Cancer is a leading cause of death and disability. Early detection can significantly improve long-term survival in cancer patients. The advent of point-of-care technologies, which are typically based on lab-on-chip tools, enables convenient and real-time healthcare at or near the patient bedside. Development of point-of-care cancer testing can keep the advantages of, but overcome the high cost of, existing expensive genetic analysis methods. It can do so while providing the results promptly to physicians as they seek to customize and improve disease treatment.

The central aim of this thesis is to develop new strategies to detect cancer prior to the spread of cancer cells to the distant organs. Metastasis relies on the release of migratory cancer cells, and is responsible for as much as 90% of cancer associated mortality. The factors that determine the invasiveness of these circulating cells remain poorly defined, and it is difficult to distinguish cancer cells having high versus low metastatic potential. New technologies are required that sort heterogeneous cancer cells into relevant subpopulations, and profile thereby small numbers of cells according to their phenotypes.

Herein we describe a powerful new capability for the monitoring of cancer progression. We developed a novel fluidic chip that selectively isolates rare cancer cells that exhibit different levels of phenotypic surface markers. We show that the device successfully profiles the surface expression of very small numbers of cells;​ and it accomplishes this directly from whole blood. We couple the surface marker profiling approach with a migration platform with single cell resolution:​ this allows us to characterize more deeply, still on-chip, the biological behavior of invasive cancer cells. We deploy these new techniques to reveal the dynamic phenotypes of these rare cells. We prototype the system and prove it out using samples of unprocessed blood from mice. We characterize the samples as a function of tumor growth and aggressiveness and prove that the new profiling technology provides powerful and relevant information that correlates with tumor stage and aggressiveness. The strategies presented offer to guide the development of sensitive and specific approaches for cancer diagnosis that provide new information not available using prior methods.