High-grade gliomas (HGGs) are aggressive brain tumors with limited treatment options and poor survival outcomes. Variants including isocitrate dehydrogenase (IDH)-wildtype, IDH-mutant, and histone 3 lysine to methionine substitution (H3K27M)-mutant subtypes demonstrate considerable tumor heterogeneity at the genetic, cellular, and microenvironmental levels. This presents a major barrier to the development of reliable models that recapitulate tumor heterogeneity, allowing for the development of effective therapies. Glioma tumor organoids (GTOs) have emerged as a promising model, offering a balance between biological relevance and practical scalability for precision medicine. In this study, we present a refined methodology for generating three-dimensional, multiregional, patient-derived GTOs across a spectrum of glioma subtypes (including primary and recurrent tumors) while preserving the transcriptomic and phenotypic heterogeneity of their source tumors. We demonstrate the feasibility of a high-throughput drug-screening platform to nominate multi-drug regimens, finding marked variability in drug response, not only between patients and tumor types, but also across regions within the tumor. These findings underscore the critical impact of spatial heterogeneity on therapeutic sensitivity and suggest that multiregional sampling is critical for adequate glioma model development and drug discovery. Finally, regional differential drug responses suggest that multi-agent drug therapy may provide better comprehensive oncologic control and highlight the potential of multiregional GTOs as a clinically actionable tool for personalized treatment strategies in HGG.

Background: Leptomeningeal disease (LMD) is challenging to diagnose and monitor given the poor sensitivity of current gold-standard diagnostics. Cerebrospinal fluid tumor cells (CSF-TCs) have been studied as a biomarker for disease management because oncogene amplification of the primary, metastatic, and CNS metastatic tumors can be heterogeneous. The CNSide platform enumerates CSF-TCs and analyzes oncogene expression via immunocytochemistry (ICC), fluorescent in situ hybridization (FISH), and next-generation sequencing (NGS). We report the utility of this combined enumerative and mutational testing for LMD diagnosis and disease monitoring. Methods: A multicenter, retrospective analysis of commercially ordered assays from two health systems between January 2020 and July 2023 included 613 tests on 218 individual patients with suspected or confirmed LMD. To date, this is the largest cohort of patients in LMD literature evaluated using CSF-TCs. Results: CSF-TCs were detected in 67% (412/613) of samples. The most analyzed cancer types were breast (n = 105) and lung (n = 65). In lung cancer, anaplastic lymphoma kinase (ALK) was detected in 14% (17/118), and c-MET was detected in 61% (78/128). In breast cancer, HER2 was detected in 39% (65/168), and estrogen receptor (ER) was detected in 26% (44/168). Sixty-six patients underwent 2+ longitudinal CSF draws; among these, there were 58 flips in oncogene detection over time, and 30% (20/66) of patients had at least one biomarker change in the CSF. Conclusions: Longitudinal combined ICC/FISH/NGS CSF testing demonstrates a wide range in CSF-TC enumeration, which may be correlated with clinical course, and furthermore identifies actionable tumor markers that frequently fluctuate over time. Utilization of this platform would enable timely, personalized LMD-specific chemotherapy.

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factors remains limited. To test the interactive effects of demographic, socioeconomic, and oncologic variables on trial enrollment, we designed boosted neural networks (BNNs) for all glioma patients ( n = 1042), women ( n = 445, 42.7%), and minorities ( n = 151, 14.5%) and externally validated these models [whole cohort, n = 230; women, n = 89 (38.7%); minority, n = 66 (28.7%)]. For the whole-cohort BNN, the most influential variables on enrollment were oncologic variables, including KPS [total effect (TE), 0.327], chemotherapy (TE, 0.326), tumor location (TE, 0.322), and seizures (TE, 0.239). The women-only BNN exhibited a similar trend. Conversely, for the minority-only BNN, socioeconomic variables [insurance status (TE, 0.213), occupation classification (TE, 0.204), and employment status (TE, 0.150)] were most influential. These results may help prioritize patient-specific initiatives to increase accrual.

Background: As cancer therapies have improved, spinal metastases are increasingly common. Resulting complications have a significant impact on patient's quality of life. Optimal methods of surveillance and avoidance of neurologic deficits are understudied. This study compares the clinical course of patients who initially presented to the emergency department (ED) versus a multidisciplinary spine oncology clinic and who underwent stereotactic body radiation therapy (SBRT) secondary to progression/presentation of metastatic spine disease.Methods: We performed a retrospective analysis of a prospectively maintained database of adult oncologic patients who underwent spinal SBRT at a single hospital from 2010 to 2021. Descriptive statistics and survival analyses were performed.Results: We identified 498 spinal radiographic treatment sites in 390 patients. Of these patients, 118 (30.3%) presented to the ED. Patients presenting to the ED compared to the clinic had significantly more severe spinal compression (52.5% vs. 11.7%; p < 0.0001), severe pain (28.8% vs. 10.3%; p < 0.0001), weakness (24.5% vs. 4.5%; p < 0.0001), and difficulty walking (24.5% vs. 4.5%; p < 0.0001). Patients who presented to the ED compared to the clinic were significantly more likely to have surgical intervention followed by SBRT (55.4% vs. 15.3%; p < 0.0001) compared to SBRT alone. Patients who presented to the ED compared to the clinic had a significantly quicker interval to distant spine progression (5.1 ± 6.5 vs. 9.1 ± 10.2 months; p = 0.004), systemic progression (5.1 ± 7.2 vs. 9.2 ± 10.7 months; p < 0.0001), and worse overall survival (9.3 ± 10.0 vs. 14.3 ± 13.7 months; p = 0.002).Conclusion: The establishment of multidisciplinary spine oncology clinics is an opportunity to potentially allow for earlier, more data‐driven treatment of their spinal metastatic disease.