Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy
Summary: The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in lim...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-07-01
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| Series: | Cell Reports |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124719308228 |
| _version_ | 1818314984118026240 |
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| author | Felix J. Hartmann Joel Babdor Pier Federico Gherardini El-Ad D. Amir Kyle Jones Bita Sahaf Diana M. Marquez Peter Krutzik Erika O’Donnell Natalia Sigal Holden T. Maecker Everett Meyer Matthew H. Spitzer Sean C. Bendall |
| author_facet | Felix J. Hartmann Joel Babdor Pier Federico Gherardini El-Ad D. Amir Kyle Jones Bita Sahaf Diana M. Marquez Peter Krutzik Erika O’Donnell Natalia Sigal Holden T. Maecker Everett Meyer Matthew H. Spitzer Sean C. Bendall |
| author_sort | Felix J. Hartmann |
| collection | DOAJ |
| description | Summary: The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery. : Hartmann et al. provide an experimental framework to identify and characterize all major human immune cell lineages in a single assay using mass cytometry (CyTOF). This validated and readily available workflow ensures comprehensive immunophenotypic analysis, improves data comparability, and allows identification of disease-associated immune signatures and biomarkers for human immunotherapy. Keywords: immunotherapy, cancer, phenotyping, monitoring, mass cytometry, biomarker, CyTOF, bone marrow transplantation |
| first_indexed | 2024-12-13T08:58:19Z |
| format | Article |
| id | doaj.art-08dc2bfd997743c2b85ccf7a773043f4 |
| institution | Directory Open Access Journal |
| issn | 2211-1247 |
| language | English |
| last_indexed | 2024-12-13T08:58:19Z |
| publishDate | 2019-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj.art-08dc2bfd997743c2b85ccf7a773043f42022-12-21T23:53:12ZengElsevierCell Reports2211-12472019-07-01283819831.e4Comprehensive Immune Monitoring of Clinical Trials to Advance Human ImmunotherapyFelix J. Hartmann0Joel Babdor1Pier Federico Gherardini2El-Ad D. Amir3Kyle Jones4Bita Sahaf5Diana M. Marquez6Peter Krutzik7Erika O’Donnell8Natalia Sigal9Holden T. Maecker10Everett Meyer11Matthew H. Spitzer12Sean C. Bendall13Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA 94305, USADepartments of Otolaryngology-Head and Neck Surgery and Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USAParker Institute for Cancer Immunotherapy, San Francisco, CA 94125, USAAstrolabe Diagnostics, Inc., Fort Lee, NJ 07024, USADepartment of Orofacial Sciences, University of California, San Francisco, San Francisco, CA 94143, USACancer Correlative Science Unit, Cancer Institute, School of Medicine, Stanford University, Palo Alto, CA 94305, USADepartments of Otolaryngology-Head and Neck Surgery and Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USAPrimity Bio, Fremont, CA 94538, USAPrimity Bio, Fremont, CA 94538, USADepartment of Microbiology and Immunology, Stanford University, Palo Alto, CA 94305, USADepartment of Microbiology and Immunology, Stanford University, Palo Alto, CA 94305, USACellular Therapy Facility, Blood and Marrow Transplantation, School of Medicine, Stanford University, Palo Alto, CA 94305, USADepartments of Otolaryngology-Head and Neck Surgery and Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA 94125, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Corresponding authorDepartment of Pathology, School of Medicine, Stanford University, Palo Alto, CA 94305, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA 94125, USA; Corresponding authorSummary: The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery. : Hartmann et al. provide an experimental framework to identify and characterize all major human immune cell lineages in a single assay using mass cytometry (CyTOF). This validated and readily available workflow ensures comprehensive immunophenotypic analysis, improves data comparability, and allows identification of disease-associated immune signatures and biomarkers for human immunotherapy. Keywords: immunotherapy, cancer, phenotyping, monitoring, mass cytometry, biomarker, CyTOF, bone marrow transplantationhttp://www.sciencedirect.com/science/article/pii/S2211124719308228 |
| spellingShingle | Felix J. Hartmann Joel Babdor Pier Federico Gherardini El-Ad D. Amir Kyle Jones Bita Sahaf Diana M. Marquez Peter Krutzik Erika O’Donnell Natalia Sigal Holden T. Maecker Everett Meyer Matthew H. Spitzer Sean C. Bendall Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy Cell Reports |
| title | Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy |
| title_full | Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy |
| title_fullStr | Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy |
| title_full_unstemmed | Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy |
| title_short | Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy |
| title_sort | comprehensive immune monitoring of clinical trials to advance human immunotherapy |
| url | http://www.sciencedirect.com/science/article/pii/S2211124719308228 |
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