Presentation description

Multiple myeloma (MM) is a malignancy of plasma cells and one of the more common|hematological malignancies (6.3/100,000 new cases/year). Although treatments have improved,|most patients fail their first line of treatment and ultimately do not survive beyond 5 years.|Identifying patients at high-risk of failing treatment early is a critical need. SPECTRA is a|statistical technique developed by the Camp Lab to characterize global gene expression (the|transcriptome) by representing it as multiple quantitative tumor variables. Spectra variables|allow gene expression to be incorporated in predictive modeling to identify high-risk groups.|| Transcriptome data for myeloma cells was available from 768 patients in the international|CoMMpass study and 39 spectra variables were derived. Each patient has a value for each of the|39 variables (their spectra ""barcode""); patients can be compared for each bar in the barcode.|Predictive modeling using spectra variables was successful in identifying risk groups for time to|treatment failure, such that a patient's tumor transcriptome can be used predict whether they are|at high-risk to have their treatment fail earlier.|| To replicate the CoMMpass data findings, we are collecting and processing local biological|samples from MM patients at the Huntsman Cancer Hospital. We collect bone marrow which is|cell-sorted to identify tumor (CD138+) cells. RNA is extracted from these cells and sequenced to|generate transcriptome data. Then the spectra barcode is calculated.|| The SPECTRA technique provides a more complete understanding of MM by better|characterizing the tumor. Each spectra is a tumor characteristic. Our future research includes|investigation of whether inherited variations (in normal DNA from saliva or whole blood) are|associated with the transcriptome risk score. We are also pursuing the SPECTRA technique in|several other cancers.