bluuebunny/crossref_metadata_2025_split huggingface dataset:
P13.03.B PREDICTING FUNCTIONAL CONNECTIVITY FROM STRUCTURAL CONNECTIVITY IN GLIOMA PATIENTS
Authors: Smolders L , De Baene W , Florack L , van der Hofstad R , Rutten G 
Published: September 2023

Abstract

BACKGROUND
The mechanism by which activity in the brain relates to its anatomical structure is a central topic of research in neuroscience. In recent years, this relation has been studied in the context of network science, where anatomical white-matter connections are captured in Structural Connectivity (SC) and statistical dependence between grey-matter activity in Functional Connectivity (FC). The relation between SC and FC is poorly understood at an individual level, especially in glioma patients. Developing methods to predict FC from SC in these patients could improve our understanding of how gliomas affect brain function, and consequently cognition. Furthermore, a model accurate at individual patient level could aid in clinical decision-making by identifying eloquent areas and connections in individuals.

MATERIAL AND METHODS
Building on earlier work predicting FC from SC in healthy subjects, we trained a deep learning model on tractography and resting-state fMRI data of 288 glioma patients to predict FC at an individual level. Since our sample size is modest in the context of deep learning, we attempted to improve accuracy by pre-training the model on a large set of healthy subjects. This way, the model should learn baseline patterns in SC and FC before learning the specific patterns associated with glioma patients. We used data from 1052 subjects of the Human Connectome Project and 633 subjects of the Cambridge Centre for Ageing and Neuroscience. Finally, we analyzed the effect of several factors on prediction accuracy: tumor volume, location and grade and patient age.

RESULTS
Training on only the patient set, the prediction model achieved an accuracy, measured as correlation between predicted and empirical FC, of 0.53 ± 0.03 at individual patient level. This is comparable with accuracy achieved in studies on healthy subjects. Pre-trained models did not improve accuracy. The model had more difficulty predicting FC in patients with a glioma in the insular region (p = 0.0014). No other factors were associated with accuracy.

CONCLUSION
Although further research is required to investigate the utility of FC predictions made by our model, our work is a first step towards predicting activity from brain structure in glioma patients at an individual level, since earlier research in patient populations has focused on group-level effects. We observed that predictions are less accurate in patients with a glioma in the insular region, which indicates that the relation between the structural and functional organization of the brain in this group is different from that in patients with tumors in other locations. Improving our methods to achieve higher accuracy could provide us, as a next step, with a tool to predict functional consequences of resective surgery on glioma patients, and consequently improve decision making by more accurately identifying eloquent regions at an individual level.
P13.07.B IMMUNE AND CELL PROLIFERATION PATHWAYS CONTRIBUTE TO THE SEX DIFFERENCES IN A-TO-I RNA EDITING-BASED SUBTYPING OF GLIOBLASTOMA
Authors: Chen S , Wong S 
Published: September 2023

Abstract

BACKGROUND
A-to-I RNA editing has been recently identified as a sex-specific prognostic factor for glioblastoma (GBM). However, the underlying molecular mechanisms of sexual dimorphism are still understudied. We aimed to identify genes displaying sexual dimorphism in patient survival and investigate their involvement in the pathogenesis of GBM.

METHODS
We performed differential expression analyses on bulk RNA-Seq data between GBM patients with distinct survival rates, controlling for sex and the sex-survival interaction. Two principal components that captured the effects of both survival and the sex-survival interaction were constructed to rank genes for gene set enrichment analysis (GSEA). We also analyzed single-cell RNA-Seq data to evaluate the interactions of sexually dimorphic genes between different cell types.

RESULTS
A negative correlation was found between survival and the sex-survival interaction, indicating a substantial proportion of DEGs with sexually dimorphic prognostic value. GSEA revealed that immune-related pathways exhibited higher expression in males with a favorable prognosis, while females with a poor prognosis showed elevated expression levels in these pathways. Conversely, cell proliferation and stemness pathways were more highly expressed in males with a poor prognosis, whereas females with a favorable prognosis displayed higher expression levels in these pathways. Additionally, we found 22 DEG-associated cell-cell interactions, many of which were between macrophage/microglia and tumors.

CONCLUSION
Our findings suggest that sexual dimorphism of RNA editing may be attributed to cell proliferation and immune-related pathways. Moreover, our results provide valuable insights into the underlying mechanisms of cellular communication during the pathogenesis of GBM.
P13.16.A MACHINE LEARNING-BASED RADIOMIC MODEL USING MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING FOR PREDICTION OF POSTOPERATIVE VISUAL RECOVERY OF PITUITARY ADENOMA PATIENTS
Authors: Zhang Y , Chen C , Xu J 
Published: September 2023

Abstract

BACKGROUND
Preoperative prediction of the visual outcome after pituitary adenoma surgery is crucial to clinical decision-making but remains challenging. We aimed to develop radiomic models based on multiparametric magnetic resonance imaging (MRI) to predict the postoperative visual outcome for pituitary adenoma patients using machine learning approaches.

MATERIAL AND METHODS
A cohort of 152 patients who underwent endoscopic endonasal transsphenoidal surgery of pituitary adenomas were retrospectively enrolled and divided into the recovery group and the non-recovery group based on the six-month postoperative visual examinations. Radiomic features of the optic chiasm were extracted from preoperative T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (T1CE), respectively. Predictive models were constructed by least absolute shrinkage and selection operator wrapped with support vector machine through the five-fold cross-validation in the development cohort, and then evaluated in the independent test cohort. Area under the receiver operating characteristic curve (AUC), accuracy, specificity and sensitivity were used to assess the predictive performance of models.

RESULTS
A total of four predictive models were established based on selected radiomic features from three sequences individually or in combinations. Three features from T1WI, two features from T2WI and nine features from T1CE were selected in the multiparametric radiomic model that represented the best performances among the four models, with AUC values of 0.851 (95% CI: 0.768 - 0.933) in the development cohort and 0.847 (95% CI: 0.722 - 0.971) in the independent test cohort.

CONCLUSION
Our proposed machine learning-based radiomic model using multiparametric MRI can be utilized to assist in predicting the postoperative visual recovery of pituitary adenoma patients in clinical practice.
P13.17.B PREDICTING KI-67 PROLIFERATION INDEX OF MENINGIOMAS ON MRI: A DEEP LEARNING METHOD BASED ON MULTI-MODAL INFORMATION
Authors: Chen C , Xu J 
Published: September 2023

Abstract

BACKGROUND
A high Ki-67 index usually suggests accelerated cell proliferation of meningioma related to significant tumor growth as well as increased recurrent risk. This study aimed to explore the feasibility of deep learning method in predicting Ki-67 index of meningiomas with multi-modal information.

MATERIAL AND METHODS
Pre-treatment magnetic resonance images were retrospectively curated from 521 patients with surgically resected, pathologically confirmed meningiomas from three institutions. The cases were classified into low-expressed or high-expressed groups with a threshold of 5% of Ki-67 index. Predictive models were developed with multi-modal deep learning network by using traditional radiological findings, radiomics features extracted from tumors, and MRIs of meningiomas. The performance of the models was evaluated with area under curve (AUC), accuracy (ACC), sensitivity, and specificity. In addition, 127 cases with incidental small meningioma were recruited and followed up in 2 years, to investigate if the model could be used for predicting the tumor growth to assist in patient management.

RESULTS
Overall, 371 patients were enrolled for model development and primary analysis. The predictive model showed good performance with AUC of 0.798, ACC of 0.710, sensitivity of 0.613, and specificity of 0.806 in the internal test. It also achieved robustness in the external test cohort consisted of 150 cases, with AUC of 0.758, ACC of 0.661, sensitivity of 0.677, and specificity of 0.645. Moreover, model-predicted high Ki-67 tumor was associated with significant tumor volume growth happened in two years.

CONCLUSION
The predictive model can efficiently predict the Ki-67 index in meningioma patients, and showed good potential in facilitating the therapeutic decisions.
P14.09.B IS BLOOD-DERIVED EXOSOMAL HTERT TRANSCRIPT A MARKER OF ONCOGENIC ACTIVITY IN PRIMARY BRAIN TUMORS? AN EXPLORATORY STUDY
Authors: Uziel O , Kanner A , Beery E , Lev S , Lahav M , Horn-Fichman S , Har Nof S , Laviv Y , Yust Katz S , Amiel A , Levi-Barda A , Raanani P , Sela Y , Cohen Z , Siegal T 
Published: September 2023

Abstract

BACKGROUND
In order to proliferate indefinitely, all tumors require a telomere maintenance mechanism. The expression of human telomerase reverse transcriptase (hTERT) enables telomere maintenance and provides cancer cells with limitless replicative potential. As such, it may serve as an attractive biomarker for oncogenic activity. This study explored whether a liquid biopsy that analyses blood derived exosomal hTERT transcript (e-hTERT-trans) may serve as such a biomarker in gliomas and meningiomas when compared to healthy controls.

MATERIAL AND METHODS
Exosomes were isolated from the pre-operative sera of patients’ samples stored in the biobank of both Rabin and Sheba Medical Centers. The levels of e-hTERT-trans were measured in 81 healthy controls, 117 meningiomas, 17 low-grade gliomas, and 61 glioblastomas. Clinical parameters of the patients were collected retrospectively and compared to the levels of the e- hTERT-trans.

RESULTS
The Upper normal limit of controls e-hTERT-trans was 1.85 relative quantitation (RQ). The rate of detection increased with rising tumor grade and correlated with tumor recurrence in meningiomas: mean RQ without recurrence (2.17+11.7) vs. with recurrence (3.59+4.42; p=0.002). In glioblastomas, pre-operative measurements correlated with tumor volume and with the disease course on serial sampling.

CONCLUSION
We demonstrated for the first time that the expression of e-hTERT-trans transcript can be measured in the serum of primary brain tumors. This exosomal marker carries the potential to serve as a biomarker once used in conjunction with other clinical and radiological parameters. Future studies are required to investigate whether the sensitivity could be augmented and whether it can be implemented into routine patients care.
P17.05.A TUMOR-TREATING FIELDS COMBINED WITH SECOND-LINE CHEMOTHERAPY REACHED PROGRESSION FREE SURVIVAL OF 8.33 MONTHS IN CHINESE RECURRENT GLIOBLASTOMA
Authors: Guo C , Yang Q , He Z , Duan H , Liu R , Mu Y 
Published: September 2023

Abstract

BACKGROUND
Tumor-treating Fields (TTFields) monotherapy has been approved for recurrent glioblastoma. However, TTFields combined with second-line chemotherapy has not been well studied in China. This study aims to explore the efficacy and safety of such combination therapy for recurrent GBM.

MATERIAL AND METHODS
This study is a prospective, single-arm, open-label clinical trial (NCT04689087) planning to enroll 40 recurrent supratentorial GBM and use TTFields combined with physician choose second-line chemotherapy. Kaplan-Meier survival curve was used to estimate PFS, OS and survival rate. Safety of the combined treatment was assessed by AE incidence.

RESULTS
Thirty-four recurrent supratentorial GBM patients was enrolled from April 2019 to February 2023. The average age was 51.9 and median KPS score was 80. Seventy-seven percent (26/34) of them underwent total resection surgery and 2.9% (1/34) only experienced biopsy. Eighty-eight percent (30/34) of patients started TTFields when they were first diagnosed as recurrence, while 12% (4/34) patients started TTFields at their second time recurrence or latter, and average compliance of TTFields was 85.5%. As for molecular biomarkers, 47.1% (16/34) patients were MGMT methylated and 38.2% (13/34) were TERT mutant. Since the study initiated in 2019, one IDH-mutant patients were also enrolled. Second-line chemotherapy was combined with antiangiogenic therapy in 47.1% (16/34) patients. The median follow-up period was 8.33 months. Median PFS of these 34 recurrent GBM patients was 8.33(95% CI 4.72-11.95) months, but median OS was not reached. Six months PFS rate was 56.8% (EF-11 historical data of physicians choose chemotherapy was 15.1%) and 6 months OS rate was 74.8%. Two thirds of patients experienced grade 1 or 2 skin adverse events which can be relieved by topical corticosteroids.

CONCLUSION
TTFields combined with second-line chemotherapy showed favorable efficacy and safety in Chinese recurrent GBM patients.
P17.08.A CLINICAL AND MOLECULAR CHARACTERIZATION OF EXTRACRANIAL METASTASES IN GLIOBLASTOMAS
Authors: Jacobsen J , O'Rourke C , Locallo A , Carlsen J , Ewald J , Scheie D , Grunnet K , Schmidt A , Melchior L , Weischenfeldt J , Larsen V , Andersen J , Poulsen H , Broholm H , Michaelsen S , Kristensen B 
Published: September 2023

Abstract

BACKGROUND
Glioblastoma (GBM) is the most common and malignant primary brain tumor in adults, but in contrast to many other malignancies they rarely metastasize. Metastasizing GBMs cause both diagnostic and therapeutic challenges and are generally poorly investigated. Therefore, our aim was to characterize these tumors clinically and molecularly.

MATERIAL AND METHODS
We collected and examined the largest cohort to date of tissue from 16 glioma patients (14 GBMs and 2 lower-grade gliomas) with extracranial metastases, including metastases to scalp (7) lymph nodes (5), bone (2), liver (1), and upper neck (1). After histopathological re-evaluation of the tumors, we assessed the associated magnetic resonance imaging (MRI) scans. Paired samples from the primary tumors, recurrences and metastases were investigated by next-generation sequencing (NGS) analysis with the TSO500 panel, genome-wide 850 K methylation profiling and immunohistochemistry followed by artificial intelligence-based quantification of markers of stemness and immune cells in the tumor microenvironment (TME).

RESULTS
Clinically, the patients were comparable to other GBM patients (gender, age, treatment, and survival). 12/16 patients developed one or more intracranial recurrence(s). MRI scans revealed proximity of the brain tumors to dura, large vessels, and ventricles in a high proportion of the patients. Moreover, we found that (6/7) scalp lesions were in fact extracranial extensions of the brain tumors. NGS data showed that the metastases were clonally derived from the primary tumors and not from the brain recurrences. Methylation- and copy number analysis overall confirmed the initial diagnoses and revealed a patient-specific signature across paired samples in a majority of the patients. Additionally, we observed methylation subclass switch during tumor progression and identified differentially methylated regions enriched in the olfactory transduction pathway when comparing metastases to primary tumors. Levels of tumor stemness were generally preserved according to methylation-based stemness index and OLIG2 and SOX2 protein expression. Similarly, the composition of immune cells in the TME did not change significantly, as shown by cell-type deconvolution and immune cell quantification.

CONCLUSION
Extracranial metastases occurred as early events and overall preserved the tumor- and TME characteristics of the primary brain tumors. Factor such as brain tumor location, neurosurgery and epigenetic regulation of genes associated with olfactory transduction could be involved in glioblastoma metastasis.
P19.02.A FUNCTIONAL CONSEQUENCES OF IDH1 AND CIC MUTATIONS ON OLIGODENDROGLIOMA CELLS OF ORIGIN
Authors: Pottier N , Joppé S , Magne N , Paris S , Delannoy L , Bardella C , Huillard E 
Published: September 2023

Abstract

BACKGROUND
Oligodendrogliomas are primitive tumors of the central nervous system characterized by mutations in isocitrate dehydrogenase 1 (IDH1R132H) gene, codeletion of 1p and 19q chromosomic arms and mutations in Capicua (CIC) gene. Oligodendrocyte precursor cells (OPCs) are potential cells of origin for oligodendrogliomas and OPC-like tumor cells are responsible for tumor amplification at early stages of gliomagenesis. Although genetic alterations are well characterized for these tumors, little is known about the roles of IDH1 and CIC in oligodendroglioma initiation and development. Individually, IDH1 and CIC mutations can induce neoplastic characteristics but are not sufficient for tumoral development. We aim to understand how IDH1 and CIC mutations impact OPC development and whether these alterations are sufficient for tumoral initiation.

METHODS
We have generated an inducible mouse model allowing endogenous expression of IDH1R132H and inactivation of CIC in postnatal OPCs. We analyzed by immunofluorescence the proliferation and differentiation status of mutated oligodendroglial cells and other brain cells, at postnatal and adult stages.

RESULTS
We describe distinct effects of these mutations on oligodendroglial cell number and proliferation, at early and late time points. In addition, we found that IDH1R132H increases the proliferation of other brain cell types, suggesting paracrine effects of this mutation in the brain. We find no evidence of tumor in the brain of mice mutated for both IDH1 and CIC at late time points.

CONCLUSION
Our study describes for the first time the phenotypic impact of the combined expression of IDH1 and CIC mutations on oligodendroglial lineage cells and other brain cells, leading to a better understanding of oligodendroglioma development.
P20.14.B SYSTEMIC THERAPY FOR RECURRENT ADULT INTRACRANIAL AND SPINAL EPENDYMOMAS: A MONO-INSTITUTIONAL EXPERIENCE
Authors: Maccari M , Padovan M , Caccese M , Cerretti G , Lombardi G 
Published: September 2023

Abstract

BACKGROUND
Ependymoma is a rare disease in adult patients (pts) and there is no standard systemic treatment in recurrent disease after surgery and radiotherapy. We reviewed our cases of confirmed intracranial and spinal ependymomas and described experience of pts treated with systemic therapies at disease recurrence.

MATERIAL AND METHODS
We retrospectively collected data of pts with histopathologically confirmed intracranial and spinal ependymomas from Veneto Institute of Oncology IOV in Padua, Italy from April 2018 to April 2023 and identified a subgroup of pts that received at least one line of systemic therapy at disease recurrence. All ependymomas were classified according to WHO 2016. As local protocol, brain and spinal MRI was performed every 2-3 months or when clinically indicated. RANO criteria were used to neuroradiological response. Primary endpoints were disease control rate and progression-free survival.

RESULTS
A total of 36 adult pts with ependymoma were identified, 18 males, median age at diagnosis 43. Tumor locations were spine (n=6), infratentorial (n=6), supratentorial (n=24). The majority were grade 3 (n=15), the others grade 2 (n=11) and grade 1 ependymoma (n=10).9 selected pts received at least one line of systemic treatments at disease recurrence (6 female, 3 male, median age at diagnosis 42 years). The majority were grade 3 (n=7), the others grade 2 (n=2). All 9 pts had undergone surgery and adjuvant radiotherapy. In this subgroup, the median time to recurrence from diagnosis was 12.4 months (range 3-32). At disease recurrence surgery was re-performed in 3 pts. Median number of lines of systemic therapies was 2, with a range from 1 to 6. TMZ alone in 4 pts with a DCR 40% and mPFS 4ms; TMZ+ cisplatin in 2 pts (DCR 50%, mPFS 4ms); TMZ+lapatinib in 3 pts (DCR 33%, mPFS 3.5ms); TMZ+bevacizumab in 1 pt (DCR 0%, mPFS 2ms); bevacizumab alone in 2 pts (DCR 0%, mPFS 2ms); bevacizumab+fotemustine in 1 pts (DCR 100%, mPFS 14ms), fotemustine alone in 2 pts (DCR 50%, mPFS 7.5ms); carboplatin 1 pts (DCR 0%, mPFS 2ms). At the data cut-off (April 2023), median overall survival from the date of diagnosis was 18.5 months (range 2-50).

CONCLUSION
The management of recurrent ependymoma in adults remains a therapeutic challenge. Our experience reflects heterogeneity regarding systemic treatments for patients with more aggressive ependymomas. Even if it was a small population, TMZ plus cisplatin ,fotemustine alone or in association with bevacizumab might represent promising treatments. However, other larger and prospective studies are needed.
Insights of Clinical Significance From 109 695 Solid Tumor Tissue-Based Comprehensive Genomic Profiles
Authors: Heilmann Andreas M , Riess Jonathan W , McLaughlin-Drubin Margaret , Huang Richard S P , Hjulstrom Meghann , Creeden James , Alexander Brian M , Erlich Rachel L 
Published: September 2023

Abstract

Background
FoundationOneCDx is approved in the US and Japan as a companion diagnostic test to identify patients with cancer who may benefit from treatment with 30 drug therapies in the US and 23 in Japan. Tumor profiling with FoundationOneCDx also detects genomic findings with evidence of clinical significance that may inform clinical care decisions beyond companion diagnostic claims. This observational study reports the breadth and impact of clinical decision insights from FoundationOneCDx solid tumor profiles.

Materials and Methods
Consecutive test result reports for patients with solid tumor diagnoses (n = 109 695) were retrospectively analyzed for clinically significant predictive, prognostic, and diagnostic genomic alterations and signatures, determined in accordance with professional guidelines. Interventional clinical trials with targeted therapies or immune checkpoint inhibitors were matched to tumor profiles based on evidence that the genomic finding may be an actionable, investigational, or hypothetical target in the patient’s tumor type.

Results
In 14 predefined cancer types (80.7% of analyzed solid tumors), predictive, prognostic, and diagnostic markers were reported in 47.6%, 13.2%, and 4.5% of samples, respectively, accounting for a total of 51.2% of tumor profiles. Pan-cancer predictive markers of tumor mutational burden (TMB) of 10 or more mutations per megabase, high microsatellite instability (MSI), or NTRK1/2/3 fusions were observed in 15.6%, 2.0%, and 0.1% of solid tumors, respectively. Most solid tumor profiles (89.2%) had genomic results that could theoretically inform decisions on the selection of immunotherapy and targeted therapy clinical trials.

Conclusion
For this real-world population of patients with FoundationOneCDx solid tumor profiles in the routine course of clinical care, clinically significant findings were reported for approximately half of patients with genomic results.