Abstract
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.
Highlights
The most common primary brain tumor, glioma, starts with glial support cells around nerve cells [1, 2]
Due to the higher malignancy of the PTEN-mut glioma, we look for potential therapies targeting the prognostic signatures (CLCF1, AEBP1, and OS9) in this subgroup
The Chinese Glioma Genome Atlas (CGGA) dataset showed worse survival in PTEN-mut gliomas compared to the PTEN-wt subgroup (Figure 2C)
Summary
The most common primary brain tumor, glioma, starts with glial support cells around nerve cells [1, 2]. Glioma is associated with high mortality and recurrence rates and poor prognosis [3, 4]. Transcriptomics, and epigenetic analyses gave rise to new concepts for the molecular classification and treatment of gliomas [6]. The molecular signature is important for the tumor’s diagnosis, patient stratification, and personalized treatment. Many studies have shown that glioma patients with IDH (Isocitrate dehydrogenase) mutations have a better prognosis [8,9,10,11,12,13,14]. MGMT was initially identified as a prognostic and predictive signature for glioma diagnosis in patients treated with temozolomide [15]. Signatures in glioma have been highly valued as prognostic, predictive, and clinical application targets
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