Metabolomics & Cancer Biomarkers

Renal cell carcinoma (RCC) is a common and aggressive form of kidney cancer, often diagnosed at advanced stages due to the lack of early symptoms. This project aims to improve RCC diagnosis by identifying metabolic biomarkers through a multiomics approach, integrating metabolomics and transcriptomics data.

Using advanced mass spectrometry (LC-MS) and computational tools like CAT Bridge, we will explore gene–metabolite interactions to uncover key regulatory pathways in RCC progression. By treating cancer staging as a progression model, we seek to establish causal links between genetic changes and metabolic alterations. This research will contribute to early detection, personalized treatment strategies, and non-invasive diagnostics, ultimately enhancing patient outcomes.

Through collaboration between Chang Gung University in Taiwan and the University of Alberta in Canada, this project combines cutting-edge analytical techniques and computational models to advance biomarker discovery and precision medicine in RCC research.

Faculty Supervisor:

Liang Li

Student:

Partner:

Chang Gung University

Discipline:

Life Sciences

Sector:

Artificial Intelligence; Health and Related Sciences & Technology

University:

University of Alberta

Program: