Objective: The purpose of the present retrospective study was to describe the epidemiology of nervous system tumors in children based on the clinical data obtained from a neurosurgical center in Beijing. Patients and Methods: During a 5-year period, from January 2001 to December 2005, 1,485 primary brain and spinal tumors in children up to 17 years of age were diagnosed histopathologically according to the World Health Organization 2000 nervous system tumor classification. The sex predilection, tumor location, and histological grade in relation to age were investigated, and the epidemiological characteristics of the 5 most common brain tumors are discussed. Result: Of the 1,485 cases evaluated, brain and spinal tumors comprised 92.3% (1,371) and 7.7% (114), respectively, with a predominance of low-grade tumors (65.1 and 78.9% for brain and spinal cord, respectively). For all tumors, the overall sex ratio (male to female) was 1.6:1. 61.9% of the brain tumors were supratentorial, whereas an infratentorial location was slightly more common in the 872 brain tumors of neuroepithelial tissue (53.7%). The 5 most common brain tumors were astrocytic tumors (30.5%), craniopharyngiomas (18.4%), medulloblastomas (14.6%), germ cell tumors (GCTs, 7.9%) and ependymal tumors (5.6%). The highest preponderance of boys was observed in GCTs followed by medulloblastomas. The most common types of spinal tumors were ependymal tumors (19.3%), neurilemmomas (16.7%) and astrocytomas (14.9%). Conclusions: Based on a large hospital series of pediatric patients, the present survey revealed the histopathological diversity of childhood neurological neoplasms, and provides a reliable profile of the epidemiology of nervous system tumors in children in a developing country.

Our study highlighted that an MRI-based radiomics signature can effectively identify the 1p/19q co-deletion in histopathologically diagnosed lower-grade gliomas, thereby offering the potential to facilitate non-invasive molecular subtype prediction of gliomas.

Background Pituitary neuroendocrine tumors (PitNETs) are the second most common intracranial tumor. We lacked a comprehensive understanding of the pathogenesis and heterogeneity of these tumors. Methods We performed high-precision single-cell RNA sequencing for 2679 individual cells obtained from 23 surgically resected samples of the major subtypes of PitNETs from 21 patients. We also performed single-cell multi-omics sequencing for 238 cells from 5 patients. Results Unsupervised clustering analysis distinguished all tumor subtypes, which was in accordance with the classification based on immunohistochemistry and provided additional information. We identified 3 normal endocrine cell types: somatotrophs, lactotrophs, and gonadotrophs. Comparisons of tumor and matched normal cells showed that differentially expressed genes of gonadotroph tumors were predominantly downregulated, while those of somatotroph and lactotroph tumors were mainly upregulated. We identified novel tumor-related genes, such as AMIGO2, ZFP36, BTG1, and DLG5. Tumors expressing multiple hormone genes showed little transcriptomic heterogeneity. Furthermore, single-cell multi-omics analysis demonstrated that the tumor had a relatively uniform pattern of genome with slight heterogeneity in copy number variations. Conclusions Our single-cell transcriptome and single-cell multi-omics analyses provide novel insights into the characteristics and heterogeneity of these complex neoplasms for the identification of biomarkers and therapeutic targets.