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Characterization of distinct immunophenotypes across pediatric brain tumor types.

ABSTRACT: Despite increasing evidence that antitumor immune control exists in the pediatric brain, these findings have yet to be exploited successfully in the clinic. A barrier to development of immunotherapeutic strategies in pediatric brain tumors is that the immunophenotype of these tumors' microenvironment has not been defined. To address this, the current study used multicolor FACS of disaggregated tumor to systematically characterize the frequency and phenotype of infiltrating immune cells in the most common pediatric brain tumor types. The initial study cohort consisted of 7 pilocytic astrocytoma (PA), 19 ependymoma (EPN), 5 glioblastoma (GBM), 6 medulloblastoma (MED), and 5 nontumor brain (NT) control samples obtained from epilepsy surgery. Immune cell types analyzed included both myeloid and T cell lineages and respective markers of activated or suppressed functional phenotypes. Immune parameters that distinguished each of the tumor types were identified. PA and EPN demonstrated significantly higher infiltrating myeloid and lymphoid cells compared with GBM, MED, or NT. Additionally, PA and EPN conveyed a comparatively activated/classically activated myeloid cell-skewed functional phenotype denoted in particular by HLA-DR and CD64 expression. In contrast, GBM and MED contained progressively fewer infiltrating leukocytes and more muted functional phenotypes similar to that of NT. These findings were recapitulated using whole tumor expression of corresponding immune marker genes in a large gene expression microarray cohort of pediatric brain tumors. The results of this cross-tumor comparative analysis demonstrate that different pediatric brain tumor types exhibit distinct immunophenotypes, implying that specific immunotherapeutic approaches may be most effective for each tumor type.

SUBMITTER: Griesinger AM

PROVIDER: S-EPMC3827919 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Characterization of distinct immunophenotypes across pediatric brain tumor types.

Griesinger Andrea M AM Birks Diane K DK Donson Andrew M AM Amani Vladimir V Hoffman Lindsey M LM Waziri Allen A Wang Michael M Handler Michael H MH Foreman Nicholas K NK

Journal of immunology (Baltimore, Md. : 1950) 20130927 9

Despite increasing evidence that antitumor immune control exists in the pediatric brain, these findings have yet to be exploited successfully in the clinic. A barrier to development of immunotherapeutic strategies in pediatric brain tumors is that the immunophenotype of these tumors' microenvironment has not been defined. To address this, the current study used multicolor FACS of disaggregated tumor to systematically characterize the frequency and phenotype of infiltrating immune cells in the mo ...[more]

PMID: 24078694

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Project description:Francesca Petralia,Nicole Tignor,Boris Reva, et al., (2020) <a href="https://www.cell.com/cell/fulltext/S0092-8674(20)31451-3" target="_blank">Cell 183, 1962-1985</a>We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.The Children's Brain Tumor Network (CBTN) and the Pacific Pediatric Neuro-Oncology Consortia (PNOC) are collaborative research consortia focused on identifying therapies for children with brain tumors (<a href="https://cbttc.org" target="_blank">https://cbttc.org</a>). The consortia have contributed a <a href="https://kidsfirstdrc.org/support/studies-and-access/#SD_BHJXBDQK" target="_blank">Pediatric Brain Tumor Atlas (PBTA) dataset</a>, a cohort of 991 brain tumor subject clinical data, with associated whole genome sequencing and RNAseq hosted by the Gabriella Miller Kids First Data Resource (<a href="https://kidsfirstdrc.org/" target="_blank">kidsfirstdrc.org</a>) as part of the Gabriella Miller Kids First Pediatric Research Program (Kids First). Kids First is a Pan NIH Common Fund program dedicated to the development of large-scale data resources to help researchers uncover new insights into the biology of childhood cancer and structural birth defects (<a href="https://commonfund.nih.gov/KidsFirst" target="_blank">https://commonfund.nih.gov/KidsFirst</a>).Mass Spectrometry raw data generation along with preliminary analyses were performed at the <a href="https://tcmp.hms.harvard.edu/" target="_blank">Thermo Fisher Scientific Center for Multiplexed Proteomics (TCMP)</a>, Harvard Medical School (HMS) under the direction of <a href="https://cellbio.med.harvard.edu/people/faculty/gygi" target="_blank">Prof. Steven Gygi</a>. Samples were prepared using the streamline (SL)-TMT protocol (<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994137/" target="_blank">Navarrete-Perea et al., 2018</a>) and MS analysis was performed using the SPS-MS3 strategy (<a href="https://www.nature.com/articles/nmeth.1714" target="_blank">Ting et al., 2011</a>) developed in the <a href="https://gygi.med.harvard.edu/" target="_blank">Gygi lab</a>. Additional data analyses from the CPTAC Common Data Analysis Pipeline (<a href="https://www.ncbi.nlm.nih.gov/pubmed/26860878" target="_blank">Rudnick et al., 2016</a>) and from the University of Michigan Proteomics and Integrative Bioinformatics Laboratory (<a href="https://github.com/Nesvilab" target="_blank">https://github.com/Nesvilab</a>) are also provided. All raw and processed genomic data, as well as pathology reports, radiology reports, MRIs, histology slide images are accessible via the <a href="https://portal.kidsfirstdrc.org/dashboard" target="_blank">Kids First DRC (Data Resource Center)</a>.

Project description:BackgroundSevere acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection causes direct lung damage, overwhelming endothelial activation, and inflammatory reaction, leading to acute respiratory failure and multi-organ dysfunction. Ongoing clinical trials are evaluating targeted therapies to hinder this exaggerated inflammatory response. Critically ill coronavirus disease 2019 (COVID-19) patients have shown heterogeneous severity trajectories, suggesting that response to therapies is likely to vary across patients.Research questionAre critically ill COVID-19 patients biologically and immunologically dissociable based on profiling of currently evaluated therapeutic targets?Study design and methodsWe did a single-center, prospective study in an ICU department in France. Ninety-six critically ill adult patients admitted with a documented SARS-CoV-2 infection were enrolled. We conducted principal components analysis and hierarchical clustering on a vast array of immunologic variables measured on the day of ICU admission.ResultsWe found that patients were distributed in three clusters bearing distinct immunologic features and associated with different ICU outcomes. Cluster 1 had a "humoral immunodeficiency" phenotype with predominant B-lymphocyte defect, relative hypogammaglobulinemia, and moderate inflammation. Cluster 2 had a "hyperinflammatory" phenotype, with high cytokine levels (IL-6, IL-1β, IL-8, tumor necrosis factor-alpha [TNF⍺]) associated with CD4+ and CD8+ T-lymphocyte defects. Cluster 3 had a "complement-dependent" phenotype with terminal complement activation markers (elevated C3 and sC5b-9).InterpretationPatients with severe COVID-19 exhibiting cytokine release marks, complement activation, or B-lymphocyte defects are distinct from each other. Such immunologic variability argues in favor of targeting different mediators in different groups of patients and could serve as a basis for patient identification and clinical trial eligibility.

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Characterization of distinct immunophenotypes across pediatric brain tumor types.

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Characterization of distinct immunophenotypes across pediatric brain tumor types.

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