Abstract
Exosome-mediated processes are increasingly being implicated in the pathobiology of many forms of solid tumors and hematologic malignancies. In the case of blood cancers, an oncogenic role for exosomes has been demonstrated for multiple myeloma (MM). An increased understanding of the abundance and disease association of extra-cellular microRNAs in particular, may lead to opportinities to improve early detection and management of MM and precursor conditions.
We performed microRNA profiling of cell-free bone marrow aspirate plasma on a series of 100 patients with diagnoses of MGUS, active multiple myeloma or relapsed multiple myeloma. The microRNA profiles were compared between disease status groups and also individually with each patient’s routine MyPRS results (ie. GEP70 high/low risk and molecular subtype gene signatures), generated from their malignant CD138+ plasma cells1. MicroRNAs with patterns of expression associated with these clinically validated genomic (mRNA) signatures were investigated to determine if they (i) were known regulators of the genes used in MyPRS and (ii) in a cross-validated analysis, were able to predict the patients MyPRS risk group and molecular subtype.
An additional series of paired peripheral blood and bone marrow aspirates (isolated CD138+ plasma cells) were also microRNA and MyPRS profiled, to further investigate the role and potential clinical utility of extracellular microRNAs in multiple myeloma. Results will be presented which describe the abundance of individual microRNA's in realtion to disease status, including microRNA's previously linked to the regulation of mRNA's contained in the GEP70 signature.
The ability to predict MGUS progression risk or active myeloma prognosis using molecular signatures in peripheral blood may increase access to, and adoption of, genomic technologies in the diagnosis and management of these related conditions.
Reference:
[1] van Laar R, Flinchum R, Brown N, et al. Translating a gene expression signature for multiple myeloma prognosis into a robust high-throughput assay for clinical use. BMC Medical Genomics. 2014;7(1):25.
Van Laar:Signal Genetics: Employment, Equity Ownership. Flinchum:Signal Genetics: Employment. Nathan:Signal Genetics: Employment. Ramsey:Signal Genetics: Employment. Shaughnessy:Signal Genetics: Consultancy.
Author notes
Asterisk with author names denotes non-ASH members.
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