4.6 Article

Characterization of Hypoxia Signature to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Glioma Groups

Journal

FRONTIERS IN ONCOLOGY
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2020.00796

Keywords

hypoxia; gene set enrichment analysis; tumor microenvironment; hypoxia risk model; glioma; immune response

Categories

Funding

  1. Fujian Province Natural Science Foundation [2017J01260]
  2. Fujian Provincial Health Technology Project [2018-CX-13]
  3. Joint Funds for the innovation of science and Technology, Fujian Province [2018Y9105]
  4. United Fujian Provincial Health and Education Project for Tackling the Key Research, China [2019-WJ-03]

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Glioma groups, including lower-grade glioma (LGG) and glioblastoma multiforme (GBM), are the most common primary brain tumor. Malignant gliomas, especially glioblastomas, are associated with a dismal prognosis. Hypoxia is a driver of the malignant phenotype in glioma groups; it triggers a cascade of immunosuppressive processes and malignant cellular responses (tumor progression, anti-apoptosis, and resistance to chemoradiotherapy), which result in disease progression and poor prognosis. However, approaches to determine the extent of hypoxia in the tumor microenvironment are still unclear. Here, we downloaded 575 LGG patients and 354 GBM patients from Chinese Glioma Genome Atlas (GGGA), and 530 LGG patients and 167 GBM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. We developed a hypoxia risk model to reflect the immune microenvironment in glioma and predict prognosis. High hypoxia risk score was associated with poor prognosis and indicated an immunosuppressive microenvironment. Hypoxia signature significantly correlated with clinical and molecular features and could serve as an independent prognostic factor for glioma patients. Moreover, Gene Set Enrichment Analysis showed that gene sets associated with the high-risk group were involved in carcinogenesis and immunosuppression signaling. In conclusion, we developed and validated a hypoxia risk model, which served as an independent prognostic indicator and reflected overall immune response intensity in the glioma microenvironment.

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