A Simple Urine Test Could Detect Brain Tumors
Complete the form below to unlock access to ALL audio articles.
Researchers in Japan have developed a new device to identify proteins – which are diagnostic biomarkers of brain cancer – in urine. The study is published in ACS Nano.
Brain cancer diagnosis is difficult
Diagnosing brain cancers can prove particularly challenging for clinicians, as tumors are most often discovered after patients start to experience neurological symptoms. These symptoms might include dizziness or headache, which are non-specific and could be indicative of a variety of conditions. As primary caregivers cannot refer all patients presenting with non-specific symptoms for extensive brain imaging, detecting brain cancer early enough for effective treatment isn’t always possible.
The presence of tumor-related extracellular vesicles (EVs) in a patient’s urine is one potential indicator of brain cancer, and is the focus of a new study by researchers at Nagoya University led by Associate Professor Takao Yasui. “Liquid biopsy can be performed using many body fluids, but blood tests are invasive,” he says. “Urine tests are an effective, simple and non-invasive method because the urine contains many informative biomolecules that can be traced back to identify the disease.”
Detecting EVs using one simple procedure
All cells secrete EVs, which are nano-sized vesicles that support the exchange of genetic information and cell-to-cell communication. They are implicated in the maintenance of physiological processes including cell development, growth, differentiation and apoptosis. In brain cancer, research demonstrates that EVs play important roles in the tumor microenvironment, supporting progression of the cancer and angiogenesis.
EVs produced by cancer cells are excreted in the urine without breaking down, making them a potentially useful diagnostic biomarker. However, current detection methods are suboptimal, as Yasui describes: “Currently, EV isolation and detection methods require more than two instruments and an assay to isolate and then detect EVs.”
Yasui and Professor Yoshinobu Baba of Nagoya University’s Graduate School of Engineering – alongside collaborators – created a new analysis platform for brain tumor EVs, by placing nanowires at the bottom of a well plate. “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,” the authors describe.
Microscopic image of nanowires. Credit: Dr Takao Yasui.
“The all-in-one nanowire assay can isolate and detect EVs using one simple procedure. In the future, users can run samples through our assay and change the detection part, by selectively modifying it to detect specific membrane proteins or miRNAs inside EVs to detect other types of cancer,” Yasui adds.
The research team captured and analyzed cell-derived EVs, brain tumor organoid-derived EVs and urine samples from glioblastoma patients and non-cancer subjects. Using their device, they were able to identify two types of EV membrane proteins – CD31 and CD63 – from the urine samples of brain tumor patients.
“The all-in-one nanowire assay can isolate and detect EVs using one simple procedure. In the future, users can run samples through our assay and change the detection part, by selectively modifying it to detect specific membrane proteins or miRNAs inside EVs to detect other types of cancer. Using this platform, we expect to advance the analysis of the expression levels of specific membrane proteins in patients’ urinary EVs, which will enable the early detection of different types of cancer,” concludes Yasui.
Reference: Chattrairat K, Yasui T, Suzuki S, et al. All-in-one nanowire assay system for capture and analysis of extracellular vesicles from an ex vivo brain tumor model. ACS Nano. 2023. doi: 10.1021/acsnano.2c08526.
This article is a rework of a press release issued by the Nagoya University. Material has been edited for length and content.