NTU Makes Breakthrough for Breast Cancer Diagnosis
Jun 27, 2020

Breast cancer is one of the most commonly diagnosed female cancers in Taiwan, as well as one of the leading causes of female cancer deaths. Certainly, early detection and diagnosis are critical to improving breast cancer treatment outcomes and patient survival rates. Conventional screening procedures include a clinical breast exam, breast ultrasound, diagnostic mammogram, and magnetic resonance imaging (MRI), as well as biopsies, such as fine-needle aspiration or core biopsy, that are performed to determine whether the removed tissue sample indicates benign or malignant. This process is time-consuming and prone to biased interpretation. In the case of National Taiwan University Hospital (NTUH), patients might have to wait for 1-2 weeks before receiving a definite diagnosis. Research has shown that longer waiting time not only results in heavy psychological burden on the patients but is associated with poorer prognosis.

To tackle this problem, Prof. Cheng-Chih Hsu’s research group at NTU’s Department of Chemistry collaborated with Dr. Ming-Yang Wang of NTUH in developing a rapid, sensitive breast cancer diagnosis tool called PSI-FAIMS-MS platform, which can be performed within five minutes. The new platform utilizes paper spray ionization-mass spectrometry (PSI-MS) with field asymmetric waveform ion mobility spectrometry (FAIMS) to obtain the predictive metabolic and lipidomic profile from breast core needle biopsies. By combining a machine learning algorithm with pathological examination reports, the team developed a classification model that can successfully identify malignant breast tumors with an overall accuracy of 87.5%.

This diagnosis platform is more efficient and simpler to operate than conventional approaches; the entire process, including the chemical profiling of core needles biopsies, sample preparation, data acquisition, and tissue typing, can be carried out in the same operating room within several minutes. As a larger mass spectrometric dataset is built from clinical samples, the PSI-FAIMS-MS platform will be able to provide fast, cost-effective, and smart point-of-care testing (POCT) in clinics in the future. The team’s work was accepted for publication and selected for the front cover of Analytical Chemistry of the January 21, 2020 issue. For the full text, please scan the QR code.

SOURCE / National Taiwan University