Overall Survival Of Glioma Patients Research Articles

Decoding the immune microenvironment: unveiling CD8 + T cell-related biomarkers and developing a prognostic signature for personalized glioma treatment

BackgroundGliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data.MethodsIn this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted.ResultsCD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram’s predictions were supported by calibration plots, further validating its accuracy.ConclusionIn conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.

The effect of depression and anxiety on survival in patients with glioma: a systematic review and meta-analysis.

Depression and anxiety's impact on glioma patient survival lacks consensus. Understanding these effects can highlight the importance of identifying depression and anxiety in glioma patients, and inform future treatments. This systematic review and meta-analysis aims to clarify the impact of depression and anxiety on glioma patient survival. We conducted a systematic literature search of major databases, including PubMed, Embase, Web of Science Core Collection, Cochrane Library, and PsycINFO, from inception to June 2023, to identify relevant studies. Eligible studies were those that examined the association between depression, anxiety, or both, and survival outcomes in glioma patients. Data were extracted and analyzed using fixed-effects meta-analysis models to calculate pooled hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 15 studies met the inclusion criteria, encompassing a diverse range of glioma patients across different clinical settings and stages. The meta-analysis revealed a statistically significant association between depression and reduced overall survival in glioma patients, with a pooled HR of 1.65 (95% CI: 1.41-1.83, 11 studies). The preliminary univariate meta-regression results indicate no impact of individual study characteristics on the effect size. Likewise, anxiety was associated with worse overall survival, with a pooled HR of 1.65 (95% CI: 1.18-2.31, 5 studies). This meta-analysis underscores the vital need to identify and treat depression and anxiety in glioma patients. Future research should explore the underlying mechanisms, aiding the creation of interventions enhancing both mental health and clinical outcomes for this vulnerable group.

Silencing UBE2K inhibits the growth of glioma cells by inducing the autophagy-related apoptosis.

Glioma is a central nervous system (CNS) malignant tumor with high heterogeneity and mortality, which severely threatens the health of patients. The overall survival of glioma patients is relatively short and it is critical to identify new molecular targets for developing effective treatment strategies. UBE2K is a ubiquitin conjugating enzyme with oncogenic function in several malignant tumors. However, whether UBE2K participates in gliomas remains unknown. Herein, in glioma cells, UBE2K was found highly expressed in U87 and U251 cells. Subsequently, U87 and U251 cells were transfected with si-UBE2K to silence UBE2K, with the si-NC transfection as the negative control. In both U87 and U251 cells, the cell viability was sharply reduced by transfecting si-UBE2K for 48 and 72 h. Markedly decreased colony number, reduced number of migrated cells and invaded cells, and declined relative wound healing rate were observed in si-UBE2K transfected U87 and U251 cells. Moreover, the Bcl-2 level was markedly reduced, while the Bax and cleaved-caspase-3 levels were sharply increased in U87 and U251 cells after the si-UBE2K transfection. Furthermore, the p62 level was signally declined, while the Beclin-1 and LC-3 II/I levels were greatly increased in U87 and U251 cells by the si-UBE2K transfection. Furthermore, the facilitating effect of si-UBE2K on the apoptosis and autophagy in U87 and U251 cells was abolished by the coculture of 3-MA, an inhibitor of autophagy. Collectively, UBE2K facilitated the in vitro growth of glioma cells, possibly by inhibiting the autophagy-related apoptosis, which might be a promising target for treating glioma.

Serum beta2-microglobulin acts as a biomarker for severity and prognosis in glioma patients: a preliminary clinical study

BackgroundGliomas are the deadliest malignant tumors of the adult central nervous system. We previously discovered that beta2-microglobulin (B2M) is abnormally upregulated in glioma tissues and that it exerts a range of oncogenic effects. Besides its tissue presence, serum B2M levels serve as biomarkers for various diseases. This study aimed to explore whether serum B2M levels can be used in the diagnosis and prognosis of gliomas.MethodsMedical records from 246 glioma patients were retrospectively analyzed. The relationship between preoperative serum B2M levels and clinicopathological features was examined. Kaplan-Meier analysis, alongside uni- and multivariate Cox regression, assessed the association between B2M levels, systemic inflammatory markers, and glioma patient prognosis. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic significance of these biomarkers specifically for glioblastoma (GBM).ResultsPatients with malignant gliomas exhibited elevated preoperative serum B2M levels. Glioma patients with high serum B2M levels experienced shorter survival times. Multivariate Cox analysis determined the relationship between B2M levels (hazard ratio = 1.92, 95% confidence interval: 1.05–3.50, P = 0.034) and the overall survival of glioma patients. B2M demonstrated superior discriminatory power in distinguishing between GBM and non-GBM compared to inflammation indicators. Moreover, postoperative serum B2M levels were lower than preoperative levels in the majority of glioma patients.ConclusionsHigh preoperative serum B2M levels correlated with malignant glioma and a poor prognosis. Serum B2M shows promise as a novel biomarker for predicting patient prognosis and reflecting the therapeutic response.

Pan-Cancer Analysis and Experimental Validation of CEND1 as a Prognostic and Immune Infiltration-Associated Biomarker for Gliomas.

Cell cycle exit and neuronal differentiation 1 (CEND1), highly expressed in the brain, is a specific transmembrane protein which plays a tumor suppressor role. This study is performed to investigate the role of CEND1 in various cancers through pan-cancer analysis, and further investigate its functions in gliomas by cell experiments. The expression and subcellular localization of CEND1 in different cancer types were analyzed utilizing the data from the GEPIA, UCSC, UALCAN and HPA databases. Relationships of CEND1 expression with prognosis, immunomodulation-related genes, immune checkpoint genes, microsatellite instability (MSI), tumor mutation burden (TMB) and RNA modifications were analyzed based on the TCGA database. The ESTIMATE algorithm was utilized to evaluate tumors' StromalScore, Immune Score, and ESTIMATES Score. The cBioPortal database was employed to analyze the categories and frequencies of CEND1 gene alterations. Biological functions and co-expression patterns of CEND1 in gliomas were explored using the LinkedOmics database, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. The interactions between CEND1 and drugs were explored employing the Comparative Toxicogenomics Database and molecular docking technology. Cell experiments were conducted to analyze triptonide's effects on glioma cells through CCK-8, flow cytometry and qRT-PCR. CEND1 was lowly expressed in gliomas, and high CEND1 expression was correlated to better overall survival of glioma patients (HR = 0.65, P = 0.02). Deep deletion was the main type of hereditary change of CEND1 mutation. CEND1 expression was markedly associated with immune infiltration, TMB, MSI, and RNA modification in various tumors (r > 0.3, P < 0.05). CEND1 co-expressed genes in gliomas were markedly correlated with immune responses and cell cycle (FDR < 0.05). Triptonide could bind well to CEND1 (-5.0kcal/mol), and triptonide could facilitate CEND1 expression in glioma cells and cell apoptosis, and block the cell cycle progression (P < 0.05). CEND1 serves as a potential biomarker for pan-cancer. Particularly in gliomas, CEND1 is a key regulator of cell apoptosis and cell cycle, and a potential target for glioma treatment.

Abstract 361: Targeting the suppressor of ferroptosis to improve the treament effeciency of glioblastoma

Abstract Glioma is the most frequent tumor in central nervous system (CNS), which makes up about 30% of CNS tumors. The current standard strategy for glioma treatment is surgery plus adjuvant chemotherapy and concurrent radiotherapy. Even though, the prognosis of glioma is still poor. It’s encouraging that temozolomide (TMZ) prolongs the overall survival of glioma patients, but the following TMZ resistance is really frustrating. It’s urgent to figure out efficient ways to improve the long term prognosis of patients, such as antagonizing the TMZ resistance. Ferroptosis was a newly discovered type of regulated cell death characterized by iron-dependent aberrant lipid peroxidation and membrane damage in the last decade. Ferroptosis-associated iron transport proteins modulate the process precisely through controlling the iron content. ZIP14, also known as SLC39A14, is an eight-transmembrane protein which could transport divalent metal ion like Mn2+, Zn2+ and Fe2+. Our preliminary data showed that the expression level of ZIP14 was higher in tumor tissues than paired normal tissue, which was corelated with poor prognosis of glioma. Knock down ZIP14 could induce cell death, and which could be rescued by inhibitors for ferroptosis but not for apoptosis or necrosis. Knock down ZIP14 decreased the ferroptosis inhibition by Ferroptosis suppress protein 1 (FSP1) which through reduction of lipid peroxidation, and sensitized cells to TMZ. Furthermore, we found that ZIP14 formed a complex with Ubiquinone. And it was known that FSP1 is critical in the switch of ubiquinone to ubiquinol. Therefore, we propose that ZIP14 suppress lipid peroxidation through blockage of the transition of ubiquinone to ubiquinol. While ZIP14 was knocked down, the complex with Ubiquinone wad damaged, and could not further change to Ubiquinol, so the suppression to lipid peroxidation was released, and then, ferroptosis was upregulated. In this study, we are going to figure out the molecular mechanism about how ZIP14 suppress ferroptosis and find out efficient small molecule inhibitors to activate ferroptosis by abolishing ZIP14 and improve the prognosis of glioma patients. Citation Format: Jing Wang. Targeting the suppressor of ferroptosis to improve the treament effeciency of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 361.

Identification and validation of a novel 9-gene signature of non-specific classification to predict prognosis in glioma patients.

This study aimed to identify and validate a 9-gene signature for predicting overall survival (OS) in glioma patients. Analysis of multiple gene expression datasets led to the identification of 135 candidate genes associated with OS in glioma patients. Further analysis revealed that IGFBP2, PBK, NRXN3, TGIF1, DNAJA4, and LGALS3BP were identified as risk factors for OS, while ENAH, PPP2R2C, and SPHKAP were found to be protective factors. Multifaceted validation using different databases confirmed their differential expression patterns in glioma tissues compared to normal brain tissue. By utilizing LASSO regression and multivariate Cox regression analysis, a risk score was developed based on the expression levels of the 9 crucial genes. The risk score showed a significant correlation with OS in both training and validation cohorts and yielded superior predictive accuracy compared to individual gene expression. Moreover, a predictive nomogram incorporating the risk score, WHO grade, age, IDH mutation, and 1p/19q co-deletion was constructed and validated, which exhibited high predictive capabilities for survival rates at different time points. Enrichment analysis revealed the involvement of extracellular matrix-related pathways and immune system signaling in glioma prognosis. Furthermore, the risk score showed a strong correlation with immune cell infiltration and immune checkpoint expression, suggesting its potential role in the tumor immune microenvironment. In conclusion, our study provides a robust 9-gene signature and a predictive nomogram for evaluating the prognosis of glioma patients, offering valuable insights into personalized treatment strategies.

Liposomal Nanomaterials: A Rising Star in Glioma Treatment.

Glioma is a primary malignant tumor in the central nervous system. In recent years, the treatment of glioma has developed rapidly, but the overall survival of glioma patients has not significantly improved. Due to the presence of the blood-brain barrier and intracranial tumor barrier, many drugs with good effects to cure glioma in vitro cannot be accurately transported to the corresponding lesions. In order to enable anti-tumor drugs to overcome the barriers and target glioma, nanodrug delivery systems have emerged recently. It is gratifying that liposomes, as a multifunctional nanodrug delivery carrier, which can be compatible with hydrophilic and hydrophobic drugs, easily functionalized by various targeted ligands, biodegradable, and hypoimmunogenic in vivo, has become a quality choice to solve the intractable problem of glioma medication. Therefore, we focused on the liposome nanodrug delivery system, and summarized its current research progress in glioma. Hopefully, this review may provide new ideas for the research and development of liposome-based nanomaterials for the clinical treatment of glioma.

Hypoxia-responsive gene F3 Promotes GBM Cell Proliferation and Migration through Activating NF-κB/p65 Signaling Pathway.

Background: Glioblastoma multiforme (GBM) is the most common malignant form of glioma, but the molecular mechanisms underlying the progression of GBM in hypoxic microenvironment remain elusive. This study aims to explore the pathological functions of hypoxia-responsive genes on GBM progression and its downstream signaling pathways. Methods: RNA-seq was performed in normoxic and hypoxic U87 cells to identify the differentially expressed genes (DEGs) under hypoxia. The mRNA expression levels of hypoxia-responsive gene F3 in glioma clinical samples were analyzed according to the transcriptional information from CGGA, TCGA and Rembrandt databases. EdU, transwell and wound-healing assays were conducted to evaluate the pathological functions of F3 on GBM proliferation and migration under hypoxia. RNA-seq and gene set enrichment analysis were conducted to analyze the enriched pathways in LN229 cells overexpressed F3 compared to controls. GBM cells were treated with NF-κB inhibitor PDTC, and cell experiments were performed to evaluate the effects of PDTC on OE-F3-LN229 and OE-F3-U87 cells. Western blot was performed to validate the downstream pathways. Results: F3 was identified as a hypoxia responsive gene in GBM cells. The mRNA expression level of F3 was negatively correlated with the overall survival of glioma patients, and significantly increased in grade IV and GBM than lower grade or other histology of glioma. Overexpression of F3 enhanced the proliferation and migration of hypoxic U87 and LN229 cells, while knockdown inhibited them. In OE-F3-LN229 cells, the NF-κB pathway was activated, with an increased level of phosphorylated p65. PDTC treatment effectively rescued the enhanced proliferation and migration of OE-F3-LN229 cells under hypoxia, indicating that the effect of F3 on GBM progression is probably dependent on the NF-κB pathway. Conclusion: Hypoxia-induced F3 activates NF-κB pathway through upregulation of the phosphorylated p65, thus promoting the proliferation and migration of GBM cells under hypoxia, which might be a potential therapeutic target for GBM treatment.

FBLIM1 mRNA is a novel prognostic biomarker and is associated with immune infiltrates in glioma.

Glioma is the most common primary brain tumor. Filamin-binding LIM protein 1 (FBLIM1) has been identified in multiple cancers and is suspected of playing a part in the development of tumors. However, the potential function of FBLIM1 mRNA in glioma has not been investigated. In this study, the clinical information and transcriptome data of glioma patients were, respectively, retrieved from the TCGA and CGGA databases. The expression level of FBLIM1 mRNA was shown to be aberrant in a wide variety of malignancies. Significantly, when glioma samples were compared to normal brain samples, FBLIM1 expression was shown to be significantly elevated in the former. A poor prognosis was related to high FBLIM1 expression, which was linked to more advanced clinical stages. Notably, multivariate analyses demonstrated that FBLIM1 expression was an independent predictor for the overall survival of glioma patients. Immune infiltration analysis disclosed that FBLIM1 expression had relevance with many immune cells. The results of RT-PCR suggested that FBLIM1 expression was markedly elevated in glioma specimens. Functional experiments unveiled that the knockdown of FBLIM1 mRNA suppressed glioma cell proliferation. In general, we initially discovered that FBLIM1 mRNA might be a possible prognostic marker in glioma.

Prognosis prediction based on methionine metabolism genes signature in gliomas

BackgroundGlioma cells have increased intake and metabolism of methionine, which can be monitored with 11 C-L-methionine. However, a short half-life of 11 C (~ 20 min) limits its application in clinical practice. It is necessary to develop a methionine metabolism genes-based prediction model for a more convenient prediction of glioma survival.MethodsWe evaluated the patterns of 29 methionine metabolism genes in glioma from the Cancer Genome Atlas (TCGA). A risk model was established using Lasso regression analysis and Cox regression. The reliability of the prognostic model was validated in derivation and validation cohorts (Chinese Glioma Genome Atlas; CGGA). GO, KEGG, GSEA and ESTIMATE analyses were performed for biological functions and immune characterization.ResultsOur results showed that a majority of the methionine metabolism genes (25 genes) were involved in the overall survival of glioma (logrank p and Cox p < 0.05). A 7-methionine metabolism prognostic signature was significantly related to a poor clinical prognosis and overall survival of glioma patients (C-index = 0.83). Functional analysis revealed that the risk model was correlated with immune responses and with epithelial-mesenchymal transition. Furthermore, the nomogram integrating the signature of methionine metabolism genes manifested a strong prognostic ability in the training and validation groups.ConclusionsThe current model had the potential to improve the understanding of methionine metabolism in gliomas and contributed to the development of precise treatment for glioma patients, showing a promising application in clinical practice.

TMIC-28. TARGETING TUMOR-ASSOCIATED SMOOTH MUSCLE ACTIN (ACTA2) EXPRESSION IN MOUSE PRE-CLINICAL GLIOMA MODELS REDUCES TUMOR PROGRESSION AND EXTENDS SURVIVAL

Abstract The ACTA2 gene, which encodes α-smooth-muscle actin, is known to be involved in contractility and oncogenic transformation. However, the specific role of tumor-associated ACTA2 mesenchymal cells in gliomas is unknown. Using genetically engineered mouse models (GEMM) of glioma, we discovered that ACTA2 expression was increased within oncostreams, which are malignant multicellular structures found in high-grade gliomas. Furthermore, we observed reduced expression of ACAT2 mRNA in IDH-Mut mouse gliomas vs WT tumors. Analyzing human glioma TCGA and CCGA databases revealed a negative correlation between tumor ACTA2 expression and overall survival in glioma patients. ACTA2 mRNA expression was also higher in grade IV and recurrent tumors. To investigate the role of ACTA2 in glioma cells, we created ACTA2 knockdown GEMM of glioma. These mice showed very large increases (~300%) in median survival (NPDS: 253 days, NPAS: 329 days) in comparison to their respective control groups (NPD: 89 days, NPA: 97 days). Glioma neurospheres derived from knockdown tumors confirmed downregulation of ACTA2, and showed reduced cell proliferation compared to controls. Moreover, orthotopic models revealed a decreased potential for tumor development in vivo. To explore the mechanism mediating the effects of ACTA2 downregulation, we conducted RNA-Seq analysis of ACTA2 knockdown neurospheres. This analysis identified approximately 5000 differentially expressed genes, with gene ontology analysis highlighting significant enrichment in biological processes such as cell adhesion, cell communication, and regulation of locomotion. Pathway analysis identified cytokine-receptor interactions, focal adhesion, and NFK-B signaling as the most significant signaling pathways affected by ACTA2 downregulation. Finally, we evaluated the release of cytokines into the cell-conditioned media and found significantly decreased levels of GSCF and GMSCF cytokines in ACTA2 knockdown compared to controls. These findings indicate that ACTA2 expression is a pro-tumoral gene involved in glioma progression and plays an essential role in altering the TME.

DNMT1-mediated regulating on FBXO32 promotes the progression of glioma cells through the regulation of SKP1 activity.

Glioma, a prevalent and serious form of brain cancer, is associated with dysregulation of DNA methylation, where DNA methyltransferase-1 (DNMT1) plays a significant role in glioma progression. However, the involvement of F-box protein 32 (FBXO32) in glioma and its regulation by DNMT1-mediated methylation remain poorly understood. In this study, we investigated FBXO32 expression in glioma cells with high DNMT1 expression using the online dataset and correlated it with patient survival. Then impact of elevated FBXO32 expression on cell proliferation, migration, and invasion was evaluated, along with the examination of EMT-related proteins. Furthermore, a xenograft model established by injecting glioma cells stably transfected with FBXO32 was used to evaluate tumor growth, volume, and weight. The ChIP assay was employed to study the interaction between DNMT1 and the FBXO32 promoter, revealing that DNMT1 negatively correlated with FBXO32 expression in glioma cells and promoted FBXO32 promoter methylation. Moreover, we investigated the interaction between FBXO32 and SKP1 using Co-IP and GST pulldown assays, discovering that FBXO32 acts as an E3 ubiquitin ligase and promotes SKP1 ubiquitination, leading to its degradation. Interestingly, our findings demonstrated that high FBXO32 expression was associated with improved overall survival in glioma patients. Knockdown of DNMT1 in glioma cells increased FBXO32 expression and suppressed malignant phenotypes, suggesting that FBXO32 functions as a tumor suppressor in glioma. In conclusion, this study reveals a novel regulatory mechanism involving DNMT1-mediated FBXO32 expression in glioma cells, where FBXO32 acts as an E3 ubiquitin ligase to degrade SKP1 via ubiquitination. This FBXO32-mediated regulation of SKP1 activity contributes to the progression of glioma cells. These findings provide important insights into the molecular mechanisms underlying glioma progression and may hold promise for the development of targeted therapies for glioma patients.

The role of APOBEC3C in modulating the tumor microenvironment and stemness properties of glioma: evidence from pancancer analysis.

It is now understood that APOBEC3 family proteins (A3s) are essential in tumor progression, yet their involvement in tumor immunity and stemness across diverse cancer types remains poorly understood. In the present study, comprehensive genome-wide statistical and bioinformatic analyses were conducted to elucidate A3 family expression patterns, establishing clinically relevant correlations with prognosis, the tumor microenvironment(TME), immune infiltration, checkpoint blockade, and stemness across cancers. Different experimental techniques were applied, including RT-qPCR, immunohistochemistry, sphere formation assays, Transwell migration assays, and wound-healing assays, to investigate the impact of A3C on low-grade glioma (LGG) and glioblastoma multiforme (GBM), as well as its function in glioma stem cells(GSCs). Dysregulated expression of A3s was observed in various human cancer tissues. The prognostic value of A3 expression differed across cancer types, with a link to particularly unfavorable outcomes in gliomas. A3s are associated with the the TME and stemness in multiple cancers. Additionally, we developed an independent prognostic model based on A3s expression, which may be an independent prognostic factor for OS in patients with glioma. Subsequent validation underscored a strong association between elevated A3C expression and adverse prognostic outcomes, higher tumor grades, and unfavorable histology in glioma. A potential connection between A3C and glioma progression was established. Notably, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses implicated A3C in immune system-related diseases, with heightened A3C levels contributing to an immunosuppressive tumor microenvironment (TME) in glioma. Furthermore, in vitro experiments substantiated the role of A3C in sustaining and renewing glioma stem cells, as A3C deletion led to diminished proliferation, invasion, and migration of glioma cells. The A3 family exhibits heterogeneous expression across various cancer types, with its expression profile serving as a predictive marker for overall survival in glioma patients. A3C emerges as a regulator of glioma progression, exerting its influence through modulation of the tumor microenvironment and regulation of stemness.

Development and validation of a two glycolysis-related LncRNAs prognostic signature for glioma and in vitro analyses

BackgroundMounting evidence suggests that there is a complex regulatory relationship between long non-coding RNAs (lncRNAs) and the glycolytic process during glioma development. This study aimed to investigate the prognostic role of glycolysis-related lncRNAs in glioma and their impact on the tumor microenvironment.MethodsThis study utilized glioma transcriptome data from public databases to construct, evaluate, and validate a prognostic signature based on differentially expressed (DE)-glycolysis-associated lncRNAs through consensus clustering, DE-lncRNA analysis, Cox regression analysis, and receiver operating characteristic (ROC) curves. The clusterProfiler package was applied to reveal the potential functions of the risk score-related differentially expressed genes (DEGs). ESTIMATE and Gene Set Enrichment Analysis (GSEA) were utilized to evaluate the relationship between prognostic signature and the immune landscape of gliomas. Furthermore, the sensitivity of patients to immune checkpoint inhibitor (ICI) treatment based on the prognostic feature was predicted with the assistance of the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Finally, qRT-PCR was used to verify the difference in the expression of the lncRNAs in glioma cells and normal cell.ResultsBy consensus clustering based on glycolytic gene expression profiles, glioma patients were divided into two clusters with significantly different overall survival (OS), from which 2 DE-lncRNAs, AL390755.1 and FLJ16779, were obtained. Subsequently, Cox regression analysis demonstrated that all of these lncRNAs were associated with OS in glioma patients and constructed a prognostic signature with a robust prognostic predictive efficacy. Functional enrichment analysis revealed that DEGs associated with risk scores were involved in immune responses, neurons, neurotransmitters, synapses and other terms. Immune landscape analysis suggested an extreme enrichment of immune cells in the high-risk group. Moreover, patients in the low-risk group were likely to benefit more from ICI treatment. qRT-PCR results showed that the expression of AL390755.1 and FLJ16779 was significantly different in glioma and normal cells.ConclusionWe constructed a novel prognostic signature for glioma patients based on glycolysis-related lncRNAs. Besides, this project had provided a theoretical basis for the exploration of new ICI therapeutic targets for glioma patients.

Intraoperative glioma characterization using time-resolved fluorescence spectroscopy.

2072 Background: Extent of surgical resection significantly improves progression-free and overall survival in glioma patients. Due to the infiltrative nature of gliomas, tumor margin detection is often difficult, and current intraoperative visualization methods are limited. Time-resolved fluorescence spectroscopy (TRFS) has the potential of differentiating glioma from normal brain tissue, thereby maximizing extent and safety of resection. Methods: Twenty-seven preoperative patients diagnosed with glioma met inclusion criteria for an IRB-approved study aimed to assess the accuracy of TRFS relative to tissue histopathology for differentiating glioma from normal cortex (NC), normal white matter (NWM), and white matter with edema (WME). A multi-channel TRFS system was developed for in vivo brain tissue and tumor characterization during glioma surgery. A custom-designed fiber optic probe was used to deliver ultrafast laser pulses to tissue regions of interest and collect fluorescence signals, with simultaneous registration to intraoperative neuronavigation. The fluorescence light was collected using a photomultiplier tube and digitized across six wavelength bands. Biopsies were taken at each measurement site for evaluation by a blinded neuropathologist to determine the accuracy of TRFS, which was calculated using parameters derived from the recorded fluorescence pulse and used to characterize tissue signatures. Results: During surgical resection of 27 patients, 162TRFS measurements were collected in vivo followed by biopsy of the same tissue. Samples from brain tumors (39 low grade gliomas (LGG, WHO grade I to III), 35 high grade gliomas (HGG, WHO grade IV)) were compared with 47 samples of normal brain tissue (NC and NWM). The time-resolved system was able to differentiate LGG from normal tissue with 97% sensitivity and 93% specificity (93% PPV and 98% NPV). When all tumor grades were tested, the sensitivity dropped to 91% (96% PPV and 86% NPV), which we believe reflects the heterogeneity of HGG. HGG alone showed a sensitivity of 83% and specificity of 93% (91% PPV and 88% NPV). Normal cortex had the fastest decays across all wavelength bands among different tissue types, WME had longer decays compared to other tissue types at all wavelengths, and HGG had a variable but predictably different fluorescence decay pattern. Conclusions: TRFS is an intraoperative tool that can distinguish glioma from normal brain tissue and has the potential to maximize safe surgical resection.

TMIGD2 as a potential therapeutic target in glioma patients.

Among all types of central nervous system cancers, glioma remains the most frequent primary brain tumor in adults. Despite significant advances in immunomodulatory therapies, notably immune checkpoint inhibitors, their effectiveness remains constrained due to glioma resistance. The discovery of TMIGD2 (Transmembrane and Immunoglobulin Domain Containing 2) as an immuno-stimulatory receptor, constitutively expressed on naive T cells and most natural killer (NK) cells, has emerged as an attractive immunotherapy target in a variety of cancers. The expression profile of TMIGD2 and its significance in the overall survival of glioma patients remains unknown. In the present study, we first assessed TMIGD2 mRNA expression using the Cancer Genome Atlas (TCGA) glioma transcriptome dataset (667 patients), followed by validation with the Chinese Glioma Genome Atlas (CGGA) cohort (693 patients). Secondly, we examined TMIGD2 protein staining in a series of 25 paraffin-embedded blocks from Moroccan glioma patients. The statistical analysis was performed using GraphPad Prism 8 software. TMIGD2 expression was found to be significantly higher in astrocytoma, IDH-1 mutations, low-grade, and young glioma patients. TMIGD2 was expressed on immune cells and, surprisingly, on tumor cells of glioma patients. Interestingly, our study demonstrated that TMIGD2 expression was negatively correlated with angiogenesis, hypoxia, G2/M checkpoint, and epithelial to mesenchymal transition signaling pathways. We also demonstrated that dendritic cells, monocytes, NK cells, gd T cells, and naive CD8 T cell infiltration correlates positively with TMIGD2 expression. On the other hand, Mantel-Cox analysis demonstrated that increased expression of TMIGD2 in human gliomas is associated with good overall survival. Cox multivariable analysis revealed that TMIGD2 is an independent predictor of a good prognosis in glioma patients. Taken together, our results highlight the tight implication of TMIGD2 in glioma progression and show its promising therapeutic potential as a stimulatory target for immunotherapy.

A novel gene, TARDBP, and the protein it encodes can predict glioma patient prognosis and establish a prediction model

BackgroundTDP-43 (43-kD transactive response DNA-binding protein) is a DNA-/RNA-binding protein that plays an important role in several nervous system diseases, such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Whether it plays an important role in glioma patients is unknown.MethodsDatasets were downloaded from the Chinese Glioma Genome Atlas (CGGA) website (http://www.cgga.org.cn/). Cox survival analysis was performed to determine the relationship between TARDBP gene expression and the overall survival of glioma patients. GO analyses were performed to determine the biological functions of the TARDBP gene. Finally, we used PRS type, age, grade, IDH mutation status, 1p/19q codeletion status, and expression value of the TARDBP gene to construct a prediction model. With this model, we can predict patients’ 1-, 2-, 3-, 5-, and 10-year survival rates.ResultsThe TARDBP gene plays an important role in glioma patients. The expression of the TARDBP gene has a significant correlation with glioma patient survival. We also constructed an ideal prediction model.ConclusionOur findings suggest that the TARDBP gene and the protein it encodes play important roles in glioma patients. The expression of the TARDBP gene has a significant correlation with the overall survival of glioma patients.

Deciphering the role of QPCTL in glioma progression and cancer immunotherapy.

Glioma is the most lethal and most aggressive brain cancer, and currently there is no effective treatment. Cancer immunotherapy is an advanced therapy by manipulating immune cells to attack cancer cells and it has been studied a lot in glioma treatment. Targeting the immune checkpoint CD47 or blocking the CD47-SIRPα axis can effectively eliminate glioma cancer cells but also brings side effects such as anemia. Glutaminyl-peptide cyclotransferase-like protein (QPCTL) catalyzes the pyroglutamylation of CD47 and is crucial for the binding between CD47 and SIRPα. Further study found that loss of intracellular QPCTL limits chemokine function and reshapes myeloid infiltration to augment tumor immunity. However, the role of QPCTL in glioma and the relationship between its expression and clinical outcomes remains unclear. Deciphering the role of QPCTL in glioma will provide a promising therapy for glioma cancer immunotherapy. QPCTL expression in glioma tissues and normal adjacent tissues was primarily analyzed in The Cancer Genome Atlas (TCGA) database, and further validated in another independent cohort from the Gene Expression Omnibus (GEO) database, Chinese Glioma Genome Atlas (CGGA), and Human Protein Atlas (HPA). The relationships between QPCTL expression and clinicopathologic parameters and overall survival (OS) were assessed using multivariate methods and Kaplan-Meier survival curves. And the proteins network with which QPCTL interacted was built using the online STRING website. Meanwhile, we use Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to investigate the relationships between QPCTL expression and infiltrated immune cells and their corresponding gene marker sets. We analyzed the Differentially Expressed Genes (DEGs) including GO/KEGG and Gene Set Enrichment Analysis (GSEA) based on QPCTL-high and -low expression tumors. In contrast to normal tissue, QPCTL expression was higher in glioma tumor tissue (p < 0.05). Higher QPCTL expression was closely associated with high-grade malignancy and advanced tumor stage. Univariate and multivariate analysis indicated the overall survival of glioma patients with higher QPCTL expression is shorter than those with lower QPCTL expression (p < 0.05). Glioma with QPCTL deficiency presented the paucity of infiltrated immune cells and their matching marker sets. Moreover, QPCTL is essential for glioma cell proliferation and tumor growth and is a positive correlation with glioma cell stemness. High QPCTL expression predicts high grades of gliomas and poor prognosis with impaired infiltration of adaptive immune cells in the tumor microenvironment as well as higher cancer stemness. Moreover, targeting QPCTL will be a promising immunotherapy in glioma cancer treatment.

Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment.

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma. Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan-Meier (K-M) analysis was performed to determine each cohort's survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT-qPCR and IHC were used to identify the consistency of the signature in tumor tissue. Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT-PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model. Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy.