bluuebunny/crossref_metadata_2025_split huggingface dataset:
EPCO-09. STEREOTACTIC IMAGE-GUIDED EPIGENOME PROFILING REVEALS DIVERSE EVOLUTIONARY GROWTH ROUTES IN DIFFUSE GLIOMAS
Authors: Barthel Floris , Verburg Niels , Anderson Kevin , Koopman Thomas , Johnson Kevin , Wesseling Pieter , de Witt Hamer Philip , Verhaak Roel 
Published: December 2020

Abstract
Intratumoral heterogeneity is a hallmark of diffuse gliomas and inhibits effective prediction of clinical outcome. To devise a three-dimensional reconstruction of tumor lineage, we used neuronavigation to acquire eight to twelve image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma, which we characterized using DNA methylation arrays. A total of 133 samples were obtained from regions with and without imaging abnormalities. Methylation profiles were analyzed to construct phylogenetic trees and subsequently projected on image-derived tumor maps. Lineage analysis of these evolutionary trees indicated that the sampled gliomas largely evolved stochastically, suggesting that critical tumor drivers were acquired early in time. These results were further validated using 102 multi-region samples from 24 independent patients. Patristic (evolutionary) and cartesian (spatial) distances between pairs of tumor samples from the same patient demonstrated strong correlations, suggesting that this information could be used to determine trajectories of tumor evolution. Evolutionary and spatial distance metrics were combined with histologically obtained and computationally quantified cellularity and proliferation rates to infer vectors representing the direction and magnitude of tumor growth. Using the resulting vector field we determined the minimum and maximum rates of change in order infer the tumor’s evolutionary trajectory. Using this metric we identified three distinct growth patterns: (1) tumors with a trajectory oriented towards the tumor core, (2) outward growing tumors with a linear trajectory pointing outside tumor boundaries, and (3) outward growing tumors with a branching trajectory directed outside tumor boundaries. Association of evolutionary growth patterns with survival demonstrated distinct impacts on outcome, suggesting that growth patterns are an important determinant of tumor aggressiveness. Taken together, although our analyses indicated that the observed glioma heterogeneity is small and largely stochastic, when spatially mapped these changes can be used to track tumor lineage and identify clinically relevant growth patterns.
EPCO-12. SINGLE CELL PROFILING OF LONG NON-CODING RNAS IN GLIOMA
Authors: Mehani Bharati , Chung Hye-Jung , Bandle Russell , Young Sarah , Kelly Michael , Aldape Kenneth 
Published: December 2020

Abstract
Non-coding RNAs have critical functions across biological processes that regulate glioma initiation and progression, and deregulated expression of long non-coding RNAs (lncRNAs) have been implicated in the onset and progression of malignancies. The majority of these transcripts exhibit tissue- and cancer-specific expression but little has been investigated at the single-cell level. We performed single cell RNA Sequencing (10x Genomics) for 9 IDH-wild-type glioblastomas from 7 patients. In total 66,825 cells dissociated from tumor tissues and not sorted were included in this analysis which encompassed 41,989 mean sequencing reads and 2,619 median coding genes per cell. Single cell analysis of lncRNAs in captured 190 median lncRNAs per cell and demonstrated a distinct lncRNA expression profile for glioma cells compared to the non-tumor cells with SOX2-OT significantly upregulated (2X) in glioma cells. Consistent with this finding, SOX2-OT is known to be overexpressed in a variety of cancers and has been previously implicated in glioma proliferation and migration. We then examined patterns of lncRNA expression in GBM expression subtypes. Subtype correlation indicated overexpression of RMST (classical subtype), PCED1B-AS1 (mesenchymal) and LINC00689 (proneural) lncRNAs in these expression subtypes. Consistent with these findings, upregulation of each of these 3 lncRNAs have previously been implicated on pro-tumorigenic effects, including in glioma. Examination of an independent published single cell GBM dataset also validated PCED1B-AS1 in the mesenchymal subtype. Comparison with bulk tumor GBM profiles (IDHwt TCGA GBM dataset) also showed correlations with the expression of RMST, PCED1B-AS1 and LINC00689 lncRNAs in the classical, mesenchymal and proneural subtypes respectively. Overall, these results indicate lncRNA expression can be determined in 10x-generated glioma single cell data and may reveal additional insights about cellular state and glioma biology.
EPCO-17. A SINGLE-CELL ATLAS OF GLIOBLASTOMA EVOLUTION UNDER THERAPY
Authors: Wang Lin , Babikir Husam , Shamardani Karin , Catalan Francisca , Sudhir Sweta , Kohanbash Gary , Aghi Manish , Chang Susan , Philips Joanna , Diaz Aaron 
Published: December 2020

Abstract
Most clinical trials for glioblastoma (GBM) enroll patients at recurrence. However, most pre-clinical animal models are of primary disease. Most studies have used tissues from primary tumors. Knowledge of GBM cellular composition at recurrence is limited. We profiled 80 human IDH-wild-type GBM specimens via single-nucleus RNA sequencing, 40 primary tumors and 40 patient-matched recurrent tumors. Select cohorts were also profiled via single-cell assay for transposase-accessible chromatin, single-cell digital-spatial, and single-cell spatial-transcriptomic assays. All patients were treated only with standard-of-care therapy: temozolomide, radiation and surgical resection. The cohort had a 1.2 male/female ratio, ages 35–76. We found a significant increase at recurrence in cells with the Verhaak mesenchymal phenotype and fewer proneural cells. Although there was an increase in the percentage of cycling cells overall, the fraction of cycling proneural cells decreased while the fraction of cycling mesenchymal cells increased. These changes were concomitant with a significant increase in the percentage of tumor-infiltrating monocytic-lineage cells derived from the periphery. Taken together, these findings support a proneural-to-mesenchymal shift at recurrence due to an increase in the birth rate of mesenchymal cells, supported by an expansion of myeloid-derived cells from peripheral blood. Although the percentages of glioblastoma-infiltrating T-cells are generally low (~1% on average in our data), we found a statistically significant increase in T-cell abundance at recurrence. We identified a cohort of T-cell outliers that demonstrate 2-to-8-fold increases in T-cells over average levels. We validated that T-cells in these tumors have extravasated beyond the perivascular space and into the cellular tumor via immunohistochemistry and single-cell spatial profiling. We present our ongoing analysis of the paracrine signals, upstream transcription-factor expression, and cis-regulatory grammars utilized in immune-outlier GBMs. We describe how these programs change under therapy. These studies shed light on the effect of standard therapy in shaping GBM composition at recurrence.
EPCO-18. MULTI-MODAL AND MULTI-TISSUE PROFILING OF GBM PATIENTS TREATED WITH CAR T CELL THERAPY TO ELUCIDATE MOLECULAR MECHANISMS OF VARIATION IN TREATMENT RESPONSE
Authors: Yahn Stephanie , Zhang Sophia , Peter Lance , Chung Mei-I , Gutierrez Austin , Starr Renate , Alizadeh Darya , Brown Christine , Banovich Nicholas 
Published: December 2020

Abstract
Recent advances in immunotherapy, particularly chimeric antigen receptor (CAR)-engineered T cell therapy, have shown promise for the treatment of many tumor types including progressive recurrent glioblastoma (GBM). While early phase clinical trials have illuminated the potential for CAR T cell therapy to effectively treat GBM, they have also highlighted the unique challenges regarding the efficacy and safety of immunotherapy for brain tumors, and many patients continue to progress during therapy. We seek to overcome these challenges and ultimately extend the time of survival for patients diagnosed with GBM by investigating the immune- and tumor-mediated mechanisms driving variation in response to CAR T cell therapy. We generated the first multi-omics time-series dataset of CAR T cells, endogenous immune cells, and tumor cells from 59 GBM patients treated with CAR T cell therapy. Using single cell RNA-sequencing and simultaneous quantification of nearly 200 cell surface proteins, we comprehensively profiled the cellular phenotypes and signaling pathways within tumor and circulating immune cells that are associated with treatment response. The combination of mRNA and protein expression allowed us to resolve cell states beyond what either modality was capable of alone. Additionally, we found differentially expressed genes and proteins between tumor biopsies collected before and after CAR T cell therapy as well as differential expression between pre-infusion CAR T cells and those identified within the tumor following infusion. By evaluating the CAR T cell phenotypes prior to and during treatment we sought to address the outstanding question of how intrinsic variability impacts the activity and persistence of CAR T cells and to determine the phenotypes that confer the greatest therapeutic benefit for patients with GBM. Our results have direct implications for precision medicine and future clinical trials investigating the use of CAR T cell therapy for GBM as well as other solid tumors.
EPCO-20. RELATING GLIOBLASTOMA HETEROGENEITY TO HUMAN FETAL GLIAL DEVELOPMENT THROUGH HIGH RESOLUTION SINGLE NUCLEI TRANSCRIPTOMICS
Authors: Mussa Zarmeen , Ramos Susana , Nabel Elisa , Allette Kimaada , Hamid Ammar , Cai Maggie , Zhao Will , Wang Ying-chih , Beaumont Kristin , Sebra Robert , Tsankov Alexander , Tsankova Nadejda 
Published: December 2020

Abstract
Glioblastoma (GBM) is thought to be driven by a therapy-resistant cancer stem cell population that recapitulates developmental phenotypes. Direct comparisons of GBM to glial states during human fetal development are limited due to paucity of data from late prenatal gestation, when gliogenesis is thought to occur. Here, we generated a comprehensive single nuclei RNA sequencing (snRNAseq) dataset of approximately 200,000 nuclei taken from the germinal matrix and the cortical plate of 16 fetal postmortem samples, ranging from 17 to 41 gestational weeks, enabling high spatiotemporal resolution of late neurogenesis and early-to-peak gliogenesis. We performed unbiased clustering to identify broad cell types within each sample and integrated all fetal samples to analyze evolving glial states and relationships across two regions and four developmental stages. Subclustering analysis of developing glia from the germinal matrix and cortical plate resolved developmental cell type signatures that are absent in the adult brain. Trajectory inference and pseudo-time analyses reconstructed relationships within these glial lineages and states, identifying a robust common glial progenitor population (GPC) with distinct signature, preceding both oligodendrocyte progenitor cell (OPC) and astrocyte lineage commitment during late prenatal development. We then performed snRNAseq on approximately 30,000 nuclei taken from the core and infiltrating edge of two surgically resected GBM samples with IDH-mutant and IDH-wildtype status and EGFR amplification. Uniform manifold approximation and projection (UMAP) dimensionality reduction revealed distinct neoplastic and non-neoplastic population clusters within each GBM sample. Projecting our previously defined neural stem cell / progenitor signatures onto each GBM UMAP identified notable predominance of the GPC-like developmental signature throughout both GBM tumors with focal minor contributions from the OPC-, transit amplifying-, and astrocyte-like signatures. The high spatial and temporal resolution of the generated roadmap dissolves GBM intratumoral heterogeneity into distinct developmental molecular states driven by potentially targetable regulatory networks.
EPCO-22. IDENTIFYING NEOANTIGENS FOR A PERSONALIZED MUTATION-DERIVED GENOMIC VACCINE IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA
Authors: Kodysh Julia , Rubinsteyn Alex , Blazquez Ana , Mandeli John , Bhardwaj Nina , Hormigo Adilia 
Published: December 2020

Abstract

BACKGROUND
Glioblastomas (GBM) are known for having a lower mutational burden than many other tumor types. Nevertheless, somatic variants that occur in GBM mutational processes may give rise to neoantigens, which can be targeted in a personalized genomic vaccine to elicit a patient-specific anti-tumor response.

METHODS
Normal and tumor DNA and tumor RNA are extracted from tumor specimens and PBMCs. Exome and RNA sequencing and HLA typing is performed for each patient. Neoantigens are identified using the OpenVax computational pipeline, which calls somatic variants in the DNA and prioritizes corresponding candidate neoantigens for vaccination based on tumor RNA expression and predicted MHC class I binding affinity for each of the patient’s HLA alleles. This work is the base for a phase I trial of personalized neoantigen vaccines in combination with Tumor Treating Fields for GBM (NCT03223103).

RESULTS
For each of the 9 patients enrolled in the trial, an average of 1005 somatic mutations were identified (range 299–2441), of which 118 were coding variants (range 52–198), 20 were coding and expressed in the tumor RNA (range 9–45), and 16 were coding, expressed and resulted in predicted MHC class I ligands (range 7–33). An average of 2.3% of all somatic variants identified in each tumor gave rise to predicted neoantigens. Sufficient numbers of neoantigens were identified in all tumor samples of the patients enrolled in the study. The overall somatic mutation landscape for the tumors revealed 4/9 PIK3R1 deletions, 2/9 IDH1 substitutions, as well as disruptions in PTEN, TP53, and ATRX, among others.

CONCLUSIONS
Identifying sufficient neoantigens for inclusion in the personalized genomic vaccine is computationally feasible despite a typically low GBM mutational burden. Driver and passenger mutations can be identified through the same computational pipeline utilized for other tumor types.
EPCO-23. COMPARATIVE TRANSCRIPTOMICS TO IDENTIFY TARGETED THERAPY CANDIDATES IN HIGH GRADE GLIOMA
Authors: Hundley Kelsey , Vaske Olena , Lyle Geoff , Learned Katrina , Beale Holly , Kephart Ellen , De Loose Annick , Lee Madison , Day J D , Rodriguez Analiz 
Published: December 2020

Abstract
Genomic characterization is often used for the identification of therapeutic targets in tumors. Recently, comparative transcriptomics has begun to be utilized for this purpose. In this pilot, we compare the transcriptome of a patient with recurrent high grade glioma (HGG) to our cohort to identify potential therapies. We reviewed transcriptomic profiles from patients who had resection of HGG at our institution over the past year as well as the UCSC cancer compendium. Briefly, tumor RNA was extracted from embedded tumor tissue sections with tumor cellularity higher than 20%. RNA libraries were sequenced to obtain approximately 65 million reads on an Illumina HiSeq 4000 System utilizing patterned flow cell technology. The RNA profile of a 24 male with Li-Fraumeni syndrome and recurrent HGG with leptomeningeal spread underwent comparative transcriptomics to identify targets. A Bayesian statistical framework for gene expression outlier detection was used. These comparisons allowed for the identification of genes and pathways that are significantly overexpressed. Our internal HGG cohort consisted of 44 adult patients and was evenly distributed among the 4 HGG Verhaak subtypes. Our patient of interest had druggable outlier expression in HDAC1, STAT1 and STAT2 in comparison to our internal cohort indicating vorinostat and ruxolitinib as potential therapies, respectively. We then compared our patient of interest to 12,747 patients in the cancer compendium and STAT2 expression was high but not an outlier. In comparison to 738 glioma samples, STAT1 and STAT2 were outliers but not HDAC1 again indicating ruxolitinib as a potential targeted therapy. The patient did not have outlier expression in notch transcriptional targets or immune checkpoint biomarkers when compared to all cohorts. In conclusion, comparative Transcriptomics can identify therapeutic targets in a patient with recurrent HGG even in small cohorts. In our pilot, we identified ruxolitinib as a potential candidate to treat leptomeningeal recurrence.
EPCO-24. COMPUTATIONAL APPROACH TO IDENTIFYING NEUROINFLAMMATION IN GLIOBLASTOMA MULTIFORME (GBM)
Authors: Sherman Wendy , Martin Katie , Rossell Larissa , Nguyen Kelly , Grady Pamela , Zimmermann Cynthia , Chesla David , Mackeigan Jeffrey 
Published: December 2020

Abstract

INTRODUCTION
Glioblastoma multiforme (GBM) is an aggressive brain cancer with dismal prognosis, despite aggressive surgery, radiation and chemotherapy. Therapies directed to the immune system are an exciting prospect in oncology and require an understanding of the interaction between tumors and immune cells. Our objective was to use computational tools to estimate immune infiltration in GBM and determine whether specific immune cell types are associated with clinical outcomes.

METHODS
RNA sequencing and targeted DNA sequencing (to 981 oncology genes) was performed from 37 surgically-resected GBM tumors. Tumor mutations were identified, and gene-level transcript counts were used to estimate tumor-associated cell types using bioinformatics tools. Clinical variables, including survival from surgery and diagnosis, were collected and tested for associations with molecular data.

RESULTS
We detected leukocyte fractions (i.e., immune infiltration) ranging from 2% to 50% in GBMs, with an average of 10.2%. Specifically, we found a statistically significant association between high Th2 cell estimates and reduced overall survival (from both surgery and diagnosis). Nine patients with high Th2 tumors had a median OS from surgery of 187 days, compared with a median of 454 days for 28 patients with low Th2 tumors (log-rank Matel-Cox test; p = 0.0023, HR = 3.1). We also found an association between NF1 mutant tumors, which were enriched for a KRAS signaling signature, and high immune infiltration (p &lt; 0.05).

CONCLUSION
Our computationally-driven approach predicted significant immune infiltration in GBM and a potential association between poor prognosis and Th2 cells. The specific class of CD4+ helper T-cells is generally associated with poor anti-tumor immunity and a Th2-bias has been reported in gliomas. Our data adds to the collective understanding of the molecular landscape of GBM, as well as the complex immune environment, which will have important implications in tumor treatment and prognosis.
EPCO-27. GLIOMA SINGLE CELL MULTI-OMIC ANALYSES REVEALS REGULATORS OF PLASTICITY AND ADAPTIVE STRESS RESPONSE
Authors: Johnson Kevin , Anderson Kevin , Courtois Elise , Barthel Floris , Varn Frederick , Luo Diane , Yi Eunhee , Kim Hoon , Estecio Marcos , Tang Ming , Navin Nicholas , Maurya Rahul , Ngan Chewyee , Bulsara Ketan , Samuels Michael , Das Sunit , Robson Paul , Verhaak Roel 
Published: December 2020

Abstract
Extensive intra- and intertumoral heterogeneity in glioma contributes to therapeutic resistance and poor patient outcomes. Alterations to DNA methylation (DNAme) modulate epigenetic homeostasis, allowing tumor cells to sample alternative cell states to promote tumorigenesis. However, the epigenetic mechanisms that promote cellular plasticity and regulate cell states are still poorly understood. To characterize the epigenetic mechanisms underlying glioma heterogeneity we profiled 914 single-cell methylomes, 55,284 single-cell transcriptomes, and bulk whole genomes across 11 patient samples spanning initial and recurrent time points and 3 molecular subtypes delineated by IDH mutation status. Local DNAme disorder, defined as epimutation burden, was increased in tumor cells relative to nontumor cells, higher in IDH wild-type than in IDH mutant glioma and was positively associated with copy number alteration (CNA). Epimutation was positively associated with transcriptional variability and enriched at genes involved in cellular differentiation. Epimutation was also increased in the binding sites of transcription factors (TFs) associated with response to extracellular stimuli, suggesting that stochastic DNAme alterations enable cellular plasticity and diverse responses to microenvironmental stressors. Integrative clustering of DNAme and scRNAseq profiles defined stem-like and differentiated-like cell states which exhibited differences in TF activity. Stem-like cells were enriched for differentially methylated binding sites of TFs associated with hypoxia response. scDNAme and scRNAseq-derived copy number profiles were compared with bulk copy number profiles and inferred tumor phylogenies to assess how the timing of CNAs impact epigenetic instability, with results suggesting that early CNA events propagate both genetic and epigenetic heterogeneity. Bulk longitudinal data was used to validate the relationship of epigenetic instability with CNA burden as well as differentially methylated binding sites of cell stress response TFs. Our work suggests that local DNAme disorder promotes cellular plasticity and enables adaptive response to cellular stress such as hypoxia.
EPID-02. STEREOTACTIC RADIOSURGERY AND CHEMOTHERAPY TREATMENT PATTERNS IN BREAST CANCER BRAIN METASTASES
Authors: Wang Jacqueline , Ascha Mustafa , Kruchko Carol , Iorgulescu Bryan , Barnholtz-Sloan Jill S 
Published: December 2020

Abstract
Brain metastases (BM) are typically treated with systemic chemotherapy and stereotactic radiosurgery (SRS). Population-level studies exploring SRS use in different patient populations and its impact on chemotherapy treatment patterns are needed. This study examines data from Surveillance, Epidemiology, and End-Results (SEER) from 2010–2012 and Medicare claims from 2008–2014 to identify the utility of SRS and associated chemotherapy treatment patterns in the breast cancer BM patient population. 25,954 breast cancer patients were identified, of which 6,657 (26%) received SRS. Chi-square and Fisher’s exact tests were used for initial univariate analyses. Univariable logistic regression models were fit for each predictor and multivariable models were selected using LASSO. Compared to patients without SRS, patients who received SRS were older, diagnosed at later disease stages, and less likely to have the Her2-/HR+ subtype. Patients with SRS most commonly received aromatase inhibitors (53.5%), followed by selective estrogen receptor modulators (SERM; 31.7%), taxanes (27.2%), alkylating agents (21.2%), monoclonal antibodies (22.2%), antimetabolite drugs (18.3%), anthracyclines (11.4%), and platinating agents (6.8%). Increased odds of SRS were associated with drug classes including taxanes (aOR: 1.29), monoclonal antibodies (aOR: 1.67), antimetabolites (aOR: 1.77), anthracyclines (aOR: 1.32), and topoisomerase-II inhibitors (aOR: 3.16). Aromatase inhibitors were associated with decreased odds of SRS use (aOR: 0.84). Alkylating agents, platinating agents, and SERM had no such associations. Our findings suggest that use of many chemotherapeutic agents increases with SRS regardless of ability to penetrate the blood-brain-barrier and parallels standard systemic breast cancer treatments. Because large-scale studies on the impact of SRS on breast cancer BM patients are lacking, it is important to identify differences in treatment usage and patterns. Important clinical implications regarding drug usage frequency, adherence to treatment guidelines, and use of different agents across SRS patients may arise by analyzing differences amongst and between populations of patients with and without SRS.