Each cancer case is unique and cancer patients often fail to respond to standard therapeutic options. In such cases our clinical DSRT (cDSRT) assay can help doctors to identify the most effective therapy for each particular patient or save them from the hurdles of inefficient therapies.
In a standard cDSRT assay, cancer cells taken directly from a patient are purified and placed in multi-well plates, where each well contains one of 528 clinically approved or experimental cancer drugs at one of five different concentrations. Cell viability is measured after 72 hours and based on this the most potent drugs are identified. The method has been extensively validated and described in peer-reviewed journals (e.g. Pemovska T. et al. 2013; Pemovska T. et al. 2015; Malani et al., 2022).
Here is a typical workflow for DSRT:
In the classical DSRT all cells in a well are evaluated as a single unit. We commonly evaluate cell viability by adding CellToxGreen reagent (Promega) at the time of cell seeding, which makes dying cells fluoresce in the green channel. In addition, at the end of the incubation period CellTiter Glow reagent (Promega) is added, which lyses all cells and releases cellular ATP leading to emitting luminescence signal proportional to the number of metabolically active (live) cells.
In addition to the classical DSRT, our high throughput flow cytometry-based DSRT allows to evaluate drug responses at the population level. Here each cell in each well produces a data point for each marker/antibody. This is particularly useful for mixed cell populations such as blood. Find out more about FIMM flow DSRT here.
The chart below illustrates the differences between the classical and flow-based DSRT
Pharmaceutical companies have the option to use the DSRT assay to test their drug candidates on the same cancer cells from patients that we use for cDSRT, as described earlier. This approach may serve as a surrogate for clinical trials. The use of stored samples is also allowed. In this situation, pharmaceutical companies can evaluate the effects of their drug candidates on real patient samples and compare their drugs with other drugs from our oncology collection.
Academic researchers can use DSRT in several ways: