Abstract |
Medulloblastoma is one of the most common malignant pediatric brain tumors and has a poor prognosis and high mortality. We investigated the prognostic significance of specific gene signatures and established a novel prognostic model for medulloblastoma patients. Ninety-seven differentially expressed genes between 69 medulloblastoma samples and 4 normal cerebellum samples were identified using the GSE68956 dataset. Univariate and multivariate Cox regression analyses revealed optimal prognosis-related genes, of which PFKP and STXBP1 exhibited significant prognostic values. A risk score model was then established to assess the prognostic value of the gene signature. Kaplan-Meier survival analysis demonstrated that patients with a high risk score had significantly poorer overall survival (OS, log-rank P = 0.003308). The concordance index (C-index) of the two-gene prognostic model for OS prediction was 0.752 (95% CI, 0.740-0.764). The area under the receiver operating characteristic curve (AUC) values for predicting 3-year and 5-year survival were 0.726 and 0.730, respectively. The risk score model was further validated in the ICGC cohort and PUMCH cohort using quantitative real-time polymerase chain reaction (qRT-PCR). Cox regression analyses were performed to assess the two-gene risk score model, metastasis stage, and chemotherapy as independent prognostic factors for medulloblastoma. The C-index of the comprehensive prognostic model composed of the two-gene signature integrated with clinicopathological features for predicting OS was 0.823 (95% CI, 0.739-0.907). The AUCs of the comprehensive prognostic model for predicting 3-year and 5-year survival were 0.774 and 0.759, respectively. Thus, the two-gene risk score model is a promising prognostic biomarker for medulloblastoma.
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Authors | Zihao Wang, Xuesong Sun, Lu Gao, Xiaopeng Guo, Chenzhe Feng, Wei Lian, Kan Deng, Bing Xing |
Journal | American journal of translational research
(Am J Transl Res)
Vol. 12
Issue 5
Pg. 1600-1613
( 2020)
ISSN: 1943-8141 [Print] United States |
PMID | 32509164
(Publication Type: Journal Article)
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Copyright | AJTR Copyright © 2020. |