Quantification of cerebrospinal fluid tumor DNA in lung cancer patients with suspected leptomeningeal carcinomatosis.

Cerebrospinal fluid tumor-derived DNA (CSF-tDNA) analysis is a promising approach for monitoring the neoplastic processes of the central nervous system. We applied a lung cancer-specific sequencing panel (CAPP-Seq) to 81 CSF, blood, and tissue samples from 24 lung cancer patients who underwent lumbar puncture (LP) for suspected leptomeningeal disease (LMD). A subset of the cohort (N = 12) participated in a prospective trial of osimertinib for refractory LMD in which serial LPs were performed before and during treatment. CSF-tDNA variant allele fractions (VAFs) were significantly higher than plasma circulating tumor DNA (ctDNA) VAFs (median CSF-tDNA, 32.7%; median plasma ctDNA, 1.8%; P < 0.0001). Concentrations of tumor DNA in CSF and plasma were positively correlated (Spearman's ρ, 0.45; P = 0.03). For LMD diagnosis, cytology was 81.8% sensitive and CSF-tDNA was 91.7% sensitive. CSF-tDNA was also strongly prognostic for overall survival (HR = 7.1; P = 0.02). Among patients with progression on targeted therapy, resistance mutations, such as EGFR T790M and MET amplification, were common in peripheral blood but were rare in time-matched CSF, indicating differences in resistance mechanisms based on the anatomic compartment. In the osimertinib cohort, patients with CNS progression had increased CSF-tDNA VAFs at follow-up LP. Post-osimertinib CSF-tDNA VAF was strongly prognostic for CNS progression (HR = 6.2, P = 0.009). Detection of CSF-tDNA in lung cancer patients with suspected LMD is feasible and may have clinical utility. CSF-tDNA improves the sensitivity of LMD diagnosis, enables improved prognostication, and drives therapeutic strategies that account for spatial heterogeneity in resistance mechanisms.

Unraveling molecular advancements in chordoma tumorigenesis and treatment response: a review of scientific discoveries and clinical implications.

Chordomas are tumors thought to originate from notochordal remnants that occur in midline structures from the cloves of the skull base to the sacrum. In adults, the most common location is the sacrum, followed by the clivus and then mobile spine, while in children a clival origin is most common. Most chordomas are slow growing. Clinical presentation of chordomas tend to occur late, with local invasion and large size often complicating surgical intervention. Radiation therapy with protons has been proven to be an effective adjuvant therapy. Unfortunately, few adjuvant systemic treatments have demonstrated significant effectiveness, and chordomas tend to recur despite intensive multimodal care. However, insight into the molecular underpinnings of chordomas may guide novel therapeutic approaches including selection for immune and molecular therapies, individualized prognostication of outcomes, and real-time noninvasive assessment of disease burden and evolution. At the genomic level, elevated levels of brachyury stemming from duplications and mutations resulting in altered transcriptional regulation may introduce druggable targets for new surgical adjuncts. Transcriptome and epigenome profiling have revealed promoter- and enhancer-dependent mechanisms of protein regulation, which may influence therapeutic response and long-term disease history. Continued scientific and clinical advancements may offer further opportunities for treatment of chordomas. Single-cell transcriptome profiling has further provided insight into the heterogeneous molecular pathways contributing to chordoma propagation. New technologies such as spatial transcriptomics and emerging biochemical analytes such as cell-free DNA have further augmented the surgeon-clinician's armamentarium by facilitating detailed characterization of intra- and intertumoral biology while also demonstrating promise for point-of-care tumor quantitation and assessment. Recent and ongoing clinical trials highlight accelerating interest to translate laboratory breakthroughs in chordoma biology and immunology into clinical care. In this review, the authors dissect the landmark studies exploring the molecular pathogenesis of chordoma. Incorporating this into an outline of ongoing clinical trials and discussion of emerging technologies, the authors aimed to summarize recent advancements in understanding chordoma pathogenesis and how neurosurgical care of chordomas may be augmented by improvements in adjunctive treatments.

Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach.

Despite the importance of informed consent in healthcare, the readability and specificity of consent forms often impede patients' comprehension. This study investigates the use of GPT-4 to simplify surgical consent forms and introduces an AI-human expert collaborative approach to validate content appropriateness. Consent forms from multiple institutions were assessed for readability and simplified using GPT-4, with pre- and post-simplification readability metrics compared using nonparametric tests. Independent reviews by medical authors and a malpractice defense attorney were conducted. Finally, GPT-4's potential for generating de novo procedure-specific consent forms was assessed, with forms evaluated using a validated 8-item rubric and expert subspecialty surgeon review. Analysis of 15 academic medical centers' consent forms revealed significant reductions in average reading time, word rarity, and passive sentence frequency (all P < 0.05) following GPT-4-faciliated simplification. Readability improved from an average college freshman to an 8th-grade level (P = 0.004), matching the average American's reading level. Medical and legal sufficiency consistency was confirmed. GPT-4 generated procedure-specific consent forms for five varied surgical procedures at an average 6th-grade reading level. These forms received perfect scores on a standardized consent form rubric and withstood scrutiny upon expert subspeciality surgeon review. This study demonstrates the first AI-human expert collaboration to enhance surgical consent forms, significantly improving readability without sacrificing clinical detail. Our framework could be extended to other patient communication materials, emphasizing clear communication and mitigating disparities related to health literacy barriers.

Demographic Representation in 3 Leading Artificial Intelligence Text-to-Image Generators.

Importance: The progression of artificial intelligence (AI) text-to-image generators raises concerns of perpetuating societal biases, including profession-based stereotypes. Objective: To gauge the demographic accuracy of surgeon representation by 3 prominent AI text-to-image models compared to real-world attending surgeons and trainees. Design, Setting, and Participants: The study used a cross-sectional design, assessing the latest release of 3 leading publicly available AI text-to-image generators. Seven independent reviewers categorized AI-produced images. A total of 2400 images were analyzed, generated across 8 surgical specialties within each model. An additional 1200 images were evaluated based on geographic prompts for 3 countries. The study was conducted in May 2023. The 3 AI text-to-image generators were chosen due to their popularity at the time of this study. The measure of demographic characteristics was provided by the Association of American Medical Colleges subspecialty report, which references the American Medical Association master file for physician demographic characteristics across 50 states. Given changing demographic characteristics in trainees compared to attending surgeons, the decision was made to look into both groups separately. Race (non-White, defined as any race other than non-Hispanic White, and White) and gender (female and male) were assessed to evaluate known societal biases. Exposures: Images were generated using a prompt template, "a photo of the face of a [blank]", with the blank replaced by a surgical specialty. Geographic-based prompting was evaluated by specifying the most populous countries on 3 continents (the US, Nigeria, and China). Main Outcomes and Measures: The study compared representation of female and non-White surgeons in each model with real demographic data using χ2, Fisher exact, and proportion tests. Results: There was a significantly higher mean representation of female (35.8% vs 14.7%; P < .001) and non-White (37.4% vs 22.8%; P < .001) surgeons among trainees than attending surgeons. DALL-E 2 reflected attending surgeons' true demographic data for female surgeons (15.9% vs 14.7%; P = .39) and non-White surgeons (22.6% vs 22.8%; P = .92) but underestimated trainees' representation for both female (15.9% vs 35.8%; P < .001) and non-White (22.6% vs 37.4%; P < .001) surgeons. In contrast, Midjourney and Stable Diffusion had significantly lower representation of images of female (0% and 1.8%, respectively; P < .001) and non-White (0.5% and 0.6%, respectively; P < .001) surgeons than DALL-E 2 or true demographic data. Geographic-based prompting increased non-White surgeon representation but did not alter female representation for all models in prompts specifying Nigeria and China. Conclusion and Relevance: In this study, 2 leading publicly available text-to-image generators amplified societal biases, depicting over 98% surgeons as White and male. While 1 of the models depicted comparable demographic characteristics to real attending surgeons, all 3 models underestimated trainee representation. The study suggests the need for guardrails and robust feedback systems to minimize AI text-to-image generators magnifying stereotypes in professions such as surgery.

Performance of ChatGPT and GPT-4 on Neurosurgery Written Board Examinations.

BACKGROUND AND OBJECTIVES: Interest surrounding generative large language models (LLMs) has rapidly grown. Although ChatGPT (GPT-3.5), a general LLM, has shown near-passing performance on medical student board examinations, the performance of ChatGPT or its successor GPT-4 on specialized examinations and the factors affecting accuracy remain unclear. This study aims to assess the performance of ChatGPT and GPT-4 on a 500-question mock neurosurgical written board examination. METHODS: The Self-Assessment Neurosurgery Examinations (SANS) American Board of Neurological Surgery Self-Assessment Examination 1 was used to evaluate ChatGPT and GPT-4. Questions were in single best answer, multiple-choice format. χ 2 , Fisher exact, and univariable logistic regression tests were used to assess performance differences in relation to question characteristics. RESULTS: ChatGPT (GPT-3.5) and GPT-4 achieved scores of 73.4% (95% CI: 69.3%-77.2%) and 83.4% (95% CI: 79.8%-86.5%), respectively, relative to the user average of 72.8% (95% CI: 68.6%-76.6%). Both LLMs exceeded last year's passing threshold of 69%. Although scores between ChatGPT and question bank users were equivalent ( P = .963), GPT-4 outperformed both (both P < .001). GPT-4 answered every question answered correctly by ChatGPT and 37.6% (50/133) of remaining incorrect questions correctly. Among 12 question categories, GPT-4 significantly outperformed users in each but performed comparably with ChatGPT in 3 (functional, other general, and spine) and outperformed both users and ChatGPT for tumor questions. Increased word count (odds ratio = 0.89 of answering a question correctly per +10 words) and higher-order problem-solving (odds ratio = 0.40, P = .009) were associated with lower accuracy for ChatGPT, but not for GPT-4 (both P > .005). Multimodal input was not available at the time of this study; hence, on questions with image content, ChatGPT and GPT-4 answered 49.5% and 56.8% of questions correctly based on contextual context clues alone. CONCLUSION: LLMs achieved passing scores on a mock 500-question neurosurgical written board examination, with GPT-4 significantly outperforming ChatGPT.

Performance of ChatGPT, GPT-4, and Google Bard on a Neurosurgery Oral Boards Preparation Question Bank.

BACKGROUND AND OBJECTIVES: General large language models (LLMs), such as ChatGPT (GPT-3.5), have demonstrated the capability to pass multiple-choice medical board examinations. However, comparative accuracy of different LLMs and LLM performance on assessments of predominantly higher-order management questions is poorly understood. We aimed to assess the performance of 3 LLMs (GPT-3.5, GPT-4, and Google Bard) on a question bank designed specifically for neurosurgery oral boards examination preparation. METHODS: The 149-question Self-Assessment Neurosurgery Examination Indications Examination was used to query LLM accuracy. Questions were inputted in a single best answer, multiple-choice format. χ 2 , Fisher exact, and univariable logistic regression tests assessed differences in performance by question characteristics. RESULTS: On a question bank with predominantly higher-order questions (85.2%), ChatGPT (GPT-3.5) and GPT-4 answered 62.4% (95% CI: 54.1%-70.1%) and 82.6% (95% CI: 75.2%-88.1%) of questions correctly, respectively. By contrast, Bard scored 44.2% (66/149, 95% CI: 36.2%-52.6%). GPT-3.5 and GPT-4 demonstrated significantly higher scores than Bard (both P < .01), and GPT-4 outperformed GPT-3.5 ( P = .023). Among 6 subspecialties, GPT-4 had significantly higher accuracy in the Spine category relative to GPT-3.5 and in 4 categories relative to Bard (all P < .01). Incorporation of higher-order problem solving was associated with lower question accuracy for GPT-3.5 (odds ratio [OR] = 0.80, P = .042) and Bard (OR = 0.76, P = .014), but not GPT-4 (OR = 0.86, P = .085). GPT-4's performance on imaging-related questions surpassed GPT-3.5's (68.6% vs 47.1%, P = .044) and was comparable with Bard's (68.6% vs 66.7%, P = 1.000). However, GPT-4 demonstrated significantly lower rates of "hallucination" on imaging-related questions than both GPT-3.5 (2.3% vs 57.1%, P < .001) and Bard (2.3% vs 27.3%, P = .002). Lack of question text description for questions predicted significantly higher odds of hallucination for GPT-3.5 (OR = 1.45, P = .012) and Bard (OR = 2.09, P < .001). CONCLUSION: On a question bank of predominantly higher-order management case scenarios for neurosurgery oral boards preparation, GPT-4 achieved a score of 82.6%, outperforming ChatGPT and Google Bard.

Can We Use Artificial Intelligence Cluster Analysis to Identify Patients with Metastatic Breast Cancer to the Spine at Highest Risk of Postoperative Adverse Events?

OBJECTIVE: Group patients who required open surgery for metastatic breast cancer to the spine by functional level and metastatic disease characteristics to identify factors that predispose to poor outcomes. METHODS: A retrospective analysis included patients managed at 2 tertiary referral centers from 2008 to 2020. The primary outcome was a 90-day adverse event. A 2-step unsupervised cluster analysis stratified patients into cohorts using function at presentation, preoperative spine radiation, structural instability, epidural spinal cord compression (ESCC), neural deficits, and tumor location/hormone status. Comparisons were performed using χ2 test and one-way analysis of variance. RESULTS: Five patient "clusters" were identified. High function (HIGH) had thoracic metastases and an Eastern Cooperative Oncology Group (ECOG) score of 1.0 ± 0.8. Low function/irradiated (LOW + RADS) had preoperative radiation and the lowest Karnofsky scores (56.0 ± 10.6). Estrogen receptor or progesterone receptor (ER/PR) positive patients had >90% estrogen/progesterone positivity and moderate Karnofsky scores (74.0 ± 11.5). Lumbar/noncompressive (NON-COMP) had the fewest patients with ESCC grade 2 or 3 epidural disease (42.1%, P < 0.001). Low function/neurologic deficits (LOW + NEURO) had ESCC grade 2 or 3 disease and neurologic deficits. Adverse event rates were 25.0% in the HIGH group, 73.3% in LOW + RADS, 24.0% in ER/PR, 31.6% in NON-COMP, and 60.0% in LOW + NEURO (P = 0.003). CONCLUSIONS: Function at presentation, tumor hormone signature, radiation history, and epidural compression delineated postoperative trajectory. We believe our results can aid in expectation management and the identification of at-risk patients who may merit closer surveillance following surgical intervention.

Assessment of Spinal Metastases Surgery Risk Stratification Tools in Breast Cancer by Molecular Subtype.

BACKGROUND: Breast cancer molecular features and modern therapies are not included in spine metastasis prediction algorithms. OBJECTIVE: To examine molecular differences and the impact of postoperative systemic therapy to improve prognosis prediction for spinal metastases surgery and aid surgical decision making. METHODS: This is a retrospective multi-institutional study of patients who underwent spine surgery for symptomatic breast cancer spine metastases from 2008 to 2021 at the Massachusetts General Hospital and Brigham and Women's Hospital. We studied overall survival, stratified by breast cancer molecular subtype, and calculated hazard ratios (HRs) adjusting for demographics, tumor characteristics, treatments, and laboratory values. We tested the performance of established models (Tokuhashi, Bauer, Skeletal Oncology Research Group, New England Spinal Metastases Score) to predict and compare all-cause. RESULTS: A total of 98 patients surgically treated for breast cancer spine metastases were identified (100% female sex; median age, 56 years [IQR, 36-84 years]). The 1-year probabilities of survival for hormone receptor positive, hormone receptor positive/human epidermal growth factor receptor 2+, human epidermal growth factor receptor 2+, and triple-negative breast cancer were 63% (45 of 71), 83% (10 of 12), 0% (0 of 3), and 12% (1 of 8), respectively ( P < .001). Patients with triple-negative breast cancer had a higher proportion of visceral metastases, brain metastases, and poor physical activity at baseline. Postoperative chemotherapy and endocrine therapy were associated with prolonged survival. The Skeletal Oncology Research Group prognostic model had the highest discrimination (area under the receiver operating characteristic, 0.77 [95% CI, 0.73-0.81]). The performance of all prognostic scores improved when preoperative molecular data and postoperative systemic treatment plans was considered. CONCLUSION: Spine metastases risk tools were able to predict prognosis at a significantly higher degree after accounting for molecular features which guide treatment response.

Elevated ETV6 Expression in Glioma Promotes an Aggressive In Vitro Phenotype Associated with Shorter Patient Survival.

Background: GBM astrocytes may adopt fetal astrocyte transcriptomic signatures involved in brain development and migration programs to facilitate diffuse tumor infiltration. Our previous data show that ETS variant 6 (ETV6) is highly expressed in human GBM and fetal astrocytes compared to normal mature astrocytes. We hypothesized that ETV6 played a role in GBM tumor progression. Methods: Expression of ETV6 was first examined in two American and three Chinese tissue microarrays. The correlation between ETV6 staining intensity and patient survival was calculated, followed by validation using public databases-TCGA and REMBRANDT. The effect of ETV6 knockdown on glioma cell proliferation (EdU), viability (AnnexinV labeling), clonogenic growth (colony formation), and migration/invasion (transwell assays) in GBM cells was tested. RNA sequencing and Western blot were performed to elucidate the underlying molecular mechanisms. Results: ETV6 was highly expressed in GBM and associated with an unfavorable prognosis. ETV6 silencing in glioma cells led to increased apoptosis or decreased proliferation, clonogenicity, migration, and invasion. RNA-Seq-based gene expression and pathway analyses revealed that ETV6 knockdown in U251 cells led to the upregulation of genes involved in extracellular matrix organization, NF-κB signaling, TNF-mediated signaling, and the downregulation of genes in the regulation of cell motility, cell proliferation, PI3K-AKT signaling, and the Ras pathway. The downregulation of the PI3K-AKT and Ras-MAPK pathways were further validated by immunoblotting. Conclusion: Our findings suggested that ETV6 was highly expressed in GBM and its high expression correlated with poor survival. ETV6 silencing decreased an aggressive in vitro phenotype probably via the PI3K-AKT and Ras-MAPK pathways. The study encourages further investigation of ETV6 as a potential therapeutic target of GBM.

Effects of rod diameter on kinematics of posterior cervical spine instrumented constructs: an ex vivo study.

OBJECTIVE: Posterior cervical spine fixation is a robust strategy for stabilizing the spine for a wide range of spinal disorders. With the evolution of spinal implant technology, posterior fixation with lateral mass screws in the subaxial spine is now common. Despite interest in variable rod diameters to meet a wide range of clinical needs such as trauma, revision, and deformity surgery, indications for use of posterior cervical spine fixation are not clear. This laboratory investigation evaluates the mechanical stability and kinematic properties of lateral mass fixation with various commercially available rod diameters. METHODS: The authors conducted an ex vivo experiment using 13 fresh-frozen human cervical spine specimens, instrumented from C3 to C6 with lateral mass screws, to evaluate the effects of titanium rod diameter on kinematic stability. Each intact spine was tested using a kinematic profiling machine with an optoelectrical camera and infrared sensors applying 1.5-Nm bending moments to the cranial vertebra (C2) simulating flexion-extension, lateral bending, and axial rotation anatomical motions. A compressive follower preload of 150 N was applied in flexion-extension prior to application of a bending moment. Instrumented spines were then tested with rod diameters of 3.5, 4.0, and 4.5 mm. The kinematic data between intact and surgical cases were studied using a nonparametric Wilcoxon signed-rank test. A multivariable, multilevel linear regression model was built to identify the relationship between segmental motion and rod diameter. RESULTS: Instrumentation resulted in significant reduction in range of motion in all three rod constructs versus intact specimens in flexion-extension, lateral bending, and axial rotation (p < 0.05). The maximum reductions in segmental ROM versus intact spines in 3.5-, 4.0-, and 4.5-mm rod constructs were 61%, 71%, and 81% in flexion-extension; 70%, 76%, and 81% in lateral bending; and 50%, 60%, and 75% in axial rotation, respectively. Segmental motion at the adjacent segments (C2-3 and C6-7) increased significantly (p < 0.05) with increasing rod diameter. The 4.5-mm rod construct had the greatest increase in motion compared to the intact spine. CONCLUSIONS: With increasing rod diameters from 3.5 to 4.0 mm, flexion-extension, lateral bending, and axial rotation across C3-6 were significantly reduced (p < 0.05). Similar trends were observed with a statistically significant reduction in motion in all anatomical planes when the rod diameter was increased to 4.5 mm. Although the increase in rod diameter resulted in a more rigid construct, it also created an increase (p < 0.05) in the kinematics of the adjacent segments (C2-3 and C6-7). Whether this increase translates into adverse long-term clinical effects in vivo requires further investigation and clinical assessment.

Evaluating frailty, mortality, and complications associated with metastatic spine tumor surgery using machine learning-derived body composition analysis.

OBJECTIVE: Cancer patients with spinal metastases may undergo surgery without clear assessments of prognosis, thereby impacting the optimal palliative strategy. Because the morbidity of surgery may adversely impact recovery and initiation of adjuvant therapies, evaluation of risk factors associated with mortality risk and complications is critical. Evaluation of body composition of cancer patients as a surrogate for frailty is an emerging area of study for improving preoperative risk stratification. METHODS: To examine the associations of muscle characteristics and adiposity with postoperative complications, length of stay, and mortality in patients with spinal metastases, the authors designed an observational study of 484 cancer patients who received surgical treatment for spinal metastases between 2010 and 2019. Sarcopenia, muscle radiodensity, visceral adiposity, and subcutaneous adiposity were assessed on routinely available 3-month preoperative CT images by using a validated deep learning methodology. The authors used k-means clustering analysis to identify patients with similar body composition characteristics. Regression models were used to examine the associations of sarcopenia, frailty, and clusters with the outcomes of interest. RESULTS: Of 484 patients enrolled, 303 had evaluable CT data on muscle and adiposity (mean age 62.00 ± 11.91 years; 57.8% male). The authors identified 2 clusters with significantly different body composition characteristics and mortality risks after spine metastases surgery. Patients in cluster 2 (high-risk cluster) had lower muscle mass index (mean ± SD 41.16 ± 7.99 vs 50.13 ± 10.45 cm2/m2), lower subcutaneous fat area (147.62 ± 57.80 vs 289.83 ± 109.31 cm2), lower visceral fat area (82.28 ± 48.96 vs 239.26 ± 98.40 cm2), higher muscle radiodensity (35.67 ± 9.94 vs 31.13 ± 9.07 Hounsfield units [HU]), and significantly higher risk of 1-year mortality (adjusted HR 1.45, 95% CI 1.05-2.01, p = 0.02) than individuals in cluster 1 (low-risk cluster). Decreased muscle mass, muscle radiodensity, and adiposity were not associated with a higher rate of complications after surgery. Prolonged length of stay (> 7 days) was associated with low muscle radiodensity (mean 30.87 vs 35.23 HU, 95% CI 1.98-6.73, p < 0.001). CONCLUSIONS: Body composition analysis shows promise for better risk stratification of patients with spinal metastases under consideration for surgery. Those with lower muscle mass and subcutaneous and visceral adiposity are at greater risk for inferior outcomes.

Comprehensive RNA analysis of CSF reveals a role for CEACAM6 in lung cancer leptomeningeal metastases.

Non-small cell lung cancer (NSCLC) metastatic to the brain leptomeninges is rapidly fatal, cannot be biopsied, and cancer cells in the cerebrospinal fluid (CSF) are few; therefore, available tissue samples to develop effective treatments are severely limited. This study aimed to converge single-cell RNA-seq and cell-free RNA (cfRNA) analyses to both diagnose NSCLC leptomeningeal metastases (LM), and to use gene expression profiles to understand progression mechanisms of NSCLC in the brain leptomeninges. NSCLC patients with suspected LM underwent withdrawal of CSF via lumbar puncture. Four cytology-positive CSF samples underwent single-cell capture (n = 197 cells) by microfluidic chip. Using robust principal component analyses, NSCLC LM cell gene expression was compared to immune cells. Massively parallel qPCR (9216 simultaneous reactions) on human CSF cfRNA samples compared the relative gene expression of patients with NSCLC LM (n = 14) to non-tumor controls (n = 7). The NSCLC-associated gene, CEACAM6, underwent in vitro validation in NSCLC cell lines for involvement in pathologic behaviors characteristic of LM. NSCLC LM gene expression revealed by single-cell RNA-seq was also reflected in CSF cfRNA of cytology-positive patients. Tumor-associated cfRNA (e.g., CEACAM6, MUC1) was present in NSCLC LM patients' CSF, but not in controls (CEACAM6 detection sensitivity 88.24% and specificity 100%). Cell migration in NSCLC cell lines was directly proportional to CEACAM6 expression, suggesting a role in disease progression. NSCLC-associated cfRNA is detectable in the CSF of patients with LM, and corresponds to the gene expression profile of NSCLC LM cells. CEACAM6 contributes significantly to NSCLC migration, a hallmark of LM pathophysiology.

Surgical outcomes of pediatric spinal cord astrocytomas: systematic review and meta-analysis.

OBJECTIVE: Pediatric spinal astrocytomas are rare spinal lesions that pose unique management challenges. Therapeutic options include gross-total resection (GTR), subtotal resection (STR), and adjuvant chemotherapy or radiation therapy. With no randomized controlled trials, the optimal management approach for children with spinal astrocytomas remains unclear. The aim of this study was to conduct a systematic review and meta-analysis on pediatric spinal astrocytomas. METHODS: The authors performed a systematic review of the PubMed/MEDLINE electronic database to investigate the impact of histological grade and extent of resection on overall survival among patients with spinal cord astrocytomas. They retained publications in which the majority of reported cases included astrocytoma histology. RESULTS: Twenty-nine previously published studies met the eligibility criteria, totaling 578 patients with spinal cord astrocytomas. The spinal level of intramedullary spinal cord tumors was predominantly cervical (53.8%), followed by thoracic (40.8%). Overall, resection was more common than biopsy, and GTR was slightly more commonly achieved than STR (39.7% vs 37.0%). The reported rates of GTR and STR rose markedly from 1984 to 2015. Patients with high-grade astrocytomas had markedly worse 5-year overall survival than patients with low-grade tumors. Patients receiving GTR may have better 5-year overall survival than those receiving STR. CONCLUSIONS: The authors describe trends in the management of pediatric spinal cord astrocytomas and suggest a benefit of GTR over STR for 5-year overall survival.

Single-Cell RNA-Sequencing in Glioma.

PURPOSE OF REVIEW: In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas. RECENT FINDINGS: Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas.

Recurrently Mutated Genes Differ between Leptomeningeal and Solid Lung Cancer Brain Metastases.

When compared with solid brain metastases from NSCLC, leptomeningeal disease (LMD) has unique growth patterns and is rapidly fatal. Patients with LMD do not undergo surgical resection, limiting the tissue available for scientific research. In this study we performed whole exome sequencing on eight samples of LMD to identify somatic mutations and compared the results with those for 26 solid brain metastases. We found that taste 2 receptor member 31 gene (TAS2R31) and phosphodiesterase 4D interacting protein gene (PDE4DIP) were recurrently mutated among LMD samples, suggesting involvement in LMD progression. Together with a retrospective review of the charts of an additional 44 patients with NSCLC LMD, we discovered a surprisingly low number of KRAS mutations (n = 4 [7.7%]) but a high number of EGFR mutations (n = 33 [63.5%]). The median interval for development of LMD from NSCLC was shorter in patients with mutant EGFR (16.3 months) than in patients with wild-type EGFR (23.9 months) (p = 0.017). Targeted analysis of recurrent mutations thus presents a useful complement to the existing diagnostic tool kit, and correlations of EGFR in LMD and KRAS in solid metastases suggest that molecular distinctions or systemic treatment pressure underpin the differences in growth patterns within the brain.

Massive Intradural Chondroma Masquerading as Lower Body Parkinsonism.

Intracranial chondromas of the dural convexity are exceedingly rare with less than 30 reported in the literature to date. We report a massive intradural convexity chondroma in a patient initially thought to have a frontal gait neurodegenerative disorder. This large tumor required a complex, piecemeal surgical resection due to the dense, fibrous nature of the tumor and the proximity of crucial structures. The patient had complete resolution of her preoperative symptoms after surgical excision.

A review of potential applications of MR-guided focused ultrasound for targeting brain tumor therapy.

Magnetic resonance-guided focused ultrasound (MRgFUS) has been used extensively to ablate brain tissue in movement disorders, such as essential tremor. At a lower energy, MRgFUS can disrupt the blood-brain barrier (BBB) to allow passage of drugs. This focal disruption of the BBB can target systemic medications to specific portions of the brain, such as for brain tumors. Current methods to bypass the BBB are invasive, as the BBB is relatively impermeable to systemically delivered antineoplastic agents. Multiple healthy and brain tumor animal models have suggested that MRgFUS disrupts the BBB and focally increases the concentration of systemically delivered antitumor chemotherapy, immunotherapy, and gene therapy. In animal tumor models, combining MRgFUS with systemic drug delivery increases median survival times and delays tumor progression. Liposomes, modified microbubbles, and magnetic nanoparticles, combined with MRgFUS, more effectively deliver chemotherapy to brain tumors. MRgFUS has great potential to enhance brain tumor drug delivery, while limiting treatment toxicity to the healthy brain.