The genetic and transcriptional makeup of Multiple Myeloma is particularly heterogeneous, with several oncogenes routinely mutated and multiple chromosomal aberrations noted in different combinations. The heterogeneous nature of this disease makes it impossible to identify a single cellular model or """"""""ideal"""""""" patient that could be utilized in a drug discovery campaign. To account for patient diversity in characterizing new anti-cancer drugs, a recent trend has been to test compounds on large panels of established cell lines in parallel. These panels provide the necessary genetic breadth and have been shown to be highly informative. However the utility of this powerful approach is limited due to the logistics and complications associated with running many cell line experiments in parallel. The increased number of cell lines multiplies the cost, manpower, and time required to perform these screens. This limits the types of assays that can be performed and also dramatically reduces the numbers of compounds that can be profiled, severely limiting the impact of this approach. In this Phase I SBIR proposal we outline a solution to these problems with the implementation of a novel cell-based assay platform that multiplexes experimental readouts with libraries of cell lines. The proposed assay platform exploits Primity's CellCode multiplexing technology which labels cell populations with unique fluorescent signatures such that multiple cell lines can be combined in a single tube and analyzed simultaneously. Using this technology, panels of up to 40 cell lines can be assayed with multiple end-points from a single sample, dramatically reducing the time and resources required - while simultaneously increasing the amount of information obtained from each cell line. Thus, the successful completion of these studies will establish a novel drug discovery tool for multiple myeloma that accounts for a wide variety of genetic diversity and maintains the throughput necessary for all phases of the drug discovery process.
The genetic heterogeneity within multiple myeloma cancer patient populations poses significant challenges to discovering new medicines, since no single cell line model can encompass the range of variations that naturally occur. The platform technology described in this proposal enables high-throughput assessment of compound activity across diverse, but representative, multiple myeloma cell lines simultaneously. This enables drug discovery for novel compounds that may be selective to specific cancer subtypes and that likely would have been overlooked with current screening technologies.