Glioma progression and recurrence involving maintenance and expansion strategies of glioma stem cells by organizing self-advantageous niche microenvironments

Taga, Tetsuya; Tabu, Kouichi

doi:10.1186/s41232-020-00142-7

Cited by 20 publications

(14 citation statements)

References 31 publications

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“…Both pathways are related to tumorassociated immune cells and regulate immunotherapeutic responses (72). Taga et al reported that co-expression of genes related to the extracellular matrix, iron metabolism, and macrophages was associated with treatment outcomes in patients with glioma (36). mTOR complex 2 can control iron metabolism by regulating acetylation of iron-related genes promoter, promoting tumor cell survival (73).…”

Section: Discussionmentioning

confidence: 99%

“…Currently, recurrence or malignant progression is still inevitable, even after treatment with surgical resection, radiotherapy, chemotherapy and immunotherapy. Recently, iron metabolism was found to participate in glioma tumorigenesis, progression, and the tumor microenvironment ( 14 , 36 ). GBM cancer stem-like cells uptake much more iron than non stem-like cells ( 37 ).…”

Section: Discussionmentioning

confidence: 99%

“…However, the non stem-like cells have higher free iron ion level, which reduces cell viability and growth ( 37 ). Iron metabolism also recently became a therapeutic target and a potential prognostic marker of glioma ( 36 , 38 ).…”

Section: Discussionmentioning

confidence: 99%

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Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Wang

et al. 2021

Front. Oncol.

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Lower-grade glioma (LGG) is characterized by genetic and transcriptional heterogeneity, and a dismal prognosis. Iron metabolism is considered central for glioma tumorigenesis, tumor progression and tumor microenvironment, although key iron metabolism-related genes are unclear. Here we developed and validated an iron metabolism-related gene signature LGG prognosis. RNA-sequence and clinicopathological data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model via differential gene expression analysis, univariate Cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO)-regression algorithm. All LGG patients were stratified into high- and low-risk groups, based on the risk score. The prognostic significance of the risk-score model in the TCGA and CGGA cohorts was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Risk- score distributions in subgroups were stratified by age, gender, the World Health Organization (WHO) grade, isocitrate dehydrogenase 1 (IDH1) mutation status, the O6‐methylguanine‐DNA methyl‐transferase (MGMT) promoter-methylation status, and the 1p/19q co-deletion status. Furthermore, a nomogram model with a risk score was developed, and its predictive performance was validated with the TCGA and CGGA cohorts. Additionally, the gene set enrichment analysis (GSEA) identified signaling pathways and pathological processes enriched in the high-risk group. Finally, immune infiltration and immune checkpoint analysis were utilized to investigate the tumor microenvironment characteristics related to the risk score. We identified a prognostic 15-gene iron metabolism-related signature and constructed a risk-score model. High risk scores were associated with an age of > 40, wild-type IDH1, a WHO grade of III, an unmethylated MGMT promoter, and 1p/19q non-codeletion. ROC analysis indicated that the risk-score model accurately predicted 1-, 3-, and 5-year overall survival rates of LGG patients in the both TCGA and CGGA cohorts. KM analysis showed that the high-risk group had a much lower overall survival than the low-risk group (P < 0.0001). The nomogram model showed a strong ability to predict the overall survival of LGG patients in the TCGA and CGGA cohorts. GSEA analysis indicated that inflammatory responses, tumor-associated pathways, and pathological processes were enriched in high-risk group. Moreover, a high risk score correlated with the infiltration immune cells (dendritic cells, macrophages, CD4+ T cells, and B cells) and expression of immune checkpoint (PD1, PDL1, TIM3, and CD48). Our prognostic model was based on iron metabolism-related genes in LGG, can potentially aid in LGG prognosis, and provides potential targets against gliomas.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Wang

et al. 2021

Front. Oncol.

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“…The concept of GSCs emerged in the early 2000s but remained to be fully characterized ( Hemmati et al, 2003 ; Singh et al, 2003 ; Galli et al, 2004 ). As a subpopulation of tumor cells, GSCs are the driving force of tumor recurrence and can self-renew and differentiate ( Taga and Tabu, 2020 ). Unlike GSCs, NSCs are tumor-tropic cells that can be used as vehicles to selectively deliver various anticancer agents to tumor sites ( Mooney et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

A Fast and Efficient Approach to Obtaining High-Purity Glioma Stem Cell Culture

Han

Cai

et al. 2021

Front. Genet.

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Glioma is the most common and malignant primary brain tumor. Patients with malignant glioma usually have a poor prognosis due to drug resistance and disease relapse. Cancer stem cells contribute to glioma initiation, progression, resistance, and relapse. Hence, quick identification and efficient understanding of glioma stem cells (GSCs) are of profound importance for therapeutic strategies and outcomes. Ideally, therapeutic approaches will only kill cancer stem cells without harming normal neural stem cells (NSCs) that can inhibit GSCs and are often beneficial. It is key to identify the differences between cancer stem cells and normal NSCs. However, reports detailing an efficient and uniform protocol are scarce, as are comparisons between normal neural and cancer stem cells. Here, we compared different protocols and developed a fast and efficient approach to obtaining high-purity glioma stem cell by tracking observation and optimizing culture conditions. We examined the proliferative and differentiative properties confirming the identities of the GSCs with relevant markers such as Ki67, SRY-box containing gene 2, an intermediate filament protein member nestin, glial fibrillary acidic protein, and s100 calcium-binding protein (s100-beta). Finally, we identified distinct expression differences between GSCs and normal NSCs including cyclin-dependent kinase 4 and tumor protein p53. This study comprehensively describes the features of GSCs, their properties, and regulatory genes with expression differences between them and normal stem cells. Effective approaches to quickly obtaining high-quality GSCs from patients should have the potential to not only help understand the diseases and the resistances but also enable target drug screening and personalized medicine for brain tumor treatment.

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“…Several groups isolate and characterize stem-like cancer cells in glioma [6][7][8], which lead to the realization that GSCs are resistant to chemotherapy and radiotherapy [9,10]. Some groups try to find the genes which regulate GSCs maintenance and glioma progression [11][12][13][14][15][16][17]. Inspite of so many struggles, the prognosis of GBM has not enhanced in the past decade [17].…”

Section: Introductionmentioning

confidence: 99%

Interferon-Beta Inhibits Human Glioma Stem Cells Rather Than Neural Stem Cells via Cell Cycle and Immune Signaling

Han

Jin

et al. 2021

Preprint

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BackgroundMalignant Glioma is considered to be a highly heterogeneous brain tumor, which may have originated from mutated neural stem cells (NSCs) many years before it was diagnosed. Malignant Glioma is characterized by strong self-renewal potential and immature differentiation potential. The main reason is that malignant glioma holds a key cluster cells, glioma stem cells (GSCs). GSCs contribute to tumorigenesis, tumor progression, recurrence, and treatment resistance. Interferon-beta (IFN-β) is well known for its anti-proliferative efficacy in diversity cancers. IFN-β also displayed potent antitumor results in malignant glioma. IFN-β treatments administered in response to gliomas affect both GSCs and NSCs. However, the function comparison, similarities and differences of IFN-β on GSCs and NSCs are rarely reported. MethodsWe used human GSCs and NSCs to detect the response difference between two cells by IFN-β. Human GSCs were constructed by ourselves and human normal NSCs line were differentiated from human embryonic stem cells. Various concentrations of IFN-β were separately used to treat human GSCs (hGSCs) and human NSCs (hNSCs). Cell morphology, growth, expression of special stemness genes, neural-related makers or proliferation related genes were staining and observed, such as SRY-box transcription factor 2 (Sox2), S100 calcium binding protein B (S100-beta) and marker of proliferation Ki-67 (Ki67). Genetic alterations were carefully analyzed by RNA-seq. We used repetitive stimulation treatment and compared the different response between hGSCs and hNSCs with IFN-β. Genomic analysis was also performed to identify genes with changes in expression levels in hGSCs but stable expression levels in hNSCs. ResultsWe found that IFN-β preferentially inhibited GSCs rather than NSCs. The cell body and nucleus size of GSCs increased after IFN-β treatment. The expression of special stemness gene Sox2 and marker of proliferation Ki67 significantly decreased. S100-beta, which was a central nervous system enrichment, cycle progression and differentiation related gene, also reduced after IFN-β treatment. Significant differences were observed between hGSCs and human NSCs after continuous IFN-β treatment. Genomic analysis revealed the enrichment of the immune response, cell adhesion, cell cycle, and ribosome pathways such as proto-oncogene NF-kB subunit ( RELB ), TRAF interacting protein with forkhead associated domain ( TIFA ), nuclear factor kappa B subunit 1 ( NFKB )and signal transducer and activator of transcription 6 ( STAT6 ). Several typical cyclin genes, including cyclin A2 ( CCNA2) , cyclin B1 ( CCNB1) , cyclin B2 ( CCNB2) , and cyclin D1 ( CCND1) , were significantly downregulated in GSCs after IFN-β stimulation. ConclusionsOur study revealed how genetic diversity resulted in differential effects in response to IFN-β treatment. These results may contribute to improve the applications of IFN-β anti-cancer immunotherapy. In addition, these results may also help to design more effective pharmacological strategies to target killing cancer stem cells while protecting normal neural stem cells.

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Glioma progression and recurrence involving maintenance and expansion strategies of glioma stem cells by organizing self-advantageous niche microenvironments

Cited by 20 publications

References 31 publications

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

A Fast and Efficient Approach to Obtaining High-Purity Glioma Stem Cell Culture

Interferon-Beta Inhibits Human Glioma Stem Cells Rather Than Neural Stem Cells via Cell Cycle and Immune Signaling

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