In recent years, scientists have increasingly proved the potential of urine tests as a promising technique for non-invasive and effective cancer diagnosis. Last year, we wrote about the impressive efficiency of urine tests in detecting lung cancer early on, and now a new study shows that the technology’s diagnosis potential may hold up for brain tumors as well.

Clinical symptoms for brain tumors typically appear only after the disease is well advanced, making early diagnosis tricky and effective treatment more complicated. In an effort to come up with a solution, scientists at Japan’s Nagoya University have recently developed a simple urine test that could detect brain cancers with high accuracy.

Diagnosing diseases with urine tests involves scanning these fluid samples for biomarkers associated with a particular condition. Seeking to enable urine tests to diagnose a larger number of diseases, the Nagoya University team decided to turn to genetic material called microRNA — short strands of non-coding RNA that play an important role in gene expression, and can take on unique forms when produced by cancer cells in the body, reports New Atlas.

In an effort to exploit these properties, the scientists developed a novel device fitted with 100 million zinc oxide nanowires that were able to extract huge amounts of microRNA from urine samples as small as a milliliter in volume.

The team collected samples from patients with brain tumors and a control group of non-cancer patients. After analyzing the samples, the team discovered that many microRNAs derived from brain tumors could be found in the urine in stable conditions.

“Urine-based liquid biopsy hadn’t been fully investigated for patients with brain tumors, because none of the conventional methodologies can extract microRNAs from urine efficiently in terms of varieties and quantities,” says study author Professor Atsushi Natsume. “So, we decided to develop a device capable of doing it.”

The scientists also developed a diagnostic model by analyzing the expression profiles of the collected microRNA. The team then used the model to identify brain cancer patients from the control group with a sensitivity of 100 percent, and specificity of 97 percent.

Source study: ACS Applied Materials & Interfaces — Urinary MicroRNA-Based Diagnostic Model for Central Nervous System Tumors