bluuebunny/crossref_metadata_2025_split huggingface dataset:
P04.03.A TARGETING SCD TRIGGERS LIPOTOXICITY OF CANCER CELLS AND ENHANCES ANTI-TUMOR IMMUNITY IN BREAST CANCER BRAIN METASTASIS MOUSE MODELS
Authors: Sammarco A , Guerra G , Eyme K M , Kennewick K , Qiao Y , El Hokayem J , Williams K J , Su B , Zappulli V , Bensinger S J , Badr C E 
Published: October 2024

Abstract

BACKGROUND
Breast cancer brain metastases (BCBM) are a significant cause of mortality and are incurable. Thus, identifying BCBM targets that reduce morbidity and mortality is critical. BCBM upregulate Stearoyl-CoA Desaturase (SCD), an enzyme that catalyzes the synthesis of monounsaturated fatty acids. This finding highlights a potential metabolic vulnerability of BCBM, but the lack of brain-penetrant inhibitors of SCD has precluded their pre-clinical effectiveness. Additionally, increasing evidence suggests that fatty acid homeostasis in immune cells represents a key regulatory node to control inflammation, and manipulation of fatty acid metabolism has significant effects on immune cell functions. In this study, we tested the effect of a brain-penetrant clinical-stage inhibitor of SCD (SCDi), on breast cancer cells and mouse models of BCBM.

MATERIAL AND METHODS
Lipidomic analyses, qPCR, and western blot were used to study the in vitro effect of SCDi on breast cancer cells. Single-cell RNA sequencing (scRNAseq) was used to explore the effects of SCDi on cancer and immune cells in the tumor microenvironment (TME) in a BCBM mouse model.

RESULTS
Pharmacological inhibition of SCD markedly reshaped the lipidome of breast cancer cells and resulted in endoplasmic reticulum stress, DNA damage, loss of DNA damage repair, and cytotoxicity. Importantly, SCDi alone or combined with a PARP inhibitor prolonged the survival of BCBM-bearing mice. When tested in a syngeneic mouse model of BCBM, scRNAseq revealed that pharmacological inhibition of SCD enhanced antigen presentation by dendritic cells, was associated with a higher interferon signaling, increased the infiltration of cytotoxic T cells, and decreased the proportion of exhausted T cells and regulatory T cells in the TME. Additionally, interaction analysis between immune cells in the TME revealed that pharmacological inhibition of SCD decreased engagement of immunosuppressive pathways, including the PD-1:PD-L1/PD-L2 and PVR/TIGIT axes.

CONCLUSION
These findings suggest that SCD inhibition could be an effective strategy to intrinsically reduce tumor growth and reprogram anti-tumor immunity in the brain microenvironment to treat BCBM.
P05.02.B MOLECULAR MECHANISMS OF ANEUPLOIDY AND GLIOBLASTOMA AGGRESSIVENESS INDUCED BY DIAPH3 LOSS
Authors: Jabbour C , Tajeddine N 
Published: October 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.
P09.16.B THE ROLE OF PERFUSION-MRI IN THE DETECTION OF PROGRESSIVE DISEASE OR THERAPY RELATED CHANGE AFTER PROTON-BOOST IRRADIATED IN PRIMARY GLIOBLASTOMA
Authors: Goett H , Singer L , Struffert T , Uhl E , Stein M 
Published: October 2024

Abstract

OBJECTIVE
Therapy related change (TRC) in glioma patients after radiotherapy are common. In daily practice TRC is difficult to differentiate from true progressive disease (PD). Perfusion-MRI could be a helpful tool to differ between PD and TRC after radiotherapy. However, data for the evaluation of perfusion-MRI after proton therapy in glioblastoma is still missing Our study aims to evaluate perfusion MRI for the differentiation between PD and TRC in primary glioblastoma patients after proton-boost radiotherapy.

METHODS
We evaluate MRI scans from 37 patients with newly diagnosed glioblastoma, who received either photon irradiation (60Gy) or photon irradiation with proton boost (50 + 10Gy). A retrospective analysis regarding T1 contrast enhancement, FLAIR hyperintensity and correlating leakage-corrected relative DSC-CBVmax (relCBVmax) values of the contrast enhancing or FLAIR hyperintense areas in a ratio to a corresponding ROI in the contralateral white matter were performed. Whether scans showed PD or TRC was defined afterwards depending on histology or proceeding growth in the follow up scans. Groups were compared via Mann-Whithney U-Test. For the CBVmax values AUC analysis was performed.

RESULTS
MRI scans in patients after proton therapy showed more often increase of contrast enhancement (59.34%) compared to patients after photon therapy (46.15%). However, the difference was not statistically significant (p=0.1001). RelCBVmax of the FLAIR hyperintense area was not significantly correlated with PD after photon therapy. To predict PD after proton-boost irradiation the cut-off value for the relCBVmax of the FLAIR hyperintense area was &gt;86.3% (sens.: 81.82%/spec.: 58.7%;p=0.0009). For prediction of PD the relCBVmax of contrast enhancing areas the cut-off value after photon irradiation was &gt;145.8% (sens.: 66.67%/spec.:84.21%; p=0.0037). PD after proton-boost therapy could be predicted with a cutoff value of the relCBVmax of 180.7% (sens.:60.61%/spec.:86.21%; p=0.0003).

CONCLUSION
The observed sensitivity was low. However, hyperperfusion in relCBVmax can help for the differentiation between PD and TRC. Perfusion-MRI is a very cost-effective technique and could be a useful tool to determine which patients should receive PET-scans for further diagnostics.
P10.06.A AGENT-BASED MODELING FOR PATIENT-CENTERED CLINICAL DECISION SUPPORT IN NEURO-ONCOLOGY
Authors: Rodriguez Almaraz E , Miao B , Yadav Y , de Groot J , Young J , Vo A , Butte A , Mitchel B S , Raleigh D , Butowski N , Alaa A 
Published: October 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.
P10.10.B CLASSIFYING LOWER-GRADE GLIOMA SUBTYPES WITH 3D WHOLE-BRAIN MRI SCANS AND DEEP LEARNING: A NON-INVASIVE AND INTERPRETABLE APPROACH
Authors: Iadarola B , Sforazzini F , Luchetti L , Leoncini M , Battaglini M , D’Aurizio R 
Published: October 2024

Abstract

BACKGROUND
Patient management with lower-grade glioma (LGG) requires tumour sampling to identify IDH mutation and 1p19q codeletion status, which are pivotal for subtype classification and subsequent therapy. The use of MRI has been investigated so far by radiomics which focuses on features extracted from 2D images of the tumour region only. Deep Learning (DL) algorithms, and in particular Neural Networks (NN), proved to be effective in improving the detection of cancers from diverse imaging data, often through tumour segmentation masking. We aimed to develop a DL-based framework to streamline the LGG molecular-based subtypes classification from the whole-brain 3D MRI scans and, subsequently, to extract a fine map of the brain regions which resulted relevant for the classification.

MATERIAL AND METHODS
Pre-operative MRI scans (T2-FLAIR, T1gad) and molecular information (IDH mutation, 1p19q codeletion status) of 82 LGG patients were collected from the TCIA and TCGA datasets. 56 “IDH-mutant astrocytomas” and 26 “IDH-mutant 1p19q codeleted oligodendrogliomas” were split into class-balanced training (65) and test (17) sets. A computational framework was developed to preprocess the MRIs, train and optimize different DL models through hyperparameters fine-tuning and to automatically detect the best-performing one. We explored a total of 162 configurations, using single and multiple MRI modalities within two residual NN and calculated the attention maps using guided back-propagation.

RESULTS
In the test set we obtained a balanced accuracy of 92% and a F1-weighted score of 89% in differentiating IDH-mutant astrocytomas (sensitivity=0.83) from IDH-mutant 1p19q codeleted oligodendrogliomas (sensitivity=1). The generated attention maps confirmed that features extracted from the perilesional regions positively influenced the classification of the tumour subtypes, especially of astrocytomas (100% of cases); on the contrary, the widely used tumoral region was scarcely considered in the classification of this subtype (10%), having an impact only in oligodendrogliomas (60%). Interestingly, contralateral and other distant-from-the-tumour areas were relevant in the classification of both subtypes (40%), with a focus on distant-from-the-tumour areas in oligodendrogliomas (60%).

CONCLUSION
3D whole-brain scans coupled with optimized DL-based approach showed to be a non-invasive and promising alternative in classifying LGG molecular-based subtypes, providing a more exploratory insight in the subject-level discrimination of brain regions differently associated with IDH mutation and 1p19q codeletion status. Further validations are needed to prove the efficacy of the proposed method in supporting the clinical decision-making.
P10.22.B PREDICTING INTRAOPERATIVE 5-ALA-INDUCED TUMOR FLUORESCENCE VIA MRI AND DEEP LEARNING IN GLIOMAS WITH RADIOGRAPHIC LOWER-GRADE CHARACTERISTICS
Authors: Suero Molina E , Azemi G , Özdemir Z , Russo C , Valls Chavarria A , Liu S , Thomas C , Stummer W , Di Ieva A 
Published: October 2024

Abstract

BACKGROUND
Lower-grade gliomas typically exhibit 5-aminolevulinic acid (5-ALA)-induced fluorescence in only 20-30% of cases, a rate that can be increased by doubling the administered dose of 5-ALA. Fluorescence can depict anaplastic foci, which can be precisely resected to avoid undergrading. We aimed to analyze whether a deep learning model can predict intraoperative fluorescence based on preoperative magnetic resonance imaging (MRI). Material and Methods: The MRI images of gliomas lacking high-grade characteristics (necrosis, extended contrast-enhancement, a.o.) consisted of T1, T1-post gadolinium, and FLAIR sequences. The preprocessed MRIs were fed into an encoder-decoder convolutional neural network (U-Net), pre-trained for tumor segmentation using those three MRI sequences. We used the outputs of the bottleneck layer of the U-Net in the Variational Autoencoder (VAE) as features for classification. We identified and utilized the most effective features in a Random Forest classifier using the principal component analysis (PCA) and the partial least square discriminant analysis (PLS-DA) algorithms. We evaluated the performance of the classifier using a 10-fold cross-validation procedure.

RESULTS
We evaluated a cohort of 163 glioma patients categorized as fluorescent (n=83) or non-fluorescent (n=80). Our proposed approach’s performance was evaluated using metrics such as mean balanced accuracy, mean sensitivity, and mean specificity. The optimal results were obtained by employing top-performing features selected by PCA, resulting in a mean balanced accuracy of 80% and mean sensitivity and specificity of 84% and 76%, respectively.

CONCLUSION
Our findings highlight the potential of a U-Net model, coupled with a random forest classifier, for intraoperative fluorescence prediction. We achieved good accuracy using advanced techniques such as deep learning-based tumor segmentation and Variational Autoencoder for radiomics feature extraction. While the model can still be improved, it has the potential for evaluating when to administer 5-ALA to gliomas lacking typical high-grade radiographic features.
P16.01.B DOXORUBICIN GLYCOSYLATION AS A NOVEL APPROACH TO SPECIFICALLY TARGET GLIOBLASTOMA
Authors: Iorio A , Marzano C , Tirinnanzi B , Lenci E , Bucaletti E , Castelli B , Fonte C , Tellini M , Guidi M , Di Nicola M , Giunti L , La Torre C , Trabocchi A , Sardi I 
Published: October 2024

Abstract

BACKGROUND
Despite recent advances in the treatment of cancer, malignant brain tumors such as Glioblastoma (GBM) are still a major challenge in oncology with a poor prognosis. This evidence can be partly explained by the inability of most drugs, such as Doxorubicin (DOX), to be delivered within the brain due to the presence of drug resistance mechanisms including the active efflux mediated by ATP-binding cassette transporters, which are overexpressed on the blood brain barrier (BBB).Malignant tumors like GBM also show a significant glycolytic rate and a high glucose request through glucose transporters (Warburg Effect). In this context, GLUT1 is reported to be implicated in glucose uptake through the BBB.In our study we have developed an innovative approach able to increase drug efficiency and selectivity, by conjugating the anticancer agent DOX to glucose.

MATERIAL AND METHODS
DOX glycoconjugates were obtained using oxime-based linkers with hydroxylamine-containing spacers between position number 6 of glucose and carbonyl group of DOX. Two different glycoconjugates (EB73 and EB74) were synthesized and characterized for their absorbance, fluorescence and binding affinity to ctDNA. MTT assay was performed to evaluate the cytotoxic effect of EB73 and EB74, compared to DOX, in two GBM cell lines (A172 and DOX resistant T98G). These cells were also used to evaluate the effect of glucose deprivation on the expression levels of GLUT1 and breast cancer resistance protein (BCRP) by Western Blot. Molecules uptake by cells was evaluated using an in vitro BBB model and immunofluorescence (IF) in glioblastoma and neuroglia cell lines.

RESULTS
Our results showed that EB73 and EB74 have kept Ka binding constants comparable to DOX itself, confirming that functionalization with glucose did not alter DOX intercalation capability and fluorescence.The in vitro cytotoxicity results demonstrated that EB74 has the major effect in A172 compared to DOX and revealed a high efficacy in T98G DOX-resistant cells starting from 24 hours of treatment. Moreover, glucose deprivation showed a GLUT1 overexpression and BCRP downregulation in both cell lines improving EB74 efficacy. According to MTT results, BBB in vitro model and IF experiments revealed that only EB74 was able to accumulate in cells nuclei as conventional DOX.

CONCLUSION
In conclusion, these results indicated that glycoconjugation of DOX and glucose deprivation may be helpful instruments to increase drugs uptake and effectiveness in aggressive and chemoresistant tumor cells.
P18.04.A APPLICATION OF THE PET RANO 1.0 CRITERIA IN DIFFUSE GLIOMA: RETROSPECTIVE SINGLE CENTER EXPERIENCE
Authors: Wiegand L , Barci E , Müller K J , Forbrig R , Brendel M , Preusser M , Schönecker S , Thon N , Harter P N , von Baumgarten L , Albert N L 
Published: October 2024

Abstract

BACKGROUND
Response evaluation and disease monitoring of gliomas relies on MRI in clinical routine and trials. Recently, novel response criteria utilizing amino acid PET (PET RANO 1.0) have been introduced. This study analyses longitudinal [18F]FET PET data of patients with diffuse glioma and applies the PET RANO 1.0 criteria to describe PET characteristics at baseline, response classes, and changes of individual parameters.

MATERIAL AND METHODS
In this retrospective single-center study, patients with diffuse glioma and a baseline as well as at least one follow-up [18F]FET PET scan were identified. PET analyses were performed according to the PET RANO 1.0 criteria and included the assessment of maximal and mean target-to-background ratios (TBRmax, TBRmean), PET volume, changes of these values between scans, and the presence of either measurable or no / non-measurable disease. Follow-up scans were classified as PET-based progressive disease (PET-PD), stable disease (PET-SD), partial response (PET-PR), or complete response (PET-CR) according to PET RANO 1.0.

RESULTS
A total of 475 scans in 148 patients were evaluated with a total of 228 treatment lines, defined as a baseline scan plus a series of one to four follow-up evaluations either with or without treatment. Overall, 164/228 baseline scans had measurable disease and 64/228 had non-measurable or no measurable disease. In the treatment lines, 4% of patients had PET-CR as best response, 23% had PET-PR, 37% had PET-SD, and 36% had PET-PD. PET-PD was determined based on significant volume changes and/or the occurrence of new lesions in the majority of cases (&gt;90%), while significant increases of uptake intensity were found in 30% of cases. A sole increase of uptake intensity as determinant for PET-PD was only found in 8% of cases. PET-PR was determined based on volume reductions in 82% of cases (25% in combination with decreasing uptake intensity) and by a sole reduction of uptake intensity in 18% of cases. Treatment lines of glioblastoma had PET-PD as a best response in 56% of cases, while astrocytomas and oligodendrogliomas only had PET-PD in 44% and 35% of cases, respectively.

CONCLUSION
This study demonstrates that significant volume changes seem to be the major determinant for treatment response according to the PET RANO 1.0 criteria and are often accompanied by changes of uptake intensity, while sole uptake intensity changes determine response classes only in a subset of patients. Best responses in treatment lines classified with the new criteria varied based on tumor type with IDH-wildtype glioblastoma showing higher rates of PET-PD in comparison with IDH-mutant gliomas. In the future, response assessment from PET RANO 1.0 should be correlated with the MRI-based RANO 2.0 criteria, as well as the clinical outcome of patients.
P19.17.B THE PREOPERATIVE LEVELS OF CIRCULATING ERYTHROCYTIC HEMOGLOBIN ARE INDEPENDENT PREDICTORS FOR WHO GRADE 2-3 HISTOLOGY IN FALCINE AND PARASAGITTAL MENINGIOMAS
Authors: Gagliardi F , De Domenico P , Braga M , Barzaghi L R , Nocera G , Poliani P L , Mortini P , Roncelli F , Silvia S 
Published: October 2024

Abstract

BACKGROUND
Falcine and parasagittal lesions stand out among other intracranial meningiomas for their extreme histological heterogeneity, accounting for the highest rate of high-grade lesions. The ability to preoperatively estimate the lesion’s grade and its clinical outcome would be of great value in orienting and customizing the treatment approach in these patients. To date, no validated clinical or radiological predictive factors for tumoral grade and prognosis are available.

MATERIAL AND METHODS
This is a single-center, retrospective, clinical study designed to assess the diagnostic and prognostic role of pre-operative peripheral blood markers in patients harboring falcine (FM) and parasagittal (PM) high-grade meningiomas. A total of 121 patients undergoing surgical resection for a single FM/PM lesion at San Raffaele Hospital between November 2007 and April 2021 were included. A propensity score-matched analysis has been performed to account for gender imbalances in the low-grade (LG) vs high-grade (HG) cohorts.

RESULTS
A total of 75 tumors FM (62%), and 46 PM (38%) meningiomas were included. The median tumoral volume was 31.1 cm3 (IQR 17.1-65.4). Low-grade lesions comprised n=77 WHO grade 1 tumors, whereas the high-grade group (HG) included n=35 grade 2 (28.9%), and n=9 grade 3 lesions (7.4%). Patients harboring HG lesions showed significantly higher baseline Hb levels significantly compared to LG (mean 14.4 ± 1.59 vs 13.7 ± 1.25 g/dl, p=0.04). Preoperative Hb demonstrated a predictive value of lesional grade (OR 1.35, 95% CI: 1.01-1.85, p=0.04). Accordingly, patients showing increased Hb levels &gt;15.4 g/dl achieved shorter OS (60.4 months, 95% CI: 14.7-106.1 vs 137.4 months, 95% CI: 111.2-163.6), p=0.0011 compared to patients with lower preoperative Hb values.

CONCLUSION
Increased levels of circulating erythrocytic hemoglobin might be independent predictors for high-grade histology, and correlate with shorter overall survival in falcine and parasagittal meningiomas.