Identification of the Prognostic Signatures of Glioma With Different PTEN Status

The high-grade glioma is characterized by cell heterogeneity, gene mutations, and poor prognosis. The deletions and mutations of the tumor suppressor gene PTEN (5%-40%) in glioma patients are associated with worse survival and therapeutic resistance. Characterization of unique prognosis molecular si...

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Published inFrontiers in oncology Vol. 11; p. 633357
Main Authors Zhang, Pei, Meng, Xinyi, Liu, Liqun, Li, Shengzhen, Li, Yang, Ali, Sakhawat, Li, Shanhu, Xiong, Jichuan, Liu, Xuefeng, Li, Shouwei, Xia, Qin, Dong, Lei
Format Journal Article
LanguageEnglish
Published Frontiers Media S.A 14.07.2021
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Summary:The high-grade glioma is characterized by cell heterogeneity, gene mutations, and poor prognosis. The deletions and mutations of the tumor suppressor gene PTEN (5%-40%) in glioma patients are associated with worse survival and therapeutic resistance. Characterization of unique prognosis molecular signatures by PTEN status in glioma is still unclear. This study established a novel risk model, screened optimal prognostic signatures, and calculated the risk score for the individual glioma patients with different PTEN status. Screening results revealed fourteen independent prognostic gene signatures in PTEN-wt and three in the -50PTEN-mut subgroup. Moreover, we verified risk score as an independent prognostic factor significantly correlated with tumor malignancy. Due to the higher malignancy of the PTEN-mut gliomas, we explored the independent prognostic signatures ( CLCF1 , AEBP1 , and OS9 ) for a potential therapeutic target in PTEN-mut glioma. We further separated IDH wild-type glioma patients into GBM and LGG to verify the therapeutic target along with PTEN status, notably, the above screened therapeutic targets are also significant prognostic genes in both IDH-wt/PTEN-mut GBM and LGG patients. We further identified the small molecule compound (+)-JQ1 binds to all three targets, indicating a potential therapy for PTEN-mut glioma. In sum, gene signatures and risk scores in the novel risk model facilitate glioma diagnosis, prognosis prediction, and treatment.
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Edited by: Theodore Nicolaides, New York University, United States
This article was submitted to Neuro-Oncology and Neurosurgical Oncology, a section of the journal Frontiers in Oncology
Reviewed by: Lavanya Choppavarapu, The University of Texas Health Science Center at San Antonio, United States; Ichiyo Shibahara, Kitasato University, Japan
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2021.633357