Gliomas are infiltrative primary brain tumors that often invade functional cortical and subcortical regions, and they mandate individualized brain mapping strategies to avoid postoperative neurological deficits. It is well known that maximal safe resection significantly improves survival, while postoperative deficits minimize the benefits associated with aggressive resections and diminish patients’ quality of life. Although non-invasive imaging tools serve as useful adjuncts, intraoperative stimulation mapping (ISM) is the gold standard for identifying functional cortical and subcortical regions and minimizing morbidity during these challenging resections. Current mapping methods rely on the use of low-frequency and high-frequency stimulation, delivered with monopolar or bipolar probes either directly to the cortical surface or to the subcortical white matter structures. Stimulation effects can be monitored through patient responses during awake mapping procedures and/or with motor-evoked and somatosensory-evoked potentials in patients who are asleep. Depending on the patient’s preoperative status and tumor location and size, neurosurgeons may choose to employ these mapping methods during awake or asleep craniotomies, both of which have their own benefits and challenges. Regardless of which method is used, the goal of intraoperative stimulation is to identify areas of non-functional tissue that can be safely removed to facilitate an approach trajectory to the equator, or center, of the tumor. Recent technological advances have improved ISM’s utility in identifying subcortical structures and minimized the seizure risk associated with cortical stimulation. In this review, we summarize the salient technical aspects of which neurosurgeons should be aware in order to implement intraoperative stimulation mapping effectively and safely during glioma surgery.

Background: There is a concern that glioma patients undergoing repeat craniotomies are more prone to complications. The study’s goal was to assess if the complication profiles for initial and repeat craniotomies were similar, to determine predictors of complications, and to compare results with those in the literature. Methods: A retrospective study was conducted of glioma patients (WHO grade II–IV) who underwent either an initial or repeat craniotomy performed by the senior author from 2012 until 2019. Complications were recorded by discharge, 30 days, and 90 days postoperatively. New neurologic deficits were recorded by 90 days postoperatively. Multivariate regression was performed to identify factors associated with complications. A meta-analysis was performed to identify rates of complications based on number of prior craniotomies. Results: Within the cohort of 714 patients, 400 (56%) had no prior craniotomies, 218 (30.5%) had undergone 1 prior craniotomy, and 96 (13.5%) had undergone ≥ 2 prior craniotomies. There were 27 surgical and 10 medical complications in 30 patients (4.2%) and 19 reoperations for complications in 19 patients (2.7%) with no deaths by 90 days. Complications, reoperation rates, and new neurologic deficits did not differ based on number of prior craniotomies. On multivariate analysis, older age (OR1.5, 95%CI 1.0–2.2) and significant leukocytosis due to steroid use (OR12.6, 95%CI 2.5–62.9) were predictors of complications. Complication rates in the cohort were lower than rates reported in the literature. Conclusion: Contrary to prior reports in the literature, repeat craniotomies can be as safe as initial operations if surgeons implement best practices.

Gliomas are infiltrative brain tumors that often involve functional tissue. While maximal safe resection is critical for maximizing survival, this is challenged by the difficult intraoperative discrimination between tumor-infiltrated and normal structures. Surgical expertise is essential for identifying safe margins, and while the intraoperative pathological review of frozen tissue is possible, this is a time-consuming task. Advances in intraoperative stimulation mapping have aided surgeons in identifying functional structures and, as such, has become the gold standard for this purpose. However, intraoperative margin assessment lacks a similar consensus. Nonetheless, recent advances in intraoperative imaging techniques and tissue examination methods have demonstrated promise for the accurate and efficient assessment of tumor infiltration and margin delineation within the operating room, respectively. In this review, we describe these innovative technologies that neurosurgeons should be aware of.

Anterior cervical discectomy and fusion (ACDF) interbody implants are shaped anatomically, with a convex superior aspect, or lordotically, with an angle and flat surfaces. However, the effect of implant shape on cervical sagittal balance (CSB) is not well described. Of the 192 cases reviewed from 2018 to 2019, 118 were included with matching pre- and postoperative imaging. Cases were categorized by interbody implant type (anatomic or lordotic) and number of levels fused (1-level, 2-level, etc.). SurgiMap was used to measure cervical lordosis (CL), C2-C7 sagittal vertical axis (cSVA), T1 slope (T1S), and T1S minus CL (T1S-CL) on pre- and postoperative imaging. Pre- and postoperative parameters were compared within and between each cohort. Change in CL (ΔCL), cSVA (ΔcSVA), and T1S-CL (ΔT1S-CL) were calculated as the difference between pre- and postoperative values and were compared accordingly (1) anatomic versus lordotic and (2) 1-level versus 2-level versus 3-level fusion. Thirty-nine (33.1%), 57 (48.3%), and 22 (18.6%) cases comprised the anatomic, lordotic, and mixed (anatomic and lordotic) groups, respectively. ACDFs improved CL and T1S-CL by 5.71° (p<.001) and 3.32° (p<.01), respectively. CL was improved in the lordotic (5.27°; p<.01) and anatomic (4.57°; p<.01) groups, while only the lordotic group demonstrated improvement in T1S-CL (3.4°; p=.02). There were no differences in ΔCL (p=.70), ΔcSVA (p=.89), or ΔT1S-CL (p=.1) between the groups. Two- and 3-level fusions improved CL by 7.48° (p<.01) and 9.62° (p<.01), and T1S-CL by 4.43° (p<.01) and 5.96° (p<.01), respectively. Overall, ACDFs significantly improved CL and T1S-CL however, there were no differences in CSB correction between the anatomic and lordotic groups. Two- and 3-level fusions more effectively improved CL (vs. single-level) and T1S-CL (vs. 3-level). These results suggest that implants should continue to be personalized to the patient's anatomy, however, future research is needed to validate these findings and incorporate the effects of preoperative deformities.

NF1 is recurrently mutated in glioblastoma yet the molecular landscape and efficacy of targeted therapies remain unclear. Here, we combine bulk and single cell genomics of human somatic NF1 mutant, IDH-wildtype glioblastomas with functional genomic analysis of cell lines and mouse intracranial tumor models to identify molecular subgroups within NF1 mutant glioblastomas and mechanisms underlying MEK inhibitor response. Targeted DNA sequencing showed homozygous deletion of the cell cycle regulator CDKN2A/B is a poor prognostic marker in somatic NF1 mutant, but not NF1 wildtype, tumors. DNA methylation array profiling revealed three epigenetic groups highlighted by distinct clinical features, co-mutation patterns, and reference methylation classifier identities. Genome-wide CRISPRi screens in glioblastoma cells revealed cell cycle regulators are conserved mediators of cell growth while response to the MEK inhibitor selumetinib converges on Ras/RAF/MEK pathway activation. Repression of the RAF regulator SHOC2 sensitizes glioblastomas to selumetinib in vitro and in vivo in mouse intracranial glioblastoma models. Single cell RNA-sequencing of mouse intracranial glioblastomas treated with the MEK inhibitor selumetinib reveals distinct responses between mesenchymal-like (MES-like) and non MES-like subpopulations suggesting non-MES like cells are intrinsically resistant to MEK inhibition. Finally, single nuclear RNA-sequencing (snRNA-seq) of human NF1 mutant, CDKN2A/B deleted glioblastomas reveals MES-like tumor cells are associated with selumetinib sensitivity signatures while non MES-like cells exhibit increased cell cycle progression and lack selumetinib sensitivity, further supporting the notion that MEK inhibition specifically targets MES-like tumor cell subpopulations. Taken together, our data underscores the heterogeneity between and within somatic NF1 mutant glioblastomas and delineates mechanisms of MEK inhibitor response across distinct tumor subpopulations, guiding the development of future therapeutic strategies that may synergize with MEK inhibition for NF1 mutant tumors. The tumor suppressor NF1 is mutated in 15% of glioblastomas, ^1–3 the most common malignant brain tumor with poor outcomes and few effective treatments. ⁴ NF1 is a GTPase activating protein (GAP) that negatively regulates Ras, and thus, NF1 loss leads to induction of Ras/RAF/MEK/ERK signaling, driving tumorigenesis and comprising a targetable molecular cascade. ^5,6 Genomic analysis of glioblastoma demonstrates NF1 mutation is associated with a mesenchymal-like (MES-like) transcriptomic tumor cell subpopulation and altered tumor microenvironment. ^7,8 More broadly, DNA methylation analysis reveals multiple epigenetic subgroups with overlapping relationships to transcriptomic subtype and DNA alterations, underscoring the complex relationship between genetic drivers and molecular signatures. ⁹ While the updated 2021 Central Nervous System WHO tumor classification incorporates an ever increasing amount of molecular criteria for diffuse astrocytic tumors, ¹⁰ the existence and clinical significance of molecular subgroups within somatic NF1 mutant, IDH-wildtype glioblastomas based on genetic co-mutations, epigenetic profile, or transcriptomic signatures remain unclear. Preclinical data support the utility of MEK inhibition in NF1 mutant gliomas, ^11,12 and the MEK inhibitor selumetinib is FDA approved for tumors arising in patients with syndromic neurofibromatosis type 1 (NF-1) harboring a germline NF1 mutation. ^13,14 In NF-1 associated gliomas, MEK inhibition demonstrates efficacy in a limited case series, ¹⁵ and combined BRAF/MEK inhibition shows efficacy in BRAF p.V600E mutant gliomas, ¹⁶ further supporting the translational potential of Ras/Raf/MEK/ERK blockade within genetically defined glioma subtypes. Nevertheless, treatment resistance to molecular monotherapy remains a challenge, ^17–20 and the mechanisms underlying MEK inhibitor resistance in NF1 mutant glioma are unknown. Here, we integrate targeted DNA sequencing, DNA methylation profiling, and single nuclear RNA-sequencing (snRNA-seq) of human patient somatic NF1 mutant, IDH-wildtype glioblastomas with single cell RNA-sequencing (scRNA-seq), genome-wide clustered regularly interspaced short palindromic repeats interference (CRISPRi) screens, and pharmacologic studies in cell lines and mouse intracranial glioblastoma models to define molecular subgroups and functional mediators of MEK inhibitor response. Targeted DNA sequencing of NF1 mutant, IDH-wildtype glioblastomas (n=186 tumors) revealed CDKN2A/B deletion was associated with poor outcomes in NF1 mutant, but not NF1 wildtype, glioblastomas. DNA methylation profiling (n=129 tumors) demonstrated three epigenetic subgroups with distinct clinical features, co- mutation patterns across cell cycle genes, and reference methylation classifier identities. Genome-wide CRISPRi screens in mouse SB28 and human GBM43 glioblastoma cells identified a conserved cell cycle gene network mediating cell growth, consistent with the clinical importance of additional hits affecting the cell cycle in human somatic NF1 mutant glioblastomas. Moreover, genome-wide mediators of selumetinib response converged upon two Ras pathway effectors mediating selumetinib sensitivity: BRAF and SHOC2. SHOC2 repression in glioblastoma cells significantly improved selumetinib response both in vitro and in intracranial allografts in vivo . Single cell RNA-sequencing (scRNA-seq) of mouse intracranial glioblastomas treated with the MEK inhibitor selumetinib revealed MES-like tumor cells correlated with CDKN2A retention and the CRISPRi screen selumetinib sensitivity signature, with selumetinib resistant cells displaying Ras pathway induction. In contrast, non-MES like tumor cells were CDKN2A deficient and lacked expression of the CRISPRi screen selumetinib sensitivity signature, with selumetinib resistant cells inducing a glial de-differentiation program. Finally, snRNA-seq of NF1 mutant, CDKN2A/B deleted, IDH-wildtype glioblastomas (n=9) showed non MES-like tumor cells exhibit increased cell cycle progression and were not associated with the CRISPRi screen selumetinib sensitivity signature. MES-like tumor cells within newly diagnosed, but not recurrent, tumors retained expression of the CRISPRi screen selumetinib sensitivity signature, suggesting resistance can arise both between and within specific transcriptomic glioblastoma cell tumor cell subpopulations. Taken together, our data identifies clinically important subgroups of NF1 mutant, IDH-wildtype glioblastomas and supports a model in which heterogeneity between tumors and within tumor cell subpopulations underlies MEK inhibitor response, supporting the need for additional synergistic therapeutic approaches beyond maximal Ras pathway blockade for NF1 mutant glioblastomas.