Glioblastoma is the most common primary intracranial malignant tumor in adults and has high morbidity and high mortality. TMEM158 has been reported to promote the progression of solid tumors. However, its potential role in glioma is still unclear. Here, we found that TMEM158 expression in human glioma cells in the tumor core was significantly higher than that in noncancerous cells at the tumor edge using bioinformatics analysis. Cancer cells in patients with primary GBMs harbored significantly higher expression of TMEM158 than those in patients with WHO grade II or III gliomas. Interestingly, regardless of tumor grading, human glioma samples that were IDH1-wild-type (IDH1-WT) exhibited higher expression of TMEM158 than those with IDH1-mutant (IDH1-Mut). We also illustrated that TMEM158 mRNA expression was correlated with poor overall survival in glioma patients. Furthermore, we demonstrated that silencing TMEM158 inhibited the proliferation of glioma cells and that TMEM158 overexpression promoted the migration and invasion of glioma cells by stimulating the EMT process. We found that the underlying mechanism involves STAT3 activation mediating TMEM158-driven glioma progression. In vivo results further confirmed the inhibitory effect of the TMEM158 downregulation on glioma growth. Collectively, these findings further our understanding of the oncogenic function of TMEM158 in gliomas, which represents a potential therapeutic target, especially for GBMs.

Heat-shock protein 90 (HSP90) is an important molecule chaperone associated with tumorigenesis and malignancy. HSP90 is involved in the folding and maturation of a wide range of oncogenic clients, including diverse kinases, transcription factors and oncogenic fusion proteins. Therefore, it could be argued that HSP90 facilitates the malignant behaviors of cancer cells, such as uncontrolled proliferation, chemo/radiotherapy resistance and immune evasion. The extensive associations between HSP90 and tumorigenesis indicate substantial therapeutic potential, and many HSP90 inhibitors have been developed. However, due to HSP90 inhibitor toxicity and limited efficiency, none have been approved for clinical use as single agents. Recent results suggest that combining HSP90 inhibitors with other anticancer therapies might be a more advisable strategy. This review illustrates the role of HSP90 in cancer biology and discusses the therapeutic value of Hsp90 inhibitors as complements to current anticancer therapies.

The tumor immunosuppressive microenvironment (IME) significantly affects tumor occurrence, progression, and prognosis, but the underlying molecular mechanisms remain to make known. We investigated the prognostic significance of PDPN and its role in IME in glioma. Weighted gene co-expression network analysis (WGCNA) found PDPN closely related to IDH wildtype status and higher immune score. Correlation analysis suggested PDPN was highly positively relevant to immune checkpoints expression and immune checkpoints block responding status. Correlation analysis together with verification in vitro suggested PDPN highly positively relevant tumor-associated neutrophils (TANs) and tumor-associated macrophages (TAMs). Least absolute shrinkage and selection operator (LASSO) regression employed to develop the prediction model with TANs and TAMs markers showed that high risk scores predicted worse prognosis. We highlight that PDPN overexpression is an independent prognostic indicator, and promotes macrophage M2 polarization and neutrophil degranulation, ultimately devotes to the formation of an immunosuppressive tumor microenvironment. Our findings contribute to re-recognizing the role of PDPN in IDH wildtype gliomas and implicate promising target therapy combined with immunotherapy for this highly malignant tumor.

BackgroundFerroptosis is a form of programmed cell death (PCD) that has been implicated in cancer progression, although the specific mechanism is not known. Here, we used the latest DepMap release CRISPR data to identify the essential ferroptosis-related genes (FRGs) in glioma and their role in patient outcomes.MethodsRNA-seq and clinical information on glioma cases were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). FRGs were obtained from the FerrDb database. CRISPR-screened essential genes (CSEGs) in glioma cell lines were downloaded from the DepMap portal. A series of bioinformatic and machine learning approaches were combined to establish FRG signatures to predict overall survival (OS) in glioma patients. In addition, pathways analysis was used to identify the functional roles of FRGs. Somatic mutation, immune cell infiltration, and immune checkpoint gene expression were analyzed within the risk subgroups. Finally, compounds for reversing high-risk gene signatures were predicted using the GDSC and L1000 datasets.ResultsSeven FRGs (ISCU, NFS1, MTOR, EIF2S1, HSPA5, AURKA, RPL8) were included in the model and the model was found to have good prognostic value (p < 0.001) in both training and validation groups. The risk score was found to be an independent prognostic factor and the model had good efficacy. Subgroup analysis using clinical parameters demonstrated the general applicability of the model. The nomogram indicated that the model could effectively predict 12-, 36-, and 60-months OS and progression-free interval (PFI). The results showed the presence of more aggressive phenotypes (lower numbers of IDH mutations, higher numbers of EGFR and PTEN mutations, greater infiltration of immune suppressive cells, and higher expression of immune checkpoint inhibitors) in the high-risk group. The signaling pathways enriched closely related to the cell cycle and DNA damage repair. Drug predictions showed that patients with higher risk scores may benefit from treatment with RTK pathway inhibitors, including compounds that inhibit RTKs directly or indirectly by targeting downstream PI3K or MAPK pathways.ConclusionIn summary, the proposed cancer essential FRG signature predicts survival and treatment response in glioma.