IDH-wildtype Glioblastoma Research Articles

Visualizing the association between the location and prognosis of isocitrate dehydrogenase wild-type glioblastoma: a voxel-wise Cox regression analysis with open-source datasets.

This study examined the correlation between tumor location and prognosis in patients with glioblastoma using magnetic resonance images of various isocitrate dehydrogenase (IDH) wild-type glioblastomas from The Cancer Imaging Archive (TCIA). The relationship between tumor location and prognosis was visualized using voxel-wise Cox regression analysis. Participants with IDH wild-type glioblastoma were selected, and their survival and demographic data and tumor characteristics were collected from TCIA datasets. Post-contrast-enhanced T1-weighted imaging, T2-fluid attenuated inversion recovery imaging, and tumor segmentation data were also compiled. Following affine registration of each image and tumor segmentation region of interest to the MNI standard space, a voxel-wise Cox regression analysis was conducted. This analysis determined the association of the presence or absence of the tumor with the prognosis in each voxel after adjusting for the covariates. The study included 769 participants of 464 men and 305 women (mean age, 63years ± 12 [standard deviation]). The hazard ratio map indicated that tumors in the medial frontobasal region and around the third and fourth ventricles were associated with poorer prognoses, underscoring the challenges of complete resection and treatment accessibility in these areas regardless of the tumor volume. Conversely, tumors located in the right temporal and occipital lobes had favorable prognoses. This study showed an association between tumor location and prognosis. These findings may assist clinicians in developing more precise and effective treatment plans for patients with glioblastoma to improve their management.

Multimodal MRI and 1H-MRS for Preoperative Stratification of High-Risk Molecular Subtype in Adult-Type Diffuse Gliomas

Isocitrate dehydrogenase (IDH) and O6-methylguanine-DNA methyltransferase (MGMT) genes are critical molecular markers in determining treatment options and predicting the prognosis of adult-type diffuse gliomas. Objectives: this study aimed to investigate whether multimodal MRI enables the differentiation of genotypes in adult-type diffuse gliomas. Methods: a total of 116 adult-type diffuse glioma patients (61 males, 51.5 (37, 62) years old) who underwent multimodal MRI before surgery were retrospectively analysed. Multimodal MRI included conventional MRI, proton magnetic resonance spectroscopy (1H-MRS), and diffusion tensor imaging (DTI). Conventional visual features, N-acetyl-aspartate (NAA)/Creatine (Cr), Choline (Cho)/Cr, Cho/NAA, fractional anisotropy (FA), mean diffusivity (MD), and diffusion histogram parameters were extracted on the whole tumour. Multimodal MRI parameters of IDH-mutant and IDH-wildtype gliomas were compared using the Mann–Whitney U test, Student’s t-test, or Pearson chi-square tests. Logistic regression was used to select the MRI parameters to predict IDH-mutant gliomas. Furthermore, multimodal MRI parameters were selected to establish models for predicting MGMT methylation in the IDH-wildtype gliomas. The performance of models was evaluated by the receiver operating characteristics curve. Results: a total of 56 patients with IDH-mutant gliomas and 60 patients with IDH-wildtype glioblastomas (GBM) (37 with methylated MGMT and 17 with unmethylated MGMT) were diagnosed by 2021 WHO classification criteria. The enhancement degree (OR = 4.298, p < 0.001), necrosis/cyst (OR = 5.381, p = 0.011), NAA/Cr (OR = 0.497, p = 0.037), FA-Skewness (OR = 0.497, p = 0.033), MD-Skewness (OR = 1.849, p = 0.035), FAmean (OR = 1.924, p = 0.049) were independent factors for the multimodal combined prediction model in predicting IDH-mutant gliomas. The combined modal based on conventional MRI, 1H-MRS, DTI parameters, and histogram performed best in predicting IDH-wildtype status (AUC = 0.890). However, only NAA/Cr (OR = 0.17, p = 0.043) and FA (OR = 0.38, p = 0.015) were associated with MGMT methylated in IDH-wildtype GBM. The combination of NAA/Cr and FA-Median is more accurate for predicting MGMT methylation levels than using these elements alone (AUC, 0.847 vs. 0.695/0.684). Conclusions: multimodal MRI based on conventional MRI, 1H-MRS, and DTI can provide compound imaging markers for stratified individual diagnosis of IDH mutant and MGMT promoter methylation in adult-type diffuse gliomas.

Serum lactate dehydrogenase as a prognostic marker for treatment response in IDH wild-type glioblastoma patients undergoing stupp protocol.

Elevated lactate dehydrogenase (LDH), a marker of tumor aggressiveness and metabolic alterations, may predict treatment response and overall survival across various tumors. This study investigates the correlation between serum LDH levels and clinical outcomes in glioblastoma patients treated with radiotherapy (RT) and temozolomide (TMZ). This retrospective study analysed patients with IDH wild-type glioblastoma (IDH-wt GB) treated at the Radiotherapy Department of Azienda Ospedaliero-Universitaria Senese from 2018 to 2023. Clinical data, including hematologic parameters (e.g., LDH), imaging (MRI), and MGMT promoter methylation status, were collected. All patients received RT and TMZ following the Stupp protocol. Serum LDH levels were measured one week before RT, and Radiological Response (RR) was assessed using RANO criteria. Overall survival (OS), progression-free survival (PFS), and RR were primary endpoints. Statistical analyses included Kaplan-Meier, Cox regression, and decision tree analysis for LDH cut-off determination. In a cohort of 147 IDH wild-type glioblastoma patients treated with the Stupp protocol, the median OS was 14 months and median PFS was 8 months. Elevated baseline LDH levels were associated with significantly poorer outcomes, showing a median OS of 9 months versus 20 months and a median PFS of 6 months versus 13 months for lower LDH levels (p < 0.001 and p = 0.0001, respectively). LDH levels also correlated with RR (p = 0,001), Multivariate analysis confirmed high LDH as an independent predictor of worse OS (HR = 2.31) and PFS (HR = 2.60), suggesting its utility as a prognostic biomarker. Elevated LDH levels before starting the Stupp protocol are clinically significant as they predict poorer overall survival and progression-free survival in glioblastoma patients and worse RR. Incorporating LDH measurements into treatment planning can help identify patients at higher risk of poor outcomes, allowing for more tailored and potentially aggressive treatment strategies to improve management and therapeutic responses in glioblastoma.

Implications of molecular classifications in glioma surgery.

The incorporation of molecular markers into neuro-oncology has transformed our understanding of adult diffuse gliomas. While surgical resection is the mainstay of treatment for many patients with gliomas, surgical management strategies warrant re-exploration in the context of characteristic molecular profiles. We reviewed the neurosurgical and neuro-oncological literature for studies investigating surgery in molecularly defined cohorts of adult diffuse gliomas. We discuss key molecular markers associated with the three subtypes of adult diffuse glioma: glioblastoma IDH-wildtype, astrocytoma IDH-mutant, and oligodendroglioma IDH-mutant and 1p/19q codeleted. We additionally discuss surgical strategies and extent of resection in these tumors, framing them in the context of key molecular alterations. Finally, we briefly discuss the practical utility of molecular markers in guiding surgical decision making. Molecular markers in gliomas are of growing relevance to surgical intervention. Advancements in preoperative and intraoperative molecular diagnostics will increase the utility of molecular biomarkers in informing surgical decision-making for patients with gliomas.

EXTH-70. PRECLINICAL TRIALS OF THE ANTIBODY-DRUG CONJUGATE TISOTUMAB VEDOTIN IN ADULT-TYPE DIFFUSE GLIOMAS

Abstract The gene F3, encoding Tissue Factor (TF), is expressed in many cancers and contributes to their malignancy. Our previous work showed that, among adult-type diffuse gliomas, IDH wild-type (IDHwt) glioblastomas (GBM) express more TF than IDH mutant (IDHmut) gliomas (PMID: 27664011, 30266764, 31222125). Tisotumab vedotin (TisVed), an anti-TF antibody conjugated to monomethyl auristatin E, is a therapeutic designed to target cells expressing TF. We therefore sought to determine the therapeutic potential of TisVed in IDHwt vs. IDHmut gliomas. TisVed was more active against cultured IDHwt GBM cells than IDHmut glioma cells (P&amp;lt;0.0001). This activity was increased by 55% with daily washout of the soluble TF secreted by IDHwt GBM cells. TisVed extended the survival of mice intracranially engrafted with IDHwt GBM by 34% (37.5 days vs. 28 days for IgG control, P=0.006), but not mice with IDHmut glioma (30.5 days, P=0.88). TisVed also reduced the growth of IDHwt GBM flank xenografts by 58% (P=0.045). Unconjugated Tis had no antitumor effect intracranially or in the flank. All 12 flank-engrafted mice treated with Tis, and 9/12 mice treated with TisVed, developed large hematomas in and around the flank xenografts, compared to 0/12 IgG-treated mice (P&amp;lt;0.001). Similarly, a semiquantitative analysis showed that intracerebral hemorrhage was more extensive in Tis/TisVed- treated GBM12 mice than in IgG-treated GBM12 mice (P=0.046). These data indicate that TisVed targets high TF-expressing IDHwt GBM, but not low TF-expressing IDHmut glioma, that its activity is predominately through the vedotin conjugate rather than inhibition of TF signaling, and that it may have some effect against TF-expressing IDHwt GBM, but intracerebral hemorrhage may be a concern.

EXTH-45. PRECLINICAL EVALUATION OF THE ANTIBODY-DRUG CONJUGATE TISOTUMAB VEDOTIN IN ADULT-TYPE DIFFUSE GLIOMAS

Abstract The gene F3, encoding Tissue Factor (TF), is expressed in many cancers and contributes to their malignancy. Our previous work showed that, among adult-type diffuse gliomas, IDH wild-type (IDHwt) glioblastomas (GBM) express more TF than IDH mutant (IDHmut) gliomas (PMID: 27664011, 30266764, 31222125). Tisotumab vedotin (TV), an anti-TF antibody conjugated to monomethyl auristatin E, is a therapeutic designed to target cells expressing TF. We therefore sought to determine the therapeutic potential of TV in IDHwt vs. IDHmut gliomas. TV was more active against cultured IDHwt GBM cells than IDHmut glioma cells (P&amp;lt;0.0001). This activity was increased by 55% with daily washout of the soluble TF secreted by IDHwt GBM cells. TV extended the survival of mice intracranially engrafted with IDHwt GBM by 34% (37.5 days vs. 28 days for IgG control, P=0.006), but not mice with IDHmut glioma (30.5 days, P=0.88). TV also reduced the growth of IDHwt GBM flank xenografts by 58% (P=0.045). Unconjugated tisotumab had no antitumor effect intracranially or in the flank. All 12 flank-engrafted mice treated with tisotumab, and 9/12 mice treated with TV, developed large hematomas in and around the flank xenografts, compared to 0/12 IgG-treated mice (P&amp;lt;0.001). Similarly, a semiquantitative analysis showed that intracerebral hemorrhage was more extensive in tisotumab/TV- treated GBM12 mice than in IgG-treated GBM12 mice (P=0.046). These data indicate that TV targets high TF-expressing IDHwt GBM, but not low TF-expressing IDHmut glioma, that its activity is predominately through the vedotin conjugate rather than inhibition of TF signaling, and that it may have some effect against TF-expressing IDHwt GBM, but intracerebral hemorrhage may be a concern.

PATH-29. LONGITUDINAL EPIGENOMIC EVOLUTION OF IDH-WILDTYPE GLIOBLASTOMA

Abstract Glioblastoma, IDH-wildtype remains a molecularly heterogeneous disease that is refractory to current therapies. To investigate how longitudinal epigenomic evolution of glioblastoma drives tumor progression and treatment resistance, we performed comprehensive histopathologic assessment, targeted genomic sequencing, and genome-wide DNA methylation profiling of paired initial and recurrent IDH-wildtype glioblastoma samples from 98 patients, as well as a separate longitudinal cohort of IDH-mutant astrocytomas for comparison. Primary treatment-naïve IDH-wildtype glioblastomas had more globally hypomethylated genomes compared to primary IDH-mutant astrocytomas. At time of recurrence, IDH-mutant astrocytomas uniformly became more hypomethylated similar to the global methylation levels in IDH-wildtype glioblastomas. In contrast, recurrent IDH-wildtype glioblastomas were heterogeneous with subsets becoming more globally hypermethylated (27%), hypomethylated (22%), or remaining stable (51%). Accordingly, a substantial proportion (52%) of recurrent glioblastomas underwent methylation class switching compared to their matched primary tumor, with a predominance of the RTK2 epigenetic subtype at initial surgery and the Mesenchymal epigenetic subtype at recurrence. Among approximately 850,000 interrogated CpG sites, we identified only 110 and 153 sites that consistently became more hypermethylated or hypomethylated between initial and recurrent IDH-wildtype glioblastomas, which regulate genes involved in neuronal morphogenesis, oligodendrocyte differentiation, and myelination. In contrast, we identified 260 and 18,527 CpG sites that consistently became more hypermethylated or hypomethylated between initial and recurrent IDH-mutant astrocytomas, which regulate genes involved in neuronal stem-like differentiation, cell cycle control, and other biologic processes. Finally, we developed a DNA methylation evolution signature incorporating change in mean beta-methylation values from initial to recurrent tumor specimens across 347 critical CpG sites that significantly correlated with clinical outcomes for patients with IDH-wildtype glioblastoma. In summary, IDH-wildtype glioblastomas demonstrate heterogeneous epigenomic evolution patterns distinct from IDH-mutant astrocytomas. These changes in epigenetic patterns may identify unique subgroups of glioblastoma with differential treatment response and inform future therapeutic studies targeting differentially methylated gene programs.

PATH-53. DNA MUTATION SEQUENCING AND METHYLATION ANALYSIS OF SOMATICNF1 MUTANT IDH-WILDTYPE GLIOBLASTOMA IDENTIFIES THREE EPIGENETIC GROUPS ANDCDKN2A/B LOSS AS A NEGATIVE PROGNOSTIC BIOMARKER

Abstract The tumor suppressor NF1 is frequently mutated in IDH-wildtype glioblastoma. However, the molecular subgroups and clinically relevant biomarkers within somatic NF1 mutant, IDH-wildtype glioblastomas remain incompletely understood. Here, we combine methylation arrays and targeted DNA sequencing to identify epigenetic subgroups and clinical biomarkers within non-syndromic NF1 mutant IDH-wildtype glioblastoma. We identified 186 patients treated at the University of California San Francisco between 2016-2024 with newly diagnosed IDH-wildtype glioblastoma containing a somatic pathogenic NF1 mutation on a CLIA certified targeted DNA sequencing assay. Illumina EPIC DNA methylation arrays (n=129 patients) were processed using the minfi package and Heidelberg random forest classifier (v12.8). Downstream analyses including hierarchical clustering and survival analyses were performed in R. DNA sequencing identified 12 recurrently altered genes in greater than 10% of cases across cell cycle regulators (CDKN2A/B, TP53, RB1), PI3K signaling (PTEN, PIK3R1, PIK3CA), epigenetic modifiers (ATRX, SETD2), and growth factor signaling (EGFR, PDGFRA, PTPN11). DNA methylation analysis revealed three epigenetic subgroups. Group 1 showed lower median patient age and significantly increased TP53 co-mutation rate. Group 2 contained a significantly higher proportion of male patients and was significantly enriched for RB1 and TERT promoter alterations, with a majority of tumors classified as GBM-MES using the Heidelberg classifier. Group 3 showed a significantly higher proportion of female patients and was significantly enriched for homozygous CDKN2A/B deletion. Homozygous CDKN2A/B loss was associated with significantly worse overall survival across the entire non-syndromic NF1 mutant glioblastoma cohort but not in a propensity score matched NF1 wildtype glioblastoma cohort. DNA methylation profiling revealed three epigenetic subgroups characterized by distinct clinical features, co-mutation patterns, and reference DKFZ methylation classifier identities. CDKN2A/B loss may be a negative prognostic biomarker specifically in NF1 mutant glioblastomas; future multi-institutional studies are required to validate these findings and their therapeutic implications in a larger, representative cohort.

BIOM-25. MOLECULAR PROFILING PREDICTS EARLY AND LATE PROGRESSION IN GLIOBLASTOMA

Abstract Patients with glioblastoma experience a wide variation in response to standard treatment, with nearly 30% experiencing tumour progression during treatment, and nearly 6% surviving more than 5 years. To date, there are few non-invasive clinical biomarkers to predict response to first – line treatment. Chemical exchange saturation transfer (CEST) MRI may have the potential to fill this gap. CEST MRI is sensitive to treatment-induced changes and changes in tumor metabolism. Our team has obtained CEST data for patients before, during and after the end of standard chemoradiation treatment, and found that CEST provides markers of early response and can identify early, standard and late progressors before treatment initiation. In this study, we aimed to establish molecular profiles of early, standard and late progressors with IDH wild-type glioblastoma. Patients (n=180) with primary, IDH wild-type glioblastoma were imaged with CEST-MRI at multiple time points throughout standard chemoradiation treatment. DNA and RNA were co-extracted from matched normal and tumour pairs and processed for whole genome sequencing, enzymatic methyl-seq and gene expression analysis using Nanostring. Clinical variables such as age, extent of resection, sex, ECOG status and MGMT promoter methylated were also collected. A survival analysis was conducted using the Kaplan-Meier method with log-rank tests. Univariate and multi-variate hazard ratios for clinical variables were calculated by fitting Cox Proportional Hazards Models. Early progressors reported a median progression-free survival (PFS) of 142 days compared to 832 days in late progressors (p&amp;lt;0.0001). Early progressors also harbored distinct and statistically significant differences in gene expression and genomic alterations, namely in DNA damage repair, glucose transport and arginine metabolism pathways. A gene signature was prognostic of PFS and overall survival. Collectively, this data has the potential to serve as a radiogenomic biomarker to assess treatment response before or within early phases of treatment and allow for individual tailoring of the treatment plan.

BIOM-49. PATIENT-CENTRIC INTEGRATED GRAPH DATABASE REVEALS CRITICAL BIOMARKERS IN THE RECURRENCE OF IDH WILD-TYPE GLIOMA

Abstract BACKGROUND IDH wild-type glioblastoma (GBM) represents a formidable therapeutic challenge due to its consistent recurrence and progression despite standard treatments. Understanding the molecular and cellular mechanisms driving GBM recurrence through data integration is crucial. This study employs a novel graph database strategy to uncover insights into these tumors and identify functional biomarkers through graph algorithms-based pathway enrichment analysis. METHOD We developed a stand-alone graph database using Neo4j for primary-recurrent paired GBMs, integrating clinical and gene expression data from the Glioma Longitudinal AnalySiS (GLASS) Consortium and internal MD Anderson cohort. Based on log2 fold-change, we used hierarchical trees for differentially expressed genes to decompose the expression profile. Nodes in the database represent patients with considerable absolute log2 values determined by hierarchical trees, while shared patients define the edges. We applied graph algorithms such as degree centrality and community detection to identify potential biomarkers and supplemented these analyses with pathway identification to refine the biomarker list. Further, we divided the data set into 80% training and 20% testing sets. We evaluated the predictive performance of these biomarkers using machine learning models, including logistic regression, random forest, SVM, and neural networks. RESULTS DEG analysis revealed 33 down-regulated and 418 up-regulated genes in recurrent tumors. The top enriched pathways included neuroactive ligand-receptor interaction and GPCR ligand binding. Our database approach implicated 35 out of 451 genes as significant drivers of recurrence in IDH wild-type GBM. The prediction performance of these biomarkers was comparable to features selected through methods such as mRMR and logistic lasso and target identification methods like WGCNA. CONCLUSION Our innovative systems biology approach reveals that ligand-receptor interactions are crucial in driving recurrence in IDH wild-type GBM. This method also yielded promising mechanistic targets for recurrence, prompting focused and therapeutically relevant functional analyses. Moreover, this methodology is not limited to our study but can be applied in other multi-omics settings, offering a robust tool for biomarker discovery and validation.

CTNI-29. A PHASE 1B STUDY TO EVALUATE THE SAFETY, PHARMACOKINETICS, AND OBJECTIVE RESPONSE OF LP-184 ALONE AND IN COMBINATION WITH SPIRONOLACTONE IN IDH WILD TYPE GLIOBLASTOMA AT FIRST PROGRESSION

Abstract LP-184 is a fully synthetic small molecule alkylator of the acylfulvene therapeutics class that induces DNA double-strand breaks and improves survival in orthotopic GBM xenograft models. In preclinical studies, LP-184 is brain penetrant with a brain tumor/plasma concentration ratio of 0.2. DNA damage induced by acylfulvenes is repaired via transcription-coupled nucleotide excision repair (TC-NER) mediated by ERCC complexes. GBM with intrinsic or pharmacologically induced DNA Damage Repair deficiency (dDDR) may preferentially respond to LP-184, independent of MGMT status. LP-184 is currently under investigation in a first-in-human Phase 1a dose-escalation safety study (NCT05933265) in adult patients with advanced solid tumors including GBM, with no dose-limiting toxicities to date at dose level 6. Following determination of the Maximum Tolerated Dose and/or Recommended Phase 2 Dose from Phase 1a, the selected expansion dose will be assessed in a Phase 1b study to evaluate the safety, pharmacokinetics, and objective response of LP-184 alone and in combination with spironolactone in IDH wild type glioblastoma at first progression. Spironolactone is a brain penetrant FDA approved agent that proteolytically degrades the TC-NER component ERCC3, thereby creating dDDR. Two rGBM cohorts will be enrolled according to a Simon’s 2-stage optimal design: (i) LP-184 alone (days 1 and 8 in a 21-day cycle, as intravenous infusion over 30 minutes) and (ii) combination of LP-184 and spironolactone (200 mg orally daily in conjunction and before the LP-184 infusion). In the first stage, 10 response evaluable subjects will be enrolled. If 1 or more of the first 10 response evaluable subjects achieve an objective response, 19 further subjects may be accrued in the second stage. In each cohort, at least 5 subjects will undergo planned tumor resection and will be treated with LP-184 or the combination the day prior to surgery to evaluate PK/PD.

BIOM-63. LONG-TERM SURVIVAL AND MOLECULAR CHARACTERIZATION OF IDH-WILDTYPE GLIOBLASTOMA IN AN ASIAN COHORT

Abstract BACKGROUND Glioblastoma (GB), the most aggressive form of brain tumor, presents a significant clinical challenge with a devastating prognosis. Globally, the median overall survival (OS) for GB is typically 12-15 months, largely due to its inherent resistance to chemotherapy and radiotherapy. However, some patients exhibit prolonged survival, and their specific demographic and genomic characteristics remain poorly defined. Understanding the clinical profile of these exceptional responders holds great promise for informing improved management strategies for GB. METHODS In a retrospective two-center study conducted in Hong Kong (IRB: UW 21-189), we recruited 80 patients diagnosed with IDH wildtype glioblastoma. All patients underwent next-generation sequencing as part of their treatment. Long-term survivor (LTS) was defined as &amp;gt;=36 months from diagnosis, while medium-term survivor (MTS) was defined as &amp;gt;=18 months, and &amp;lt;18 months as short-term survivors (STS). When appropriate, descriptive statistics were used to report frequency with percentage or median with range. Fisher’s exact test was employed to analyze categorical variables, while continuous variables were assessed using the Kruskal-Wallis test. All statistical analyses were conducted using R (version 4.2.3). Result: Among the cohort of 80 recruited patients, the median survival was 18.8 months (95% CI 17.2-24.8). Notably, 21% (n=17) were LTS, 31% (n=25) were MTS, and 48% (n=38) were STS. A statistically significant variation (p &amp;lt; 0.05) was evident across three groups: gender distribution, the number of resections performed, the proportion of patients receiving genomic-guided treatment, and their participation in clinical trials. However, no significant difference was observed in MGMT promoter status and ECOG score. CONCLUSION Identifying these clinical factors enhances the clinical management of GB. The implications of these findings underscore the potential importance of incorporating genomic-guided treatment in both local and global clinical practices in GB.

INNV-04. SINGLE INSTITUTION RETROSPECTIVE STUDY TO DETERMINE TIME TO FIRST PROGRESSION IN MGMT METHYLATED GLIOBLASTOMA PATIENTS WHO RECEIVED STANDARD OF CARE

Abstract MGMT methylated glioblastomas respond well to standard of care with temozolomide, have a longer survival as well as increased risk of pseudo-progression as compared to unmethylated patients. Shorter survival in these patients despite effective treatments is due to misdiagnosis of true progression (in cases with pseudo-progression) that leads to overtreatment or discontinuation of effective treatments. There are limited non-invasive diagnostic tools to distinguish true progression from pseudo-progression. Knowing the expected time to first true progression will aid with interpretation of MRI changes and serve as an additional tool to distinguish true from pseudo-progression. OBJECTIVE We sought to define the time to first progression in MGMT methylated glioblastoma patients who were treated with standard of care/Stupp protocol (this has not been previously defined). METHODS We conducted a retrospective analysis of an IRB-approved database at our institution from 2019 to 2022 of all MGMT methylated glioblastoma patients who completed Stupp protocol. Time to first progression (time from initial surgery to first true progression) was determined by treating multidisciplinary team based on radiographic review +/- pathology. Eligible MGMT methylated glioblastoma patients had IDH status determined by NGS and completed standard Stupp protocol after surgery. RESULTS Approximately 30% (27) patients with IDH wild-type glioblastoma were MGMT methylated. 10 patients met eligibility criteria. 50% of MGMT methylated GBM patients had multifocal disease at presentation. Median time to first progression in MGMT methylated GBM who received standard of care was 28 months. 20% patients have not had first progression 3 years after initial surgery. CONCLUSION MRI changes on surveillance scans should be carefully interpreted in the first 28 months. Knowing time to first true progression will aid with management decisions and decrease unnecessary early aggressive interventions in MGMT methylated glioblastoma patients. We will validate these findings in a larger patient population at our institution.

Postoperative Karnofsky performance status prediction in patients with IDH wild-type glioblastoma: A multimodal approach integrating clinical and deep imaging features.

Glioblastoma is a highly aggressive brain tumor with limited survival that poses challenges in predicting patient outcomes. The Karnofsky Performance Status (KPS) score is a valuable tool for assessing patient functionality and contributes to the stratification of patients with poor prognoses. This study aimed to develop a 6-month postoperative KPS prediction model by combining clinical data with deep learning-based image features from pre- and postoperative MRI scans, offering enhanced personalized care for glioblastoma patients. Using 1,476 MRI datasets from the Brain Tumor Segmentation Challenge 2020 public database, we pretrained two variational autoencoders (VAEs). Imaging features from the latent spaces of the VAEs were used for KPS prediction. Neural network-based KPS prediction models were developed to predict scores below 70 at 6 months postoperatively. In this retrospective single-center analysis, we incorporated clinical parameters and pre- and postoperative MRI images from 150 newly diagnosed IDH wild-type glioblastoma, divided into training (100 patients) and test (50 patients) sets. In training set, the performance of these models was evaluated using the area under the curve (AUC), calculated through fivefold cross-validation repeated 10 times. The final evaluation of the developed models assessed in the test set. Among the 150 patients, 61 had 6-month postoperative KPS scores below 70 and 89 scored 70 or higher. We developed three models: a clinical-based model, an MRI-based model, and a multimodal model that incorporated both clinical parameters and MRI features. In the training set, the mean AUC was 0.785±0.051 for the multimodal model, which was significantly higher than the AUCs of the clinical-based model (0.716±0.059, P = 0.038) using only clinical parameters and the MRI-based model (0.651±0.028, P<0.001) using only MRI features. In the test set, the multimodal model achieved an AUC of 0.810, outperforming the clinical-based (0.670) and MRI-based (0.650) models. The integration of MRI features extracted from VAEs with clinical parameters in the multimodal model substantially enhanced KPS prediction performance. This approach has the potential to improve prognostic prediction, paving the way for more personalized and effective treatments for patients with glioblastoma.

DISP-17. OUTCOMES, CLINICAL AND MOLECULAR CHARACTERISTICS OF HISPANIC PATIENTS WITH IDH WILDTYPE GLIOBLASTOMA

Abstract BACKGROUND Knowledge about outcomes in Hispanic patients with gliomas is scant and mainly derived from tumor registries. IDH wild-type glioblastomas (GBM) are the most common and aggressive malignant primary brain tumor. Hispanics account for 19% of US population, reaching 29% in Florida and 65% in Miami-Dade County. As a reference center for GBM serving the community of South Florida we provide care for many Hispanic patients. Herein, we aim to describe the clinical and molecular features, including RNA seq analysis of Hispanic vs non-Hispanic patients with IDH wild-type GBM. METHODS Retrospective study of adult patients with diagnosis of IDH Wild-type Glioblastoma, who had NGS testing, treated at University of Miami. RESULTS 179 patients were included, 63 (35%) were Hispanic. 41 (65%) of Hispanic patients were males as compared to 65 (56%) of the non-Hispanics. Median age at diagnosis was 54 years (45-67) for the Hispanic vs 62 (54-72) years for non-Hispanic, p=.002. With a median follow up of 17 months (CI 95% 14-19), median overall survival for Hispanic patients was 22 months (18-25) and 23 months (18-28) for non-Hispanics, p=.99. 42 (23%) patients were enrolled in clinical trials, of whom 21 (50%) were Hispanic, meaning 33% of Hispanic patients enrolled. The molecular characteristics from these patients by next-generation sequencing, including RNA seq, are being analyzed. CONCLUSIONS In our series of IDH wild-type Glioblastomas, Hispanic patients were significantly younger at diagnosis compared to non-Hispanic patients, but there were no differences in overall survival. 33% of Hispanic patients were enrolled in clinical trials. As the latest growing ethnic group in the USA, major efforts have to be made to better understand the disease characteristics and outcomes of this particular population. To our knowledge this will be the first report of the molecular characteristics by NGS from Hispanic patients with GBM.

TMIC-53. USE OF CEREBRAL OPEN-FLOW MICROPERFUSION TO IDENTIFY POTENTIAL ONCOMETABOLITE, L-2-HYDROXYGLUTARATE, IN GLIOBLASTOMA CHEMOTHERAPY ADAPTATION

Abstract Glioblastoma (GBM) is among the most prevalent and lethal brain tumors, comprising nearly half of all central nervous system malignancies and imparting a median overall survival of only 18-20 months. One major challenge in curing this disease is the limited understanding of how GBM cells biologically respond to treatments like radiotherapy and chemotherapy, including temozolomide (TMZ), in real-time. A significant challenge is observing changes within the tumor interstitial fluid (ISF), which mediates adaptive intercellular signaling between tumor cells and their surrounding tumoral and stromal neighbors. Microfluidic sampling methods, such as cerebral microdialysis and microperfusion, have started to provide valuable insights into the ISF signaling dynamics. These methods enable real-time biomolecular monitoring of this often-neglected component of the tumor microenvironment (TME). We have performed in vivo cerebral open-flow microperfusion (cOFM) pilot studies to identify metabolomic and proteomic changes within the tumor ISF resulting from differential treatment with either TMZ or vehicle control. Among these metabolite and protein changes, we identified an increase in 2-hydroxyglutarate (2-HG). While D-2-HG is a hallmark metabolite of isocitrate dehydrogenase mutant (IDH-mut) tumors, our model utilized the IDH wild-type (IDH-WT) CT2A mouse-syngeneic glioma model. Subsequent analysis of enantiomeric confirmation characterized this to be predominantly L-2-HG. Follow-up in vitro studies have shown that elevated L-2-HG plays a functional role in IDH-WT patient-derived glioma cells via non-canonical HIF1α stabilization and subsequent expression of HRE genes. This suggested that L-2-HG may play a similar role in IDH-WT GBM as D-2-HG plays in IDH-mutant tumors. This study demonstrates the potential of L-2-HG to function as a chemo-responsive oncometabolite in the TME of highly aggressive IDH-WT glioblastoma. By targeting the metabolic and signaling properties of L-2-HG, it may be possible to prevent chemo-resistant adaptations mounted by GBM cells when treated with TMZ.

EXTH-08. IVOSIDENIB THERAPY FOR IDH-MUTANT WHO GRADE 4 ASTROCYTOMA

Abstract BACKGROUND Isocitrate Dehydrogenase (IDH) is a commonly mutated gene in gliomas, present in approximately 10% of high-grade gliomas. Its oncometabolite, D-2-hydroxyglutarate, has been implicated in promoting gliomagenesis and epileptogenesis. IDH-1 or IDH-2 mutations confer a more favorable prognosis in gliomas than wildtype IDH, leading to the differentiation between IDH-wild type glioblastoma and IDH-mutant WHO Grade 4 astrocytoma. Although IDH-mutant WHO Grade 4 astrocytomas tend to occur in younger patients and show an improved survival, prognosis remains poor and treatment options are limited. Ivosidenib is a small molecule inhibitor of IDH-1 that has shown promise for treating low-grade IDH-mutant glioma. However, little is known about its efficacy in IDH-mutant WHO Grade 4 astrocytoma. METHODS We present a retrospective case of a 38-year-old male with a WHO Grade 4 astrocytoma. Molecular characterization revealed that it was IDH-mutant, MGMTp methylated, and 1p/19q co-deleted. It was treated with ivosidenib at second recurrence. He was originally treated with gross total resection, followed by radiation and 6 cycles of adjuvant temozolomide. At the time of 1st progression (approximately 19 months postoperatively), he was treated with lomustine at 90mg/m2 but progressed after 2 cycles. Here we report the effects of off label use of ivosidenib. RESULTS Radiological surveillance showed interval decrease in tumor size starting two months after initiation of ivosidenib. The patient remained neurologically intact and no adverse effects were observed. A review of the literature revealed only three studies analyzing the effects of ivosidenib in IDH-mutated WHO Grade 4 astrocytomas with varying results. CONCLUSION The INDIGO trial published last year showed evidence of efficacy in using an IDH inhibitor for low-grade gliomas. The role of these drugs in high-grade IDH-mutated gliomas is currently unknown. Further studies are needed to assess their efficacy in overall and progression free survival, specifically in IDH-mutated WHO Grade 4 astrocytoma.

TMET-11. IMPACT OF METABOLIC RISK FACTORS ON SURVIVAL IN GLIOBLASTOMA IDH-WILD TYPE

Abstract Altered cellular metabolism is a hallmark of cancer. Systemic metabolic dysregulation has been associated with the pathogenesis of cancer, including glioblastoma. In particular, the metabolic syndrome has been found to increase the risk of developing various systemic cancers, but it is not known how often the metabolic syndrome occurs in patients with glioblastoma or how it affects their clinical outcomes. This study retrospectively investigates the prevalence and impact of metabolic syndrome, and its component risk factors, on survival in patients with glioblastoma IDH-wild type. Interim analysis includes results from 73 patients with anticipation of over 100 patients who received treatment at UC Davis between 2018-2024. Metabolic syndrome prevalence prior to diagnosis was 41% (30/73), higher than the prevalence of 33% in the general population. Patients with metabolic syndrome showed a trend towards reduced overall survival. A significant dose-response association was found between the number of metabolic risk factors and overall survival (p=0.03). Hyperglycemia demonstrated worsened survival (p=0.04), aligning with prior studies. Obesity, hypertension, and dyslipidemia were not significantly associated with survival. These findings highlight the therapeutic potential for targeting systemic metabolic dysregulation, and hyperglycemia in particular, in patients with glioblastoma.

NIMG-58. MACHINE LEARNING-GENERATED WHOLE-BRAIN RADIO-PATHOMIC TUMOR PROBABILITY MAPS WITHIN CONTRAST-ENHANCEMENT STRATIFY SURVIVAL IN GLIOBLASTOMA PATIENTS UNDERGOING GROSS-TOTAL RESECTION

Abstract BACKGROUND Even for those undergoing gross total resection (GTR), patients with WHO grade 4 glioblastoma (GBM) have poor overall survival (OS). Stratifying those who will have better OS vs. those that will not remains challenging, with conventional imaging and radiomic models falling short. This study utilizes machine learning (ML)-generated radio-pathomic models based on autopsy tissue as ground-truth to enhance prognostication through tumor probability maps (TPM) within preoperative contrast-enhancing (CE) regions of GBM. METHODS Data from the UCSF-PDGM-v2 and UPenn-GBM databases were analyzed, focusing on patients who underwent GTR with WHO 4 IDH-wildtype glioblastoma (n = 528). Preoperative tumor cellularity within CE was quantified using ML-generated TPMs, with a median threshold of 0.7242. Kaplan-Meier survival curves were employed to compare OS between patients with low (≤ 0.7242) and high (&amp;gt; 0.7242) TPM values in CE regions. Statistical significance was evaluated using log-rank tests. RESULTS Kaplan-Meier curves demonstrated significant stratification in survival outcomes based on TPM values. Patients with lower TPM values in CE regions had a median OS of 567 days, compared to 457 days for those with higher TPM values (log-rank p-value: &amp;lt; 0.001). These findings suggest that lower tumor cellularity in CE regions as assessed by TPMs correlates with improved survival, offering a more nuanced stratification than current MRI-based methods. CONCLUSION This study underscores the potential of TPM metrics as a powerful prognostic tool in GBM. The significant correlation between lower TPM values in CE regions and better median OS indicates that TPM can effectively stratify patients, aiding in clinical decision-making and personalized treatment planning. Future research is necessary to validate these findings in larger, diverse patient populations and to explore the biological mechanisms underlying these survival differences.

CTNI-31. AI-GUIDED PERSONALIZED PRECISION RADIATION THERAPY WITH TARGETED DOSE ESCALATION FOR NEWLY DIAGNOSED GLIOBLASTOMA: A MATCHED-CONTROL STUDY

Abstract BACKGROUND The purpose of this study was to assess the feasibility and effectiveness of AI-guided personalized precision radiation therapy (PPRT) with targeted dose escalation in enhancing outcomes for patients with newly diagnosed glioblastoma. METHODS An open-label trial was conducted at the University of Pennsylvania (NCT03477513) from August 2018 to April 2023, enrolling 20 patients with IDH-wildtype glioblastoma who underwent maximal safe resection. They were matched with a contemporaneous cohort of glioblastoma patients based on age, sex, extent of resection (EOR), O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation status, and IDH status. Propensity score matching (PSM) was employed to select the control group, utilizing one-to-four nearest neighbor matching. One patient was excluded due to concurrent treatment with tumor treating fields (TTFields). The PPRT group received personalized radiation dose escalation to 75 Gy in 30 fractions guided by AI-based predictive modeling of recurrence, along with temozolomide chemotherapy. The control group received standard-of-care chemoradiotherapy, 60 Gy in 30 fractions. A previously published and evaluated (retrospectively and prospectively) predictive AI model, which has demonstrated high predictive value for neoplastic cell infiltration and future tumor recurrence using preoperative, multi-parametric MRIs, was utilized. RESULTS Median overall survival was 24.3 months in the PPRT-temozolomide group compared to 17.5 months in the standard-of-care treatment group (hazard ratio [HR]=0.30; 95% CI: 0.16-0.57; p&amp;lt;0.001). Excluding two patients with leptomeningeal disease and bone marrow metastasis, the median survival was 35.4 months (HR=0.25; 95% CI: 0.12-0.51; p&amp;lt;0.001). CONCLUSION AI-guided PPRT for newly diagnosed glioblastoma patients demonstrated feasibility in routine clinical practice and significantly improved overall survival compared to matched controls receiving standard-of-care treatment. These findings underscore the potential of personalized precision radiation therapy, with focused dose escalation, in improving outcomes for glioblastoma patients and emphasize the need for prospective validation in a randomized controlled clinical trial.