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RNA processing genes characterize RNA splicing and further stratify lower-grade glioma.


ABSTRACT: BACKGROUND:Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes. METHODS:This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk-signature. The receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to study the prognosis value of the risk-signature. RESULTS:Among the tested 784 RNA processing genes, 276 were significantly correlated with the OS of LGGs. Further LASSO Cox regression identified a 19-gene risk-signature, whose risk score was also an independently prognosis factor (P<0.0001, multiplex Cox regression) in the validation dataset. The signature had better prognostic value than the traditional factors "age", "grade" and "WHO 2016 classification" for 3- and 5-year survival both two datasets (AUCs > 85%). Importantly, the risk-signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. mRNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score. CONCLUSIONS:Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role.

SUBMITTER: Chai RC 

PROVIDER: S-EPMC6777941 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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RNA processing genes characterize RNA splicing and further stratify lower-grade glioma.

Chai Rui-Chao RC   Li Yi-Ming YM   Zhang Ke-Nan KN   Chang Yu-Zhou YZ   Liu Yu-Qing YQ   Zhao Zheng Z   Wang Zhi-Liang ZL   Chang Yuan-Hao YH   Li Guan-Zhang GZ   Wang Kuan-Yu KY   Wu Fan F   Wang Yong-Zhi YZ  

JCI insight 20190813


<h4>Background</h4>Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes.<h4>Methods</h4>This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a  ...[more]

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