A 4-gene panel predicting the survival of patients with glioblastoma

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses

BACKGROUND

Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM.

METHODS

A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023.

RESULTS

From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts.

CONCLUSION

We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

Unveiling the Influence of Tumor Microenvironment and Spatial Heterogeneity on Temozolomide Resistance in Glioblastoma Using an Advanced Human In Vitro Model of the Blood-Brain Barrier and Glioblastoma

Glioblastoma (GBM) is the most common primary malignant brain cancer in adults with a dismal prognosis. Temozolomide (TMZ) is the first-in-line chemotherapeutic; however, resistance is frequent and multifactorial. While many molecular and genetic factors have been linked to TMZ resistance, the role of the solid tumor morphology and the tumor microenvironment, particularly the blood-brain barrier (BBB), is unknown. Here, the authors investigate these using a complex in vitro model for GBM and its surrounding BBB. The model recapitulates important clinical features such as a dense tumor core with tumor cells that invade along the perivascular space; and a perfusable BBB with a physiological permeability and morphology that is altered in the presence of a tumor spheroid. It is demonstrated that TMZ sensitivity decreases with increasing cancer cell spatial organization, and that the BBB can contribute to TMZ resistance. Proteomic analysis with next-generation low volume sample workflows of these cultured microtissues revealed potential clinically relevant proteins involved in tumor aggressiveness and TMZ resistance, demonstrating the utility of complex in vitro models for interrogating the tumor microenvironment and therapy validation.

EMP3 sustains oncogenic EGFR/CDK2 signaling by restricting receptor degradation in glioblastoma

Epithelial membrane protein 3 (EMP3) is an N-glycosylated tetraspanin with a putative trafficking function. It is highly expressed in isocitrate dehydrogenase-wild-type glioblastoma (IDH-wt GBM), and its high expression correlates with poor survival. However, the exact trafficking role of EMP3 and how it promotes oncogenic signaling in GBM remain unclear. Here, we show that EMP3 promotes EGFR/CDK2 signaling by regulating the trafficking and enhancing the stability of EGFR. BioID2-based proximity labeling revealed that EMP3 interacts with endocytic proteins involved in the vesicular transport of EGFR. EMP3 knockout (KO) enhances epidermal growth factor (EGF)-induced shuttling of EGFR into RAB7 + late endosomes, thereby promoting EGFR degradation. Increased EGFR degradation is rescued by the RAB7 negative regulator and novel EMP3 interactor TBC1D5. Phosphoproteomic and transcriptomic analyses further showed that EMP3 KO converges into the inhibition of the cyclin-dependent kinase CDK2 and the repression of EGFR-dependent and cell cycle transcriptional programs. Phenotypically, EMP3 KO cells exhibit reduced proliferation rates, blunted mitogenic response to EGF, and increased sensitivity to the pan-kinase inhibitor staurosporine and the EGFR inhibitor osimertinib. Furthermore, EGFR-dependent patient-derived glioblastoma stem cells display a transcriptomic signature consistent with reduced CDK2 activity, as well as increased susceptibility to CDK2 inhibition upon EMP3 knockdown. Lastly, using TCGA data, we showed that GBM tumors with high EMP3 expression have increased total and phosphorylated EGFR levels. Collectively, our findings demonstrate a novel EMP3-dependent mechanism by which EGFR/CDK2 activity is sustained in GBM. Consequently, EMP3's stabilizing effect provides an additional layer of tumor cell resistance against targeted kinase inhibition.

Effect of NMB-regulated ERK1/2 and p65 signaling pathway on proliferation and apoptosis of cervical cancer

Aberrant expression of Neuromedin B (NMB) is associated with the malignant progression of cancer, such as breast cancer, lung cancer and glioma. However, the role of NMB in cervical cancer remains unclear. The present study found that NMB and its receptor NMBR are aberrantly expressed in cervical cancer. NMB activates ERK1/2 and NF-κB signaling pathways, which promote the proliferation of cervical cancer cells and increase the expression of tumor necrosis factor α (TNF-α). The downregulation of NMBR by the specific inhibitor, PD168368, abrogates proliferation and promotes apoptosis of cervical cancer cells. In addition, the NMB/NMBR signaling axis mediates the promoting effect of cancer-associated adipocytes on cervical cancer progression. These findings demonstrate the potential role of NMB/NMBR-regulated ERK1/2 and p65 signaling pathway in cervical cancer progression, which provide new opportunities to diagnose and treat cervical cancer.

DAXX-ATRX regulation of p53 chromatin binding and DNA damage response

DAXX and ATRX are tumor suppressor proteins that form a histone H3.3 chaperone complex and are frequently mutated in cancers with the alternative lengthening of telomeres (ALT). Here, we show that DAXX and ATRX knock-out (KO) U87-T cells that have acquired ALT-like features have defects in p53 chromatin binding and DNA damage response. RNA-seq analysis revealed that p53 pathway is among the most perturbed. ChIP-seq and ATAC-seq revealed a genome-wide reduction in p53 DNA-binding and corresponding loss of chromatin accessibility at many p53 response elements across the genome. Both DAXX and ATRX null cells showed a depletion of histone H3.3 and accumulation of γH2AX at many p53 sites, including subtelomeres. These findings indicate that loss of DAXX or ATRX can compromise p53 chromatin binding and p53 DNA damage response in ALT-like cells, providing a link between histone composition, chromatin accessibility and tumor suppressor function of p53.

Gene clusters based on OLIG2 and CD276 could distinguish molecular profiling in glioblastoma

Background

The molecular profiling of glioblastoma (GBM) based on transcriptomic analysis could provide precise treatment and prognosis. However, current subtyping (classic, mesenchymal, neural, proneural) is time-consuming and cost-intensive hindering its clinical application. A simple and efficient method for classification was imperative.

Methods

In this study, to simplify GBM subtyping more efficiently, we applied a random forest algorithm to conduct 26 genes as a cluster featured with hub genes, OLIG2 and CD276. Functional enrichment analysis and Protein–protein interaction were performed using the genes in this gene cluster. The classification efficiency of the gene cluster was validated by WGCNA and LASSO algorithms, and tested in GSE84010 and Gravandeel’s GBM datasets.

Results

The gene cluster (n = 26) could distinguish mesenchymal and proneural excellently (AUC = 0.92), which could be validated by multiple algorithms (WGCNA, LASSO) and datasets (GSE84010 and Gravandeel’s GBM dataset). The gene cluster could be functionally enriched in DNA elements and T cell associated pathways. Additionally, five genes in the signature could predict the prognosis well (p = 0.0051 for training cohort, p = 0.065 for test cohort).

Conclusions

Our study proved the accuracy and efficiency of random forest classifier for GBM subtyping, which could provide a convenient and efficient method for subtyping Proneural and Mesenchymal GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03083-y.

Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. This study aimed to construct a multi-PCG signature to predict survival for LGG patients.

Methods: LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis, and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature.

Results: From the training (n = 524) and test (n = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with a significantly different overall survival (log rank P < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found that PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways.

Conclusions: The new five-PCG signature is a reliable prognostic marker for LGG patients and has a good prospect in clinical application.

Systematic Analysis of 4-gene Prognostic Signature in Patients with Diffuse Gliomas Based on Gene Expression Profiles

Background: Diffuse gliomas are a group of diseases that contain different degrees of malignancy and complex heterogeneity. Previous studies proposed biomarkers for certain grades of gliomas, but few of them have conducted a systematic analysis of different grades to search for molecular markers.

Methods: WGCNA was used to find significant genes associated with malignant progression of diffuse glioma in TCGA glioma sequencing expression data and the GEO expression profile-merge meta dataset. Lasso regression was used for potential model building and the best model was selected by CPE, IDI, and C_index. Risk score model was used to evaluate the gene signature prognostic power. Multi-omics data, including CNV, methylation, clinical traits, and mutation, were used for model evaluation.

Results: We found out 67 genes significantly associated with malignant progression of diffuse glioma by WGCNA. Next, we established a new 4 gene molecular marker (KDELR2, EMP3, TIMP1, and TAGLN2). Multivariate cox analysis identified the risk score of the 4 genes as an independent predictor of prognosis in patients with diffuse gliomas, and its predictive power was independent of the histopathological grades of glioma. Further, we had confirmed in five independent test datasets and the risk score remained good predictive power. The combination of the prognosis model with specific molecular characteristics possessed a better predictive power. Furthermore, we divided the low-risk group into three subtypes: LowRisk_IDH1^wt, LowRisk_IDH1^mut/ATRX^mut, and LowRisk_IDH1^mut/ATRX^wt by combining IDH1 mutation with ATRX mutation, which possessed obvious survival difference. In further analysis, we found that the 4 gene prognosis model possessed multi-omics features.

Conclusion: We established a malignant-related 4-gene molecular marker by glioma expression profile data from multiple microarrays and sequencing data. The four markers had good predictive power on the overall survival of glioma patients and were associated with gliomas' clinical and genetic backgrounds, including clinical features, gene mutation, methylation, CNV, signal pathways.

The Multifunctional Role of EMP3 in the Regulation of Membrane Receptors Associated with IDH-Wild-Type Glioblastoma

Epithelial membrane protein 3 (EMP3) is a tetraspan membrane protein overexpressed in isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma (GBM). Several studies reported high EMP3 levels as a poor prognostic factor in GBM patients. Experimental findings based on glioma and non-glioma models have demonstrated the role of EMP3 in the regulation of several membrane proteins known to drive IDH-wt GBM. In this review, we summarize what is currently known about EMP3 biology. We discuss the regulatory effects that EMP3 exerts on a variety of oncogenic receptors and discuss how these mechanisms may relate to IDH-wt GBM. Lastly, we enumerate the open questions towards EMP3 function in IDH-wt GBM.

Bombesin Receptor Family Activation and CNS/Neural Tumors: Review of Evidence Supporting Possible Role for Novel Targeted Therapy

G-protein-coupled receptors (GPCRs) are increasingly being considered as possible therapeutic targets in cancers. Activation of GPCR on tumors can have prominent growth effects, and GPCRs are frequently over-/ectopically expressed on tumors and thus can be used for targeted therapy. CNS/neural tumors are receiving increasing attention using this approach. Gliomas are the most frequent primary malignant brain/CNS tumor with glioblastoma having a 10-year survival <1%; neuroblastomas are the most common extracranial solid tumor in children with long-term survival<40%, and medulloblastomas are less common, but one subgroup has a 5-year survival <60%. Thus, there is an increased need for more effective treatments of these tumors. The Bombesin-receptor family (BnRs) is one of the GPCRs that are most frequently over/ectopically expressed by common tumors and is receiving particular attention as a possible therapeutic target in several tumors, particularly in prostate, breast, and lung cancer. We review in this paper evidence suggesting why a similar approach in some CNS/neural tumors (gliomas, neuroblastomas, medulloblastomas) should also be considered.

An Immune-Related Signature for Predicting the Prognosis of Lower-Grade Gliomas

Background

Lower-grade gliomas (LGGs) have more favorable outcomes than glioblastomas; however, LGGs often progress to process glioblastomas within a few years. Numerous studies have proven that the tumor microenvironment (TME) is correlated with the prognosis of glioma.

Methods

LGG RNA-Sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were extracted and then divided into training and testing cohorts, respectively. Immune-related differentially expressed genes (DEGs) were screened to establish a prognostic signature by a multivariate Cox proportional hazards regression model. The immune-related risk score and clinical information, such as age, sex, World Health Organization (WHO) grade, and isocitrate dehydrogenase 1 (IDH1) mutation, were used to independently validate and develop a prognostic nomogram. GO and KEGG pathway analyses to DEGs between immune-related high-risk and low-risk groups were performed.

Results

Sixteen immune-related genes were screened for establishing a prognostic signature. The risk score had a negative correlation with prognosis, with an area under the receiver operating characteristic (ROC) curve of 0.941. The risk score, age, grade, and IDH1 mutation were identified as independent prognostic factors in patients with LGGs. The hazard ratios (HRs) of the high-risk score were 5.247 [95% confidence interval (CI) = 3.060–8.996] in the multivariate analysis. A prognostic nomogram of 1-, 3-, and 5-year survival was established and validated internally and externally. Go and KEGG pathway analyses implied that immune-related biological function and pathways were involved in the TME.

Conclusion

The immune-related prognostic signature and the prognostic nomogram could accurately predict survival.

Prognosis Analysis and Validation of m6A Signature and Tumor Immune Microenvironment in Glioma

Glioma is one of the most typical intracranial tumors, comprising about 80% of all brain malignancies. Several key molecular signatures have emerged as prognostic biomarkers, which indicate room for improvement in the current approach to glioma classification. In order to construct a more veracious prediction model and identify the potential prognosis-biomarker, we explore the differential expressed m⁶A RNA methylation regulators in 665 gliomas from TCGA-GBM and TCGA-LGG. Consensus clustering was applied to the m6A RNA methylation regulators, and two glioma subgroups were identified with a poorer prognosis and a higher grade of WHO classification in cluster 1. The further chi-squared test indicated that the immune infiltration was significantly enriched in cluster 1, indicating a close relation between m⁶A regulators and immune infiltration. In order to explore the potential biomarkers, the weighted gene co-expression network analysis (WGCNA), along with Least absolute shrinkage and selection operator (LASSO), between high/low immune infiltration and m⁶A cluster 1/2 groups were utilized for the hub genes, and four genes (TAGLN2, PDPN, TIMP1, EMP3) were identified as prognostic biomarkers. Besides, a prognostic model was constructed based on the four genes with a good prediction and applicability for the overall survival (OS) of glioma patients (the area under the curve of ROC achieved 0.80 (0.76-0.83) and 0.72 (0.68-0.76) in TCGA and Chinese Glioma Genome Atlas (CGGA), respectively). Moreover, we also found PDPN and TIMP1 were highly expressed in high-grade glioma from The Human Protein Atlas database and both of them were correlated with m6A and immune cell marker in glioma tissue samples. In conclusion, we construct a novel prognostic model which provides new insights into glioma prognosis. The PDPN and TIMP1 may serve as potential biomarkers for prognosis of glioma.

Systematic identification of lncRNA-based prognostic biomarkers for glioblastoma

Glioblastoma (GBM), a primary malignant tumor of the central nervous system, has a very poor prognosis. Analysis of global GBM samples has revealed a variety of long non-coding RNAs (lncRNAs) associated with prognosis; nevertheless, there remains a lack of accurate prognostic markers. Using RNA-Seq, methylation, copy number variation (CNV), mutation and clinical follow-up data for GBM patients from The Cancer Genome Atlas, we performed univariate analysis, multi-cluster analysis, differential analysis of different subtypes of lncRNA and coding genes, weighted gene co-expression network analyses, gene set enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis, Gene Ontology analysis, and lncRNA CNV analyses. Our analyses yielded five lncRNAs closely related to survival and prognosis for GBM. To verify the predictive role of these five lncRNAs on the prognosis of GBM patients, the corresponding RNA-seq data from Chinese Glioma Genome Atlas were downloaded and analyzed, and comparable results were obtained. The role of one lncRNA LINC00152 has been observed previously; the others are novel findings. Expression of these lncRNAs could become effective predictors of survival and potential prognostic biomarkers for patients with GBM.

The Pivotal Roles of the Epithelial Membrane Protein Family in Cancer Invasiveness and Metastasis

The members of the family of epithelial membrane proteins (EMPs), EMP1, EMP2, and EMP3, possess four putative transmembrane domain structures and are composed of approximately 160 amino acid residues. EMPs are encoded by the growth arrest-specific 3 (GAS3)/peripheral myelin protein 22 kDa (PMP22) gene family. The GAS3/PMP22 family members play roles in cell migration, growth, and differentiation. Evidence indicates an association of these molecules with cancer progression and metastasis. Each EMP has pro- and anti-metastatic functions that are likely involved in the complex mechanisms of cancer progression. We have recently demonstrated that the upregulation of EMP1 expression facilitates cancer cell migration and invasion through the activation of a small GTPase, Rac1. The inoculation of prostate cancer cells overexpressing EMP1 into nude mice leads to metastasis to the lymph nodes and lungs, indicating that EMP1 contributes to metastasis. Pro-metastatic properties of EMP2 and EMP3 have also been proposed. Thus, targeting EMPs may provide new insights into their clinical utility. Here, we highlight the important aspects of EMPs in cancer biology, particularly invasiveness and metastasis, and describe recent therapeutic approaches.