Citations

Abstract Effective immune synapses are a prerequisite for desirable immune surveillance and control of tumour growth. Cell-to-cell interactions form the basis of immune synapses, resulting in either immunoprotected or immunosuppressed manifestations in the tumour brain that could explain glioblastoma (GBM) recurrence. Using state-of-the-art multiplex imaging, spatial statistics, and spatially aware deep learning tools in 14 patient-matching tissues from primary and recurrent GBM, we detected spatial immune networks (SINets). SINets across 105 regions of interest comprising 2.3 million cells show stronger spatial engagement between myeloid and lymphoid lineages at recurrence. SINets’ architecture in primary tumours is associated with relapse timing. Patients, where the SINets are more modular, recur sooner than patients with denser SiNets. In addition, this association presents sexual dimorphism in our cohort (N=3 females, and N=4 males). Phenotype-to-phenotype spatial coexistence also contributes to enhancing phenotype prediction. A spatial-aware deep learning model trained with single-cell data from primary tumours reaches an average balanced accuracy of 0.76 in primary tumour cellular communities unseen during training, compared to a spatial-agnostic model that reached an average balanced accuracy of 0.69. In summary, we detected a distinct spatial engagement in glioblastoma undergoing chemo-radiation treatment. The spatial patterns of coexistence represent ecological niches that contribute to defining cell occurrence and may underpin effective immune synapses. Overall, the spatiotemporal elements provide a newer approach for dissecting glioblastoma’s complexity and discovering opportunities for stratifying patients by harnessing spatial information encoded in multicellular niches.

Abstract BACKGROUND As an adjunct to direct electrical stimulation (DES), intraoperative electrocorticography (ECoG) can aid detection of language-eloquent cortex. However, it is unclear how surgical impact upon mapping findings relates to cognitive-linguistic outcomes. METHODS Ten patients underwent awake craniotomy for tumor resection with ECoG and DES language mapping. Mapping utilized iPad stimulus presentation coupled to an electrode array capable of both recording ECoG activity and delivering DES. Time-frequency gamma band activations were visualized (Early, Long, Late, Double Peak) for 3 naming paradigms (Object, Action, Auditory). DES was also conducted for each task. Mapping results were overlayed on postoperative MRI to examine proximity to parenchymal trauma (cavity, sulcal displacement). Patients completed cognitive-linguistic testing [WAB-R (N=3) or Neuropsychological Assessment (N=7)] prior to surgery and <2 months postoperatively. Patients with persisting aphasia at 6-month follow-up were also identified. RESULTS Postoperative language decline was found in 50% of patients, with 30% showing worsening (>1SD) in Naming and Phonemic Fluency, and 60% in Semantic Fluency. Surgery impacted ECoG features in 60% of patients and DES arrest sites in 30%. A trend was observed where Early and Late Object naming ECoG features were associated with Semantic Fluency decline [rpb(5)=-.69, p=.067]. Arrest during Auditory naming DES <1 cm of surgical effect was associated with decline in Abstraction [rpb(5)=-.83, p=.042; FET, p=.029] and Semantic Fluency [rpb(5)=-.87, p=.012; FET, p=.024]. Excluding the 3 transsulcal surgeries, arrest during Auditory naming DES <1 cm of resection was associated with general language decline [FET, p=.047]. All 3 patients with persisting aphasia had Auditory naming arrest <1 cm of resection and 2/3 patients had Object naming ECoG features resected. CONCLUSIONS While preliminary, results suggest that surgical proximity to ECoG and DES mapping results may inform risk of surgically-acquired cognitive-linguistic decline. Findings support the potential of multimethod-multitask intraoperative language mapping.

Abstract BACKGROUND Few studies have examined concordance between intraoperative electrocorticography (ECoG) and direct electrical stimulation (DES) language mapping, especially across varied naming tasks. METHODS Twelve patients (Mdn age=59; 75% HGG) underwent awake craniotomy with ECoG and DES language mapping. Mapping utilized iPad stimulus presentation coupled to a 4x8 electrode array for both ECoG and DES. Time-frequency ECoG gamma band activity (Early and Late) was visualized for 3 naming paradigms (Object, Action, Auditory). Bipolar DES was also conducted for each task at each electrode pair. ECoG activations and DES hits were overlayed on preoperative MRI. DES hits represented ground truth for eloquence. ECoG accuracy was examined for each task with 3 different criteria: exact (identical electrodes for ECoG activation and DES hits), adjacent (ECoG <1cm of DES hits), and adjacent within a predefined peritumoral region of interest (<2 cm from boundaries). RESULTS 32 DES hits (40% Auditory, 32% Action, 28% Obj) were observed across patients. Exact ECoG-DES accuracy ranged from 78%-90% [Object: Sens=11%, Spec=91%, PPV=6%, NPV=95%; Action: Sens=40%, Spec=93%, PPV=24%, NPV=97%; Auditory: Sens=69%, Spec=78%, PPV=19%, NPV=78%]. Adjacent ECoG-DES accuracy ranged from 82%-91% [Object: Sens=33%, Spec=92%, PPV=18%, NPV=97%; Action: Sens=44%, Spec=93%, PPV=25%, NPV=97%; Auditory: Sens=91%, Spec=81%, PPV=37%, NPV=99%]. When restricted to the peritumoral region, adjacent ECoG-DES accuracy ranged from 94%-97% [Object: Sens=14%, Spec=99%, PPV=25%, NPV=97%; Action: Sens=25%, Spec=99%, PPV=25%, NPV=99%; Auditory: Sens=100%, Spec=94%, PPV=54%, NPV=100%]. For patients with DES hits (N=10), all had at least 1 task activation <1 cm of DES hits, with 7/10 having convergence of activations across at least 2 tasks. CONCLUSIONS Negative ECoG mapping is strongly predictive of non-eloquence confirmed by DES for all naming tasks. Additionally, gamma band activation elicited by auditory naming within the peritumoral region is strongly predictive of eloquence. Findings support task-based ECoG language mapping for prediction of eloquence and identification of targets for DES confirmation.

Abstract The RBBP4/p300 complex was recently shown to control genes critical for DNA damage repair and may play a role in glioblastoma (GBM) therapy responsiveness, especially to temozolomide (TMZ). However, the role of this complex in the modulation of the GBM tumor microenvironment (GBM-TME) remains elusive. Because pro-tumorigenic GBM-TME is primarily due to angiogenesis and immune tolerance, we evaluated whether the RBBP4/p300 complex may control these critical processes. To that end, we used shRNA to silence each RBBP4/p300 complex member in GBM43 cells and RNAseq to identify angiogenesis and immune genes regulated by this complex. Our data demonstrated that silencing RBBP4 or p300 suppressed the expression of HIF1α and several other hypoxia response genes, including VEGFA and DDIT4, suggesting that RBBP4/p300 complex may regulate angiogenesis. Consistent with a role in regulating angiogenesis, culture medium conditioned by GBM43 cells expressing the control non-targeting shRNA (shNT) significantly induced angiogenic tube formation by human umbilical vein endothelial cells (HUVEC). In contrast, this effect was blocked by the medium conditioned by the shRBBP4 or shp300 expressing cells. Both shRBBP4 and shp300 expressing cells failed to activate HIF1α accumulation and other signaling in response to hypoxia. Additionally, the control shNT-conditioned medium inhibited IFN-γ production while the medium conditioned by the shRBBP4 or shp300 expressing cells supported IFN-ɣ production from CD8+ T cells. Intriguingly, silencing RBBP4 or p300 also suppressed the expression of CCL2 and PD-L1 (CD274). CCL2 protein is a chemokine that promotes TME infiltration by myeloid-derived suppressor cells (MDSCs), while PD-L1 interacts with PD1 to suppress cytotoxic CD8+ T cell activation. Although this is an ongoing investigation, we conclude that RBBP4/p300 complex mediates the expression of hypoxia response genes, including HIF1α, and immunosuppressive genes, including PD-L1, and this activity may enhance angiogenic and immunosuppressed GBM-TME, making this complex a potential target for GBM therapy.

Abstract Many cancers, including glioblastoma (GBM), exhibit a male-biased incidence and outcome disparity. The underlying reasons for this sex bias are unclear but likely involve differences in tumor cell state and immune response. This effect is further influenced by sex hormones, including androgens, which have been shown to inhibit anti-tumor T cell immunity in other solid tumors. Using a series of pre-clinical models, we observed that androgens drive anti-tumor immunity in brain tumors, contrasting with their effect in other tumor types. Upon castration, tumor growth was accelerated in GBM and brain tumor models, while the opposite effect was observed when tumors were located outside the brain. This castration effect could be reversed by testosterone administration. Flow cytometry revealed decreased T cell function, indicated by reduced anti-tumor cytokines (IFNγ and TNFα), and increased T cell exhaustion in both tumors and peripheral tissues in castrated mice, suggesting systemic immunosuppression. Indeed, the survival difference was completely abrogated in T cell deficient mice (RAG1 knockout). Mechanistically, increased hypothalamus-pituitary-adrenal (HPA) axis activity in castrated mice was responsible for the observed systemic immunosuppression, particularly in those with brain tumors. Blocking glucocorticoid receptors reversed the accelerated tumor growth in castrated mice, indicating that elevated glucocorticoid signaling mediated the castration effect. This mechanism was brain-specific rather than GBM-specific, as hyperactivation of the HPA axis was also observed with intracranial implantation of non-GBM tumors. Neuroinflammation caused by brain tumors was stronger in castrated mice, and proinflammatory cytokines like IL-1 and TNF induced HPA axis hyperactivation. Together, these findings highlight that brain tumors drive distinct endocrine-mediated mechanisms in the androgen-deprived setting and highlight the importance of organ-specific effects on anti-tumor immunity.

Abstract Brain tumors constitute significant morbidity and mortality in sub-Saharan Africa (SSA). There is no previous large-scale effort focusing on brain tumor genetics in SSA. This project aims to map out the current neuro-oncology capacity in terms of workforce and available services in SSA. This is an ongoing online survey among a cross section of neuro-oncology practitioners spread across SSA countries to capture information on the distribution, number of available neuro-oncology care practitioners, capacity for neuropathology and molecular diagnosis, management of brain tumors, cancer registration, and tumor biobanking. The survey was disseminated by the Society for Neuro-oncology in SSA (SNOSSA). There were 83 respondents representing 15 countries and 52 health institutions: 46 tertiary, 4 secondary, 1 private and 1 other. Here, we present data on the 52 institutions. The prevalence of specialties was 87% neurosurgery, 75% anatomic pathology, 69% medical oncology, 64% neurology, 60% radiation oncology, and 39% neuropathology. For radiologic evaluation, 81% of institutions were reported to have both CT and MRI, 17% CT only, and one institution neither. For molecular testing, 46% have access to IHC or NGS testing, whereas 52% were reported to have neither. A neuro-oncology tumor board was reported at 58% of institutions. A general cancer registry is available in 64% of institutions, 31% have a brain tumor specific registry and 10% have a brain tumor biorepository. This study shows that SSA has substantial potential in neuro-oncology care practice capacity and facilities. Most significant gaps remain in areas such as neuropathology and molecular testing, which makes widespread implementation of the WHO 2021 diagnosis challenging. Understanding the prevalence of CNS tumor subtypes is also difficult due to low number of brain tumor registries and biobanks in SSA. The present findings reveal strategic opportunities, especially in neuropathology, tumor registries, biobanks, and infrastructure for IHC and NGS in SSA.

Abstract BACKGROUND Despite changes in national policy, women and minority patients remain under-accrued in glioma clinical trials. Supervised machine learning may serve as a novel approach to understanding which variables and their complex interplay most influence enrollment for underrepresented patients. We aimed to design and externally validate machine learning models to predict therapeutic clinical trial enrollment for a) all patients, b) women, and c) NIH-designated minority patients with low- and high-grade glioma. METHODS In a 20-year retrospective cohort of 1042 adult patients with low- and high-grade glioma, boosted neural network (BNN) models for the whole, women, and minority cohorts were used to analyze the combined effects of demographic, socioeconomic, and oncologic variables on clinical trial enrollment. These models were validated using an external cohort (n=103). RESULTS In the development cohort (445 [42.7%] women; 151 [14.5%] minorities; median age, 51.5 [interquartile range: 39.4-62.5] years), 350 patients (33.6%) enrolled in a therapeutic clinical trial. The whole cohort BNN (AUC: 0.827, misclassification rate (MR): 0.175), the women cohort BNN (AUC: 0.895, MR: 0.125), and the minority cohort BNN (AUC: 0.983, MR: 0.053) models accurately predicted trial enrollment on external validation. For the whole cohort and women models, several demographic (race, ethnicity, minority status, sex), socioeconomic (insurance, employment status), and oncologic variables (seizure, chemotherapy, KPS, WHO grade, tumor lobe) were equally influential (Main effect (ME): 1.000, Total effect (TE): 1.000) on enrollment. For the minority model, socioeconomic variables including insurance status (ME: 0.089, TE: 0.417) and occupation classification (ME: 0.087, TE: 0.381) drove enrollment. CONCLUSION We designed and externally validated the first machine learning model for predicting therapeutic clinical trial enrollment for patients with diffuse glioma. Model features driving trial enrollment varied for underrepresented patients. These results may help prioritize personalized patient-specific initiatives to address barriers to equitable patient accrual.

Abstract BACKGROUND Central nervous system (CNS) tumors are frequently characterized by physical disabilities, and treatment is often associated with side effects, as well as financial toxicity and loss of income owing to disease-related neurological deficits. Treatment at centers with specialized neuro-oncology care is associated with an overall survival benefit. However, access to such centers can be limited for many patients. Telehealth services represent an option for improving access to specialized care. During the COVID-19 pandemic public health emergency (PHE), regulatory and reimbursement changes provided patients improved access to neuro-oncology by telehealth. METHODS We retrospectively analyzed our institutional utilization of telehealth visits in the neuro-oncology vs solid tumor oncology practice after the COVID-19 pandemic. RESULTS Between July 2020 and April 2021, telehealth represented 24.1% of all neuro-oncology visits compared to 13.3% for all solid tumor groups. Between May 2021 and April 2023, telehealth visits remained frequent in neuro-oncology compared to solid tumor groups (34.6% vs 15.2%). Utilization rates declined across the practice in the year following expiration of the COVID-19 PHE in May 2023, though remained high for neuro-oncology at 34.1% vs 15.2% for solid tumor groups. Overall, telehealth visit utilization for neuro-oncology has remained more than double that of the oncology practice as a whole. CONCLUSIONS The striking difference between telehealth visit utilization in neuro-oncology compared with general medical oncology indicates that patients with CNS tumors, and those that provide care for these patients, have come to depend on this mode of care delivery. Even after expiration of the COVID-19 PHE, telehealth use remains high in neuro-oncology at our institution. Prospective evaluation to determine the safety of and clinical outcomes associated with telehealth visits for individuals with CNS tumors are critically needed. Such data may promote regulatory and reimbursement reform enabling broader adoption, service sustainability, and improved access to specialized care.

Abstract BACKGROUND Standard of care surgery for high grade glioma (HGG) employs Magnetic Resonance Imaging to identify the contrast enhancing (CE) core for resection, leaving a non-enhancing (NE) invasive rim of tumor which contributes to recurrence. Multi-parametric MRI (mpMRI) has recently been used to map regional biological heterogeneity of neuronal and immune signatures in HGG, and continues to offer a promising strategy for non-invasive surveillance of tumor progression. Here, we present a graph network analysis relating mpMRI to biological signatures in the NE tumor rim and show the utility of communities of imaging features for discriminating tumor phenotypes. METHODS 53 mpMRI features across 101 spatially-localized RNA-sequenced biopsy samples from 64 patients with IDH-wt HGG were represented as nodes within a Neo4j graph network. Modularity optimization was used to identify communities of densely connected nodes. Communities of nodes representing high proportions of NE samples (one-tailed test) were kept for further analysis. Gene set enrichment analysis (GSEA) on samples within selected imaging communities was analyzed for biological process enrichment using clusterProfiler. Single sample GSEA (ssGSEA) using ssGSEA2 was used to annotate neuronal and immune cell states across samples within selected communities. mpMRI feature selection within each community identified the most relevant imaging features for isolating samples classified into neuronal and immune cell states. RESULTS 11 imaging communities gathered a high proportion of NE samples. Three NE communities showed significant enrichment of neuronal signatures, while one showed significant enrichment of immune pathways. One neuronal-predominant community showed unique upregulation of 14 pathways related to neuronal migration/astrocyte projection. CONCLUSION Network imaging communities can identify clusters of NE glioma samples showing contrasting neuronal and immune signatures, including distinct upregulation of migration and projection pathways. Mapping these imaging feature communities to specific biological processes implicated in glioma progression may aid treatment planning and prognostication for glioma patients.

Abstract BACKGROUND Pineocytoma is a rare pineal parenchymal WHO grade 1 tumor, typically well-managed with surgical resection alone. With gross total resection (GTR), 91% 1-year and 84% 5-year survival rates have been reported. Recurrent pineocytoma is rare and optimal management in that setting is unknown, in part owing to the rarity of the condition. METHODS We report an atypical course of pineocytoma in a 58-year-old male involving metastatic disease. RESULTS A pineal mass was identified upon MRI of the brain obtained for vision changes. Patient underwent GTR, pathology was consistent with pineocytoma, WHO grade 1. Ki-67 labeling index was low at 1-2%. Despite low-grade pathology, two years later, surveillance imaging demonstrated recurrence in the pineal region and a second lesion in the right thalamus. The patient underwent gamma knife surgery (GKRS) to both lesions. Three years later, he developed three new lesions in the right cerebellum and again underwent GKRS. Subsequent surveillance imaging identified new lesions in the right cerebellum and along ventricular walls, treated with further GKRS. Nine years after initial diagnosis, focal nodular leptomeningeal metastases were discovered, along with progression at the primary tumor site. Patient was treated with GKRS to the nodular deposits followed by pembrolizumab. Further disease progression as noted despite immunotherapy. Patient was treated with 6 cycles of temozolomide chemotherapy and at further progression 3 cycles of lomustine. Upon additional progression, further radiation therapy was administered with bevacizumab to reduce risk of radiation necrosis. Patient remains on surveillance 13 years after initial diagnosis with visual changes and mild headache representing only clinical issues. CONCLUSIONS Although exceedingly rare, pineocytoma is capable of metastasizing to brain parenchyma and the leptomeninges, as demonstrated in our patient. However, our case demonstrates prolonged survival is possible even in the setting of relentlessly progressive metastatic disease with utilization of multimodality treatment.