Predicting Carfilzomib Resistance Mechanisms and Therapeutics Using Computational Modelling of Genomics and Proteomics

 Multiple myeloma (MM) is a malignancy of plasma cells accounting for around 10% of all hematologic cancers. MM is an incurable heterogeneous malignancy which impacts the response rate due to complex nature of the disease. Although with standard of care treatment, including proteasome inhibitors (PI), a significant response and remission is achieved, the majority of patients still develops resistance. There is no precise method for determining the pathways which govern the acquired resistance to PI. Computational biology modelling (CBM), which uses genomics for creating the MM specific disease characteristics, can be used for deciphering the dominance of signaling changes in acquired resistance and accordingly select right treatment combination. Predicting a priori treatment response based on disease characteristics would enable optimal treatment selection and potentially reduce the trial and error approach that impacts outcome and health care costs.

Blood Journal 2018