Establishment of a nomogram with EMP3 for predicting clinical outcomes in patients with glioma: A bi-center study

EMP3 as a prognostic biomarker correlates with EMT in GBM

BACKGROUND

Glioblastoma (GBM) is the most aggressive malignant central nervous system tumor with a poor prognosis.The malignant transformation of glioma cells via epithelial-mesenchymal transition (EMT) has been observed as a main obstacle for glioblastoma treatment. Epithelial membrane protein 3 (EMP3) is significantly associated with the malignancy of GBM and the prognosis of patients. Therefore, exploring the possible mechanisms by which EMP3 promotes the growth of GBM has important implications for the treatment of GBM.

METHODS

We performed enrichment and correlation analysis in 5 single-cell RNA sequencing datasets. Differential expression of EMP3 in gliomas, Kaplan-Meier survival curves, diagnostic accuracy and prognostic prediction were analyzed by bioinformatics in the China Glioma Genome Atlas (CGGA) database and The Cancer Genome Atlas (TCGA) database. EMP3-silenced U87 and U251 cell lines were obtained by transient transfection with siRNA. The effect of EMP3 on glioblastoma proliferation was examined using the CCK-8 assay. Transwell migration assay and wound healing assay were used to assess the effect of EMP3 on glioblastoma migration. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) and western blot were used to detect the mRNA and protein expression levels of EMT-related transcription factors and mesenchymal markers.

RESULTS

EMP3 is a EMT associated gene in multiple types of malignant cancer and in high-grade glioblastoma. EMP3 is enriched in high-grade gliomas and isocitrate dehydrogenase (IDH) wild-type gliomas.EMP3 can be used as a specific biomarker for diagnosing glioma patients. It is also an independent prognostic factor for glioma patients' overall survival (OS). In addition, silencing EMP3 reduces the proliferation and migration of glioblastoma cells. Mechanistically, EMP3 enhances the malignant potential of tumor cells by promoting EMT.

CONCLUSION

EMP3 promotes the proliferation and migration of GBM cells, and the mechanism may be related to EMP3 promoting the EMT process in GBM; EMP3 may be an independent prognostic factor in GBM.

Noninvasive prediction of IDH mutation status in gliomas using preoperative multiparametric MRI radiomics nomogram: A mutlicenter study

PURPOSE

To establish and validate a radiomics nomogram for preoperative prediction of isocitrate dehydrogenase (IDH) mutation status of gliomas in a multicenter setting.

METHODS

414 gliomas patients were collected (306 from local institution and 108 from TCGA). 851 radiomics features were extracted from contrast-enhanced T1-weighted (CE-T1W) and fluid attenuated inversion recovery (FLAIR) sequence, respectively. The features were refined using least absolute shrinkage and selection operator (LASSO) regression combing 10-fold cross-validation. The optimal radiomics features with age and sex were processed by multivariate logistic regression analysis to construct a prediction model, which was developed in the training dataset and assessed in the test and validation dataset. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis were applied in the test and external validation datasets to evaluate the performance of the prediction model.

RESULTS

Ten robust radiomics features were selected from the 1702 features (four CE-T1W features and six FLAIR features). A nomogram was plotted to represent the prediction model. The accuracy and AUC of the radiomics nomogram achieved 86.96% and 0.891(0.809-0.947) in the test dataset and 84.26% and 0.881(0.805-0.936) in the external validation dataset (all p < 0.05). The positive predictive value (PPV) and negative predictive value (NPV) were 83.72% and 87.75% in the test dataset and 87.81% and 82.09% in the external validation dataset.

CONCLUSION

IDH genotypes of gliomas can be identified by preoperative multiparametric MRI radiomics nomogram and might be clinically meaningful for treatment strategy and prognosis stratification of gliomas.

Epithelial Membrane Protein-3 and Chitinase-3-like Protein-1 as New Prognostic Predictors of Glioma, a Two-Gene Study

BACKGROUND

Glioblastoma multiforme is the most common primary intracranial tumor, with a high degree of malignancy, poor therapeutic effect, and poor prognosis. According to previous studies, CHI3L1 and EMP3 are two independent tumor predictors that are of great significance for the prognostic prediction of other tumors, and their expression levels may be related to the prognosis of glioma patients.

METHODS

using Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Chinese Glioma Genome Atlas (CGGA), cBioPortal, LinkedOmics, and other databases, 693 glioma patients were screened to analyze the relationship between EMP3 and CHI3L1 expression and prognosis in glioma patients.

RESULTS

low-grade glioma patients with a low expression of EMP3/CHI3L1 had a better prognosis, and the combination of EMP3/CHI3L1 is a new predictor for glioma patients.

CONCLUSION

We used the TCGA and CGGA databases to analyze the effect of EMP3 and CHI3L1 expression on the prognosis of glioma patients and their correlation with gene expression using bioinformation analysis. The results showed that low-grade glioma patients with a low expression of EMP3 and CHI3L1 had a better prognosis, and EMP3 and CHI3L1 co-expression genes were correlated. The combination of these two factors could be a new prognostic index for glioma patients.

Advances in the application of neuroinflammatory molecular imaging in brain malignancies

The prevalence of brain cancer has been increasing in recent decades, posing significant healthcare challenges. The introduction of immunotherapies has brought forth notable diagnostic imaging challenges for brain tumors. The tumor microenvironment undergoes substantial changes in induced immunosuppression and immune responses following the development of primary brain tumor and brain metastasis, affecting the progression and metastasis of brain tumors. Consequently, effective and accurate neuroimaging techniques are necessary for clinical practice and monitoring. However, patients with brain tumors might experience radiation-induced necrosis or other neuroinflammation. Currently, positron emission tomography and various magnetic resonance imaging techniques play a crucial role in diagnosing and evaluating brain tumors. Nevertheless, differentiating between brain tumors and necrotic lesions or inflamed tissues remains a significant challenge in the clinical diagnosis of the advancements in immunotherapeutics and precision oncology have underscored the importance of clinically applicable imaging measures for diagnosing and monitoring neuroinflammation. This review summarizes recent advances in neuroimaging methods aimed at enhancing the specificity of brain tumor diagnosis and evaluating inflamed lesions.

Identification of a pyroptosis-related prognosis gene signature and its relationship with an immune microenvironment in gliomas

BACKGROUND

Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma is poor. Pyroptosis is a newly discovered inflammatory programmed cell death. However, the expression of pyroptosis-related genes (PRGs) in glioma and its correlation with prognosis are unclear.

METHODS

27 pyroptosis genes differentially expressed between glioma and adjacent normal tissues were identified. All glioma cases could be stratified into 2 subtypes based on these differentially expressed PRGs. The prognostic value of each PRG was evaluated to construct a prognostic model.

RESULTS

A novel 16-gene signature was constructed by using the least absolute shrinkage and selection operator Cox regression method. Then, patients with glioma were divided into low- and high-risk groups in the TCGA cohort. The survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P = .001). Patients with glioma from the Gene Expression Omnibus (GEO) cohort were stratified into 2 risk groups by using the median risk score. The overall survival (OS) of the low-risk group was longer than that of the high-risk group (P = .001). The risk score was considered an independent prognostic factor of the OS of patients with glioma. Gene ontology and Kyoto Encylopedia of Genes and Genomes analysis showed that the differentially expressed PRGs were mainly related to neutrophil activation involved in immune responses, focal adhesion, cell cycle, and p53 signaling pathway.

CONCLUSION

PRGs could predict the prognosis of glioma and play significant roles in a tumor immune microenvironment.

Differences in the Expression Patterns of TGFβ Isoforms and Associated Genes in Astrocytic Brain Tumors

Genes associated with the TGFβ isoforms are involved in a number of different cancers, and their effect on the progression of brain tumors is also being discussed. Using an oligonucleotide microarray method, we assessed differences in expression patterns of genes in astrocytic brain tumor sections from 43 patients at different stages of disease. Quantitative mRNA assessment of the three TGFβ isoforms was also performed by real-time RT-qPCR. Oligonucleotide microarray data were analyzed using the PL-Grid Infrastructure. The microarray analysis showed a statistically significant (p < 0.05) increase in TGFβ1 and TGFβ2 expression in G3/G4 stage relative to G2, whereas real-time RT-qPCR validation confirmed this change only for the TGFβ2 isoform (p < 0.05). The oligonucleotide microarray method allowed the identification of 16 differential genes associated with TGFβ isoforms. Analysis of the STRING database showed that the proteins encoded by the analyzed genes form a strong interaction network (p < 0.001), and a significant number of proteins are involved in carcinogenesis. Differences in expression patterns of transcripts associated with TGFβ isoforms confirm that they play a role in astrocytic brain tumor transformation. Quantitative assessment of TGFβ2 mRNA may be a valuable method to complement the diagnostic process in the future.