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A central question in cancer therapy is how individual cells within a population of tumor cells respond to drugs designed to arrest their growth. However, the absolute growth of cells, their change in physical mass, whether cancerous or physiologic, is difficult to measure directly with traditional techniques. Here, we develop live cell interferometry for rapid, real-time quantification of cell mass in cells exposed to a changing environment. We used tunicamycin induction of the unfolded protein stress response in multiple myeloma cells to generate a mass response that was temporally profiled for hundreds of cells simultaneously. Within 2 h, the treated cells were growth suppressed compared to controls, with a few cells in both populations showing a robust increase (+15%) or little change (<5%) in mass accumulation. Overall, live cell interferometry provides a conceptual advance for assessing cell populations to identify, monitor, and measure single cell responses, such as to therapeutic drugs.

Live cell mass profiling is a promising new approach for rapidly quantifying responses to therapeutic agents through picogram-scale changes in cell mass over time. A significant barrier in mass profiling is the inability of existing methods to handle pleomorphic cellular clusters and clumps, which are more commonly present in patient-derived samples or tissue cultures than are isolated single cells. Here we demonstrate automated Live Cell Interferometry (LCI) as a rapid and accurate quantifier of the sensitivity of single cell and colony-forming human breast cancer cell lines to the HER2-directed monoclonal antibody, trastuzumab (Herceptin). The relative sensitivities of small samples (< 500 cells) of four breast cancer cell lines were determined tens-to-hundreds of times faster than is possible with traditional proliferation assays. These LCI advances in clustered sample assessment and speed open up the possibility for therapeutic response testing of patient-derived solid tumor samples, which are viable only for short periods ex vivo and likely to be in the form of cell aggregates and clusters.

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