Monitoring multiple myeloma patients treated with daratumumab: teasing out monoclonal antibody interference.

BACKGROUND: Monoclonal antibodies are promising anti-myeloma treatments. As immunoglobulins, monoclonal antibodies have the potential to be identified by serum protein electrophoresis (SPE) and immunofixation electrophoresis (IFE). Therapeutic antibody interference with standard clinical SPE and IFE can confound the use of these tests for response assessment in clinical trials and disease monitoring. METHODS: To discriminate between endogenous myeloma protein and daratumumab, a daratumumab-specific immunofixation electrophoresis reflex assay (DIRA) was developed using a mouse anti-daratumumab antibody. To evaluate whether anti-daratumumab bound to and shifted the migration pattern of daratumumab, it was spiked into daratumumab-containing serum and resolved by IFE/SPE. The presence (DIRA positive) or absence (DIRA negative) of residual M-protein in daratumumab-treated patient samples was evaluated using predetermined assessment criteria. DIRA was evaluated for specificity, limit of sensitivity, and reproducibility. RESULTS: In all of the tested samples, DIRA distinguished between daratumumab and residual M-protein in commercial serum samples spiked with daratumumab and in daratumumab-treated patient samples. The DIRA limit of sensitivity was 0.2 g/L daratumumab, using spiking experiments. Results from DIRA were reproducible over multiple days, operators, and assays. The anti-daratumumab antibody was highly specific for daratumumab and did not shift endogenous M-protein. CONCLUSIONS: As the treatment of myeloma evolves to incorporate novel monoclonal antibodies, additional solutions will be needed for clinical monitoring of patient responses to therapeutic regimens. In the interim, assays such as DIRA can inform clinical outcomes by distinguishing daratumumab from endogenous M-protein by IFE.

Translation of a tumor microenvironment mimicking 3D tumor growth co-culture assay platform to high-content screening.

For drug discovery, cell-based assays are becoming increasingly complex to mimic more realistically the nature of biological processes and their diversifications in diseases. Multicellular co-cultures embedded in a three-dimensional (3D) matrix have been explored in oncology to more closely approximate the physiology of the human tumor microenvironment. High-content analysis is the ideal technology to characterize these complex biological systems, although running such complex assays at higher throughput is a major endeavor. Here, we report on adapting a 3D tumor co-culture growth assay to automated microscopy, and we compare various imaging platforms (confocal vs. nonconfocal) with correlating automated image analysis solutions to identify optimal conditions and settings for future larger scaled screening campaigns. The optimized protocol has been validated in repeated runs where established anticancer drugs have been evaluated for performance in this innovative assay.