Heterogeneity in cancer cells and in the tumor microenvironment (TME) is considered to contribute to individual patient's clinical responses to different drugs at different points during therapy. However, there is a paucity of functional assays to analyze the heterogeneity in primary cell drug responses in the presence of patient's unique and varying TME components. Multiple myeloma (MM) is one example of a heterogenous cancer in genetic makeup, clinical manifestations, and therapy responses. To address the need to study cellular events and behaviors of drug-treated primary MM cells ex vivo in real time, we have developed a three-dimensional time-lapse drug sensitivity assay incorporating patient's own cell and soluble TME components and several new technologies. These include Java-based application of transport-of-intensity equation (TIE) on quantitative phase imaging (QPI), coupled with the use of Hoechst 33258, for noise reduction, label-free single-cell identification and robust quantification of cell division and death events, and open source JEX software package for objective image analysis and feasible data management of large timelapse experiments using a desktop computer. This time-lapse assay provides a new platform toward the development of a sensitive diagnostic tool which can model the tumor cell and TME heterogeneity to predict individual patient's therapeutic responses. New Discovery: As patient-to-patient heterogeneity is a fundamental barrier to MM clinical management, the development of this assay embraces heterogeneity to study cell death beyond survival endpoints and the technological advancements within the timelapse provides a quantitative and functional measure of the individual and combined influences of drugs and TME components within specific patient cells.
Label free, quantitative single-cell fate tracking of time-lapse movies
