Tumor Region Research Articles

SURGICAL RESECTION OF A COMPLEX TUBERCULUM SELLAE MENINGIOMA ENCASING MAJOR ARTERIES

Introduction Though constituting only a minor proportion (1%) of sellar masses, suprasellar meningiomas pose a significant diagnostic challenge within the region of sellar and suprasellar tumors. Pituitary adenomas, at nearly 90% prevalence, dominate this anatomical region. Distinguishing these two entities is paramount, as both clinical presentation and, to some extent, biochemical profiles exhibit notable overlap. Accurate preoperative differentiation is critical due to the contrasting behaviors of these tumors. Meningiomas, with their robust vascularity supplied by dural and osseous arteries, present a heightened risk of intraoperative hemorrhage. Clinical Case A 53-year-old woman presented with a two-month history of worsening headaches and gradual vision loss. Neurological examination revealed only visual acuity decline. Her hormone profile showed elevated prolactin but lacked clinical features of prolactin excess, suggesting a possible prolactin-secreting pituitary macroadenoma. A contrast-enhanced MRI confirmed a significant sellar and suprasellar mass with homogeneous enhancement, extending to the right paramedian region and encasing the right internal carotid artery (ICA) at its critical segment involving the cavernous and supraclinoid portions. Furthermore, the right middle meningeal artery (M1) and anterior cerebral artery (A1) originated from this same location, highlighting the high surgical risk. Surgical resection was deemed necessary. The patient underwent a right pterional craniotomy, revealing a grayish, extradural soft mass lesion encasing the ICA bifurcation. Careful microsurgical dissection with basal devascularization was performed, followed by near-complete tumor removal using an ultrasonic aspirator to minimize damage to the encased arteries. Postoperative follow-up CT scan confirmed successful near-total tumor ablation. Conclusion This case underscores the critical role of meticulous preoperative diagnosis in managing complex sellar tumors. While pituitary adenomas dominate this region, suprasellar meningiomas, despite their rarity, demand a high index of suspicion. Overlapping clinical and biochemical presentations highlight the reliance on advanced imaging for accurate differentiation. The intricate vascularity of meningiomas, as exemplified by the encasement of critical arteries in this case, necessitates meticulous surgical technique with devascularization strategies. This successful near-complete tumor removal emphasizes the importance of such surgical expertise in navigating these diagnostically challenging sellar lesions.

Abstract A026: A novel ddPCR detects hypermethylated RASSF1A in plasma of patients with pediatric Wilms tumor

Abstract Background: Wilms tumor is the most common pediatric renal cancer. Within the SIOP-Renal Tumor Study Group (SIOP-RTSG), diagnosis is based on imaging and patients receive neo- adjuvant treatment. Final diagnosis is established via histopathological analysis at the timepoint of surgery, which also determines the intensity of adjuvant treatment. Overall, patients with Wilms tumor have a 90% survival rate, but one in five patients will suffer from a relapse, which requires intensive treatment and induces long-term toxicity. It is challenging to identify patients at risk of suffering from relapse at initial diagnosis. Hence the need for additional biomarkers that will optimize risk stratification and minimal residual disease monitoring. RASSF1A is a tumor suppressor gene that is silenced via hypermethylation of its promotor region in multiple adult and pediatric tumors and is reported to represent an aggressive phenotype. We have previously reported on thirteen patients with Wilms tumor where increased hypermethylation of RASSF1A (RASSF1A-M) was observed in plasma cell-free DNA (cfDNA). The aim of this study was to further investigate the levels of RASSF1A-M in a larger cohort. Methods: The presence of RASSF1A-M in plasma cfDNA of patients with Wilms tumor was quantified using a multiplexed droplet digital PCR comprising methylation-specific restriction enzymes. Diagnosis and pre- surgery samples were included to evaluate RASSF1A-M levels during treatment. Results: A total of 49 patients were evaluated. At diagnosis, 37/46 (80.4%) samples were positive for RASSF1A-M. Negative samples were from patients with localized disease (N=6), regressive type regionally advanced Wilms (N=1) or mixed type metastatic Wilms (N=2). RASSF1A-M levels were significantly elevated in regionally advanced and metastatic disease compared to localized disease. Of the 37 positive diagnosis samples, 23 pre-surgical follow-up samples were available. In 7/23, RASSF1A-M was still detectable. These belong to patients with stromal-, regressive- or diffuse anaplastic predominant tumors. Interestingly, an increasing methylation level was seen in one patient with a regressive tumor. Conclusion: RASSF1A-M is a potential biomarker for patients with Wilms tumor, since it was detected in the majority of patients. Furthermore, significantly increased levels were observed in regionally advanced and metastatic disease. In the small number of patients with persisting levels of RASSF1A-M, we did not observe an association with risk groups. In collaboration with SIOP-RTSG, additional follow-up samples will be analyzed to explore the potential of RASSF1A-M as biomarker for relapse detection. Citation Format: Julia Sprokkerieft, Nathalie S.M. Lak, Zeinab van Gestel-Fadaie, Marry M. van den Heuvel-Eibrink, Godelieve A.M. Tytgat. A novel ddPCR detects hypermethylated RASSF1A in plasma of patients with pediatric Wilms tumor [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A026.

HRCUNet: Hierarchical Region Contrastive Learning for Segmentation of Breast Tumors in DCE‐MRI

ABSTRACTSegmenting breast tumors from dynamic contrast‐enhanced magnetic resonance images is a critical step in the early detection and diagnosis of breast cancer. However, this task becomes significantly more challenging due to the diverse shapes and sizes of tumors, which make it difficult to establish a unified perception field for modeling them. Moreover, tumor regions are often subtle or imperceptible during early detection, exacerbating the issue of extreme class imbalance. This imbalance can lead to biased training and challenge accurately segmenting tumor regions from the predominant normal tissues. To address these issues, we propose a hierarchical region contrastive learning approach for breast tumor segmentation. Our approach introduces a novel hierarchical region contrastive learning loss function that addresses the class imbalance problem. This loss function encourages the model to create a clear separation between feature embeddings by maximizing the inter‐class margin and minimizing the intra‐class distance across different levels of the feature space. In addition, we design a novel Attention‐based 3D Multi‐scale Feature Fusion Residual Module to explore more granular multi‐scale representations to improve the feature learning ability of tumors. Extensive experiments on two breast DCE‐MRI datasets demonstrate that the proposed algorithm is more competitive against several state‐of‐the‐art approaches under different segmentation metrics.

An insight to PDAC tumor heterogeneity across pancreatic subregions using computed tomography images

Pancreatic Ductal Adenocarcinoma (PDAC) is an exceptionally deadly form of pancreatic cancer with an extremely low survival rate. From diagnosis to treatment, PDAC is highly challenging to manage. Studies have demonstrated that PDAC tumors in distinct regions of the pancreas exhibit unique characteristics, influencing symptoms, treatment responses, and survival rates. Gaining insight into the heterogeneity of PDAC tumors based on their location in the pancreas can significantly enhance overall management of PDAC. Previous studies have explored PDAC tumor heterogeneity across pancreatic subregions based on their genetic and molecular profiles through biopsy-based histologic assessment. However, biopsy examinations are highly invasive and impractical for large populations. Abdominal imaging, such as Computed Tomography (CT) offers a completely non-invasive means to evaluate PDAC tumor heterogeneity across pancreatic subregions and an opportunity to correlate image feature of tumors with treatment outcome and monitoring. In this study, we explored the inter-tumor heterogeneity in PDAC tumors across three primary pancreatic subregions: the head, body, and tail. Utilizing contrast-enhanced abdominal CT scans and a thorough radiomic analysis of PDAC tumors, several morphological and textural tumor features were identified to be notably different between tumors in the head and those in the body and tail regions. To validate the significance of the identified features, a machine learning ML model was trained to automatically classify PDAC tumors into their respective regions i.e. head or body/tail subregion using their CT features. The study involved 200 CT abdominal scans, with 100 used for radiomic analysis and model training, and the remaining 100 for model testing. The ML model achieved an average classification accuracy, sensitivity, and specificity of 87%, 86%, and 88% on the testing scans respectively. Evaluating the heterogeneity of PDAC tumors across pancreatic subregions provides valuable insights into tumor composition and has the potential to enhance diagnosis and personalize treatment based on tumor characteristics and location.

MCRANet: MTSL-based connectivity region attention network for PD-L1 status segmentation in H&E stained images

The quantitative analysis of Programmed death-ligand 1 (PD-L1) via Immunohistochemical (IHC) plays a crucial role in guiding immunotherapy. However, IHC faces challenges, including high costs, time consumption and result variability. Conversely, Hematoxylin-Eosin (H&E) staining offers cost-effectiveness, speed, and stable results. Nonetheless, H&E staining, which solely visualizes cellular morphological features, lacks clinical applicability in detecting biomarker expressions like PD-L1. Substituting H&E staining for IHC in determining PD-L1 status is a clinically significant and challenging task. Motivated by above observations, we propose a Multi-Task supervised learning (MTSL)-based connectivity region attention network (MCRANet) for PD-L1 status segmentation in H&E stained images. To reduce interference from non-tumor areas, the MTSL-based region attention is proposed to enhances the network's capability to distinguish between tumor and non-tumor regions. Consequently, this augmentation further improves the network's segmentation efficacy for PD-L1 positive and negative regions. Furthermore, the PD-L1 expression regions demonstrate interconnection throughout the tissue section. Leveraging this topological prior knowledge, we integrate a connectivity modeling module (CM module) within the MTSL-based region attention module (MRA module) to enhance the precision of MTSL-based region attention localization. This integration further improves the structural similarity between the segmentation results and the ground truth. Extensive visual and quantitative results demonstrate that our supervised-learning-guided MRA module produces more interpretable attention and the introduced CM module provides accurate positional attention to the MRA module. Compared to other state-of-the-art networks, MCRANet exhibits superior segmentation performance with a dice similarity coefficient (DSC) of 79.6 % on the lung squamous cell carcinoma (LUSC) PD-L1 status dataset.

NIMG-79. A RADIOMIC-RISK SCORE FOR SURVIVAL PREDICTION IN GLIOMA: A LARGE MULTI-INSTITUTIONAL RETROSPECTIVE VALIDATION STUDY

Abstract Gliomas have dismal survival. Recently, radiomics has demonstrated success in developing non-invasive image-based biomarkers for survival prediction in gliomas. However, clinical applicability of radiomics-based biomarkers will ultimately require rigorous validation on large, multi-institutional data. This work attempts to evaluate a radiomic-based survival risk-assessment prognostic score on a multi-institutional cohort of Glioma patients. Our rationale is that optimizing and validating radiomic features that capture intensity-based textural variations and morphology-based changes (e.g., local curvature and global contour) on large multi-institutional cohorts can allow for robust risk assessment in Glioma. n=668 pre-operative T1w MRI scans for Glioma patients from 4 cohorts: University of California San Francisco “UCSF” (n=495), LUMIERE (n=86)), xCures (n=13), and Cleveland Clinic (CCF) (n=74) were analyzed. Subjects from UCSF, CCF, and xCures were used for training, whereas the LUMIERE cohort was used for hold-out testing. Following pre-processing, expert-vetted tumor segmentation into Edema (ED) and Enhancing tumor (ET) regions was performed. A total of n=1558 radiomic features were extracted from the tumor regions (779 per region), namely, 31 global contour, 20 curvature-based, 624 gradient co-occurrence statistics, and 104 Collage features. Cox regression model was employed to create a radiomic risk score (RRS) for every subject, which included radiomics features as well as on clinical and demographic variables (IDH, MGMT, sex, age), for survival analysis. RRS incorporated a total of 43 radiomic features, and the associated clinical and demographic variables (CDS), yielding significant differences between high and low risk groups in the training (RRS: p=0.043, HR = 2, CSD: p=0.0031, HR = 2.8) and testing sets (RRS: p=0.0096, HR = 1.8, CSD: p=0.0071, HR = 1.8). Combining RRS and CDS improved the OS prediction at group level (p=3.6e-6, 0.0011, HR=5.4, 2, for training and testing, respectively). Radiomics-based risk-stratification may be promising for reliable risk-stratification in glioma.

DDDR-05. SPATIALLY RESOLVED DRUG SENSITIVITY PROFILING IN GLIOBLASTOMA

Abstract BACKGROUND Glioblastoma is the most common malignant primary brain tumor in adults, characterized by poor overall survival and an urgent need for more effective treatment strategies. Macroscopic heterogeneity, as observed through MR imaging, divides the tumor into distinct regions: a tumor-cell dense contrast-enhancing tumor core and a non-contrast-enhancing infiltration zone that appears hyperintense on T2/FLAIR imaging. The infiltration zone contains both infiltrating tumor cells and non-malignant cells from the local brain microenvironment. Although genomic and transcriptomic differences between the tumor core and the infiltration zone have been reported, functional differences, such as differential drug sensitivities, remain largely unknown. METHODS To investigate this, we collected region-specific glioblastoma patient tissue samples from both the contrast-enhancing tumor core and the non-contrast-enhancing but 5-aminolevulinic acid (5-ALA) fluorescent infiltration zone during surgery. Using pharmacoscopy, a microscopy-based single-cell drug screening platform, we assessed drug responses across regions and patients. RESULTS To determine whether drug responses within a single tumor region were more similar compared to responses across different regions we collected multiple tissue samples from each tumor region in seven patients. We identified region-specific drug responses for temozolomide and lomustine, among other drugs, in some of the patients. However, drug sensitivities were not consistent within the same region across different patients. Thus, across patients, the region-specific drug responses were obscured by patient heterogeneity. To address intra- and inter-tumor drug response heterogeneity, we developed a complementarity score based on region-specific drug response data of 60 drugs across 23 paired samples. The complementarity score identified promising drug combinations that demonstrated strong anti-tumor activity across tumor regions and patients. CONCLUSIONS Monotherapy approaches have largely failed in glioblastoma, despite extensive molecular profiling efforts aimed at identifying tumor-specific vulnerabilities. Identifying drug combinations that synergistically target the locoregional heterogeneity of glioblastoma may open up new avenues of personalized therapy.

EPCO-40. TRANSCRIPTIONAL TRAJECTORY INFERENCE OF IMAGE-LOCALIZED, MULTI-REGIONAL HIGH-GRADE GLIOMA BIOPSIES REVEALS DISTINCT POPULATION ECOLOGIES AND SEX-ASSOCIATED ENRICHED PATHWAYS

Abstract The intra- and inter-patient heterogeneity in high-grade glioma (HGG) continues to contribute to its poor prognosis. Clinical biopsies are often harvested from limited regions and typically are not image localized. Thus, they fail to capture the diversity within tumor regions, immune expression or normal cell abundances that play key roles in tumor development. It is important to gain an understanding of these subpopulation ecologies, their spatial resolution, and interactions between them that may then be exploited for future therapeutic benefit. Further, these may differ by patient characteristics such as sex, age at diagnosis and treatment status. Using an ongoing image-localized biopsy collection protocol, we have so far evaluated the bulk transcriptomics of 202 multi-regional biopsies from 58 patients to characterize HGG heterogeneity. These samples were processed through Monocle, a reverse graph embedding algorithm that groups samples into states and orders them along developmental trajectories. Deconvolution methods were previously used to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell subpopulations for each sample, which we have now overlaid on the Monocle graph. Monocle classified HGG into 4 main states along a three-pronged trajectory. These states reveal distinct population ecologies with associated enriched gene pathways. We also note significant immune pathway enrichments that differ between state and patient-reported sex. Together, these algorithms reveal a simple transcriptomic trajectory that helps us understand the development and evolution of HGG. Characterizing the in vivo diversity within and between high grade gliomas is important for understanding prognosis, stratifying future treatments and ultimately improving patient outcome.

TMIC-25. MICROGLIA IN THE GLIOBLASTOMA MICROENVIRONMENT SECRETE ACETYLATED AMINO ACIDS WHICH ASSIST IN THE REPAIR OF RADIATION INDUCED DNA DAMAGE

Abstract Rapid repair of DNA damage mediates genotoxic therapy resistance and poor prognosis in glioblastoma (GBM). The GBM tumor microenvironment (TME) is heterogenous, and we hypothesized that non-malignant cells support the repair of DNA damage in glioblastoma cells. Consistent with this hypothesis, we found that GBM tumors grown intracranially in mice had rapid DNA repair and were resistant to radiation compared to tumors of identical genotype grown extracranially in mouse flanks. Further interrogation of irradiated intracranial tumors using gamma-H2AX immunofluorescence revealed spatial heterogeneity in DNA damage repair, with spatially separate regions of rapid and slow gamma-H2AX resolution. Paired spatial transcriptomic analysis and gamma-H2AX immunofluorescence showed that tumor regions with rapid DNA repair were rich in microglia. Having nominated microglia from these results, we cocultured GBM cells and microglia in direct contact as well as in transwell coculture. We found that GBM cells cocultured with microglia repair DNA damage faster in a contact-independent manner. We then assessed the supernatant metabolome of microglia and GBM monocultures and cocultures and found that acetylated amino acids are secreted by microglia and consumed by GBM cells. Supplementation with acetylated amino acids promotes radiation resistance by speeding the repair of radiation-induced DNA damage. Mechanistically, acetylated amino acid supplementation allows glioma cells to re-route glucose utilization away from the TCA cycle and towards nucleotide synthesis. Hence, we show that microglia in the GBM microenvironment assist GBM cells to repair radiation induced DNA damage by secreting acetylated amino acids which are consumed by GBM cells and used to fuel the TCA cycle allowing utilization of glucose for nucleotide synthesis, thereby making the GBM cells resistant to radiation therapy.

NIMG-75. SIMILARITY DISTANCES-BASED DELTA RADIOMICS (SDDR) ENABLES LONGITUDINAL MRI COMPARISONS FOR SURVIVAL PREDICTION IN GLIOMAS: A MULTI-INSTITUTIONAL VALIDATION

Abstract Radiomics (computerized feature analysis) on treatment-naive MRI scans has demonstrated great value in outcome prediction for Glioblastoma (GBM). However, delta radiomics (analysis of radiomic feature variation between different events, e.g., before and after treatment) has not been explored on account of challenges with precise spatial correspondences between pre- and post-operative scans. This work presents a survival prediction model for GBM, Similarity Distances-based delta radiomics (SDDR), based on the hypothesis that similarity distance-measures between radiomic features on pre-, and post-treatment images can accurately capture temporal changes within-and-around the tumor, and provide improved prediction of overall survival, compared to models based on a single timepoint. 150 patients from 2 publicly-available Glioma repositories (University of California San Francisco “UCSF” (n=48), LUMIERE (n=67)) and 2 two proprietary datasets (from xCures (n=13), and Cleveland Clinic (CCF) (n=74)) were obtained. UCSF and LUMIERE cohorts were used as separate hold-out sets, in each of which the remaining collections were used as discovery set. Following pre-processing, tumor segmentation into Edema (ED) and Enhancing tumor (ET) were performed. SDDR was then computed, which is the distance between probability densities functions from 156 gray co-occurrence (GLCM) and 52 gradient-based co-occurrences statistics (COLLAGE) features extracted from pre and-post-treatment MRI. Six statistical distances (e.g., Earth mover distance) normalized by the scanning interval (in weeks) yielded n=2496 SDDR measurements per tumor region (1248/region, 936 delta-GLCM, and 312 delta-COLLAGE). The same set of features were computed from pretreatment MRI (Pre-R) for comparison. Features were fed to LASSO-Cox regression for survival analysis. SDDR for GLCM features extracted from ET outperformed Pre-R, and demonstrated significant differences between high and low risk groups for both hold out tests: UCSF (p=0.0069, HR =2.8, C-index=0.69) and LUMIERE (p=0.0061, HR = 1.9, C-index 0.65). SDDR-based multi-institutional survival analysis demonstrated promise in reliable longitudinal risk-stratification in GBM.

EPCO-38. IDENTIFYING THE MOLECULAR SIGNATURE OF INFILTRATING EDGE IN GLIOBLASTOMA AS DRIVERS OF TUMOUR INVASION AND RECURRENCE

Abstract Complete tumour resection in glioblastoma patients is not possible. Residual therapy-resistant edge-derived cells drive tumour recurrence and infiltrative expansion in glioblastoma. Features that are specific to malignant edge-derived cells may serve as predictive biomarkers to allow individual tailoring of the treatment plan to slow down tumour invasion and prevent tumour recurrence in GBM patients following standard therapy. Intratumoural spatial heterogeneity facilitates therapeutic resistance and recurrence in glioblastoma. Our knowledge on glioblastoma heterogeneity is mostly restricted to the surgically resectable tumour core, while the functional characterization of tumour cells at the infiltrating edge remains largely elusive due to the presence of normal functional brain tissue in the peritumoural lesion. Edge-derived cells exhibit larger capacity for infiltrative expansion and are the main drivers of treatment failure and tumour recurrence, making them action targets for novel treatment approaches in glioblastoma. To resolve the transcriptional heterogeneity of GBM within the spatial context, we profiled gene expression of different tumour regions (“edge” and “core”) obtained at initial surgical resection from primary and recurrent IDH-WT GBM patients with Visium 10x and GeoMx. We show that infiltrative edge-derived cells are spatially segregated and are characterized by regionally shared distinct genomic and transcriptomic signatures that promote invasiveness and underly disease recurrence. Tumour edge is enriched for neuronal signatures, while tumour core displays larger transcriptional subpopulation diversity and abundance of proliferative cells with a high capacity for self-renewal, consistent with the proliferative and cancer stem cell-enriched phenotype in early GBM progressors. Upregulated DEGs of tumour edge cells are significantly associated with ion regulation of transport, chemical synaptic transmission, and nervous system development. These modules may represent tumour cell hijacking of neuronal programs specifically at the tumour periphery as described in the context of glioma-neuron synaptic communication and formation of neurite-like microtubes. Upregulation of ion regulation transport at the tumour periphery indicates enhanced neuronal activity and excitability driving infiltrating growth.

CTNI-55. A PHASE 0/1B STUDY OF AZD1390 PLUS RADIOTHERAPY IN NEWLY DIAGNOSED, MGMT-UNMETHYLATED AND RECURRENT GLIOBLASTOMA PATIENTS

Abstract BACKGROUND ATM inhibition is hypothesized to potentiate the effects of radiation by preventing acute phase DNA damage repair. This Phase 0/1b study evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of AZD1390, a first-in-class ATM inhibitor, in combination with radiation in newly-diagnosed and recurrent GBM patients (NCT05182905). METHODS All patients received 3 days of AZD1390 prior to planned resection at 2-4, 4-6 or 23-25 hrs following the final dose (120/300mg for nGBM and 400mg for rGBM). Tumor tissue, cerebrospinal fluid (CSF), and plasma were collected. Total and unbound drug concentrations were measured using validated LC-MS/MS methods. ATM inhibition was assessed via ex vivo tissue radiation, quantifying pRAD50 levels compared to non-radiated control. A PK ‘trigger’ determined eligibility for Phase 1b and patients exceeding the PK threshold (2 nM unbound drug levels in Gd-non-enhancing tumor region) were eligible for therapeutic dosing of AZD1390 plus radiotherapy. RESULTS Thirty nGBM patients and twenty-nine rGBM patients were enrolled. Forty-eight out of the forty-nine evaluable patients exceeded the PK threshold and qualified for therapeutic dosing. The mean unbound concentrations of AZD1390 in Gd-nonenhancing tumors of both nGBM and rGBM patients were significantly above the threshold at all dose levels and time intervals. Following 5Gy ex vivo radiation of surgical specimens, pRAD50 expression was significantly suppressed in AZD1390-treated patients compared to untreated controls. To date, 6 MGMT-unmethylated nGBM patients and 15 rGBM patients were enrolled in the Phase 1b component of the study, with median clinical follow-up of 7.0 months. Median PFS and OS have not been reached in the nGBM population. Median OS for rGBM patients was 15.4 months. CONCLUSION AZD1390 is well-tolerated in both newly-diagnosed and recurrent GBM patients, achieving pharmacologically relevant concentrations in Gd-nonenhancing tumor tissue, and suppressing radiation-induced increase in pRAD50 levels. These data are the first to demonstrate AZD1390-mediated PD and PK responses in nGBM and rGBM patients. Clinical outcomes data are maturing and will be reported.

TMIC-18. ROLE OF NEUROTRANSMITTERS IN GLIOBLASTOMA PATHOPHYSIOLOGY: EMERGING INSIGHTS

Abstract INTRODUCTION Glioblastoma (GBM) are the most common primary brain tumor in adults associated with a dismal patient outcome. While it is well-known that glutamatergic neurons can form functional synapses with glioblastoma cells to enhance tumor growth, lesser is known about the effects of activity of other neuronal types on glioblastoma biology, especially among different glioblastoma molecular subtypes. Here, we examined the effects of various neurotransmitters on the growth of glioblastoma cells characterized as classical, proneural and mesenchymal subtypes. METHODS Patient-derived glioblastoma cell lines were exposed to varying concentrations of different neurotransmitters and assessed for cell viability using CCK-8 assay. Transcriptomic data from TCGA (The Cancer Genome Atlas) database was analyzed for correlation of expression of neurotransmitter receptors (NTRs) with patient survival. Using IVY-GAP database, we compared the expression of NTRs at leading-edge versus tumor core of tumors to assess their possible involvement in cell migration and microenvironmental interactions. RESULTS Consistent with previous findings, we observed an increase in cell viability in all GBM cell lines after being incubated with L-glutamate. The classical subtype has a stronger growth response to L-glutamate compared to the other two subtypes. TCGA data revealed the expression of GRIK4 (glutamate ionotropic receptor kainate type subunit 4) as highest in the classical subtype as well as inversely correlated with worse patient survival in this GBM subtype, as opposed to proneural or mesenchymal patient groups. CCK8 assay also suggested that acetylcholine and dopamine increase glioblastoma cell growth. A subset of cholinergic and glutamatergic receptors (CHRM1, GRM2) was found upregulated in infiltrating/leading-edge regions of glioblastoma tumors compared to the tumor core, suggesting possible involvement in glioblastoma-neuron interactions. CONCLUSION Our findings suggest that GBM subtypes may differentially leverage neuro-modulatory mechanisms to support their growth. Future studies will investigate the differential neuronal responses in GBM subtypes using pharmacological/genetic approaches.

CTNI-51. A PHASE 0/1 STUDY OF BDTX-1535 IN RECURRENT GLIOBLASTOMA (GBM) PATIENTS WITH EGFR ALTERATIONS OR FUSIONS

Abstract BACKGROUND Alterations to epidermal growth factor receptor (EGFR) occur frequently in high-grade gliomas (HGG) and are critical to its pathogenesis. This Phase 0/1 study evaluates pharmacokinetic (PK), pharmacodynamic (PD), and clinical response to an ATP-competitive, irreversible EGFR inhibitor, BDTX-1535, in recurrent HGG patients with EGFR alterations and/or fusions. MATERIALS/METHODS Recurrent HGG patients with EGFR alterations (Arm A) or EGFR fusions (Arm B) received 5 days of BDTX-1535 at 200 mg/daily (cohort 1) or 400 mg/every other day (cohort 2) prior to planned resection at 2-4 hours following the final dose. In the Phase 0 component of the study, total and unbound drug concentrations were measured in tumor tissue (gadolinium (Gd) enhancing and non-enhancing regions), cerebrospinal fluid (CSF), and plasma using validated LC-MS/MS methods. A PK ‘trigger’ was defined as unbound drug concentration above 1 nM and 4.1 nM in Gd non-enhancing tumor in patients with EGFR mutations and amplification, respectively, determined eligibility for Phase 1 therapeutic dosing. PD response was assessed by quantification of percentage of positive pEGFR, pERK and MIB-1 cells in the surgical tumor tissue compared to baseline pre-treatment tissue. RESULTS Eleven recurrent HGG patients were enrolled (Arm A, n=11; Arm B, n=0). Mean unbound concentrations of BDTX-1535 in non-enhancing tumor regions were 11.9 nM and 18.8 nM in cohorts 1 and 2, respectively. Eight of nine (88.9%) evaluable patients exceeded the PK threshold and qualified for Phase 1. Suppression of pEGFR and MIB1 was observed in 55% and 67% of patients, respectively. No serious adverse events related to BDTX-1535 were observed. At the time of submission, median PFS and OS have not yet been reached. CONCLUSIONS BDTX-1535 is well-tolerated in recurrent HGG patients, achieves pharmacologically relevant concentrations in non-enhancing tumor tissue, and is associated with suppression of EGFR signaling. Efficacy data accompanying this PK/PD response will be reported.

NIMG-87. MULTIREGIONAL, MRI-LOCALIZED SAMPLING OF HIGH GRADE GLIOMAS REVEAL SEX-DISTINCT PATTERNS OF 5-ALA FLUORESCENCE AND IMAGING FEATURES

Abstract High grade gliomas (HGGs) are aggressive brain tumors that are difficult to remove completely, leading to poor survival rates. Contrast enhancement on T1Gd magnetic resonance imaging (MRI) has traditionally been used to guide resection, however it often underestimates true tumor burden, adding a layer of uncertainty for surgeons during pre-operative planning. Fluorescence guided surgery using 5-aminolevulinic acid (5-ALA) has emerged as an intraoperative solution and understanding it in conjunction with MRI features can address the limitations of routine T1Gd imaging during surgical planning. Here we investigate sex-specific patterns in HGGs using 5-ALA fluorescence and imaging features. We analyzed a patient dataset of 202 multiregional MRI-localized biopsies from 42 HGG patients (20 male and 22 female). Data included patient demographics, 5-ALA status (positive or negative), MRI annotations (CE = contrast enhancement, NE = non-enhancement, BAT = brain around tumor non-enhancement), and survival outcomes. Statistical analyses included Wilcoxon rank-sum tests, Kruskal-Wallis tests, and chi-squared tests to assess differences in imaging annotations and 5-ALA positive vs negative status among sex cohorts. Among all samples, CE and BAT were associated with higher 5-ALA positivity, while NE was associated with higher 5-ALA negativity (p = 0.02119). Female patients were less likely to have detectable 5-ALA in their multiregional biopsy samples than males (p < 0.0001). CE at the biopsy location was more likely to be indicative of 5-ALA positivity in males than females (p = 0.001927); whereas NE was associated with higher 5-ALA negativity in females than males (p = 0.03426). BAT was associated with higher 5-ALA positivity in males than females (p = 0.03895). Our study reveals sex-specific patterns in 5-ALA fluorescence and image features among HGG patients. These unique features may serve as potential pre-surgical markers for tumor regions that are more likely to benefit from 5-ALA-guided resection.

CTNI-50. CLINICAL EFFICACY AND PK/PD RESPONSE IN A PHASE 0/2 STUDY OF NIRAPARIB PLUS RADIOTHERAPY FOR NEWLY-DIAGNOSED, MGMT-UNMETHYLATED GLIOBLASTOMA

Abstract BACKGROUND Poly (ADP-ribose) polymerase (PARP) mediates DNA damage response; niraparib is a PARP1/2-selective inhibitor. This Phase 0/2 study evaluates tumor pharmacokinetics (PK), pharmacodynamics (PD), and clinical efficacy of niraparib plus fractionated radiotherapy in newly diagnosed, O6-methylguanine methyltransferase (MGMT)-unmethylated glioblastoma (GBM). METHODS Newly-diagnosed GBM patients received 4 days of niraparib (300/200 mg QD) prior to planned resection 3-5 (cohort 1) or 8-10 hours (cohort 2) following the last dose. Tumor tissue (gadolinium-enhancing and non-enhancing regions), cerebrospinal fluid (CSF), and plasma were collected. Total and unbound drug concentrations were measured using validated LC-MS/MS methods. PARP inhibition was assessed by quantification of PAR induction after ex vivo irradiation vs non-irradiated control. A PK response was defined as unbound [niraparib] > 5-fold biochemical IC50 (19 nM) in non-enhancing tumor. Patients with MGMT-unmethylated tumors and a PK response were eligible for Phase 2 dosing of niraparib plus radiotherapy followed by niraparib monotherapy. RESULTS All Phase 0 patients (n=46) met the PK threshold. The mean unbound concentrations of niraparib in non-enhancing tumor regions were 335.1 nM (cohort 1; n=43) and 331.9 nM (cohort 2; n=3). Ex vivo PAR suppression was observed in 73% of the patients (24/33). 71.4% patients with unmethylated tumors were enrolled into Phase 2. Five patients in Phase 2 experienced Grade 4 thrombocytopenia related to niraparib and all adverse events resolved without sequelae. At a mean clinical follow-up of 13.4 months, median overall survival was 20.3 months. CONCLUSIONS Niraparib achieves pharmacologically relevant concentrations in non-enhancing, newly-diagnosed GBM tissue. Accompanying PD effects were observed in tumor tissue, no new safety signals were observed, and clinical outcomes were promising. A global Phase 3, open-label, randomized 2-arm study comparing niraparib versus temozolomide in adult patients with newly diagnosed, MGMT-unmethylated glioblastoma is underway.

NIMG-55. DEVELOPING A COMPUTATIONAL PIPELINE TO FORECAST AND SPATIALLY MAP HIGH-GRADE GLIOMA RESPONSE TO RADIOTHERAPY USING BIOPHYSICAL MODELS AND DATA-DRIVEN STATISTICAL ANALYSIS

Abstract High-grade glioma (HGG) presents significant treatment challenges, particularly in identifying less responsive tumor areas to target with adaptive radiotherapy (RT). This study introduces a patient-specific computational pipeline designed to predict and spatially map HGG response to RT, focusing on regions demonstrating resilience to RT. Our computational pipeline is centered around a family of 3D biophysical models describing tumor cell invasion, proliferation, and response to RT which can be personalized for individual patients using longitudinal multiparametric MRI data. Utilizing longitudinal multiparametric MRI data reporting on cell density (diffusion weighted MRI) and the extent of disease (T2-FLAIR and contrast-enhanced T1-weighted MRIs) from 21 patients, ranging from baseline to three weeks into RT, we calibrated a family of biophysical models to forecast tumor cell density up to the final week of RT and one-month follow-up. By employing pareto tail analysis on empirical cumulative distribution function fits of voxel-wise changes in apparent diffusion coefficient maps (ΔADC) between the future images (end of RT, one-month follow-up) and pre-treatment images, we identified areas of increased tumor cellularity on both the ground truth and model predicted cellularity maps. The analysis differentiated tumor voxels into “non-responding” and “responding” categories, based on cutoffs determined through ROC analysis across various conditions—including assessments of both enhancing and non-enhancing tumor regions at different time points. Optimal ΔADC cutoffs for predicted and measured data were established, leading to high area under curve (AUC; ranging from 0.803 to 0.934) values and significant Youden’s index scores (ranging from 0.526 to 0.765) across all conditions. Our findings demonstrate the feasibility of this novel pipeline in delineating biologically relevant RT targets, offering a potential tool for enhancing the efficacy of adaptive RT strategies in treating HGG.

IMMU-25. B-CELL BASED THERAPY (BVAX) PRODUCES ANTIBODIES TO SUPPRESS GLIOBLASTOMA TUMOR MIGRATION AND INVASION

Abstract Glioblastoma (GBM) presents as a highly aggressive and malignant brain tumor with limited treatment options. Despite the availability of existing therapies, the invasive characteristics of GBM frequently result in tumor recurrence and poor prognosis. We previously developed a B-cell-based therapy (BVax) that has shown promising results in its ability to induce therapeutic responses in preclinical models of GBM. Our research revealed potency of BVax can be attributed to its robust antigen-presenting capability, cognate antigen specificity with T cells, and ability to generate tumor-reactive antibodies. The present study aims to characterize the unique antigenic reactivity of BVax-derived antibodies by evaluating their immunological effects and therapeutic potential in both murine models and GBM patient-specific samples. Leveraging CD45.1 and CD45.2 congenic mouse models, we first revealed that BVax preferentially migrated to glioma-bearing brains upon intravenous injection, resulting in a CD38+CD20-CD19+ plasmablast phenotype. To further characterize the reactivity of BVax-derived immunoglobulins (Ig), we utilized proteomic analysis and identified preferential targets of Gelsolin, Fibronectin, Versican, Fibrinogen, and collagen type IV alpha, commonly associated with cell motility and the extracellular matrix. Microdialysis data confirmed the increased presence of many of these BVax-derived Igs-recognized antigens in tumor regions compared to normal brain regions in GBM patients. Utilizing purified BVax-derived antibodies from patient specimen, in vitro cell motility assays demonstrated a significant prevention of the invasion and migration of cell lines from patient derived xenograft (PDX). In this study, we concluded that BVax elicits antitumor activity through targeted migration to tumor-bearing regions, differentiation into plasmablasts, and robust secretion of specific Igs that retain the ability to inhibit functionalities associated with cell invasion and migration. Here, we present the first in-depth study that characterizes GBM patients’ antibody reactivity, specifically a subset of inflammatory B cells (BVax) with therapeutic effects that offer an indication for a new direction of immunotherapies.

BIOM-27. VOXEL-WISE SURVIVAL ANALYSIS IN GLIOBLASTOMA: TUMOR PROBABILITY MAPS REVEAL CRITICAL REGIONS NEAR WHITE MATTER TRACTS

Abstract BACKGROUND Glioblastoma is the most aggressive primary brain tumor, characterized by rapid growth and poor prognosis. Understanding spatial determinants of survival in GBM is crucial for improving prognostic accuracy and treatment strategies. Our study employs voxel-wise survival analysis (VSA) of tumor probability maps (TPMs) derived from MRI to identify high-risk brain regions. TPMs are generated through radio-pathomic mapping and can predict non-enhancing tumor regions not captured by traditional imaging. We aim to determine if high tumor probability regions are near previously identified critical white matter (WM) tracts and assess their impact on survival outcomes. METHODS We analyzed data from 374 GBM patients from the UCSF-PDGM-v2 dataset. Using a pretrained radio-pathomic model, TPMs were predicted based on T1, T1C, ADC, and FLAIR MRI sequences. All TPMs were rigidly registered to MNI space using ANTs. A Cox proportional hazards model was applied voxel-wise to assess the association between tumor probability and overall survival (OS). A p-value map was generated, thresholded, and cluster corrected (p < 0.05) for further analysis. RESULTS The VSA revealed that high tumor probability regions were significantly associated with poorer OS in GBM. Gray matter (GM) regions near WM tracts with high tumor probability showed markedly reduced survival. GM regions adjacent to the left IFOF (p < 0.05, HR = 1.19, 845 vs. 961 days for high/low TPM), Corpus Callosum Forceps Minor (p = 0.0001, HR = 1, 740 vs. 902 days), Body of the Corpus Callosum (p = 0.005, HR = 0.97, 748 vs. 798 days for high/low TPM) and other WM tracts, such as the left thalamic radiation superior and left reticulospinal tracts had similar trends. CONCLUSIONS Our study demonstrates that regions with high tumor probability, particularly those in the GM near critical WM tracts, are strongly associated with worse overall survival in GBM patients.

CTNI-30. A PHASE 2 DOUBLE-BLIND, RANDOMIZED, PROSPECTIVE, PLACEBO CONTROLLED STUDY OF NANO₂TM COMBINED WITH RADIATION AND TEMOZOLOMIDE IN PATIENTS WITH NEWLY-DIAGNOSED GLIOBLASTOMA: RESTORE

Abstract INTRODUCTION Glioblastoma (GBM) commonly has extensive hypoxic regions, possibly due to thrombosis from tumor-produced pro-coagulant factors. Radiation-induced cell death relies on oxygen free radicals and oxygen fixation of DNA-strand breaks. In the absence of oxygen tumor cells can repair the DNA strand breaks leading to treatment resistance. Hypoxic cells also exhibit chemoresistance due to decreased drug efficacy, limited drug diffusion, and poor delivery to distant cells. This study hypothesizes that increasing oxygen delivery to hypoxic GBM tissue using NanO₂ (2% w/v dodecafluoropentane emulsion) infusion will enhance the effectiveness of radiation therapy (RT) and chemotherapy (CT). METHODS Patients diagnosed with GBM per CNS5-WHO criteria receive standard chemoradiation: 30 fractions of focal RT with 60 Gy, delivered as 2 Gy fractions five days per week for six weeks with concurrent oral TMZ at 75 mg/m²/day for six weeks. Patients are randomized in a 1:2 ratio to receive either a placebo (0.9% Sodium Chloride) or NanO₂ infusion administered immediately prior to each RT dose. Patients continuously breathe oxygen during infusion and RT. Following six weeks of RT with temozolomide, patients have a four-week break before starting adjuvant temozolomide. RESULTS Ten patients have been enrolled in the RESTORE trial. Seven continue to be followed through maintenance treatment and long term follow up. There have been 23 non-hematologic adverse events described as CTCAE severity grade 3 and above. Grade 4, hematologic toxicity occurred in two patients, with one patient experiencing prolonged pancytopenia necessitating hematologic support and discontinuation of temozolomide. Two patients discontinued therapy due to early tumor progression. CONCLUSION This study is ongoing, assessing the safety and potential efficacy of NanO₂ in improving treatment outcomes for GBM by enhancing oxygen delivery to hypoxic tumor regions.