Glioblastoma Multiforme Patients Research Articles

Missing the message to brain tumor patients: a 2023 twitter analysis among patients, informal caregivers, and healthcare professionals in glioblastoma multiforme.

Social media platforms, particularly Twitter (X), play an important role in healthcare communication by sharing information and personal disease experiences. We investigated glioblastoma multiforme (GBM) posting behaviors on Twitter by comparing patient and informal caregiver tweets to healthcare professional tweets. Using Keyhole, a third-party analytics tool, we analyzed 1,639 tweets containing the keyword "#glioblastoma" from January 1 to December 31, 2023. Users were categorized as patients, informal caregivers, or healthcare professionals. We employed Generalized Estimating Equation models and multinomial distributions to compare sentiment, thematic, and frequency engagement patterns across stakeholder groups. Informal caregivers produced the slight majority of tweets (51.6%), followed by healthcare professionals (39.0%). Informal caregivers expressed significantly more negative sentiments (relative to neutral ones) than healthcare professionals (p < 0.001). Thematic analysis revealed that patients (p < 0.001) and informal caregivers (p < 0.001) engaged in more emotional support than healthcare professionals. Healthcare professionals were more likely than patients (p < 0.001) and informal caregivers (p < 0.001) to self-promote. Patients (p < 0.001) and informal caregivers (p < 0.001) tweeted more on survival/mortality than healthcare professionals. Additionally, patients (p < 0.001) and informal caregivers (p < 0.001) had a higher average posting frequency per user than healthcare professionals. Our findings indicate that GBM patients and informal caregivers were more likely to discuss emotional aspects of GBM care, while healthcare professionals had more informational and professional motives. Healthcare professionals who address these emotional, social, and financial communication disconnects can make their social media engagement more meaningful to patients who are often at least one of the primary targets of these accounts.

Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e., phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein–protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

HOTAIR expression as a biomarker in glioblastoma multiforme: a comprehensive meta-analysis of current evidence.

Glioblastoma multiforme (GBM) is an aggressive brain tumor. This meta-analysis investigates the association between HOTAIR expression levels and GBM. We searched the literature for studies on HOTAIR expression in GBM patients. A meta-analysis of nine studies assessed standardized mean difference (SMD) and 95% confidence intervals (CIs) using a random-effects model. Subgroup analyses were performed based on sample source, country, and study design. Additionally, we conducted meta-regression and publication bias analyses. The meta-analysis found a significant positive association between elevated HOTAIR expression and GBM (SMD = 8.3, 95% CI 5.8-10.8, p = 0.00). Considerable heterogeneity was observed (Q-value: 1174.2, df = 9, I2 = 99.2%, p = 0.00). Subgroup analyses indicated significant associations in tissue samples and studies from the USA and China. Meta-regression revealed that study design and country contributed to the observed heterogeneity, with no significant publication bias detected. This analysis confirms the significant link between HOTAIR expression and GBM, highlighting HOTAIR as a potential therapeutic target and biomarker. Further research is necessary to clarify the biological mechanisms involved in this association.

Expression of some circulating microRNAs as predictive biomarkers for prognosis and treatment response in glioblastoma

Glioblastoma multiforme (GBM) is the most prevalent, treatment-resistant, and fatal form of brain malignancy. It is characterized by genetic heterogeneity, and an infiltrative nature, and GBM treatment is highly challenging. Despite multimodal therapies, clinicians lack efficient prognostic and predictive markers. Therefore, new insights into GBM management are urgently needed to increase the chance of therapeutic success. Circulating miRNAs (miRs) are important regulators of cancer progression and are potentially useful for GBM diagnosis and treatment. This study investigated how miR-29a, miR-106a, and miR-200a affect the prognosis of GBM patients. This study was conducted on 25 GBM patients and 20 healthy volunteers as a control group. The expression levels of target miRs were analyzed pre- and post-treatment using qRT-PCR and evaluated in relation to both clinical GBM criteria and the patient’s survival modes. The diagnostic efficacy of target miRs was assessed using the receiver operating characteristic (ROC) curve. MiRs levels showed significant differences among the enrolled participants. All investigated miRs were significantly elevated in GBM patients with non-frontal lesions. Only miR-200a showed a significant difference in GBM patients older than 60 years with a tumor size ≥ 5 mm. Regarding miR-106a, a significant difference was detected based on the surgical strategy and use of an Eastern Cooperative Oncology Group (ECOG) performance status equal to 2. For miR-29a, a significant upregulation was detected according to the surgical strategy. All post-treatment miRs levels in GBM patients were significantly downregulated. In conclusion, circulating miRs revealed a significant role in predicting GBM patient treatment outcomes providing valuable insights for personalized therapeutic strategies.

High expression of nucleotide-binding oligomerization domain protein 1 correlates with poor prognosis and immune cell infiltration in Glioblastoma Multiforme patients

Nucleotide-binding oligomerization domain protein 1 (NOD1) is one of the innate immune receptors that has been associated with tumorigenesis and abnormally expressed in various cancers. However, the role of NOD1 in Glioblastoma Multiforme (GBM) has not been investigated. We used the Tumor Immune Estimate Resource (TIMER) database to compare the differential expression of NOD1 in various tumors. NOD1 expression in GBM was further validated in the GEO database, and the survival of NOD1 was assessed by the Kaplan–Meier method. Clinical samples were collected to validate NOD1 expression. GSEA was carried out to expound on NOD1-related pathways involved in GBM. NOD1 co-expression and enrichment analysis were performed using the Linked Omics database and R software. The relationship between immune infiltrates and NOD1 expression was assessed by TIMER. Besides, the correlation between NOD1 and immune signatures (immunomodulators and chemokine) was evaluated by TISIDB. We found that NOD1 expression was significantly upregulated in GBM patients, and higher expression of NOD1 was associated with a poor prognosis. GSEA and enrichment analysis revealed that NOD1 might play a vital role in immune response and GBM progression. TIMER analysis showed a positive correlation between NOD1 expression and 17 types of tumor-infiltrating immune cells. Moreover, NOD1 expression was positively correlated with the expression of chemokine and immunomodulators in GBM. Overall, our findings suggest that NOD1 is a promising prognostic biomarker and is associated with immune cell infiltration in GBM, making it a potential diagnostic biomarker for this aggressive brain cancer.

FSD1 inhibits glioblastoma diffuse infiltration through restriction of HDAC6-mediated microtubule deacetylation.

The infiltration of glioblastoma multiforme (GBM) is predominantly characterized by diffuse spread, contributing significantly to therapy resistance and recurrence of GBM. In this study, we reveal that microtubule deacetylation, mediated through the downregulation of fibronectin type III and SPRY domain-containing 1 (FSD1), plays a pivotal role in promoting GBM diffuse infiltration. FSD1 directly interacts with histone deacetylase 6 (HDAC6) at its second catalytic domain, thereby impeding its deacetylase activity on α-tubulin and preventing microtubule deacetylation and depolymerization. This inhibitory interaction is disrupted upon phosphorylation of FSD1 at its Ser317 and Ser324 residues by activated CDK5, leading to FSD1 dissociation from microtubules and facilitating HDAC6-mediated α-tubulin deacetylation. Furthermore, increased expression of FSD1 or interference with FSD1 phosphorylation reduces microtubule deacetylation, suppresses invasion of GBM stem cells, and ultimately mitigates tumor infiltration in orthotopic GBM xenografts. Importantly, GBM tissues exhibit diminished levels of FSD1 expression, correlating with microtubule deacetylation and unfavorable clinical outcomes in GBM patients. These findings elucidate the mechanistic involvement of microtubule deacetylation in driving GBM cell invasion and offer potential avenues for managing GBM infiltration.

LDH Isoenzyme and GAA-BSA Nanoparticles: A Novel Therapy Approach for Proneural Subtype Glioblastoma Multiforme.

Glioblastoma multiforme (GBM), whose pathogenesis involves proneural-to-mesenchymal transition (PMT), is the most malignant type of glioma and is associated with a bleak prognosis. Lactate dehydrogenase (LDH) comprises two major subunits, LDHA and LDHB, which can assemble into five different isoenzymes (LDH1-5). However, the role of LDH isoenzyme and its subunits in different GBM subtypes is largely unknown. Our findings reveal that LDHA and LDHB subunits correlated with mesenchymal and proneural subtype classification, and have prognostic and clinical significance in GBM patients. Moreover, it is demonstrated that LDH5, characterized by high LDHA and low LDHB levels, is highly expressed in mesenchymal subtype GBM cells and promotes proliferation, migration, and PMT. Conversely, proneural subtype GBM cells exhibited LDH1 dominance, and low LDHA and high LDHB levels. Notably, LDH1 played a pivotal role in the proliferation, migration, and PMT of proneural glioma cells. For treatment of proneural subtype GBM, gossypol-acetic acid (GAA)-bovine serum albumin (BSA) nanoparticles (GAA-BSA NPs) were developed to ameliorate PMT by targeting LDH1. These nanoparticles effectively suppress proneural subtype tumor growth both in vitro and in vivo, surpassing their efficacy against the mesenchymal subtype. The results offer several novel insights into the role of LDH isoenzyme in subtype classification between mesenchymal and proneural GBM and provide a promising therapeutic approach for proneural subtype GBM.

Nanosystems at Nexus: Navigating Nose-to-Brain Delivery for Glioblastoma Treatment.

Glioblastoma multiforme (GBM) is considered to be one of the most devastating brain tumors with a shorter life expectancy. Several factors contribute to the dismal prognosis of GBM patients including the complicated nature of GBM, the ability of tumor cells to resist treatment, and the difficulty of delivering drugs to the brain because of barriers like the blood-brain barrier (BBB) and blood-tumor barrier (BTB). The unique challenges posed by the BBB in delivering therapeutic agents to the brain have led to the development of innovative nanotechnology-based approaches. By exploiting the olfactory/trigeminal pathway, nanosystems offer a promising strategy for targeted drug delivery to the brain, glioblastoma tumors in particular. This review contemplates varied nanocarriers, including polymeric nanoparticles, lipid-based nanosystems, in situ gel formulations, peptide, and stem cell-based nanoformulations, signifying their utility in brain targeting with minimal systemic side effects. Emerging trends in gene therapy and immunotherapy in the context of GBM treatment have also been discussed. Since safety is a paramount aspect for any drug product to get approved, this review also delves into toxicological considerations associated with intranasal delivery of nanosystems. Regulatory aspects and critical factors for the successful development of intranasal products are also explored in this review. Overall, this review underscores the significant advancements in nanotechnology for nose-to-brain delivery and its potential impact on GBM management.

Elevated Serum IL-6 as a Negative Prognostic Biomarker in Glioblastoma: Integrating Bioinformatics and Clinical Validation.

Background: Glioblastoma multiforme (GBM) is the most lethal type of primary brain tumor, necessitating the discovery of reliable serum prognostic biomarkers. This study aimed to investigate the prognostic value of serum Interleukin-6 (IL-6) in GBM patients. Methods: Bioinformatics analysis via gene set enrichment analysis was conducted on The Cancer Genome Atlas RNA-seq data to explore the pathways enriched in samples with high IL-6 expression. The Tumor IMmune Estimation Resource database was used to analyze the association between IL-6 expression and immune cell infiltration. To validate the role of IL-6 in a clinical setting, a retrospective cohort study was conducted on newly diagnosed GBM patients. Serum IL-6 levels were repeatedly measured at key milestone time points, and their correlation with survival data was analyzed. Results: Bioinformatics analysis revealed that high IL-6 expression is associated with the activation of procancer pathways, that there is a positive correlation between IL-6 expression and immune cell infiltration in GBM. Between March 2021 and September 2023, 36 GBM patients and their serum IL-6 measurements at various time points were included in the clinical data analyses. Elevated serum IL-6 levels at baseline, with a cutoff of 7pg/mL, were identified in 11 patients (30.6%). In the multivariate analyses for overall survival (OS), elevated IL-6 was a significant risk factor (p = 0.048), along with unfavorable surgical resection (p = 0.039) and O6-methylguanine-DNA methyltransferase promotor unmethylation (p = 0.027). The median actuarial OS of the high initial IL-6 group was significantly shorter than that of the low initial IL-6 group (6.4 vs. 19.7 months, p < 0.001). However, IL-6 levels at other time points were not related to patient prognosis. Conclusion: Elevated IL-6 mRNA expression is correlated with the activation of procancer pathways, increased immune cell infiltration, and poor prognosis in GBM patients. In addition, elevated serum IL-6 at baseline is a negative prognostic factor confirmed in a clinical study. Serum IL-6 may be a potential prognostic biomarker enhancing the management of GBM.

The Impact of PTEN Status on Glioblastoma Multiforme: A Glial Cell Type-Specific Study Identifies Unique Prognostic Markers

Glioblastoma multiforme (GBM) is the most invasive form of brain tumor, accounting for 5% of the cases per 100,000 people in various countries. The phosphatase and tensin homolog deleted from chromosome 10 (PTEN) is a well-known tumor suppressor, and its alteration leads to a deleterious effect on GBM progression. The molecular mechanism of tumorigenesis in glial cell types, driven by PTEN status, is yet to be elucidated. In this study, we analyzed publicly available single-cell transcriptome profiles of PTEN wild-type (WT) and NULL GBM patients. We compared them with normal brain data to uncover many unique gene sets influenced by PTEN status. The co-expression network analysis of differentially expressed genes (DEGs) between normal brain and PTEN (WT and NULL) identified highly interconnected genes. The weighted gene co-expression network analysis (WGCNA), based on the DESeq2 algorithm, identified glial cell-type-specific modules in PTEN status-dependent bulk RNA expression profiles. We overlapped network module gene sets from single-cell and bulk transcriptome profiles, and shared genes were considered for further analysis. The hallmark pathway enrichment analysis of the genes unique to PTEN-WT and NULL revealed various tumor growth-related pathways across the glial cell types. Further characterization of PTEN-WT and PTEN-NULL networks belonging to the single-cell and bulk RNA datasets revealed that PTEN status influences the network modules in astrocytes, microglia, and oligodendrocyte precursor cells. An integrated influence value algorithm identified hub genes for each glial cell type. The prognostic analysis identified clinically relevant hub genes specific to the cell type in PTEN-WT: GLIPR2 (astrocytes), CFH, IL32, MXRA5 (microglia), and PTEN-NULL: ID1 (astrocytes) and LAT2 (microglia). Our glial cell type-level transcriptome analysis unearthed unique molecular pathways and prognostic markers in PTEN status-dependent GBM patients.

ADAR1 Promotes the Progression and Temozolomide Resistance of Glioma Through p62-Mediated Selective Autophagy.

Resistance to temozolomide (TMZ) remains is an important cause of treatment failure in patients with glioblastoma multiforme (GBM). ADAR1, as a member of the ADAR family, plays an important role in cancer progression and chemotherapy resistance. However, the mechanism by which ADAR1 regulates GBM progression and TMZ resistance is still unclear. We first constructed stable transfected strains in which ADAR1 was knocked down and overexpressed to investigate the effect of ADAR1 on the first-line glioma chemotherapy drug TMZ. Subsequently, we validated that ADAR1 induces autophagy activation and used autophagy inhibitors to suppress autophagy, demonstrating that ADAR1 enhances TMZ resistance through autophagy. We further knocked down p62 (SQSTM1) based on the overexpression of ADAR1, and the results showed that ADAR1 regulates selective autophagy through the p62 regulation. Finally, we demonstrated through mutations at both edited and nonedited sites that ADAR1 regulates selective autophagy in an edited dependent way. Further analysis showed that in the presence of TMZ, elevated ADAR1 promoted TMZ induced autophagy activation. Further research revealed that ADAR1 enhances TMZ resistance through p62-mediated selective autophagy. Further, ADAR1 regulates selective autophagy in an edited dependent way. Our results indicate a relationship between ADAR1 levels and the response of glioma patients to TMZ treatment. We found that the expression of ADAR1 is upregulated in GBM and is associated with tumor grade and TMZ resistance. Elevated expression of ADAR1 predicts poor prognosis in GBM patients and promotes tumor growth invivo or invitro.

Radiomics and deep learning models for glioblastoma treatment outcome prediction based on tumor invasion modeling.

We investigate the feasibility of using a biophysically guided approach for delineating the Clinical Target Volume (CTV) in Glioblastoma Multiforme (GBM) by evaluating its impact on the treatment outcomes, specifically Overall Survival (OS) time. An established reaction-diffusion model was employed to simulate the spatiotemporal evolution of cancerous regions in T1-MRI images of GBM patients. The effects of the parameters of this model on the simulated tumor borders were quantified and the optimal values were used to estimate the distribution of infiltrative cells (CTVmodel). Radiomics and deep learning models were examined to predict the OS time by analyzing the GTV, clinical CTV, and CTVmodel. The study involves 126 subjects for model development and 62 independent subjects for testing. Evaluation of the proposed approach demonstrates comparable predictive power for OS time that is achieved with the clinically defined CTV. Specifically, for the binary survival prediction, short vs. long time, the proposed CTVmodelresulted in improvements of prognostic power, in terms of AUROC, both for the validation (0.77 from 0.75) and the testing (0.73 from 0.71) set. Quantitative comparisons for three-class prediction and survival regression models exhibited a similar trend of comparable performance. The findings highlight the potential of biophysical modeling for estimating and incorporating the spread of infiltrating cells into CTV delineation. Further clinical investigations are required to validate the clinical efficacy.

Elimination of High-grade Gliomas Through Induced Cytolysis, Elucidated by Two Patient Cases.

Glioblastoma multiforme (GBM) is the most common and aggressive form of primary malignant tumors in the central nervous system of adults. In practice, all patients with GBM experience relapse, and treatment options become limited following first-line therapy. We previously reported a new, successful treatment approach for a GBM patient, implemented in direct conjunction with surgical intervention. Here, we present an additional case demonstrating the success of this protocol, along with an overview of its underlying rationale and mechanisms. Following maximal safe tumor resection, our protocol involves the placement of two catheters in the tumor excision bed, connected to drug infusion pumps for continuous administration. The tumor's excision beds are irrigated for 90-120 hours with a slightly alkaline Tris-buffered solution containing L-2,4 diaminobutyric acid, an unnatural amino acid, and Prazosin, a proapoptotic drug widely used as an antihypertensive. Both patients demonstrated marked clinical improvement. Recent contrast-enhanced magnetic resonance imaging revealed no evidence of malignancy, with Case 1 remaining disease-free for seven years and Case 2 for two years of follow-up. This innovative approach not only enhances local drug delivery but also minimizes systemic side effects, addressing a critical challenge in GBM treatment. These cases highlight the potential of this protocol as an adjunct to standard therapies, offering a promising option for managing inoperable or recurrent GBM.

Role of Podoplanin (PDPN) in Advancing the Progression and Metastasis of Glioblastoma Multiforme (GBM).

Glioblastoma multiforme (GBM) is a malignant primary brain tumor categorized as a Grade 4 astrocytic glioma by the World Health Organization (WHO). Some of the established risk factors of GBM include inherited genetic syndromes, body mass index, alcohol consumption, use of non-steroidal anti-inflammatory drugs (NSAIDs), and therapeutic ionizing radiation. Vascular anomalies, including local and peripheral thrombosis, are common features of GBM. Podoplanin (PDPN), a ligand of the C-type lectin receptor (CLEC-2), promotes platelet activation, aggregation, venous thromboembolism (VTE), lymphatic vessel formation, and tumor metastasis in GBM patients. It is regulated by Prox1 and is expressed in developing and adult mammalian brains. It was initially identified on lymphatic endothelial cells (LECs) as the E11 antigen and on fibroblastic reticular cells (FRCs) of lymphoid organs and thymic epithelial cells as gp38. In recent research studies, its expression has been linked with prognosis in GBM. PDPN-expressing cancer cells are highly pernicious, with a mutant aptitude to form stem cells. Such cells, on colocalization to the surrounding tissues, transition from epithelial to mesenchymal cells, contributing to the malignant carcinogenesis of GBM. PDPN can be used as an independent prognostic factor in GBM, and this review provides strong preclinical and clinical evidence supporting these claims.

Proteomic Profiling of Pre- and Post-Surgery Saliva of Glioblastoma Patients: A Pilot Investigation.

Glioblastoma multiforme (GBM) is an extremely aggressive brain tumor characterized by a high infiltration capability and recurrence rate. Early diagnosis is crucial to improve the prognosis and to personalize the therapeutic approach. This research explored, by LC-MS proteomic analysis after proteolytic digestion, the molecular profile of pre- and post-operative saliva pools from newly diagnosed (ND) GBM patients by comparing different times of collection and tumor recurrence (R). CYCS, PRDX2, RAB1C, PSMB1, KLK6, TMOD3, PAI2, PLBD1, CAST, and AHNAK, all involved in processes of tumor invasiveness and chemo- and radio-resistance, were found to depict the pre-surgery saliva of both ND and R GBM. PADI4 and CRYAB proteins, identified among the most abundant proteins exclusive of ND GBM pre-surgery saliva and classified as proteins elevated in glioma, could have a potential role as disease biomarkers. Selected panels of S100 proteins were found to potentially differentiate ND from R GBM patient saliva. TPD52 and IGKV3, exclusively identified in R GBM saliva, could be additionally distinctive of tumor relapse. Among the proteins identified in all pools, label-free relative quantitation showed statistically significant different levels of TXN, SERPINB5, FABP5, and S100A11 proteins between the pools. All of these proteins showed higher levels in both ND_ and R_T0 pre-surgery saliva with respect to CTRL and different modulation after surgery or chemo-radiotherapy combined treatment, suggesting a role as a potential panel of GBM predictive and prognostic biomarkers. These results highlight and confirm that saliva, a biofluid featured for an easily accessible and low invasiveness collection, is a promising source of GBM biomarkers, showing new potential opportunities for the development of targeted therapies and diagnostic tools.

Investigating the Role of MUC19 in Glioblastoma Multiforme: Genetic Alterations and Implications for Patient Survival and Therapeutic Targeting

Abstract* Background Glioblastoma multiforme (GBM) is the most aggressive and lethal form of brain cancer, and is characterized by rapid progression and poor patient survival. Genetic mutations play a significant role in cancer development and recurrence. This study investigated the role of Mucin 19 (MUC19), a member of the mucin family that has been implicated in cancer progression. We aimed to assess whether MUC19 mutations are associated with a worse prognosis in patients with GBM and explore its potential as a therapeutic target. Methods Data from 16 independent GBM patient datasets were retrieved from the cBioPortal for Cancer Genomics, comprising over 5,600 patients. These patients were categorized into two groups based on their survival status: living and deceased. Clinical attributes, including mutation frequencies and survival outcomes, were analyzed to identify significant genetic alterations in the deceased group. MUC19 is one of the most prominent mutations. To functionally investigate the role of MUC19, we conducted RNA interference (RNAi) experiments using A172 glioblastoma cells. Small interfering RNA (siRNA) specific to MUC19 (siMUC19) was used to knock down MUC19 expression, whereas the negative control group was treated with non-targeting siRNA. The effects on cell viability, proliferation, and MUC19 expression were also assessed. Results Our analysis identified 10 significantly mutated genes in deceased GBM patients, with MUC19 showing the most prominent association with poor outcome. siRNA-mediated knockdown of MUC19 resulted in a significant reduction in cell growth and viability compared to the control group, supporting its role in GBM progression. Conclusion MUC19 plays a significant role in GBM progression, and its suppression leads to reduced tumor cell growth. These findings suggest that MUC19 may be a promising therapeutic target for improving outcomes in patients with GBM. Further research is needed to explore its potential in clinical settings.

In Silico and In Vitro Study of mRNA Biomarkers for Glioblastoma Multiforme Resistance to Temozolomide (TMZ): The Association with Stemness.

Glioblastoma multiforme (GBM) is an aggressive brain tumor that primarily affects adults. The Stupp Protocol, which includes surgical resection, chemoradiation, and monotherapy with temozolomide (TMZ), is the standard treatment regimen for GBM. However, repeated use of TMZ leads to resistance in GBM cells, resulting in a poor prognosis for patients. This resistance is driven by several intrinsic factors. This study aims to identify potential biomarkers of resistance associated with stemness. We utilized datasets from GEO, performed Venn diagram intersection analysis, conducted GO enrichment analysis using DAVID and ENRICHR, carried out pathway enrichment analysis with KEGG and REACTOME, and executed survival analysis with GEPIA. Additionally, we compared mRNA expression using the Human Protein Atlas and validated our findings with qRT-PCR. We identified that PAQR6 and ITPKB mRNA expression was consistently higher in TMZ-resistant T98G cells, but TGFBI mRNA expression was found to be significantly higher in TMZ-resistant T98G cells compared to U87MG cells. In addition, a significantly higher CD133 mRNA expression as a stemness marker was found in T98G cells compared to U87MG cells. It is hoped that the acquired disease-related resistance biomarker candidates will be able to be used at the clinical level in terms of non-invasive early detection in GBM patients. However, additional research is required to validate the findings of this preliminary biomarker discovery study.

Construction and validation of a novel prognostic model with palmitoylation-related genes for glioblastoma.

Glioblastoma multiforme (GBM), the most prevalent and aggressive primary brain tumor, poses substantial challenges in both treatment and prognosis. Post-translational modifications, like palmitoylation, are known to have critical roles in the development and progression of glioma. Yet, the molecular mechanisms involved in palmitoylation and its prognostic significance in GBM are still not fully understood. This study aimed to explore prognostic biomarkers for GBM based on palmitoylation-related genes and to construct a prognostic risk model. The messenger ribonucleic acid (mRNA) expressions data and the clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to explore palmitoylation-related mechanisms in GBM. The Cox regression analysis was performed to identify prognostic palmitoylation-related genes and the consensus clustering was used for molecular classification. The package "limma" was used for differential gene expression analysis and the least absolute shrinkage and selection operator (LASSO) regression was applied to construct a risk signature. A nomogram model was established using the risk score and clinical variables. Receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA) were used to assess the predicted accuracy and clinical benefit of the model. The difference in immune cell infiltration was compared between different risk groups. The drug susceptibility analysis and immunotherapy response prediction were conducted to access the ability of the risk signature in predicting the therapeutic effect. Based on datasets from TCGA, five palmitoylation-related genes were identified as prognostic markers, allowing for the categorization of GBM patients into two subtypes with differing survival rates. Through differential expression analysis, 570 specific genes linked to GBM advancement were uncovered. A total of seven signature genes (COL22A1, IGFBP6, SOD3, UPP1, CA14, TIMP4 and FERMT1) were applied to establish a prognostic risk model, which was demonstrated to be an independent prognostic indicator for patients with GBM. Kaplan-Meier analysis indicted that the GBM patients in low-risk group exhibited a better survival outcome compared the patients in high-risk group. The ROC curve analyses demonstrated that the risk score model was reliable. The nomograms showed excellent predictive ability. Two external cohort of patients from the GSE74187 and GSE83300 in the GEO database confirmed the model's strong predictive performance. The immune infiltration, drug sensitivity and immunotherapy responses were significantly different between the low- and high-risk groups. Our study offers insights into the molecular classification and prognostic assessment of GBM, focusing on palmitoylation-related mechanisms. The prognostic model we constructed provides valuable guidance for tailoring personalized treatment strategies for GBM patients.

Abstract B026: Glioblastoma multiforme disseminates outside the central nervous system

Abstract Introduction: The liquid biopsy (LB) concept has gained significant attention in the last decade and has the potential to revolutionize cancer care. However, more validation in clinical trials is required on the value of LB in medical settings. Here, we focus on glioblastoma multiforme (GBM), a highly invasive and fatal subtype of the central nervous system malignant tumors. Circulating tumor cells (CTCs) are primary tumor cells released into the peripheral blood and migrating to distant organs. CTC presence is related to tumor spread and recurrence. In GBM, factors like short patient survival, the blood-brain barrier (BBB), and lack of lymphatic drainage in brain tissue make systemic dissemination rare but possible. Thus, noninvasive CTC detection can hold potential for diagnostic, predictive, and prognostic applications. Material and Methods: For cell stability preservation before sample processing, the peripheral blood samples from curatively resected GBM patients were collected preoperatively in Cell-Free DNA BCT® tubes (Streck, Inc.). CTCs were identified using CytoTrack CT11TM (2/C), a semi-automated immunofluorescence microscopy using glial fibrillary acidic protein, vimentin, and CD45 immunostaining, and DAPI counterstaining. The preliminary Kaplan-Maier survival analysis based on CTC positivity was performed in 39 patients with a follow-up longer than two years. Results: We analyzed the CTC presence in 100 GBM patient peripheral blood samples. The CTCs or cancer cell clusters were found in 35% of GBM patients. The Kaplan-Maier survival analysis did not show a correlation between CTC presence and survival. This phenomenon may be associated with the generally short survival of these patients, which is expected to increase with advances in oncology and palliative care and/or a possible suppression of tumor cell growth outside the CNS. Conclusions: We have observed the CTCs in the peripheral blood of GBM patients. The patient enrollment and clinical data recording are still ongoing. Citation Format: Pavel Stejskal, Josef Srovnal, Alona Rehulkova, Ondrej Kalita, Marek Slachta, Marian Hajduch. Glioblastoma multiforme disseminates outside the central nervous system [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B026.

TMET-08. RADIATION-INDUCED SLC25A22 CONTRIBUTES TO GLIOBLASTOMA RADIORESISTANCE ACQUISITION THROUGH REMODELING GLUTAMATE METABOLISM

Abstract Glioblastoma Multiforme (GBM), a malignant primary brain tumor, is treated by surgical resection followed by chemo- and radiotherapy. Nevertheless, most GBM patients show dismal prognosis due to the radioresistance acquisition of GBM cells via metabolic rewiring. Therefore, it is urgently required to discover how metabolic rewiring attributes to GBM radioresistance, and its targeting strategies. To identify GBM radioresistance driver genes, we previously established radioresistance GBM cells (RGCs) via repetitive in vivo selection, followed by mRNA sequencing, and selected candidate genes that are altered in RGCs (fold change&amp;gt;2 or &amp;lt;0.5, p-value&amp;lt;0.05) and also related with GBM patients’ prognosis. Here, we focused on amino acid transmembrane transporter (Gene Ontology: 0003333) and found that SLC25A22 was the most increased in RGCs. SLC25A22 exhibits uni-directional properties, exporting glutamate to cytosol, resulting in cytosolic glutamate accumulation in RGCs. Using 13C glutamine isotope tracing analysis following mitochondrial fractionation, we quantified the mitochondrial metabolic flux of glutamine. Despite decreased 13C glutamate efflux from RGCs mitochondria after genetic inhibition of SLC25A22, glutamine metabolites (a-ketoglutarate, succinate, malate, fumarate) remained constant. Cytosolic glutamate, as a substrate, is incorporated into various biosynthetic pathways, especially glutathione (GSH) and proline synthesis pathways in radioresistant GBM cells. GSH protects GBM cells by scavenging radiation-induced reactive oxygen species. Whereas, proline, a rate-limiting substrate for collagen biosynthesis, leads GBM cells to show an invasiveness phenotype via extracellular matrix remodeling. Genetic inhibition of SLC25A22 using short hairpin RNA (shRNA) or microRNA-184 mimic suppresses RGCs radioresistance and aggressiveness. Additionally, intranasal administration of microRNA-184 mimic prolonged the survival (median survival: 26 days after irradiation) of GBM-bearing mice, compared with non-target control (median survival: 16 days after irradiation). Together, our study demonstrates that SLC25A22 upregulation confers GBM radioresistance by inducing cytosolic glutamate-driven biosynthesis and suggests SLC25A22 as a therapeutic target to overcome GBM radioresistance.