tbuckley/cabot-search huggingface dataset:
P07.04.A THE LOSS OF THE X CHROMOSOME IN THE CONTEXT OF THE MALIGNANCY OF MENINGIOMAS
Authors: N Berghaus, D Savran, T Hielscher, D Schrimpf, C Herold-Mende, W Wick, A von Deimling, F Sahm
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND In recent years, molecular markers have become increasingly important in the diagnosis and risk assessment of brain tumours. Besides mutations and methylation, this also includes copy number variations (CNVs). It is well known that CNVs contribute to cancer initiation, progression and therapeutic resistance. Investigating the most common primary intracranial tumours in adults, meningiomas, several studies propose new stratification systems with a more accurate risk prediction than the WHO grading. Several of these approaches combine morphology, methylation, or both, with CNV status to derive a more precise risk assessment. However, a common shortcoming is the absence of separate analyses based on the sex of the patients or the inclusion of the X chromosome. MATERIAL AND METHODS A cohort of over 6000 meningiomas was stratified and analysed regarding the loss of the X chromosome. Further, a differential methylation analysis was conducted based on EPIC v1 data. RESULTS In general, meningiomas from females displayed a loss of chromosome X more than three times more often than tumours from males (p = &amp;lt;0.001) and were significantly associated with a more malignant classification, affecting both the WHO classes and the methylation classification. Calculating oncogenetic trees, females and males share the loss of chr22q as first node followed by a loss of chr1p but only in females, the loss of chromosome X directly follows the high-risk CNV event “loss of chr14q”. However, not only CNVs, but also DNA methylation is a decisive factor. Therefore, a differential methylation analysis was conducted between meningiomas from females with and without a loss of the X chromosome, stratified for methylation classes. Within the methylation class (MC) ben-1, almost no difference between the two cohorts could be detected for the autosomes. In contrast, within the MC mal, the highest and significant difference was noted for a region overlapping with the RUNX3 gene (p = &amp;lt;0.001) - indicating a higher methylation in the “noloss” subgroup. This is of special interest as RUNX3, a transcription factor, regulates gene expression, impacts the cell cycle, cell differentiation, apoptosis, tumor suppression, and cancer cell metastasis. Analyzing the MC mal regarding the X chromosome, for example, a significant difference was detected for a region overlapping COX7 (p = &amp;lt;0.001). The mitochondrial protein COX7b has previously been linked to driving metastasis of human breast cancer cells in mice. CONCLUSION The findings indicate that the loss of the X chromosome in females is linked to tumor malignancy and can also be correlated with different methylation patterns.
P10.06.A AGENT-BASED MODELING FOR PATIENT-CENTERED CLINICAL DECISION SUPPORT IN NEURO-ONCOLOGY
Authors: E Rodriguez Almaraz, B Miao, Y Yadav, J de Groot, J Young, A Vo, A Butte, B S Mitchel, D Raleigh, N Butowski, A Alaa
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Complex clinical decision-making in neuro-oncology is a multifaceted process involving numerous specialties influenced by various objective factors and patient preferences. Modeling these multidisciplinary neuro-oncology discussions presents significant challenges, particularly given the multimodal nature of the data. Recent advancements in large language models (LLMs) have enabled the development of LLM “agents”. These agents pave the way for multi-agent systems capable of simulating interacting components, thus capturing the nuances of interdisciplinary clinical discussions. MATERIAL AND METHODS Utilizing GPT-4, we developed conversational agents with an agent-based modeling (ABM) approach; each agent was assigned a specific specialty. We simulated their interactions in various clinical decision-making scenarios. Lastly, we simulated 30 patient-agents and included them in the ABM system. We applied this ABM approach to a dataset of 16 clinical vignettes extracted from the UCSF Clinical Data Warehouse of primary adult glioma patients who underwent tumor board (TB) reviews. The TB decision was used as ground truth for quantitative evaluation. Seven independent clinicians evaluated the final decisions. RESULTS Our quantitative assessment showed that, when blinded to whether ABM or TB generated responses, evaluators preferred ABM recommendations 47.8% of the time, followed by TB recommendations (38%). The highest recommendation concordance was between TB and ABM (50.6%). The ABM was deemed clinically accurate in 76.8% of cases and provided clinically appropriate reasoning in 73.2%. Our qualitative assessment showed that including the patient agent significantly influenced the course of discussions, notably when the patient agents participated in the system by stating their healthcare goals. The most recommended individual treatment was standard-of-care chemotherapy, followed by targeted therapies, clinical trials, immunotherapy, and palliative care. The least frequently recommended management options were radiation, surgery, consultation with other specialties, and devices. CONCLUSION This study underscores the potential of ABM in neuro-oncology, particularly in simulating complex, real-world scenarios. ABM not only empowers patients but also offers clinicians a novel tool for understanding and navigating the multifaceted landscape of patient preferences and treatment options. It provides a platform for clinicians to visualize the potential impacts of various decisions, enhancing their ability to provide personalized, effective care. We envision future work where ABM systems are patient-centric, enabling patients to explore the potential impacts of their individual characteristics on clinical management options.
P10.02.A A NOVEL APPROACH CONCERNING MEDICAL EDUCATION ON AI AND ML THROUGH THE ASNR MICCAI BRATS 2023 BRAIN METASTASES CHALLENGE
Authors: A Janas, A Gkampenis, N Yordanov, P Fehringer, K Krantchev, A W Moawad, U Baid, K E Link, Y S Velichko, D LaBella, F Kofler, E Calabrese, U Shafique, G Conte, R Saluja, N H Tahon, N Maleki, A Abayazeed, S Aneja, A Nada, H Li, M Foltyn, S Bakas, J Rudie, M Aboian
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Artificial intelligence (AI) and machine learning (ML) are in the process of being integrated into modern healthcare, especially in imaging data-dependent fields like Radiology. Unfortunately, data shows that the acquaintance of physicians and medical students with AI is far from sufficient. Therefore, we implemented an educational chapter within the ASNR MICCAI BraTS 2023 Brain Metastases Challenge. Its purpose is to educate medical students on the basics of AI and ML application in the diagnostic imaging and apply deliberate learning approach to teach biology and physics of MRI imaging of brain metastases. MATERIAL AND METHODS Pilot group of 15 medical students from EU was expanded to 150, to include radiology residents and research associates. Fundamentals of MR imaging and process of lesion segmentation was taught through lectures and written guides. Trainees were involved in refining preprocessed cases to create ground truth segmentations for AI algorithm training within BraTS-METS Challenge. The annotators received individual support through question and answer sessions and expert reviews. Lectures specifically targeted to AI, ML, ethics, and Open Science introduced trainees to field experts. Specific skills related to building and publishing databases suitable for ML algorithm training, including all necessary preprocessing steps such as quality control, skull stripping, and normalization, were developed throughout the training process. Alternative methods for education, including #BraTSBrainMetsTeachingPearls Twitter series were also implemented which offered in-depth guidance on interpreting the imaging features of brain metastases and the ability to interact with imaging content. RESULTS Participants reported an enhanced understanding of neuroradiology, particularly in identifying imaging features of brain metastases. Their gained proficiency in ML/AI empowers them to efficiently assess existing models or replicate the workflow of model training. The early clinical exposure and extensive ML/AI lectures were highly valued, providing deeper insights into the applications and limitations of these technologies. The educational strategy combining constructivist principles with practical experience proved highly beneficial, equipping them with skills relevant to both research and clinical practice. CONCLUSION Insufficient integration of AI and ML in medical education necessitates effective and early training. Adopting a constructivist approach has equipped students with vital skills in Open Science, database development, and model training, preparing them to fully utilize these technologies while understanding their limitations.
P10.03.B A NOVEL MACHINE LEARNING (ML) MODEL INTEGRATING CLINICAL AND MOLECULAR DATA TO PREDICT RESPONSE TO SECOND LINE TREATMENT IN RECURRENT IDHWT-GLIOBLASTOMA (RGBM)
Authors: M Polano, E Cella, M Padovan, A Bosio, L Bertero, M Caccese, G Cerretti, R Rudà, G Toffoli, G Lombardi
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Nitrosoureas (lomustine/fotemustine) and antiangiogenic drugs (bevacizumab or regorafenib) are second-line treatment options for patients with rGBM, but to date predictors of efficacy are lacking. We aimed to develop a multi-classification ML algorithm to predict the response to different second line therapies. MATERIAL AND METHODS We conducted a retrospective study to assess the combined predictive value of molecular profiles (tested by FoundationOne®CDx on tissue) and clinical data (clinical-pathological and treatment characteristics) in a cohort of patients with first rGBM treated with Regorafenib, Lomustine/Fotemustine or Bevacizumab from Oct 2019 to Jan 2023. WHO2021 classification was used for pathological diagnosis, and RANO criteria for neuroradiological response evaluation.ML was applied using a gradient boosting framework that uses tree-based algorithms LightGBM to integrate clinical and genomic data. In this context we apply the ML approach to identify the best responders. Matthews correlation coefficients (MCC) were used as a metric. To create a multi-classification model, we included all the cases with complete information (gene mutations and clinical data). Best responders were labeled for having a median progression free survival (mPFS) above the third quartile for each treatment performed in the second line in recurrent glioblastoma. RESULTS 153 patients, treated with Regorafenib (n=95), Bevacizumab (n=19), Nitrosoureas (n=39) were enrolled. The mPFS in each treatment cohort was 2.1 ms (95% CI 1.9-3.3), 3.6 ms (95% CI 2.1-4.8) and 3.0 ms (95% CI 2.4-5.7), respectively. The mOS from the start of treatment was12 ms (95% CI 9.1-14), 7.0 ms(95% CI 6.0-11), and 8.0 ms (95% CI 5.0-13). By performing the multi-classification model we obtained a MCC of 0.32. The SHAP analysis showed age at diagnosis, gender, methylation status and CDKN2B, CDKN2A, PTEN, EGFR, TP53, MTAP mutational status as the most important predictors.These variables were ranked in a different order for each second-line treatment, thus demonstrating that the multi-classification ML approach could discriminate which patients are likely to benefit from each second-line treatment. CONCLUSION The multi-classification ML model developed in this study was able to identify clinical and molecular signatures of rGBM responding to second-line with bevacizumab or regorafenib or nitrosoureas.This model could be useful to choose the more effective second-line therapy in rGBM patients.
P05.02.B MOLECULAR MECHANISMS OF ANEUPLOIDY AND GLIOBLASTOMA AGGRESSIVENESS INDUCED BY DIAPH3 LOSS
Authors: C Jabbour, N Tajeddine
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Diaphanous-related formin 3 (Diaph3) belongs to the formin family of dimeric multidomain proteins that are master regulators of actin and microtubule dynamics. It plays a role in the cytoskeleton remodeling, more specifically in cytokinesis and karyokinesis. In the mouse brain, loss of Diaph3 induced aneuploidy followed by massive apoptosis in neural stem cell, leading to microcephaly. Given the potential role of aneuploidy in cancer development, we are interested to unravel whether Diaph3 depletion during gliomagenesis could aggravate glioblastoma (GBM) aggressiveness MATERIAL AND METHODS To analyze whether Diaph3 is a potential therapeutic target in human GBM, we will use siRNA-mediated depletion of Diaph3 in a panel of GBM cell lines (U251 and U87). We conducted karyotyping followed by analysis of the DNA Damage response (DDR) induction, DNA repair and cell cycle progression. RESULTS Our results showed that siRNA-mediated depletion of Diaph3 in p53 mutated GBM cells (U251 cells) disrupted microtubules and caused mitotic defects such as multipolar mitosis. Karyotyping showed an increase in aneuploidy in Diaph3-depleted U251 cells. Since it has been shown that numerical abnormalities in chromosomes segregation could trigger DDR, we hypothesize that the loss of Diaph3 induces increased activity of the DDR pathway and we aim to decipher their underlying molecular mechanism. CONCLUSION We believe that this study may provide insights into the mechanisms by which Diaph3 prevents aneuploidy in glioblastoma cells but also, more generally, into the role of aneuploidy in gliomagenesis.
P05.01.A ATR INHIBITORS INCREASE THE ANTI-PROLIFERATIVE EFFECTS OF STANDARD TREATMENT ON PATIENT-DERIVED GLIOBLASTOMA CELLS
Authors: M Lozinski, N Bowden, M Graves, B Day, B Stringer, M Fay, P Tooney
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Glioblastoma is treated with surgery to remove as much as the tumour as possible then radiation therapy (RT) and temozolomide (TMZ) to cause extensive DNA damage in any remaining tumour cells, triggering cell death by apoptosis. However, glioblastoma cells respond by upregulating the DNA damage response (DDR) triggering DNA repair that contributes to treatment resistance. Progression then generally occurs rapidly leaving patients with a poor prognosis and survival. We previously showed that gartisertib, an inhibitor of ATM- and Rad3-Related protein (ATR), a serine/threonine kinase that triggers DNA repair, sensitises glioblastoma cells to TMZ and RT. We extend this investigation to brain-penetrant ATR inhibitors elimusertib (BAY1895344) and ceralasertib (AZD6738). MATERIAL AND METHODS Patient-derived glioblastoma cell lines were treated with a dose response of ATRi (elimusertib and ceralasertib) combined with a clinically relevant dose of TMZ (35uM) and/or RT (2Gy). A human astrocyte cell line was also treated with a dose response of single agent elimusertib and ceralasertib. Cells were incubated for 7 days and assessed for cell viability through an MTT assay or cell-cell Incucyte analysis. RESULTS Both elimusertib and ceralasertib as single agents reduced glioblastoma cell growth, with elimusertib being more potent compared to ceralasertib. Elimusertib had greater potency in causing cell death of the glioblastoma cell lines than a human astrocyte cell line. However, there was less difference between glioblastoma and astrocyte cell death when treated with ceralasetib. When combined with RT and/or TMZ, elimusertib once again was more potent in reducing glioblastoma cell growth compared to ceralasertib. CONCLUSION We have expanded our in vitro data showing that various ATR inhibitors (elimusertib, ceralasertib and previously gartisertib) are able to reduce the growth of glioblastoma cells in combination with RT and TMZ treatment. This provides further support for initiating a clinical trial of ATR inhibition in combination with standard treatment for patients with glioblastoma.
P06.03.A EXPLORING THE THERAPEUTIC EFFICACY OF CHLOROQUINE AND HYDROXYCHLOROQUINE IN IDH-WILDTYPE AND IDH-MUTANT GLIOMA
Authors: A Eisele, M Mastall, M Weller, P Roth
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Within the treatment of the most common and aggressive brain tumors - gliomas - the last decades have been characterized by an enormously high rate of failed and cost-intensive drug trials. Repurposing established medications for the treatment of cancer has the advantage of faster availability as well as cost-effectiveness. Chloroquine (CQ) and hydroxychloroquine (HCQ) are approved medications for the treatment of rheumatologic diseases and malaria and have gained attention in recent years due to evidence of potential anti-tumor efficacy in various cancer types. The data available to date on the use of (H)CQ for the treatment of gliomas are limited and remain controversial. Here, we study (H)CQ as a therapeutic option in IDH-wildtype and IDH-mutant glioma models in vitro. MATERIAL AND METHODS The effects of (H)CQ alone and in combination with other clinically relevant treatment modalities are characterized on several key biological properties of glioma cells. RESULTS Both CQ and HCQ show in vitro activity against IDH-wildtype (LN-229, LN-308, ZH-161, GL-261, SMA-560) and IDH-mutant (GS-827) glioma cells, with most cell lines being more sensitive to CQ than to HCQ. This effect is potentiated by a combination of (H)CQ with temozolomide or radiotherapy. Cell death is mediated by apoptosis and is associated with an upregulation of caspase 3 activity. (H)CQ induce autophagy inhibition and reduce TGF-beta 2 and 3 mRNA expression in glioma cells. CONCLUSION CQ and HCQ show promising effects against IDH-wildtype and IDH-mutant glioma cells in vitro. (H)CQ inhibits autophagy and is associated with a down-regulation of TGF-beta expression. Whether the anti-glioma activity of (H)CQ can be translated into in vivo models will be investigated in further studies.
P09.15.A SATURATION TRANSFER MRI ENABLES EARLY DETECTION OF CANCER LESIONS IN THE CNS
Authors: N Lehman, A Chudzik, W W Lam, R Rola, G J Stanisz
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Chemical exchange saturation transfer (CEST) MRI provides chemical-group-specificity (e.g., amide, guanidinium, and aliphatic) to exchangeable protons in dissolved proteins. Magnetization transfer (MT) MRI is sensitive to water bound to macromolecules, e.g., myelin and collagen. The major objective of the study was to identify the chemical exchange saturation transfer- and magnetization transfer-derived magnetic resonance images that have high contrast between orthotopic U87 tumours and normal-appearing brain. MATERIAL AND METHODS U-87 MG glioblastoma cell line-derived xenografts were implanted in RNU nude rats (n=9). Animals were divided into two groups based on the scanning schedule. The rats were imaged using 7 tesla scanner (PharmaScan; Bruker BioSpin) at three time points for all animals: 3-5, 7-9, and 11-13 days after implantation. Single-slice saturation-transfer-weighted CEST (saturation amplitude: 0.5 and 2 µT) and MT (3 and 5 µT) contrast Z-spectra and T1 and T2 maps were acquired. The MT Z-spectra and T1 map were fitted to a two-pool quantitative MT model to estimate the T2 of the free and macromolecular-bound water molecules, the relative macromolecular pool size (M0, MT), and the magnetization exchange rate from the macromolecular pool to the free pool. RESULTS Statistically significant differences, by pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment, were found. The differences between enhancing lesion and contralateral cortex for the magnetization transfer ratio with 2 µT saturation at 3.6 ppm frequency offset (corresponding to the amide chemical group) and M0, MT are both strongly significant (p &amp;lt; 0.001) at all time points. CONCLUSION MT and CEST are a promising method of identifying the earliest time points of glioblastoma development. Such an early image biomarker of neoplasia may allow for improved treatment outcomes leading to reduced recurrence events.
P11.10.B THE SYNDROME OF THE SUPPLEMENTARY MOTOR AREA: CLINICAL COURSE AND PREDICTORS OF OUTCOME AFTER RESECTION OF PREMOTOR LESIONS
Authors: N Teske, L B Jung, J O Nöldeke, T Weig, J Blobner, R Forbrig, J Tonn, M Kunz, N Thon, P Karschnia
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND The syndrome of the supplementary motor area (SMA) frequently occurs after resection of lesions in the premotor cortex or its associated white matter tracts. Brain plasticity involving the interhemispheric connectivity including the contralateral SMA region might be crucially involved in the development of and recovery from SMA syndrome. We herein aimed to identify predictors of outcome by quantifying pre-operative structural alterations in the non-affected contralateral hemisphere. METHODS We retrospectively searched our institutional database for patients developing SMA syndrome after undergoing resection of lesions localized in the SMA region between 2013 and 2023. Clinical characteristics, imaging data, and neurological outcomes were collected. Structural network analysis was performed using the previously validated morphometric inverse divergence (MIND) network. MIND estimates a patient’s axonal connectivity and cortical cytoarchitectonics based upon the comparison of the patient’s MRI with a large cohort of more than 10,000 healthy controls. RESULTS We identified 27 patients with a mean age of 39.2 ± 17.7 years who developed SMA syndrome following resection of premotor lesions, including 13/27 patients (48.1%) who underwent tumor resection for primary brain tumors and 14/27 patients (51.9%) who underwent focal resection for intractable lesional epilepsy. Postoperative SMA syndrome was most characterized by contralateral upper extremity hemiparesis (19/27 patients, 70.4%) and aphasia in case dominant hemisphere involvement (13/13 patients, 100%). Patients with a primary brain tumor had generally more severe symptoms, and were less likely to fully recover from SMA syndrome after 7 days compared to epilepsy patients (full recovery: 2/13 [15.4%] versus 9/14 [64.3%] patients, p = 0.018). At last follow-up after a median time of 5 months (IR 3-16 months), most patients (23/27, 85.2%) experienced a full recovery of SMA syndrome, with no difference between patients with tumors or epilepsy (p = 0.999). Preoperative contralateral intra-hemispheric connectivity was similar between patients receiving tumor or focal resection (0.183 vs 0.177, p = 0.295). However, imaging analyses point towards baseline affection of the SMA connectivity network in patients with brain tumors as characterized by reduced cortical thickness of the contralateral frontal lobe and the cingulate gyrus compared to epilepsy patients. CONCLUSION While full recovery from SMA syndrome is common, SMA syndrome is frequently less severe and more transient in patients with epilepsy. This might be due to more severe affection of contralateral SMA network in tumor patients due to the infiltrative nature of the disease. Imaging analyses might assist in identifying network affections at baseline to guide informed discussions with patients and caregivers.