bluuebunny/crossref_metadata_2025_split huggingface dataset:
P12.06.A PERICYTE-LIKE CELLS EXPRESSING FIBROBLAST ACTIVATION PROTEIN ARE MAIN PRODUCERS OF FIBRILLAR EXTRACELLULAR MATRIX IN GLIOBLASTOMA
Authors: Vymola P , Garcia-Borja E , Cervenka J , Balaziova E , Vymolova B , Vodicka P , Busek P , Sedo A 
Published: September 2023

Abstract

BACKGROUND
Compared to the normal brain, glioblastomas (GBMs) contain higher amounts of extracellular matrix (ECM) composed of fibrillar proteins such as collagen I and fibronectin. These proteins are associated with glioma cell invasion and poor clinical outcome of GBM patients, but their origin remains unclear. The highest levels of fibrillar ECM can be found in perivascular niches, which are, among others, resided by fibroblast activation protein (FAP) expressing pericyte-like cells. The aim of this study was to determine the role of FAP+ pericyte-like cells in the production of fibrillar ECM proteins and their importance in glioma cell biology.

MATERIAL AND METHODS
FAP+ pericyte-like cells, glioma stem-like cells (GSCs) and primary endothelial cells were isolated from human GBMs. M2 macrophages were differentiated from monocytes isolated from healthy donors´ buffy coats. The expression of FAP, collagen I and fibronectin in GBM tissues and different cell types (FAP+ pericyte-like cells, glioma cell lines, GSCs, M2 macrophages) was analyzed by immunohistochemistry and ELISA. FAP+ pericyte-like cells and glioma cells were used to prepare extracellular matrices, which were analyzed using mass spectrometry. Solubilized ECM was used in a modified transwell migration assay.

RESULTS
Compared to the non-tumorous brain, high levels of collagen I and fibronectin were present in the vicinity of FAP+ pericyte-like cells in GBMs. The expression of collagen I and fibronectin was higher in GBMs with higher FAP expression. In vitro, FAP+ pericyte-like cells produced the largest amount of collagen I and fibronectin compared to other cell types and secreted these proteins extracellularly, resulting in production of 3D extracellular matrices rich in collagen I and fibronectin. Mass spectrometry revealed that the ECM produced by FAP+ pericyte-like cells strongly differs in composition compared to glioma cell ECM. The ECM produced by FAP+ pericyte-like cells enhanced migration of glioma stem-like cells.

CONCLUSION
FAP+ pericyte-like cells are the main producers of fibrillar ECM proteins such as collagen I and fibronectin in GBM tissue. By this means, their presence within the GBM microenvironment affect the migration of glioma stem-like cells.
Funding: Supported by the National institute for cancer research (LX22NPO5102), Charles University Grant Agency (GAUK 1084120) and Centre for Tumour Ecology (CZ.02.1.01/0.0/0.0/16_019/0000785). EATRIS-CZ (LM2023053), Cooperatio Program, research area ,,Oncology and Haematology", and Ministry of Health of the Czech Republic (NV19 03 00501).
P12.13.B FIBROBLAST ACTIVATION PROTEIN AS A POTENTIAL THERANOSTIC TARGET IN BRAIN METASTASES OF DIVERSE SOLID TUMOURS
Authors: Vymolova B , Zubal M , Matrasova I , Vymola P , Veprkova J , Syrucek M , Tomas R , Vanickova Z , Krepela E , Konecna D , Busek P , Sedo A 
Published: September 2023

Abstract

BACKGROUND
Brain metastases (BM) are a common complication of oncologic disease associated with dismal prognosis and there is an urgent need for novel therapeutic approaches. Fibroblast activation protein (FAP), a transmembrane serine protease, is an emerging theranostic target in cancer due to its frequent upregulation in the tumour microenvironment. FAP protein itself and/or FAP+ cells were shown to promote cancer progression in several extracranial malignancies. However, very little is known about the expression of FAP and the role of FAP+ cells in the unique microenvironment of BM. In this study, we quantified FAP expression and characterized FAP+ cells in BM of various origin.

MATERIAL AND METHODS
FAP enzymatic activity and protein concentration were determined in samples of BM (n=58) and control non-tumorous brain tissue (n=12) by an enzymatic assay using a specific fluorogenic substrate, western blot, and ELISA. Expression of FAP and the characteristics of FAP+ cells were analysed by IHC (n=112). Expression of collagen was quantified by Masson´s trichrome staining (n=106) and collagen I concentration was measured by ELISA (n=56).

RESULTS
FAP expression was significantly higher in BM in comparison to non-tumorous brain tissue, both at the protein and enzymatic activity level. BM with higher FAP expression displayed higher levels of collagen I. FAP was predominantly confined to stromal cells expressing markers typical of cancer-associated fibroblasts and residing in collagen rich regions. FAP expression on tumour cells in a portion of BM was also noted , mainly in BM originating from lung, breast, and renal cancer, melanoma, and sarcoma. Increased FAP expression and the presence of FAP+ stromal cells were common features of BM irrespective of their origin.

CONCLUSION
We are the first to provide a detailed analysis of FAP expression in BM of diverse origin and characterise FAP+ cells in their microenvironment. The frequent upregulation of FAP and its presence on both stromal and tumour cells support the use of FAP as a promising theranostic target in BM.
Funding: This research was funded by the Charles University grant no. 342522 and Program Cooperatio, research area ,,Oncology and Haematology"; Ministry of Health of the Czech Republic - grant NU22-03-00318; Ministry of Education, Youth and Sports of the Czech Republic - LM2023053 of EATRIS-CZ and project “Center of Tumor Ecology” (CZ.02.1.01/0.0/0.0/16_019/0000785) - Operational Program Research, Development and Education; project National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102) by the European Union - Next Generation EU.
P12.14.B HIGHLY INVASIVE GLIOMA CELLS MOTILITY MEASUREMENTS ON A VARIETY OF EXTRACELLULAR MATRIX PROTEINS
Authors: Shevtsov M , Tagaeva R , Yudintceva N , Fedorov E , Kim A , Rozanov O , Garaev T , Samochernykh K , Bobkov D 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma multiforme (GBM) is a heterogeneous highly invasive malignant brain tumor. The extracellular matrix (ECM) produced by tumor microenvironment plays an important role in the regulation of cell motility and invasion into surrounding healthy tissue. In this research we determined the effect of various ECM proteins on the motility of primary tumor cells.

MATERIAL AND METHODS
Primary tumor cells were isolated from biopsy material obtained during GBM surgical removal. Cultivation of the piece of tumor (0.5 mm3) was carried out in the form of an 3D explant model at 37°C in 5% CO2-incubator. After several months, cells migrated from the tumor spontaneously formed spheroids. To assess the rate of cell migration, spheroids were seeded on 24-well plate coated with poly-L-lysine, fibrinogen, collagen type I, and Matrigel. After 3 days, the field of view in the well (n=9) was microphotographed every 15 min for 56 hours, after which the tracks of cells outside the spheroids were manually marked (n=50) on the obtained images. The average and maximum speeds were calculated, as well as the straightness of the track (the ratio of the Euclidean distance to the track length). The Mean square displacement (MSD) was plotted against time for each protein studied in comparison with random walk simulation calculated for the equal track parameters (number of steps, mean and sd) on correspondent protein.

RESULTS
Live-cell imaging of the patient-derived cells revealed the heterogeneous population of actively moving cells outside the spheroids. The following results of measuring cell motility were obtained (mean ± sd): (1) Mean speed on poly-L-lysine 4.3 ± 2.5 μm/h; on fibrinogen 11.1 ± 5.7 μm/h; on collagen type I 8.8 ± 5.1 μm/h; on Matrigel 9.7 ± 3.6 μm/h. (2) Max speed on poly-L-lysine 63.8 ± 30.1 μm/h; on fibrinogen 90.0 ± 38.9 μm/h; on collagen type I 96.1 ± 42.1 μm/h; on Matrigel 84.1 ± 34.1 μm/h. (3) Straightness on poly-L-lysine 0.24 ± 0.14 μm/h; on fibrinogen 0.18 ± 0.11 μm/h; on collagen type I 0.14 ± 0.09 μm/h; on Matrigel 0.20 ± 0.12 μm/h. MSD analysis showed the greatest contribution of random walk in the motility of cells on collagen type I, the smallest - on Matrigel.

CONCLUSION
Proteins of ECM affect not only the speed of cell movement, but also the tortuosity of their tracks. Further studies will clarify the mechanisms of GBM invasion depending on the composition of the ECM.
P13.04.A REPRODUCIBLE CRISPR-SEQ PIPELINE FOR NGS FUNCTIONAL GENOMICS SCREENINGS FOR GLIOMA CELL LINES
Authors: Kuhlburger L , Mir Pedrol J , Haeusser L A , Walter B , Gabernet G , Merk D , Tabatabai G , Nahnsen S 
Published: September 2023

Abstract

BACKGROUND
The CRISPR/Cas9 genome editing technology has revolutionized the field of functional genomics by enabling precise editing of DNA. Over the past few years, CRISPR technology has been widely employed to identify genetic dependencies in a broad spectrum of applications paving the way for the discovery and validation of relevant molecular targets, for example potential drug targetsGlioblastoma are incurable primary tumors of the central nervous system. Functional genomics could enable the discovery of novel therapeutic targets or even combination therapies.

MATERIAL AND METHODS
Here, we present a bioinformatics pipeline that combines functional screens and target editing analysis to identify potential vulnerabilities and drug targets in glioblastoma or other diseases. The pipeline consists of two workflows, one performing functional screening and one performing base editing analysis. This developed CRISPR-seq pipeline is reproducible and containerized, allowing high-throughput processing. All processes are modularized in Nextflow DSL2 (Domain Specific Language) and versioned which facilitates maintainability and customization, as well as the addition of new tools. A quality control report is also automatically generated, allowing the user an overview of their ran experiments. The pipeline also helps us to keep the data FAIR (Findable, Accessible, Interoperable and Reusable) and optimized, making it easier to share with other researchers and collaborate on future studies.

RESULTS
This pipeline was applied to functional screens using CRISPR/Cas9 genome-wide knockout or activation libraries to detect genetic vulnerabilities that might enhance drug treatment efficacy, e.g. for ataxia telangiectasia and Rad3 related (ATR) inhibition in experimental glioma.With this pipeline, we were able to identify several genes that are involved in drug resistance in glioblastoma, by starting from raw data (fastq files) to genes presenting vulnerabilities.The results obtained through our pipeline provided important information on the disease's molecular mechanisms, which were subsequently confirmed through wet lab validation.

CONCLUSION
In conclusion, the crisprseq software described in this abstract is a powerful tool for identifying potential genetic dependencies. The pipeline aims at analyzing this output data in a reproducible and containerized way using Nextflow and respecting nf-core community standards. By combining functional screens and base editing analysis with bioinformatics tools, this pipeline allows for the identification of essential genes and pathways, as well as the characterization of specific mutations that contribute to the development and progression of glioblastoma.
P13.13.B INTERPRETABLE WHOLE SLIDE IMAGE PROGNOSTIC STRATIFICATION OF GLIOBLASTOMA PATIENTS FURTHERING DISEASE UNDERSTANDING
Authors: Baheti B , Innani S , Mehdiratta G , Nasrallah M P , Bakas S 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma is the most common malignant adult brain tumor, with a grim prognosis and heterogeneous morphology. Stagnant patient prospects over the last 20 years reflect our limited disease understanding. Robust prognostic patient stratification from whole slide images (WSI) using interpretable computational methods could improve disease understanding and patient management.

MATERIAL AND METHODS
Assessment of the TCGA-GBM and TCGA-LGG data collections by the 2021 WHO classification criteria of CNS tumors identified 188 glioblastoma (IDH-wt, grade 4) cases, divided into short (&lt;9 months, n=94) and long (&gt;13 months, n=94) survivors. An H&E-stained WSI from each patient is selected and comprehensively pre-processed to remove artifactual and non-tissue regions by partitioning them into 256x256 patches. An interpretability mechanism via a weakly supervised attention-based multiple-instance-learning algorithm is leveraged for prognostic stratification. The attention scores are visualized as a heatmap to identify the essential ROIs driving decisions. The model is evaluated on 10-fold monte carlo cross-validation, using training (80%), validation (10%), and test (10%) sets.

RESULTS
Quantitative evaluation revealed ValidationACCURACY=70%, TestACCURACY =62%, ValidationAUC= 0.75, and TestAUC=0.68. Heatmaps indicate weight given throughout histologically malignant areas for correctly predicted long survivors, including necrosis, hypercellularity, atypia, infiltration, and proliferation. Correct prediction of short survival weighted infiltrative features, including leptomeningeal involvement. For misclassified long-survivors, necrotic areas are not heavily weighted, and gemistocytic cells are seen in a densely packed rather than infiltrating arrangement. For some misclassified short-survivors, the hot regions are hypercellular; however, these are a minority of the specimen, which predominantly showed a less cellular, fibroblastic, spindled appearance.

CONCLUSION
The interpretation of algorithmic decisions through qualitative visualization of heatmaps can offer insights into histologic regions with prognostic relevance. In the case of glioblastoma, the histologic appearance of long survivors based on a neuropathologist's observation suggests aggressive tumors traditionally considered indicative of poor prognosis. The algorithm's ability to accurately predict long survival based on these areas indicates that further investigation of these features may be warranted for improved prognostication through histologic assessment. Our findings support the use of data-driven interpretation of algorithmic decisions to identify morphological patterns with prognostic significance, which would further our understanding of glioblastoma.
P13.15.B ULTRA-FAST DEEP-LEARNED CNS TUMOR CLASSIFICATION DURING SURGERY
Authors: Vermeulen C , Pages Gallego M , Kester L , Kranendonk M , Wesseling P , Verburg N , de Witt Hamer P , Kooi E , Dankmeijer L , van der Lugt J , van Baarsen K , Hoving E , Tops B , de Ridder J 
Published: September 2023

Abstract

BACKGROUND
Central nervous system (CNS) tumors are the most lethal category of tumors, particularly among children. Most commonly, the first line treatment of CNS tumors is neurosurgical resection of the tumor. During this procedure a delicate balance must be struck between extent of resection and risk of comorbidity. Ideally, the surgical plan is based on a detailed classification of the tumor. However this classification is often unknown at the start of the surgery. Current practice consists of preoperative imaging and intraoperative diagnosis achieved by rapid histological assessment of frozen tumor sections. However, these tests do not always result in a clear diagnosis, and are sometimes even revised based on postoperative tissue-based diagnostics. As a result, some patients require a second surgery, while others could in hindsight have been operated less radically.

MATERIAL AND METHODS
Nanopore sequencing enables direct detection of DNA methylation status in real time, making it ideally suited for intraoperative sequencing and molecular tumor classification. The major challenge of this approach is that the classification must be performed on very few randomly distributed sequence reads. To this end we developed Sturgeon, a neural-network training approach that delivers classification models capable of classifying 81 different CNS tumor subtypes based on sparse methylation data. Sturgeon leverages illumina 450K DNA methylation profiles to simulate millions of nanopore sequencing experiments, which are then used to train and validate classifier models. The resulting models are portable, work across patients and sequence depths and require less than a minute of computation on a laptop CPU.

RESULTS
We demonstrate our method to be fast enough to provide a correct diagnosis with as little as 20 to 40 minutes of sequencing in 45 out of 50 retrospective pediatric brain tumor samples. We applied Sturgeon in an intraoperative setting in 25 cases, where we consistently achieve a turnaround time of 60-90 minutes from biopsy to result with a correct molecular subclassification in 18 cases and an inconclusive result in 7 cases.

CONCLUSION
Sturgeon classification can be used in parallel with intraoperative frozen section histology. In cases where it agrees with the pathologist, Sturgeon offers a valuable independent confirmation, and a more detailed molecular subclassification. In the rare cases where Sturgeon disagrees with the histology diagnosis, or where the histology is inconclusive, it has the potential to prevent misdiagnoses that would result in unnecessary risk of comorbidity, or the requirement for a second surgery.
P14.02.B LONGITUDINAL COMPARATIVE ANALYSIS OF BLOOD NEUROFILAMENTS AS BIOMARKERS OF CHEMOTHERAPY-INDUCED PERIPHERAL NEUROTOXICITY
Authors: Velasco R , Marco C , Ferrer G , Domingo-Domènech E , Stradella A , Santos C , Laquente B , Argyriou A , Bruna J 
Published: September 2023

Abstract

BACKGROUND
The identification of a biomarker of chemotherapy-induced peripheral neurotoxicity (CIPN) remains an unmet need. Increasing evidence supports that light-chain Neurofilament (NfL) could be useful to quantify the extend of peripheral nerve damage due to chemotherapy. The aim of the study is to ascertain differences in plasma NfL (pNfL) among agents to evaluate the clinical usefulness of pNfL.

MATERIAL AND METHODS
Prospective longitudinal comparative study including patients treated with paclitaxel (N=24) for breast cancer, brentuximab vedotin (BV) (n=20) for lymphoma and oxaliplatin (n=16) for gastrointestinal cancer. All patients were assessed using the Total Neuropathy Score-clinical, Common Toxicity Criteria for Adverse Events before (T1), at finishing (T2) and at next follow-up (T3). Serial pNfL were collected at the same timepoints and quantified using the SIMOA technique. The changes in pNfL were compared between group of agents (platinum (oxaliplatin) or microtubule disruptors (MT) (BV or paclitaxel) and correlated with clinical data, depending on the degree of CIPN. Clinically relevant (CR) was defined as &gt; grade 2-CIPN.

RESULTS
60 patients are included, mostly women (66,7%) with median age of 52 [22-88] years. pNfL at T1 was 16,51 ± 1,65 pg/mL, and correlated with age (r= 0.284, p &lt; 0.036). pNfL increased at T2 (141,39 ± 18,89 pg/mL) and decreased at last follow-up (T3) (28,08 ± 2,52 pg/mL) in the whole series, at a median of 3 (1-5) months after finishing chemotherapy. Patients with CR-CIPN had higher pNfL at T2 (209,90 ± 40,09 vs 103.02 ± 96.74 pg/mL, p=0.005). One third of patients receiving MT disruptors (31,6%) or platinum agents (35,7%) developed CR-CIPN. Higher pNfL level at T2 were identified in patients receiving anti MT agents than oxaliplatin (160, 27 ± 22,75 vs 70,04 ± 11,24 pg/mL), p&lt;0,001). Among the group of MT, pNfL at T2 were higher in those receiving paclitaxel compared to BV (233,90 ± 31.84 vs 62,09 ± 9.60 pg/mL, p&lt;0.001), despite no differences in rate of CR-CIPN (26,6% BV and 34.7% Paclitaxel, p=0.7). At T3, no differences in pNfL were identified between BV (33,53 ± 4,67 pg/mL) and paclitaxel (29,20 ± 4,24 pg/mL) treated patients. A significant correlation between pNfL and TNSc was identified (r = 0.663, p &lt; 0.001).

CONCLUSION
Variable change of pNfL according to the type of agent and mechanism of neurotoxicity can be observed regardless of the comparable degree of clinical CIPN severity. Further studies to better dissect cut-off values for each agent are needed before implementing pNfL as CIPN biomarker.
P15.06.A HYBRID [18F]FET PET-MRI; A VALUABLE ADVANCED IMAGING TOOL TO DISCRIMINATE BETWEEN TUMOR RECURRENCE AND PSEUDOPROGRESSION IN GLIOMA PATIENTS
Authors: de Jong J , Pruis I J , Valkema R , van den Bent M J , Veldhuijzen van Zanten S E M 
Published: September 2023

Abstract

BACKGROUND
One of the well-known challenges in the response assessment of glioma patients is differentiating tumor recurrence from treatment-related effects, i.e. pseudoprogression. The PET tracer O-(2-18F-fluoroethyl)-L-tyrosine ([18F]FET) visualizes increased amino acid metabolism and can potentially aid differentiation between vital tumor tissue and reactive changes, and can herewith guide clinical decision-making and surgical planning. This study aimed to assess the diagnostic yield of hybrid [18F]FET PET-MRI in a series of pre-treated patients suspected of glioma recurrence.

MATERIAL AND METHODS
This retrospective study included histologically-confirmed glioma patients who had undergone standard-of-care therapy consisting of gross-total resection surgery and/or radiotherapy. [18F]FET PET-MRI scans were performed between 04/2022 and 03/2023. Patient received 204 MBq (median, range: 180-242) [18F]FET intravenously, followed directly by a 45 minute dynamic PET and simultaneous MRI including DWI and gadolinium-based sequences (PWI). Time-activity-curves (TACs), showing the mean tissue radioactivity in tumor regions of interest as a function of time, were compared to the TAC in healthy tissue. Static PET images for qualitative visual analysis were reconstructed by accumulating the 20-40 minute timeframes. Tumor recurrence (i.e., a positive scan) was defined as focal uptake exceeding uptake in healthy brain parenchyma according to the joint EANM/EANO/RANO practice guideline/SNMMI procedure standard. Outcomes were compared to previously-obtained MRIs, post-operative pathology, and clinical/radiological follow-up.

RESULTS
Thirteen patients, 31% female, median age 39 (range: 28-50), with astrocytoma (grade 2_n=2; grade 3_n=1; grade 4_n=2), oligodendroglioma (grade 2_n=6; grade 3_n=1), and glioblastoma (n=1) were included. [18F]FET PET-MRI was positive in 9/13 patients (70%), which in 5/9 (55%) was confirmed by pathology (n=3) or clinical follow-up (n=2). In 6/9 patients with a positive scan (66%), the previously-obtained MRI (time interval range: 0.5-4.1 months) showed negative (n=4) or unclear (n=2) DWI and PWI findings. Four/13 (30%) patients had a negative [18F]FET PET-MRI and did not show signs of tumor progression after an average follow-up of 3, 5, 11 and 12 months, respectively.

CONCLUSION
Simultaneous [18F]FET PET-MRI shows high potential for accurate differentiation between true tumor progression and treatment-related pseudoprogression in glioma patients with equivocal findings on MRI including DWI and PWI. The diagnostic yield of this hybrid imaging technique exceeded that of MRI-only in our case series, and thus provides a promising advanced imaging tool in the follow-up of glioma patients. We aim at prospective studies to validate the clinical value of this multimodal approach.