No abstract

Mitochondrial transcription factor A (TFAM), a high-mobility group (HMG) protein, plays a central role in mitochondrial DNA (mtDNA) replication, transcription and inheritance. It has been shown that TFAM is associated with tumorigenesis. However, little is known regarding the posttranscriptional regulation of TFAM in glioma. In the present study, we found that the protein levels of TFAM were gradually increased, while the expression of miRNA-23b was gradually downregulated with the malignancy of glioma. Luciferase assay data demonstrated that miRNA-23b directly regulated TFAM. Furthermore, forced overexpression of miRNA-23b in U251 cells markedly inhibited the proliferation, cell cycle progression, migration and colony formation, while overexpression of TFAM significantly enhanced these biological processes. We further examined the related molecular mechanism, and found that the activity of the PI3K/Akt signaling pathway, critical for cell proliferation and migration, was suppressed in miRNA-23b-overexpressing U251 cells but was upregulated in TFAM-overexpressing cells. In addition, the expression levels of invasion-related MMP2 and MMP9 were decreased in miRNA-23b-overexpressing U251 cells but were increased in TFAM-overexpressing cells. Taken together, the present study provides a new regulatory mechanism as well as a promising therapy target for glioma.

Abstract. Podocalyxin (PODXL) has been found to increase the aggressive phenotype of a number of cancers, including astrocytoma. In addition, the progression of astrocytoma has been associated with sperm-associated antigen 9 (SPAG9), a recently characterized oncoprotein. In the present study, the association between SPAG9 and PODXL in human astrocytoma invasion and the underlying mechanisms were investigated for the first time, to the best of our knowledge. Overexpression and knockdown of SPAG9 were performed in SW1783 (grade III astrocytoma) and U87 (grade IV astrocytoma; glioblastoma) cells, respectively. PODXL expression at both the mRNA and the protein level, as well as the PODXL gene promoter activity, were significantly increased and decreased in parallel with the overexpression and knockdown of SPAG9 in astrocytoma cells; these effects were blocked by the selective c-Jun N-terminal kinase (JNK) inhibitor SP600125 (5 µM) and restored by the JNK agonist anisomycin (25 ng/ml), respectively. SPAG9 overexpression significantly increased cell invasion and matrix metalloproteinase-9 (MMP-9) expression in SW1783 cells, and this effect was reversed by knockdown of PODXL. In U87 cells, knockdown of SPAG9 markedly decreased cell invasion and MMP-9 expression, which was completely restored by overexpression of PODXL. In conclusion, it was demonstrated in the present study that SPAG9 upregulates PODXL expression in human astrocytoma cells at the PODXL gene promoter/transcriptional level through a JNK-dependent mechanism and that PODXL is a critical mediator of the promoting effect of SPAG9 on astrocytoma cell invasion, possibly through upregulation of MMP-9 expression. This study provides novel insights into the molecular mechanisms involved in astrocytoma invasion.

Glioblastoma (GBM) is the most common brain tumor, with rapid proliferation and fatal invasiveness. Large-scale genetic and epigenetic profiling studies have identified targets among molecular subgroups, yet agents developed against these targets have failed in late clinical development. We obtained the genomic and clinical data of GBM patients from the Chinese Glioma Genome Atlas (CGGA) and performed the least absolute shrinkage and selection operator (LASSO) Cox analysis to establish a risk model incorporating 17 genes in the CGGA693 RNA-seq cohort. This risk model was successfully validated using the CGGA325 validation set. Based on Cox regression analysis, this risk model may be an independent indicator of clinical efficacy. We also developed a survival nomogram prediction model that combines the clinical features of OS. To determine the novel classification based on the risk model, we classified the patients into two clusters using ConsensusClusterPlus, and evaluated the tumor immune environment with ESTIMATE and CIBERSORT. We also constructed clinical traits-related and co-expression modules through WGCNA analysis. We identified eight genes (ANKRD20A4, CLOCK, CNTRL, ICA1, LARP4B, RASA2, RPS6, and SET) in the blue module and three genes (MSH2, ZBTB34, and DDX31) in the turquoise module. Based on the public website TCGA, two biomarkers were significantly associated with poorer OS. Finally, through GSCALite, we re-evaluated the prognostic value of the essential biomarkers and verified MSH2 as a hub biomarker.