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Frederico SC, Raphael I, Nisnboym M, Huq S, Schlegel BT, Sneiderman CT, Jackson SA, Jain A, Olin MR, Rood BR, Pollack IF, Hwang EI, Rajasundaram D, Kohanbash G. Transcriptomic observations of intra and extracellular immunotherapy targets for pediatric brain tumors. Expert Rev Clin Immunol 2024:1-10. [PMID: 39114885 DOI: 10.1080/1744666x.2024.2390023] [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: 05/14/2024] [Accepted: 08/04/2024] [Indexed: 08/20/2024]
Abstract
OBJECTIVES Despite surgical resection, chemoradiation, and targeted therapy, brain tumors remain a leading cause of cancer-related death in children. Immunotherapy has shown some promise and is actively being investigated for treating childhood brain tumors. However, a critical step in advancing immunotherapy for these patients is to uncover targets that can be effectively translated into therapeutic interventions. METHODS In this study, our team performed a transcriptomic analysis across pediatric brain tumor types to identify potential targets for immunotherapy. Additionally, we assessed components that may impact patient response to immunotherapy, including the expression of genes essential for antigen processing and presentation, inhibitory ligands and receptors, interferon signature, and overall predicted T cell infiltration. RESULTS We observed distinct expression patterns across tumor types. These included elevated expression of antigen genes and antigen processing machinery in some tumor types while other tumors had elevated inhibitory checkpoint receptors, known to be associated with response to checkpoint inhibitor immunotherapy. CONCLUSION These findings suggest that pediatric brain tumors exhibit distinct potential for specific immunotherapies. We believe our findings can guide investigators in their assessment of appropriate immunotherapy classes and targets in pediatric brain tumors.
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Affiliation(s)
- Stephen C Frederico
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Itay Raphael
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michal Nisnboym
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
- Department of Neurology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
| | - Sakibul Huq
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brent T Schlegel
- Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chaim T Sneiderman
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sydney A Jackson
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Anya Jain
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael R Olin
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Brian R Rood
- Division of Oncology, Children's National Medical Center, Washington, DC, USA
| | - Ian F Pollack
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eugene I Hwang
- Division of Oncology, Children's National Medical Center, Washington, DC, USA
| | | | - Gary Kohanbash
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Immunology, University of Pittsburgh, Pittsburgh, PA, USA
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Constantinides M, Robert N, Multrier C, Coënon L, Campos-Mora M, Jacquard C, Gao F, Zemiti S, Presumey J, Cartron G, Moreaux J, Villalba M. FCGR3A F158V alleles frequency differs in multiple myeloma patients from healthy population. Oncoimmunology 2024; 13:2388306. [PMID: 39175948 PMCID: PMC11340758 DOI: 10.1080/2162402x.2024.2388306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 06/28/2024] [Accepted: 07/31/2024] [Indexed: 08/24/2024] Open
Abstract
FCGR3A presents a single nucleotide polymorphism at location 158 (V/F), which affects its binding to the fragment crystallizable (Fc) of antibodies (Abs). FcγRIIIa-158 V allotype has the highest affinity and is associated with a better clinical response to IgG1 monoclonal Abs (mAb) treatment. We compared the allele frequency of FCGR3A-F158V polymorphism in cohorts of patients with B-cell lymphoproliferative disorders, including multiple myeloma (MM), monoclonal gammopathy of undetermined significance (MGUS), non-Hodgkin lymphoma (NHL), and B-cell chronic leukemia (B-CLL). FCGR3A-158F homozygous were enriched and tended to be in MM and MGUS patients, respectively; but neither in B-CLL nor in NHL patients. We identified a significantly lower concentration of CD8 T-cells and resting memory CD4 T-cells in MM patients bone marrow with the F/F genotype, associated with an increase in the macrophage percentage. In contrast, natural killer cells increased in V/V homozygous patients. This suggests a deregulation of the immune microenvironment in FCGR3A-F/F homozygous patients. However, we did not observe difference in response following treatment combining chemotherapy associated or not with daratumumab, an IgG1 mAb direct against CD38. Our findings suggest that FCGR3A F158V polymorphism can regulate the immune environment and affect the development of tumor plasma cells.
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Affiliation(s)
- Michaël Constantinides
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
- Department of Clinical Hematology, CHU Montpellier, Montpellier, France
| | - Nicolas Robert
- Department of Biological Hematology, CHU Montpellier, Montpellier, France
| | - Caroline Multrier
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Loïs Coënon
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | | | - Carine Jacquard
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Fei Gao
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Sara Zemiti
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Jessy Presumey
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
| | - Guillaume Cartron
- Department of Clinical Hematology, CHU Montpellier, Montpellier, France
| | - Jérome Moreaux
- Department of Biological Hematology, CHU Montpellier, Montpellier, France
- Institute of Human Genetics, UMR CNRS-UM 9002, Montpellier, France
- Institut Universitaire de France (IUF), Paris, France
| | - Martin Villalba
- IRMB, Univ Montpellier, INSERM, CHU Montpellier, Montpellier, France
- IRMB, Univ Montpellier, INSERM, CNRS, CHRU de Montpellier, Montpellier, France
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Hoffmann M, Willruth LL, Dietrich A, Lee HK, Knabl L, Trummer N, Baumbach J, Furth PA, Hennighausen L, List M. Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2. Sci Rep 2024; 14:2808. [PMID: 38307916 PMCID: PMC10837437 DOI: 10.1038/s41598-024-53117-w] [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: 11/03/2023] [Accepted: 01/28/2024] [Indexed: 02/04/2024] Open
Abstract
Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that-combined with sequence alignments and BLASTp-they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.
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Affiliation(s)
- Markus Hoffmann
- Data Science in Systems Biomedicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
- Institute for Advanced Study, Technical University of Munich, Lichtenbergstrasse 2 a, 85748, Garching, Germany.
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, 20892, USA.
| | - Lina-Liv Willruth
- Data Science in Systems Biomedicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Alexander Dietrich
- Data Science in Systems Biomedicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Hye Kyung Lee
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, 20892, USA
| | | | - Nico Trummer
- Data Science in Systems Biomedicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Jan Baumbach
- Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Computational BioMedicine Lab, University of Southern Denmark, Odense, Denmark
| | - Priscilla A Furth
- Institute for Advanced Study, Technical University of Munich, Lichtenbergstrasse 2 a, 85748, Garching, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, 20892, USA
- Departments of Oncology & Medicine, Georgetown University, Washington, DC, USA
| | - Lothar Hennighausen
- Institute for Advanced Study, Technical University of Munich, Lichtenbergstrasse 2 a, 85748, Garching, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD, 20892, USA
| | - Markus List
- Data Science in Systems Biomedicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
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Hoffmann M, Willruth LL, Dietrich A, Lee HK, Knabl L, Trummer N, Baumbach J, Furth PA, Hennighausen L, List M. Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.03.564190. [PMID: 38076885 PMCID: PMC10705570 DOI: 10.1101/2023.11.03.564190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.
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Affiliation(s)
- Markus Hoffmann
- Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Lina-Liv Willruth
- Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Alexander Dietrich
- Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Hye Kyung Lee
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | | | - Nico Trummer
- Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Jan Baumbach
- Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Computational BioMedicine Lab, University of Southern Denmark, Odense, Denmark
| | - Priscilla A. Furth
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
- Departments of Oncology & Medicine, Georgetown University, Washington, DC, United States of America
| | - Lothar Hennighausen
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Markus List
- Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
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