Clinical and Molecular Characterization of Incidentally Discovered Lower-Grade Gliomas with Enrichment of Aerobic Respiration

Extracellular Vesicles Derived from Glioma Stem Cells Affect Glycometabolic Reprogramming of Glioma Cells Through the miR-10b-5p/PTEN/PI3K/Akt Pathway

OBJECTIVE

Glioma is one of the most prevalently diagnosed types of primary malignant brain tumors. Glioma stem cells (GSCs) are crucial in glioma recurrence. This study aims to elucidate the mechanism by which extracellular vehicles (EVs) derived from GSCs modulate glycometabolic reprogramming in glioma.

METHODS

Xenograft mouse models and cell models of glioma were established and treated with GSC-EVs. Additionally, levels and activities of PFK1, LDHA, and FASN were assessed to evaluate the effect of GSC-EVs on glycometabolic reprogramming in glioma. Glioma cell proliferation, invasion, and migration were evaluated using MTT, EdU, Colony formation, and Transwell assays. miR-10b-5p expression was determined, with its target gene PTEN and downstream pathway PI3K/Akt evaluated. The involvement of miR-10b-5p and the PI3K/Akt pathway in the effect of GSC-EVs on glycometabolic reprogramming was tested through joint experiments.

RESULTS

GSC-EVs facilitated glycometabolic reprogramming in glioma mice, along with enhancing glucose uptake, lactate level, and adenosine monophosphate-to-adenosine triphosphate ratio. Moreover, GSC-EV treatment potentiated glioma cell proliferation, invasion, and migration, reinforced cell resistance to temozolomide, and raised levels and activities of PFK1, LDHA, and FASN. miR-10b-5p was highly-expressed in GSC-EV-treated glioma cells while being carried into glioma cells by GSC-EVs. miR-10b-5p targeted PTEN and activated the PI3K/Akt pathway, hence stimulating glycometabolic reprogramming.

CONCLUSION

GSC-EVs target PTEN and activate the PI3K/Akt pathway through carrying miR-10b-5p, subsequently accelerating glycometabolic reprogramming in glioma, which might provide new insights into glioma treatment.

Incidental diffuse low-grade gliomas: A systematic review and meta-analysis of treatment results with correction of lead-time and length-time biases

Background

Better overall survival (OS) reported in patients with incidental diffuse low-grade glioma (iLGG) in comparison to symptomatic LGG (sLGG) may be overestimated by lead-time and length-time.

Methods

We performed a systematic review and meta-analysis of studies on adult hemispheric iLGGs according to the PRISMA statement to adjust for biases in their outcomes. Survival data were extracted from Kaplan-Meier curves. Lead-time was estimated by 2 methods: Pooled data of time to become symptomatic (LTs) and time calculated from the tumor growth model (LTg).

Results

We selected articles from PubMed, Ovid Medline, and Scopus since 2000. Five compared OS between patients with iLGG (n = 287) and sLGG (n = 3117). The pooled hazard ratio (pHR) for OS of iLGG to sLGG was 0.40 (95% confidence interval [CI] {0.27-0.61}). The estimated mean LTs and LTg were 3.76 years (n = 50) and 4.16-6.12 years, respectively. The corrected pHRs were 0.64 (95% CI [0.51-0.81]) by LTs and 0.70 (95% CI [0.56-0.88]) by LTg. In patients with total removal, the advantage of OS in iLGG was lost after the correction of lead-time. Patients with iLGG were more likely to be female pooled odds ratio (pOR) 1.60 (95% CI [1.25-2.04]) and have oligodendrogliomas (pOR 1.59 [95% CI {1.05-2.39}]). Correction of the length-time bias, which increased the pHR by 0.01 to 0.03, preserved the statistically significant difference in OS.

Conclusions

The reported outcome in iLGG was biased by lead-time and length-time. Although iLGG had a longer OS after correction of biases, the difference was less than previously reported.

Molecular characteristics of incidental lower-grade glioma for treatment decision-making

OBJECTIVE

Several limitations are associated with the early diagnosis and treatment of incidental lower-grade glioma (iLGG), and due to its unknown molecular features, its management is categorized as either the "wait-and-see" strategy or immediate treatment. Therefore, in this study the authors explored iLGG's clinical and molecular landscape to improve its management.

METHODS

The authors retrospectively assessed the differences between the molecular and clinical characteristics of iLGG and symptomatic lower-grade glioma (sLGG) samples filtered based on symptom data corresponding to The Cancer Genome Atlas cohort with mutations. Thereafter, genomic and transcriptomic analysis was performed.

RESULTS

There was no significant difference between iLGG and sLGG with respect to mutation status; however, there was an increase in the interaction between major mutations in sLGG, depending on the histological subtype and the IDH1 mutation status. Furthermore, the IDH1 mutation characteristics corresponding to wild-type glioma were much more obvious in sLGG than in iLGG. Additionally, in sLGG, genes associated with malignancy, including cell proliferation-related, cell migration-related, epithelial-to-mesenchymal transition-related, and negative regulation of cell death-related genes, were significantly upregulated, and groups showing higher expression levels of these genes were associated with worse prognosis. Also, 8 of the 75 identified upregulated genes showed positive correlation with resistance to the drugs that are normally used for glioma treatment, including procarbazine, carmustine, vincristine, and temozolomide.

CONCLUSIONS

The new insights regarding the different molecular features of iLGG and sLGG indicated that the immediate management of iLGG could result in better prognosis than the wait-and-see strategy.

Modern surgical management of incidental gliomas

Purpose

Gliomas are the most common primary tumors of the central nervous system and are categorized by the World Health Organization into either low-grade (grades 1 and 2) or high-grade (grades 3 and 4) gliomas. A subset of patients with glioma may experience no tumor-related symptoms and be incidentally diagnosed. These incidental low-grade gliomas (iLGG) maintain controversial treatment course despite scientific advancements. Here we highlight the recent advancements in classification, neuroimaging, and surgical management of these tumors.

Methods

A review of the literature was performed. The authors created five subtopics of focus: histological criteria, diagnostic imaging, surgical advancements, correlation of surgical resection and survival outcomes, and clinical implications.

Conclusions

Alternating studies suggest that these tumors may experience higher mutational rates than their counterparts. Significant progress in management of gliomas, regardless of the grade, has been made through modern neurosurgical treatment modalities, diagnostic neuroimaging, and a better understanding of the genetic composition of these tumors. An optimal treatment approach for patients with newly diagnosed iLGG remains ill-defined despite multiple studies arguing in favor of safe maximal resection. Our review emphasizes the not so benign nature of incidental low grade glioma and further supports the need for future studies to evaluate survival outcomes following surgical resection.

MET overexpression contributes to STAT4-PD-L1 signaling activation associated with tumor-associated, macrophages-mediated immunosuppression in primary glioblastomas

Background

Dysregulated receptor tyrosine kinases, such as the mesenchymal-epidermal transition factor (MET), have pivotal role in gliomas. MET and its interaction with the tumor microenvironment have been previously implicated in secondary gliomas. However, the contribution of MET gene to tumor cells’ ability to escape immunosurveillance checkpoints in primary gliomas, especially in glioblastoma (GBM), which is a WHO grade 4 glioma with the worst overall survival, is still poorly understood.

Methods

We investigated the relationship between MET expression and glioma microenvironment by using multiomics data and aimed to understand the potential implications of MET in clinical practice through survival analysis. RNA expression data from a total of 1243 primary glioma samples (WHO grades 2–4) were assembled, incorporating The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and GSE16011 data sets.

Results

Pearson’s correlation test from the three data sets indicated that MET showed a robust correlation with programmed death-ligand 1 (PD-L1) and STAT pathways. Western blot analysis revealed that in GBM cell lines (N33 and LN229), PD-L1 and phosphorylated STAT4 were upregulated by MET activation treatment with hepatocyte growth factor and were downregulated on MET suppression by PLB-1001. Tumor tissue microarray analysis indicated a positive correlation between MET and PD-L1 and macrophage-associated markers. Chromatin immunoprecipitation-PCR assay showed enrichment of STAT4 in the PD-L1 DNA. Transwell co-culture and chemotaxis assays revealed that knockdown of MET in GBM cells inhibited macrophage chemotaxis. Moreover, we performed CIBERSORTx and single-cell RNA sequencing data analysis which revealed an elevated number of macrophages in glioma samples with MET overexpression. Kaplan-Meier survival analysis indicated that activation of the MET/STAT4/PD-L1 pathway and upregulation of macrophages were associated with shorter survival time in patients with primary GBM.

Conclusions

These data indicated that the MET-STAT4-PD-L1 axis and tumor-associated macrophages might enforce glioma immune evasion and were associated with poor prognosis in GBM samples, suggesting potential clinical strategies for targeted therapy combined with immunotherapy in patients with primary GBM.

Tumor microenvironment is associated with clinical and genetic properties of diffuse gliomas and predicts overall survival

Tumor microenvironment (TME) is a complex and dynamic evolving environment which facilitates tumor proliferation and progression. We aimed at investigating the characteristics of tumor microenvironment and its prognostic value in gliomas. Transcriptome data of 702 glioma samples from The Cancer Genome Atlas were included as training dataset, while 325 samples from Chinese Glioma Genome Atlas database and 268 samples from GSE16011 database were used to validate. We found that the infiltration of stromal and immune cell varied in gliomas of different grades and pathological types, and was associated with poor prognosis. Based on the gene expression profile, we constructed a TME-related signature (TMERS), which was closely related to clinical features and genomic variation of gliomas. In TMERS-high group, specific gene mutations and increased copy number alternations were observed. Kaplan-Meier survival and Cox regression analysis showed that TMERS was an independent prognostic indicator. Then we developed a nomogram prognostic model to predict 1-year, 3-year and 5-year survival of patients. Functional analysis confirmed that TMERS could reflect the status of glioma microenvironment, and immunological analysis showed that macrophages were significantly enriched in the TMERS-high group. We established a novel TME-related signature for predicting prognosis and provided new insights into immunotherapy.

Comprehensive analysis of multi-omics data of recurrent gliomas identifies a recurrence-related signature as a novel prognostic marker

Tumor recurrence is a common clinical dilemma in diffuse gliomas. We aimed to identify a recurrence-related signature to predict the prognosis for glioma patients. In the public Chinese Glioma Genome Atlas dataset, we enrolled multi-omics data including genome, epigenome and transcriptome across primary and recurrent gliomas. We included RNA sequencing data from the batch 1 patients (325 patients) as the training set, while RNA sequencing data from the batch 2 patients (693 patients) were selected as the validation set. The R language was used for subsequent analysis. Compared with primary gliomas, more somatic mutations and copy number alterations were revealed in recurrent gliomas. In recurrent gliomas, we identified 113 genes whose methylation levels were significantly different from those of the primary glioma. Through differential expression analysis between primary and recurrent gliomas, we screened 121 recurrence-related genes. Based on these 121 gene expression profiles, consensus clustering of 325 patients yielded two robust groups with different molecular and prognostic features. We developed a recurrence-related risk signature with the lasso regression algorithm. High-risk group had shorter survival and earlier tumor recurrence than the low-risk group. Compared with traditional indicators, the signature showed better prognostic value. In addition, we constructed a nomogram model to predict glioma survival. Functional characteristics analysis found that the signature was associated with cell division and cell cycle. Immune analysis suggested that immunosuppressive status and macrophages might promote glioma recurrence. We demonstrated a novel 18-gene signature that could effectively predict recurrence and prognosis for glioma patients.