bluuebunny/crossref_metadata_2025_split huggingface dataset:
P12.03.A MULTIMODAL ANALYSIS OF GLIOBLASTOMA REVEALS THE POTENTIAL OF CXCR7-CXCL12 IN GBM CELLS SENSITIZES GBM TO IMMUNE CHECKPOINT BLOCKADE THERAPY
Authors: Liu C , Chien C , Yang W , Chuang J , Chang K 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma (GBM), a WHO Grade IV glioma, is one of the most lethal brain tumors. In spite of the standard of care and currently developed advanced treatment, the prognosis of GBM patients is still poor. In addition to the understanding of GBM cells, the microenvironment plays a critical role in regulating GBM progression. Also, more and more information indicates the interaction of GBM-associated macrophages (GAMs) and GBM cells facilitates GBM progression via sculpturing immunosurveillance, cancer stemness, and cancer resistance. And thus, we hypothesized that GBM cells sculptured the microenvironment via macrophage alternation of which interventions may potentialize immune checkpoint blockade therapy.

MATERIAL AND METHODS
The bulk RNA sequencing (seq.) of the paired primary-recurrent GBM specimens, single-cell RNA seq., in vitro (including mRNA, protein, and cell behavior tests), and in vivo validation, were integrated to explore our hypothesis.

RESULTS
The bulk RNA seq. of the paired primary-recurrent GBM specimens showed recurrent GBM enhanced the neuroinflammation pathway. Among the secretory components, CXCL12, also known as stromal cell-derived factor 1 was accumulated during GBM progression and upregulated in temozolomide (TMZ)-resistant GBM cells compared with parental GBM cell lines. In addition, the newly CXCL12 receptor CXCR7 may act as a scavenger to breakdown CXCL12-CXCR4 positive feedback in GBM resistance. Moreover, the bulk RNA sequencing seq. showed that recurrent GBM reduced CXCR7 expression. Single-cell RNA seq. of GBM patients’ specimens suggested that CXCR7 was majorly expressed in GBM cells than in normal neural and immune cells. Developing TMZ resistance in GBM cell lines also down-regulated CXCR7 expression. Furthermore, silencing CXCR7 attenuated TMZ cytotoxicity while silencing CXCR7 and CXCL12 simultaneously reversed the effects. In contrast, combining CXCR7 agonists and TMZ enhanced TMZ cytotoxicity Otherwise, the GBM-associated CXCL12 activated M0 macrophages into GAMs by facilitating macrophage proliferation and inducing pro-tumor factors, including IL-1β and its receptors, IL-6, MMP9, and immune checkpoint PD-L1. Mechanistically, GBM-associated CXCL12 upregulated PD-L1 in GAMs via NF-κB. Also, in the orthotopic GBM mouse model, CXCR7 knockdown in GBM cells led to poor survival and increased PD-L1 expression in GAMs. Finally, we combined CXCR7 agonist and anti-PD-L1 to show prolonged survival, in contrast, anti-PD-L1 did not show this effect.

CONCLUSION
In accordance with the multimodal analysis, GBM regulated the accumulation of CXCL12 via silencing CXCR7 in GBM cells. The CXCR7-CXCL12 axis confers the immunosuppression by up-regulating PD-L1 in GAMs. Our study suggested that CXCR7 activation treatment alone or combined with an immune checkpoint inhibitor may be a potential strategy for the treatment of GBM.
P12.07.B THE POST-SURGICAL MICROENVIRONMENT OF GLIOBLASTOMA AS THERAPEUTIC TARGET TO AVOID RECURRENCES
Authors: TCHOGHANDJIAN A 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma (GBM) is an incurable primary brain tumour. Most GBM patients undergo surgery prior to chemoradiation, but recurrences inevitably lead to patient death. The brain physiological regenerative responses following tumor debulking have a beneficial role in the healing process. However, they also evoke characteristic time-dependent peritumoral immune responses which can promote the formation of recurrences. The crosstalk between glial, immune and GBM cells at the surgical borders and their impact on recurrences still lacks appropriate characterization. This project aims at dissecting the GBM post-surgical microenvironment (SMe) over time and space to identify therapeutic targets and develop tailored GBM therapies to avoid the onset of recurrences.

MATERIAL AND METHODS
We developed a tumor resection model in transgenic mice bearing GL261 tumors and established a chronic intracranial window post-surgery by biphotonic imaging. Nuclear imaging was performed at defined time points using 99mTc-DTPA, 68Ga-RGD and 18F-FDG to evaluate neuroinflammation, neoangiogenesis, infiltrating tumor cells metabolism and BBB permeability. The dynamics of the inflammatory landscape following surgery was characterized by blood sampling and post-mortem analysis on brain samples (peripheral and local immunophenotyping by multiparametric flow cytometry; brain clearing and ultramicroscopy).

RESULTS
We analyzed the dynamics of recruitment and localization of immune cells coming to the resection site from the brain parenchyma or from the periphery from surgery to recurrence. BBB disruption was observed post-surgery followed by a recovery within three days. Based on the results obtained we finally tested a therapeutic approach combining the local administration of lauroyl-gemcitabine lipid nanocapsules hydrogel with the repeated systemic administration of a SMAC-mimetic drug showing an increase in survival of GBM-bearing mice.

CONCLUSION
This comprehensive study expands the knowledge on the SMe by analyzing the impact of BBB disruption on immune cells recruitment and the role of lymphoid and myeloid populations - as well as macrophages and microglia - on the onset of tumor recurrences. Moreover, it proposes a rationally designed combinatory treatment able to target the identified cellular targets to delay or inhibit the onset of recurrences.
P12.15.A THE IMPACT OF MICROGLIA MODULATION ON THE IMMUNE TUMOR MICROENVIRONMENT IN SYNGENEIC GLIOBLASTOMA MOUSE MODELS
Authors: Kaymak D , Shekarian T , Ritz M , Ferrari N , Kälin R , Glass R , Hutter G 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma is exceptionally resistant to T-cell targeting immunotherapies for which the immunosuppressive myeloid compartment is held responsible. As influencer and instructor of antitumoral T-cell-immunity this compartment mainly consists of Monocyte-derived Cells (MdCs) and tissue-resident (TR) macrophages called microglia (MG). Since the response to immunotherapies depend on antigen presenting cells at the tumor site, we aim to investigate this compartment and its individual role in tumor progression by genetically depleting/activating the TR MG.

METHODS
We made use of two MG-specific and tamoxifen inducible knockout mouse models in which 1) we activate MG by excision of the activation-repressing transcription factor Sall1 (Sall1CreERT2/wt x Sall1fl/wt) and 2) deplete MG by deleting the “survival-receptor” Csf1r on MG (Sall1CreERT2/wt x Csf1rfl/fl). To investigate the effect of MG activation and depletion on the immune tumor microenvironment (iTME), immunocompetent mice were engrafted with syngeneic glioma cells (CT-2A, GL261) and the iTME subsequently characterized by scRNAseq, spectral flow cytometry and immunofluorescence imaging.

RESULTS
Upon Sall1-KO MG demonstrate a morphologically reactive phenotype reminiscent of activated MG. The MG-specific deletion of Csf1r effectively depletes the brain parenchyma of TR MG which rapidly gets repopulated by a morphologically distinct microglia-(like) population. Genetic activation of MG leads to a survival benefit in Gl261-engrafted mice compared to Cre-negative littermates. In contrast, depletion of MG significantly reduces the survival in Gl261 and CT-2A engrafted mice. ScRNAseq confirms the effective depletion of MG and the subsequent emergence of a microglia-like cell population that despite microscopical resemblance to MG, transcriptionally remains distinct. The iTME in MG-depleted mice is characterized by a decreased abundance of exhausted and naïve CD8-Tcells and an increased infiltration of MdCs. Gene set enrichment analysis demonstrate a dampened inflammatory immune profile of infiltrating MdCs highlighted by a downregulation of hallmark gene sets of “interferon-α and γ response” and “TNFα-signaling via NF-κB”.

CONCLUSION
The presence of MG orchestrate the development towards a more antitumorigenic iTME by shaping the antitumoral response of incoming myeloid cells and furthermore directly or indirectly influencing T-cell immunity. Understanding this interplay of MG and MdCs in cancer and its impact on instruction of antitumoral T-cell immunity could help guiding the development of novel immunotherapeutic strategies in GBM.
P13.02.A APPLICATION OF NOVEL PACS-BASED INFORMATICS PLATFORM TO IDENTIFY IMAGING BASED PREDICTORS OF CDKN2A ALLELIC STATUS IN GLIOBLASTOMAS
Authors: Tillmanns N J , Lost J , Tabor J , Vasandani S , Vetsa S , Marianayagam N , Yalcin K , Erson-Omay Z , von Reppert M , Jekel L , Merkaj S , Ramakrishnan D , Avesta A , Dixe de Oliveira Santo I , Jin L , Huttner A , Bousabarah K , Ikuta I , Lin M , Aneja S , Turowski B , Aboian M , Moliterno J 
Published: September 2023

Abstract

BACKGROUND
Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features withVisually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS.

MATERIAL AND METHODS
Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithmsincorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS.

RESULTS
GBMs without CDKN2A alterations were significantly larger (64% vs. 30%, p=0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI:1.5-12.1; p&lt;0.001). The pial invasion was predictive of HOMDEL (OR: 8.1, 95% CI: 1.8-53.2; p&lt;0.012) as tumors with pial invasion were eight times more likely to be HOMDEL, even after adjusting for deep white matter and subependymal invasion.

CONCLUSION
We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.
P13.05.B INCORPORATION OF AI-BASED AUTOSEGMENTATION AND CLASSIFICATION INTO NEURORADIOLOGY WORKFLOW: PACS-BASED AI TO BUILD YALE GLIOMA DATASET
Authors: Tillmanns N , Lost J , Merkaj S , von Reppert M , Chadha S , Lin M , Bousabarah K , Huttner A , Aneja S , Avesta A , Omuro A , Aboian M 
Published: September 2023

Abstract

BACKGROUND
Translation of AI algorithms into clinical practice is significantly limited by lack of large individual hospital-based datasets with expert annotations. Current methods for generation of annotated imaging data are significantly limited due to inefficient imaging data transfer, complicated annotation software, and time required for experts to generate ground truth information. We incorporated AI tools for auto-segmentation of gliomas into PACS that is used at our institution for reading clinical studies and developed a workflow for annotation of images and development of volumetric segmentations in neuroradiology clinical workflow.

MATERIAL AND METHODS
1990 patients from Yale Radiation Oncology Registry (2012-2019) were screened. Segmentations were performed using a UNETR algorithm trained on BRaTS 2021 and an internal dataset of manually segmented tumors. AI generated segmentation can be revised and confirmed in PACS. Segmentations were validated by a board-certified neuro-radiologist, after which natively embedded PyRadiomics in PACS was used for direct feature extraction.

RESULTS
In 7 Months (05/2021 - 08/2021, 03/2022 - 05/2022) segmentations and annotations were performed in 1033 patients (429 female, 604 male, mean age 53 yrs). Dataset includes 595 Grade 4 Gliomas (96 Grade 3, 105 Grade 2, 45 Grade 1, 192 unknown). Molecular subtypes include IDH (129 mutated, 651 wildtype, 253 unknown), 1p/19q (94 deleted or co-deleted, 135 intact, 804 unknown), MGMT promotor (216 methylated, 110 partially methylated, 321 unmethylated, 383 unknown), EGFR (125 amplified, 248 not amplified, 660 unknown), ATRX (41 mutated, 238 retained, 754 unknown), Ki-67 (726 known, 307 unknown) and p53 (639 known, 394 unknown). Classification of gliomas between grade 3/4 and grade 1/2, yielded AUC of 0.85.

CONCLUSION
We developed a method for incorporation of volumetric segmentation, feature extraction, and classification that is easily incorporated into neuroradiology workflow. These tools allowed us to annotate over 100 gliomas per month, thus establishing a proof of concept for rapid development of annotated imaging database for AI applications.
P13.09.B FULLY AUTOMATED BRAIN METASTASES SEGMENTATION USING T1-WEIGHTED CONTRAST-ENHANCED MR IMAGES BEFORE AND AFTER STEREOTACTIC RADIOSURGERY
Authors: Kanakarajan H , De Baene W , Verhaak E , Hanssens P , Sitskoorn M 
Published: September 2023

Abstract

BACKGROUND
Brain metastases (BM) represent the most common intracranial tumor in adults. An estimated 20% of all patients with cancer will develop BM. Stereotactic Radiosurgery (SRS) is a major treatment option for BM. For SRS treatment planning and outcome evaluation, magnetic resonance images (MRI) are acquired before and at multiple stages during the follow-up. Accurate segmentation of brain tumors on MRI is crucial for treatment planning and response evaluation. Detection and segmentation of BM which is a tedious and time-consuming task for many radiologists could be optimized with machine learning

METHODS
. The accuracy of the auto-segmentation, however, is influenced by the presence of false-positive and false-negative segmentation. There are studies which evaluated the segmentation performance of several deep learning algorithms, these were mainly focused on training and testing the models on either the pre-treatment or post-treatment images. The purpose of this study was to investigate a well-known deep learning approach (nnU-Net) for BM segmentation and to evaluate its performance on both pre-treatment and post-treatment images to assess if it could be a handy tool for the clinicians.

METHODS
Pre-treatment T1-weighted brain MRIs which were contrast-enhanced with triple-dose gadolinium were collected retrospectively for 266 patients with BM. Scans were made as part of clinical care at the Gamma Knife Center of the Elisabeth-TweeSteden Hospital (Tilburg, the Netherlands). All patients underwent Gamma Knife Radiosurgery, a form of SRS. This total of 266 patients were randomly split into 210 patients for model training/validation and 56 patients for testing. For these 56 patients used for testing, the post treatment follow-up T1-weighted brain MRI scans which were contrast-enhanced with single-dose gadolinium were also retrospectively collected. The nnU-Net model was trained with the pre-treatment training data, and then tested separately against the pre-treatment and follow-up data.

RESULTS
The model obtained a Dice score of 0.91 when tested with the pre-treatment images and a Dice score of 0.80 when tested with the follow-up after treatment T3 images. The False Negative Rate (FNR) when tested with the pre-treatment images was 0.07 and 0.24 when tested with post-treatment T3 images.

CONCLUSION
The model achieved a good performance score for pre-treatment images. The nnU-Net model can automatically detect and segment brain metastases with high sensitivity, and low FNR for treatment planning. This could be a beneficial tool for clinicians and assist SRS management for diagnosis and treatment planning. Though there is a decline in the Dice score and an increase in the FNR of the model for the post-treatment images, the performance still remained higher than in other similar studies.
P13.11.B CLINICAL-RADIOMICS MODEL FOR LOW-GRADE GLIOMA SURVIVAL PREDICTION
Authors: Neimantaite A , Carstam L , Gómez Vecchio T , Dunås T , Häggström I , Smits A , Jakola A S 
Published: September 2023

Abstract

BACKGROUND
Low-grade gliomas are by the latest WHO classification exclusively IDH-mutated tumors, and are further divided into astrocytomas (1p19q non co-deleted) and oligodendrogliomas (1p19q co-deleted). Radiomics, that is extraction of mathematical features of images, has prognostic potential and the method is able to capture properties of whole tumors, in contrast to typical biological samples. Our aim was to investigate how a radiomics prognostication model performs in relation to a clinical prognostication model for IDH-mutated tumors.

MATERIAL AND METHODS
143 cases (71 astrocytomas and 72 oligodendrogliomas) were included in the analysis. Median follow-up time was 75 months. The data was divided in training and test set with 70:30 ratio. Four different radiomics models were investigated including image features extracted from tumor and peritumor zones respectively.

RESULTS
Preliminary results have shown best radiomics model performance for prognostication purposes in IDH-mutated tumors were based on the peritumoral zone 0-10 mm around the segmented tumor. This model resulted in a c-index of 0.88 on training set and 0.76 on test set in explaining the overall survival when the cohort of IDH-mutated tumors were analyzed together. The model will also be evaluated in the molecular subgroups and on an external test set, and finally compared to a clinical model.

CONCLUSION
Our findings will identify the top features in radiomics prognostication of IDH-mutated tumors, and also provide important data on the best area for radiomics extraction in these cases. The clinical implications of our findings will show whether radiomics adds additional value to the clinical model of low-grade glioma prognostication.
P14.06.A GLIOMA ESPIONAGE: UTILIZING CSF PROTEOMICS FOR PHARMACODYNAMIC BIOMARKER DISCOVERY
Authors: Riviere-Cazaux C , Carlstrom L , Munoz-Casabella A , Andersen K , Ikram S , Warrington A , Burns T 
Published: September 2023

Abstract

BACKGROUND
Cerebrospinal fluid (CSF) is emerging as an abundant source of candidate biomarkers, including proteins, for gliomas. Longitudinal CSF access may enable insights into treatment response and resistance. To that end, we have established a growing biobank of CSF samples, many of which have been obtained longitudinally via CSF access devices, such as Ommaya reservoirs, through our ongoing biomarker discovery clinical trials (NCT04692337, 04692324). We have previously presented our initial data demonstrating a conserved proteomic signature of HGG that decreased with resection and increased with recurrence. Since then, samples have been acquired throughout individual patients’ treatments toward our goal of identifying CSF-derived biomarkers of treatment response.

MATERIAL AND METHODS
CSF samples obtained prior to, during, and throughout treatment underwent global proteomics analysis via the SomaScan® assay by Somalogic, which uses slow off-rate modified aptamers to sensitively detect over 7,000 proteins. Fold-changes for each protein were calculated between different timepoints for each patient and ranked based on the comparison of interest. Comparisons included prior to versus after resection, chemoradiation or adjuvant temozolomide (each with or without pembrolizumab), bevacizumab, and low versus high blood contamination.

RESULTS
Treatment with pembrolizumab alone resulted in increased IL-23 (5.01x), IL-12 (4.25x), lymphocyte activation gene 3 protein (LAG3) (3.26x), and granzyme A (2.93x). Chemoradiation, with or without pembrolizumab, consistently downregulated NAD kinase, acetyl CoA transferase, and Bcl-2 and upregulated proteins related to neuronal signaling, such as neurexins and cerebellins, in addition to LAG-3, suggesting potential for synergy between chemoradiation and anti-LAG-3 antibodies currently in clinical trials. Interestingly, pembrolizumab and chemoradiation decreased MMP-12 and MMP-9 abundance as compared to chemoradiation alone (0.25x vs. 18.5x; 0.54x vs. 4.99x). Finally, bevacizumab treatment consistently increased VEGF (7.32x), GFAP (3.38x), and MMP-3 (2.99x) abundance, while decreasing the presence of our previously reported plasma-associated protein signature in CSF, suggesting decreased blood-brain barrier disruption.

CONCLUSION
The global CSF proteome can be longitudinally accessed to evaluate response to standard-of-care and experimental therapies. Further studies are ongoing to identify signatures of therapeutic resistance and to assess the impact of novel immunotherapeutic combinations on the CSF proteome.
P15.11.B POSTOPERATIVE68GA-DOTATATE/PET-CT IMAGING IS PROGNOSTIC FOR PROGRESSION-FREE SURVIVAL IN MENINGIOMA WHO GRADE 1: A PROSPECTIVE SINGLE-CENTER STUDY
Authors: Teske N , Biczok A , Quach S , Dekorsy F J , Forbrig R , Bodensohn R , Niyazi M , Tonn J , Albert N L , Schichor C , Ueberschaer M 
Published: September 2023

Abstract

BACKGROUND
Microsurgical tumor resection represents the first-line treatment for symptomatic meningiomas, and extent of resection has been shown to be of prognostic importance. Assessment of tumor remnants with somatostatin receptor PET proves to be superior to intraoperative estimation with Simpson grading or MRI. However, prognostic relevance of postoperative PET for progression-free survival in meningiomas remains unclear.

METHODS
We conducted a prospective study including patients with surgically removed meningioma WHO grade 1 and collected clinical and imaging data. All patients received postoperative MRI and 68Gallium-DOTATATE/PET, and were followed regularly with MRI surveillance scans for detection of tumor recurrence/progression.

RESULTS
We included 46 patients with 49 tumors. Mean age at diagnosis was 57.8 ± 1.7 years with a male-to-female ratio of 1:1.7. Local tumor progression occurred in 7/49 patients (14%) after a median follow-up of 52 months. Positive PET was associated with an increased risk for progression (*p = 0.015) and a lower progression-free survival (*p = 0.029) whereas MRI was not. 20/20 patients (100%) with negative PET findings remained recurrence-free. Location of recurrence/progression on MRI was adjacent to regions where postoperative PET indicated tumor remnants in all cases. Gross tumor volumes were higher on PET compared to MRI (*p = 0.032).

CONCLUSION
Our data show that 68Ga-DOTATATE/PET is highly sensitive in revealing tumor remnants in patients with meningioma WHO grade 1. Negative PET findings were associated with a higher progression-free survival, thus improving surveillance. In patients with tumor remnants, additional PET can optimize adjuvant radiotherapy target planning of surgically resected meningiomas.