Hallmarks of glioblastoma: a systematic review

Nørøxe, Dorte Schou; Poulsen, Hans Skovgaard; Lassen, Ulrik

doi:10.1136/esmoopen-2016-000144

Cited by 151 publications

(121 citation statements)

References 77 publications

(71 reference statements)

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“…From the list of 273 GO terms enriched, the top 25 given by the percentage of genes in the gene set associated to the term are listed, and sorted by increased false discovery rate (from top to bottom). From the genes selected, known markers in glioma and GBM, namely SOX9 and EGFR [5,[19][20][21], are here associated to astrocyte development and differentiation.…”

Section: Resultsmentioning

confidence: 99%

“…Among the genes selected by Model I, discriminating between tumor core and periphery neoplastic astrocytes, 3 genes up-regulated in GBM infiltrating tumor cells with functions involving the invasion of the interstitial matrix were also pointed by Darmanis et al (2017) [5], namely: ATP1A2, a NA + /K + ATPase involved in size regulation; PRODH, related to proline catabolism and might contribute to increase ATP energy demands of migrating cells; and FGFR3, inducing increased infiltrating cell expression of cell survival signaling [5]. Among the genes always selected by Model II, discriminating between tumor periphery neoplastic astrocytes and normal tumor periphery astrocytes, the epidermal growth factor receptor (EGFR), up-regulated in neoplastic periphery astrocytes over normal periphery astrocytes, is a previously reported significantly mutated gene in GBM [20,21].…”

Section: Discussionmentioning

confidence: 99%

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Tracking intratumoral heterogeneity in glioblastoma via regularized classification of single-cell RNA-Seq data

Lopes

Vinga

2020

BMC Bioinformatics

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Background: Understanding cellular and molecular heterogeneity in glioblastoma (GBM), the most common and aggressive primary brain malignancy, is a crucial step towards the development of effective therapies. Besides the inter-patient variability, the presence of multiple cell populations within tumors calls for the need to develop modeling strategies able to extract the molecular signatures driving tumor evolution and treatment failure. With the advances in single-cell RNA Sequencing (scRNA-Seq), tumors can now be dissected at the cell level, unveiling information from their life history to their clinical implications. Results: We propose a classification setting based on GBM scRNA-Seq data, through sparse logistic regression, where different cell populations (neoplastic and normal cells) are taken as classes. The goal is to identify gene features discriminating between the classes, but also those shared by different neoplastic clones. The latter will be approached via the network-based twiner regularizer to identify gene signatures shared by neoplastic cells from the tumor core and infiltrating neoplastic cells originated from the tumor periphery, as putative disease biomarkers to target multiple neoplastic clones. Our analysis is supported by the literature through the identification of several known molecular players in GBM. Moreover, the relevance of the selected genes was confirmed by their significance in the survival outcomes in bulk GBM RNA-Seq data, as well as their association with several Gene Ontology (GO) biological process terms. Conclusions:We presented a methodology intended to identify genes discriminating between GBM clones, but also those playing a similar role in different GBM neoplastic clones (including migrating cells), therefore potential targets for therapy research. Our results contribute to a deeper understanding on the genetic features behind GBM, by disclosing novel therapeutic directions accounting for GBM heterogeneity.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Tracking intratumoral heterogeneity in glioblastoma via regularized classification of single-cell RNA-Seq data

Lopes

Vinga

2020

BMC Bioinformatics

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“…However, in spite of multimodal treatment, patients have poor prognosis with a median survival of 14-16 months and 5-year overall survival (OS) of 9.8% [21].…”

Section: Discussionmentioning

confidence: 99%

“…e molecular profile associated with the clinical outcome has proposed IDH as an essential prognostic biomarker in brain tumours. e IDH is an enzyme involved in cellular metabolism, which is explicitly designated as a hallmark of the "reprogramming cellular energetics" mechanisms [21].…”

Section: Genetic Profile and Epigenetic Plasticity In Glioblastomamentioning

confidence: 99%

Extracellular Vesicles Involvement in the Modulation of the Glioblastoma Environment

Ciccocioppo

Lanuti

Marchisio

et al. 2020

Journal of Oncology

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Glioblastoma (GBM) is the most deadly primary brain tumour and is a paradigmatic example of heterogeneous cancer. Although expanding data propose the phenotypic plasticity exhibited by glioblastoma cells, as a critical feature involved in the tumour development and posttherapy recurrence, the central machinery responsible for their aggressiveness remains elusive. Despite decades of research, the complex biology of the glioblastoma is still unknown. Progress in genetic and epigenetic discoveries has improved diagnostic classification, prognostic information, and therapeutic planning. In the complex model of intercellular signalling, several studies have shown that extracellular vesicles have a key role in the intercellular communication among GBM cells and the tumour microenvironment modulation. The purpose of this review is to summarize the role of the EV-mediated intercellular crosstalk in the glioblastoma physiopathology.

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“…Temozolomide (first-line chemotherapeutic for treatment of GBM) and radiotherapy has been limited due to treatment toxicity and therapeutic resistance, and failure to successfully remove all surrounding tumour cells during surgical resection (Candolfi et al, 2007), thus resulting in a high chance of tumour recurrence. Consequently, survival rates have remained relatively stagnant over the past 30 years (Nørøxe et al, 2016). In order to improve clinical outcomes for patients undergoing therapy, there is a need for the development of new therapeutic strategies that investigate alternative compounds that possess cytotoxic activity with the ability to inhibit tissue invasion.…”

Section: Introductionmentioning

confidence: 99%

Ursolic acid inhibits cell migration and promotes JNK-dependent lysosomal associated cell death in Glioblastoma multiforme cells

Conway

Zizyte

Mondala

et al. 2020

Preprint

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Running title: Ursolic Acid is Pro-Apoptotic and Anti-Invasive in GBM Abbreviations: UA, Ursolic acid; GBM, Glioblastoma Multiforme; TMZ, temozolomide; 3-MA, 3methyladenine. AbstractUrsolic acid (UA) is a bioactive compound which has demonstrated therapeutic efficacy in a variety of cancer cell lines. UA activates various signalling pathways in Glioblastoma multiforme (GBM), however, the relationship between cell death and migration has yet to be elucidated. UA induces a dose dependent cytotoxic response demonstrated by flow cytometry and biochemical cytotoxicity assays. Inhibitor and fluorescent probe studies demonstrated that UA induces a caspase independent, JNK dependent, mechanism of cell death. Migration studies established that UA inhibits GBM cell migration in a time dependent manner that is independent of the JNK signalling pathway. The cytotoxic insult induced by UA resulted in the formation of acidic vesicle organelles (AVOs), speculating activation of autophagy. However, inhibitor and spectrophotometric analysis demonstrated that autophagy was not responsible for the formation of the AVOs and confocal microscopy identified the AVO's as lysosomes. Further investigation using isosurface visualisation of confocal imaging determined co-localisation of lysosomes with the previously identified acidic vesicles, thus providing evidence that lysosomes are likely to be playing a role in UA induced cell death.Collectively, our data identifies that UA rapidly induces a lysosomal associated mechanism of cell death in addition to UA acting as an inhibitor of GBM cell migration.

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Hallmarks of glioblastoma: a systematic review

Cited by 151 publications

References 77 publications

Tracking intratumoral heterogeneity in glioblastoma via regularized classification of single-cell RNA-Seq data

Tracking intratumoral heterogeneity in glioblastoma via regularized classification of single-cell RNA-Seq data

Extracellular Vesicles Involvement in the Modulation of the Glioblastoma Environment

Ursolic acid inhibits cell migration and promotes JNK-dependent lysosomal associated cell death in Glioblastoma multiforme cells

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