There are no accurate mass screening methods for early detection of central nervous system (CNS) tumors. Recently, liquid biopsy has received a lot of attention for less-invasive cancer screening. Unlike other cancers, CNS tumors require efforts to find biomarkers due to the blood–brain barrier, which restricts molecular exchange between the parenchyma and blood. Additionally, because a satisfactory way to collect urinary biomarkers is lacking, urine-based liquid biopsy has not been fully investigated despite the fact that it has some advantages compared to blood or cerebrospinal fluid-based biopsy. Here, we have developed a mass-producible and sterilizable nanowire-based device that can extract urinary microRNAs efficiently. Urinary microRNAs from patients with CNS tumors (n = 119) and noncancer individuals (n = 100) were analyzed using a microarray to yield comprehensive microRNA expression profiles. To clarify the origin of urinary microRNAs of patients with CNS tumors, glioblastoma organoids were generated. Glioblastoma organoid-derived differentially expressed microRNAs (DEMs) included 73.4% of the DEMs in urine of patients with parental tumors but included only 3.9% of those in urine of noncancer individuals, which suggested that many CNS tumor-derived microRNAs could be identified in urine directly. We constructed the diagnostic model based on the expression of the selected microRNAs and found that it was able to differentiate patients and noncancer individuals at a sensitivity and specificity of 100 and 97%, respectively, in an independent dataset. Our findings demonstrate that urinary microRNAs extracted with the nanowire device offer a well-fitted strategy for mass screening of CNS tumors.

Extracellular vesicles (EVs) have promising potential as biomarkers for early cancer diagnosis. The EVs have been widely studied as biological cargo containing essential biological information not only from inside vesicles such as nucleic acids and proteins but also from outside vesicles such as membrane proteins and glycolipids. Although various methods have been developed to isolate EVs with high yields such as captures based on density, size, and immunoaffinity, different measurement systems are needed to analyze EVs after isolation, and a platform that enables all-in-one analysis of EVs from capture to detection in multiple samples is desired. Since a nanowire-based approach has shown an effective capability for capturing EVs via surface charge interaction compared to other conventional methods, here, we upgraded the conventional well plate assay to an all-in-one nanowire-integrated well plate assay system (i.e., a nanowire assay system) that enables charge-based EV capture and EV analysis of membrane proteins. We applied the nanowire assay system to analyze EVs from brain tumor organoids in which tumor environments, including vascular formations, were reconstructed, and we found that the membrane protein expression ratio of CD31/CD63 was 1.42-fold higher in the tumor organoid-derived EVs with a p-value less than 0.05. Furthermore, this ratio for urine samples from glioblastoma patients was 2.25-fold higher than that from noncancer subjects with a p-value less than 0.05 as well. Our results demonstrated that the conventional well plate method integrated with the nanowire-based EV capture approach allows users not only to capture EVs effectively but also to analyze them in one assay system. We anticipate that the all-in-one nanowire assay system will be a powerful tool for elucidating EV-mediated tumor-microenvironment crosstalk.

The transcriptome analysis of injured Xenopus laevis tadpole and mice suggested that Neurod4L.S., a basic-helix-loop-helix transcription factor, was the most promising transcription factor to exert neuroregeneration after spinal cord injury (SCI) in mammals. We generated a pseudotyped retroviral vector with the neurotropic lymphocytic choriomeningitis virus (LCMV) envelope to deliver murine Neurod4 to mice undergoing SCI. SCI induced ependymal cells to neural stem cells (NSCs) in the central canal. The LCMV envelope-based pseudotypedvector preferentially introduced Neurod4 into activated NSCs, which converted to neurons with axonal regrowth and suppressed the scar-forming glial lineage. Neurod4-induced inhibitory neurons predominantly projected to the subsynaptic domains of motor neurons at the epicenter, and Neurod4-induced excitatory neurons predominantly projected to subsynaptic domains of motor neurons caudal to the injury site suggesting the formation of functional synapses. Thus, Neurod4 is a potential therapeutic factor that can improve anatomical and functional recovery after SCI.

Isocitrate dehydrogenase-mutant low-grade gliomas (IDHmut-LGG) grow slowly but frequently undergo malignant transformation, which eventually leads to premature death. Chemotherapy and radiotherapy treatments prolong survival, but can also induce genetic (or epigenetic) alterations involved in transformation. Here, we developed a mathematical model of tumor progression based on serial tumor volume data and treatment history of 276 IDHmut-LGGs classified by chromosome 1p/19q codeletion (IDHmut/1p19qcodel and IDHmut/1p19qnoncodel) and performed genome-wide mutational analyses, including targeted sequencing and longitudinal whole-exome sequencing data. These analyses showed that tumor mutational burden correlated positively with malignant transformation rate, and chemotherapy and radiotherapy significantly suppressed tumor growth but increased malignant transformation rate per cell by 1.8 to 2.8 times compared with before treatment. This model revealed that prompt adjuvant chemoradiotherapy prolonged malignant transformation-free survival in small IDHmut-LGGs (≤ 50 cm3). Furthermore, optimal treatment differed according to genetic alterations for large IDHmut-LGGs (> 50 cm3); adjuvant therapies delayed malignant transformation in IDHmut/1p19qnoncodel but often accelerated it in IDHmut/1p19qcodel. Notably, PI3K mutation was not associated with malignant transformation but increased net postoperative proliferation rate and decreased malignant transformation-free survival, prompting the need for adjuvant therapy in IDHmut/1p19qcodel. Overall, this model uncovered therapeutic strategies that could prevent malignant transformation and, consequently, improve overall survival in patients with IDHmut-LGGs.Significance: A mathematical model successfully estimates malignant transformation-free survival and reveals a link between genetic alterations and progression, identifying precision medicine approaches for optimal treatment of IDH-mutant low-grade gliomas.