Mathematical framework for activity-based biomarkers

Our work examining the use of activity-based biomarkers for early cancer detection has been published in PNAS.

Summary | The discovery of cancer at an early stage improves treatment outcomes, yet cancer detection thresholds based on blood biomarkers shed by small tumors lack predictivity. We develop a mathematical framework to explore the use of activity-based biomarkers for early cancer detection. In contrast to blood biomarkers, activity-based biomarkers rely on the catalytic activity of enzymes to amplify cancer-derived signals. Using a class of activity-based biomarkers called synthetic biomarkers, we comprehensively explore how detection sensitivities depend on probe design, enzymatic activity, and organ physiology, and how they may be precisely tuned to reveal the presence of small tumors in humans.

Kwong PNAS 2015

Proceedings of the National Academy of Sciences: Mathematical framework for activity-based cancer biomarkers

Georgia Tech Petit Institute: Amplifying the signals of cancer