TIMM44 is a potential therapeutic target of human glioma.

TIMM44 (translocase of inner mitochondrial membrane 44) is essential for the maintenance of mitochondrial functions. Bioinformatics studies and results from the local high-grade glioma tissues showed that TIMM44 mRNA and protein levels are elevated in glioma, correlating with poor overall survival. Mitochondrial TIMM44 upregulation was also detected in patient-derived primary glioma cells and immortalized cell line. In primary and established glioma cells, TIMM44 depletion, using the lentiviral shRNA strategy or the CRISPR/Cas9 knockout (KO) method, robustly inhibited cell viability, proliferation and migration. Moreover, TIMM44 silencing/KO resulted in mitochondrial complex I inhibition, ATP depletion, mitochondrial membrane potential reduction, oxidative stress and DNA damage, and eventually provoked apoptosis. Conversely, ectopic overexpression of TIMM44 augmented glioma cell proliferation and migration. TIMM44 upregulation in glioma is possibly due to increased TIMM44 transcriptional machinery by the transcription factor GATA3 in a YME1L (YME1 Like 1 ATPase)-dependent manner. In vivo, the growth of subcutaneous glioma xenografts was suppressed after intratumoral injection of TIMM44 shRNA adeno-associated virus (AAV). TIMM44 depletion, ATP reduction, oxidative injury and apoptosis were detected in TIMM44 shRNA AAV-injected glioma xenografts. Moreover, the intracranial growth of TIMM44 KO glioma cells in the mouse brain was largely inhibited. Together, overexpressed TIMM44 could be a novel and promising therapeutic target of human glioma.

A novel tailored immune gene pairs signature for overall survival prediction in lower-grade gliomas.

Lower-grade gliomas (LGGs) have a good prognosis with a wide range of overall survival (OS) outcomes. An accurate prognostic system can better predict survival time. An RNA-Sequencing (RNA-seq) prognostic signature showed a better predictive power than clinical predictor models. A signature constructed using gene pairs can transcend changes from biological heterogeneity, technical biases, and different measurement platforms. RNA-seq coupled with corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Immune-related gene pairs (IRGPs) were used to establish a prognostic signature through univariate and multivariate Cox proportional hazards regression. Weighted gene co-expression network analysis (WGCNA) was used to evaluate module eigengenes correlating with immune cell infiltration and to construct gene co-expression networks. Samples in the training and testing cohorts were dichotomized into high- and low-risk groups. Risk score was identified as an independent predictor, and exhibited a closed relationship with prognosis. WGCNA presented a gene set that was positively correlated with age, WHO grade, isocitrate dehydrogenase (IDH) mutation status, 1p/19 codeletion, risk score, and immune cell infiltrations (CD4 T cells, B cells, dendritic cells, and macrophages). A nomogram comprising of age, WHO grade, 1p/19q codeletion, and three gene pairs (BIRC5|SSTR2, BMP2|TNFRSF12A, and NRG3|TGFB2) was established as a tool for predicting OS. The IPGPs signature, which is associated with immune cell infiltration, is a novel tailored tool for individual-level prediction.