Correction to: Mutations within FGFR1 are associated with superior outcome in a series of 83 diffuse midline gliomas with H3F3A K27M mutations
Ulrich SchüllerPeter IglauerMario M. DorostkarChristian MawrinJochen HermsArmin GieseMarkus GlatzelJulia E. Neumann
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Tumor progression
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Malignant glioma is the most common and aggressive primary brain tumor and the overall prognosis for glioma patients remains poor. Clarification of the molecular mechanism responsible for glioma progression is critical for the effective treatment of glioma. Melanoma antigen gene (MAGE)-A2 (MAGEA2) is a member of the MAGE-A family proteins widely studied for cancer vaccine development and identification of tumor markers. However, MAGEA2 clinical significance and biological function in glioma remain unclear, especially for the prognosis of glioma patients. This study investigates MAGEA2 expression in glioma tissue samples and its significance in predicting glioma patient prognosis. MAGEA2 protein expression in tissue samples was measured by immunohistochemistry and western blotting, and MAGEA2 mRNA expression was determined by real-time polymerase chain reaction. Our results confirmed that MAGEA2 mRNA and protein expression levels were upregulated in glioma tissues, compared with normal brain tissue. The high expression of MAGEA2 in glioma tissues significantly correlated with World Health Organization advanced grade. Univariate and multivariate analyses revealed that high MAGEA2 expression is an independent prognostic factor for glioma patient poor overall survival. The P53 mRNA expression levels were downregulated in glioma tissues compared to noncancerous brain tissue and MAGEA2 expression negatively correlated with P53 expression. Taken together, our results suggest that MAGEA2 plays an oncogenic role in glioma progression, and they provide insight into MAGEA2 application as a novel predictor of clinical outcomes and a potential glioma biomarker.
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Tumor progression
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Virotherapy
Combination therapy
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A compensatory mutation occurs when the fitness loss caused by one mutation is remedied by its epistatic interaction with a second mutation at a different site in the genome. This poorly understood biological phenomenon has important implications, not only for the evolutionary consequences of mutation, but also for the genetic complexity of adaptation. We have carried out the first direct experimental measurement of the average rate of compensatory mutation. An arbitrary selection of 21 missense substitutions with deleterious effects on fitness was introduced by site-directed mutagenesis into the bacteriophage phiX174. For each deleterious mutation, we evolved 8-16 replicate populations to determine the frequency at which a compensatory mutation, instead of the back mutation, was acquired to recover fitness. The overall frequency of compensatory mutation was approximately 70%. Deleterious mutations that were more severe were significantly more likely to be compensated for. Furthermore, experimental reversion of deleterious mutations revealed that compensatory mutations have deleterious effects in a wild-type background. A large diversity of intragenic compensatory mutations was identified from sequencing fitness-recovering genotypes. Subsequent analyses of intragenic mutation diversity revealed a significant degree of clustering around the deleterious mutation in the linear sequence and also within folded protein structures. Moreover, a likelihood analysis of mutation diversity predicts that, on average, a deleterious mutation can be compensated by about nine different intragenic compensatory mutations. We estimate that about half of all compensatory mutations are located extragenically in this organism.
Mutation Accumulation
Reversion
Epistasis
Mutation frequency
Suppressor mutation
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Abstract Background: Glioma is a type of malignant cancer in the central nervous system. New predictive biomarkers have been investigated in recent years, but the clinical prognosis in glioma remains poor. The function of CPLX2 in glioma and the probable molecular mechanism of tumor suppression was the focus of this investigation. Methods: The glioma transcriptome profile is downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were performed to analyze the expression of CPLX2 in glioma. RT-qPCR was performed to detect the expression of CPLX2 in 68 glioma subjects, these patients who have been followed up. Kaplan-Meier survival analyses were done to evaluate the effect of CPLX2 on the prognosis of glioma patients. The CPLX2 knockdown and overexpressed cell lines were constructed to investigate the effect of CPLX2 on glioma. The cell growth, colony formation, and tumor formation in xenograft were performed. Results: The expression of CPLX2 was downregulated in glioma and negatively correlated to the grade of glioma. The higher expression of CPLX2 predicted a longer survival through the analysis of Kaplan-Meier survival curves. Overexpressed CPLX2 impaired tumorigenesis in glioma progression both in vivo and in vitro . Knocking down of CPLX2 promoted the proliferation of the glioma cells. The analysis of GSEA and co-expression analysis revealed that CPLX2 may affect the malignancy of glioma by regulating hypoxia and inflammation pathway. Conclusions: Our data indicated that CPLX2 functioned as a tumor suppressor and could be used as a potential prognostic marker in glioma.
Tumor progression
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Expression (computer science)
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Nonsynonymous substitution
Pseudogene
Synonymous substitution
Silent mutation
Nonsense mutation
Neutral mutation
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Glioma is a tumor of the brain. Although the clinical regimens and surgical techniques for glioma have improved, therapies of advanced glioma remain challenging, carrying dismal overall survival and therapeutic success rates. Evidence has shown that miRNAs played important roles in glioma development. The current study aimed at investigating the function of a novel cancerogenic miRNA, miR-93, in glioma progression by investigating the expression and mechanism of it.qRT-PCR was conducted to assess the miR-93 expression and the mRNA expression of target gene in glioma tissues and cells. The invasion and migration abilities of the glioma cells were determined by transwell assays. Luciferase reporter assay was performed to confirm the target of miR-93.The results indicated that miR-93 expression in glioma tissues and cells was increased significantly than that in normal brain tissues and cells. Furthermore, miR-93 promoted glioma cell migration and invasion. RBL2 was recognized as a direct target of miR-93 in glioma cells, and overexpression of RBL2 could reverse the stimulative effect of miR-93 in glioma cell.The above findings suggested that miR-93 together with RBL2 could be diagnostic targets and novel prognostic markers for glioma.
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Glioma is the most common primary intracranial tumor and is related to poor clinical outcomes. The developments of sensitive markers can be applied to reveal the mechanisms involved in the progression of glioma. This study examined CDCA2 expression in glioma samples and its significance in predicting glioma patient outcome. GEPIA and GEO datasets were used to explore the expression of CDCA2 in glioma. Kaplan-Meier and multivariate assays were applied to delve into the prognostic values of CDCA2 expression in glioma patients using CGGA datasets. Our group also determined the associations between CDCA2 and clinical characteristics. Coexpression analysis was performed. In this research, we observed that CDCA2 expression was distinctly upregulated in glioma specimens compared with nontumor specimens. The prognosis of glioma with high CDCA2 expression was distinctly worse compared with that of glioma with low CDCA2 expression. Additionally, multivariate Cox regression analysis revealed that high CDCA2 expression was an independent poor prognostic indicator for glioma patients. High expression of CDCA2 was positively associated with advanced clinical progression. Coexpression analysis revealed that CDCA2 could be positively related to ASPM, SKA1, DLGAP5, NCAPG, and CDCA8 and was negatively associated with ETNPPL, LDHD, MRVI1, CBX7, and CENPJ. Overall, our findings revealed that CDCA2 might serve as an independent prognosis indicator for glioma.
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