabi Hajkarim
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
| | - Ella Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of HelsinkiHelsinkiFinland
| | - Mikhail Osipovitch
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
| | | | - Sandra L Gordon
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
| | - Francesca Ambri
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
| | - Kasper Dindler Rasmussen
- Centre for Gene Regulation and Expression, School of Life Sciences, University of DundeeDundeeUnited Kingdom
| | - Kirsten Grønbæk
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
- RigshospitaletCopenhagenDenmark
| | - Kristian Helin
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
- Cell Biology Program and Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center (MSKCC)New YorkUnited States
| | - Krister Wennerberg
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
| | - Kyoung-Jae Won
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of CopenhagenCopenhagenDenmark
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26
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Lozano AX, Chaudhuri AA, Nene A, Bacchiocchi A, Earland N, Vesely MD, Usmani A, Turner BE, Steen CB, Luca BA, Badri T, Gulati GS, Vahid MR, Khameneh F, Harris PK, Chen DY, Dhodapkar K, Sznol M, Halaban R, Newman AM. T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma. Nat Med 2022; 28:353-362. [PMID: 35027754 DOI: 10.1038/s41591-021-01623-z] [Citation(s) in RCA: 158] [Impact Index Per Article: 52.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 11/09/2021] [Indexed: 12/15/2022]
Abstract
Severe immune-related adverse events (irAEs) occur in up to 60% of patients with melanoma treated with immune checkpoint inhibitors (ICIs). However, it is unknown whether a common baseline immunological state precedes irAE development. Here we applied mass cytometry by time of flight, single-cell RNA sequencing, single-cell V(D)J sequencing, bulk RNA sequencing and bulk T cell receptor (TCR) sequencing to study peripheral blood samples from patients with melanoma treated with anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination ICIs. By analyzing 93 pre- and early on-ICI blood samples and 3 patient cohorts (n = 27, 26 and 18), we found that 2 pretreatment factors in circulation-activated CD4 memory T cell abundance and TCR diversity-are associated with severe irAE development regardless of organ system involvement. We also explored on-treatment changes in TCR clonality among patients receiving combination therapy and linked our findings to the severity and timing of irAE onset. These results demonstrate circulating T cell characteristics associated with ICI-induced toxicity, with implications for improved diagnostics and clinical management.
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Affiliation(s)
- Alexander X Lozano
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA.,Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Aadel A Chaudhuri
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Computer Science & Engineering, Washington University, St. Louis, MO, USA. .,Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA.
| | - Aishwarya Nene
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | | | - Noah Earland
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Matthew D Vesely
- Department of Dermatology, Yale University School of Medicine, New Haven, CT, USA
| | - Abul Usmani
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brandon E Turner
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Chloé B Steen
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.,Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Bogdan A Luca
- Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA
| | - Ti Badri
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Gunsagar S Gulati
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Milad R Vahid
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Farnaz Khameneh
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Peter K Harris
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - David Y Chen
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA.,Division of Dermatology, Washington University School of Medicine, St. Louis, MO, USA
| | - Kavita Dhodapkar
- Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, USA
| | - Mario Sznol
- Department of Medicine, Division of Medical Oncology, Yale University School of Medicine, New Haven, CT, USA.,Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
| | - Ruth Halaban
- Department of Dermatology, Yale University School of Medicine, New Haven, CT, USA.,Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aaron M Newman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA. .,Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
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27
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Spurgeon BEJ, Frelinger AL. Comprehensive phenotyping of human platelets by single-cell cytometry. Cytometry A 2022; 101:290-297. [PMID: 34997669 DOI: 10.1002/cyto.a.24531] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 12/22/2021] [Accepted: 12/23/2021] [Indexed: 11/07/2022]
Abstract
Platelets are small anucleate blood cells that contribute to hemostasis, immunity, and inflammation. Circulating platelets are heterogeneous in size, age, receptor expression, and reactivity. They inherit many features from megakaryocytes and are further modified on exposure to bioactive substances in the bloodstream. Among these substances, prothrombotic agonists, vasodilators, and bloodborne pathogens modulate platelet phenotypes via distinct signaling cascades. The ability of platelets to respond to (patho)physiologic signals is incompletely understood but likely depends on their repertoire of surface receptors, which may partition them into discrete subsets with specialized functions and divergent abilities. The single-cell resolution of flow and mass cytometry is ideal for immunophenotyping and allows the identification of platelet subsets in remarkable detail. In this report, we describe the surface markers and gating strategies needed for the comprehensive characterization of platelets.
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Affiliation(s)
- Benjamin E J Spurgeon
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew L Frelinger
- Center for Platelet Research Studies, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts, USA
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28
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Drápela S, Fedr R, Vacek O, Remšík J, Souček K. High-Throughput, Parallel Flow Cytometry Screening of Hundreds of Cell Surface Antigens Using Fluorescent Barcoding. Methods Mol Biol 2022; 2543:99-111. [PMID: 36087262 DOI: 10.1007/978-1-0716-2553-8_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Multicolor flow cytometry allows for analysis of tens of cellular parameters in millions of cells at a single-cell resolution within minutes. The lack of technologies that would facilitate feasible and relatively cheap profiling of such a number of cells with an antibody-based approach led us to the development of a high-throughput cytometry-based platform for surface profiling. We coupled the fluorescent cell barcoding with preexisting, commercially available screening tools to analyze cell surface fingerprint at a large scale. This powerful approach will help to identify novel biomarkers and druggable targets and facilitate the discovery of new concepts in immunology, oncology, and developmental biology.
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Affiliation(s)
- Stanislav Drápela
- Department of Cytokinetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital in Brno, Brno, Czech Republic
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Radek Fedr
- Department of Cytokinetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital in Brno, Brno, Czech Republic
| | - Ondřej Vacek
- Department of Cytokinetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital in Brno, Brno, Czech Republic
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Ján Remšík
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Karel Souček
- Department of Cytokinetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic.
- International Clinical Research Center, St. Anne's University Hospital in Brno, Brno, Czech Republic.
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic.
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29
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Fernandez MA, Alzayat H, Jaimes MC, Kharraz Y, Requena G, Mendez P. High-Dimensional Immunophenotyping with 37-Color Panel Using Full-Spectrum Cytometry. Methods Mol Biol 2022; 2386:43-60. [PMID: 34766264 DOI: 10.1007/978-1-0716-1771-7_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
A comprehensive study of the cellular components of the immune system demands both deep and broad immunophenotyping of numerous cell subsets in an effective and practical way. Novel full-spectrum technology reveals the complete emission spectrum of each dye maximizing the amount of information that can be obtained on a single sample regarding conventional flow cytometry and provide an expanded knowledge of biological processes. In this chapter, we describe a 37-color protocol that allows to identify more than 45 different cell populations on whole blood samples of SARS-CoV-2-infected patients.
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Affiliation(s)
- Marco A Fernandez
- Flow Cytometry Facility, Germans Trias i Pujol Research Institute, Badalona, Spain
| | - Hammad Alzayat
- Flow Cytometry Facility, Germans Trias i Pujol Research Institute, Badalona, Spain
| | | | | | - Gerard Requena
- Flow Cytometry Facility, Germans Trias i Pujol Research Institute, Badalona, Spain
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30
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Abstract
Inflammation is intimately involved at all stages of atherosclerosis and remains a substantial residual cardiovascular risk factor in optimally treated patients. The proof of concept that targeting inflammation reduces cardiovascular events in patients with a history of myocardial infarction has highlighted the urgent need to identify new immunotherapies to treat patients with atherosclerotic cardiovascular disease. Importantly, emerging data from new clinical trials show that successful immunotherapies for atherosclerosis need to be tailored to the specific immune alterations in distinct groups of patients. In this Review, we discuss how single-cell technologies - such as single-cell mass cytometry, single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing - are ideal for mapping the cellular and molecular composition of human atherosclerotic plaques and how these data can aid in the discovery of new precise immunotherapies. We also argue that single-cell data from studies in humans need to be rigorously validated in relevant experimental models, including rapidly emerging single-cell CRISPR screening technologies and mouse models of atherosclerosis. Finally, we discuss the importance of implementing single-cell immune monitoring tools in early phases of drug development to aid in the precise selection of the target patient population for data-driven translation into randomized clinical trials and the successful translation of new immunotherapies into the clinic.
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Affiliation(s)
- Dawn M Fernandez
- Department of Medicine, Division of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chiara Giannarelli
- Department of Medicine, Division of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- New York University Cardiovascular Research Center, New York University Langone Health, New York, NY, USA.
- Department of Pathology, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA.
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31
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Graham A, Korecky J, Schultz E, Gregory M, Asosingh K. Considerations for user consultation in a flow cytometry shared resource laboratory. Cytometry A 2021; 101:228-236. [PMID: 34787950 DOI: 10.1002/cyto.a.24519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 11/12/2021] [Accepted: 11/15/2021] [Indexed: 11/06/2022]
Abstract
User consultation is an essential first step in assuring high-quality flow cytometric data. A central challenge to shared resource laboratory (SRL) staff is how to best guide new and current users to meet each projects' needs. One solution to this challenge is to follow a standard user consultation platform addressing all critical steps between the conception of the experiment and the actual acquisition of samples. Here we describe considerations to help an SRL understand the researcher's goals and how best the SRL staff can provide expert advice in a structured manner. User consultation has an educational nature, informing users about current best practices in cytometry that apply to their specific utilization. A consultation report also improves communication between the SRL, principal investigator, and lab members of the collaborating researcher. Development of best SRL practices is spearheaded by the ISAC SRL committee and this communication sets the foundation to initiate such report for user consultation. Implementation of best practices during user consultation will improve rigor and reproducibility in cytometry.
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Affiliation(s)
- Amy Graham
- Flow Cytometry Core Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jena Korecky
- Flow Cytometry Core Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Eric Schultz
- Flow Cytometry Core Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Michael Gregory
- Florida Research and Innovation Center, Cleveland Clinic, Port St Lucie, Florida, USA
| | - Kewal Asosingh
- Flow Cytometry Core Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.,Department of Inflammation and Immunity, Cleveland Clinic, Cleveland, Ohio, USA
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32
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Jašarević E, Hill EM, Kane PJ, Rutt L, Gyles T, Folts L, Rock KD, Howard CD, Morrison KE, Ravel J, Bale TL. The composition of human vaginal microbiota transferred at birth affects offspring health in a mouse model. Nat Commun 2021; 12:6289. [PMID: 34725359 PMCID: PMC8560944 DOI: 10.1038/s41467-021-26634-9] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 10/12/2021] [Indexed: 12/12/2022] Open
Abstract
Newborns are colonized by maternal microbiota that is essential for offspring health and development. The composition of these pioneer communities exhibits individual differences, but the importance of this early-life heterogeneity to health outcomes is not understood. Here we validate a human microbiota-associated model in which fetal mice are cesarean delivered and gavaged with defined human vaginal microbial communities. This model replicates the inoculation that occurs during vaginal birth and reveals lasting effects on offspring metabolism, immunity, and the brain in a community-specific manner. This microbial effect is amplified by prior gestation in a maternal obesogenic or vaginal dysbiotic environment where placental and fetal ileum development are altered, and an augmented immune response increases rates of offspring mortality. Collectively, we describe a translationally relevant model to examine the defined role of specific human microbial communities on offspring health outcomes, and demonstrate that the prenatal environment dramatically shapes the postnatal response to inoculation.
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Affiliation(s)
- Eldin Jašarević
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
- Department of Obstetrics, Gynecology and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Elizabeth M Hill
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Patrick J Kane
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Lindsay Rutt
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Trevonn Gyles
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Lillian Folts
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Kylie D Rock
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Christopher D Howard
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Kathleen E Morrison
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Jacques Ravel
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Tracy L Bale
- Center for Epigenetic Research in Child Health and Brain Development, University of Maryland, School of Medicine, Baltimore, MD, 21201, USA.
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
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33
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Becht E, Tolstrup D, Dutertre CA, Morawski PA, Campbell DJ, Ginhoux F, Newell EW, Gottardo R, Headley MB. High-throughput single-cell quantification of hundreds of proteins using conventional flow cytometry and machine learning. SCIENCE ADVANCES 2021; 7:eabg0505. [PMID: 34550730 PMCID: PMC8457665 DOI: 10.1126/sciadv.abg0505] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 07/14/2021] [Indexed: 06/03/2023]
Abstract
Modern immunologic research increasingly requires high-dimensional analyses to understand the complex milieu of cell types that comprise the tissue microenvironments of disease. To achieve this, we developed Infinity Flow combining hundreds of overlapping flow cytometry panels using machine learning to enable the simultaneous analysis of the coexpression patterns of hundreds of surface-expressed proteins across millions of individual cells. In this study, we demonstrate that this approach allows the comprehensive analysis of the cellular constituency of the steady-state murine lung and the identification of previously unknown cellular heterogeneity in the lungs of melanoma metastasis–bearing mice. We show that by using supervised machine learning, Infinity Flow enhances the accuracy and depth of clustering or dimensionality reduction algorithms. Infinity Flow is a highly scalable, low-cost, and accessible solution to single-cell proteomics in complex tissues.
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Affiliation(s)
- Etienne Becht
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Daniel Tolstrup
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Charles-Antoine Dutertre
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore
- Program in Emerging Infectious Disease, Duke-NUS Medical School, Singapore, Singapore
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Center, Singapore 169856, Singapore
| | - Peter A. Morawski
- Center for Fundamental Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Daniel J. Campbell
- Center for Fundamental Immunology, Benaroya Research Institute, Seattle, WA, USA
- Department of Immunology, University of Washington School of Medicine, Seattle, WA, USA
| | - Florent Ginhoux
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Center, Singapore 169856, Singapore
- Shanghai Institute of Immunology, Shanghai JiaoTong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China
| | - Evan W. Newell
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Raphael Gottardo
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mark B. Headley
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Immunology, University of Washington School of Medicine, Seattle, WA, USA
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34
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Sahaf B, Pichavant M, Lee BH, Duault C, Thrash EM, Davila M, Fernandez N, Millerchip K, Bentebibel SE, Haymaker C, Sigal N, Del Valle DM, Ranasinghe S, Fayle S, Sanchez-Espiridion B, Zhang J, Bernatchez C, Wu CJ, Wistuba II, Kim-Schulze S, Gnjatic S, Bendall SC, Song M, Thurin M, Lee JJ, Maecker HT, Rahman A. Immune Profiling Mass Cytometry Assay Harmonization: Multicenter Experience from CIMAC-CIDC. Clin Cancer Res 2021; 27:5062-5071. [PMID: 34266889 PMCID: PMC8448982 DOI: 10.1158/1078-0432.ccr-21-2052] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/10/2021] [Accepted: 07/12/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE The Cancer Immune Monitoring and Analysis Centers - Cancer Immunologic Data Commons (CIMAC-CIDC) Network is supported by the NCI to identify biomarkers of response to cancer immunotherapies across clinical trials using state-of-the-art assays. A primary platform for CIMAC-CIDC studies is cytometry by time of flight (CyTOF), performed at all CIMAC laboratories. To ensure the ability to generate comparable CyTOF data across labs, a multistep cross-site harmonization effort was undertaken. EXPERIMENTAL DESIGN We first harmonized standard operating procedures (SOPs) across the CIMAC sites. Because of a new acquisition protocol comparing original narrow- or new wide-bore injector introduced by the vendor (Fluidigm), we also tested this protocol across sites before finalizing the harmonized SOP. We then performed cross-site assay harmonization experiments using five shared cryopreserved and one lyophilized internal control peripheral blood mononuclear cell (PBMC) with a shared lyophilized antibody cocktail consisting of 14 isotype-tagged antibodies previously validated, plus additional liquid antibodies. These reagents and samples were distributed to the CIMAC sites and the data were centrally analyzed by manual gating and automated methods (Astrolabe). RESULTS Average coefficients of variation (CV) across sites for each cell population were reported and compared with a previous multisite CyTOF study. We reached an intersite CV of under 20% for most cell subsets, very similar to a previously published study. CONCLUSIONS These results establish the ability to reproduce CyTOF data across sites in multicenter clinical trials, and also highlight the importance of quality control procedures, such as the use of spike-in control samples, for tracking variability in this assay.
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Affiliation(s)
- Bita Sahaf
- Stanford Cancer Institute, Stanford Medicine, Stanford University, California.
| | - Mina Pichavant
- Stanford Institute for Immunity, Transplantation and Infection, Stanford Medicine, Stanford university, California
| | - Brian H Lee
- Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Caroline Duault
- Stanford Institute for Immunity, Transplantation and Infection, Stanford Medicine, Stanford university, California
| | - Emily M Thrash
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Melanie Davila
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Nicolas Fernandez
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Karen Millerchip
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Salah-Eddine Bentebibel
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Cara Haymaker
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Natalia Sigal
- Stanford Institute for Immunity, Transplantation and Infection, Stanford Medicine, Stanford university, California
| | - Diane M Del Valle
- Human Immune Monitoring Center, Tisch Cancer Institute and the Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Srinika Ranasinghe
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sarah Fayle
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Beatriz Sanchez-Espiridion
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jiexin Zhang
- Department of Bioinformatics & Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chantale Bernatchez
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Harvard University, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Seunghee Kim-Schulze
- Human Immune Monitoring Center, Tisch Cancer Institute and the Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Sacha Gnjatic
- Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Sean C Bendall
- Department of Pathology, Stanford Medicine, Stanford University, Stanford, California
| | - Minkyung Song
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Magdalena Thurin
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - J Jack Lee
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Holden T Maecker
- Stanford Institute for Immunity, Transplantation and Infection, Stanford Medicine, Stanford university, California
| | - Adeeb Rahman
- Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
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35
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Chen HX, Song M, Maecker HT, Gnjatic S, Patton D, Lee JJ, Adam SJ, Moravec R, Liu XS, Cerami E, Lindsay J, Tang M, Hodi FS, Wu CJ, Wistuba II, Al-Atrash G, Bernatchez C, Bendall SC, Hewitt SM, Sharon E, Streicher H, Enos RA, Bowman MD, Tatard-Leitman VM, Sanchez-Espiridion B, Ranasinghe S, Pichavant M, Del Valle DM, Yu J, Janssens S, Peterson-Klaus J, Rowe C, Bongers G, Jenq RR, Chang CC, Abrams JS, Mooney M, Doroshow JH, Harris LN, Thurin M. Network for Biomarker Immunoprofiling for Cancer Immunotherapy: Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC). Clin Cancer Res 2021; 27:5038-5048. [PMID: 33419780 PMCID: PMC8491462 DOI: 10.1158/1078-0432.ccr-20-3241] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 11/09/2020] [Accepted: 12/23/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE Immunoprofiling to identify biomarkers and integration with clinical trial outcomes are critical to improving immunotherapy approaches for patients with cancer. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assay performance further limits comparison and interpretation of data across studies and laboratories. EXPERIMENTAL DESIGN To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute (NCI) and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the NIH. RESULTS The CIMAC-CIDC Network is composed of four academic centers with multidisciplinary expertise in cancer immunotherapy that perform validated and harmonized assays for immunoprofiling and conduct correlative analyses. A data coordinating center (CIDC) provides the computational expertise and informatics platforms for the storage, integration, and analysis of biomarker and clinical data. CONCLUSIONS This overview highlights strategies for assay harmonization to enable cross-trial and cross-site data analysis and describes key elements for establishing a network to enhance immuno-oncology biomarker development. These include an operational infrastructure, validation and harmonization of core immunoprofiling assays, platforms for data ingestion and integration, and access to specimens from clinical trials. Published in the same volume are reports of harmonization for core analyses: whole-exome sequencing, RNA sequencing, cytometry by time of flight, and IHC/immunofluorescence.
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Affiliation(s)
- Helen X Chen
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland.
| | - Minkyung Song
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland
| | - Holden T Maecker
- The Human Immune Monitoring Center (HIMC), Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, California
| | - Sacha Gnjatic
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - David Patton
- Center for Biomedical Informatics and Information Technology, NCI, Bethesda, Maryland
| | - J Jack Lee
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stacey J Adam
- Foundation for the National Institutes of Health, North Bethesda, Maryland
| | - Radim Moravec
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
- Kelly Services, Rockville, Maryland
| | - Xiaole Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ethan Cerami
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - James Lindsay
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ming Tang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - F Stephen Hodi
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gheath Al-Atrash
- Department of Stem Cell Transplantation and Cellular Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chantale Bernatchez
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sean C Bendall
- Department of Pathology, School of Medicine, Stanford University, Stanford, California
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, NCI, Bethesda, Maryland
| | - Elad Sharon
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland
| | - Howard Streicher
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland
| | | | | | | | - Beatriz Sanchez-Espiridion
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Srinika Ranasinghe
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mina Pichavant
- The Human Immune Monitoring Center (HIMC), Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, California
| | - Diane M Del Valle
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joyce Yu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | | | - Cathy Rowe
- Center for Biomedical Informatics and Information Technology, NCI, Bethesda, Maryland
- Essex Management, Rockville, Maryland
| | - Gerold Bongers
- Microbiome Translational Center, Precision Immunology Institute, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Robert R Jenq
- Department of Stem Cell Transplantation and Cellular Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chia-Chi Chang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jeffrey S Abrams
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland
| | - Margaret Mooney
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland
| | - James H Doroshow
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Magdalena Thurin
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland.
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36
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Quintelier K, Couckuyt A, Emmaneel A, Aerts J, Saeys Y, Van Gassen S. Analyzing high-dimensional cytometry data using FlowSOM. Nat Protoc 2021; 16:3775-3801. [PMID: 34172973 DOI: 10.1038/s41596-021-00550-0] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 03/31/2021] [Indexed: 02/06/2023]
Abstract
The dimensionality of cytometry data has strongly increased in the last decade, and in many situations the traditional manual downstream analysis becomes insufficient. The field is therefore slowly moving toward more automated approaches, and in this paper we describe the protocol for analyzing high-dimensional cytometry data using FlowSOM, a clustering and visualization algorithm based on a self-organizing map. FlowSOM is used to distinguish cell populations from cytometry data in an unsupervised way and can help to gain deeper insights in fields such as immunology and oncology. Since the original FlowSOM publication (2015), we have validated the tool on a wide variety of datasets, and to write this protocol, we made use of this experience to improve the user-friendliness of the package (e.g., comprehensive functions replacing commonly required scripts). Where the original paper focused mainly on the algorithm description, this protocol offers user guidelines on how to implement the procedure, detailed parameter descriptions and troubleshooting recommendations. The protocol provides clearly annotated R code, and is therefore relevant for all scientists interested in computational high-dimensional analyses without requiring a strong bioinformatics background. We demonstrate the complete workflow, starting from data preparation (such as compensation, transformation and quality control), including detailed discussion of the different FlowSOM parameters and visualization options, and concluding with how the results can be further used to answer biological questions, such as statistical comparison between groups of interest. An average FlowSOM analysis takes 1-3 h to complete, though quality issues can increase this time considerably.
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Affiliation(s)
- Katrien Quintelier
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium.,Department of Pulmonary Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Artuur Couckuyt
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium
| | - Annelies Emmaneel
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium
| | - Joachim Aerts
- Department of Pulmonary Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Yvan Saeys
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium
| | - Sofie Van Gassen
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium. .,Data Mining and Modeling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium.
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37
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Pritchett JC, Yang ZZ, Kim HJ, Villasboas JC, Tang X, Jalali S, Cerhan JR, Feldman AL, Ansell SM. High-dimensional and single-cell transcriptome analysis of the tumor microenvironment in angioimmunoblastic T cell lymphoma (AITL). Leukemia 2021; 36:165-176. [PMID: 34230608 DOI: 10.1038/s41375-021-01321-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/20/2021] [Accepted: 06/05/2021] [Indexed: 02/08/2023]
Abstract
Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive lymphoid malignancy associated with a poor clinical prognosis. The AITL tumor microenvironment (TME) is unique, featuring a minority population of malignant CD4+ T follicular helper (TFH) cells inter-mixed with a diverse infiltrate of multi-lineage immune cells. While much of the understanding of AITL biology to date has focused on characteristics of the malignant clone, less is known about the many non-malignant populations that comprise the TME. Recently, mutational consistencies have been identified between malignant cells and non-malignant B cells within the AITL TME. As a result, a significant role for non-malignant populations in AITL biology has been increasingly hypothesized. In this study, we have utilized mass cytometry and single-cell transcriptome analysis to identify several expanded populations within the AITL TME. Notably, we find that B cells within the AITL TME feature decreased expression of key markers including CD73 and CXCR5. Furthermore, we describe the expansion of distinct CD8+ T cell populations that feature an exhausted phenotype and an underlying expression profile indicative of dysfunction, impaired cytotoxicity, and upregulation of the chemokines XCL2 and XCL1.
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Affiliation(s)
| | - Zhi-Zhang Yang
- Department of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Hyo Jin Kim
- Department of Hematology, Mayo Clinic, Rochester, MN, USA
| | | | - Xinyi Tang
- Department of Hematology, Mayo Clinic, Rochester, MN, USA
| | | | - James R Cerhan
- Department of Health Sciences Research and Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Andrew L Feldman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
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38
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Bartemes KR, Choby G, O’Brien EK, Stokken JK, Pavelko KD, Kita H. Mass cytometry reveals unique subsets of T cells and lymphoid cells in nasal polyps from patients with chronic rhinosinusitis (CRS). Allergy 2021; 76:2222-2226. [PMID: 33370459 DOI: 10.1111/all.14720] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 12/11/2020] [Accepted: 12/20/2020] [Indexed: 01/09/2023]
Affiliation(s)
- Kathleen R. Bartemes
- Division of Allergic Diseases and Department of Medicine Mayo Clinic Rochester MN USA
- Department of Otolaryngology Mayo Clinic Rochester MN USA
| | - Garret Choby
- Department of Otolaryngology Mayo Clinic Rochester MN USA
| | | | | | | | - Hirohito Kita
- Division of Allergic Diseases and Department of Medicine Mayo Clinic Rochester MN USA
- Department of Immunology Mayo Clinic Rochester MN USA
- Division of Allergy, Asthma, and Immunology and Department of Medicine Mayo Clinic Scottsdale AZ USA
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39
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Westfall S, Caracci F, Estill M, Frolinger T, Shen L, Pasinetti GM. Chronic Stress-Induced Depression and Anxiety Priming Modulated by Gut-Brain-Axis Immunity. Front Immunol 2021; 12:670500. [PMID: 34248950 PMCID: PMC8264434 DOI: 10.3389/fimmu.2021.670500] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 06/08/2021] [Indexed: 12/18/2022] Open
Abstract
Chronic stress manifests as depressive- and anxiety-like behavior while recurrent stress elicits disproportionate behavioral impairments linked to stress-induced immunological priming. The gut-brain-microbiota-axis is a promising therapeutic target for stress-induced behavioral impairments as it simultaneously modulates peripheral and brain immunological landscapes. In this study, a combination of probiotics and prebiotics, known as a synbiotic, promoted behavioral resilience to chronic and recurrent stress by normalizing gut microbiota populations and promoting regulatory T cell (Treg) expansion through modulation of ileal innate lymphoid cell (ILC)3 activity, an impact reflecting behavioral responses better than limbic brain region neuroinflammation. Supporting this conclusion, a multivariate machine learning model correlatively predicted a cross-tissue immunological signature of stress-induced behavioral impairment where the ileal Treg/T helper17 cell ratio associated to hippocampal chemotactic chemokine and prefrontal cortex IL-1β production in the context of stress-induced behavioral deficits. In conclusion, stress-induced behavioral impairments depend on the gut-brain-microbiota-axis and through ileal immune regulation, synbiotics attenuate the associated depressive- and anxiety-like behavior.
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Affiliation(s)
- Susan Westfall
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Francesca Caracci
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Molly Estill
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Tal Frolinger
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Li Shen
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Giulio M. Pasinetti
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Geriatric Research, Education and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, United States
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40
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Microenvironment immune reconstitution patterns correlate with outcomes after autologous transplant in multiple myeloma. Blood Adv 2021; 5:1797-1804. [PMID: 33787859 DOI: 10.1182/bloodadvances.2020003857] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 02/12/2021] [Indexed: 01/01/2023] Open
Abstract
The immediate postautologous stem cell transplant (ASCT) period in multiple myeloma represents a unique opportunity for long-term disease control because many patients have eradicated most of their disease but also a challenge because it is characterized by the increase of immune subsets detrimental to tumor immunosurveillance. The impact of the tumor immune microenvironment (iTME) in post-ASCT outcomes is not known. In this study, we included 58 patients undergoing upfront ASCT and evaluated their cellular and humoral iTME with cytometry by time of flight (CyTOF) and luminex, respectively, at day +60 to 100 post-ASCT. We identified 2 cellular iTME patterns. Group 1 was enriched in T-cell subsets at the opposite ends of the spectrum of T-cell differentiation compared with the rest of the patients, that is, cells already terminally differentiated (immune senescent or exhausted) and naive T cells. This group had worse hematologic responses post-ASCT, inferior survival, and shorter time to hematologic progression independent of established risk factors. No differences in the humoral iTME were noted between the 2 groups. In addition, no differences in the cellular/humoral iTME were noted according to high-risk fluorescence in situ hybridization status, early or late relapse. Finally, males had higher levels of natural killer cells negative for CD16, a key receptor mediating antibody-dependent cell cytotoxicity, a major mechanism of antitumor efficacy by therapeutic antibodies such as elotuzumab. Our findings suggest that T-cell iTME dysfunction post-ASCT, some of which could be reversible (exhaustion), correlates with worse outcomes. These results could be used to guide rational selection of post-ASCT maintenance/consolidation approaches in these patients.
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41
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Rybakowska P, Van Gassen S, Quintelier K, Saeys Y, Alarcón-Riquelme ME, Marañón C. Data processing workflow for large-scale immune monitoring studies by mass cytometry. Comput Struct Biotechnol J 2021; 19:3160-3175. [PMID: 34141137 PMCID: PMC8188119 DOI: 10.1016/j.csbj.2021.05.032] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 05/14/2021] [Accepted: 05/20/2021] [Indexed: 12/27/2022] Open
Abstract
Mass cytometry is a powerful tool for deep immune monitoring studies. To ensure maximal data quality, a careful experimental and analytical design is required. However even in well-controlled experiments variability caused by either operator or instrument can introduce artifacts that need to be corrected or removed from the data. Here we present a data processing pipeline which ensures the minimization of experimental artifacts and batch effects, while improving data quality. Data preprocessing and quality controls are carried out using an R pipeline and packages like CATALYST for bead-normalization and debarcoding, flowAI and flowCut for signal anomaly cleaning, AOF for files quality control, flowClean and flowDensity for gating, CytoNorm for batch normalization and FlowSOM and UMAP for data exploration. As proper experimental design is key in obtaining good quality events, we also include the sample processing protocol used to generate the data. Both, analysis and experimental pipelines are easy to scale-up, thus the workflow presented here is particularly suitable for large-scale, multicenter, multibatch and retrospective studies.
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Affiliation(s)
- Paulina Rybakowska
- GENYO, Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Spain
| | - Sofie Van Gassen
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, Gent Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Gent, Belgium
| | - Katrien Quintelier
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, Gent Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Gent, Belgium
- Department of Pulmonary Diseases, Erasmus MC, Rotterdam, the Netherlands
| | - Yvan Saeys
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, Gent Belgium
- Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Gent, Belgium
| | - Marta E. Alarcón-Riquelme
- GENYO, Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Spain
- Institute for Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Concepción Marañón
- GENYO, Centre for Genomics and Oncological Research, Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Spain
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42
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Geanon D, Lee B, Gonzalez‐Kozlova E, Kelly G, Handler D, Upadhyaya B, Leech J, De Real RM, Herbinet M, Magen A, Del Valle D, Charney A, Kim‐Schulze S, Gnjatic S, Merad M, Rahman AH. A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID-19. Cytometry A 2021; 99:446-461. [PMID: 33496367 PMCID: PMC8013522 DOI: 10.1002/cyto.a.24317] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/10/2020] [Accepted: 01/06/2021] [Indexed: 01/21/2023]
Abstract
Mass cytometry (CyTOF) represents one of the most powerful tools in immune phenotyping, allowing high throughput quantification of over 40 parameters at single-cell resolution. However, wide deployment of CyTOF-based immune phenotyping studies are limited by complex experimental workflows and the need for specialized CyTOF equipment and technical expertise. Furthermore, differences in cell isolation and enrichment protocols, antibody reagent preparation, sample staining, and data acquisition protocols can all introduce technical variation that can confound integrative analyses of large data-sets of samples processed across multiple labs. Here, we present a streamlined whole blood CyTOF workflow which addresses many of these sources of experimental variation and facilitates wider adoption of CyTOF immune monitoring across sites with limited technical expertise or sample-processing resources or equipment. Our workflow utilizes commercially available reagents including the Fluidigm MaxPar Direct Immune Profiling Assay (MDIPA), a dry tube 30-marker immunophenotyping panel, and SmartTube Proteomic Stabilizer, which allows for simple and reliable fixation and cryopreservation of whole blood samples. We validate a workflow that allows for streamlined staining of whole blood samples with minimal processing requirements or expertise at the site of sample collection, followed by shipment to a central CyTOF core facility for batched downstream processing and data acquisition. We apply this workflow to characterize 184 whole blood samples collected longitudinally from a cohort of 72 hospitalized COVID-19 patients and healthy controls, highlighting dynamic disease-associated changes in circulating immune cell frequency and phenotype.
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Affiliation(s)
- Daniel Geanon
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Brian Lee
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Edgar Gonzalez‐Kozlova
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Geoffrey Kelly
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Diana Handler
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Bhaskar Upadhyaya
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - John Leech
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ronaldo M. De Real
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Manon Herbinet
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Assaf Magen
- Department of Oncological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Diane Del Valle
- Department of Oncological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Alexander Charney
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Seunghee Kim‐Schulze
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Sacha Gnjatic
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Oncological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Miriam Merad
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Oncological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Adeeb H. Rahman
- Human Immune Monitoring CenterIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
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43
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Relapsed multiple myeloma demonstrates distinct patterns of immune microenvironment and malignant cell-mediated immunosuppression. Blood Cancer J 2021; 11:45. [PMID: 33649314 PMCID: PMC7921408 DOI: 10.1038/s41408-021-00440-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 02/07/2021] [Accepted: 02/10/2021] [Indexed: 02/06/2023] Open
Abstract
Immunotherapy has shown efficacy in relapsed multiple myeloma (MM). However, these therapies may depend on a functional tumor immune microenvironment (iTME) for their efficacy. Characterizing the evolution of the iTME over the disease course is necessary to optimize the timing of immunotherapies. We performed mass cytometry, cytokine analysis, and RNA sequencing on bone marrow samples from 39 (13 newly diagnosed [NDMM], 11 relapsed pre-daratumumab exposure [RMM], and 13 triple-refractory [TRMM]) MM patients. Three distinct cellular iTME clusters were identified; cluster 1 comprised mainly of NDMM and RMM patients; and clusters 2 and 3 comprised primarily of TRMM patients. We showed that naive T cells were decreased in clusters 2 and 3, cluster 2 was characterized by increased senescent T cells, and cluster 3 by decreased early memory T cells. Plasma cells in clusters 2 and 3 upregulated E2F transcription factors and MYC proliferation pathways, and downregulated interferon, TGF-beta, interleuking-6, and TNF-αlpha signaling pathways compared to cluster 1. This study suggests that the MM iTME becomes increasingly dysfunctional with therapy whereas the MM clone may be less dependent on inflammation-mediated growth pathways and less sensitive to IFN-mediated immunosurveillance. Our findings may explain the decreased sensitivity of TRMM patients to novel immunotherapies.
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44
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Spurgeon BEJ, Michelson AD, Frelinger AL. Platelet mass cytometry: Optimization of sample, reagent, and analysis parameters. Cytometry A 2021; 99:170-179. [DOI: 10.1002/cyto.a.24300] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/27/2020] [Accepted: 12/23/2020] [Indexed: 12/28/2022]
Affiliation(s)
- Benjamin E. J. Spurgeon
- Center for Platelet Research Studies, Dana‐Farber/Boston Children's Cancer and Blood Disorders Center Harvard Medical School Boston Massachusetts USA
| | - Alan D. Michelson
- Center for Platelet Research Studies, Dana‐Farber/Boston Children's Cancer and Blood Disorders Center Harvard Medical School Boston Massachusetts USA
| | - Andrew L. Frelinger
- Center for Platelet Research Studies, Dana‐Farber/Boston Children's Cancer and Blood Disorders Center Harvard Medical School Boston Massachusetts USA
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45
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Jensen HA, Wnek R. Analytical performance of a
25‐marker
spectral cytometry immune monitoring assay in peripheral blood. Cytometry A 2020. [DOI: 10.1002/cyto.a.24290] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Holly A. Jensen
- Translational Molecular Biomarkers Merck & Co., Inc Kenilworth New Jersey USA
| | - Richard Wnek
- Translational Molecular Biomarkers Merck & Co., Inc Kenilworth New Jersey USA
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46
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Ng TL, Johnson A, Nemenoff RA, Hsieh E, Osypuk AA, van Bokhoven A, Li H, Camidge DR, Schenk EL. Prospective Observational Study Revealing Early Pulmonary Function Changes Associated With Brigatinib Initiation. J Thorac Oncol 2020; 16:486-491. [PMID: 33307191 DOI: 10.1016/j.jtho.2020.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/10/2020] [Accepted: 11/15/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Symptomatic early onset pulmonary events (EOPEs) were observed in 3% to 6% of patients within 1 week of starting brigatinib at 90 mg daily for 7 days followed by 180 mg daily. We conducted a prospective observational cohort study to measure pulmonary function changes on initiating brigatinib. METHODS Patients initiating brigatinib were eligible. Pulmonary function test (PFT) with diffusing capacity for carbon monoxide (DLCO), Borg dyspnea scale, six-minute walk test, and blood draw for cytometry by time-of-flight were performed at baseline, day 2, and day 8 plus or minus day 15 of brigatinib. The primary end point was the incidence of PFT-defined EOPEs, prespecified as greater than or equal to 20% DLCO reduction from baseline. An interim analysis was performed owing to a higher than expected incidence of DLCO reduction. RESULTS A total of 90% (nine of 10) experienced DLCO reduction with the nadir occurring on day 2 or day 8. Median DLCO nadir was -13.33% from baseline (range: -34.44 to -5.00). Three participants met the PFT-defined EOPE criteria. All patients, including these three, were asymptomatic, none required brigatinib interruption or dose reduction, and all patients escalated to 180 mg without further issues. Despite continued dosing, by day 15, all assessed patients experienced DLCO recovery. Dyspnea and six-minute walk test results did not correlate with DLCO changes. Patients with a PFT-defined EOPE had significantly higher levels of activated neutrophils at baseline and day 8. CONCLUSIONS DLCO reduction occurred in 90% during the first 8 days of brigatinib dosing without any related symptoms. DLCO improved in all six patients assessed at day 15 despite continued dosing and dose escalation. Pretreatment levels of neutrophil activation should be explored as a biomarker for developing EOPEs.
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Affiliation(s)
- Terry L Ng
- Division of Medical Oncology, University of Ottawa, Ottawa, Ontario, Canada; Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
| | - Amber Johnson
- Division of Renal Diseases and Hypertension, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Raphael A Nemenoff
- Division of Renal Diseases and Hypertension, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Elena Hsieh
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado; Division of Allergy and Immunology, Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Andrea Abeyta Osypuk
- Pathology Shared Resource, Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Adrie van Bokhoven
- Pathology Shared Resource, Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Howard Li
- Department of Medicine, University of Colorado, Aurora, Colorado; Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia
| | - D Ross Camidge
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Erin L Schenk
- Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
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Rybakowska P, Burbano C, Van Gassen S, Varela N, Aguilar-Quesada R, Saeys Y, Alarcón-Riquelme ME, Marañón C. Stabilization of Human Whole Blood Samples for Multicenter and Retrospective Immunophenotyping Studies. Cytometry A 2020; 99:524-537. [PMID: 33070416 DOI: 10.1002/cyto.a.24241] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 09/14/2020] [Accepted: 10/12/2020] [Indexed: 02/06/2023]
Abstract
Whole blood is often collected for large-scale immune monitoring studies to track changes in cell frequencies and responses using flow (FC) or mass cytometry (MC). In order to preserve sample composition and phenotype, blood samples should be analyzed within 24 h after bleeding, restricting the recruitment, analysis protocols, as well as biobanking. Herein, we have evaluated two whole blood preservation protocols that allow rapid sample processing and long-term stability. Two fixation buffers were used, Phosphoflow Fix and Lyse (BD) and Proteomic Stabilizer (PROT) to fix and freeze whole blood samples for up to 6 months. After analysis by an 8-plex panel by FC and a 26-plex panel by MC, manual gating of circulating leukocyte populations and cytokines was performed. Additionally, we tested the stability of a single sample over a 13-months period using 45 consecutive aliquots and a 34-plex panel by MC. We observed high correlation and low bias toward any cell population when comparing fresh and 6 months frozen blood with FC and MC. This correlation was confirmed by hierarchical clustering. Low coefficients of variation (CV) across studied time points indicate good sample preservation for up to 6 months. Cytokine detection stability was confirmed by low CVs, with some differences between fresh and fixed conditions. Thirteen months regular follow-up of PROT samples showed remarkable sample stability. Whole blood can be preserved for phenotyping and cytokine-response studies provided the careful selection of a compatible antibody panel. However, possible changes in cell morphology, differences in antibody affinity, and changes in cytokine-positive cell frequencies when compared to fresh blood should be considered. Our setting constitutes a valuable tool for multicentric and retrospective studies. © 2020 International Society for Advancement of Cytometry.
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Affiliation(s)
- Paulina Rybakowska
- Department of Medical Genomics, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS, Granada, Spain
| | - Catalina Burbano
- Grupo de Inmunología Celular e Inmunogenética, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Sofie Van Gassen
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Nieves Varela
- Department of Medical Genomics, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS, Granada, Spain
| | | | - Yvan Saeys
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Marta E Alarcón-Riquelme
- Department of Medical Genomics, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS, Granada, Spain.,Unit for Chronic Inflammatory Diseases, Institute for Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Concepción Marañón
- Department of Medical Genomics, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS, Granada, Spain
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Crosby EJ, Hobeika AC, Niedzwiecki D, Rushing C, Hsu D, Berglund P, Smith J, Osada T, Gwin Iii WR, Hartman ZC, Morse MA, Lyerly HK. Long-term survival of patients with stage III colon cancer treated with VRP-CEA(6D), an alphavirus vector that increases the CD8+ effector memory T cell to Treg ratio. J Immunother Cancer 2020; 8:jitc-2020-001662. [PMID: 33177177 PMCID: PMC7661359 DOI: 10.1136/jitc-2020-001662] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/20/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND There remains a significant need to eliminate the risk of recurrence of resected cancers. Cancer vaccines are well tolerated and activate tumor-specific immune effectors and lead to long-term survival in some patients. We hypothesized that vaccination with alphaviral replicon particles encoding tumor associated antigens would generate clinically significant antitumor immunity to enable prolonged overall survival (OS) in patients with both metastatic and resected cancer. METHODS OS was monitored for patients with stage IV cancer treated in a phase I study of virus-like replicon particle (VRP)-carcinoembryonic antigen (CEA), an alphaviral replicon particle encoding a modified CEA. An expansion cohort of patients (n=12) with resected stage III colorectal cancer who had completed their standard postoperative adjuvant chemotherapy was administered VRP-CEA every 3 weeks for a total of 4 immunizations. OS and relapse-free survival (RFS) were determined, as well as preimmunization and postimmunization cellular and humoral immunity. RESULTS Among the patients with stage IV cancer, median follow-up was 10.9 years and 5-year survival was 17%, (95% CI 6% to 33%). Among the patients with stage III cancer, the 5-year RFS was 75%, (95%CI 40% to 91%); no deaths were observed. At a median follow-up of 5.8 years (range: 3.9-7.0 years) all patients were still alive. All patients demonstrated CEA-specific humoral immunity. Patients with stage III cancer had an increase in CD8 +TEM (in 10/12) and decrease in FOXP3 +Tregs (in 10/12) following vaccination. Further, CEA-specific, IFNγ-producing CD8+granzyme B+TCM cells were increased. CONCLUSIONS VRP-CEA induces antigen-specific effector T cells while decreasing Tregs, suggesting favorable immune modulation. Long-term survivors were identified in both cohorts, suggesting the OS may be prolonged.
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Affiliation(s)
- Erika J Crosby
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
| | - Amy C Hobeika
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
| | - Donna Niedzwiecki
- Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
- Biostatistics, Duke Cancer Institute, Durham, North Carolina, USA
| | - Christel Rushing
- Biostatistics, Duke Cancer Institute, Durham, North Carolina, USA
| | - David Hsu
- Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | | | | | - Takuya Osada
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
| | | | - Zachary C Hartman
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
- Pathology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Michael A Morse
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
- Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Herbert Kim Lyerly
- Surgery, Duke University School of Medicine, Durham, North Carolina, USA
- Pathology, Duke University School of Medicine, Durham, North Carolina, USA
- Immunology, Duke University School of Medicine, Durham, North Carolina, USA
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49
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Steele NG, Carpenter ES, Kemp SB, Sirihorachai VR, The S, Delrosario L, Lazarus J, Amir EAD, Gunchick V, Espinoza C, Bell S, Harris L, Lima F, Irizarry-Negron V, Paglia D, Macchia J, Chu AKY, Schofield H, Wamsteker EJ, Kwon R, Schulman A, Prabhu A, Law R, Sondhi A, Yu J, Patel A, Donahue K, Nathan H, Cho C, Anderson MA, Sahai V, Lyssiotis CA, Zou W, Allen BL, Rao A, Crawford HC, Bednar F, Frankel TL, Pasca di Magliano M. Multimodal Mapping of the Tumor and Peripheral Blood Immune Landscape in Human Pancreatic Cancer. NATURE CANCER 2020; 1:1097-1112. [PMID: 34296197 PMCID: PMC8294470 DOI: 10.1038/s43018-020-00121-4] [Citation(s) in RCA: 290] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 08/31/2020] [Indexed: 12/17/2022]
Abstract
Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that renders it largely refractory to immunotherapy. We implemented a multimodal analysis approach to elucidate the immune landscape in PDA. Using a combination of CyTOF, single-cell RNA sequencing, and multiplex immunohistochemistry on patient tumors, matched blood, and non-malignant samples, we uncovered a complex network of immune-suppressive cellular interactions. These experiments revealed heterogeneous expression of immune checkpoint receptors in individual patient's T cells and increased markers of CD8+ T cell dysfunction in advanced disease stage. Tumor-infiltrating CD8+ T cells had an increased proportion of cells expressing an exhausted expression profile that included upregulation of the immune checkpoint TIGIT, a finding that we validated at the protein level. Our findings point to a profound alteration of the immune landscape of tumors, and to patient-specific immune changes that should be taken into account as combination immunotherapy becomes available for pancreatic cancer.
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Affiliation(s)
- Nina G Steele
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Eileen S Carpenter
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Samantha B Kemp
- Molecular and Cellular Pathology Graduate Program, University of Michigan, Ann Arbor, MI, USA
| | | | - Stephanie The
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | | | - Jenny Lazarus
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | | | - Valerie Gunchick
- Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Carlos Espinoza
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Samantha Bell
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Lindsey Harris
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Fatima Lima
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | | | - Daniel Paglia
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Justin Macchia
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Angel Ka Yan Chu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | | | - Erik-Jan Wamsteker
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Richard Kwon
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Allison Schulman
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Anoop Prabhu
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Law
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Arjun Sondhi
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Jessica Yu
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Arpan Patel
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Katelyn Donahue
- Cancer Biology Program, University of Michigan, Ann Arbor, MI, USA
| | - Hari Nathan
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Clifford Cho
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Michelle A Anderson
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Vaibhav Sahai
- Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Costas A Lyssiotis
- Molecular and Cellular Pathology Graduate Program, University of Michigan, Ann Arbor, MI, USA
- Cancer Biology Program, University of Michigan, Ann Arbor, MI, USA
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Weiping Zou
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Benjamin L Allen
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Cancer Biology Program, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Michigan Institute of Data Science (MIDAS), University of Michigan, Ann Arbor, MI, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Howard C Crawford
- Molecular and Cellular Pathology Graduate Program, University of Michigan, Ann Arbor, MI, USA.
- Cancer Biology Program, University of Michigan, Ann Arbor, MI, USA.
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
| | - Filip Bednar
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA.
| | | | - Marina Pasca di Magliano
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA.
- Molecular and Cellular Pathology Graduate Program, University of Michigan, Ann Arbor, MI, USA.
- Cancer Biology Program, University of Michigan, Ann Arbor, MI, USA.
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA.
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50
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Effects of processing conditions on stability of immune analytes in human blood. Sci Rep 2020; 10:17328. [PMID: 33060628 PMCID: PMC7566484 DOI: 10.1038/s41598-020-74274-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/09/2020] [Indexed: 11/30/2022] Open
Abstract
Minimizing variability in collection and processing of human blood samples for research remains a challenge. Delaying plasma or serum isolation after phlebotomy (processing delay) can cause perturbations of numerous analytes. Thus, a comprehensive understanding of how processing delay affects major endpoints used in human immunology research is necessary. Therefore, we studied how processing delay affects commonly measured cytokines and immune cell populations. We hypothesized that short-term time delays inherent to human research in serum and plasma processing impact commonly studied immunological analytes. Blood from healthy donors was subjected to processing delays commonly encountered in sample collection, and then assayed by 62-plex Luminex panel, 40-parameter mass cytometry panel, and 540,000 transcript expression microarray. Variance for immunological analytes was estimated using each individual’s baseline as a control. In general, short-term processing delay led to small changes in plasma and serum cytokines (range − 10.8 to 43.5%), markers and frequencies of peripheral blood mononuclear cell phenotypes (range 0.19 to 3.54 fold), and whole blood gene expression (stable for > 20 K genes)—with several exceptions described herein. Importantly, we built an open-access web application allowing investigators to estimate the degree of variance expected from processing delay for measurements of interest based on the data reported here.
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