Prognostic Estimation Model for Oligodendroglioma: An mRNA-Sequence Data-Based Analysis

Abstract

Abstract Object: In contrast with the previous diagnostic strategy, which relied only on histopathologic evidence, the integrated diagnosis of oligodendroglioma based on the 5th edition of World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS 5) criteria requires the codeletion of chromosome arms 1p and 19q and isocitrate dehydrogenase gene (IDH1 or IDH2) mutation (mt). The existing prognostic indicators may not be completely suitable for oligodendroglioma patients based on the new diagnostic criteria. We aimed to identify a prognostic prediction model for oligodendrogliomas based on the WHO CNS5 classification.Methods: We collected 175 glioma samples to investigate significant changes in mRNAs using the Chinese Glioma Genome Atlas (CGGA) database and to establish a prediction model for prognosis by Least Absolute Shrinkage and Selection Operator (LASSO) and Cox logistic analysis.Results: Eighty-eight differentially expressed RNAs (DERNAs) were identified between the long survival group and the short survival group. Seven RNAs were selected to calculate risk scores. Risk level, age and Primary-or-Recurrent Status (PRS) type were used as factors for the prognostic model.Conclusion: An individualized prognostic model for oligodendroglioma patients based on the WHO CNS5 criteria was established. The predictive ability of this model was validated in a validation cohort, which demonstrated its predictive accuracy. In the future, more pathological evidence is needed to support our predictive model to further classify oligodendrogliomas.