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Spit Test Detects Breast Cancer in Five Seconds

By LabMedica International staff writers
Posted on 19 Feb 2024

Breast cancer is the most commonly diagnosed cancer worldwide, with over 2.3 million new cases and approximately 685,000 deaths reported in 2020. Currently, mammography, ultrasound, MRI, and biopsies are the primary methods for diagnosing breast cancer. Despite their effectiveness, these techniques have several drawbacks, such as high costs, limited accessibility, potential inaccuracies in early detection in young women with dense breast tissue, invasiveness, and radiation exposure risks, especially for radiation-sensitive patients. Given the increasing prevalence of breast cancer in women, there is an urgent need for more innovative and efficient detection methods. Now, a saliva test that screens for breast cancer is showing promising results in experimental testing.

Developed collaboratively by researchers from the University of Florida (Gainesville, FL, USA) and National Yang Ming Chiao Tung University (Hsinchu City, Taiwan), this innovative hand-held device can detect breast cancer biomarkers using just a small saliva sample. The device operates by applying saliva to a test strip treated with specific antibodies that react to cancer biomarkers. It then sends electrical impulses to contact points on the biosensor, measuring signals that are converted into digital data, indicating the level of biomarkers present. This method provides rapid and easily interpretable results.


Image: Breast cancer could now be detected through a spit test (Photo courtesy of 123RF)
Image: Breast cancer could now be detected through a spit test (Photo courtesy of 123RF)

In trials, the device successfully differentiated between healthy breast tissue, early-stage breast cancer, and advanced breast cancer in a group of 21 women. The non-invasive test could be completed in less than a minute, including the application of a 3–5 μl saliva sample onto the strip, with each test performed 10 times within 15 milliseconds. The design of this biosensor incorporates common elements like glucose testing strips and the Arduino open-source hardware-software platform, making it user-friendly and promising for broad public use in the future.

Related Links:
University of Florida 
Yang Ming Chiao Tung University 


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