bluuebunny/crossref_metadata_2025_split huggingface dataset:
EPCO-19. INTEGRATED ANALYSIS OF INTRA-TUMORAL HETEROGENEITY IN GLIOBLASTOMAS THROUGH SINGLE NUCLEI ATAC-SEQ AND RNA-SEQ
Authors: Raviram Ramya , Raman Anugraha , Preissl Sebastian , Ning Jianfang , Wu Shaoping , Deynze Kinsey , Chen Clark , Ren Bing 
Published: December 2020

Abstract
Glioblastoma, the most common form of primary brain cancer in adult, consists of an ecosystem of cancer cells characterized by cell-to-cell variations in genotypes and phenotypes. This intra-tumoral heterogeneity forms the substrate for cancer evolution, which in turn fuels therapeutic failure and resistance. To better define this heterogeneity, we profiled clinical glioblastoma specimens using single nuclei assays for Transposase-Accessible Chromatin with sequencing (snATAC-seq), RNA-Seq (snRNA-Seq), Paired snATAC/snRNA-seq, and whole genome-seq (WGS). We found that snATAC-Seq detected focal amplifications (~40kb-2MB) of genomic regions, revealing magnitudes of intra-tumoral heterogeneity previously unappreciated. snATAC-seq and WGS provided high resolution chromatin-state maps of extrachromosomal DNA (ecDNA), while Paired-seq delineated gene expression patterns associated with these chromatin-states. sn-RNAseq confirmed distinct cell states previously defined by others, including oligodendrocyte progenitor cell (OPC), neural progenitor cell (NPC), astrocyte, and mesenchymal -like glioblastomas. Analysis of snATAC-seq profiles in this context revealed shared dependency of these cell states on the Nuclear Factor 1 complex (NFIA and NFIB). Our results demonstrate the utility of cross-platform integration of single cell genomic technologies and suggest that, despite the overwhelming genotypic and phenotypic heterogeneity, shared vulnerability of predominant glioblastoma cell states can be identified.
EPCO-21. STING PROMOTER EPIGENETIC SILENCING IN GLIOBLASTOMA
Authors: Low Justin , Bowie Michelle , Chandramohan Vidya , Fuller Rebecca , Muscat Andrea , Brown Michael , Hariharan Seethalakshmi , Hostettler Janell , Briley Aaron , Danehower Sarah , Baker Ali , Wong Nick , Ashley David 
Published: December 2020

Abstract
The Stimulator of interferon genes (STING) protein is a critical component of the innate immune response to pathogenic and cytosolic self DNA. The importance of STING signalling has recently been demonstrated in a number of tumor types, including glioblastoma (GBM), and its activation through STING agonism is a promising antitumor therapeutic avenue. Recent studies have shown a loss of STING expression in cancer and an overall dysregulation of the CGAS/STING pathway. A potential mechanism of STING silencing is the methylation of its promoter. Using bulk methylation array data from patient samples, we explore epigenetic control of the TMEM173 gene that encodes STING. We find that the STING promoter is highly methylated in glioblastoma and that STING RNA expression is correspondingly low. Methylation data from normal brain and non-cancer cerebral diseases reveal a consistent pattern of STING promoter hypermethylation in these diverse states. The degree of bulk STING methylation in GBM samples inversely correlates with tumor purity and markers of immune infiltration. Single-cell transcriptome sequencing reveals that STING is expressed specifically in immune cells and endothelial cells, but not glioma cells. Collectively these results suggest that STING signalling is disrupted in GBM, that STING is epigenetically silenced by DNA methylation in the tumor, and that STING expression in bulk GBM tumor samples arises from infiltrating immune cells in the tumor microenvironment. Therapeutic approaches stimulating the innate STING signalling pathway are therefore likely to be effective on infiltrating immune cells rather than tumor cells themselves. This work motivates further study into mechanisms of STING activation in the broader GBM tumor microenvironment.
EPCO-30. A RADIOMICS BASED REGRESSION MODEL TO PREDICT GLIOBLASTOMA CELL MOTILITY
Authors: Mulford Kellen , McMahon Mariah , Odde David , Wilke Christopher 
Published: December 2020

Abstract

PURPOSE
Radiomics has shown considerable success as a diagnostic tool in the classification of tumor grade, stage, and prognosis. The purpose of this work is to examine the potential for radiomics techniques to accurately predict the motility properties of glioblastoma cells.

METHODS
Tissues specimens were obtained from a total of 31 patients undergoing surgical resection of glioblastoma. Mean tumor cell motility was calculated from time-lapse videos using previously described methods (Bangasser et al. Nat Comm 2017). Preoperative, post-contrast T1-weighted MR images with 1 mm voxels were obtained from the medical records for each patient. Manual segmentation was used to define the border of the enhancing tumor and 108 radiomics features were extracted from the normalized image volumes using the PyRadiomics software package. Imaging features that correlated strongly with cellular motility were selected in a stepwise manner by p-value. The four features most strongly correlated with cellular motility were included in a regression model using the adaptive lasso technique with leave-one-out cross validation (LOOCV).

RESULTS
Two first order and two gray-level run length matrix features were selected for the model. The R-squared value for the predictive model was 0.60 with p-values for each individual parameter estimate less than 0.0001. An analysis of the residual values of the predicted model did not show any evidence of bias in the estimate. The average root mean squared error between the predicted and actual motility from the LOOCV for the model was 0.75.

CONCLUSION
The results of this work suggest that it is possible for a quantitative image feature-based model to predict the cellular motility of glioblastomas. Further work will prospectively test the model and explore the role of cellular motility in clinical outcomes such as time to recurrence and patterns of failure.
EPCO-34. CLINICAL AND GENETIC EVOLUTION OF EPENDYMOMA
Authors: Chen Zhong-ping , Wang Jing , Yang Qun-ying , Zeng Jing 
Published: December 2020

Abstract
Ependymomas are glial brain tumors accounting for approximately 2~3% of all primary tumors in central nervous system (CNS), and 12% of all pediatric intracranial tumors. To better understand the evolution process of ependymomas, we studied the clinical, pathological and genetic development of a rare girl case with repeatedly recurrent ependymoma. This girl was diagnosed as anaplastic ependymoma at age of 9 years old, and experienced 7 times tumor relapse and received 9 times surgeries but finally ceased at19 years old with multiregional recurrences. The pathological characteristics, radiographic images and therapeutic strategies of the patient were all retrieved. Molecular markers confirmed the diagnosis based on the updated WHO guideline for CNS tumors. Whole-genome sequencing (WGS) was performed to elucidate the landscape of mutation signatures and to identify potential driver mutations along the tumor progression. The seven tumor specimens showed a highly branched evolutionary pattern. There were six gene mutations found in 5 of the 7 specimens (PCDHA4, PCDHA8, SEC14L6, SETD2, RIOK2, and SLCO2A1) and three in 6 of 7 the samples (RYR1, SNX25, DSC2). Strikingly, there was one gene, ADGRL3, which was found to be consistently mutated in the entire disease progression process. Our findings therefore suggest that ADGRL3 might play roles in the disease progression of ependymoma patient.
EPCO-35. SINGLE-CELL RNA-SEQ OF PEDIATRIC EPENDYMOMA REVEALS PROGNOSTIC IMPACT OF IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION
Authors: Englinger Bernhard , Gojo Johannes , Jiang Li , Hübner Jens M , Shaw McKenzie , Hack Olivia , Liu Ilon , Madlener Sibylle , Kirchhofer Dominik , Pyrdol Jason , Hovestadt Volker , Mazzola Emanuele , Mathewson Nathan , Trissal Maria , Lötsch Daniela , Dorfer Christian , Haberler Christine , Halfmann Angela , Mayr Lisa , Peyrl Andreas , Geyeregger Rene , Schwalm Benjamin , Mauermann Monica , Pajtler Kristian , Milde Till , Shore Marni , Geduldig Jack , Pelton Kristine , Czech Thomas , Ashenberg Orr , Wucherpfennig Kai , Rozenblatt-Rosen Orit , Alexandrescu Sanda , Ligon Keith , Pfister Stefan , Regev Aviv , Slavc Irene , Berger Walter , Suva Mario , Kool Marcel , Filbin Mariella 
Published: December 2020

Abstract
Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/single nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets such as IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.
EPID-01. METASTATIC BRAIN TUMORS IN THE CENTRAL TEXAS MILITARY AND VETERAN POPULATION
Authors: Murillo Jennifer , Benge Jared , Levacic Danijela , Anyanda Elizabeth 
Published: December 2020

Abstract
There are relatively few studies on brain metastases in the military population, despite increased risk factors for the development of some cancers. This data was compared to the results from previously published epidemiological data Surveillance, Epidemiology, and End Results (SEER; Cagney et al, 2017) from the general population. PURPOSE: The purpose of our research was to compare the frequency and etiology of metastatic brain cancer in the military and veteran population in our database relative to the general population. METHODS: Retrospective chart review of diagnoses retrieved from the Electronic Medical Record dated January 1, 2016 to July 1, 2019 capturing visits to the Baylor Scott & White Medical Center with specific ICD 10 brain cancer codes for nonhematologic malignancies originating outside of the CNS. RESULTS: Data from 63 individuals that met criteria for the study was analyzed. The military group was predominantly male (92.1%), white (66.7%) and non-Hispanic (90.5%). In our current sample (N=63) 74.6% had metastatic lung cancer with a histology subset of 24.5% having adenocarcinoma. Compared to the SEER general population our sample was more likely to have metastatic lung cancer with a similar frequency in the histologic subset adenocarcinoma. CONCLUSION: In this exploratory study using retrospective data, trends were found for lung cancer diagnosis with brain metastatic disease, appearing more common in the military sample from a single-center relative to previously published estimates in the general population. Rates were similar for adenocarcinoma. More research into the higher frequency of lung cancer in the military population compared to the general population should be further explored.
EPID-08. PRE-SURGERY IMMUNE PROFILES OF ADULT GLIOMA PATIENTS
Authors: Bracci Paige , Rice Terri , Hansen Helen , Francis Stephen , Lee Sean , McCoy Lucie , Shrestha Pavan , Warrier Gayathri , Clarke Jennifer , Molinaro Annette , Taylor Jennie , Wiencke John , Wrensch Margaret 
Published: December 2020

Abstract
Changes in glioma patients’ immune profiles over the course of disease may predict outcomes. DNA based immunomethylomics quantifies blood immune cells based on cell specific DNA methylation signatures. To assess changes in immune profiles, we are longitudinally collecting blood samples from glioma patients pre-surgery and at other clinically relevant time points. Here we report patients’ pre-surgery immune profiles. All patients underwent biopsy or resection of a presumed new glioma or recurrent lower grade glioma. Blood DNA methylation was assessed with Illumina EPIC methylation arrays. Relative cell fractions of CD4, CD8, B-cells, natural killer cells, monocytes, and neutrophils, were estimated via our validated deconvolution algorithm. Total nucleated cell counts from Nexcelom cytometry were used to compute absolute cell counts. Other measures include total lymphocytes, CD4/CD8 ratio, neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR)). The first 125 participants includes 56 newly diagnosed glioblastomas (GBM), 28 newly diagnosed grade II-III gliomas, and 41 recurrent grade II-III gliomas. Median patient age is 49 years. 53 (43%) had recent dexamethasone exposure. In overall non-parametric analyses, most cell subsets, especially CD4, differed across grade, diagnosis group, WHO classification and dexamethasone exposure. In post-hoc pairwise analyses, immune profiles of IDH wildtype GBM patients who had taken dexamethasone differed from patients with GBM or grade II-III glioma who had not taken dexamethasone; they had clinically relevant and statistically significantly lower absolute CD4 counts, total white cell counts, and percent of total lymphocytes, and higher absolute neutrophil counts, NLR and LMR. However, some dexamethasone naïve GBM patients also had altered immune profiles. Comparisons of relative immune cell fractions with those from 454 non-glioma controls from the UCSF Adult Glioma Study showed that across grade and WHO classification, for the most part, immune profiles of glioma patients not exposed to dexamethasone did not differ from controls.
EPID-11. A MULTI-INSTITUTIONAL COMPARATIVE ANALYSIS OF THE CLINICAL, GENOMIC, AND SURVIVAL CHARACTERISTICS OF PEDIATRIC, YOUNG ADULT AND OLDER ADULT PATIENTS WITH IDH-MUTANT GLIOMA
Authors: Jane Lim-Fat Mary , Vogelzang Jayne , Woodward Eleanor , McGovern Alana , Ma Clement , Al-sayegh Hasan , Alexandrescu Sanda , Margol Ashley , Cotter Jennifer , Cole Kristina , Li Marilyn , Owens Emily , Smith Amy , Goldman Stewart , Kaneva Kristiyana , Burton Emily , Nazemi Kellie , Wright Karen , Wen Patrick , Warren Katherine , Touat Mehdi , Reardon David , Bi Wenya Linda , Ligon Keith , Yeo Kee Kiat 
Published: December 2020

Abstract

BACKGROUND
Prognostic significance of IDH-mutation in glioma is incompletely understood in children and adolescents/young adults (YAs). We compared the clinico-genomic features, outcomes and prognostic factors observed in IDH-mutant gliomas across age groups.

METHODS
Clinical, histologic and molecular data of patients with IDH-mutant gliomas from 8 pediatric institutions (spanning twenty years) and adult patients from two institutions (from 2013–2019) were identified. Patients were grouped as pediatric (&lt; 19y), YA (19y to &lt; 40y) or older adult (≥ 40y). Genomic alterations, including somatic mutations and copy number variants, were captured with institutional next generation sequencing. Factors were compared across age categories using Fisher’s exact test or analysis-of-variance. Cox proportional-hazards regression tested factors for association with overall (OS) and progression-free survival (PFS).

RESULTS
Of 379 patients, 48(13%) were pediatric, 204(54%) YA and 127(33%) older adult. Histological subtype differed significantly by age group (p&lt; 0.0001). YAs had higher rates of malignant transformation (p=0.01) and shorter time-from-diagnosis-to-malignant transformation (p=0.01) compared to other age groups. Analysis of genomic alterations revealed an age-related difference in distribution in ATRX mutations only (p=0.0018). Median PFS and OS for the entire cohort were 4.62 and 17.19 years. In univariate models, PFS differed by age group (p=0.0012), with YAs having the worst outcomes. Lack of MGMT methylation (p=0.024) predicted poorer OS. Upfront observant management was predictive of poorer PFS. Gene mutations were not associated with PFS. In multi-variable models, YAs had shorter PFS compared to pediatric (hazard ratio [HR]=2.03, p=0.01) and older adults (HR=1.59, p=0.003) after adjusting for histology, extent of resection, and initial therapy. Age at diagnosis was not associated with OS in multi-variable analysis.

CONCLUSIONS
Within our cohort, YA with IDH-mutant tumors progressed more quickly compared to their pediatric counterparts. Further study of YA patients with IDH-mutant glioma is critical to better define best practices for this group.
EPID-14. RACIAL DIFFERENCES AND DISPARITIES IN PATIENTS WITH GLIOMAS: A SINGLE COMPREHENSIVE CANCER CENTER EXPERIENCE FROM 2008–2020
Authors: Coffee Elizabeth , Tucker Zachary , Lobbous Mina , Baskin Monica , Markert James , Fiveash John , Miller C Ryan , Nabors Louis 
Published: December 2020

Abstract

BACKGROUND
Disparities in healthcare delivery in the United States based on race and socioeconomic status are well-documented. Our study examined these disparities along with demographic differences in patients with gliomas.

METHODS
Data was collected retrospectively from an NCI Comprehensive Cancer Center between 2008–2020; 163 African-American patients and 1207 non-Hispanic white patients were included. Demographic variables were entered as predictors of tumor grade and type in an ANOVA model and multinomial logistic regression, respectively. A MANOVA model was used to assess differences in treatments received. Predictors of outcome were determined using cox regression.

RESULTS
Significant differences (p&lt; 0.05) were found between African-American and non-Hispanic white patient groups in; age at diagnosis (48.68 vs 56.12 years, respectively), male/female gender ratio (0.75 vs 1.22), annual household income ($29,442 vs $40,028), insurance type (53.1% private and 42% public vs 63.4% private and 33.6% public) and marital status (43% married vs 74.1%). When controlling for these, there were no significant differences in tumor grade, type, MGMT methylation or IDH1 alteration statuses. Race alone did not predict treatment received, however, two-way interactions between race and other variables did. While gender differences in resection were small for non-Hispanic white controls, resection took place more often in African-American females than males (F = 4.779, p = 0.029). The deleterious effect of increased age on overall survival was diminished in African-Americans (B = -0.033, p &lt; 0.001), while the effect of tumor grade was more pronounced (B = 0.595, p &lt; 0.001).

DISCUSSION
This study suggests that disparities in outcomes are identified when race is considered within the context of other demographic, socioeconomic, and clinical factors. Moreover, these observations demonstrate the need for further studies into intersectional effects on treatment access and clinical outcomes, along with aggressive countermeasures to ensure equity of care.
EPID-15. RACIAL AND SOCIOECONOMIC DISPARITIES DIFFERENTIALLY AFFECT OVERALL AND CAUSE-SPECIFIC SURVIVAL IN GLIOBLASTOMA
Authors: Liu Elisa , Yu Sharon , Sulman Erik , Kurz Sylvia 
Published: December 2020

Abstract

BACKGROUND
The prognostic role of racial and socioeconomic factors in patients with glioblastoma is controversially debated. We aimed to evaluate how these factors may affect survival outcomes in an overall and cause-specific manner using large, national cancer registry cohort data in the temozolomide chemoradiation era.

METHODS
The National Cancer Institute’s Surveillance, Epidemiology, and End Results database was queried for patients diagnosed with glioblastoma between 2005 and 2016. Overall survival was assessed using Cox proportional hazard models using disease intrinsic and extrinsic factors. Cause-specific mortality was assessed using cumulative incidence curves and modeled using multivariate cumulative risk regression.

RESULTS
A total of 28,954 patients met the prespecified inclusion criteria and were included in this analysis. The following factors were associated with all-cause mortality: age, calendar year of diagnosis, sex, treatment receipt, tumor size, tumor location, extent of resection, median household income, and race. Asian/Pacific Islanders and Hispanic Whites had lower mortality compared to Non-Hispanic Whites. Cause-specific mortality was associated with both racial and socioeconomic groups. After adjusting for treatment and tumor-related factors, Asian/Pacific and black patients had lower glioblastoma-specific mortality. However, lower median household income and black race were associated with significantly higher non-glioblastoma mortality.

CONCLUSION
Despite the aggressive nature of glioblastoma, racial and socioeconomic factors influence glioblastoma-specific and non-glioblastoma associated mortality. Our study shows that patient race has an impact on glioblastoma-associated mortality independently of tumor and treatment related factors. Importantly, socioeconomic and racial differences largely contribute to non-glioblastoma mortality, including death from other cancers, cardio- and cerebrovascular events.