Background: Cerebral cavernous malformations (CCMs) presenting with seizures can be treated with neurosurgery or radiosurgery, but the ideal treatment remains unclear. Currently, there is no adequate randomized controlled trial comparing surgical treatment and radiotherapy for epileptogenic CCMs. Therefore, we conducted a systematic review and meta-analysis of available data from published literature to compare the efficacy and safety of neurosurgery and radiosurgery for epileptogenic CCMs. Methods: We performed a comprehensive search of the Ovid MEDLINE, Web of Science, PubMed, China Biological Medicine and China National Knowledge Infrastructure databases for studies published between January 1994 and October 2019. The search terms were as follows: "epilepsy," "seizures," "brain cavernous hemangioma," "cerebral cavernous malformation," "cerebral cavernous hemangioma," "hemangioma, cavernous, central nervous system." Two researchers independently extracted the data and reviewed all the articles. We compared the advantages and disadvantages of the two treatments. Results: A total of 45 studies were included in our analysis. Overall, the seizure control rate was 79% (95% CI: 75-83%) for neurosurgery and 49% (95% CI: 38-59%) for radiosurgery. In the neurosurgery studies, 4.4% of patients experienced permanent morbidity, while no patients in the radiotherapy studies had permanent morbidity. In addition, the results of subgroup analysis showed that ethnicity, CCMs location and average lesion number are likely significant factors influencing the seizure outcome following treatment. Conclusions: The epilepsy control rate after neurosurgery was higher than that after radiosurgery, but neurosurgery also had a relatively higher rate of permanent morbidity.

Background: Brainstem cavernous malformations (BSCMs) are a subset of cerebral cavernous malformations with precarious locations and potentially devastating clinical courses. The effects and outcomes of treating BSCMs by microsurgery or gamma knife radiosurgery (GKRS) vary across studies.Methods: We searched the Medline, Web of Science, The Cochrane Library, PubMed, and China Biology Medicine disc databases for original articles published in peer-reviewed journals of cohort studies reporting on 20 or more patients of any age with BSCMs with at least 80% completeness of follow-up.Results: We included 43 cohorts involving 2,492 patients. Both microsurgery (RR = 0.04, 95% CI 0.01–0.16, P < 0.01) and GKRS (RR = 0.11, 95% CI 0.08–0.16, P < 0.01) demonstrated great efficacy in reducing the rehemorrhage rate after treatment for BSCMs. The incidence rates of composite outcomes were 19.8 (95% CI 16.8–22.8) and 15.7 (95% CI 11.7–19.6) after neurosurgery and radiosurgery, respectively. In addition, we found statistically significant differences in the median numbers of patients between neurosurgical and radiosurgical cohorts in terms of symptomatic intracranial hemorrhage (ICH; neurosurgical cohorts: median 0, range 0–33; radiosurgical cohorts: median 4, range 1–14; P < 0.05) and persistent focal neurological deficit (FND; neurosurgical cohorts: median 5, range 0–140; radiosurgical cohorts: median 1, range 0–3; P < 0.05).Conclusions: The reported effects of treating BSCMs by microsurgery or GKRS are favorable for reducing recurrent hemorrhage from BSCMs. Patients in the neurosurgery cohort had a lower incidence of symptomatic ICH, while patients in the radiosurgical cohort had a lower incidence of persistent FND.

Background: Glioma is the most common primary tumor of the central nervous system with a high lethality rate. This study aims to mine fibroblast-related genes with prognostic value and construct a corresponding prognostic model. Methods: A glioma-related TCGA (The Cancer Genome Atlas) cohort and a CGGA (Chinese Glioma Genome Atlas) cohort were incorporated into this study. Variance expression profiling was executed via the “limma” R package. The “clusterProfiler” R package was applied to perform a GO (Gene Ontology) analysis. The Kaplan–Meier (K–M) curve, LASSO regression analysis, and Cox analyses were implemented to determine the prognostic genes. A fibroblast-related risk model was created and affirmed by independent cohorts. We derived enriched pathways between the fibroblast-related high- and low-risk subgroups using gene set variation analysis (GSEA). The immune infiltration cell and the stromal cell were calculated using the microenvironment cell populations-counter (MCP-counter) method, and the immunotherapy response was assessed with the SubMap algorithm. The chemotherapy sensitivity was estimated using the “pRRophetic” R package. Results: A total of 93 differentially expressed fibroblast-related genes (DEFRGs) were uncovered in glioma. Seven prognostic genes were filtered out to create a fibroblast-related gene signature in the TCGA-glioma cohort training set. We then affirmed the fibroblast-related risk model via TCGA-glioma cohort and CGGA-glioma cohort testing sets. The Cox regression analysis proved that the fibroblast-related risk score was an independent prognostic predictor in prediction of the overall survival of glioma patients. The fibroblast-related gene signature revealed by the GSEA was applicable to the immune-relevant pathways. The MCP-counter algorithm results pointed to significant distinctions in the tumor microenvironment between fibroblast-related high- and low-risk subgroups. The SubMap analysis proved that the fibroblast-related risk score could predict the clinical sensitivity of immunotherapy. The chemotherapy sensitivity analysis indicated that low-risk patients were more sensitive to multiple chemotherapeutic drugs. Conclusion: Our study identified prognostic fibroblast-related genes and generated a novel risk signature that could evaluate the prognosis of glioma and offer a theoretical basis for clinical glioma therapy.