Gene expression signatures of conventional prognostic factors in multiple myeloma

Abstract

6606 Background: Recent advances in Multiple Myeloma have led to identification of novel therapeutic targets and new agents highlighting the need for patient specific treatment plans. We have initiated molecular studies of MM plasma cells (PC) to correlate conventional prognostic factors with the genomic signature of MM PCs. Factors with high discriminatory value will allow clinicians to tailor therapy to the patient, decreasing toxicity and improving outcome. Methods: Gene expression profiling was performed on CD138 sorted PCs from 14 pts with newly diagnosed MM using the Affymetrix U133A platform. The data was analyzed using dChip software (V1.3). Results: We have identified differentially expressed genes with biological relevance that correlates with the important prognostic factors; plasma cell labeling index (PCLI), circulating PCs, LDH and β2 microglobulin. High PCLI was associated with upregulation of growth and proliferation related genes (IGFBP-7, WHSC1 [mapped to 4p16 and correlated with t(4;14)], TIMP1 [related with STAT3 phosphorylation] and down regulation of wnt5a, CD79a (MB1, member of Ig superfamily gene), NEDD9 (associated with β1 integrin signaling), BCR1 (B cell receptor signaling) and Lysosomal associated multispanning membrane protein 5 (described in MM progression). Increased number of circulating PCs was associated with modulation of adhesion-related and migration associated genes such as CD86, metastasis associated protein S100A4, galectin-1 (associated with β1 integrin), hsp27, glucosamine-6-sulfatase, NCAM1, and cyclin D1, among others. Similar analyses performed grouping patients according to LDH, β2 microglobulin also revealed differentially expressed genes that may have correlative significance.Conclusions: Identification of differentially expressed genes that correlates with MM-related prognostic factors can help understand the biological basis for these factors. Additionally, identification of non-overlapping discriminatory genes for individual prognostic factors can lead to development of focused arrays that can be used clinically for prognostication. Ongoing studies with additional patients as well as in vitro studies are underway to validate these results. No significant financial relationships to disclose.