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Manea, A.J.; Ray, S.K. Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme. Encyclopedia. Available online: https://encyclopedia.pub/entry/42826 (accessed on 18 June 2024).
Manea AJ, Ray SK. Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme. Encyclopedia. Available at: https://encyclopedia.pub/entry/42826. Accessed June 18, 2024.
Manea, Amanda J., Swapan K. Ray. "Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme" Encyclopedia, https://encyclopedia.pub/entry/42826 (accessed June 18, 2024).
Manea, A.J., & Ray, S.K. (2023, April 05). Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme. In Encyclopedia. https://encyclopedia.pub/entry/42826
Manea, Amanda J. and Swapan K. Ray. "Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme." Encyclopedia. Web. 05 April, 2023.
Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme
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As the most malignant primary brain tumor in adults, a diagnosis of glioblastoma multiforme (GBM) continues to carry a poor prognosis. GBM is characterized by cytoprotective homeostatic processes such as the activation of autophagy, capability to confer therapeutic resistance, evasion of apoptosis, and survival strategy even in the hypoxic and nutrient-deprived tumor microenvironment. The gold standard of therapy, which involves radiotherapy and concomitant and adjuvant chemotherapy with temozolomide (TMZ), has been a game-changer for patients with GBM, relatively improving both overall survival (OS) and progression-free survival (PFS); however, TMZ is now well-known to upregulate undesirable cytoprotective autophagy, limiting its therapeutic efficacy for induction of apoptosis in GBM cells. The identification of targets utilizing bioinformatics-driven approaches, advancement of modern molecular biology technologies such as clustered regularly interspaced short palindromic repeats (CRISPR)—CRISPR-associated protein (Cas9) or CRISPR-Cas9 genome editing, and usage of microRNA (miRNA)-mediated regulation of gene expression led to the selection of many novel targets for new therapeutic development and the creation of promising combination therapies.

autophagy inhibition bioinformatics analysis CRISPR-Cas9 gene editing glioblastoma multiforme microRNAs

1. Introduction

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor, with a median patient survival of less than 15 months from the time of diagnosis [1]. Classified as a Grade IV neoplasm by the World Health Organization (WHO), GBM is histologically characterized by elevated levels of mitotic activity, loss of common morphological characteristics of mature cells, cellular pleomorphism, abnormal appearance of nuclei, coagulation necrosis, and high vascular proliferation combined with intra-tumoral and inter-tumoral heterogeneity [2]. The WHO classification of GBM provides guidelines for improving its diagnosis and prognosis. There are two main types of GBM—primary and secondary—and the diverging factors that influence the progression of each type include the genotypic status of the tumor, patient age of onset, and history of previous lower-grade diffuse glioma. Primary GBM constitutes around 90% of all cases, it is prevalent in adults aged 55 years and up, and it demonstrates higher malignancy, isocitrate dehydrogenase 1 (IDH1) wild-type status, and poorer clinical outcomes, as median overall survival is around 1.1 years as opposed to 3.8 years for tumors with mutant IDH1 [3].

The existing treatment regimen for GBM continues to be the one developed by Stupp and colleagues in 2005 and is currently the gold standard of therapy [5]. Following maximum surgical resection, radiotherapy and concomitant and adjuvant temozolomide (TMZ) administration are utilized to combat the growth of GBM in adults who are otherwise in good general health and are less than 70 years of age [4]. TMZ is an orally administered alkylating agent that has been proven to mitigate the progression of various solid tumors, including GBM.

Although TMZ is highly effective in some GBM patients, the O6-methylguanine-DNA methyltransferase (MGMT) gene encodes an enzyme that readily repairs O6-methylguanine (O6-MeG) lesions in the DNA by removing the TMZ-mediated alkyl groups, and MGMT is expressed in around 55% of the patients [5]. Expression of this gene drives a resistant phenotype that often results in treatment failure and worse survival, as shown in clinical trials involving elderly patients in Sweden and Germany [6][7].

Autophagy is a cellular homeostatic process that involves the degradation and recycling of intracellular components, such as faulty proteins and organelles, via the use of lysosomes, generating cellular building blocks that can then be recycled in metabolic and biosynthetic pathways. Although present in all cells at basal levels, autophagy is commonly upregulated in the context of cancer to mitigate the effects of stressors such as nutrient deprivation, hypoxia, accumulation of reactive oxygen species (ROS), and cellular damage due to chemotherapy [8].

Dysregulation of this homeostatic process, especially in the context of cancer, gives autophagy the potential to influence invasiveness, motility, chemoresistance, and maintenance of GBM stem cells (GSCs). Unfortunately, even though TMZ can drive the induction of apoptosis through its ability to produce O6-MeG lesions in genomic DNA, TMZ also promotes the induction of cytoprotective autophagy, that, in turn, limits its therapeutic effects.

Current avenues of investigation include the identification of novel biomarkers to detect levels of autophagy, genome editing with advanced technology such as the clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas) or CRISPR-Cas9 system to mitigate chemotherapeutic resistance, the use of targeted microRNA (miRNA) to turn off genes that promote autophagy [9][10].

2. Autophagy over the Course of GBM Progression

Autophagy comes in three forms based on how intracellular components are delivered to the autolysosome for their degradation: macroautophagy, microautophagy, and chaperone-mediated autophagy (CMA) [11]. The most thoroughly investigated form is macroautophagy, which is characterized by the de novo formation of a double-membraned vesicle known as an autophagosome that sequesters cargo such as organelles, protein aggregates, and other soluble proteins. Fusion of the autophagosome with the lysosome results in the formation of an autolysosome for degradation of the cargo via lysosomal acid hydrolases [12]. The overall process of autophagy can be broken down into a series of five main steps that include (i) initiation, (ii) nucleation, (iii) elongation, (iv) maturation, and (v) fusion, and it is regulated by over thirty autophagy-related genes (ATG) [8][10].

The removal of ROS and retrotransposons (the mobile genetic elements known to spread via reverse transcription of RNA intermediates), degradation of abnormal micronuclei and toxic unfolded proteins, and promotion of anti-cancer immunosurveillance all underly the oncosuppressive action of autophagy in initial stages of cancer development [13][14][15][16].

Suppression of autophagy in the initial stages of tumor development may be correlated with oncogenesis; however, it is now clear that autophagy is activated aggressively as a cytoprotective mechanism in the advanced stages of tumor progression, as it is constitutively upregulated in many cancer types, including GBM [8][17][18][19][20]. The recycling of the damaged and dysfunctional intracellular components via autophagy can enable cancer cells to survive in the face of hypoxia, nutrient deprivation, and exposure to toxic therapeutics, maintain the GSCs and promote metastatic potential and invasiveness [21][22][23][24].

The upregulation of autophagy in tumor cells in response to hypoxia is highly evident by an increased number of autophagosomes that are localized in the hypoxic areas of the TME [14]. In addition, a relationship has been found between the upregulation of a downstream regulator of hypoxia-inducible factor 1-alpha (HIF1-α) known as the Bcl-2/adenovirus E1B 19 kDa interacting protein 3 (BNIP3) and increased turnover of p62, indicating that hypoxia increases autophagic flux (amount of autophagic degradation activity) in GBM [25]. Similarly, the upregulation of autophagy plays a key role in maintaining optimal bioenergetics even in an environment characterized by nutrient depletion. Autophagy can degrade organelle membranes and lipid droplets to generate lipids, proteins to generate amino acids, and sugars through complex carbohydrate degradation to create a huge pool of building blocks that can then be fed into the tricarboxylic acid (TCA) cycle to sustain mitochondrial metabolism [14].

Moreover, tumor cells often modify mitochondrial dynamics to meet cellular energy needs, either utilizing fusion or fission of mitochondria to increase utilization of the electron transport chain or reduce oxidative capacity, respectively [26]. Mitochondrial fission is common in GBM, and the facilitation of a high turnover of mitochondria via mitophagy plays a critical role in the maintenance of the cancer stem cell phenotype [27][28]

Autophagy plays a dual role in tumor progression that has changed the way it has been characterized over time, but at this moment, there is more evidence showing that autophagy potentiates cancer progression rather than its suppression, indicating that autophagy is detrimental in progressive cancers. As such, targeting autophagy is a potential therapeutic option to mitigate GBM progression, invasion, and recurrence.

3. Bioinformatics Analysis for Identification of Biomarkers of Autophagy in GBM

A statistical analysis of large genomic and proteomic datasets has led to the creation of various nomograms (diagrams representing relations among various key parameters) and protein-protein interaction (PPI) networks that can be used to determine how variations in specific autophagy-related genes (ARGs) can affect prognosis and drive individualized treatments [29][30][31]. Utilizing data from the Cancer Genome Atlas (TCGA), Kondapuram and Coumar have conducted a pan-cancer gene expression analysis, determining which ARGs are commonly upregulated or down regulated across 21 different cancers [29]. Focusing on the ARG expression analysis on GBM yielded two genes that have significant effects on overall survival (OS) in GBM: integrin subunit beta 1 (ITGB1) and BIRC5, as mentioned above. The ITGB1 gene was found to map to the phagosome pathway, specifically the PI3K/Akt/mTOR axis, and be involved in autophagosome formation. Using this information, three drugs were identified to target commonly dysregulated ARGs and suggested for GBM therapy: panabinostat, vorinostat, and abexinostat [29].

Wang and colleagues found cohorts of GBM patients with lower expression of integrin subunit alpha 3 (ITGA3), neuregulin 1 (NRG1), and microtubule-associated protein 1 light chain 3 alpha (MAP1LC3A) to have a significantly better prognosis. Utilizing these three targets, a risk score model was created where patients were divided into low-risk and high-risk groups using the median risk score as a cutoff [30]. Patients that were in the high-risk group had a one-year OS of 39.5%, while those in the low-risk group had an OS of 73.4%, showing that these might be viable targets for therapy. The nomogram was verified using data from the Chinese Glioma Genome Atlas (CGGA) and achieved AUC (area under the receiver operating characteristic curve) values of 0.76, 0.72, and 0.69 for 0.5-, 1-, and 2-year OS rates, respectively.

Another nomogram that achieved relatively high AUC values for 1-, 3-, and 5-year OS for GBM was developed using the TCGA, REMBRANDT (an acronym for: REpository for Molecular BRAin Neoplasia DaTa), and Gravendeel datasets. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression yielded four ARGs that were identified as either risk factors or protective factors. With a hazard ratio (HR) greater than one, Di-Ras (DIRAS) family GTPase 3 (DIRAS3) and galectin-8 (LGALS8) are known to promote autophagy either through the EGFR/Akt axis or through mTOR inhibition, respectively [31].

Additional genomic analysis has focused on the relationship among ARG expression, immune infiltration, and alternative splicing (AS) [32][33]. Analysis of AS in 134 GBM patients utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that autophagy is the most enriched process of prognostic AS in GBM. Spliced core genes identified following univariate and multivariate Cox regression of the TCGA data included ubiquitin C (UBC), von Hippel-Lindau tumor suppressor (VHL), potassium channel tetramerization domain containing 7 (KCTD7), f-box and leucine-rich repeat protein 19 (FBXL19), ring finger protein 7 (RNF7), and ubiquitin-conjugating enzyme E2 N (UBE2N).

Biomedical informatics, growing genomic databases, novel methods for proteomic analysis, and identification of key miRNAs and lncRNAs in GBM provide some unparalleled opportunities for selecting targets that can curb the progression of GBM. However, certain limitations continue to exist for the development of nomograms that may potentially be used to identify key ARGs and pharmaceutical interventions that target these ARGs.

4. Gene Editing Technology for Targeting Cytoprotective Autophagy in GBM

The creation of modular DNA recognition proteins utilizing the zinc ion-regulated small protein motifs and the nuclease domain of the Fok1 restriction nuclease, leading to what would be called zinc finger nucleases (ZFNs), represented a major advancement in the field of gene editing; however, validation and protein design proved to be barriers to the widespread use of ZFNs [34]. Similarly, although transcription activator-like (TAL) effector nucleases (TALENs) were even more efficient than ZFNs to produce, challenges with protein design and synthesis persisted [35].

The DNA sequence of CRISPR was first characterized in 1987 by Ishino and colleagues when examining the genome of Escherichia coli [36]. Subsequent investigation revealed the importance of CRISPR-associated (Cas) genes that encode proteins with nuclease and helicase domains, mature CRISPR RNAs (crRNAs) that can guide the formation of complex Cas proteins, and trans-activating crRNA (tracrRNA) for crRNA maturation. Major applications of CRISPR-Cas9 technology include the reproduction of tumor-associated chromosomal translocations and the creation of more accurate disease models, systemic analyses of gene function, and correction of genetic mutations.

4.1. CRISPR-Cas9 Technology for Targeting Molecular Components of Autophagy

As an effective method of identifying the action of individual genes, CRISPR-Cas9 technology has been employed for creating knockouts (KOs) of various ARGs that regulate canonical autophagy pathways and organelle-specific forms of autophagy [37][38]. ARGs involved in canonical autophagy pathways that have undergone KO include ATG7, which is integral for autophagosome formation, leading to a blockage of basal and starvation-induced autophagic flux and substantially greater cell death in the immortalized human embryonic kidney cell line HEK293T [37][39]

Determining the role of key ARGs in organelle-specific autophagy, such as mitophagy and ER-phagy, has led to fervent investigation and elucidation of novel pathways. The ATG8 protein family consists of two subdivisions: LC3 and gamma-aminobutyric acid (GABA) type A receptor-associated protein (GABARAP). Known to be an integral component in autophagosome expansion and closure, as well as in sequestration of selective cargo, their relationship with the phosphatase and tensin homolog (PTEN) induced kinase 1 (PINK1)/Parkinson disease 2 (PARK2)-dependent mitophagy was explored. Utilizing CRISPR-Cas9, KO of LC3 and GABARAP subfamilies and an additional six ATG8 family proteins in HeLa cells led to the failure of autophagosome-lysosome fusion but did not lead to complete prevention of autophagosome closure or selective sequestration of mitochondria. Additional interrogation revealed that GABARAPs recruited the pleckstrin homology and RUN domain containing M1 (PLEKHM1) for autophagosome-lysosome fusion, providing novel insight into the mechanics of PINK1/PARK2-dependent mitophagy [40]. Moreover, Wang and colleagues found that even in the ATG7 KO chronic myelogenous leukemia K562 cells, mitophagy continued to be activated due to the action of the Ras-related protein Rab-9A (RAB9A) and that KO of RAB9A inhibited mitophagy, increased ROS and apoptosis, and reduced repair of DNA damage [41].

4.2. CRISPR-Cas9 Technology for Targeting GBM Growth and Recurrence

The application of CRISPR-Cas9 technology to target GBM growth has primarily taken place in four areas: mitigation of GSC proliferation, modulation of epigenetics, animal modeling and organoid development, and immunotherapy. A key target identified for CRISPR-Cas9 mediated KO is an enhancer that is located between the promoters of the marker of proliferation Ki67 (MKI67) and MGMT genes. By preventing epigenetic regulation of the enhancer region in cell lines with high MGMT expression, TMZ sensitivity was restored, impairing the proliferation of GBM12 cells [42]

One exciting result from the CRISPR-Cas9 gene editing was that the KO of the signal transducer and activator of transcription 3 (STAT3) led to significant inhibition of GBM proliferation, preferentially targeting GSCs when the gene editing technology was delivered via intracranial injection [43]. STAT3 has already been shown to be an upstream inhibitor of autophagy through multiple axes, the most well-established being the upregulation of hypoxia-inducible factor-1 alpha (HIF-1α), followed by an increase in the association of Bcl-2 and Beclin 1, resulting in down-regulation of autophagy [44][45]. Differential effects of autophagy upregulation and down regulation in GSCs as opposed to other GBM cells can potentially explain how KO of STAT3 may be beneficial in the context of GSCs. Another gene, which was identified through the CRISPR-Cas9 screening to be expressed in a manner that implied an ‘addiction’ in GSCs when compared to neural stem cells (NSCs), was WEE1 (a protein kinase for regulating the G2 checkpoint in the cell cycle in response to DNA damage)-like kinase (PKMYT1) that was essential for mitosis. In neural stem cells (NSCs), redundancy with WEE1 prevents inhibition of mitosis following KO of PKMYT1; however, overexpression of EGFR and Akt1 overcomes redundancy [46]. WEE1 has also been recently analyzed with respect to autophagy in GBM, and the lncRNA LINC00470 has been found to competitively bind to miR-580-3p in the presence of WEE1, leading to autophagy inhibition via activation of the PI3K/Akt/mTOR pathway [47]. Stem cell-specific models have also been developed using the CRISPR-Cas9 technology. Combination of the RCAS-TVA (replication-competent avian sarcoma-leukosis virus long-terminal repeat with splice acceptor (RCAS) vectors targeting the tumor virus A (TVA) receptor) method with the CRISPR-Cas9 gene editing technology enabled KO of p53, CDKN2A, and PTEN in NSCs, resulting in the formation of high-grade glioma [48]. Essentially, the CRISPR-Cas9 gene editing technology is an efficient method to screen many genes to determine what differentials may exist between GSCs and other GBM cells, as well as create representative models of GSCs to understand the intricacies of tumorigenesis.

Modeling GBM in vivo and through organoids has been another area of application of CRISPR-Cas9 gene editing technology to better understand the pathogenesis of GBM, investigate loss-of-function (LOF) mutations of tumor suppressors, engineer oncogene constructs, and improve target identification [49][50]. In the case of the animal model, Zuckermann and colleagues were able to induce the formation of GBM through the KO of p53, PTEN, and neurofibromatosis type 1 (NF1) [51]. Using electroporation into the ventricular zone, about 6-14 weeks after the delivery, they observed histological features that matched those of GBM [51]

Targeted immunotherapy in GBM has been another area in which CRISPR-Cas9 gene editing technology has been employed to reduce sensitivity to immunosuppression and improve anti-tumor T cell activity. Autophagy can increase resistance to anti-cancer immunity, so the identification of novel targets for the potentiation of immunotherapy may mitigate the effects of cytoprotective autophagy [52].

5. miRNAs and Inhibition of Autophagy for Potentiation of TMZ Efficacy in GBM

Following their discovery in 1993, the role of non-coding RNAs (ncRNAs) in the regulation of gene expression has opened new doors for the diagnosis of disease, prediction of patient prognosis, and the manipulation of their activity for therapeutic intervention [53]. Small ncRNAs termed miRNAs were first described in the context of cancer in 2002, with certain miRNAs being differentially downregulated in B-cell chronic lymphocyte leukemia (B-CLL) [54]. Since then, an intensive investigation has led to the characterization of key miRNAs and their action within a variety of pathways integral to cancer progression, radio-resistance and chemo-resistance [55].

Frequently, miRNA targets are chosen following quantitative polymerase chain reaction (qPCR), miRNA microarray, or bioinformatics-driven analysis where correlations are drawn between levels of a particular miRNA and either improved or worsened prognosis for GBM patients. An example is miR-517c, a member of the C19MC RNA cluster that has been shown to be positively correlated with improved prognosis in GBM patients [56]. The proposed mechanism of action is the miR-517c/karyopherin alpha 2 (KPNA2, RAG cohort 1, or importin alpha 1)/cytoplasmic p53 axis, where miR-517c degrades KPNA2, negatively impacting the nuclear translocation of p53, leading to the inhibition of autophagy in U87MG cells harboring wild-type p53. In the context of combination treatment with TMZ, inhibition of autophagy by miR-517c was correlated with reduced migration and infiltration, as well as an increased expression of epithelial markers and inhibition of endothelial-to-mesenchymal transition (EMT) [56].

Other groups found that overexpression of miRNA-30a and miRNA-17 led to the inhibition of autophagy and increased TMZ sensitivity in GBM [57][58]. The observation that TMZ treatment leads to a reduction of miRNA-30a levels in a dose-dependent manner has led investigators to explore the effects of overexpression of miRNA-30a, finding that miRNA-30a directly acts upon Beclin 1 and thus is an inhibitor of cytoprotective autophagy [58]. Moreover, evidence that miRNA-17 inhibits ATG7, an integral protein in autophagosome formation, motivated the investigators to transfect the miRNA into human GBM T98G cells and yield increased TMZ sensitivity [57]. In addition, overexpression of yet another miRNA, miR-7-1-3p, in concert with flavonoid combination therapy employing luteolin (LUT) and silibinin (SIL), led to autophagy inhibition in rapamycin (an mTOR inhibitor and promoter of autophagy) pre-treated U87MG and T98G tumors in vivo [59].

A relationship between an increase in levels of HIF-1α and a decrease in levels of miR-224-3p led to the elucidation of the negative regulation of ATG5 due to the action of miR-224-3p [60]. As such, overexpression of miR-224-3p led to inhibition of autophagy, decreased cell mobility, and increased chemosensitivity of GBM cells to TMZ in hypoxic conditions [60]. Hypoxia has also been shown to induce the expression of interleukin-6 (IL-6), which has been correlated with a poor prognosis in GBM. Utilizing a pathway that involves miR-155-3p, IL-6 promotes autophagy, fueling the progression of GBM [61]. Specifically, the mechanism of action involves a hypoxia-induced IL-6/pSTAT3/miR-155-3p/cAMP responsive element binding protein 3 (CREB3)/ATG5 axis. Reduction in miR-155-3p led to inhibition of IL-6-induced cytoprotective autophagy and blockage of the IL-6 receptor; using tocilizumab in combination with TMZ showed drug synergism and elevated induction of apoptosis in human GBM U251 and T98G cell lines [61].

6. Future Directions

GBM continues to be a highly deadly malignancy with a dismal prognosis even today. The discovery that concomitant and adjuvant administration of TMZ with radiotherapy could lead to significant regression of the disease and improvements in overall survival (OS) and progression-free survival (PFS) was a major advancement in GBM therapy [62]. However, several limitations still exist, as lack of MGMT promoter methylation renders TMZ largely ineffective, and the activation of cytoprotective autophagy in response to TMZ administration can power GBM chemotherapy resistance and tumor recurrence over time [5][8].

To identify novel targets for the regulation of autophagy and mitigation of GBM progression, various advanced bioinformatics-driven approaches have been employed in recent years. Utilizing public genomic databases such as the TCGA, REMBRANDT, Gravendeel, KEGG, and CGGA, univariate and multivariate Cox regression and LASSO regression have been applied to both identify therapeutic targets and create predictive nomograms  [30][31]. Used in conjunction with bioinformatics-driven approaches, CRISPR-Cas9 gene editing technology can knockout or knock-in genes of interest to inhibit autophagy, GSC proliferation and mitigate immunosuppression. Various targets have been exploited in both the contexts of autophagy and GBM; however, an investigation into the modification of ARGs for GBM therapy, specifically in conjunction with TMZ combination therapy, is still limited [13]. Exploiting miRNAs can also lead to broad changes in protein expression and inhibition of cytoprotective autophagy in the context of combination therapy with TMZ in GBM. Identification of miRNA targets utilizing qPCR, miRNA microarrays, and bioinformatics-driven analysis has led to either their overexpression or knockdown to inhibit autophagy, synergize with TMZ, and induce apoptosis in GBM cell lines [57][58][60].

GBM is a complex disease characterized by inter-tumoral and intra-tumoral heterogeneity, recurrence, and poor prognosis; however, many new advancements in both the identification of targets and development of novel genetic therapeutic strategies may lead to another breakthrough therapy that can supplement the current Stupp protocol to give GBM patients a new fighting chance.

References

  1. Zygogianni, A.; Protopapa, M.; Kougioumtzopoulou, A.; Simopoulou, F.; Nikoloudi, S.; Kouloulias, V. From imaging to biology of glioblastoma: New clinical oncology perspectives to the problem of local recurrence. Clin. Transl. Oncol. 2018, 20, 989–1003.
  2. Abdullah, K.G.; Adamson, C.; Brem, S. The Molecular Pathogenesis of Glioblastoma. In Glioblastoma, 1st ed.; Brem, S., Abdullah, K.G., Eds.; Elsevier, Inc.: Amsterdam, The Netherlands, 2016; pp. 21–31.
  3. Parsons, D.W.; Jones, S.; Zhang, X.; Lin, J.C.-H.; Leary, R.J.; Angenendt, P.; Mankoo, R.; Carter, H.; Siu, I.-M.; Gallia, G.L.; et al. An Integrated Genomic Analysis of Human Glioblastoma Multiforme. Science 2008, 321, 1807.
  4. Weller, M.; van den Bent, M.; Preusser, M.; Le Rhun, E.; Tonn, J.C.; Minniti, G.; Bendszuz, M.; Balana, C.; Chinot, O.; Dirven, L.; et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat. Rev. Clin. Oncol. 2021, 18, 170–186.
  5. Hegi, M.E.; Diserens, A.-C.; Gorlia, T.; Harnou, M.-F.; de Tribolet, N.; Weller, M.; Kros, J.M.; Hainfellner, J.A.; Mason, W.; Mariani, L.; et al. MGMT Gene Silencing and Benefit from Temozolomide in Glioblastoma. N. Engl. J. Med. 2005, 352, 997–1003.
  6. Malmstrom, A.; Gronberg, B.H.; Marosi, C.; Stupp, R.; Frappaz, D.; Schultz, H.; Abacioglu, U.; Tavelin, B.; Lhermitte, B.; Hegi, M.E.; et al. Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: The Nordic randomised, phase 3 trial. Lancet Oncol. 2012, 13, 916–926.
  7. Wick, W.; Platten, M.; Meisner, C.; Felsberg, J.; Tabatabai, G.; Simon, M.; Nikkhah, G.; Papsdorf, K.; Steinbach, J.P.; Sable, M.; et al. Temozolomide chemotherapy alone versus radiotherapy alone for malignant astrocytoma in the elderly: The NOA-08 randomised, phase 3 trial. Lancet Oncol. 2012, 13, 707–715.
  8. Kimmelman, A.C.; White, E. Autophagy and Tumor Metabolism. Cell Metab. 2017, 25, 1037–1043.
  9. Al-Sammarraie, N.; Ray, S.K. Application of CRISPR-Cas9 Technology to Genome Editing in Glioblastoma Multiforme. Cells 2021, 10, 2342.
  10. Manea, A.J.; Ray, S.K. Regulation of autophagy as a therapeutic option in glioblastoma. Apoptosis 2021, 26, 574–599.
  11. Martinez-Vicente, M.; Cuervo, A.M. Autophagy and neurodegeneration: When the cleaning crew goes on strike. Lancet Neurol. 2007, 6, 352–361.
  12. Bejarano, E.; Cuervo, A.M. Chaperone-Mediated Autophagy. Proc. Am. Thorac. Soc. 2010, 7, 29–39.
  13. Morselli, E.; Galluzzi, L.; Kepp, O.; Marino, G.; Michaud, M.; Vitale, I.; Maiuri, M.C.; Kroemer, G. Oncosuppressive functions of autophagy. Antioxid. Redox Signal. 2011, 14, 2251–2269.
  14. White, E. Deconvoluting the context-dependent role for autophagy in cancer. Nat. Rev. Cancer 2012, 12, 401–410.
  15. Ma, Y.; Galluzzi, L.; Zitvogel, L.; Kroemer, G. Autophagy and cellular immune response. Immunity 2013, 39, 211–227.
  16. Galluzzi, L.; Pietrocola, F.; Bravo-San Pedro, J.M.; Amaravadi, R.; Baehrecke, E.H.; Cecconi, F.; Codogno, P.; Debnath, J.; Gewirtz, D.A.; Karantza, V.; et al. Autophagy in malignant transformation and cancer progression. EMBO J. 2015, 34, 856–880.
  17. Yang, Z.J.; Chee, C.E.; Huang, S.; Sinicrope, F.A. The Role of Autophagy in Cancer: Therapeutic Implications. Mol. Cancer Ther. 2011, 10, 1533–1541.
  18. Gammoh, N.; Fraser, J.; Puente, C.; Syred, H.M.; Kang, H.; Ozawa, T.; Lam, D.; Acosta, J.C.; Finch, A.J.; Holland, E.; et al. Suppression of autophagy impedes glioblastoma development and induces senescence. Autophagy 2016, 12, 1431–1439.
  19. Padmakrishnan, C.J.; Easwer, H.V.; Vijayakurup, V.; Menon, G.V.; Nair, S.; Gopala, S. High LC3/Beclin Expression Correlates with Poor Survival in Glioma: A Definitive Role for Autophagy as Evidenced by In Vitro Autophagic Flux. Pathol. Oncol. Res. 2017, 25, 137–148.
  20. Simpson, J.E.; Gammoh, N. The impact of autophagy during the development and survival of glioblastoma. Open Biol. 2020, 10, 200184.
  21. Galavotti, S.; Bartesaghi, S.; Faccenda, D.; Shaked-Rabi, M.; Sanzone, S.; McEvoy, A.; Dinsdale, D.; Condorelli, F.; Brandner, S.; Campanella, M.; et al. The autophagy-associated factors DRAM1 and p62 regulate cell migration and invasion in glioblastoma stem cells. Oncogene 2012, 32, 699–712.
  22. Hou, J.; Han, Z.-P.; Jing, Y.-Y.; Yang, X.; Zhang, S.-S.; Sun, K.; Hao, C.; Meng, Y.; Yu, F.-H.; Liu, X.-Q.; et al. Autophagy prevents irradiation injury and maintains stemness through decreasing ROS generation in mesenchymal stem cells. Cell Death Dis. 2013, 4, e844.
  23. Garcia-Prat, L.; Martinez-Vincente, M.; Periguero, E.; Ortet, L.; Rodriguez-Ubreva, J.; Rebollo, E.; Ruiz-bonilla, V.; Gutarra, S.; Ballestar, E.; Serrano, A.L.; et al. Autophagy maintains stemness by preventing senescence. Nature 2016, 529, 37–42.
  24. Dolma, S.; Selvadurai, H.J.; Lan, X.; Lee, L.; Kushida, M.; Voisin, V.; Whetstone, H.; So, M.; Aviv, T.; Park, N.; et al. Inhibition of Dopamine Receptor D4 Impedes Autophagic Flux, Proliferation, and Survival of Glioblastoma Stem Cells. Cancer Cell 2016, 29, 859–873.
  25. Mahase, S.; Rattenni, R.N.; Wesseling, P.; Leenders, W.; Baldotto, C.; Jain, R.; Zagzag, D. Hypoxia-Mediated Mechanisms Associated with Antiangiogenic Treatment Resistance in Glioblastomas. Am. J. Pathol. 2017, 187, 940–953.
  26. Yang, K.; Niu, L.; Bai, Y.; Le, W. Glioblastoma: Targeting the autophagy in tumorigenesis. Brain Res. Bull. 2019, 153, 334–440.
  27. Skoda, J.; Borankova, K.; Jansson, P.J.; Huang, M.L.-H.; Veselska, R.; Richardson, D.R. Pharmacological targeting of mitochondria in cancer stem cells: An ancient organelle at the crossroad of novel anti-cancer therapies. Pharmacol. Res. 2019, 139, 298–313.
  28. Rodrigues, T.; Ferraz, L.S. Therapeutic potential of targeting mitochondrial dynamics in cancer. Biochem. Pharmacol. 2020, 182, 114282.
  29. Kondapuram, S.K.; Coumar, M.S. Pan-cancer gene expression analysis: Identification of deregulated autophagy genes and drugs to target them. Gene 2022, 844, 146821.
  30. Wang, Z.; Gao, L.; Guo, X.; Feng, C.; Lian, W.; Deng, K.; Xing, B. Development and validation of a nomogram with an autophagy-related gene signature for predicting survival in patients with glioblastoma. Aging 2019, 11, 12246–12269.
  31. Wang, Y.; Zhao, W.; Xiao, Z.; Guan, G.; Liu, X.; Zhuang, M. A risk signature with four autophagy-related genes for predicting survival of glioblastoma multiforme. J. Cell. Mol. Med. 2020, 24, 3807–3821.
  32. Xie, Z.-C.; Wu, H.-Y.; Dang, Y.-W.; Chen, G. Role of alternative splicing signatures in the prognosis of glioblastoma. Cancer Med. 2019, 8, 7623–7636.
  33. Wang, D.; Jiang, Y.; Wang, T.; Wang, Z.; Zou, F. Identification of a novel autophagy-related prognostic signature and small molecule drugs for glioblastoma by bioinformatics. BMC Med. Genom. 2022, 15, 111.
  34. Adli, M. The CRISPR tool kit for genome editing and beyond. Nat. Commun. 2018, 9, 1911.
  35. Doudna, J.A.; Charpentier, E. The new frontier of genome engineering with CRISPR-Cas9. Science 2014, 346, 1258096.
  36. Ishino, Y.; Shinagawa, H.; Makino, K.; Amemura, M.; Nakata, A. Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. J. Bacteriol. 1987, 169, 5429–5433.
  37. Cui, J.; Chew, S.J.L.; Shi, Y.; Gong, Z.; Shen, H.-M. CRISPR system for genome engineering: The application for autophagy study. BMB Rep. 2017, 50, 247–256.
  38. Liang, J.R.; Corn, J.E. A CRISPR view on autophagy. Trends Cell Biol. 2022, 32, 1008–1022.
  39. Hou, W.; Xie, Y.; Song, X.; Sun, X.; Lotze, M.T.; Zeh, H.J., 3rd; Kang, R.; Tang, D. Autophagy promotes ferroptosis by degradation of ferritin. Autophagy 2016, 12, 1425–1428.
  40. Padman, B.S.; Nguyen, T.N.; Lazarou, M. Autophagosome formation and cargo sequestration in the absence of LC3/GABARAPs. Autophagy 2016, 13, 772–774.
  41. Wang, J.; Fang, Y.; Yan, L.; Yuan, N.; Zhang, S.; Xu, L.; Nie, M.; Zhang, X.; Wang, J. Erythroleukemia cells acquire an alternative mitophagy capability. Sci. Rep. 2016, 6, 24641.
  42. Ganguly, D.; Fan, M.; Yang, C.H.; Zbytek, B.; Finkelstein, D.; Roussel, M.F.; Pfeffer, L.M. The critical role that STAT3 plays in glioma-initiating cells: STAT3 addiction in glioma. Oncotarget 2018, 9, 22095–22112.
  43. Yuan, G.; Yan, S.-F.; Xue, H.; Zhang, P.; Sun, J.-T.; Li, G. Cucurbitacin I Induces Protective Autophagy in Glioblastoma in Vitro and in Vivo. Signal Transduct. 2014, 285, P10607–P10619.
  44. Yuan, S.; Yan, Q.; Zhao, Z.-Y.; Zhang, J.-L.; Zhang, H.; Hang, Y.; Yuan, Z. STAT3-mediated upregulation of LINC00520 contributed to temozolomide chemoresistance in glioblastoma by interacting with RNA-binding protein LIN28B. Cancer Cell Int. 2022, 22, 248.
  45. Liang, J.R.; Lingeman, E.; Luong, T.; Ahmed, S.; Muhar, M.; Nguyen, T.; Olzmann, J.A.; Corn, J.E. A Genome-wide ER-phagy Screen Highlights Key Roles of Mitochondrial Metabolism and ER-Resident UFMylation. Cell 2020, 180, 1160–1177.
  46. Toledo, C.M.; Ding, Y.; Hoellerbauer, P.; Davis, R.J.; Basom, R.; Girard, E.J.; Lee, E.; Corrin, P.; Hart, T.; Bolouri, H.; et al. Genome-wide CRISPR-Cas9 Screens Reveal Loss of Redundancy between PKMYT1 and WEE1 in Glioblastoma Stem-like Cells. Cell Rep. 2015, 13, 2425–2439.
  47. Ma, W.; Zhou, Y.; Liu, M.; Qin, Q.; Cui, Y. Long non-coding RNA LINC00470 in serum derived exosome: A critical regulator for proliferation and autophagy in glioma cells. Cancer Cell Int. 2021, 21, 149.
  48. Oldrini, B.; Curiel-Garcia, A.; Marques, C.; Matia, V.; Uluckan, O.; Grana-Castro, O.; Torres-Ruiz, R.; Rodriguez-Perales, S.; Huse, J.T.; Squatrito, M. Somatic genome editing with the RCAS-TVA-CRISPR-Cas9 system for precision tumor modeling. Nat. Commun. 2018, 9, 1466.
  49. Cai, X.; Sughrue, M.E. Glioblastoma: New therapeutic strategies to address cellular and genomic complexity. Oncotarget 2017, 9, 9540–9554.
  50. Robertson, F.L.; Marques-Torrejon, M.-A.; Morrison, G.M.; Pollar, S.M. Experimental models and tools to tackle glioblastoma. Dis. Model Mech. 2019, 12, dmm040386.
  51. Zuckermann, M.; Hovestadt, V.; Knobbe-Thomsen, C.B.; Zapatka, T.; Northcott, P.A.; Schramm, K.; Belic, J.; Jones, D.T.W.; Tschida, B.; Moriarity, B.; et al. Somatic CRISPR/Cas9-mediated tumour suppressor disruption enables versatile brain tumour modelling. Nat. Commun. 2015, 6, 7391.
  52. Li, Y.-Y.; Feun, L.G.; Thongkum, A.; Tu, C.-H.; Chen, S.-M.; Wangpaichitr, M.; Wu, C.; Kuo, M.T.; Savaraj, N. Autophagic Mechanism in Anti-Cancer Immunity: Its Pros and Cons for Cancer Therapy. Int. J. Mol. Sci. 2017, 18, 1297.
  53. O’Brien, J.; Hayder, H.; Zayed, Y.; Peng, C. Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation. Front. Endocinol. 2018, 9, 402.
  54. Calin, G.A.; Dumitru, C.D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; et al. Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 2002, 99, 15524–15529.
  55. Sufianov, A.; Begliarzade, S.; Ilyasova, T.; Liang, Y.; Beylerli, O. MicroRNAs as prognostic markers and therapeutic targets in gliomas. Noncoding RNA Res. 2022, 7, 171–177.
  56. Lu, Y.; Xiao, L.; Liu, Y.; Wang, H.; Li, H.; Zhou, Q.; Pan, J.; Lei, B.; Huang, A.; Qi, S. MIR517C inhibits autophagy and the epithelial-to-mesenchymal (-like) transition phenotype in human glioblastoma through KPNA2-dependent disruption of TP53 nuclear translocation. Autophagy 2015, 11, 2213–2232.
  57. Comincini, S.; Allavena, G.; Palumbo, S.; Morini, M.; Durando, F.; Angeletti, F.; Pirtoli, L.; Miracco, C. microRNA-17 regulates the expression of ATG7 and modulates the autophagy process, improving the sensitivity to temozolomide and low-dose ionizing radiation treatments in human glioblastoma cells. Cancer Biol. Ther. 2013, 14, 574–586.
  58. Xu, J.; Huang, H.; Peng, R.; Ding, X.; Jiang, B.; Yuan, X.; Xi, J. MicroRNA-30a increases the chemosensitivity of U251 glioblastoma cells to temozolomide by directly targeting beclin 1 and inhibiting autophagy. Exp. Ther. Med. 2018, 15, 4798–4804.
  59. Chakrabarti, M.; Ray, S.K. Anti-tumor activities of luteolin and silibinin in glioblastoma cells: Overexpression of miR-7-1-3p augmented luteolin and silibinin to inhibit autophagy and induce apoptosis in glioblastoma in vivo. Apoptosis 2016, 21, 312–328.
  60. Huang, S.; Qi, P.; Zheng, T.; Li, F.; He, X. The HIF-1α/miR-224-3p/ATG5 axis affects cell mobility and chemosensitivity by regulating hypoxia-induced protective autophagy in glioblastoma and astrocytoma. Oncol. Rep. 2019, 41, 1759–1768.
  61. Xue, H.; Yuan, g.; Guo, X.; Liu, Q.; Zhang, J.; Gao, X.; Guo, X.; Xu, S.; Li, T.; Shao, Q.; et al. A novel tumor-promoting mechanism of IL6 and the therapeutic efficacy of tocilizumab: Hypoxia-induced IL6 is a potent autophagy initiator in glioblastoma via the p-STAT3-MIR155-3p-CREBRF pathway. Autophagy 2016, 12, 1129–1152.
  62. Stupp, R.; Mason, W.P.; van den Bent, M.J.; Weller, M.; Fisher, B.; Taphoorn, M.J.B.; Belanger, K.; Brandes, A.A.; Marosi, C.; Bogdahn, U.; et al. Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. N. Engl. J. Med. 2005, 352, 987–996.
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