A study on the correlation between STAT‑1 and mutant p53 expression in glioma

Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.

Bioinformatics Analysis of Expression Profiles and Prognostic Values of the Signal Transducer and Activator of Transcription Family Genes in Glioma

Signal transducer and activator of transcription (STAT) family genes—of which there are seven members: STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, and STAT6—have been associated with the progression of multiple cancers. However, their prognostic values in glioma remain unclear. In this study, we systematically investigated the expression, the prognostic value, and the potential mechanism of the STAT family genes in glioma. The expression of STAT1/2/3/5A/6 members were significantly higher and positively correlated with IDH mutations, while the expression of STAT5B was lower and negatively correlated with IDH mutations in glioma. Survival analysis indicated that the upregulation of STAT1/2/3/5A/6 and downregulation of STAT5B expression was associated with poorer overall survival in glioma. Joint effects analysis of STAT1/2/3/5A/5B/6 expression suggested that the prognostic value of the group was more significant than that of each individual gene. Thus, we constructed a risk score model to predict the prognosis of glioma. The receiver operating characteristic curve and calibration curves showed good performance as prognostic indicators in both TCGA (The Cancer Genome Atlas) and the CGGA (Chinese Glioma Genome Atlas) databases. Furthermore, we analyzed the correlation between STAT expression with immune infiltration in glioma. The Protein–protein interaction network and enrichment analysis showed that STAT members and co-expressed genes mainly participated in signal transduction activity, Hepatitis B, the Jak-STAT signaling pathway, transcription factor activity, sequence-specific DNA binding, and the cytokine-mediated signaling pathway in glioma. In summary, our study analyzed the expression, prognostic values, and biological roles of the STAT gene family members in glioma, based on which we developed a new risk score model to predict the prognosis of glioma more precisely.

miR-29a sensitizes the response of glioma cells to temozolomide by modulating the P53/MDM2 feedback loop

Recently, pivotal functions of miRNAs in regulating common tumorigenic processes and manipulating signaling pathways in brain tumors have been recognized; notably, miR‐29a is closely associated with p53 signaling, contributing to the development of glioma. However, the molecular mechanism of the interaction between miR-29a and p53 signaling is still to be revealed. Herein, a total of 30 glioma tissues and 10 non-cancerous tissues were used to investigate the expression of miR‐29a. CCK-8 assay and Transwell assay were applied to identify the effects of miR-29a altered expression on the malignant biological behaviors of glioma cells in vitro, including proliferation, apoptosis, migration and invasion. A dual-luciferase reporter assay was used to further validate the regulatory effect of p53 or miR-29a on miR-29a or MDM2, respectively, at the transcriptional level. The results showed that miR-29a expression negatively correlated with tumor grade of human gliomas; at the same time it inhibited cell proliferation, migration, and invasion and promoted apoptosis of glioma cells in vitro. Mechanistically, miR-29a expression was induced by p53, leading to aberrant expression of MDM2 targeted by miR-29a, and finally imbalanced the activity of the p53-miR-29a-MDM2 feedback loop. Moreover, miR-29a regulating p53/MDM2 signaling sensitized the response of glioma cells to temozolomide treatment. Altogether, the study demonstrated a potential molecular mechanism in the tumorigenesis of glioma, while offering a possible target for treating human glioma in the future.

Radiomic prediction models for the level of Ki-67 and p53 in glioma

OBJECTIVE

To identify glioma radiomic features associated with proliferation-related Ki-67 antigen and cellular tumour antigen p53 levels, common immunohistochemical markers for differentiating benign from malignant tumours, and to generate radiomic prediction models.

METHODS

Patients with glioma, who were scanned before therapy using standard brain magnetic resonance imaging (MRI) protocols on T1 and T2 weighted imaging, were included. For each patient, regions-of-interest (ROI) were drawn based on tumour and peritumoral areas (5/10/15/20 mm), and features were identified using feature calculations, and used to create and assess logistic regression models for Ki-67 and p53 levels.

RESULTS

A total of 92 patients were included. The best area under the curve (AUC) for the Ki-67 model was 0.773 for T2 weighted imaging in solid glioma (sensitivity, 0.818; specificity, 0.833), followed by a less reliable AUC of 0.773 (sensitivity, 0.727; specificity 0.667) in 20-mm peritumoral areas. The highest AUC for the p53 model was 0.709 (sensitivity, 1; specificity, 0.4) for T2 weighted imaging in 10-mm peritumoral areas.

CONCLUSION

Using T2-weighted imaging, the prediction model for Ki-67 level in solid glioma tissue was better than the p53 model. The 20-mm and 10-mm peritumoral areas in the Ki-67 and p53 model, respectively, showed predictive effects, suggesting value in further research into areas without conventional MRI features.

The effects of 2-hydroxyglutarate on the tumorigenesis of gliomas

Mutation of the isocitrate-dehydrogenase (IDH) enzymes is one of the central research topics regarding gliomagenesis. Indeed, 70% of gliomas are associated with a gain-of-function IDH mutation and consequently synthesize the oncometabolite, 2-hydroxyglutarate (2-HG). This review aims to elucidate the effects of 2-HG on gliomagenesis. 2-HG promotes tumorigenesis by impacting metabolism, vascularization and altering the epigenome of glioma cells. Glioma metabolism and vascularization is altered by 2-HG's effect on the stability of hypoxia-inducible factor (HIF) and inhibition of endostatin. However, 2-HG's impacts on epigenetic mechanisms are more profound to gliomagenesis. Through competitive inhibition of JHDMs and TET proteins, 2-HG orchestrates histone and DNA hypermethylation, which is associated with gene silencing and dedifferentiation of cells. The hypermethylator phenotype induced by 2-HG also results in alterations of the interaction of the immune system with the tumour. Additionally, this study reviews 2-HG promotion of tumorigenesis by inhibiting repair of DNA alkylation damage through competitive inhibition of AlkB proteins.