bluuebunny/crossref_metadata_2025_split huggingface dataset:
P02.07.B FIBROBLAST ACTIVATION PROTEIN EXPRESSING MESENCHYMAL CELLS INFLUENCE T CELL ABUNDANCE AND FUNCTION IN GLIOBLASTOMA
Authors: Ternerova N , Houdova Megova M , Buna T , Svablova T , Vymolova B , Balaziova E , Vanickova Z , Krepela E , Hrabal P , Tomas R , Netuka D , Busek P , Sedo A 
Published: October 2024

Abstract

BACKGROUND
Glioblastomas (GBMs) are aggressive brain tumors with strong immunosuppressive properties. In epithelial cancers, mesenchymal cells expressing fibroblast activation protein (FAP) play an important role in modulating the T cell response. We have recently shown that FAP+ mesenchymal cells are present in human GBMs. The aim of this study was to determine their effect on T cell abundance and function.

MATERIAL AND METHODS
GBM tumors (16 samples) were mechanically and enzymatically dissociated and analyzed for immune cell subpopulations by flow cytometry. Expression of T cell related genes was analyzed by qRT-PCR in GBMs selected based on FAP protein concentration determined by ELISA (14 FAP high [upper tercile], 16 FAP low [lower tercile]). Immunohistochemistry (IHC) was used to compare the number of CD3+, CD4+, and CD8+ T cells in GBMs with high (upper tercile, n=21) and low abundance of FAP+ stroma (lower tercile, n=20). Co-localization of FAP+ mesenchymal cells and CD3, PD-L1 and PD-L2 was evaluated by immunofluorescence in frozen sections. 8 FAP+ mesenchymal and 3 glioblastoma stem-like cell cultures were derived from human GBMs and PD-L1 and PD-L2 expression was determined using ELISA. Peripheral blood mononuclear cells were isolated from healthy donors´ buffy coats. Proliferation of stimulated T cells in conditioned media from FAP+ mesenchymal cells was analyzed by flow cytometry.

RESULTS
The percentage of T cells in CD45+ cells from GBMs positively correlated with FAP expression. Expression of the T cell inhibitory molecule PD-L2 was higher in FAP high GBMs. Immunohistochemisty revealed that the numbers of CD3+ and CD8+ T cells were higher in GMBs with a high abundance of FAP+ stroma and T cells were frequently in close proximity to FAP+ mesenchymal cells, which were often PD-L2 positive. In vitro, FAP+ mesenchymal cells expressed more PD-L2 than glioblastoma stem-like cells. T cell proliferation was decreased after exposure to conditioned media from FAP+ mesenchymal cells.

CONCLUSION
FAP+ mesenchymal cells influence T cell abundance in GBMs and may affect T cell functions by limiting their proliferation via soluble factors or cell-cell contact. Acknowledgment: This work was supported by the National Institute for Cancer Research (LX22NPO5102), the Center for Tumor Ecology (CZ.02.1.01/0.0/0.0/16_019/0000785), Charles University project GAUK 365022 and Cooperatio Program Oncology and Haematology“.
P02.10.A IDENTIFYING NOVEL HEXOKINASE-2 ASSOCIATED PROCESSES IN THE GLIOBLASTOMA TUMOUR MICROENVIRONMENT
Authors: Edwards C L , Morris M , Shivakumar S P , Richards T , Small B , Butcher K , Dawson T , Warr T , Karakoula K 
Published: October 2024

Abstract

BACKGROUND
Glioblastoma (GB) is the most common and aggressive type of adult brain tumour. With a median patient survival of only 16 months, new therapies for GB are desperately needed. Deregulation of cellular metabolism is a hallmark of cancers, where they upregulate glycolysis and preferentially ferment glucose to lactate (over pyruvate) in the ‘Warburg effect’. Upregulation of hexokinase 2 (HK2), which catalyses the first rate-limiting step of glycolysis, is key to Warburg metabolism. Several studies have shown HK2 to be selectively overexpressed in GB, while normal human brain tissue (NHBT) relies upon its isoform HK1. As a result, HK2-orientated therapies may selectively target GB tumours while limiting toxicity to normal metabolising healthy tissue. In this study we sought to identify HK2-associated tumour processes in GB which could serve as potential therapeutic co-targets.

MATERIAL AND METHODS
High HK2 expressing (&gt;20-fold upregulation vs NHBT) established and patient-derived GB cell cultures (U87-MG, IN859) were identified by RT-qPCR. HK2 expression was knocked down in these cultures by transfection with targeted siRNA, while non-targeting siRNA was used as a negative control (NC). Expression profiles of HK2 knockdown (HK2KD) and NC cultures were compared using RNAseq. Differentially expressed genes (DEGs) found to be associated with HK2KD were analysed for gene ontology category enrichment (GOSeq) and protein-protein interactions (STRING). DEGs shared between HK2KD cultures were validated by RT-qPCR.

RESULTS
HK2KD was associated with significantly (padj ≤0.05) enriched GO biological processes (BPs) in both U87-MG (117) and IN859 (109). BPs related to glycolysis or glucose metabolism were not enriched. Large clusters of enriched BPs related to inflammatory and immune response were prominent in both HK2KD-U87-MG and HK2KD-IN859. Notable members of these clusters included ‘regulation of neuroinflammatory response’, ‘activation of innate immune response’, and ‘response to bacterium’. Numerous enriched BPs linked to the recruitment of immune cells, such as ‘leukocyte migration’ and ‘granulocyte chemotaxis’, were also evident. STRING analyses further revealed clusters of interacting DEG-encoded cytokines (i.e. CSF2, IL1A/1B/6, TNF) and chemokines (i.e. CCL3, CXCL1/2/3/5/6/8) associated with HK2KD. Several angiogenesis related BPs were also enriched, which corresponded with the downregulation of the major angiogenic regulators HIF2A, VEGF and FGF2 in these HK2KD cultures.

CONCLUSION
These findings highlight potential non-canonical roles for HK2 in regulating inflammatory, immune and angiogenesis related processes within the GB tumour microenvironment. Agents targeting HK2 may thus improve the efficacy of existing preclinical immuno/anti-angiogenic therapies against GB, which warrants further investigation.
P02.23.A SPATIAL PROFILING OF THE MYELOID COMPARTMENT IN MENINGIOMA REVEALS DISTINCT PHENOTYPIC HETEROGENEITY ACROSS METHYLATION CLASSES
Authors: Calafato D , Tang Y , Rukhovich G , Patel B , Suwala A , Sahm F , Gerstung M , Hartmann F 
Published: October 2024

Abstract

BACKGROUND
Recent advances in neuro-oncology highlighted the meninges as an important immunological hub at the crossroads between systemic immunity and the central nervous system. Meningiomas are predominantly benign tumors arising from meningeal cells. However, about 20% are high-grade cases, commonly refractory to standard treatment, showing high recurrence rates. Methylation-based classification has crucially improved meningioma patient stratification. However, the biological processes that govern differences between these classes remain unknown. Here, we investigate the role of differential immune infiltration, cellular communities, and their spatial organization. In light of previously found differential immune infiltration across methylation classes, this study aims to spatially resolve the role of myeloid cells and study their influence on tumor progression and recurrence.

MATERIAL AND METHODS
We deployed multiplexed ion beam imagining and spatial transcriptomics on a retrospective cohort with extensive clinical annotations. Analyzing single-cell transcriptomic data of a subset of patients (n=22), we delineated the expression of gene and protein markers that were used to design an antibody panel comprising 41 targets for cell-type identification, phenotypic and metabolic characterization at the protein level. Additionally, we curated a targeted gene panel for spatial transcriptomics to perform granular spatial analysis. An integration of histological, spatial transcriptomic, and protein layers provides a comprehensive multi-omics approach to studying spatial cellular interactions.

RESULTS
Transcriptional programs and cell populations observed in single-nuclei data were captured in the spatial context revealing differences in the myeloid compartment across meningioma methylation classes. In specific classes, myeloid cells constitute a significant part of the tumor bulk warranting further investigation into their phenotypic differences. Accordingly, our analyses revealed a distinct phenotypic macrophage landscape along disease progression. Furthermore, spatial profiling of the metabolic regulome displayed distinct niche formation within perivascular and tumor compartments.

CONCLUSION
In this study we confirm that macrophages undergo a phenotypic switch from more tolerogenic in low-grade to inflammatory in high-grade cases of meningioma. Correspondingly, specific phenotypic and metabolic features of myeloid and tumor cells contribute to tumor progressions. Considering the limited targeted therapy options and poor responses to immunotherapy in meningioma patients, we hope that our spatial multi-omics analysis may reveal recurrent infiltration patterns of phenotypically distinct cell types that could be informative of biological processes and predictive of disease outcome.
P03.02.B DECIPHERING THE IDENTITY AND CHARACTERISTICS OF LONG-TERM LABEL RETAINING GLIOBLASTOMA CELLS AND THEIR ROLE IN TUMOUR RELAPSE
Authors: Chow H , Kourtesakis A , Hai L , Schaffranek S , Pusch S , Hoffmann D , Reibold D , Wick W , Wagener R 
Published: October 2024

Abstract

BACKGROUND
Glioblastoma (GB) stem cells (GSCs) are described to recapitulate the expression signatures of stem and progenitor cell classes in the neurodevelopmental hierarchy and are implicated in driving therapeutic resistance. However, the heterogeneity of both the GSC subclasses and their expression of stemness markers hinders comprehensive labelling of these cells. Cellular dormancy is a key feature of GSCs that can be captured by label retention method to track slowly dividing cells. We used CellTrace (CT) dye to identify long term label retaining GB cells (LRGC) in orthotopic xenograft model. We analysed the distribution of LRGC versus the tumour bulk in histology. Additionally, we analysed the transcriptional signature by FAC-sorting LGRC for single cell RNA sequencing. Further, we demonstrated that LRCs survived through temozolomide (TMZ) treatment in vivo and re-initiated tumour proliferation in a faster pace than other surviving glioma cells, signifying its role in therapeutic relapse.

MATERIAL AND METHODS
To label LRGC, patient derived GB cell lines were stained with CT dye before transplantation into the striatum of immunodeficient mice. After 6 weeks of growth the brains were cryosectioned, histologically stained and imaged via confocal microscopy, followed by histologic AI assisted analysis with the AIVIA software. LRGC and non-label retaining tumor cells were FAC-sorted for single-cell RNA sequencing (SMART seq2). To explore the role of LGRC in therapeutic resistance, tumors were treated with TMZ. Re-initiation of tumor growth was tracked by subcutaneous surgical implantation of BrdU pumps at different timepoints after therapy. The proliferation patterns of LRGC versus other surviving tumor cells were analysed in histology again using an AI assisted software.

RESULTS
LRGC could be identified in histology 6 weeks after tumor growth. LRGC were found near the centre of tumor but rarely at the invasion front. Single cell RNA-seq of LRGC showed differentially expressed pathways related to lipid metabolism and neurodevelopment. Re-initiation of tumor growth started 12-14 days after therapy. LRGC showed a more intense proliferation compared to other surviving tumor cells, indicating the ability of LRGC to not only survive TMZ treatment, but also drive GB relapse.

CONCLUSION
LRGC could be visualized 6-8 weeks after tumor growth in an orthotopic xenograft model. On a transcriptional level these cells share similarities with stem cells in normal brain development but also show distinct features. An important role of LRGC in re-initiation of tumor growth after therapy could be confirmed.
P06.01.A TARGETING MRNA DECAPPING ENZYME SCAVENGER (DCPS) IS A PROMISING STRATEGY AGAINST GLIOBLASTOMA VIA THE DOWN-REGULATION OF STAT5B
Authors: Duan H , Xie Y , Yu Y , Hu W , Ma W , Mou Y 
Published: October 2024

Abstract

BACKGROUND
Patients with glioblastoma (GBM) have poor prognosis and limited treatment options. The mRNA decapping enzyme scavenger (DCPS) is a cap-hydrolyzing enzyme. The inhibitor targeting DCPS exhibited excellent central nervous system bioavailability in vivo and was safe and well tolerated in healthy volunteers in a phase 1 clinical trial. In this study, we investigated the expression of DCPS in GBM and the anti-tumor activity of the DCPS inhibitor in various preclinical models of GBM.

MATERIAL AND METHODS
DCPS expression was examined in human GBM and paired peritumoral tissues. Its prognostic role was evaluated together with clinicopathological characteristics of patients. The anti-GBM effect of targeting DCPS was determined using GBM cell lines, patient-derived organoids,and orthotopic mouse models. The therapeutic mechanisms of DCPS inhibition were explored.

RESULTS
DCPS is overexpressed in GBMand associated with poor survival of patients with GBM. The DCPS inhibitor exhibited robust anti-GBM activities in GBM cell lines, patient-derived organoids and orthotopic mouse models, with drug exposure achievable in humans. Mechanistically, inhibition of DCPS downregulatedSTAT5Bexpression, thereby suppressing proliferation, survival and colony formation of GBM cells.

CONCLUSION
Inhibition of DCPS at doses achievable in humans downregulates STAT5B expression and reduces proliferation, survival and colony formation of GBM cells. Given the excellent anti-cancer activity and central nervous system bioavailability in vivo and good tolerance in humans, DCPS is a promising target for GBM.
P09.01.B 18-FET-PET ENHANCED DIAGNOSIS OF PSEUDOPROGRESSION IN GLIOBLASTOMA IS AN INDEPENDENT PROGNOSTIC FACTOR FOR OVERALL SURVIVAL
Authors: Schmidt T , Oezdemir Z , Oster C , Sure U , Hermann K , Stuschke M , Deuschl C , Kleinschnitz C , Müther M , Glas M , Kebir S 
Published: October 2024

Abstract

BACKGROUND
Detecting pseudoprogression (PSP) in glioblastoma during first-line treatment remains challenging and has significant clinical implications for patient management. The detection of PSP has been shown feasible using FET-PET. The prognostic impact of FET-PET diagnosed PSP on overall survival is still uncertain, as retrospective studies provide limited insights due to the substantial differences in the distribution of prognostic factors between TP and PSP groups. This study aims to address these uncertainties by leveraging advanced analysis techniques.

MATERIAL AND METHODS
Patients with newly diagnosed glioblastoma (WHO 2021) who underwent chemoradiation and contrast-enhanced MRI suspected for TP and subsequent FET-PET scan at Essen University Hospital were retrospectively evaluated. The modified Response Assessment in Neuro-Oncology (RANO) criteria were used to diagnose PSP. FET-PET analysis included mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax). The two groups (TP/PSP) were balanced using a propensity scoreanalysis including age at diagnosis, extent of resection, Karnofsky-Performance-Status Scale (KPS) and MGMT methylation status. Overall survival was predicted using Kaplan-Meier and multivariate analysis as well as conventional FET-PET parameters, PET/MRI volumetry, and FET/MRI-derived radiomics. An independent cohort was used for validation. Results: Out of the 165 patients analysed in this study, 38 were diagnosed with PSP. Following balancing analysis, our study cohort consisted of 40 patients (20 TP/20 PSP). Patients with PSP had a significantly longer mean overall survival (mOS) compared to those with TP (mOS TP 20.24 months; mOS PSP 33.25 months; p=0.0023). The multivariate Cox-Regression analysis confirmed PSP as a significant prognostic marker for overall survival (p=0.0153). Confirmation of these results on an independent validation cohort is pending and will be presented at the meeting.Conclusion: This study shows that PSP is an independent prognostic factor for overall survival in newly diagnosed glioblastoma patients.
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: Polano M , Cella E , Padovan M , Bosio A , Bertero L , Caccese M , Cerretti G , Rudà R , Toffoli G , Lombardi G 
Published: October 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.
P10.09.A BLOOD-BASED CLASSIFICATION OF IDH-STATUS OF NON-ENHANCING GLIOMAS: A MACHINE LEARNING APPROACH
Authors: Hadad S , Warrier G , McCoy L , Hansen H , Chen J , Rice T , Wrensch M , Taylor J , Clarke J , Wiencke J , Molinaro A 
Published: October 2024

Abstract

BACKGROUND
Non-invasive determination of IDH mutational status in patients with glioma could offer significant therapeutic opportunities. While IDH wildtype tumors (e.g., GBM) typically show enhancement on MRI, IDH mutant tumors often lack this enhancement. However, relying solely on anatomic radiology may lead to misclassification, and currently, tissue acquisition is the primary method for assessing IDH status in gliomas. This limitation hampers the development of neoadjuvant or intraoperative therapeutic strategies based on IDH status; thus, more minimally invasive methods to determine IDH status are needed. In this study, we assessed immune cell proportions, which vary by glioma subtype, from pre-surgery peripheral blood samples as an alternative method of classifying the IDH status in gliomas without enhancement.

MATERIAL AND METHODS
First, we employed a highly accurate large language model (GPT-4-Turbo-128k) with over 99% accuracy to read radiology notes and exclude patients with enhancing gliomas. Then, we identified twelve immune cell subtypes from whole blood using deconvolution algorithms based on DNA methylation data. These immune cell subtypes, along with patient age, were integrated into a machine learning model (random forest) to predict IDH status (wildtype vs. mutant), leveraging conditional Generative Adversarial Networks to generate synthetic data and mitigate bias in the datasets. Two independent datasets were included for training and validating the model.

RESULTS
The random forest model had an area under the ROC curve (AUC) of 0.90 and accurately identified IDH status in 81% of a training set of 287 gliomas (65 wildtype and 222 mutant tumors at varied time points after diagnosis). In an independent validation data set of 99 gliomas (6 wildtype and 93 mutant) from pre-surgery blood samples, the AUC was 0.93, and accuracy predicted IDH status in 92% of cases with a sensitivity of 93% and specificity of 83%.

CONCLUSION
We could accurately predict IDH status in pre-surgical peripheral blood samples from patients with non-enhancing gliomas. This minimally invasive approach is a promising step toward reducing risk and exploring opportunities for earlier therapies based on IDH status.
P12.12.B IMMUNOTHERAPY WITH CAR T-CELLS IN THE TREATEMENT OF RECURRENT GLIOBLASTOMAS: A SYSTEMATIC REVIEW
Authors: Souza P H L , Fracaroli N O , Almeida I M , Suaid R G , Guaresqui H A , Motta R N T , Monici V C , Moysés R C A , Moraes G A , Ramalho A O , Berriel C C , Bellotti G K , Nogueira B V 
Published: October 2024

Abstract

BACKGROUND
Glioblastomas are common malignant tumors in the central nervous system. Currently, the standard of treatment (SOD) for this kind of disease is maximum surgical resection associated with postoperative chemotherapy. However, the current SOD for this tumor still promotes a strict prognosis, with a median Overall Survival (mOS) of less than 24 months. In consequence, many studies are carried out in order to explore new treatment strategies; among those studies, Chimeric Antigen Receptor (CAR) T-cell therapy stands out. This therapy offers a promising alternative for treating those neoplasias resistant to conventional treatment. Therefore, we conducted a systematic review aiming to consolidate and summarize current knowledge on the efficacy of CAR T-cell therapy specifically for glioblastoma.

METHODS
We searched Medline, Embase, and Web of Science databases following Cochrane and PRISMA guidelines. bThe endpoints of this systematic review were mOS, T-cell persistence, and maximum tolerated dose of CAR-T cell.

RESULTS
The analysis included 8 studies with a total population of 70 patients diagnosed with recurrent glioblastoma treated with CAR T-cells The pooled data of mean Overall Survival was 265,57 days. Of the 70 patients, only 5 had complete tumor regression, while 36 had tumor progression.

CONCLUSION
This systematic review showed that CAR T-cell therapy does not seen to be an optimal treatment for recurrent glioblastoma patients due to its low tumor regression rate and high tumor progression. However, current research needs to solidify the evidence base before its widespread clinical use in treating recurrent glioblastoma can be justified.