Search

Refereed/Peer-reviewed The introduction of the proteasome inhibitor bortezomib into treatment regimens for myeloma has led to substantial improvement in patient survival. However, whilst bortezomib elicits initial responses in many myeloma patients, this haematological malignancy remains incurable due to the development of acquired bortezomib resistance. With other patients presenting with disease that is intrinsically bortezomib resistant, it is clear that new therapeutic approaches are desperately required to target bortezomib-resistant myeloma. We have previously shown that targeting sphingolipid metabolism with the sphingosine kinase 2 (SK2) inhibitor K145 in combination with bortezomib induces synergistic death of bortezomib-naive myeloma. In the current study, we have demonstrated that targeting sphingolipid metabolism with K145 synergises with bortezomib and effectively resensitises bortezomib-resistant myeloma to this proteasome inhibitor Notably, these effects were dependent on enhanced activation of the unfolded protein response, and were observed in numerous separate myeloma models that appear to have different mechanisms of bortezomib resistance, including a new bortezomib-resistant myeloma model we describe which possesses a clinically relevant proteasome mutation. Furthermore, K145 also displayed synergy with the next-generation proteasome inhibitor carfilzomib in bortezomib-resistant and carfilzomib-resistant myeloma cells. Together, these findings indicate that targeting sphingolipid metabolism via SK2 inhibition may be effective in combination with a broad spectrum of proteasome inhibitors in the proteasome inhibitor resistant setting, and is an approach worth clinical exploration.

Homology modelling has become a useful tool for the prediction of protein structure when only sequence data are available. Structural information is often more valuable than sequence alone for determining protein function. Homology modelling is potentially a very useful tool for the mycologist, as the number of fungal gene sequences available has exploded in recent years, whilst the number of experimentally determined fungal protein structures remains low. Programs available for homology modelling utilise different approaches and methods to produce the final model. Within each step of the homology modelling process, many factors affect the quality of the model produced, and appropriate selection of the program can significantly improve the quality of the model. This review discusses the advantages and limitations of the currently available methods and programs and provides a starting point for novices wishing to create a structural model. We have taken a practical approach as we hope to enable any scientist to utilise homology modelling as a tool for the analysis of their protein, or genome, of interest.