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An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma
Introduction: Patients with glioblastoma (GBM), one of the most aggressive forms of primary brain tumors, exhibit a wide range of neurologic signs, ranging from headaches to neurologic deficits and cognitive impairment, at first clinical presentation. While such variability is attributed to inter-in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559211/ https://www.ncbi.nlm.nih.gov/pubmed/31231419 http://dx.doi.org/10.3389/fgene.2019.00488 |
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author | Katrib, Amal Jeong, Hyun-Hwan Fransen, Nina L. Henzel, Kristin S. Miller, Jeremy A. |
author_facet | Katrib, Amal Jeong, Hyun-Hwan Fransen, Nina L. Henzel, Kristin S. Miller, Jeremy A. |
author_sort | Katrib, Amal |
collection | PubMed |
description | Introduction: Patients with glioblastoma (GBM), one of the most aggressive forms of primary brain tumors, exhibit a wide range of neurologic signs, ranging from headaches to neurologic deficits and cognitive impairment, at first clinical presentation. While such variability is attributed to inter-individual differences in increased intracranial pressure, tumor infiltration, and vascular compromise, a direct association with disease stage, tumor size and location, edema, and necrotic cell death has yet to be established. The lack of specificity of neurologic symptoms often confounds the diagnosis of GBM. It also limits clinicians’ ability to elect treatment regimens that not only prolong survival but also promote symptom management and high quality of life. Methods: To decipher the heterogeneous presentation of neurologic symptoms in GBM, we investigated differences in the molecular makeup of tumors from patients with and without preoperative neurologic deficits. We used the Ivy GAP (Ivy Glioblastoma Atlas Project) database to integrate RNA sequencing data from histologically defined GBM tumor compartments and neurologic examination records for 41 patients. We investigated the association of neurologic deficits with various tumor and patient attributes. We then performed differential gene expression and co-expression network analysis to identify a transcriptional signature specific to neurologic deficits in GBM. Using functional enrichment analysis, we finally provided a comprehensive and detailed characterization of involved pathways and gene interactions. Results: An exploratory investigation of the association of tumor and patient variables with the early development of neurologic deficits in GBM revealed a lack of robust and consistent clinicopathologic prognostic factors. We detected significant differences in the expression of 728 genes (FDR-adjusted p-value ≤ 0.05 and relative fold-change ≥ 1.5), unique to the cellular tumor (CT) anatomical compartment, between neurologic deficit groups. Upregulated differentially expressed genes in CT were enriched for mesenchymal subtype-predictive genes. Applying a systems approach, we then identified co-expressed gene sets that correlated with neurological deficit manifestation (FDR-adjusted p-value < 0.1). Collectively, these findings uncovered significantly enriched immune activation, oxidative stress response, and cytokine-mediated proinflammatory processes. Conclusion: Our study posits that inflammatory processes, as well as a mesenchymal tumor subtype, are implicated in the pathophysiology of preoperative neurologic deficits in GBM. |
format | Online Article Text |
id | pubmed-6559211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65592112019-06-21 An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma Katrib, Amal Jeong, Hyun-Hwan Fransen, Nina L. Henzel, Kristin S. Miller, Jeremy A. Front Genet Genetics Introduction: Patients with glioblastoma (GBM), one of the most aggressive forms of primary brain tumors, exhibit a wide range of neurologic signs, ranging from headaches to neurologic deficits and cognitive impairment, at first clinical presentation. While such variability is attributed to inter-individual differences in increased intracranial pressure, tumor infiltration, and vascular compromise, a direct association with disease stage, tumor size and location, edema, and necrotic cell death has yet to be established. The lack of specificity of neurologic symptoms often confounds the diagnosis of GBM. It also limits clinicians’ ability to elect treatment regimens that not only prolong survival but also promote symptom management and high quality of life. Methods: To decipher the heterogeneous presentation of neurologic symptoms in GBM, we investigated differences in the molecular makeup of tumors from patients with and without preoperative neurologic deficits. We used the Ivy GAP (Ivy Glioblastoma Atlas Project) database to integrate RNA sequencing data from histologically defined GBM tumor compartments and neurologic examination records for 41 patients. We investigated the association of neurologic deficits with various tumor and patient attributes. We then performed differential gene expression and co-expression network analysis to identify a transcriptional signature specific to neurologic deficits in GBM. Using functional enrichment analysis, we finally provided a comprehensive and detailed characterization of involved pathways and gene interactions. Results: An exploratory investigation of the association of tumor and patient variables with the early development of neurologic deficits in GBM revealed a lack of robust and consistent clinicopathologic prognostic factors. We detected significant differences in the expression of 728 genes (FDR-adjusted p-value ≤ 0.05 and relative fold-change ≥ 1.5), unique to the cellular tumor (CT) anatomical compartment, between neurologic deficit groups. Upregulated differentially expressed genes in CT were enriched for mesenchymal subtype-predictive genes. Applying a systems approach, we then identified co-expressed gene sets that correlated with neurological deficit manifestation (FDR-adjusted p-value < 0.1). Collectively, these findings uncovered significantly enriched immune activation, oxidative stress response, and cytokine-mediated proinflammatory processes. Conclusion: Our study posits that inflammatory processes, as well as a mesenchymal tumor subtype, are implicated in the pathophysiology of preoperative neurologic deficits in GBM. Frontiers Media S.A. 2019-06-04 /pmc/articles/PMC6559211/ /pubmed/31231419 http://dx.doi.org/10.3389/fgene.2019.00488 Text en Copyright © 2019 Katrib, Jeong, Fransen, Henzel and Miller. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Katrib, Amal Jeong, Hyun-Hwan Fransen, Nina L. Henzel, Kristin S. Miller, Jeremy A. An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title | An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title_full | An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title_fullStr | An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title_full_unstemmed | An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title_short | An Inflammatory Landscape for Preoperative Neurologic Deficits in Glioblastoma |
title_sort | inflammatory landscape for preoperative neurologic deficits in glioblastoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559211/ https://www.ncbi.nlm.nih.gov/pubmed/31231419 http://dx.doi.org/10.3389/fgene.2019.00488 |
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