Targeting glioma-initiating cells via the tyrosine metabolic pathway

TRIM21-mediated ubiquitylation of TAT suppresses liver metastasis in gallbladder cancer

Liver metastasis is common in patients with gallbladder cancer (GBC), imposing a significant challenge in clinical management and serving as a poor prognostic indicator. However, the mechanisms underlying liver metastasis remain largely unknown. Here, we report a crucial role of tyrosine aminotransferase (TAT) in liver metastasis of GBC. TAT is frequently up-regulated in GBC tissues. Increased TAT expression is associated with frequent liver metastasis and poor prognosis of GBC patients. Overexpression of TAT promotes GBC cell migration and invasion in vitro, as well as liver metastasis in vivo. TAT knockdown has the opposite effects. Intriguingly, TAT promotes liver metastasis of GBC by potentiating cardiolipin-dependent mitophagy. Mechanistically, TAT directly binds to cardiolipin and leads to cardiolipin externalization and subsequent mitophagy. Moreover, TRIM21 (Tripartite Motif Containing 21), an E3 ubiquitin ligase, interacts with TAT. The histine residues 336 and 338 at TRIM21 are essential for this binding. TRIM21 preferentially adds the lysine 63 (K63)-linked ubiquitin chains on TAT principally at K136. TRIM21-mediated TAT ubiquitination impairs its dimerization and mitochondrial location, subsequently inhibiting tumor invasion and migration of GBC cells. Therefore, our study identifies TAT as a novel driver of GBC liver metastasis, emphasizing its potential as a therapeutic target.

Smad2/3/4 complex could undergo liquid liquid phase separation and induce apoptosis through TAT in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) represents one of the most significant causes of mortality due to cancer-related deaths. It has been previously reported that the TGF-β signaling pathway may be associated with tumor progression. However, the relationship between TGF-β signaling pathway and HCC remains to be further elucidated. The objective of our research was to investigate the impact of TGF-β signaling pathway on HCC progression as well as the potential regulatory mechanism involved.

METHODS

We conducted a series of bioinformatics analyses to screen and filter the most relevant hub genes associated with HCC. E. coli was utilized to express recombinant protein, and the Ni-NTA column was employed for purification of the target protein. Liquid liquid phase separation (LLPS) of protein in vitro, and fluorescent recovery after photobleaching (FRAP) were utilized to verify whether the target proteins had the ability to drive force LLPS. Western blot and quantitative real-time polymerase chain reaction (qPCR) were utilized to assess gene expression levels. Transcription factor binding sites of DNA were identified by chromatin immunoprecipitation (CHIP) qPCR. Flow cytometry was employed to examine cell apoptosis. Knockdown of target genes was achieved through shRNA. Cell Counting Kit-8 (CCK-8), colony formation assays, and nude mice tumor transplantation were utilized to test cell proliferation ability in vitro and in vivo.

RESULTS

We found that Smad2/3/4 complex could regulate tyrosine aminotransferase (TAT) expression, and this regulation could relate to LLPS. CHIP qPCR results showed that the key targeted DNA binding site of Smad2/3/4 complex in TAT promoter region is -1032 to -1182. In addition. CCK-8, colony formation, and nude mice tumor transplantation assays showed that Smad2/3/4 complex could repress cell proliferation through TAT. Flow cytometry assay results showed that Smad2/3/4 complex could increase the apoptosis of hepatoma cells. Western blot results showed that Smad2/3/4 complex would active caspase-9 through TAT, which uncovered the mechanism of Smad2/3/4 complex inducing hepatoma cell apoptosis.

CONCLUSION

This study proved that Smad2/3/4 complex could undergo LLPS to active TAT transcription, then active caspase-9 to induce hepatoma cell apoptosis in inhibiting HCC progress. The research further elucidate the relationship between TGF-β signaling pathway and HCC, which contributes to discover the mechanism of HCC development.

Metabolic Profiles of Cancer Stem Cells and Normal Stem Cells and Their Therapeutic Significance

Cancer stem cells (CSCs) are a rare cancer cell population, responsible for the facilitation, progression, and resistance of tumors to therapeutic interventions. This subset of cancer cells with stemness and tumorigenic properties is organized in niches within the tumor microenvironment (TME) and presents altered regulation in a variety of metabolic pathways, including glycolysis, oxidative phosphorylation (OXPHOS), as well as lipid, amino acid, and iron metabolism. CSCs exhibit similarities as well as differences when comparedto normal stem cells, but also possess the ability of metabolic plasticity. In this review, we summarize the metabolic characteristics of normal, non-cancerous stem cells and CSCs. We also highlight the significance and implications of interventions targeting CSC metabolism to potentially achieve more robust clinical responses in the future.

Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using 18F-FET PET

Molecular markers are of increasing importance for classifying, treating, and determining the prognosis for central nervous system tumors. Isocitrate dehydrogenase (IDH) is a critical regulator of glucose and amino acid metabolism. Our objective was to investigate metabolic reprogramming of glioma using compartmental uptake (CU) characteristics in O-(2-18F-fluoroethyl)-l-tyrosine (FET) PET and to evaluate its diagnostic potential for IDH genotyping. Methods: Between 2017 and 2022, patients with confirmed glioma were preoperatively investigated using static 18F-FET PET. Metabolic tumor volume (MTV), MTV for 60%-100% uptake (MTV60), and T2-weighted and contrast-enhancing lesion volumes were automatically segmented using U-Net neural architecture and isocontouring. Volume intersections were determined using the Dice coefficient. Uptake characteristics were determined for metabolically defined compartments (central [80%-100%] and peripheral [60%-75%] areas of 18F-FET uptake). CU ratio was defined as the fraction between the peripheral and central compartments. Mean target-to-background ratio was calculated. Comparisons were performed using parametric and nonparametric tests. Receiver-operating-characteristic curves, regression, and correlation were used for statistical analysis. Results: In total, 52 participants (male, 27, female, 25; mean age ± SD, 51 ± 16 y) were evaluated. MTV60 was greater and distinct from contrast-enhancing lesion volume (P = 0.046). IDH-mutated tumors presented a greater volumetric CU ratio and SUV CU ratio than IDH wild-type tumors (P < 0.05). Volumetric CU ratio determined IDH genotype with excellent diagnostic performance (area under the curve [AUC], 0.88; P < 0.001) at more than 5.49 (sensitivity, 86%, specificity, 90%), because IDH-mutated tumors presented a greater peripheral metabolic compartment than IDH wild-type tumors (P = 0.045). MTV60 and MTV were not suitable for IDH classification (P > 0.05). SUV CU ratio (AUC, 0.72; P = 0.005) and target-to-background ratio (AUC, 0.68; P = 0.016) achieved modest diagnostic performance-inferior to the volumetric CU ratio. Furthermore, the classification of loss of heterozygosity of chromosomes 1p and 19q (AUC, 0.75; P = 0.019), MGMT promoter methylation (AUC, 0.70; P = 0.011), and ATRX loss (AUC, 0.73; P = 0.004) by amino acid PET was evaluated. Conclusion: We proposed parametric 18F-FET PET as a noninvasive metabolic biomarker for the evaluation of CU characteristics, which differentiated IDH genotype with excellent diagnostic performance, establishing a critical association between spatial metabolic heterogeneity, mitochondrial tricarboxylic acid cycle, and genomic features with critical implications for clinical management and the diagnostic workup of patients with central nervous system cancer.

A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors

Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I-IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476-0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

Blood-brain barrier disruption defines the extracellular metabolome of live human high-grade gliomas

The extracellular microenvironment modulates glioma behaviour. It remains unknown if blood-brain barrier disruption merely reflects or functionally supports glioma aggressiveness. We utilised intra-operative microdialysis to sample the extracellular metabolome of radiographically diverse regions of gliomas and evaluated the global extracellular metabolome via ultra-performance liquid chromatography tandem mass spectrometry. Among 162 named metabolites, guanidinoacetate (GAA) was 126.32x higher in enhancing tumour than in adjacent brain. 48 additional metabolites were 2.05-10.18x more abundant in enhancing tumour than brain. With exception of GAA, and 2-hydroxyglutarate in IDH-mutant gliomas, differences between non-enhancing tumour and brain microdialysate were modest and less consistent. The enhancing, but not the non-enhancing glioma metabolome, was significantly enriched for plasma-associated metabolites largely comprising amino acids and carnitines. Our findings suggest that metabolite diffusion through a disrupted blood-brain barrier may largely define the enhancing extracellular glioma metabolome. Future studies will determine how the altered extracellular metabolome impacts glioma behaviour.

UHPLC-HRMS-based metabolomic and lipidomic characterization of glioma cells in response to anlotinib

Anlotinib, as a promising oral small-molecule antitumor drug, its role in glioma has been only reported in a small number of case reports. Therefore, anlotinib has been considered as a promising candidate in glioma. The aim of this study was to investigate the metabolic network of C6 cells after exposure to anlotinib and to identify anti-glioma mechanism from the perspective of metabolic reprogramming. Firstly, CCK8 method was used to evaluate the effects of anlotinib on cell proliferation and apoptosis. Secondly, ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomic and lipidomic were developed to characterize the metabolite and lipid changes in cell and cell culture medium (CCM) caused by anlotinib in the treatment of glioma. As a result, anlotinib had concentration-dependent inhibitory effect with the concentration range. In total, twenty-four and twenty-three disturbed metabolites in cell and CCM responsible for the intervention effect of anlotinib were screened and annotated using UHPLC-HRMS. Altogether, seventeen differential lipids in cell were identified between anlotinib exposure and untreated groups. Metabolic pathways, including amino acid metabolism, energy metabolism, ceramide metabolism, and glycerophospholipid metabolism, were modulated by anlotinib in glioma cell. Overall, anlotinib has an effective treatment against the development and progression of glioma, and these remarkable pathways can generate the key molecular events in cells treated with anlotinib. Future research into the mechanisms underlying the metabolic changes is expected to provide new strategies for treating glioma.

Spatial metabolic heterogeneity of oligodendrogliomas at single-cell resolution

Oligodendrogliomas are a type of rare and incurable gliomas whose metabolic profiles have yet to be fully examined. The present study examined the spatial differences in metabolic landscapes underlying oligodendrogliomas and should provide unique insights into the metabolic characteristics of these uncommon tumors. Single-cell RNA-sequencing expression profiles from 4044 oligodendroglioma cells derived from tumors resected from four locations frontal, temporal, parietal, and frontotemporoinsular) and in which 1p/19q co-deletion and IDH1 or IDH2 mutations were confirmed were computationally analyzed through a robust workflow to elucidate relative differences in metabolic pathway activities among the different locations. Dimensionality reduction using metabolic expression profiles exhibited clustering corresponding to each location subgroup. From the 80 metabolic pathways examined, over 70 pathways had significantly different activity scores between location subgroups. Further analysis of metabolic heterogeneity suggests that mitochondrial oxidative phosphorylation accounts for considerable metabolic variation within the same locations. Steroid and fatty acid metabolism pathways were also found to be major contributors to heterogeneity. Oligodendrogliomas display distinct spatial metabolic differences in addition to intra-location metabolic heterogeneity.

Rewired Metabolism of Amino Acids and Its Roles in Glioma Pathology

Amino acids (AAs) are indispensable building blocks of diverse bio-macromolecules as well as functional regulators for various metabolic processes. The fact that cancer cells live with a voracious appetite for specific AAs has been widely recognized. Glioma is one of the most lethal malignancies occurring in the central nervous system. The reprogrammed metabolism of AAs benefits glioma proliferation, signal transduction, epigenetic modification, and stress tolerance. Metabolic alteration of specific AAs also contributes to glioma immune escape and chemoresistance. For clinical consideration, fluctuations in the concentrations of AAs observed in specific body fluids provides opportunities to develop new diagnosis and prognosis markers. This review aimed at providing an extra dimension to understanding glioma pathology with respect to the rewired AA metabolism. A deep insight into the relevant fields will help to pave a new way for new therapeutic target identification and valuable biomarker development.

Genome-wide profiling of dysregulated piRNAs and their target genes implicated in oncogenicity of Tongue Squamous Cell Carcinoma

PIWI-interacting RNAs (piRNAs) are single-stranded, 23-36 nucleotide long RNAs that regulate gene expression in the germline but are also detected in some cancers. However, there are no reports yet on piRNA expression in tongue squamous cell carcinoma (TSCC), the most common oral cancer (80-90% percent of all oral cancers). We performed small RNA and whole transcriptome sequencing in H357 tongue cancer and HOK cells (GEO database accession numbers: GSE196674 and GSE196688). We also examined nine published sets of gene expression array data of TSCC tissues from the GEO database to decode piRNAs and their putative targets that may be involved in tumorigenesis. We identified a pool of 16058 and 25677 piRNAs in H357 and HOK, respectively, among which 406 are differentially expressed. We also found that 2094 protein-coding genes are differentially expressed in either TSCC tissues or cell lines. We performed target predictions for these piRNA, pathway and disease function (DF) analyses, as well as qRT-PCR validation of piRNA-target pairs. These experiments revealed one up-regulated (FDFT1) and four down-regulated (OGA, BDH1, TAT, HYAL4) target genes that are enriched in 11 canonical pathways (CPs), with postulated roles in the initiation and progression of TSCC. Downregulation of piR-33422 is predicted to upregulate the FDFT1 gene, which encodes a mevalonate/cholesterol-pathway related farnesyl-diphosphate farnesyltransferase. The FDFT1 appears to be involved in the largest number of oncogenesis-related processes and is interacting with statins, which is a classical cancer drug. This study provides the first evidence of the piRNome of TSCC, which could be investigated further to decode piRNA-mediated gene regulations in malignancy and potential drug targets, such as FDFT1.

Gene Expression Analysis Reveals Prognostic Biomarkers of the Tyrosine Metabolism Reprogramming Pathway for Prostate Cancer

Background

Tyrosine metabolism pathway-related genes were related to prostate cancer progression, which may be used as potential prognostic markers.

Aims

To dissect the dysregulation of tyrosine metabolism in prostate cancer and build a prognostic signature based on tyrosine metabolism-related genes for prostate cancer. Materials and Method. Cross-platform gene expression data of prostate cancer cohorts were collected from both The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Based on the expression of tyrosine metabolism-related enzymes (TMREs), an unsupervised consensus clustering method was used to classify prostate cancer patients into different molecular subtypes. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to evaluate prognostic characteristics based on TMREs to obtain a prognostic effect. The nomogram model was established and used to synthesize molecular subtypes, prognostic characteristics, and clinicopathological features. Kaplan–Meier plots and logrank analysis were used to clarify survival differences between subtypes.

Results

Based on the hierarchical clustering method and the expression profiles of TMREs, prostate cancer samples were assigned into two subgroups (S1, subgroup 1; S2, subgroup 2), and the Kaplan–Meier plot and logrank analysis showed distinct survival outcomes between S1 and S2 subgroups. We further established a four-gene-based prognostic signature, and both in-group testing dataset and out-group testing dataset indicated the robustness of this model. By combining the four gene-based signatures and clinicopathological features, the nomogram model achieved better survival outcomes than any single classifier. Interestingly, we found that immune-related pathways were significantly concentrated on S1-upregulated genes, and the abundance of memory B cells, CD4+ resting memory T cells, M0 macrophages, resting dendritic cells, and resting mast cells were significantly different between S1 and S2 subgroups.

Conclusions

Our results indicate the prognostic value of genes related to tyrosine metabolism in prostate cancer and provide inspiration for treatment and prevention strategies.

Decreased SLC27A5 Suppresses Lipid Synthesis and Tyrosine Metabolism to Activate the Cell Cycle in Hepatocellular Carcinoma

Tyrosine is an essential ketogenic and glycogenic amino acid for the human body, which means that tyrosine is not only involved in protein metabolism, but also participates in the metabolism of lipids and carbohydrates. The liver is an important place for metabolism of lipids, carbohydrates, and proteins. The metabolic process of biological macro-molecules is a basis for maintaining the physiological activities of organisms, but the cross-linking mechanism of these processes is still unclear. Here, we found that the tyrosine-metabolizing enzymes, which were specifically and highly expressed in the liver, were significantly down-regulated in hepatocellular carcinoma (HCC), and had a correlation with a poor prognosis of HCC patients. Further analysis found that the reduction of tyrosine metabolism would activate the cell cycle and promote cell proliferation. In addition, we also found that the solute carrier family 27 member 5 (SLC27A5) regulates the expression of tyrosine-metabolizing enzymes through nuclear factor erythroid 2-related factor 2 (NRF2). Therefore, the SLC27A5 and tyrosine-metabolizing enzymes that we have identified coordinate lipid and tyrosine metabolism, regulate the cell cycle, and are potential targets for cancer treatment.

Electrotherapies for Glioblastoma

Non-thermal, intermediate frequency (100-500 kHz) electrotherapies present a unique therapeutic strategy to treat malignant neoplasms. Here, pulsed electric fields (PEFs) which induce reversible or irreversible electroporation (IRE) and tumour-treating fields (TTFs) are reviewed highlighting the foundations, advances, and considerations of each method when applied to glioblastoma (GBM). Several biological aspects of GBM that contribute to treatment complexity (heterogeneity, recurrence, resistance, and blood-brain barrier(BBB)) and electrophysiological traits which are suggested to promote glioma progression are described. Particularly, the biological responses at the cellular and molecular level to specific parameters of the electrical stimuli are discussed offering ways to compare these parameters despite the lack of a universally adopted physical description. Reviewing the literature, a disconnect is found between electrotherapy techniques and how they target the biological complexities of GBM that make treatment difficult in the first place. An attempt is made to bridge the interdisciplinary gap by mapping biological characteristics to different methods of electrotherapy, suggesting important future research topics and directions in both understanding and treating GBM. To the authors' knowledge, this is the first paper that attempts an in-tandem assessment of the biological effects of different aspects of intermediate frequency electrotherapy methods, thus offering possible strategies toward GBM treatment.

Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.

Sequential Orbitrap Secondary Ion Mass Spectrometry and Liquid Extraction Surface Analysis-Tandem Mass Spectrometry-Based Metabolomics for Prediction of Brain Tumor Relapse from Sample-Limited Primary Tissue Archives

We present here a novel surface mass spectrometry strategy to perform untargeted metabolite profiling of formalin-fixed paraffin-embedded pediatric ependymoma archives. Sequential Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) and liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) permitted the detection of 887 metabolites (163 chemical classes) from pediatric ependymoma tumor tissue microarrays (diameter: <1 mm; thickness: 4 μm). From these 163 classes, 60 classes were detected with both techniques, whilst LESA-MS/MS and 3D OrbiSIMS individually allowed the detection of another 83 and 20 unique metabolite classes, respectively. Through data fusion and multivariate analysis, we were able to identify key metabolites and corresponding pathways predictive of tumor relapse, which were retrospectively confirmed by gene expression analysis with publicly available data. Altogether, this sequential mass spectrometry strategy has shown to be a versatile tool to perform high-throughput metabolite profiling on sample-limited tissue archives.

Targeting RGS4 Ablates Glioblastoma Proliferation

Glioblastoma (GBM) is the most common type of adult primary brain tumor with a median survival rate of less than 15 months, regardless of the current standard of care. Cellular heterogeneity, self-renewal ability and tumorigenic glioma cancer stem cell (GSC) populations contribute to the difficulty in treating GBM. G-protein-coupled receptors (GPCRs) are the largest group of membrane proteins and mediate many cellular responses. Regulators of G-protein signaling 4 (RGS4) are negative regulators of G-protein signaling, and elevated levels of RGS4 are reportedly linked with several human diseases, including cancer. This study investigates the effect of silencing RGS4, resulting in inhibition of GSC growth, invasion and migration. Data obtained from The Cancer Genome Atlas (TCGA) demonstrated poor patient survival with high expression of RGS4. Immunohistochemistry and immunoblot analysis conducted on GBM patient biopsy specimens demonstrated increased RGS4 expression correlative with the TCGA data. RNA sequencing confirmed a significant decrease in the expression of markers involved in GSC invasion and migration, particularly matrix metalloproteinase-2 (MMP2) in knockout of RGS4 using CRISPR plasmid (ko-RGS4)-treated samples compared to parental controls. Gelatin zymography confirmed the reduced activity of MMP2 in ko-RGS4-treated samples. Silencing RGS4 further reduced the invasive and migratory abilities and induction of apoptosis of GSCs as evidenced by Matrigel plug assay, wound healing assay and human apoptosis array. Collectively, our results showed that the silencing of RGS4 plays an important role in regulating multiple cellular functions, and is an important therapeutic target in GBM.

Tumor edge-to-core transition promotes malignancy in primary-to-recurrent glioblastoma progression in a PLAGL1/CD109-mediated mechanism

BACKGROUND

Glioblastoma remains highly lethal due to its inevitable recurrence. Most of this recurrence is found locally, indicating that postsurgical tumor-initiating cells (TICs) accumulate at the tumor edge. These edge-TICs then generate local recurrence harboring new core lesions. Here, we investigated the clinical significance of the edge-to-core (E-to-C) signature generating glioblastoma recurrence and sought to identify its central mediators.

METHODS

First, we examined the association of E-to-C-related expression changes to patient outcome in matched primary and recurrent samples (n = 37). Specifically, we tested whether the combined decrease of the edge-TIC marker PROM1 (CD133) with the increase of the core-TIC marker CD109, representing E-to-C transition during the primary-to-recurrence progression, indicates poorer patient outcome. We then investigated the specific molecular mediators that trigger tumor recurrence driven by the E-to-C progression. Subsequently, the functional and translational significance of the identified molecule was validated with our patient-derived edge-TIC models in vitro and in vivo.

RESULTS

Patients exhibiting the CD133low/CD109high signature upon recurrence representing E-to-C transition displayed a strong association with poorer progression-free survival and overall survival among all tested patients. Differential gene expression identified that PLAGL1 was tightly correlated with the core TIC marker CD109 and was linked to shorter patient survival. Experimentally, forced PLAGL1 overexpression enhanced, while its knockdown reduced, glioblastoma edge-derived tumor growth in vivo and subsequent mouse survival, suggesting its essential role in the E-to-C-mediated glioblastoma progression.

CONCLUSIONS

E-to-C axis represents an ongoing lethal process in primary glioblastoma contributing to its recurrence, partly in a PLAGL1/CD109-mediated mechanism.