Autophagy in glioma cells: An identity crisis with a clinical perspective

Xanthatin suppresses proliferation and tumorigenicity of glioma cells through autophagy inhibition via activation of the PI3K-Akt-mTOR pathway

Glioma is the most common and aggressive primary brain tumor in adults with high morbidity and mortality. Rapid proliferation and diffuse migration are the main obstacles to successful glioma treatment. Xanthatin, a sesquiterpene lactone purified from Xanthium strumarium L., possesses a significant antitumor role in several malignant tumors. In this study, we report that xanthatin suppressed glioma cells proliferation and induced apoptosis in a time- and concentration-dependent manner, and was accompanied by autophagy inhibition displaying a significantly reduced LC3 punctate fluorescence and LC3II/I ratio, decreased level of Beclin 1, while increased accumulation of p62. Notably, treating glioma cells with xanthatin resulted in obvious activation of the PI3K-Akt-mTOR signaling pathway, as indicated by increased mTOR and Akt phosphorylation, decreased ULK1 phosphorylation, which is important in modulating autophagy. Furthermore, xanthatin-mediated pro-apoptosis in glioma cells was significantly reversed by autophagy inducers (rapamycin or Torin1), or PI3K-mTOR inhibitor NVP-BEZ235. Taken together, these findings indicate that anti-proliferation and pro-apoptosis effects of xanthatin in glioma are most likely by inhibiting autophagy via activation of PI3K-Akt-mTOR pathway, suggesting a potential therapeutic strategy against glioma.

Construction and validation of a prognostic model for osteosarcoma patients based on autophagy-related genes

BACKGROUND

Osteosarcoma is the most frequent primary bone malignancy with a poor prognosis because of pulmonary metastasis. Autophagy is strongly associated with tumor metastasis, and it is valuable to construct an autophagy-related gene risk model for predicting the prognosis of osteosarcoma.

METHODS

We obtained ARGs from the Human Autophagy Database and RNA-sequencing data of osteosarcoma patients from the Gene Expression Omnibus (GEO) database. Subsequently, univariate and multivariate cox regression analyses were performed to construct a three-gene prognostic model and its accuracy was further confirmed in the Therapeutic Applications Research to Generate Effective Treatments (TARGET) database. Afterward, we detected the expression levels and effects on osteosarcoma cells metastasis of MYC and MBTPS2, which were involved in the model.

RESULTS

In both training and verification cohorts, patients with lower risk scores had longer OS, and the model was identified as an independent prognostic factor in osteosarcoma. Besides, the ROC curve demonstrated the reliability of the model. Furthermore, RT-qPCR, Western Blotting and IHC results indicated that MYC and MBTPS2 were differently expressed in osteosarcoma tissues and cell lines. MYC knockdown or MBTPS2 overexpression prevented the capacity of migration and invasion in osteosarcoma cell lines through inhibiting cellular autophagy.

CONCLUSION

The risk model based on three ARGs had a strong ability to predict the prognosis of osteosarcoma patients. Our findings also suggested that MYC and MBTPS2 were two major factors regulating autophagy in osteosarcoma, and could serve as potential therapeutic targets for osteosarcoma.

Identification and validation of an autophagy-related signature for predicting survival in lower-grade glioma

Abnormal levels of autophagy have been implicated in the pathogenesis of multiple diseases, including cancer. However, little is known about the role of autophagy-related genes (ARGs) in low-grade gliomas (LGG). Accordingly, the aims of this study were to assess the prognostic values of ARGs and to establish a genetic signature for LGG prognosis. Expression profile data from patients with and without primary LGG were obtained from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression databases, respectively, and consensus clustering was used to identify clusters of patients with distinct prognoses. Nineteen differentially expressed ARGs were selected with threshold values of FDR < 0.05 and |log2 fold change (FC)| ≥ 2, and functional analysis revealed that these genes were associated with autophagy processes as expected. An autophagy-related signature was established using a Cox regression model of six ARGs that separated patients from TCGA training cohort into high- and low-risk groups. Univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor. The signature was successfully validated using the TCGA testing, TCGA entire, and Chinese Glioma Genome Atlas cohorts. Stratified analyses demonstrated that the signature was associated with clinical features and prognosis, and gene set enrichment analysis revealed that autophagy- and cancer-related pathways were more enriched in high-risk patients than in low-risk patients. The prognostic value and expression of the six signature-related genes were also investigated. Thus, the present study constructed and validated an autophagy-related prognostic signature that could optimize individualized survival prediction in LGG patients.

The IL13α 2R paves the way for anti-glioma nanotherapy

Glioblastoma (GBM) is one of the most aggressive (grade IV) gliomas characterized by a high rate of recurrence, resistance to therapy and a grim survival prognosis. The long-awaited improvement in GBM patients' survival rates essentially depends on advances in the development of new therapeutic approaches. Recent preclinical studies show that nanoscale materials could greatly contribute to the improvement of diagnosis and management of brain cancers. In the current review, we will discuss how specific features of glioma pathobiology can be employed for designing efficient targeting approaches. Moreover, we will summarize the main evidence for the potential of the IL-13R alpha 2 receptor (IL13α2R) targeting in GBM early diagnosis and experimental therapy.

Tailoring drug co-delivery nanosystem for mitigating U-87 stem cells drug resistance

Glioblastoma multiforme (GBM) is the most prevalent form of brain tumor, which generally has a poor prognosis. According to consensus, recurrence of the tumor and chemotherapy resistance acquisition are the two distinguishing features of GBM originated from glioblastoma stem cells (GSCs). To eliminate these obstacles inherent in GBM chemotherapy, targeting GSCs through a smart drug delivery system has come to the front position of GBM therapeutics. In this study, B19 aptamer (Apt)-conjugated polyamidoamine (PAMAM) G4C12 dendrimer nanoparticles (NPs), called Apt-NPs, were formulated for the co-delivery of paclitaxel (PTX) and temozolomide (TMZ) to U-87 stem cells. These drugs were loaded using a double emulsification solvent evaporation method. As a result, drug-loaded Apt-NPs significantly inhibited the tumor growth of U-87 stem cells, by the initiation of apoptosis via the downregulation of autophagic and multidrug resistance (MDR) genes. Additionally, by their downregulation by qPCR of CD133, CD44, SOX2, and the canonical Wnt/β-catenin pathway, cell proliferation has substantially decreased. Altogether, the results demonstrate that this intelligent drug co-delivery system is capable of effectively transferring PTX and TMZ to U-87 stem cells and without any toxic effect on Apt-NPs alone to U-87 stem cells. Furthermore, the designed dendrimer-based pharmaceutical system along with single-stranded B19 aptamer might be utilized as a new therapeutic strategy for the treatment of U-87 stem cells drug resistance in the GBM.

Oncolytic Virus-Induced Autophagy in Glioblastoma

Simple Summary

Glioblastoma (GBM) is the most common and aggressive brain tumor with an incidence rate of nearly 3.19/100,000. Current therapeutic options fall short in improving the survival of patients with GBM. Various genetic and microenvironmental factors contribute to GBM progression and resistance to therapy. The development of gene therapies using self-replicating oncolytic viruses can advance GBM treatment. Due to GBM heterogeneity, oncolytic viruses have been genetically modified to improve the antiglioma effect in vitro and in vivo. Oncolytic viruses can activate autophagy signaling in GBM upon tumoral infection. Autophagy can be cytoprotective, whereby the GBM cells catabolize damaged organelles to accommodate to virus-induced stress, or cytotoxic, whereby it leads to the destruction of GBM cells. Understanding the molecular mechanisms that control oncolytic virus-induced autophagic signaling in GBM can fuel further development of novel and more effective genetic vectors.

Abstract

Autophagy is a catabolic process that allows cells to scavenge damaged organelles and produces energy to maintain cellular homeostasis. It is also an effective defense method for cells, which allows them to identify an internalized pathogen and destroy it through the fusion of the autophagosome and lysosomes. Recent reports have demonstrated that various chemotherapeutic agents and viral gene therapeutic vehicles provide therapeutic advantages for patients with glioblastoma as monotherapy or in combination with standards of care. Despite nonstop efforts to develop effective antiglioma therapeutics, tumor-induced autophagy in some studies manifests tumor resistance and glioma progression. Here, we explore the functional link between autophagy regulation mediated by oncolytic viruses and discuss how intracellular interactions control autophagic signaling in glioblastoma. Autophagy induced by oncolytic viruses plays a dual role in cell death and survival. On the one hand, autophagy stimulation has mostly led to an increase in cytotoxicity mediated by the oncolytic virus, but, on the other hand, autophagy is also activated as a cell defense mechanism against intracellular pathogens and modulates antiviral activity through the induction of ER stress and unfolded protein response (UPR) signaling. Despite the fact that the moment of switch between autophagic prosurvival and prodeath modes remains to be known, in the context of oncolytic virotherapy, cytotoxic autophagy is a crucial mechanism of cancer cell death.

Bioinformatic Analyses Identify a Prognostic Autophagy-Related Long Non-coding RNA Signature Associated With Immune Microenvironment in Diffuse Gliomas

Background

Autophagy and long non-coding RNA (lncRNA) play a critical role in tumor progression and microenvironment. However, the role of autophagy-related lncRNAs (ARLs) in glioma microenvironment remains unclear.

Methods

A total of 988 diffuse glioma samples were extracted from TCGA and CGGA databases. Consensus clustering was applied to reveal different subgroups of diffuse gliomas. Kaplan-Meier analysis was used to evaluate survival differences between groups. The infiltration of immune cells was estimated by ssGSEA, TIMER, and CIBERSORT algorithms. The construction of ARL signature was conducted using principal component analysis.

Results

Consensus clustering revealed two clusters of diffuse gliomas, in which cluster 1 was associated with poor prognosis and enriched with malignant subtypes of gliomas. Moreover, cluster 1 exhibited high apoptotic and immune characteristics, and it had a low purity and high infiltration of several immune cells. The constructed ARL signature showed a promising accuracy in predicting the prognosis of glioma patients. ARL score was significantly elevated in the malignant subtype of glioma and the high ARL score indicated a poor prognosis. Besides, the high ARL score notably indicated low tumor purity and high infiltration of macrophages and neutrophils.

Conclusion

Our study developed and validated a novel ARL signature for the classification of diffuse glioma, which was closely associated with glioma immune microenvironment and could serve as a promising prognostic biomarker for glioma patients.

An autophagic gene-based signature to predict the survival of patients with low-grade gliomas

Background

Since autophagy remains an important topic of investigation, the RNA‐sequence profiles of autophagy‐related genes (ARGs) can provide insights into predicting low‐grade gliomas (LGG) prognosis.

Methods

The RNA‐seq profiles of autophagic genes and prognosis data of LGG were integrated from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model were carried out to identify the differentially expressed prognostic autophagy‐related genes. Then, the autophagic‐gene signature was formed and verified in TCGA test set and external CGGA cohorts. Time‐dependent receiver operating characteristic (ROC) was examined to test the accuracy of this signature feature. A nomogram was conducted to meet the needs of clinicians. Sankey diagrams were performed to visualize the relationship between the multigene signatures and clinic‐pathological features.

Results

Twenty‐four ARGs were finally identified most relevant to LGG prognosis. According to the specific prediction index formula, the patients were classified into low‐risk or high‐risk groups. Prognostic accuracy was proved by time‐dependent ROC analysis, with AUC 0.9, 0.93, and 0.876 at the survival time of 2‐, 3‐, and 5‐year, respectively, which was superior to the AUC of the isocitrate dehydrogenase (IDH) mutation. The result was confirmed while validated in the TCGA test set and external validation CGGA cohort. A nomogram was constructed to meet individual needs. With a visualization approach, Sankey diagrams show the relationship of the histological type, IDH status, and predict index. In TCGA and CGGA cohorts, both low‐risk groups displayed better survival rate in LGG while histological type and IDH status did not show consistency results.

Conclusions

24‐ARGs may play crucial roles in the progression of LGG, and LGG patients were effectively divided into low‐risk and high‐risk groups according to prognostic prediction. Overall, our study will provide novel strategies for clinical applications.

Development of Autophagy Signature-Based Prognostic Nomogram for Refined Glioma Survival Prognostication

The current glioma classification could be optimized to cover such a separate and individualized prognosis ranging from a few months to over ten years. Considering its highly conserved role and potential in therapies, autophagy might be a promising element to be incorporated as a refinement for improved survival prognostication. The expression and RNA-seq data of 881 glioma patients from the Gene Expression Omnibus and The Cancer Genome Atlas were included, mapped with autophagy-related genes. Weighted gene coexpression network analysis and Cox regression analysis were used for the autophagy signature establishment, which composed of MUL1, NPC1, and TRIM13. Validations were represented by Kaplan-Meier plots and receiver operating curves (ROC). Cluster analysis suggested the IDH1 mutant involved in the favorable prognosis of the signature clusters. The signature was also immune-related shown by the Gene Ontology analysis and the Gene Set Enrichment Analysis. The high signature risk group held a higher ESTIMATE score (p = 2.6e - 11) and stromal score (p = 1.8e - 10). CD276 significantly correlated with the signature (r = 0.51, p < 0.05). The final nomogram integrated with the autophagy signature, IDH1 mutation, and pathological grade was built with accuracy and discrimination (1-year survival AUC = 0.812, 5-year survival AUC = 0.822, and 10-year survival AUC = 0.834). Its prognostic value and clinical utility were well-defined by the superiority in the comparisons with the current World Health Organization glioma classification in ROC (p < 0.05) and decision curve analysis. The autophagy signature-based IDH1 mutation and grade nomogram refined glioma classification for a more individualized and clinically applicable survival estimation and inspired potential autophagy-related therapies.

RND2 attenuates apoptosis and autophagy in glioblastoma cells by targeting the p38 MAPK signalling pathway

BACKGROUND

Inhibition of p38 MAPK signalling leads to glioblastoma multiform (GBM) tumourigenesis. Nevertheless, the molecular mechanism that induces p38 MAPK signalling pathway silencing during GBM genesis has yet to be determined. Identifying new factors that can regulate p38 MAPK signalling is important for tumour treatment.

METHODS

Flow cytometry, TUNEL assays, immunofluorescence, JC-1 assays, and western blot analyses were used to detect the apoptosis of GBM cells. The specific methods used to detect autophagy levels in GBM cells were western blot analysis, LC3B protein immunofluorescence, LC3B puncta assays and transmission electron microscopy. The functions of these critical molecules were further confirmed in vivo by intracranial xenografts in nude mice. Tumour tissue samples and clinical information were used to identify the correlation between RND2 and p62 and LC3B expression, survival time of patients, and tumour volumes in clinical patients.

RESULTS

By summarizing data from the TCGA database, we found that expression of the small GTPase RND2 was significantly increased in human glioblastomas. Our study demonstrated that RND2 functions as an endogenous repressor of the p38 MAPK phosphorylation complex. RND2 physically interacted with p38 and decreased p38 phosphorylation, thereby inhibiting p38 MAPK signalling activities. The forced expression of RND2 repressed p38 MAPK signalling, which inhibited glioblastoma cell autophagy and apoptosis in vitro and induced tumour growth in the xenografted mice in vivo. By contrast, the downregulation of RND2 enhanced p38 MAPK signalling activities and promoted glioma cell autophagy and apoptosis. The inhibition of p38 phosphorylation abolished RND2 deficiency-mediated GBM cell autophagy and apoptosis. Most importantly, our study found that RND2 expression was inversely correlated with patient survival time and was positively correlated with tumour size.

CONCLUSIONS

Our findings revealed a new function for RND2 in GBM cell death and offered mechanistic insights into the inhibitory effects of RND2 with regard to the regulation of p38 MAPK activation.

Nano delivery of natural substances as prospective autophagy modulators in glioblastoma

Glioblastoma is the most destructive type of malignant brain tumor in humans due to cancer relapse. Latest studies have indicated that cancer cells are more reliant on autophagy for survival than non-cancer cells. Autophagy is entitled as programmed cell death type II and studies imply that it is a comeback of cancer cells to innumerable anti-cancer therapies. To diminish the adverse consequences of chemotherapeutics, numerous herbs of natural origin have been retained in cancer treatments. Additionally, autophagy induction occurs via their tumor suppressive actions that could cause cell senescence and increase apoptosis-independent cell death. However, most of the drugs have poor solubility and thus nano drug delivery systems possess excessive potential to improve the aqueous solubility and bioavailability of encapsulated drugs. There is a pronounced need for more therapies for glioblastoma treatment and hereby, the fundamental mechanisms of natural autophagy modulators in glioblastoma are prudently reviewed in this article.

Cathepsin B: A sellsword of cancer progression

Clinical, biochemical and molecular biology studies have identified lysosome-encapsulated cellular proteases as critical risk factors for cancer progression. Cathepsins represent a group of such proteases aimed at maintenance of cellular homeostasis. Nevertheless, recent reports suggest that Cathepsin B executes other cellular programs such as controlling tumor growth, migration, invasion, angiogenesis, and metastases development. In fact, elevated levels of Cathepsins are found under different pathological conditions including inflammation, infection, neurodegenerative disease, and cancer. Furthermore, the discovery of Cathepsin B secretion and function as an extracellular matrix protein has broadened our appreciation for the impact of Cathepsin B on cancer progression. Underneath a façade of an intracellular protease with limited therapeutic potential hides a central role of cathepsins in extracellular functions. Moreover, this role is incredibly diverse from one condition to the next - from driving caspase-dependent apoptosis to facilitating tumor neovascularization and metastasis. Here we discuss the role of Cathepsin B in the oncogenic process and perspective the use of Cathepsin B for diagnostic and therapeutic applications.

Curcumin: A naturally occurring autophagy modulator

Autophagy is a self-degradative process that plays a pivotal role in several medical conditions associated with infection, cancer, neurodegeneration, aging, and metabolic disorders. Its interplay with cancer development and treatment resistance is complicated and paramount for drug design since an autophagic response can lead to tumor suppression by enhancing cellular integrity and tumorigenesis by improving tumor cell survival. In addition, autophagy denotes the cellular ability of adapting to stress though it may end up in apoptosis activation when cells are exposed to a very powerful stress. Induction of autophagy is a therapeutic option in cancer and many anticancer drugs have been developed to this aim. Curcumin as a hydrophobic polyphenol compound extracted from the known spice turmeric has different pharmacological effects in both in vitro and in vivo models. Many reports exist reporting that curcumin is capable of triggering autophagy in several cancer cells. In this review, we will focus on how curcumin can target autophagy in different cellular settings that may extend our understanding of new pharmacological agents to overcome relevant diseases.