Urinary MicroRNA-Based Diagnostic Model for Central Nervous System Tumors Using Nanowire Scaffolds

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 massproducible 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.

Automated summary

There is currently a lack of accurate mass screening methods for early detection of central nervous system tumors. Research suggests that liquid biopsy based on urinary microRNAs may be an effective screening method, with high sensitivity and specificity in differentiating patients from noncancer individuals.