IDH Mutation Status Research Articles

RETROSPECTIVE ANALYSIS OF GLIOBLASTOMA OUTCOMES

Background Glioblastoma (GBM) is one of the most aggressive brain cancers, with a median overall survival (OS) of about 15 months. This retrospective study focuses on 144 GBM cases treated over 12 years in our clinic in Romania, analyzing factors affecting progression-free survival (PFS) and OS, including genetic markers and treatment modalities. Methods This study involved patients treated between 2012 and 2024 at the National Institute of Neurology and Neurovascular Diseases in Bucharest. The cohort included 144 patients, with variables such as age, gender, tumor location, IDH mutation status, Karnofsky Performance Status (KPS), and genetic markers (MGMT methylation and EGFR amplification) analyzed. Survival outcomes were evaluated using Kaplan-Meier curves and log-rank tests. Results - Patient Demographics: The cohort included 64 males (44.4%) and 80 females (55.6%) with a mean age of 60.7 years. - Tumor Characteristics: The most common tumor location was the frontal lobe (31.9%), followed by multilobular GBM (26.3%). Right-side tumors were more prevalent (51.3%). - Genetic Markers: MGMT promoter was methylated in 46 patients (31.9%), and EGFR was amplified in 76 patients (52.7%). - Treatment Modalities: 105 patients (72.9%) received chemotherapy with temozolomide (TMZ), and 116 patients (80.5%) underwent radiotherapy. - Survival Outcomes: Median PFS was 5 months, and median OS was 8.5 months. Kaplan-Meier survival curves indicated significantly increased OS in patients with MGMT methylation undergoing chemotherapy (p<0.005) and radiotherapy (p<0.005). Similarly, OS was significantly higher in patients without EGFR amplification receiving chemotherapy (p<0.005) and radiotherapy (p<0.005). Conclusion The study emphasizes the importance of MGMT methylation and EGFR amplification in predicting survival outcomes in GBM patients. Immediate postoperative adjuvant therapy significantly improves PFS and OS. The findings underscore the need for coordinated care and timely access to adjuvant therapies to enhance survival rates in GBM patients. Second surgical interventions also showed a survival benefit, highlighting their potential role as salvage therapy in recurrent GBM cases.

RTID-04. A MULTICENTER, RANDOMIZED, CONTROLLED PHASE 2B TRIAL OF SURVIVIN VACCINE SURVAXM PLUS ADJUVANT TEMOZOLOMIDE FOR NEWLY-DIAGNOSED GLIOBLASTOMA (SURVIVE)

Abstract BACKGROUND Glioblastoma cells express high levels of survivin protein, whose presentation by MHC class I gets recognized by antibodies and cytotoxic T-lymphocytes (CTLs). A phase 2a trial (NCT02455557) demonstrated a median overall survival (OS) of 25.9 months in newly-diagnosed glioblastoma (nGBM) patients with 15-amino-acid-peptide-conjugate survivin vaccine (SurVaxM), which also stimulated production of survivin-directed antibodies and anti-tumor CTL. This phase 2b trial aims to further investigate efficacy and safety of SurVaxM plus adjuvant temozolomide (TMZ) for nGBM. METHODS SURVIVE is an ongoing, multicenter, randomized, placebo-controlled, investigator- and patient-blinded, phase 2b trial that randomizes nGBM patients receiving standard-of-care therapies to either SurVaxM (SurVaxM arm) or saline (control arm) in 3:2 ratio at 15 sites. Included patients have age ≥18 years, normal organ function, KPS≥70, and receive surgical resection with ≤1cm3 residual MRI contrast enhancement within 72 hours post-resection plus TMZ. Patients with recurrent, multicentric, brainstem- or cerebellar-origin GBM are excluded as well as patients on TTFields or other immunotherapies. All patients undergo 3 phases: (1) vaccine priming (VP) phase, starting ≤4 weeks after completing chemoradiation – 4 doses of SurVaxM or placebo administered q2weeks; (2) TMZ phase, started after ≥1 VP dose; and (3) vaccine maintenance phase, started 8 weeks after VP, with SurVaxM or placebo given q8weeks. TMZ phase overlaps with VP and VM phases. Primary endpoint is median OS. Assuming 1-year-OS of 75% in SurVaxM arm, based on prior trials, and 60% for control, the required sample size is N=228; 137 in SurVaxM and 91 in control arm. Accounting for dropouts, we aimed to enroll 239 patients. A log-rank test stratified by KPS (70-80 vs 90-100), MGMT methylation status, and IDH mutation status will be used for analysis. Secondary endpoints are OS and PFS at 15, 18, and 24 months, median PFS, and toxicity. A single sequential OS-driven interim analysis is planned when 50% of deaths occur. Trial is fully enrolled (NCT05163080).

CTNI-27. SYSTEMIC DELIVERY OF LOW ENERGY RADIOFREQUENCY ELECTROMAGNETIC FIELDS FOR THE TREATMENT OF PATIENTS WITH PRIMARY BRAIN TUMORS

Abstract BACKGROUND Tumor Treating Fields plus maintenance temozolomide (mTMZ) showed a survival advantage in the first-line glioblastoma (GBM) treatment. The survival benefit remains limited in patients with unmethylated MGMT gene promoter. The AutEMsys device emits low-energy amplitude modulated systemic electromagnetic fields (EMF) at patient specific frequencies. It is an outpatient procedure that can be integrated with mTMZ. METHODS This study involved a prospective compassionate access program targeting adult GBM patients using an intrabuccal EMF exposure via AutEMsys in addition to chemoRT+mTMZ. The program explored the effects on survival and patients’ reported quality-of-life (QOL) by EORTC-QL-C30. Patients underwent a 90-minute session of EMF exposure therapy repeated every 2 weeks until progression, deterioration in QOL or death. All patients had pathological specimens for diagnosis, IDH mutation status through NGS techniques, and MGMT promoter region methylation status. RESULTS 31 participants were enrolled, including 29 with GBM and 2 with diffuse midline glioma. 14 patients (45%) received EMF+chemoRT followed by EMF+mTMZ and 17 patients (55%) received EMF+mTMZ (post chemoRT). Survival time was measured from the start of mTMZ to the date of the last follow-up. The median overall survival (mOS) for all 31 patients was 26.0 months (95% CI: 14.4 – 37.2 months). Specifically for 21 patients with unmethylated MGMT, the mOS was 25.0 months (95% CI: 15.9 – 34.1 months). Similarly, for the 28 patients with IDH wildtype status, the mOS remained 26.0 months (95% CI: 9.6 – 42.4 months). The addition of AutEMsys with chemoRT+mTMZ demonstrated an improved role functioning in 79% of patients with 25% of these with >10-point score. CONCLUSION The AutEMsys device has shown promising initial results when added to chemoRT+mTMZ treatment of GBM. These findings warrant further prospective investigation and validation in a multicenter clinical trial setting.

QOL-31. RESULTS OF A TELEHEALTH-BASED PSYCHOLOGICAL INTERVENTION FOR CAREGIVERS OF PATIENTS WITH PRIMARY MALIGNANT BRAIN TUMORS: A MODERATION ANALYSIS OF A RANDOMIZED CONTROLLED TRIAL

Abstract BACKGROUND In a recent randomized controlled trial, caregivers of patients with primary malignant brain tumors (PMBT) who received NeuroCARE—a six-session, telehealth-based psychological intervention—demonstrated improved anxiety and depression symptoms, coping, and self-efficacy at 11-weeks compared to usual care (UC) participants. We now explore how sociodemographic variables, disease-specific factors, and baseline mood symptoms moderate intervention effects on anxiety and depression symptoms. METHODS We examined data from 120 enrolled caregivers (Mage=53 years; 83% female, 92% White, 70% spouses/partners) of PMBT patients (84% glioblastoma). Eligible caregivers had elevated anxiety (Generalized Anxiety Disorder-7 ≥ 5). Participants were randomized 1:1 to NeuroCARE or UC and completed baseline sociodemographic questionnaires and the Hospital Anxiety and Depression Scale at baseline and 11-weeks. We used linear regression to evaluate whether selected sociodemographic characteristics (gender, age, relationship to patient), tumor characteristics (tumor location/laterality, IDH mutation status), and baseline mood symptoms moderated intervention effects on anxiety and depression symptoms. We report the group-by-moderator (b) effects, using a 0.20 significance level. RESULTS The beneficial effects of NeuroCARE on reducing 11-week anxiety symptoms were greater in women compared to men (b=-2.63, CI: -6.17, 0.91, p=0.14) and greater in caregivers who reported higher baseline anxiety symptoms (b=-0.43, CI: -0.78, -0.08, p=0.02) and depression symptoms (b=-0.56, CI: -0.96, -0.17, p=0.01). The beneficial effects of NeuroCARE on reducing 11-week depression symptoms were greater in caregivers of patients with IDH-wildtype tumors compared to caregivers of patients with IDH-mutant tumors (b=2.49, CI: -0.26, 5.24, p=0.08). Caregiver age, relationship to patient, and tumor location/laterality did not significantly moderate NeuroCARE effects on mood. CONCLUSIONS The positive effects of NeuroCARE were particularly salient for caregivers with elevated anxiety and/or depression symptoms and those caring for patients with IDH-wildtype tumors. Content may be further tailored to account for the unique needs of men and caregivers of patients with IDH-mutant tumors.

PATH-62. CORRELATES OF NEURAL SIGNALING ELUCIDATE SURVIVAL BENEFIT IN GLIOMAS

Abstract Recent literature has highlighted neural signaling markers (SM) as drivers for synaptogenesis, invasion, and proliferation in gliomas. Further work on elucidating key mutations can provide improved prognostication and potential treatment targets. Our objective is to identify correlates of neural signaling in relation to glioma histopathology and patient outcomes. We used a combination of bulk RNA sequencing (RNA-seq) and a DNA gene panel (DPG) by Tempus next-generation sequencing. Differential gene expression (DGE) was performed using DESeq2 after subsetting genes for neural SM. Dimensionality reduction was applied through t-SNE projections. Variant calls were analyzed using EnsemblVEP and maftools. Survival analysis was determined through log-rank tests. All analyses were conducted with R. 176 and 184 patient samples were analyzed for RNA-seq and DPG, respectively. t-SNE of DGE highlights two distinct functional clusters with no correlation to WHO classification status (Chi-squared p = 0.39) The median survival for the big cluster was observed at 957 days, while no median survival was reached even after 4,420 days of follow-up in the small cluster (p = 0.01). This contrast remains consistent when examining subsets of gliomas with unmethylated MGMT promoter (p = 0.02) and glioblastomas (p = 0.02), but not others such as IDH mutation status and low-grade gliomas (p > 0.1). Genes upregulated in the small cluster had equal representation of synaptic and paracrine SM (45% and 55%), while the big cluster had a greater representation of paracrine SM (69% and 31%). DPG of low-grade gliomas highlighted 3 somatic signaling mutations (FGFR1, PTPRD, and SLIT2) that are more prevalent in the big cluster. Functional classification based on neural signaling markers can elucidate a novel set of biomarkers that may impact survival in glioma patients. Further studies are required to validate such findings and develop therapeutic targets.

Identification of a coagulation-related gene signature for predicting prognosis in recurrent glioma.

Recurrent gliomas rapidly progress and have high mortality and poor prognosis in the central nervous system. Therefore, further investigation of prognostic and therapeutic markers is needed. The mRNA expression, clinical data, and coagulation-related genes (CRGs) associated with recurrent glioma were obtained and calculated from the Chinese Glioma Genome Atlas and Kyoto Encyclopedia of Genes and Genomes databases. The significant CRGs were calculated by Weighted gene co-expression network analysis and PPI network. A prediction model was constructed using the least absolute shrinkage and selection operator regression analysis. Recurrent gliomas were stratified into high and low-risk groups based on the median risk score (RS). The Kaplan-Meier curve was used to analyze the difference in overall survival (OS) between these groups, while the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the gene model at 1-, 3-, and 5-years. Clinical factors, including age, gender, MGMT methylation status, radiotherapy, chemotherapy, and RS, were included in the univariate and multivariate regression analysis. A prognostic nomogram and calibration curve were established based on these factors. Overall, seven CRGs associated with the prognosis were identified, including BTK, ITGB1, GNAI3, CFH, LYN, CFI, and F3. OS and survival rates were lower in the high-risk group compared with the low-risk group. The ROC curve demonstrated the area under the curve values >0.65 at 1-, 3-, and 5-years, confirming the reliability of the prognostic model. The univariate regression analysis indicated that tumor grade (grades 2, 3, and 4), histopathology (GBM or not), chemotherapy, IDH mutation, and 1p19q co-deletion status were independent prognostic indicators. Univariate and multivariate regression analyses indicated that RS was an independent prognostic factor for patients with recurrent glioma. Immune analysis revealed low infiltration of resting dendritic cells and high expression of programmed death receptor 1 in the high-risk group. This study comprehensively investigated the correlation between CRGs and recurrent glioma prognosis, offering crucial insights for further research into glioma recurrence mechanisms and treatment strategies.

EPID-28. TRENDS IN LOW GRADE GLIOMA PROGNOSIS AND THE EVOLVING IMPACT OF GROSS TOTAL RESECTION ACROSS FIFTY YEARS: A MULTICOHORT ANALYSIS

Abstract OBJECTIVE Significant advancements in neurosurgical planning, approach, and practice over the past five decades have improved the surgical management of diffuse low and high-grade gliomas. We sought to evaluate the extent to which LGG survival outcomes have evolved over the past fifty years using glioma registry datasets with histopathological groups defined by WHO diagnostic criteria and supplemented with next generation genome-sequencing. METHODS Three datasets (SEER, TCGA, and GENIE) were used to evaluate trends in prognosis following LGG diagnosis and resection between 1975 and present (GBM as a comparator cohort). The primary outcomes evaluated were longitudinal disease-specific survival and overall survival, with secondary fixed-timepoint outcomes evaluated at 12-months, 24-months, and 60-months. Subjects from SEER were categorized by histology, while subjects from TCGA and GENIE were included based IDH mutation status with available histopathology. RESULTS A total of 39,958 adult patients were included. Overall survival increased for both LGG and GBM between 1975 and 2010, however only LGG outcomes continued to improve following 2010 (2010-; HR=0.955, 95%CI 0.926 to 0.986). Evaluation of the interaction between resection extent and diagnosis year revealed a progressive increase in the survival benefit of GTR in recent years, particularly for LGG. Independent of other available clinical/molecular features and considering the interaction term between year of diagnosis and resection extent, the gap in independent prognostic benefit associated with GTR between LGG and GBM has significantly widened (2010-2020 vs 1990-2000, p<0.05). CONCLUSION Over the past three decades, consistent improvements in LGG outcomes were observed while prognosis following GBM diagnosis has remained largely unchanged following 2010. Notably, we observed increasing prognostic value of achieving GTR particularly in patients with LGG.

EPID-19. INTERACTION BETWEEN GERMLINE AND SOMATIC GENETICS TO ELUCIDATE RISK OF ADULT DIFFUSE GLIOMA

Abstract Acquired tumor alterations are part of the WHO diagnosis of glioma. However, germline predisposition to these alterations is unknown. GWAS in European and Asian populations identified germline variants in 30 regions, many in or near genes that also acquire alterations, suggesting that interactions between inherited and acquired genetics are involved in glioma development. To evaluate such interactions, we used 3686 glioma cases and 1889 controls. A case-control design and multinomial logistic regression were used to identify germline variants associated with development of TERT-promoter mutant gliomas, generating two interesting observations. First, TERT germline variants were associated with predisposition to IDHwt glioma that have a TERT promoter mutation, but not with IDH-mutant codeleted gliomas that have a TERT promoter mutation. Second, two novel regions were observed in this more homogeneous subgroup of TERT mutated tumors: variants in TXNDC11 (OR=2.66, p=5.7x10-8) and RUVBL2 (OR=3.1, p=5.8x10-8). High tumor expression of TXNDC11 is associated with poor prognosis in glioma and RUVBL2 interacts with TERT to affect telomerase activity. Similar analyses are being performed on additional clinically relevant acquired alterations. In parallel, case-case GWAS analyses were performed to evaluate germline variants associated with other tumor alterations. Comparing IDH-mutant versus IDHwt stratified by rs55705857 genotype, the most significant variants were PHLDB1 (p=1.2x10-13) and D2HGDH (p=2.1x10-10), highlighting the importance of these two variants independent of CCDC26 for the development of IDH-mutant glioma. As a parallel approach, we utilized recursive partitioning and regression trees (rpart) to classify IDH mutation status using the 30 known variants. The top four branches of the regression tree included CCDC26, D2HGDH, PHLDB1, and MAML2, as well as two Asian variants (RAB27A, CYP4F12). This highlights the importance of utilizing variants discovered in non-European populations in analyses. Overall, understanding these interactions are necessary to develop therapeutics, stratify clinical trials, and to develop relevant tumor models.

Mitochondrial Iron Metabolism as a Potential Key Mediator of PD-L1 Thermal Regulation

Glioblastoma (GBM) is the most common primary brain malignancy in the U.S. with a 5-year overall survival < 5% despite an aggressive standard of care. Laser interstitial thermal therapy (LITT) is a surgical approach to treating GBM that has gained traction, providing a safe option for reducing intracranial tumor burden. LITT is believed to potentially modulate GBM immune responses; however, the biochemical mechanisms underlying the modulation of immune checkpoints in GBM cells have been poorly characterized. The present study aimed to preliminarily evaluate the effects of thermal therapy and radiation on PD-L1 modulation in vitro, as a function of IDH mutational status. U87 cells and their IDH-mutant counterpart (U87R132H), which was generated using a crispr-cas9 knock-in approach, were utilized for this preliminary evaluation. Cell heating was achieved by harvesting with trypsin centrifugation where the cell pellets were treated on a heat block for the associated time and temperature. Following thermal therapy, cells were resuspended and irradiated using a 37-Cesium irradiator at 0.6 Gy min−1. Immediately following treatment, cells were either plated as single cells to allow colonies to form, and stained with Coomassie blue to be counted approximately 10–14 days later or harvested for Western blot analysis. Cell lysates were analyzed for PD-L1 expression with respect to various iron metabolic parameters (mortalin (HSPA9), transferrin receptor, and ferritin heavy chain) using a Western blotting approach. In both U87 and U87R132H cell lines, thermal therapy showed a temperature-dependent cell-killing effect, but U87R132H cells appeared more sensitive to thermal treatment when treated at 43 °C for 10 min. Moreover, thermal therapy had minimal effects on cell responses to 2 Gy irradiation. Treatment with thermal therapy downregulated PD-L1 expression in U87R132H cells, which was associated with increased expression of the mitochondrial iron metabolic enzyme, HSPA9. Thermal therapy reversed the radiation-induced overexpression of PD-L1, transferrin receptor, and ferritin heavy chain in U87R132H cells. No effects were observed in wild-type U87 cells. Moreover, Ga(NO3)3 depleted mitochondrial iron content which, in turn, significantly enhanced the sensitivity of U87R132H cells to thermal therapy and 2 Gy irradiation and caused a significant increase in PD-L1 expression. These results suggest that thermal therapy alone can modulate the immune checkpoint PD-L1. This effect was more pronounced when thermal therapy was combined with radiation. Mechanistically, mitochondrial iron trafficking through HSPA9 may coordinate the regulation of PD-L1 in the context of thermal therapy and ionizing radiation, which can be targeted with gallium-based therapy. These novel, preliminary findings warrant further mechanistic investigations in pre-clinical models of LITT.

Predicting IDH and ATRX mutations in gliomas from radiomic features with machine learning: a systematic review and meta-analysis.

This systematic review aims to evaluate the quality and accuracy of ML algorithms in predicting ATRX and IDH mutation status in patients with glioma through the analysis of radiomic features extracted from medical imaging. The potential clinical impacts and areas for further improvement in non-invasive glioma diagnosis, classification and prognosis are also identified and discussed. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic and Test Accuracy (PRISMA-DTA) statement. Databases including PubMed, Science Direct, CINAHL, Academic Search Complete, Medline, and Google Scholar were searched from inception to April 2024. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used to assess the risk of bias and applicability concerns. Additionally, meta-regression identified covariates contributing to heterogeneity before a subgroup meta-analysis was conducted. Pooled sensitivities, specificities and area under the curve (AUC) values were calculated for the prediction of ATRX and IDH mutations. Eleven studies involving 1,685 patients with grade I-IV glioma were included. Primary contributors to heterogeneity included the MRI modalities utilised (conventional only vs. combined) and the types of ML models employed. The meta-analysis revealed pooled sensitivities of 0.682 for prediction of ATRX loss and 0.831 for IDH mutations, specificities of 0.874 and 0.828, and AUC values of 0.842 and 0.948, respectively. Interestingly, incorporating semantics and clinical data, including patient demographics, improved the diagnostic performance of ML models. The high AUC in the prediction of both mutations demonstrates an overall robust diagnostic performance of ML, indicating the potential for accurate, non-invasive diagnosis and precise prognosis. Future research should focus on integrating diverse data types, including advanced imaging, semantics and clinical data while also aiming to standardise the collection and integration of multimodal data. This approach will enhance clinical applicability and consistency.

P10.09.A BLOOD-BASED CLASSIFICATION OF IDH-STATUS OF NON-ENHANCING GLIOMAS: A MACHINE LEARNING APPROACH

Abstract BACKGROUND Non-invasive determination of IDH mutational status in patients with glioma could offer significant therapeutic opportunities. While IDH wildtype tumors (e.g., GBM) typically show enhancement on MRI, IDH mutant tumors often lack this enhancement. However, relying solely on anatomic radiology may lead to misclassification, and currently, tissue acquisition is the primary method for assessing IDH status in gliomas. This limitation hampers the development of neoadjuvant or intraoperative therapeutic strategies based on IDH status; thus, more minimally invasive methods to determine IDH status are needed. In this study, we assessed immune cell proportions, which vary by glioma subtype, from pre-surgery peripheral blood samples as an alternative method of classifying the IDH status in gliomas without enhancement. MATERIAL AND METHODS First, we employed a highly accurate large language model (GPT-4-Turbo-128k) with over 99% accuracy to read radiology notes and exclude patients with enhancing gliomas. Then, we identified twelve immune cell subtypes from whole blood using deconvolution algorithms based on DNA methylation data. These immune cell subtypes, along with patient age, were integrated into a machine learning model (random forest) to predict IDH status (wildtype vs. mutant), leveraging conditional Generative Adversarial Networks to generate synthetic data and mitigate bias in the datasets. Two independent datasets were included for training and validating the model. RESULTS The random forest model had an area under the ROC curve (AUC) of 0.90 and accurately identified IDH status in 81% of a training set of 287 gliomas (65 wildtype and 222 mutant tumors at varied time points after diagnosis). In an independent validation data set of 99 gliomas (6 wildtype and 93 mutant) from pre-surgery blood samples, the AUC was 0.93, and accuracy predicted IDH status in 92% of cases with a sensitivity of 93% and specificity of 83%. CONCLUSION We could accurately predict IDH status in pre-surgical peripheral blood samples from patients with non-enhancing gliomas. This minimally invasive approach is a promising step toward reducing risk and exploring opportunities for earlier therapies based on IDH status.

Cognitive phenotypes: Unraveling the heterogeneity in cognitive dysfunction among patients with primary brain tumors receiving radiotherapy.

Patients with primary brain tumors demonstrate heterogeneous patterns of cognitive dysfunction, which we explore using latent profile analysis (LPA) to identify cognitive phenotypes and their trajectories in patients receiving radiotherapy (RT). Ninety-six patients completed neuropsychological testing before and post-RT (3, 6, 12-months) on a prospective longitudinal trial, including measures of processing speed, executive function, language, and verbal and visual memory. Models with 2-4 classes were examined. Demographic and clinical data were examined across phenotypes and post-RT cognitive change was evaluated. The optimal model identified three unique cognitive phenotypes including a group of patients with generalized impairments (11.5%), a group with isolated verbal memory impairments (21.9%), and a group with minimal impairments (66.7%). The Verbal Memory phenotype had fewer years of education (p=.007) and a greater proportion of males (p<.001); the Generalized group had a greater proportion of patients with IDH-wild type gliomas and showed greater symptoms of anxiety and poorer quality of life (p-values<.05); and the Minimal Impairment phenotype had higher rates of IDH-Mutant gliomas. Approximately 50% of patients declined on at least one cognitive domain with memory the most vulnerable. Patients that declined reported greater symptoms of depression (p=.007) and poorer quality of life (p=.025). We identified three distinct cognitive phenotypes in patients with primary brain tumors receiving RT, each associated with unique demographic and clinical (e.g., IDH mutational status) profiles, with mood symptoms associated with late cognitive decline. This patient-centered approach enhances our understanding of clinical profiles associated with cognitive dysfunction and treatment-related neurotoxicity.

Amino acid metabolism in glioma: in vivo MR-spectroscopic detection of alanine as a potential biomarker of poor survival in glioma patients.

Reprogramming of amino acid metabolism is relevant for initiating and fueling tumor formation and growth. Therefore, there has been growing interest in anticancer therapies targeting amino acid metabolism. While developing personalized therapeutic approaches to glioma, in vivo proton magnetic resonance spectroscopy (MRS) is a valuable tool for non-invasive monitoring of tumor metabolism. Here, we evaluated MRS-detected brain amino acids and myo-inositol as potential diagnostic and prognostic biomarkers in glioma. We measured alanine, glycine, glutamate, glutamine, and myo-inositol in 38 patients with MRI-suspected glioma using short and long echo-time single-voxel PRESS MRS sequences. The detectability of alanine, glycine, and myo-inositol and the (glutamate + glutamine)/total creatine ratio were evaluated against the patients' IDH mutation status, CNS WHO grade, and overall survival. While the detection of alanine and non-detection of myo-inositol significantly correlated with IDH wildtype (p = 0.0008, p = 0.007, respectively) and WHO grade 4 (p = 0.01, p = 0.04, respectively), glycine detection was not significantly associated with either. The ratio of (glutamate + glutamine)/total creatine was significantly higher in WHO grade 4 than in 2 and 3. We found that the overall survival was significantly shorter in glioma patients with alanine detection (p = 0.00002). Focusing on amino acids in MRS can improve its diagnostic and prognostic value in glioma. Alanine, which is visible at long TE even in the presence of lipids, could be a relevant indicator for overall survival.

Radiosensitizing Effect of PARP Inhibition on Chondrosarcoma and Chondrocyte Cells Is Dependent on Radiation LET.

Chondrosarcoma is a rare malignant tumor that forms in bone and cartilage. The primary treatment involves surgical removal of the tumor with a margin of healthy tissue. Especially if complete surgical removal is not possible, radiation therapy and chemotherapy are used in conjunction with surgery, but with a generally low efficiency. Ongoing researches are focused on understanding the genetic and molecular basis of chondrosarcoma following high linear energy transfer (LET) irradiation, which may lead to treatments that are more effective. The goal of this study is to evaluate the differential effects of DNA damage repair inhibitors and high LET irradiation on chondrosarcoma versus chondrocyte cells and the LET-dependency of the effects. Two chondrosarcoma cell lines with different IDH mutation status and one chondrocyte cell line were exposed to low LET (X-ray) and high LET (carbon ion) irradiation in combination with an Olaparib PARP inhibitor. Cell survival and DNA repair mechanisms were investigated. High LET irradiation drastically reduced cell survival, with a biological efficiency three times that of low LET. Olaparib significantly inhibited PARylation in all the tested cells. A significant reduction in cell survival of both chondrosarcoma and chondrocyte cells was observed following the treatment combining Olaparib and X-ray. PARP inhibition induced an increase in PARP-1 expression and a reduced effect on the cell survival of WT IDH chondrosarcoma cells. No radiosensitizing effect was observed in cells exposed to Olaparib paired with high LET irradiation. NHEJ was activated in response to high LET irradiation, neutralizing the PARP inhibition effect in both chondrosarcoma cell lines. When high LET irradiation is not available, PARP inhibition could be used in combination with low LET irradiation, with significant radiosensitizing effects on chondrosarcoma cells. Chondrocytes may be affected by the treatment combination too, showing the need to preserve normal tissues from radiation fields when this kind of treatment is suggested.

Comprehensive exploration on the role of base excision repair genes in modulating immune infiltration in low-grade glioma

IntroductionGlioma is a brain tumour occurring in all age groups but common in adults. Despite advances in the understanding of tumours, we cannot improve the survival of the patients and do not have an appropriate biomarker for progression and prognosis prediction. The base excision repair mechanism maintains the integrity of the genome, preventing tumour formation. However, continuous chemical damage to the cells results in mutations that escape the repair mechanism and support tumour growth. The tumour microenvironment in cancer is crucial in determining the tumour growth, development, and response to treatments. The present study explored the significance of Base Excision Repair genes (BER) in modulating the tumour microenvironment. MethodsWe used the publically available data sets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to explore the role of the base excision repair gene in the modulating tumour microenvironment. The data was analysed for the expression of base excision repair genes, their correlation with the immune markers, their prognostic potential, and enrichment analysis to understand the pathways they modulate in low-grade glioma (LGG) progression. ResultsThe analysis showed BER genes contribute an integral role in the overall and disease-free survival of LGG. Genes like MUTYH, PNKP, UNG and XRCC1 showed a correlation with the immune infiltration levels and a significant correlation with various immune markers associated with different immune cells, including tumour-associated macrophages. MUTYH, UNG and XRCC1 correlated with IDH1 mutation status, and functional enrichment analysis showed that these genes are enriched in several pathways like Wnt, PD-1 and Integrin signalling. ConclusionOur findings suggest that the BER genes MUTYH, PNKP, UNG and XRCC1 can potentially be prognostic biomarkers and highly correlate with the immune cells of the tumour microenvironment.

Exploring the multifaceted role of key lncRNA in glioma: From genetic expression to clinical implications and immunotherapy potential

BackgroundLong non-coding RNAs (lncRNAs) are implicated in a variety of regulatory functions within tumors, yet their specific roles in glioma remain underexplored. MethodsWe extracted glioma patient data from The Cancer Genome Atlas and UCSC Xena database for analysis using R, focusing on genomic characterization, biological enrichment, immune evaluation, and the development of a predictive model employing machine learning techniques. Additionally, we conducted cell culture and proliferation assays. ResultsOur analysis revealed that the lncRNA SLC16A1-AS1 plays a pivotal role in glioma pathogenesis and prognosis. We observed that abnormal expression of SLC16A1-AS1 varied with tumor grade, IDH mutation status, and histological type, correlating with worse survival outcomes. Genomically, SLC16A1-AS1 was associated with Tumor Mutational Burden and other prognostic biomarkers. The expression of this lncRNA was also linked to the activation of critical biological pathways and appeared to modulate the immune microenvironment, enhancing the presence of immune cells and checkpoints, which may be predictive of immunotherapy outcomes. Our predictive model, constructed from genes associated with SLC16A1-AS1, accurately forecasted glioma prognosis, strongly correlating with survival and treatment responses. In vitro experiments further demonstrated that SLC16A1-AS1 significantly influences glioma cell proliferation, invasion, and migration, underscoring its role in tumor aggression and its potential as a therapeutic target. ConclusionsThis study underscores the significant influence of SLC16A1-AS1 on glioma progression and prognosis, with its expression correlating with tumor traits and immune responses. The findings highlight the potential of targeting SLC16A1-AS1 in therapeutic strategies aimed at mitigating glioma aggressiveness.

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma

BackgroundTreatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood.MethodsThe differential expression of ALOX5AP was evaluated based on public Databases. Kaplan–Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray.ResultALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma.ConclusionALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Assessment the Impact of IDH Mutation Status on MRI Assessments of White Matter Integrity in Glioma Patients: Insights From Peak Width of Skeletonized Mean Diffusivity and Free Water Metrics.

Gliomas are highly invasive brain tumors that evade accurate geographic assessment by conventional MRI due to microscopic invasion along white matter (WM) tracts. Advanced diffusion MRI techniques are needed to assess occult WM involvement. To evaluate peak width of skeletonized mean diffusivity (PSMD) and peak width of skeletonized free water (PSFW), and axonal water fraction (AWF) for assessing glioma-induced alterations in normal-appearing WM and their relationship with isocitrate dehydrogenase 1 (IDH1) mutation. Retrospective. One hundred five glioma patients (46 ± 13 years), 53 healthy controls (HCs) (46 ± 9 years). 3.0 T, T1WI, T1-CE, T2WI, T2FLAIR, and DKI. PSMD and PSFW were compared between lesion and contralateral sides in glioma patients and between patients and HCs. The associations between these metrics and clinical variables, including IDH1 mutation, was assessed. Corpus callosum (CC) injury, quantified by the AWF, was evaluated for its mediated effect of IDH1 mutation on contralesional PSMD and PSFW. Paired-t tests, ANCOVA, univariate and multivariate linear regression, and mediation analysis with significance set at P < 0.05. Contralateral PSMD and PSFW were significantly higher in left-sided gliomas (PSMD: 0.206 ± 0.027 vs. 0.193 ± 0.023; PSFW: 0.119 ± 0.019 vs. 0.106 ± 0.020) than in HCs, with similar increases in right-sided gliomas (PSMD: 0.219 ± 0.036 vs. 0.195 ± 0.023; PSFW: 0.129 ± 0.031 vs. 0.109 ± 0.020). IDH1 wild-type gliomas were associated with higher contralateral PSMD and PSFW (β = -0.302 and -0.412). AWF of CC mediated the impact of IDH1 mutations on contralesional PSMD and PSFW (mediated proportion: 42.7% and 53.7%). PSMD and PSFW are effective biomarkers for assessing WM integrity in gliomas, significantly associated with IDH1 mutation status. AWF of CC mediates the relationship between IDH1 mutation and contralesional PSMD and PSFW. 4 TECHNICAL EFFICACY: Stage 2.

Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients

Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model’s predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner.

Revisiting gliomatosis cerebri in adult-type diffuse gliomas: a comprehensive imaging, genomic and clinical analysis

Although gliomatosis cerebri (GC) has been removed as an independent tumor type from the WHO classification, its extensive infiltrative pattern may harbor a unique biological behavior. However, the clinical implication of GC in the context of the 2021 WHO classification is yet to be unveiled. This study investigated the incidence, clinicopathologic and imaging correlations, and prognostic implications of GC in adult-type diffuse glioma patients. Retrospective chart and imaging review of 1,211 adult-type diffuse glioma patients from a single institution between 2005 and 2021 was performed. Among 1,211 adult-type diffuse glioma patients, there were 99 (8.2%) patients with GC. The proportion of molecular types significantly differed between patients with and without GC (P = 0.017); IDH-wildtype glioblastoma was more common (77.8% vs. 66.5%), while IDH-mutant astrocytoma (16.2% vs. 16.9%) and oligodendroglioma (6.1% vs. 16.5%) were less common in patients with GC than in those without GC. The presence of contrast enhancement, necrosis, cystic change, hemorrhage, and GC type 2 were independent risk factors for predicting IDH mutation status in GC patients. GC remained as an independent prognostic factor (HR = 1.25, P = 0.031) in IDH-wildtype glioblastoma patients on multivariable analysis, along with clinical, molecular, and surgical factors. Overall, our data suggests that although no longer included as a distinct pathological entity in the WHO classification, recognition of GC may be crucial considering its clinical significance. There is a relatively high incidence of GC in adult-type diffuse gliomas, with different proportion according to molecular types between patients with and without GC. Imaging may preoperatively predict the molecular type in GC patients and may assist clinical decision-making. The prognostic role of GC promotes its recognition in clinical settings.