Targeting fatty acid synthase in preclinical models of TNBC brain metastases synergizes with SN-38 and impairs invasion.

Fatty acid synthesis (FAS) has been shown to play a key role in the survival of brain-metastatic (BM) breast cancer. We demonstrate that the fatty acid synthase inhibitor TVB-2640 synergizes with the topoisomerase inhibitor SN-38 in triple-negative breast cancer (TNBC) BM cell lines, upregulates FAS and downregulates cell cycle progression gene expression, and slows the motility of TNBC BM cell lines. The combination of SN-38 and TVB-2640 warrants further consideration as a potential therapeutic option in TNBC BMs.

Combined cytotoxic and immune-stimulatory gene therapy for primary adult high-grade glioma: a phase 1, first-in-human trial.

BACKGROUND: High-grade gliomas have a poor prognosis and do not respond well to treatment. Effective cancer immune responses depend on functional immune cells, which are typically absent from the brain. This study aimed to evaluate the safety and activity of two adenoviral vectors expressing HSV1-TK (Ad-hCMV-TK) and Flt3L (Ad-hCMV-Flt3L) in patients with high-grade glioma. METHODS: In this dose-finding, first-in-human trial, treatment-naive adults aged 18-75 years with newly identified high-grade glioma that was evaluated per immunotherapy response assessment in neuro-oncology criteria, and a Karnofsky Performance Status score of 70 or more, underwent maximal safe resection followed by injections of adenoviral vectors expressing HSV1-TK and Flt3L into the tumour bed. The study was conducted at the University of Michigan Medical School, Michigan Medicine (Ann Arbor, MI, USA). The study included six escalating doses of viral particles with starting doses of 1×1010 Ad-hCMV-TK viral particles and 1×109 Ad-hCMV-Flt3L viral particles (cohort A), and then 1×1011 Ad-hCMV-TK viral particles and 1×109 Ad-hCMV-Flt3L viral particles (cohort B), 1×1010 Ad-hCMV-TK viral particles and 1×1010 Ad-hCMV-Flt3L viral particles (cohort C), 1×1011 Ad-hCMV-TK viral particles and 1×1010 Ad-hCMV-Flt3L viral particles (cohort D), 1×1010 Ad-hCMV-TK viral particles and 1×1011 Ad-hCMV-Flt3L viral particles (cohort E), and 1×1011 Ad-hCMV-TK viral particles and 1×1011 Ad-hCMV-Flt3L viral particles (cohort F) following a 3+3 design. Two 1 mL tuberculin syringes were used to deliver freehand a mix of Ad-hCMV-TK and Ad-hCMV-Flt3L vectors into the walls of the resection cavity with a total injection of 2 mL distributed as 0·1 mL per site across 20 locations. Subsequently, patients received two 14-day courses of valacyclovir (2 g orally, three times per day) at 1-3 days and 10-12 weeks after vector administration and standad upfront chemoradiotherapy. The primary endpoint was the maximum tolerated dose of Ad-hCMV-Flt3L and Ad-hCMV-TK. Overall survival was a secondary endpoint. Recruitment is complete and the trial is finished. The trial is registered with ClinicalTrials.gov, NCT01811992. FINDINGS: Between April 8, 2014, and March 13, 2019, 21 patients were assessed for eligibility and 18 patients with high-grade glioma were enrolled and included in the analysis (three patients in each of the six dose cohorts); eight patients were female and ten were male. Neuropathological examination identified 14 (78%) patients with glioblastoma, three (17%) with gliosarcoma, and one (6%) with anaplastic ependymoma. The treatment was well-tolerated, and no dose-limiting toxicity was observed. The maximum tolerated dose was not reached. The most common serious grade 3-4 adverse events across all treatment groups were wound infection (four events in two patients) and thromboembolic events (five events in four patients). One death due to an adverse event (respiratory failure) occurred but was not related to study treatment. No treatment-related deaths occurred during the study. Median overall survival was 21·3 months (95% CI 11·1-26·1). INTERPRETATION: The combination of two adenoviral vectors demonstrated safety and feasibility in patients with high-grade glioma and warrants further investigation in a phase 1b/2 clinical trial. FUNDING: Funded in part by Phase One Foundation, Los Angeles, CA, The Board of Governors at Cedars-Sinai Medical Center, Los Angeles, CA, and The Rogel Cancer Center at The University of Michigan.

Optimizing Precision Medicine for Breast Cancer Brain Metastases with Functional Drug Response Assessment.

The development of novel therapies for brain metastases is an unmet need. Brain metastases may have unique molecular features that could be explored as therapeutic targets. A better understanding of the drug sensitivity of live cells coupled to molecular analyses will lead to a rational prioritization of therapeutic candidates. We evaluated the molecular profiles of 12 breast cancer brain metastases (BCBM) and matched primary breast tumors to identify potential therapeutic targets. We established six novel patient-derived xenograft (PDX) from BCBM from patients undergoing clinically indicated surgical resection of BCBM and used the PDXs as a drug screening platform to interrogate potential molecular targets. Many of the alterations were conserved in brain metastases compared with the matched primary. We observed differential expressions in the immune-related and metabolism pathways. The PDXs from BCBM captured the potentially targetable molecular alterations in the source brain metastases tumor. The alterations in the PI3K pathway were the most predictive for drug efficacy in the PDXs. The PDXs were also treated with a panel of over 350 drugs and demonstrated high sensitivity to histone deacetylase and proteasome inhibitors. Our study revealed significant differences between the paired BCBM and primary breast tumors with the pathways involved in metabolisms and immune functions. While molecular targeted drug therapy based on genomic profiling of tumors is currently evaluated in clinical trials for patients with brain metastases, a functional precision medicine strategy may complement such an approach by expanding potential therapeutic options, even for BCBM without known targetable molecular alterations. Significance: Examining genomic alterations and differentially expressed pathways in brain metastases may inform future therapeutic strategies. This study supports genomically-guided therapy for BCBM and further investigation into incorporating real-time functional evaluation will increase confidence in efficacy estimations during drug development and predictive biomarker assessment for BCBM.

Milestones for neurosurgery sub-interns: a novel evaluation tool to quantitatively differentiate residency applicants.

OBJECTIVE: The study objective was to create a novel milestones evaluation form for neurosurgery sub-interns and assess its potential as a quantitative and standardized performance assessment to compare potential residency applicants. In this pilot study, the authors aimed to determine the form's interrater reliability, relationship to percentile assignments in the neurosurgery standardized letter of recommendation (SLOR), ability to quantitatively differentiate tiers of students, and ease of use. METHODS: Medical student milestones were either adapted from the resident Neurological Surgery Milestones or created de novo to evaluate a student's medical knowledge, procedural aptitude, professionalism, interpersonal and communication skills, and evidence-based practice and improvement. Four milestone levels were defined, corresponding to estimated 3rd-year medical student through 2nd-year resident levels. Faculty and resident evaluations as well as student self-evaluations were completed for 35 sub-interns across 8 programs. A cumulative milestone score (CMS) was computed for each student. Student CMSs were compared both within and between programs. Interrater reliability was determined with Kendall's coefficient of concordance (Kendall's W). Student CMSs were compared against their percentile assignments in the SLOR using analysis of variance with post hoc testing. CMS-derived percentile rankings were assigned to quantitatively distinguish tiers of students. Students and faculty were surveyed on the form's usefulness. RESULTS: The average faculty rating overall was 3.20, similar to the estimated competency level of an intern. Student and faculty ratings were similar, whereas resident ratings were lower (p < 0.001). Students were rated most highly in coachability and feedback (3.49 and 3.67, respectively) and lowest in bedside procedural aptitude (2.90 and 2.85, respectively) in both faculty and self-evaluations. The median CMS was 26.5 (IQR 21.75-29.75, range 14-32) with only 2 students (5.7%) achieving the highest rating of 32. Programs that evaluated the most students differentiated the highest-performing students from the lowest by at least 13 points. A program with 3 faculty raters demonstrated scoring agreement across 5 students (p = 0.024). The CMS differed significantly between SLOR percentile assignments, despite 25% of students being assigned to the top fifth percentile. CMS-driven percentile assignment significantly differentiated the bottom, middle, and top third of students (p < 0.001). Faculty and students strongly endorsed the milestones form. CONCLUSIONS: The medical student milestones form was well received and differentiated neurosurgery sub-interns both within and across programs. This form has potential as a replacement for numerical Step 1 scoring as a standardized, quantitative performance assessment for neurosurgery residency applicants.

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma (n = 153) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of 93.3 ± 1.6%. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.

102 AI-Based Molecular Classification of Diffuse Gliomas using Rapid, Label-Free Optical Imaging.

INTRODUCTION: Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. Access to timely molecular diagnostic testing for brain tumor patients is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. METHODS: By combining stimulated Raman histology (SRH), a rapid, label-free, non-consumptive, optical imaging method, and deep learning-based image classification, we are able to predict the molecular genetic features used by the World Health Organization (WHO) to define the adult-type diffuse glioma taxonomy, including IDH-1/2, 1p19q-codeletion, and ATRX loss. We developed a multimodal deep neural network training strategy that uses both SRH images and large-scale, public diffuse glioma genomic data (i.e. TCGA, CGGA, etc.) in order to achieve optimal molecular classification performance. RESULTS: One institution was used for model training (University of Michigan) and four institutions (NYU, UCSF, Medical University of Vienna, and University Hospital Cologne) were included for patient enrollment in the prospective testing cohort. Using our system, called DeepGlioma, we achieved an average molecular genetic classification accuracy of 93.2% and identified the correct diffuse glioma molecular subgroup with 91.5% accuracy within 2 minutes in the operating room. DeepGlioma outperformed conventional IDH1-R132H immunohistochemistry (94.2% versus 91.4% accuracy) as a first-line molecular diagnostic screening method for diffuse gliomas and can detect canonical and non-canonical IDH mutations. CONCLUSIONS: Our results demonstrate how artificial intelligence and optical histology can be used to provide a rapid and scalable alternative to wet lab methods for the molecular diagnosis of brain tumor patients during surgery.

Metabolomic Profiles of Human Glioma Inform Patient Survival.

Aims: Targeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data. Results: We found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival, while those whose tumors were enriched for nucleotides, redox molecules, and lipid metabolites fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data. Innovation: Our results suggest the existence of metabolic subtypes of GBM with differing prognoses, and further support the concept that metabolism may drive the aggressiveness of human gliomas. Conclusions: Our data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes. Antioxid. Redox Signal. 39, 942-956.

Subclonal evolution and expansion of spatially distinct THY1-positive cells is associated with recurrence in glioblastoma.

PURPOSE: Glioblastoma(GBM) is a lethal disease characterized by inevitable recurrence. Here we investigate the molecular pathways mediating resistance, with the goal of identifying novel therapeutic opportunities. EXPERIMENTAL DESIGN: We developed a longitudinal in vivo recurrence model utilizing patient-derived explants to produce paired specimens(pre- and post-recurrence) following temozolomide(TMZ) and radiation(IR). These specimens were evaluated for treatment response and to identify gene expression pathways driving treatment resistance. Findings were clinically validated using spatial transcriptomics of human GBMs. RESULTS: These studies reveal in replicate cohorts, a gene expression profile characterized by upregulation of mesenchymal and stem-like genes at recurrence. Analyses of clinical databases revealed significant association of this transcriptional profile with worse overall survival and upregulation at recurrence. Notably, gene expression analyses identified upregulation of TGFß signaling, and more than one-hundred-fold increase in THY1 levels at recurrence. Furthermore, THY1-positive cells represented <10% of cells in treatment-naïve tumors, compared to 75-96% in recurrent tumors. We then isolated THY1-positive cells from treatment-naïve patient samples and determined that they were inherently resistant to chemoradiation in orthotopic models. Additionally, using image-guided biopsies from treatment-naïve human GBM, we conducted spatial transcriptomic analyses. This revealed rare THY1+ regions characterized by mesenchymal/stem-like gene expression, analogous to our recurrent mouse model, which co-localized with macrophages within the perivascular niche. We then inhibited TGFBRI activity in vivo which decreased mesenchymal/stem-like protein levels, including THY1, and restored sensitivity to TMZ/IR in recurrent tumors. CONCLUSIONS: These findings reveal that GBM recurrence may result from tumor repopulation by pre-existing, therapy-resistant, THY1-positive, mesenchymal cells within the perivascular niche.

Association of Autologous Tumor Lysate-Loaded Dendritic Cell Vaccination With Extension of Survival Among Patients With Newly Diagnosed and Recurrent Glioblastoma: A Phase 3 Prospective Externally Controlled Cohort Trial.

Importance: Glioblastoma is the most lethal primary brain cancer. Clinical outcomes for glioblastoma remain poor, and new treatments are needed. Objective: To investigate whether adding autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) to standard of care (SOC) extends survival among patients with glioblastoma. Design, Setting, and Participants: This phase 3, prospective, externally controlled nonrandomized trial compared overall survival (OS) in patients with newly diagnosed glioblastoma (nGBM) and recurrent glioblastoma (rGBM) treated with DCVax-L plus SOC vs contemporaneous matched external control patients treated with SOC. This international, multicenter trial was conducted at 94 sites in 4 countries from August 2007 to November 2015. Data analysis was conducted from October 2020 to September 2021. Interventions: The active treatment was DCVax-L plus SOC temozolomide. The nGBM external control patients received SOC temozolomide and placebo; the rGBM external controls received approved rGBM therapies. Main Outcomes and Measures: The primary and secondary end points compared overall survival (OS) in nGBM and rGBM, respectively, with contemporaneous matched external control populations from the control groups of other formal randomized clinical trials. Results: A total of 331 patients were enrolled in the trial, with 232 randomized to the DCVax-L group and 99 to the placebo group. Median OS (mOS) for the 232 patients with nGBM receiving DCVax-L was 19.3 (95% CI, 17.5-21.3) months from randomization (22.4 months from surgery) vs 16.5 (95% CI, 16.0-17.5) months from randomization in control patients (HR = 0.80; 98% CI, 0.00-0.94; P = .002). Survival at 48 months from randomization was 15.7% vs 9.9%, and at 60 months, it was 13.0% vs 5.7%. For 64 patients with rGBM receiving DCVax-L, mOS was 13.2 (95% CI, 9.7-16.8) months from relapse vs 7.8 (95% CI, 7.2-8.2) months among control patients (HR, 0.58; 98% CI, 0.00-0.76; P < .001). Survival at 24 and 30 months after recurrence was 20.7% vs 9.6% and 11.1% vs 5.1%, respectively. Survival was improved in patients with nGBM with methylated MGMT receiving DCVax-L compared with external control patients (HR, 0.74; 98% CI, 0.55-1.00; P = .03). Conclusions and Relevance: In this study, adding DCVax-L to SOC resulted in clinically meaningful and statistically significant extension of survival for patients with both nGBM and rGBM compared with contemporaneous, matched external controls who received SOC alone. Trial Registration: ClinicalTrials.gov Identifier: NCT00045968.

IMPACT the Brain: A Team-Based Approach to Management of Metastatic Breast Cancer With CNS Metastases.

PURPOSE: CNS metastases are associated with decreased survival and quality of life for patients with metastatic breast cancer (MBC). Team-based care can optimize outcomes. IMPACT the Brain is a care coordination program that aims to improve access to team-based care for patients with MBC and CNS metastases. MATERIALS AND METHODS: Patients with MBC and CNS metastases were eligible for enrollment in this care coordination program. A team of specialists supported a dedicated program coordinator who provided navigation, education, specialty referral, and clinical trial screening. A unique intake form developed for the program created personalized, coordinated, and expedited specialty referrals. Patient-reported outcomes and caregiver burden assessments were collected on a voluntary basis throughout enrollment. Data were analyzed using descriptive statistics. RESULTS: Sixty patients were referred, and 53 were enrolled (88%). The median time to program enrollment was 1 day (range, 0-11) and to first visit was 5 days (range, 0-25). On the basis of the program intake form, 47 referrals were made across six specialties, most commonly physical medicine and rehabilitation (n = 10), radiation oncology (n = 10), and neuropsychology (n = 10). Nineteen patients (36%) consented to enroll in clinical trials. CONCLUSION: A tailored team-based care coordination program for patients with MBC and CNS metastases is feasible. Use of a unique intake screening form by a dedicated program coordinator resulted in faster time to first patient visit, enabled access to subspecialist care, and supported enrollment in clinical trials. Future research should focus on intervention development using PRO data collected in this care coordination program.

Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.

BACKGROUND: Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources. OBJECTIVE: To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence. METHODS: We used a fiber laser-based, label-free, nonconsumptive, high-resolution microscopy method (<60 seconds per 1 × 1 mm2), called stimulated Raman histology (SRH), to image a consecutive, multicenter cohort of patients with skull base tumor. SRH images were then used to train a convolutional neural network model using 3 representation learning strategies: cross-entropy, self-supervised contrastive learning, and supervised contrastive learning. Our trained convolutional neural network models were tested on a held-out, multicenter SRH data set. RESULTS: SRH was able to image the diagnostic features of both benign and malignant skull base tumors. Of the 3 representation learning strategies, supervised contrastive learning most effectively learned the distinctive and diagnostic SRH image features for each of the skull base tumor types. In our multicenter testing set, cross-entropy achieved an overall diagnostic accuracy of 91.5%, self-supervised contrastive learning 83.9%, and supervised contrastive learning 96.6%. Our trained model was able to segment tumor-normal margins and detect regions of microscopic tumor infiltration in meningioma SRH images. CONCLUSION: SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.

Correlation between brain tissue oxygen tension and regional cerebral oximetry in uninjured human brain under conditions of changing ventilation strategy.

Controversy surrounds regional cerebral oximetry (rSO2) because extracranial contamination and unmeasured changes in cerebral arterial:venous ratio confound readings. Correlation of rSO2 with brain tissue oxygen (PbrO2), a "gold standard" for cerebral oxygenation, could help resolve this controversy but PbrO2 measurement is highly invasive. This was a prospective cohort study. The primary aim was to evaluate correlation between PbrO2 and rSO2 and the secondary aim was to investigate the relationship between changing ventilation regimens and measurement of PbrO2 and rSO2. Patients scheduled for elective removal of cerebral metastases were anesthetized with propofol and remifentanil, targeted to a BIS range 40-60. rSO2 was measured using the INVOS 5100B monitor and PbrO2 using the Licox brain monitoring system. The Licox probe was placed into an area of normal brain within the tumor excision corridor. FiO2 and minute ventilation were sequentially adjusted to achieve two set points: (1) FiO2 0.3 and paCO2 30 mmHg, (2) FiO2 1.0 and paCO2 40 mmHg. PbrO2 and rSO2 were recorded at each. Nine participants were included in the final analysis, which showed a positive Spearman's correlation (r = 0.50, p = 0.036) between PbrO2 and rSO2. From set point 1 to set point 2, PbrO2 increased from median 6.0, IQR 4.0-11.3 to median 22.5, IQR 9.8-43.6, p = 0.015; rSO2 increased from median 68.0, IQR 62.5-80.5 to median 83.0, IQR 74.0-90.0, p = 0.047. Correlation between PbrO2 and rSO2 is evident. Increasing FiO2 and PaCO2 results in significant increases in cerebral oxygenation measured by both monitors.

Targeting integrated epigenetic and metabolic pathways in lethal childhood PFA ependymomas.

Childhood posterior fossa group A ependymomas (PFAs) have limited treatment options and bear dismal prognoses compared to group B ependymomas (PFBs). PFAs overexpress the oncohistone-like protein EZHIP (enhancer of Zeste homologs inhibitory protein), causing global reduction of repressive histone H3 lysine 27 trimethylation (H3K27me3), similar to the oncohistone H3K27M. Integrated metabolic analyses in patient-derived cells and tumors, single-cell RNA sequencing of tumors, and noninvasive metabolic imaging in patients demonstrated enhanced glycolysis and tricarboxylic acid (TCA) cycle metabolism in PFAs. Furthermore, high glycolytic gene expression in PFAs was associated with a poor outcome. PFAs demonstrated high EZHIP expression associated with poor prognosis and elevated activating mark histone H3 lysine 27 acetylation (H3K27ac). Genomic H3K27ac was enriched in PFAs at key glycolytic and TCA cycle­related genes including hexokinase-2 and pyruvate dehydrogenase. Similarly, mouse neuronal stem cells (NSCs) expressing wild-type EZHIP (EZHIP-WT) versus catalytically attenuated EZHIP-M406K demonstrated H3K27ac enrichment at hexokinase-2 and pyruvate dehydrogenase, accompanied by enhanced glycolysis and TCA cycle metabolism. AMPKα-2, a key component of the metabolic regulator AMP-activated protein kinase (AMPK), also showed H3K27ac enrichment in PFAs and EZHIP-WT NSCs. The AMPK activator metformin lowered EZHIP protein concentrations, increased H3K27me3, suppressed TCA cycle metabolism, and showed therapeutic efficacy in vitro and in vivo in patient-derived PFA xenografts in mice. Our data indicate that PFAs and EZHIP-WT­expressing NSCs are characterized by enhanced glycolysis and TCA cycle metabolism. Repurposing the antidiabetic drug metformin lowered pathogenic EZHIP, increased H3K27me3, and suppressed tumor growth, suggesting that targeting integrated metabolic/epigenetic pathways is a potential therapeutic strategy for treating childhood ependymomas.

G-CSF secreted by mutant IDH1 glioma stem cells abolishes myeloid cell immunosuppression and enhances the efficacy of immunotherapy.

Mutant isocitrate-dehydrogenase 1 (mIDH1) synthesizes the oncometabolite 2-hydroxyglutarate (2HG), which elicits epigenetic reprogramming of the glioma cells' transcriptome by inhibiting DNA and histone demethylases. We show that the efficacy of immune-stimulatory gene therapy (TK/Flt3L) is enhanced in mIDH1 gliomas, due to the reprogramming of the myeloid cells' compartment infiltrating the tumor microenvironment (TME). We uncovered that the immature myeloid cells infiltrating the mIDH1 TME are mainly nonsuppressive neutrophils and preneutrophils. Myeloid cell reprogramming was triggered by granulocyte colony-stimulating factor (G-CSF) secreted by mIDH1 glioma stem/progenitor-like cells. Blocking G-CSF in mIDH1 glioma­bearing mice restores the inhibitory potential of the tumor-infiltrating myeloid cells, accelerating tumor progression. We demonstrate that G-CSF reprograms bone marrow granulopoiesis, resulting in noninhibitory myeloid cells within mIDH1 glioma TME and enhancing the efficacy of immune-stimulatory gene therapy.

A customized 3D implant to target laser interstitial thermal therapy ablation of a posterior fossa mass.

Laser interstitial thermal therapy (LITT) is a minimally invasive neurosurgical technique that has been demonstrated to successfully ablate intracranial tumors. While LITT for supratentorial lesions can often be straightforward, ablation of infratentorial lesions can be difficult with current targeting technologies and instrumentation. The anatomical difficulty of targeting posterior fossa masses can be further complicated in patients who have had a prior craniectomy or other procedure that removed the bone that is required to set the surgical trajectory. This article describes use of a three-dimensional (3D)-printed customized surgical implant to improve and enable targeting of posterior fossa lesions using LITT, particularly in the setting of prior craniectomy. A 3D-printed implant was customized for a patient with a history of metastatic lung cancer and prior posterior fossa craniectomy who presented for treatment of a progressively enlarging contrast-enhancing lesion in the right cerebellar hemisphere. The device included a built-in bolt trajectory for LITT ablation. The temporary implant was successfully fabricated for use with laser ablation of a right cerebellar mass. Three potential trajectories for the LITT bolt were incorporated into the temporary implant, but only the primary trajectory was utilized. Laser ablation was performed with the implant and a SideFire laser probe. Customized 3D-printed implants can enable the use of LITT for patients who would not otherwise be candidates.

Introduction to special issue dedicated to the 35th anniversary of the joint section on tumors.

The American Association of Neurological Surgeons (AANS)/Congress of Neurological Surgeons (CNS) Joint Section on Tumors was formed in December of 1984 as the first professional organization devoted to the study and treatment of brain tumors. One year earlier, the Journal of Neuro-Oncology had been established and went on to be sponsored by the Joint Section on Tumors. To celebrate the 35th anniversary of the founding of the Section, we are thrilled to bring you this special issue of Journal of Neuro-Oncology in which current leaders of the Joint Section on Tumors highlight their work and the work of others that have led to significant recent advances in the management of tumors of the central nervous system.

A Phase 2 Study of Dose-intensified Chemoradiation Using Biologically Based Target Volume Definition in Patients With Newly Diagnosed Glioblastoma.

PURPOSE: We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TVHCV) and hyperperfused (TVCBV) tumor volumes would improve outcomes in patients with glioblastoma. METHODS AND MATERIALS: This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TVHCV/TVCBV >1 cm3, identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TVHCV/TVCBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TVHCV/TVCBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised. RESULTS: Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TVHCV alone, and 13 patients were boosted to both TVHCV/TVCBV. Gross or subtotal resection was performed in 87% of patients; 22% were O6-methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TVHCV/TVCBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TVHCV/TVCBV decreased to less than the median volume (3 cm3) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy. CONCLUSIONS: Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy.

Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks.

BACKGROUND: Detection of glioma recurrence remains a challenge in modern neuro-oncology. Noninvasive radiographic imaging is unable to definitively differentiate true recurrence versus pseudoprogression. Even in biopsied tissue, it can be challenging to differentiate recurrent tumor and treatment effect. We hypothesized that intraoperative stimulated Raman histology (SRH) and deep neural networks can be used to improve the intraoperative detection of glioma recurrence. METHODS: We used fiber laser-based SRH, a label-free, nonconsumptive, high-resolution microscopy method (<60 sec per 1 × 1 mm2) to image a cohort of patients (n = 35) with suspected recurrent gliomas who underwent biopsy or resection. The SRH images were then used to train a convolutional neural network (CNN) and develop an inference algorithm to detect viable recurrent glioma. Following network training, the performance of the CNN was tested for diagnostic accuracy in a retrospective cohort (n = 48). RESULTS: Using patch-level CNN predictions, the inference algorithm returns a single Bernoulli distribution for the probability of tumor recurrence for each surgical specimen or patient. The external SRH validation dataset consisted of 48 patients (recurrent, 30; pseudoprogression, 18), and we achieved a diagnostic accuracy of 95.8%. CONCLUSION: SRH with CNN-based diagnosis can be used to improve the intraoperative detection of glioma recurrence in near-real time. Our results provide insight into how optical imaging and computer vision can be combined to augment conventional diagnostic methods and improve the quality of specimen sampling at glioma recurrence.