bluuebunny/crossref_metadata_2025_split huggingface dataset:
HGG-36. HIF-2: A NEW DRUG TARGET IN PEDIATRIC HIGH-GRADE GLIOMA WITH PROMISING PRECLINICAL RESULTS
Authors: Fuchs Quentin , Pierrevelcin Marina , Papin Christophe , Dontenwill Monique , Entz-Werlé Natacha 
Published: December 2020

Abstract
Pediatric high-grade gliomas (pHGGs) have a very dismal prognosis and need new innovative strategy for treatment. Despite the past discovery of histone H3 driver mutations, we are not able for instance to stop this induced epigenetic remodulation. Therefore, proactive translational studies wish to go further discovering new targetable proteins in pHGG. In our past clinical work, we were able to link significantly HIF-2alpha to a worse pHGG outcome and to their treatment resistance. We designed this new work to determine in several patient-derived cell lines (6 PDCLs) with or without H3.3 mutation the variation of HIF-2alpha, its role, its induction in normoxic and hypoxic microenvironment and its transcriptional targets using RNAseq, metabolomics and ChipSeq analyses. Complementary functional analyses were performed using siRNA strategy during cultures and migration assays. Finally, preclinical drug testing involving commercialized and non-commercialized HIF-2alpha specific inhibitors in the same PDCLs were evaluating their antiproliferative and pro-apoptotic effect. Our results confirmed the central role of HIF-2alpha in cell resistance to treatment, in pHGG stemness features and its direct link with metabolism adaptation and histone interaction. After the confirmation of its frequent presence in multiple PDCLs initiated from thalamic pHGGs and DIPG, we were using inhibitors in a single and combinatorial strategy targeting HIF-2alpha plus another hypoxia biomarker (mTor). This preclinical targeting was highly effective to favor cell arrest, apoptosis and to stop cell migration. In conclusion, HIF-2alpha seem to be a major biomarker in pHGGs that might be targeted giving a useful new opportunity for pHGG treatments.
HGG-41. STRUCTURAL VARIANT DRIVERS IN PEDIATRIC HIGH-GRADE GLIOMA
Authors: Dubois Frank , Shapira Ofer , Greenwald Noah , Zack Travis , Tsai Jessica W , Harutyunyan Ashot S , Kumar Kiran , Sinai Claire , Malkin Hayley , Jones Robert , Ho Patricia , O’Rourke Ryan , Kang Kyung S , Jabado Nada , Kieran Mark W , Ligon Keith , Beroukhim Rameen , Bandopadhayay Pratiti 
Published: December 2020

Abstract

BACKGROUND
Driver single nucleotide variants (SNV) and somatic copy number aberrations (SCNA) of pediatric high-grade glioma (pHGGs), including Diffuse Midline Gliomas (DMGs) are characterized. However, structural variants (SVs) in pHGGs and the mechanisms through which they contribute to glioma formation have not been systematically analyzed genome-wide.

METHODS
Using SvABA for SVs as well as the latest pipelines for SCNAs and SNVs we analyzed whole-genome sequencing from 174 patients. This includes 60 previously unpublished samples, 43 of which are DMGs. Signature analysis allowed us to define pHGG groups with shared SV characteristics. Significantly recurring SV breakpoints and juxtapositions were identified with algorithms we recently developed and the findings were correlated with RNAseq and H3K27ac ChIPseq.

RESULTS
The SV characteristics in pHGG showed three groups defined by either complex, intermediate or simple signature activities. These associated with distinct combinations of known driver oncogenes. Our statistical analysis revealed recurring SVs in the topologically associating domains of MYCN, MYC, EGFR, PDGFRA & MET. These correlated with increased mRNA expression and amplification of H3K27ac peaks. Complex recurring amplifications showed characteristics of extrachromosomal amplicons and were enriched in coding SVs splitting protein regulatory from effector domains. Integrative analysis of all SCNAs, SNVs & SVs revealed patterns of characteristic combinations between potential drivers and signatures. This included two distinct groups of H3K27M DMGs with either complex or simple signatures and different combinations of associated variants.

CONCLUSION
Recurrent SVs associate with signatures shaped by an underlying process, which can lead to distinct mechanisms to activate the same oncogene.
HGG-42. CLINICAL FEATURES AND TREATMENT OUTCOME OF MALIGNANT GLIOMAS IN CHILDREN AND ADOLESCENTS
Authors: Yonezawa Hajime , Uchida Hiroyuki , Higa Nayuta , Oyoshi Tatsuki , Yoshimoto Koji 
Published: December 2020

Abstract

INTRODUCTION
Malignant gliomas in children and adolescents are rare. They are difficult to treat and are associated with an extremely poor prognosis.

SUBJECTS AND METHODS
The treatment and outcomes of WHO grade IV -gliomas and diffuse intrinsic pontine gliomas (DIPG) in children and adolescents (Age 4–39, median 28) treated at our institute since 2001 were retrospectively reviewed. Thirty-five cases were included in this study. Nine cases were located in their brain stem and 2 of them were diagnosed as DIPG clinically without biopsy. Three (brain stem -2, thalamus- 1) cases were diffuse midline glioma H3 K27 M mutant. Remaining 30 cases were diagnosed histologically as glioblastoma. Expect for 2 cases, all were irradiated. Twenty-four cases were treated with temozolomide (TMZ). Bevacizumab (BEV) was administrated as an initial therapy in 10 cases (concomitant with TMZ in 9 cases) and was administrated at the time of relapse in 9 cases. In summary, 19 cases were treated with BEV.

RESULTS
Median survival time (MST) of all cases was 16.8 (4.4 -152.3) months. In total, BEV did not prolonged overall survival (OS), MST 16.02 vs 14.44, (p=0.498). Among adolescents (age 15–39), patients treated with BEV had a trend of longer OS but did not reached statistical significance, MST 19.64 vs 10.76 (p=0.167). An extent of resection and KPS =&gt;70 at discharge from hospital were beneficial factors associated with prolonged OS.

CONCLUSION
As well as in elderly cases, multidisciplinary treatment including resection, radiation and chemotherapy including BEV improves outcomes.
HGG-43. CONGENITAL GLIOBLASTOMA MULTIFORME: A CASE REPORT OF A RARE PEDIATRIC BRAIN TUMOR, MOLECULAR ANALYSIS, AND REVIEW OF THE LITERATURE
Authors: Amend Christina , Stadler James , Salamat Shahriar , Dedekam Erik , Waanders Angela , Wadhwani Nitin 
Published: December 2020

Abstract
Congenital brain tumors are rare, accounting for less than 4% of all pediatric brain tumors. Congenital glioblastoma multiforme (GBM) is rarer still, accounting for 3–15% of congenital brain tumors. There is literature to suggest that these tumors differ from pediatric and adult GBM clinically and molecularly, and as such should be treated as their own distinct entity. Our case is a 4 week old male who initially presented to his pediatrician for enlarging head circumference and upward gaze palsy. An MRI was obtained revealing a right parietal mass. He underwent gross total resection the following day with pathology revealing glioblastoma, WHO grade IV. Further analysis revealed ATRX retained, p53 immunoreactivity in 15–20% of nuclei, IDH1 and IDH2 wildtype, MGMT promoter not methylated, H3K27M wildtype, no 1p and/or 19q deletion/codeletion. Interestingly, RNA analysis of his tumor detected the PPP1CB-ALK fusion transcript as well as amplification of the ALK gene. Co-occurrence of these mutations has been reported in a small number of pediatric glioblastoma patients and PPP1CB-ALK fusions are one of the most common receptor tyrosine kinase fusions in infantile gliomas. ALK rearrangements and amplifications suggest a potential therapeutic target with tyrosine kinase inhibitors in glioblastoma. This patient serves as an example of a rare congenital glioblastoma with unique molecular features that may suggest novel treatment opportunities. We present his clinical course along with a pertinent review of the literature.
HGG-44. DEFECTS OF MISMATCH REPAIR PROTEINS IN PEDIATRIC HIGH GRADE GLIOMAS
Authors: Haberler Christine , Muller Philippe , Müllauer Leonhard , Peyrl Andreas , Czech Thomas , Wimmer Katharina , Slavc Irene 
Published: December 2020

Abstract
Hetero- and homozygous germline mutations of the mismatch repair genes MLH1, PMS2, MSH2 and MSH6 cause Lynch and constitutional mismatch repair (CMMRD) cancer predisposition syndrome, respectively. Affected CMMRD individuals are at risk to develop a variety of neoplasms including CNS tumors, particularly high grade gliomas (HGG), during childhood. Currently, few data exist on the prevalence of CMMRD in children with pediatric HGG. We screened a consecutive series of 79 supratentorial HGGs. Tumor tissue was available in 42 patients, 5 were reclassified as non-HGGs. Immunohistochemistry with antibodies against MLH1, PMS2, MSH2 and MSH6 was performed in 37 tumors. Four patients (3 families) with known CMMRD were included. The evaluation of the slides was performed blinded to the CMMRD status. All four patients with known CMMRD (3 patients with PMS2, one with MSH6 mutation) were identified, showing loss of PMS2 and MSH2/MSH6, respectively. Additionally, we identified 6 patients with loss of MSH2/MSH6 staining in tumor cells, but retained staining in preexisting cells, indicating a pattern like in Lynch syndrome. NGS sequencing of these tumor tissues revealed in 2 patients MSH2 mutations and in one patient a hypermutator phenotype with MSH2 and MSH6 mutations. In 3/6 patients no mutations in the MMR genes were detectable. In summary, we found a low prevalence of CMMRD among HGGs, but identified also 2 patients with probable Lynch syndrome. Immunhistochemistry is an effective tool to screen for patients with MMR defects and should be performed in HGGs to optimize treatment and offer affected families genetic counseling.
IMG-03. RESPONSE ASSESSMENT IN PEDIATRIC LOW-GRADE GLIOMA: RECOMMENDATIONS FROM THE RESPONSE ASSESSMENT IN PEDIATRIC NEURO-ONCOLOGY (RAPNO) WORKING GROUP
Authors: Fangusaro Jason , Witt Olas , Driever Pablo Hernaiz , Bag Asim , de Blank Peter , Kadom Nadja , Kilburn Lindsay , Lober Robert , Robison Nathan , Fisher Michael , Packer Roger , Poussaint Tina Young , Papusha Ludmila , Avula Shivaram , Brandes Alba , Bouffet Eric , Bowers Daniel , Artemov Anton , Chintagumpala Murali , Zurakowski David , van den Bent Martin , Bison Brigitte , Yeom Kristen , Taal Walter , Warren Katherine 
Published: December 2020

Abstract

INTRODUCTION
Pediatric low-grade gliomas (pLGG) show clinical and biological features that are distinct from their adult counterparts. Consequently, additional considerations are needed for response assessment in children compared to the established adult Response Assessment in Neuro-Oncology (RANO) criteria. Standardized response criteria in pediatric clinical trials are lacking, complicating comparisons of responses across studies. We therefore established an international committee of the Radiologic Assessment in Pediatric Neuro-Oncology (RAPNO) working group to develop consensus recommendations for response assessment in pLGG.

METHODS
The committee consisted of 25 international experts in the areas of Pediatric Neuro-Oncology, Neuroradiology and Neurosurgery. The committee first developed a set of agreed upon topics they deemed necessary to understand the controversies of imaging utilization and assessment in pLGG. These topics were divided up among the committee members who presented all available literature to the entire RAPNO committee via web teleconference. Once presented, the group discussed these data and developed consensus statements and recommendations based on available literature, committee expertise and clinical experience. Each topic was discussed until a consensus was reached.

RESULTS
Final consensus included recommendations about the following topics: specific imaging sequences, advanced imaging techniques, NF1-associated pLGG, molecular and histologic classification, assessment of cysts, vision and other functional outcomes as well as overall radiologic response assessment.

CONCLUSIONS
The RAPNO pLGG consensus establishes systemic recommendations that represent an initial effort to uniformly collect and assess response in pLGG. These recommendations should now be evaluated internationally and prospectively in an effort to assess clinical utility, validate and modify as appropriate.
IMG-06. PREDICTING SURVIVAL FROM PERFUSION AND DIFFUSION MRI BY MACHINE LEARNING
Authors: Grist James T , Withey Stephanie , Bennett Christopher , Rose Heather , MacPherson Lesley , Oates Adam , Powell Stephen , Novak Jan , Abernethy Laurence , Pizer Barry , Bailey Simon , Mitra Dipayan , Arvanitis Theodoros N , Auer Dorothee P , Avula Shivaram , Grundy Richard , Peet Andrew C 
Published: December 2020

Abstract

INTRODUCTION
Magnetic Resonance Imaging (MRI) is routinely used in the assessment of children’s brain tumours. Reduced diffusion and increased perfusion on MRI are commonly associated with higher grade but there is a lack of quantitative data linking these parameters to survival. Machine learning is increasingly being used to develop diagnostic tools but its use in survival analysis is rare. In this study we combine quantitative parameters from diffusion and perfusion MRI with machine learning to develop a model of survival for paediatric brain tumours. METHOD: 69 children from 4 centres (Birmingham, Liverpool, Nottingham, Newcastle) underwent MRI with diffusion and perfusion (dynamic susceptibility contrast) at diagnosis. Images were processed to form ADC, cerebral blood volume (CBV) and vessel leakage correction (K2) parameter maps. Parameter mean, standard deviation and heterogeneity measures (skewness and kurtosis) were calculated from tumour and whole brain and used in iterative Bayesian survival analysis. The features selected were used for k-means clustering and differences in survival between clusters assessed by Kaplan-Meier and Cox-regression.

RESULTS
Bayesian analysis revealed the 5 top features determining survival to be tumour volume, ADC kurtosis, CBV mean, K2 mean and whole brain CBV mean. K-means clustering using these features showed two distinct clusters (high- and low-risk) which bore significantly different survival characteristics (Hazard Ratio = 5.6).

DISCUSSION AND CONCLUSION
Diffusion and perfusion MRI can be used to aid the prediction of survival in children’s brain tumours. Tumour perfusion played a particularly important role in predicting survival despite being less routinely measured than diffusion.
IMG-07. GADOLINIUM IS NOT NECESSARY FOR SURVEILLANCE MR IMAGING IN CHILDREN WITH CHIASMATIC-HYPOTHALAMIC LOW GRADE GLIOMA
Authors: Malbari Fatema , Chintagumpala Murali , Su Jack , Okcu Mehmet , Lin Frank , Lindsay Holly , Rednam Surya , Baxter Patricia , Aldave Guillermo , Whitehead William , Dauser Robert , Kralik Stephen 
Published: December 2020

Abstract

BACKGROUND
Patients with chiasmatic-hypothalamic low grade glioma (CHLGG) have frequent MRIs with gadolinium based contrast agents (GBCA) for disease monitoring. Cumulative gadolinium deposition in children is a potential concern. The purpose of this research is to establish whether MRI with GBCA is necessary for determining tumor progression in children with CHLGG.

METHODS
Children with progressive CHLGG were identified from Texas Children’s Cancer Center between 2005–2019. Pre- and post-contrast MRI sequences were separately reviewed by one neuroradiologist who was blinded to the clinical course. Three dimensional measurements and tumor characteristics were collected. Radiographic progression was defined as a 25% increase in size (product of two largest dimensions) compared to baseline or best response after initiation of therapy.

RESULTS
A total of 28 patients with progressive CHLGG including 683 MRIs with GBCA (mean 24 MRIs/patient; range: 10–43 MRIs) were reviewed. No patients had a diagnosis of NF1. Progression was observed 92 times, 91 (98.9%) on noncontrast and 90 (97.8%) on contrast imaging. Sixty-seven radiographic and/or clinical progressions necessitating management changes were identified in all (100%) noncontrast sequences and 66 (98.5%) contrast sequences. Tumor growth &gt;2 mm in any dimension was identified in 184/187(98.4%) on noncontrast and 181/187(96.8%) with contrast imaging. Non primary metastatic disease was seen in seven patients (25%), which were better visualized on contrast imaging in 4 (57%).

CONCLUSION
MRI without GBCA effectively identifies patients with progressive disease. One should consider eliminating contrast in imaging of children with CHLGG with GBCA reserved for monitoring those with metastatic disease.
IMG-10. MRI-BASED RADIOMIC PROGNOSTIC MARKERS OF DIFFUSE MIDLINE GLIOMA
Authors: Tam Lydia , Han Michelle , Wright Jason , Toescu Sebastien , Campion Andrew , Shpanskaya Katie , Mankad Kshitij , Ho Chang , Lober Robert , Cheshier Samuel , Hargrave Darren , Jacques Tom , Aquilina Kristian , Monje Michelle , Grant Gerald , Mattonen Sarah , Vitanza Nick , Yeom Kristen 
Published: December 2020

Abstract

BACKGROUND
Diffuse midline gliomas (DMG) are lethal pediatric brain tumors with dismal prognoses. Presently, MRI is the mainstay of disease diagnosis and surveillance. We aimed to identify prognostic image-based radiomics markers of DMG and compare its performance to clinical variables at presentation.

METHODS
104 treatment-naïve DMG MRIs from five centers were used (median age=6.5yrs; 18 males, median OS=11mos). We isolated tumor volumes of T1-post-contrast (T1gad) and T2-weighted (T2) MRI for PyRadiomics high-dimensional feature extraction. 900 features were extracted on each image, including first order statistics, 2D/3D Shape, Gray Level Co-occurrence Matrix, Gray Level Run Length Matrix, Gray Level Size Zone Matrix, Neighboring Gray tone Difference Matrix, and Gray Level Dependence Matrix, as defined by Imaging Biomarker Standardization Initiative. Overall survival (OS) served as outcome. 10-fold cross-validation of LASSO Cox regression was used to predict OS. We analyzed model performance using clinical variable (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variable. Concordance metric was used to assess the Cox model.

RESULTS
Nine radiomic features were selected from T1gad (2 texture wavelet) and T2 (5 first-order features (1 original, 4 wavelet), 2 texture features (1 wavelet, 1 log-sigma). This model demonstrated significantly higher performance than a clinical model alone (C: 0.68 vs 0.59, p&lt;0.001). Adding clinical features to radiomic features slightly improved prediction, but was not significant (C=0.70, p=0.06).

CONCLUSION
Our pilot study shows a potential role for MRI-based radiomics and machine learning for DMG risk stratification and as image-based biomarkers for clinical therapy trials.
IMG-14. DEVELOPING A PREDICTIVE GRADING MODEL FOR CHILDREN WITH GLIOMAS BASED ON DIFFUSION KURTOSIS IMAGING METRICS: ACCURACY AND CLINICAL CORRELATIONS WITH SURVIVAL
Authors: Voicu Ioan Paul , Napolitano Antonio , Carboni Alessia , Lattavo Lorenzo , Carai Andrea , Vinci Maria , Diomedi-Camassei Francesca , Cacchione Antonella , Del Baldo Giada , Tomà Paolo , Mastronuzzi Angela , Colafati Giovanna Stefania 
Published: December 2020

Abstract

PURPOSE
To develop a predictive grading model based on diffusion kurtosis imaging (DKI) metrics in children affected by gliomas, and to investigate the clinical impact of the model via correlations with overall survival and progression-free survival.

MATERIALS AND METHODS
We retrospectively studied 59 children (33M, 26F, median age 7.2 years) affected by gliomas on a 3T magnet. Patients with tumor locations other than infratentorial midline were included. Conventional and DKI sequences were obtained. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) maps were obtained. Whole tumor volumes (VOIs) were segmented semiautomatically. Mean DKI values were calculated for each metric. The quantitative values from DKI-derived metrics were used to develop a predictive grading model with penalized logistic regression (glmnet package, R). Elasticnet regularization was used to avoid model overfitting. Fitted model coefficients from each metric were used to develop a probability prediction of a high-grade glioma (HGG). Grading accuracy of the resulting probabilities was tested with ROC analysis. Finally, model predictions were correlated to progression-free survival (PFS) with a Kaplan-Meier analysis.

RESULTS
The cohort included 46 patients with low-grade gliomas (LGG) and 13 patients with HGG. The developed model predictions yielded an AUC of 0.946 (95%CI: 0.890–1). Model predictions were significantly correlated with PFS (23.1 months for HGG vs 34.7 months for LGG, p&lt;0.004).

CONCLUSION
In our cohort, a DKI-based predictive model was highly accurate for pediatric glioma grading. DKI-based model predictions were significantly correlated with progression-free survival.
IMG-18. ASSESSMENT OF SUSPECTED DISEASE PROGRESSION USING MULTIPARAMETRIC 18F-CHOLINE PET/MRI IN CHILDHOOD AND TEENAGE-YOUNG ADULT GLIOMAS
Authors: Ferrazzoli Valentina , Shankar Ananth , Cockle Julia , Tang Christine , Al-khayfawee Ahmed , Thomas Benjamin , Barnes Anna , Bomanji Jamshed , Fraioli Francesco , Hyare Harpreet 
Published: December 2020

Abstract

OBJECTIVES
Evaluation of post-treatment glioma burden remains a significant challenge in children, teenagers and young adults (TYA). The aim of this study was to evaluate the utility of ChoPET/MRI for evaluation of suspected disease progression in childhood and TYA gliomas.

METHODS
27 patients (mean age 14 years, range 6–21 years) with suspected glioma disease progression were evaluated with ChoPET/MRI (n=59). Relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and maximum standardised uptake values (SUVmax) in enhancing (enh) and non-enhancing (ne) tumour and normal-appearing white matter (wm) were calculated (rCBVenh, rCBVne, rCBVwm, ADCenh, ADCne, ADCwm, SUVenh, SUVne, SUVwm). 2 blinded radiologists scored tumour probability (1 = unlikely; 5 = definitely). Sensitivity and specificity calculated with gold standard histopathology or clinical follow-up.

RESULTS
Accuracy for the detection of residual/recurrent tumour on conventional MRI was 96.3% (91.7% ≤14 years, 100% ≥15 years) and ChoPET was 73.1% (66.7% ≤14 years, 80.0% ≥15 years). Lack of agreement was observed in 9/27 patients, with ChoPET superior to MRI in 1 case of a posterior fossa tumour. Tumour component analysis demonstrated significantly higher SUVenh and SUVne than SUVwm (SUVenh: p&lt;0.001; SUVne: p=0.004, equivalent to results were observed for ADV and rCBV (ADCenh, ADCne: p&lt;0.001 vs ADCwm; rCBVenh, rCBVne: p&lt;0.001 vs rCBVwm).

CONCLUSIONS
MRI is more sensitive than ChoPET in the evaluation of suspected disease progression in TYA gliomas. However, quanititative ChoPET is able to detect enhancing and non-enhancing tumour and may be helpful in evaluating posterior fossa disease where MRI is equivocal.