OUP accepted manuscript

BackgroundGliomas are often in close proximity to functional regions of the brain; therefore, electrocortical stimulation (ECS) mapping is a common technique utilized during glioma resection to identify functional areas. Stimulation-induced seizure (SIS) remains the most common reason for aborted procedures. Few studies have focused on oncological factors impacting cortical stimulation thresholds.ObjectiveTo examine oncological factors thought to impact stimulation threshold in order to understand whether a linear relationship exists between stimulation current and number of functional cortical sites identified.MethodsWe retrospectively reviewed single-institution prospectively collected brain mapping data of patients with dominant hemisphere gliomas. Comparisons of stimulation threshold were made using t-tests and ANOVAs. Associations between oncologic factors and stimulation threshold were made using multivariate regressions. The association between stimulation current and number of positive sites was made using a Poisson model.ResultsOf the 586 patients included in the study, SIS occurred in 3.92% and the rate of SIS events differed by cortical location (frontal 8.5%, insular 1.6%, parietal 1.3%, and temporal 2.8%; P = .009). Stimulation current was lower when mapping frontal cortex (P = .002). Stimulation current was not associated with tumor plus peritumor edema volume, world health organization) (WHO grade, histology, or isocitrate dehydrogenase (IDH) mutation status but was associated with tumor volume within the frontal lobe (P = .018). Stimulation current was not associated with number of positive sites identified during ECS mapping (P = .118).ConclusionSISs are rare but serious events during ECS mapping. SISs are most common when mapping the frontal lobe. Greater stimulation current is not associated with the identification of more cortical functional sites during glioma surgery

EPID-08. PRE-SURGERY IMMUNE PROFILES OF ADULT GLIOMA PATIENTS

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

The Relationship Between Stimulation Current and Functional Site Localization During Brain Mapping

BackgroundGliomas are often in close proximity to functional regions of the brain; therefore, electrocortical stimulation (ECS) mapping is a common technique utilized during glioma resection to identify functional areas. Stimulation-induced seizure (SIS) remains the most common reason for aborted procedures. Few studies have focused on oncological factors impacting cortical stimulation thresholds.ObjectiveTo examine oncological factors thought to impact stimulation threshold in order to understand whether a linear relationship exists between stimulation current and number of functional cortical sites identified.MethodsWe retrospectively reviewed single-institution prospectively collected brain mapping data of patients with dominant hemisphere gliomas. Comparisons of stimulation threshold were made using t-tests and ANOVAs. Associations between oncologic factors and stimulation threshold were made using multivariate regressions. The association between stimulation current and number of positive sites was made using a Poisson model.ResultsOf the 586 patients included in the study, SIS occurred in 3.92% and the rate of SIS events differed by cortical location (frontal 8.5%, insular 1.6%, parietal 1.3%, and temporal 2.8%; P = .009). Stimulation current was lower when mapping frontal cortex (P = .002). Stimulation current was not associated with tumor plus peritumor edema volume, world health organization) (WHO grade, histology, or isocitrate dehydrogenase (IDH) mutation status but was associated with tumor volume within the frontal lobe (P = .018). Stimulation current was not associated with number of positive sites identified during ECS mapping (P = .118).ConclusionSISs are rare but serious events during ECS mapping. SISs are most common when mapping the frontal lobe. Greater stimulation current is not associated with the identification of more cortical functional sites during glioma surgery

Comparative analysis of the DNA methylation landscape in CD4, CD8, and B memory lineages.

BackgroundThere is considerable evidence that epigenetic mechanisms and DNA methylation are critical drivers of immune cell lineage differentiation and activation. However, there has been limited coordinated investigation of common epigenetic pathways among cell lineages. Further, it remains unclear if long-lived memory cell subtypes differentiate distinctly by cell lineages.ResultsWe used the Illumina EPIC array to investigate the consistency of DNA methylation in B cell, CD4 T, and CD8 T naïve and memory cells states. In the process of naïve to memory activation across the three lineages, we identify considerable shared epigenetic regulation at the DNA level for immune memory generation. Further, in central to effector memory differentiation, our analyses revealed specific CpG dinucleotides and genes in CD4 T and CD8 T cells with DNA methylation changes. Finally, we identified unique DNA methylation patterns in terminally differentiated effector memory (TEMRA) CD8 T cells compared to other CD8 T memory cell subtypes.ConclusionsOur data suggest that epigenetic alterations are widespread and essential in generating human lymphocyte memory. Unique profiles are involved in methylation changes that accompany memory genesis in the three subtypes of lymphocytes

EPCO-25. AN IMMUNOMETHYLOMIC PLATFORM INTEGRATING SYSTEMIC IMMUNE PROFILES AND EPIGENETIC AGE IN NEURO-ONCOLOGY

Abstract Lineage-specific DNA methylation marks differentiate leukocyte cell types while individual biological aging mechanisms impact other methylation alterations. Human glioma incidence and survival times have been shown to be associated with aberrant immune profiles and have a strong dependency on age. Here we developed a single epigenetic analysis framework to evaluate both immune cell fractions and epigenetic age in peripheral blood. We examined these measures in archived blood from 197 triple-negative glioma patients (TNG; IDH wildtype, 1p19q intact and TERT wildtype) and 312 frequency-matched controls from the SF Bay Area Adult Glioma Study (AGS). Significant differences were observed with TNG cases having lower CD4 and CD8 T cell, natural killer, and B cell fractions, and higher neutrophil fractions than controls. TNG cases were significantly older than controls in two of three epigenetic age estimates; however, there was no difference in epigenetic age acceleration once immune cell proportions were considered. For the TNG cases, we augmented results from several machine learning methods to delineate risk groups of TNG patients with significantly different overall survival. We compared survival models built by recursive partitioning, random forest, and elastic net methods. The final model was chosen by repeated bootstrap sampling via the Brier score loss function and validated in an independent set of 72 IDH-mutant only or TERT-mutant only glioma patients also from the AGS. The final model indicated important interactions between immune cell fractions (including CD4 and CD8 T cells and neutrophils) and treatment, age, and dexamethasone status when adjusted for the main effects of epigenetic age, glioblastoma status, and the neutrophil-to-lymphocyte ratio. The capacity of immunomethylomics to capture diverse, clinically relevant information and the simplicity of its implementation make this a powerful tool for personalized patient evaluation in the neuro-oncology clinic

BIOM-43. CROSS-PLATFORM ROBUSTNESS IN THE GLUCOCORTICOID RESPONSE PHARMACODYNAMIC BIOMARKER

Abstract The neutrophil dexamethasone methylation index (NDMI) is an algorithm-based biomarker to assess individuals’ exposures to dexamethasone, a synthetic glucocorticoid commonly administered for inflammation. Cortisol is the main endogenous glucocorticoid that controls vital processes including the immune response and lipid and carbohydrate metabolism. Variations in the NDMI score reflect individuals’ sensitivities of exposures to both exogenous and endogenous glucocorticoids, and this biomarker was trained using elastic net regression on Illumina’s most recent DNA methylation beadarray, the EPIC array, which contains 850,000 cytosine-guanine (CpG) sites. While technology for microarray research continues to advance over time, researchers are capable of conducting more comprehensive epigenome-wide association studies (EWAS). However, many studies are still run and archived using Illumina’s historical 450K platform with approximately 450,000 CpGs, and there are fewer published databases using the 850K EPIC array. To evaluate the cross-platform bioinformatic comparability, we performed elastic net regression modeling using predictors available in the 450K to train the NDMI. Among the 135 pre-surgery glioma cases from the UCSF Immune Profiles Study (IPS), NDMI scores between the 450K and 850K model were strongly correlated (r = 0.99, p < 0.0001). In the 311 controls from the UCSF Adult Glioma Study (AGS), similar correlations were observed (r = 0.96, p < 0.0001). We observe that NDMI remains a robust tool using historical 450K data and conclude that this algorithmic tool is capable of detecting the variations in individuals’ responses to dexamethasone

IMMU-07. IMMUNE PROFILES IN THE SAN FRANCISCO ADULT GLIOMA STUDY (AGS) USING IMMUNOMETHYLOMICS

Abstract Glioma patients demonstrate abnormalities in peripheral blood leukocytes that have been associated with survival time. Here we assessed immune cell profiles in archival blood samples obtained 5–25 years ago using a novel epigenetic approach called immunomethylomics. We first validated the approach to measure the proportions of CD4 T cells, CD8 T cells, B cells, NK cells, neutrophils, and monocytes in archival blood using the new 850,000 feature EPIC Illumina methylation bead array. The immunomethylomic assay was shown to match the performance of multiparametric flow cytometry and thus is a highly accurate method for immune profiling. We next measured cell profiles in blood from 312 molecularly defined AGS subjects. In this cohort we enriched for patients with triple negative tumor subtypes (IDH wildtype, 1p19q negative, TERT non-mutant). Elevations in the neutrophil lymphocyte ratio (NLR) significantly increased with grade, whereas the proportions of T cells decreased with increasing grade. Using an established cut point of > 4.0 for the NLR revealed that this immune parameter was associated with shorter survival times in glioblastoma (median overall survival (mOS) 12.6 vs. 16.9 months) and non-glioblastoma (mOS 16.7 vs. 36 months) patients. Ongoing analyses of the cohort will be presented to evaluate the effects of age, gender, surgery, chemoradiation and tumor grade on the survival results. Because DNA based immune cell profiles do not require intact cells nor preserved proteins, they provide a powerful tool to glean potentially important immunologic information from historic stored samples that could not otherwise be utilized using current cytometry-based approaches

BIOM-13. DNA METHYLATION MARKS GLUCOCORTICOID PATHWAY RESPONSE IN DEXAMETHASONE-TREATED BRAIN TUMOR PATIENTS

Abstract Dexamethasone (DEX) is routinely prescribed in brain tumor patients to limit vasogenic edema but may also exacerbate immunosuppression and adversely affect survival. The wide spectrum of dosing and individual variation in glucocorticoid (GC) response makes it difficult to assess the impact of DEX exposures. A potential marker of steroid pathway activation and GC load affecting the immune system are induced changes in chromatin structure marked by DNA methylation. We identified DEX-responsive DNA methylation sites in blood leukocytes from glioma patients treated with the drug at various doses and times during the course of their disease. Using weighted co-methylation network analysis, we show that DEX-induced hypomethylation includes well-known regulators of GC receptor (GR) sensitivity (e.g., FK506 binding protein 51: FKBP5) and inflammation (e.g., myeloperoxidase: MPO) and is enriched at genomic locations containing glucocorticoid receptor (GR) binding sites. Elastic net regression modeling was used to train a multilocus GC methylation index (GCMI) that discriminates current DEX users and non-users. GCMI scores showed wide interindividual variation among cases and DEX naïve control subjects. Using independent samples of DEX naïve and exposed glioma patients we show that the GCMI is a sensitive and specific indicator of DEX exposure. GCMI measured in non-glioma controls indicated sensitivity to non-DEX steroid treatments (e.g. prednisolone, fluticasone). Subjects with elevated neutrophil and decreased lymphocyte counts demonstrated high GCMI scores, reflecting the clinically relevant in vivo impact of this marker. Among 195 IDH wildtype and hTERT non-mutant glioma subjects, the GCMI was associated with a HR of 1.11 (95% CI 1.06–1.17) p< 0.0001 in Cox survival models that included age and tumor grade. We conclude that epigenetic remodeling in the peripheral immune compartment in response to DEX exposures is a rich source of potentially powerful markers of individual response to GC pathway activation and associated alterations in the immune response

Evaluation of cross-platform compatibility of a DNA methylation-based glucocorticoid response biomarker

Identifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450). The NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays. We developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care