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Bracci L, Fragale A, Gabriele L, Moschella F. Towards a Systems Immunology Approach to Unravel Responses to Cancer Immunotherapy. Front Immunol 2020; 11:582744. [PMID: 33193392 PMCID: PMC7649803 DOI: 10.3389/fimmu.2020.582744] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 10/01/2020] [Indexed: 12/23/2022] Open
Abstract
Immunotherapy, particularly immune checkpoint blockade and chimeric antigen receptor (CAR)-T cells, holds a great promise against cancer. These treatments have markedly improved survival in solid as well as in hematologic tumors previously considered incurable. However, durable responses occur in a fraction of patients, and existing biomarkers (e.g. PD-L1) have shown limited prediction power. This scenario highlights the need to dissect the complex interplay between immune and tumor cells to identify reliable biomarkers of response to be used for patients’ selection. In this context, systems immunology represents indeed the new frontier to address important clinical challenges in biomarker discovery. Through the integration of multiple layers of data obtained with several high-throughput approaches, systems immunology may give insights on the vast range of inter-individual differences and on the influences of genes and factors that cooperatively shape the individual immune response to a given treatment. In this Mini Review, we give an overview of the current high-throughput methodologies, including genomics, epigenomics, transcriptomics, metabolomics, proteomics, and multi-parametric phenotyping suitable for systems immunology as well as on the key steps of data integration and biological interpretation. Additionally, we review recent studies in which multi-omics technologies have been used to characterize mechanisms of response and to identify powerful biomarkers of response to checkpoint inhibitors, CAR-T cell therapy, dendritic cell-based and peptide-based cancer vaccines. We also highlight the need of favoring the collaboration of researchers with complementary expertise and of integrating multi-omics data into biological networks with the final goal of developing accurate markers of therapeutic response.
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Affiliation(s)
- Laura Bracci
- Tumor Immunology Unit, Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Alessandra Fragale
- Tumor Immunology Unit, Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Lucia Gabriele
- Tumor Immunology Unit, Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Federica Moschella
- Tumor Immunology Unit, Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
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Siebert JC, Görg C, Palmer B, Lozupone C. Visualizing microbiome-immune system interplay. Immunotherapy 2019; 11:63-67. [PMID: 30730269 PMCID: PMC6354219 DOI: 10.2217/imt-2018-0138] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 10/23/2018] [Indexed: 12/21/2022] Open
Affiliation(s)
- Janet C Siebert
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- CytoAnalytics, Denver, CO 80113, USA
| | - Carsten Görg
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Brent Palmer
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Catherine Lozupone
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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Ellsworth SG, Rabatic BM, Chen J, Zhao J, Campbell J, Wang W, Pi W, Stanton P, Matuszak M, Jolly S, Miller A, Kong FM. Principal component analysis identifies patterns of cytokine expression in non-small cell lung cancer patients undergoing definitive radiation therapy. PLoS One 2017; 12:e0183239. [PMID: 28934231 PMCID: PMC5608186 DOI: 10.1371/journal.pone.0183239] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 08/01/2017] [Indexed: 02/07/2023] Open
Abstract
Background/Purpose Radiation treatment (RT) stimulates the release of many immunohumoral factors, complicating the identification of clinically significant cytokine expression patterns. This study used principal component analysis (PCA) to analyze cytokines in non-small cell lung cancer (NSCLC) patients undergoing RT and explore differences in changes after hypofractionated stereotactic body radiation therapy (SBRT) and conventionally fractionated RT (CFRT) without or with chemotherapy. Methods The dataset included 141 NSCLC patients treated on prospective clinical protocols; PCA was based on the 128 patients who had complete CK values at baseline and during treatment. Patients underwent SBRT (n = 16), CFRT (n = 18), or CFRT (n = 107) with concurrent chemotherapy (ChRT). Levels of 30 cytokines were measured from prospectively collected platelet-poor plasma samples at baseline, during RT, and after RT. PCA was used to study variations in cytokine levels in patients at each time point. Results Median patient age was 66, and 22.7% of patients were female. PCA showed that sCD40l, fractalkine/C3, IP10, VEGF, IL-1a, IL-10, and GMCSF were responsible for most variability in baseline cytokine levels. During treatment, sCD40l, IP10, MIP-1b, fractalkine, IFN-r, and VEGF accounted for most changes in cytokine levels. In SBRT patients, the most important players were sCD40l, IP10, and MIP-1b, whereas fractalkine exhibited greater variability in CFRT alone patients. ChRT patients exhibited variability in IFN-γ and VEGF in addition to IP10, MIP-1b, and sCD40l. Conclusions PCA can identify potentially significant patterns of cytokine expression after fractionated RT. Our PCA showed that inflammatory cytokines dominate post-treatment cytokine profiles, and the changes differ after SBRT versus CFRT, with vs without chemotherapy. Further studies are planned to validate these findings and determine the clinical significance of the cytokine profiles identified by PCA.
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Affiliation(s)
- Susannah G. Ellsworth
- Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indianapolis, United States of America
| | - Bryan M. Rabatic
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jie Chen
- Department of Biostatistics & Epidemiology, Augusta University; Augusta, Georgia, United States of America
| | - Jing Zhao
- Department of Radiation Oncology, Augusta University, Augusta, Georgia, United States of America
| | - Jeffrey Campbell
- Department of Radiation Oncology, Augusta University, Augusta, Georgia, United States of America
| | - Weili Wang
- Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indianapolis, United States of America
| | - Wenhu Pi
- Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indianapolis, United States of America
| | - Paul Stanton
- Department of Radiation Oncology, Augusta University, Augusta, Georgia, United States of America
| | - Martha Matuszak
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, United States of America
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, United States of America
| | - Amy Miller
- Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indianapolis, United States of America
| | - Feng-Ming Kong
- Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indianapolis, United States of America
- * E-mail:
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Stroncek DF, Butterfield LH, Cannarile MA, Dhodapkar MV, Greten TF, Grivel JC, Kaufman DR, Kong HH, Korangy F, Lee PP, Marincola F, Rutella S, Siebert JC, Trinchieri G, Seliger B. Systematic evaluation of immune regulation and modulation. J Immunother Cancer 2017; 5:21. [PMID: 28331613 PMCID: PMC5359947 DOI: 10.1186/s40425-017-0223-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 02/10/2017] [Indexed: 02/06/2023] Open
Abstract
Cancer immunotherapies are showing promising clinical results in a variety of malignancies. Monitoring the immune as well as the tumor response following these therapies has led to significant advancements in the field. Moreover, the identification and assessment of both predictive and prognostic biomarkers has become a key component to advancing these therapies. Thus, it is critical to develop systematic approaches to monitor the immune response and to interpret the data obtained from these assays. In order to address these issues and make recommendations to the field, the Society for Immunotherapy of Cancer reconvened the Immune Biomarkers Task Force. As a part of this Task Force, Working Group 3 (WG3) consisting of multidisciplinary experts from industry, academia, and government focused on the systematic assessment of immune regulation and modulation. In this review, the tumor microenvironment, microbiome, bone marrow, and adoptively transferred T cells will be used as examples to discuss the type and timing of sample collection. In addition, potential types of measurements, assays, and analyses will be discussed for each sample. Specifically, these recommendations will focus on the unique collection and assay requirements for the analysis of various samples as well as the high-throughput assays to evaluate potential biomarkers.
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Affiliation(s)
- David F Stroncek
- Department of Transfusion Medicine, National Institutes of Health, 10 Center Drive, Building 10, Room 3C720, Bethesda, MD 20892 USA
| | - Lisa H Butterfield
- Department of Medicine, Surgery and Immunology, University of Pittsburgh Cancer Institute, 5117 Centre Avenue, Pittsburgh, PA 15213 USA
| | - Michael A Cannarile
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Munich, Nonnenwald 2, 82377 Penzberg, Germany
| | - Madhav V Dhodapkar
- Department of Hematology & Immunobiology, Yale University, 333 Cedar Street, Box 208021, New Haven, CT 06510 USA
| | - Tim F Greten
- GI-Malignancy Section, Thoracic and GI Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Building 10 Room 12 N226, 9000 Rockville, Bethesda, MD 20892 USA
| | - Jean Charles Grivel
- Division of Translational Medicine, Sidra Medical and Research Center, PO Box 26999, Al Luqta Street, Doha, Qatar
| | - David R Kaufman
- Merck Research Laboratories, PO Box 1000, UG 3CD28, North Wales, PA 19454 USA
| | - Heidi H Kong
- Dermatology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Building 10, MSC 1908, Bethesda, MD 20892-1908 USA
| | - Firouzeh Korangy
- GI-Malignancy Section, Thoracic and GI Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Building 10 Room 12 N226, 9000 Rockville, Bethesda, MD 20892 USA
| | - Peter P Lee
- Department of Immuno-Oncology, City of Hope, 1500 East Duarte Road, Duarte, CA 91010 USA
| | - Francesco Marincola
- Division of Translational Medicine, Sidra Medical and Research Center, PO Box 26999, Al Luqta Street, Doha, Qatar
| | - Sergio Rutella
- The John van Geest Cancer Research Centre, Nottingham Trent University, Clifton Campus, Nottingham, NG11 8NS UK
| | - Janet C Siebert
- CytoAnalytics, 3500 South Albion Street, Cherry Hills Village, CO 80113 USA
| | - Giorgio Trinchieri
- Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Building 37/Room 4146, Bethesda, MD 20892 USA
| | - Barbara Seliger
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, Halle, Germany
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Gulley JL, Berzofsky JA, Butler MO, Cesano A, Fox BA, Gnjatic S, Janetzki S, Kalavar S, Karanikas V, Khleif SN, Kirsch I, Lee PP, Maccalli C, Maecker H, Schlom J, Seliger B, Siebert J, Stroncek DF, Thurin M, Yuan J, Butterfield LH. Immunotherapy biomarkers 2016: overcoming the barriers. J Immunother Cancer 2017; 5:29. [PMID: 28653584 PMCID: PMC5359902 DOI: 10.1186/s40425-017-0225-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 02/13/2017] [Indexed: 12/18/2022] Open
Abstract
This report summarizes the symposium, 'Immunotherapy Biomarkers 2016: Overcoming the Barriers', which was held on April 1, 2016 at the National Institutes of Health in Bethesda, Maryland. The symposium, cosponsored by the Society for Immunotherapy of Cancer (SITC) and the National Cancer Institute (NCI), focused on emerging immunotherapy biomarkers, new technologies, current hurdles to further progress, and recommendations for advancing the field of biomarker development.
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Affiliation(s)
- James L Gulley
- Genitourinary Malignancies Branch, Center for Cancer Research, NCI, 10 Center Dr., 13 N240, Bethesda, MD, 20892, USA
| | - Jay A Berzofsky
- Vaccine Branch, Center for Cancer Research, 41 Medlars Dr, Bldg 41 Rm D702D, Bethesda, MD, 20892, USA
| | - Marcus O Butler
- Princess Margaret Cancer Center/Ontario Cancer Institute, RM 9-622, 610 University Ave, Toronto, ON, Canada
| | - Alessandra Cesano
- NanoString, Inc., 500 Fairview Avenue North, Seattle, WA, 98109, USA
| | - Bernard A Fox
- Earle A. Chiles Research Institute, Providence Cancer Center, 4805 NE Glisan Street, Portland, OR, 97213, USA
| | - Sacha Gnjatic
- Department of Hematology/Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, S5-105, 1470 Madison Avenue, Box 1128, New York, NY, 10029, USA
| | - Sylvia Janetzki
- ZellNet Consulting, Inc., 555 North Avenue, Fort Lee, NJ, 07024, USA
| | - Shyam Kalavar
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, 1401 Rockville Pike, Rockville, MD, 20852, USA
| | - Vaios Karanikas
- Roche Innovation Center Zurich, Wagistrasse 18, Schlieren, Switzerland
| | - Samir N Khleif
- Georgia Cancer Center, Augusta University, 1120 15th Street, CN-2101A, Augusta, GA, 30912, USA
| | - Ilan Kirsch
- Adaptive Biotechnologies, Inc., 1551 Eastlake Ave. E., Seattle, WA, 98102, USA
| | - Peter P Lee
- Department of Immuno-oncology, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA
| | - Cristina Maccalli
- Department of Translational Medicine, Sidra Medical and Research Center, Doha, Qatar
| | - Holden Maecker
- Stanford University Medical Center, 299 Campus Drive, Stanford, CA, 94303, USA
| | - Jeffrey Schlom
- National Cancer Institute, National Institutes of Health, 10 Center Drive, Bldg. 10, Room 8B09, Bethesda, MD, 20892, USA
| | - Barbara Seliger
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, Halle, Germany
| | - Janet Siebert
- CytoAnalytics, 3500 South Albion Street, Cherry Hills Village, CO, 80113, USA
| | - David F Stroncek
- Department of Transfusion Medicine, National Institutes of Health, 10 Center Drive, Building 10, Room 3C720, Bethesda, MD, 20892, USA
| | - Magdalena Thurin
- National Cancer Institute, Cancer Diagnosis Program, DCTD, National Institutes of Health, 9609 Medical Center Drive, Bethesda, 20892, MD, USA
| | - Jianda Yuan
- Early Clinical Oncology Development, Merck Research Laboratories, Rahway, NJ, 07065, USA
| | - Lisa H Butterfield
- Department of Medicine, Surgery and Immunology, University of Pittsburgh Cancer Institute, 5117 Centre Avenue, Pittsburgh, PA, 15213, USA.
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Morel PA, Lee REC, Faeder JR. Demystifying the cytokine network: Mathematical models point the way. Cytokine 2016; 98:115-123. [PMID: 27919524 DOI: 10.1016/j.cyto.2016.11.013] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 11/21/2016] [Indexed: 12/22/2022]
Abstract
Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed.
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Affiliation(s)
- Penelope A Morel
- Department of Immunology, University of Pittsburgh, Pittsburgh, USA.
| | - Robin E C Lee
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, USA
| | - James R Faeder
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, USA
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Burel JG, Apte SH, Doolan DL. Systems Approaches towards Molecular Profiling of Human Immunity. Trends Immunol 2016; 37:53-67. [DOI: 10.1016/j.it.2015.11.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Revised: 11/14/2015] [Accepted: 11/15/2015] [Indexed: 12/12/2022]
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Rijkers GT, Meek B, van Overveld FJ. More or less. Expert Rev Clin Immunol 2015; 11:875-6. [PMID: 26092383 DOI: 10.1586/1744666x.2015.1059277] [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: 11/08/2022]
Abstract
Current laboratory investigation of patients with suspected immunodeficiency or immune-mediated disease includes extensive analysis of lymphocyte subsets, T-cell receptor use, antibody profiles, cytokine profiles and genetic polymorphisms of relevant genes, all in all: big data. Clinical immunology clearly has entered the omics era, generating more and more data.
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Affiliation(s)
- Ger T Rijkers
- Science Department, University College Roosevelt, Lange Noordstraat 1, PO Box 94, 4331 CB Middelburg, The Netherlands
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Affiliation(s)
- Glen C Jickling
- From the Department of Neurology and the MIND Institute, University of California at Davis, Sacramento.
| | - Frank R Sharp
- From the Department of Neurology and the MIND Institute, University of California at Davis, Sacramento
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