The Pq Laboratory of BiomeDx/Rx

Dx to Rx: The Key to Advancing Precision Medicine

Our research is focused on Translational Medicine. Through working at the interface of medicine, material, and engineering our interdisciplinary team aims to develop groundbreaking technologies for the detection of biofluid biomarkers and drug delivery. Ultimately, we hope that by working in close partnership with medical practitioners, these techniques can be implemented in clinical practice. On the other hand, leveraging clinical data mining we are interested in exploring, identifying, and validating potential biomarkers for disease diagnosis and therapy. We will further bring them back to the patient's bedside to improve outcomes. Currently, our team focuses on  lung cancer early diagnosis, treatment monitoring, and drug delivery systems.

Lung Cancer Diagnosis

Drug Delivery Nanocarriers

EVs have also been exploited as drug delivery nanocarriers. EVs as a natural delivery system can evade phagocytosis, have extended blood half-life, and exhibit optimal biocompatibility. Moreover, the small size of EVs facilitates their extravasation, translocation through physical barriers, and passage through the extracellular matrix. Recently, we developed engineered EVs which can specifically bind to receptors on tumor cell membranes and then deliver drugs to the cytosol via highly efficient membrane fusion. On the other hand, we developed chimeric nanobodies that can spontaneously assemble into lipid bilayers and form cancer-targeting liposomes in one step. This new technology shows promise for industrial manufacturing and clinical translation.

​Extracellular vesicles (EVs) are lipid bilayer-enclosed vesicles with sub-micrometer size that are released by cells. EVs contain a tissue-specific signature wherein a variety of proteins and nucleic acids are selectively packaged. Incontestably, growing evidence has shown important biological roles and clinical relevance of EVs in cancers. In particular, recent studies validate that EV can be used for non-invasive repetitive cancer (early) diagnostics, staging, and treatment monitoring. Currently, we are investigating the role of EV-DNA in early diagnosis of malignant pulmonary nodule (MPN). To further provide a more powerful diagnostic strategy for patients with MPN, a deep learning-based diagnostic system is under development, which can quickly raise a red flag on patients with high risk of MPN. Subsequently, physicians would recommend these patients take EV-based liquid biopsy. The combination of medical imaging and molecular detection would significantly improve diagnostic accuracy of MPN with a two-day turnaround time. In contrast, a definitive diagnosis of MSPN generally takes 3 to 12 months, and it heavily relies on follow-up CT scans. The other ongoing project is focusing on EV-based treatment monitoring of patients with advanced lung cancer. The ultimate goal is to develop a point-of-care device for patients, allowing them to monitoring targetable mutations at home.