The MMprofiler

Multiple Myeloma (MM) is cancer of plasma cells, a type of white blood cells. These tumors generally develop in the bone marrow and lead to a mortality rate of 50% to 90%, depending on their stage. During the last decade, the clinical management of patients with MM has changed considerably. At present, the majority of patients with advanced stages of the disease are now being treated with high-dose chemotherapy and subsequent bone marrow transplantation. Over 50% of MM patients respond well to this approach and remain in remission for years. Furthermore, novel targeted drug therapies offer new opportunities to treat patients with this disease.

Compared to the extensive range of diagnostic tests offered to patients of e.g. leukemia, the diagnostic arsenal for MM patients remains rather limited. Primarily, standard microscopic evaluation and cytogenetic analysis are deployed. However, gene expression profiling studies have already proven substantial molecular differences in MM subtypes. Such differences can form the basis of improved and more accurate diagnostics of this disease.

In collaboration with several pharmaceutical companies and the Erasmus Medical Center in Rotterdam, Skyline measured the genome-wide gene expression profiles of hundreds of MM patients. Analysis of these results revealed clear gene signatures, which are developed by Skyline into a new Profiler: the MMprofiler.

The MMprofiler is anticipated to come with these features:
•    Prediction of side effects of one of the new major drugs in MM treatment. Likelihood of occurrence is crucial for effective patient management, as this is a frequent side effect which can be severely health compromising. By making use of highly discriminating single nucleotide polymorphisms (SNPs), the MMprofiler will become a valuable tool in drug selection for MM patients.

•    Prediction of drug responsiveness for the mentioned drug. Drug efficacy can be significantly enhanced, if potential responders and non-responders can be discriminated by gene signatures. Consequently, use of the Profiler will have direct impact on overall MM patient health.

•    In analogy with the AMLprofiler, specific classes of MM will be distinguished on basis of gene signatures. Prognostic meaning of these classes will be determined, which will empower the MMprofiler as a prognostic tool.