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Immune-Related lncRNA Correlated with Transcription Factors Provide Strong Prognostic Prediction in Gliomas.
Tian, Yixin; Ke, Yi-Quan; Ma, Yanxia.
Afiliação
  • Tian Y; Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Ke YQ; The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Guangzhou, China.
  • Ma Y; Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
J Oncol ; 2020: 2319194, 2020.
Article em En | MEDLINE | ID: mdl-33178271
ABSTRACT
Glioma is the most common and deadly tumor in central nervous system. According to previous studies, long noncoding RNAs (lncRNA) and transcription factors were significant factors of gliomas progression by regulating gliomas immune microenvironment. In our study, we built two independent cohorts from CGGA and TCGA. And we extracted 253 immune-related lncRNA correlated with prognosis. After LASSO analysis and multivariate Cox regression analysis, 8 immune-related lncRNA were used to construct classifier. The effectiveness of classifier was confirmed in both CGGA (AUC = 0.869) and TCGA (AUC = 0.902) cohorts. The correlation between transcription factors and immune-related lncRNA was calculated by WCGNA. Eventually, we built a network between 8 lncRNA and transcription factors. The function of core immune-related lncRNA in gliomas immune microenvironment was also investigated by CIBERTSORT. Our research provided a strong classifier of immune-related lncRNA to predict gliomas patient outcome. We also found the correlation between core immune-related lncRNA and transcription factors. These results may stimulate new strategy of immunotherapy in gliomas patients.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Oncol Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Oncol Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China