Multiple Myeloma (MM) is a plasma cell disorder characterized by bone marrow infiltration with clonal plasma cells, which secrete monoclonal immunoglobulin detectable in serum and/or urine. The development of novel targeted therapies has markedly improved the response rate and survival outcome, but MM remains incurable. While novel agents have improved treatment outcomes, identification of biomarkers that will facilitate clinicians in determining which treatment is optimum is a crucial area in the clinical management of MM. Quantitative measurement of cellular proteins from malignant plasma cells or cells within the tumour microenvironment are likely to play a significant role for the selection of the most effective therapeutic option. The ability to perform these quantitative measurements on widely available analysis platforms (flow cytometry and protein arrays) is an important consideration so a wide cohort of patients can be evaluated in the future. The availability of predictive biomarkers would be useful in avoiding ineffective treatments, and allow for the administration of alternative regimens which are continuing to be approved for the treatment of MM. In this project, we will combine mass spectrometry-based proteomics analysis together with ex vivo drug response profiles and in vitro cell line experiments to elucidate a best possible accurate phenotype of the resistant sub-clones. These results will yield a theranostic profile of each patient that will then translate into biomarker panels that will predict response to specific anti-myeloma therapeutics. Development and implementation of antibody array and flow cytometry clinical assays will then correlate treatment outcome with biomarker panel predictions. When complete, this project will allow for an iterative adjustment of therapies for patients with MM, one patient at a time, thus providing a personalised medicine approach.
