Screening and Identification of Key Biomarkers in Lower Grade Glioma via Bioinformatical Analysis.
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ABSTRACT:
SUBMITTER: Guo F
PROVIDER: S-EPMC8759910 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundInflammatory response is an important characteristic affecting prognosis and therapeutic response in lower-grade glioma (LGG). However, the molecular subtypes based on inflammatory response are still under exploitation.MethodsThe RNA sequencing, somatic mutation, and corresponding clinical data from 1205 LGG patients were obtained from the TCGA, CGGA, and Rembrandt cohorts. Consensus clustering was performed to identify molecular subtypes associated with inflammation. Prognosis, clinicopathologic features, immune cell infiltration, and somatic mutation profile were compared among these inflammation-associated subtypes.ResultsOur results demonstrate that LGG could be categorized into inflammation-, low, -mid, and -high subtypes with distinct clinicopathologic features, prognostic and tumor microenvironment. We established that this categorization was reproducible, as well as predictable. In general, inflammation-high subtype presents a dismal prognosis with the immunosuppressive microenvironment and high frequency of oncogene mutation. Inversely, inflammation-low subtype was associated with the most favorable clinical outcomes with the immunoreactive microenvironment among three subtypes. Moreover, we develop and validate an inflammation-related prognostic model, which shows strong power for prognosis assessment.ConclusionIn conclusion, we established a novel glioma classification based on the inflammation subtype. This classification had significant outcomes for estimating the prognosis, as well as the tumor microenvironment.
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