Using Blood Biomarkers to Aid App-Based Cancer Monitoring

ASPIRE Award (2019-2022)

James Heath, PhD, Institute for Systems Biology

James Heath, PhD

Smart, wearable devices and corresponding health-tracking apps can monitor patients at risk for developing cancer on a nearly continuous basis. They can detect subtle changes in health-related measures such as sleep quality, cognition, and heart rate before they are noticeable to either patients or clinicians. Currently, the connections between data collected by smart technologies and molecular markers of patient health and physiology have not been established, yet the combination of both types of patient information could lead to more precise tracking of patients’ disease trajectories. The Heath lab is conducting extensive analyses of biomarkers in blood samples from 100 patients with central nervous system (CNS) cancers who are being monitored for disease recurrence using wearable devices and health apps in a Mark Foundation-funded clinical trial set up by Stephen Friend and colleagues at the non-profit research organization 4YouandMe. Anna Goldenberg and colleagues at the University of Toronto will use computational methods to uncover the relationships among the multi-variate aspects of these data types. This effort will allow the team to calibrate data produced by the wearable devices and health apps and correlate it with known features that inform on patient health. The Heath lab will measure blood serum levels of 200 known cancer-marker proteins at four different time-points starting prior to surgical removal of the tumors followed up by an additional three measurements over the course of the clinical study. If any data from these serum measurements, the wearable technology data, or clinical observations are consistent with disease recurrence, the researchers will follow up with to perform tests that will measure different neurological biomarkers, detect immune cell activation, and/or analyze genetic material circulating in the bloodstream. The team is also developing methods to account for other health concerns that might influence interpretation of either the biomarker or health monitoring data. This research will pave the way for smart technology to be used as a stand-alone tool for early screening and disease monitoring in patients with CNS cancers.