Lim, Michael

OBJECTIVE Intramedullary spinal cord tumors (IMSCTs) are typically treated with maximal safe resection, during which neurosurgeons often monitor for neurological injury using muscle motor evoked potential (mMEP) and direct wave (D-wave) neuromonitoring. The predictive value of changes in D-waves for identifying motor outcomes is underexplored. This study evaluated the utility of D-waves for predicting postoperative motor deficits. METHODS Patients who underwent resection of a primary IMSCT with mMEP neuromonitoring from 2003 to 2023 at a tertiary care hospital were identified. Patients who underwent D-wave monitoring in addition to mMEP monitoring were compared to those who underwent mMEP monitoring alone using the Mann-Whitney U-test, chi-square test, and Fisher’s exact test. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of D-wave and mMEP monitoring for identifying new neurological deficits immediately postoperatively and at 1 month, 6 months, and last follow-up were calculated. RESULTS After matching, 125 patients were included (median age 42.0 years; 57.6% male; median follow-up 34.0 months), of whom 88 had both mMEP and D-wave data. The most common pathologies were ependymoma (64.0%) and astrocytoma (17.6%). Patients who did and did not undergo D-wave neuromonitoring had similar preoperative neurological function, primary pathology, tumor grade, and tumor location. D-wave use was associated with increased gross-total resection (88.6% vs 64.9%, p = 0.002) and reduced mortality (5.7% vs 24.3%, p = 0.007), length of stay (5.0 vs 6.0 days, p = 0.033), and 30-day readmission (2.3% vs 13.5%, p = 0.013) and reoperation (1.1% vs 10.8%, p = 0.012). At the 6-month follow-up, D-wave monitoring alone was superior to mMEP and combination monitoring for detecting new motor deficits. D-wave monitoring had peak sensitivity (77.8%) and NPV (96.5%) at 6 months and peak specificity (95.8%) and PPV (76.9%) in the immediate postoperative period. CONCLUSIONS D-wave monitoring was associated with reduced mortality and was more accurate than mMEP monitoring alone or combination monitoring for detecting new postoperative neurological deficits. Further prospective studies are needed to validate these results.

PURPOSE GBM AGILE (ClinicalTrials.gov identifier: NCT03970447 ) is a phase II/III Bayesian adaptive platform registration trial testing multiple arms against a common control; the primary end point is overall survival (OS). Regorafenib, a multikinase inhibitor, showed OS benefit in recurrent (RD) glioblastoma in the phase II REGOMA trial and entered GBM AGILE as the first investigational arm. METHODS Patient subtypes included in the regorafenib arm of GBM AGILE were newly diagnosed unmethylated (NDU) and RD glioblastoma. Prospective defined sets of subtypes, or arm signatures, were NDU, RD, and all (NDU + RD). As the first investigational arm in GBM AGILE, regorafenib was equally randomized to the control arm. Treatment in the control arm is temozolomide + radiotherapy (in newly diagnosed) or lomustine (in RD). Efficacy was assessed by OS hazard ratio (HR), arm/control, and demonstrated when the Bayesian probability of benefit (HR <1.00) was ≥98%. Analysis was performed monthly for limited efficacy, which occurs when the Bayesian predictive power is <25% for all signatures, and determines stopping enrollment. Follow-up continued for 12 months after accrual stopped. RESULTS When the predictive power was <25% in all predefined signatures for regorafenib, accrual stopped for limited efficacy. The final analysis did not demonstrate OS improvement in the regorafenib arm in RD nor NDU glioblastoma. Median HRs were 1.05 (NDU), 1.07 (RD), and 1.07 (all) with final probabilities of benefit (HR <1.00) of 0.421 (NDU), 0.312 (RD), and 0.296 (all). Regorafenib was associated with increased toxicity relative to control. CONCLUSION GBM AGILE did not show superiority of regorafenib over control in RD (lomustine) or NDU (temozolomide + radiotherapy) glioblastoma, yet caused increased toxicities. Regorafenib has been removed from National Comprehensive Cancer Network guidelines as a treatment option for RD.

Abstract Glioblastoma is the most common type of malignant primary brain tumor and a major cause of morbidity and mortality. In 2021, the World Health Organization updated the classification of Central Nervous System (CNS) tumors to restrict glioblastomas to isocitrate dehydrogenase-wildtype (IDHwt) tumors, improving understanding of the prognosis and optimal therapy for these tumors. This revision also enables more homogeneous populations of patients to be enrolled in clinical trials, facilitating the evaluation of novel therapies. In this updated consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of patients with glioblastoma is discussed. In addition, novel therapies such as immunotherapies, viral therapies, targeted molecular therapies, theranostics, and antibody–drug conjugates will be reviewed, as well as the current challenges and future directions for research.

Abstract GBM AGILE(NCT03970447) is a phase 2/3 Bayesian adaptive registration platform trial testing multiple therapies against a common control. Paxalisib, a PI3K/mTOR inhibitor, is the 3rd arm in the trial to conclude evaluation. METHODS Paxalisib was open to patients with newly diagnosed unmethylated (NDU) and recurrent (RD) glioblastoma, with three possible signatures: NDU, RD, and All(NDU+RD). Arm enrollment occurred Dec2020 through May2022. Control patients were enrolled from study initiation (July2019) and were treated with temozolomide(NDU) or lomustine(RD). GBM AGILE investigational arms have 1 or 2 stages, with adaptive randomization in stage 1 and fixed randomization if arms continue to stage 2. Efficacy is based on OS hazard ratio(HR) of Arm/Control. Efficacy goal is final Bayesian probability ≥ 98% for HR&lt;1.00 in combined Stages. An Arm continues to Stage 2 if Bayesian predictive power (PP) ≥ 0.8. An Arm stops accruing in Stage 1 if it reaches maximal sample size(N) or does not meet a minimum efficacy threshold (PP&lt;0.25 for all signatures when N&gt;50). Clinical cut-off is 12 months after accrual stops. The maximum N for paxalisib was approximately 150(Stage 1) and 50(Stage 2). RESULTS After paxalisib reached &gt;150 patients in Stage 1, accrual stopped [Paxalisib/control N 54/75(NDU), 100/188(RD)]. Neither PP thresholds for moving to Stage 2 nor stopping for minimum efficacy were met. Following an unplanned public disclosure that the arm did not continue to stage 2, clinical cut-off for final analysis (planned May2023) was updated to public disclosure date (August2022). At final analysis mean HRs were 0.89(NDU), 1.25(RD), 1.05(All), probabilities of HR&lt;1.00 of 0.72(NDU), 0.076(RD), 0.398(All). Model estimated median OS paxalisib/control (months) were 14.77/13.84(NDU) and 8.58/10.06(RD). CONCLUSION Paxalisib did not show survival benefit over cumulative control in final primary analysis; additional secondary analyses are being considered. GBM AGILE continues to rapidly and efficiently assess therapies in ND and RD glioblastoma.

The legacy of Stanford University's Department of Neurosurgery began in 1858, with the establishment of a new medical school on the West Coast. Stanford Neurosurgery instilled an atmosphere of dedication to neurosurgical care, scientific research, education, and innovation. We highlight key historical events leading to the formation of the medical school and neurosurgical department, the individuals who shaped the department's vision and expansion, as well as pioneering advances in research and clinical care. The residency program was started in 1961, establishing the basis of the current education model with a strong emphasis on training future leaders, and the Moyamoya Center, founded in 1991, became the largest Moyamoya referral center in the United States. The opening of Stanford Stroke Center (1992) and seminal clinical trials resulted in a significant impact on cerebrovascular disease by expanding the treatment window of IV thrombolysis and intra-arterial thrombectomy. The invention and implementation of CyberKnife ® (1994) marks another important event that revolutionized the field of radiosurgery, and the development of Stanford's innovative Brain Computer Interface program is pushing the boundaries of this specialty. The more recent launch of the Neurosurgery Virtual Reality and Simulation Center (2017) exemplifies how Stanford is continuing to evolve in this ever-changing field. The department also became a model for diversity within the school as well as nationwide. The growth of Stanford Neurosurgery from one of the youngest neurosurgery departments in the country to a prominent comprehensive neurosurgery center mirrors the history of neurosurgery itself: young, innovative, and willing to overcome challenges.

Abstract Immunotherapy has revolutionized treatment for many hard-to-treat cancers but has yet to produce significant improvement in outcomes for patients with glioblastoma. This reflects the multiple and unique mechanisms of immune evasion and escape in this highly heterogeneous tumor. Glioblastoma engenders profound local and systemic immunosuppression and is remarkably effective at inducing T-cell dysfunction, posing a challenge to any immunotherapy-based approach. To overcome these mechanisms, multiple disparate modes of immune-oriented therapy will be required. However, designing trials that can evaluate these combinatorial approaches requires careful consideration. In this review, we explore the immunotherapy resistance mechanisms that have been encountered to date and how combinatorial approaches may address these. We also describe the unique aspects of trial design in both preclinical and clinical settings and consider endpoints and markers of response best suited for an intervention involving multiple agents.

With rapid advances in our understanding of cancer, there is an expanding number of potential novel combination therapies, including novel–novel combinations. Identifying which combinations are appropriate and in which subpopulations are among the most difficult questions in medical research. We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review of trials of novel–novel combination therapies involving immunotherapies or molecular targeted therapies in advanced solid tumors. A MEDLINE search was conducted using a modified Cochrane Highly Sensitive Search Strategy for published clinical trials between July 1, 2017, and June 30, 2020, in the top-ranked medical and oncology journals. Trials were evaluated according to a criterion adapted from previously published Food and Drug Administration guidance and other key considerations in designing trials of combinations. This included the presence of a strong biological rationale, the use of a new established or emerging predictive biomarker prospectively incorporated into the clinical trial design, appropriate comparator arms of monotherapy or supportive external data sources and a primary endpoint demonstrating a clinically meaningful benefit. Of 32 identified trials, there were 11 (34%) trials of the novel–novel combination of anti-programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and anti-cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) therapy, and 10 (31%) trials of anti-PD-1/PD-L1 and anti-vascular endothelial growth factor (VEGF) combination therapy. 20 (62.5%) trials were phase II trials, while 12 (37.5%) were phase III trials. Most (72%) trials lacked significant preclinical evidence supporting the development of the combination in the given indication. A majority of trials (69%) were conducted in biomarker unselected populations or used pre-existing biomarkers within the given indication for patient selection. Most studies (66%) were considered to have appropriate comparator arms or had supportive external data sources such as prior studies of monotherapy. All studies were evaluated as selecting a clinically meaningful primary endpoint. In conclusion, designing trials to evaluate novel–novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design. Designing trials to evaluate novel–novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design.

AbstractBackgroundIt remains unknown how the COVID-19 pandemic has changed neuro-oncology clinical practice, training, and research efforts.MethodsWe performed an international survey of practitioners, scientists, and trainees from 21 neuro-oncology organizations across 6 continents, April 24–May 17, 2020. We assessed clinical practice and research environments, institutional preparedness and support, and perceived impact on patients.ResultsOf 582 respondents, 258 (45%) were US-based and 314 (55%) international. Ninety-four percent of participants reported changes in their clinical practice. Ninety-five percent of respondents converted at least some practice to telemedicine. Ten percent of practitioners felt the need to see patients in person, specifically because of billing concerns and pressure from their institutions. Sixty-seven percent of practitioners suspended enrollment for at least one clinical trial, including 62% suspending phase III trial enrollments. More than 50% believed neuro-oncology patients were at increased risk for COVID-19. Seventy-one percent of clinicians feared for their own personal safety or that of their families, specifically because of their clinical duties; 20% had inadequate personal protective equipment. While 69% reported increased stress, 44% received no psychosocial support from their institutions. Thirty-seven percent had salary reductions and 63% of researchers temporarily closed their laboratories. However, the pandemic created positive changes in perceived patient satisfaction, communication quality, and technology use to deliver care and mediate interactions with other practitioners.ConclusionsThe pandemic has changed treatment schedules and limited investigational treatment options. Institutional lack of support created clinician and researcher anxiety. Communication with patients was satisfactory. We make recommendations to guide clinical and scientific infrastructure moving forward and address the personal challenges of providers and researchers.

Abstract A subset of stem-like cells in glioblastoma (GBM; GSC) underlies tumor propagation, therapeutic resistance, and tumor recurrence. Immune evasion is critical for GSCs to carry out these functions. However, the molecular mechanisms employed by GSCs to escape antitumor immunity remain largely unknown. The reprogramming transcription factors Oct4 and Sox2 function as core multipotency factors and play an essential role in the formation and maintenance of GSCs, but the roles of these transcription factors in GSC immune escape have not been well explored. Here we examine how Oct4/Sox2 coexpression contributes to the immunosuppressive phenotype of GSCs. Combined transcription profiling and functional studies of Oct4/Sox2 coexpressing GSCs and differentiated GBM cells demonstrated that Oct4 and Sox2 cooperatively induce an immunosuppressive transcriptome consisting of multiple immunosuppressive checkpoints (i.e., PD-L1, CD70, A2aR, TDO) and dysregulation of cytokines and chemokines that are associated with an immunosuppressive tumor microenvironment. Mechanistically, induction and function of BRD/H3k27Ac-dependent immunosuppressive genes played a role in the immunosuppressive phenotype of GSCs. Pan-BET bromodomain inhibitors (e.g., JQ1) and shBRD4 constructs significantly inhibited the immunosuppressive transcriptome and immunosuppressive biological responses induced by Oct4/Sox2. Our findings identify targetable mechanisms by which tumor-propagating GSCs contribute to the immunosuppressive microenvironment in GBM. Significance: This report identifies mechanisms by which the reprogramming transcription factors Oct4 and Sox2 function to drive the immunomodulatory transcriptome of GSCs and contribute to the immunosuppressive microenvironment in GBM.