Abstract
Although multiple myeloma is clinically defined as the accumulation of clonal, malignant plasma cells in the bone marrow, the disease shows significant heterogeneity with regard to progression and therapeutic response. It is likely that germline genetic polymorphisms contribute significantly to an individual’s disease course and response. Bank On A CureTM (BOAC) is a collaborative project initiated with the International Myeloma Foundation (IMF) to develop a DNA bank of myeloma patient samples, through international cooperation. As the bank continues to expand, it provides a resource for the development of cooperative partnerships to assess specific clinical trials as well as conglomerate data. In this study, we have combined data from 3 phase III trials: ECOG trial E9486 (VBMCP + cyclophosphamide or interferon); SWOG trial 9321 (VAD induction followed by randomization to PBSC-supported high dose therapy versus standard dose therapy of VBMCP); and the MRC7 trial (comparing conventional chemotherapy [ABCM] with intravenous chemotherapy and high dose melphalan [CVAMP + HDM +PBSCT]). Five single nucleotide polymorphisms were examined based on associations demonstrated in previous individual trials: GSTP1, IL-6, LT-a, TNF-a, and ERCC2 (DNA repair). Patient samples included 412 from E9486, 569 from S9321, and 232 from MRC7 (total=1213). As a combined data set, genotype associations with overall survival did not reach statistical significance, suggesting SNP associations with survival may be therapy specific. One single association that did reach significance in the conglomerate data was TNF-a genotype association with age of disease onset (the high producer variant AA genotype showing a 5 year later age of onset than the AG/GG genotypes, or the overall mean of the trial, age 61 vs 56; p=.03). This is interesting in light of reports suggesting high production of TNF-a is found in myeloma patients and may actually promote myeloma. Yet, high production may also delay disease onset due to its role in other immunologic processes. Additional parameters including genotype associations with bone disease, CR rates, toxicities, and stage are being evaluated and will be presented. Preliminary results show that when SNPs from S9321 were included in a linear regression model, genotype risk groups could be identified; showing 73% correct association with ISS stage 1, and 75% correct association with ISS stage 3. This model, however, was not validated in the E9486 trial, with less than 50% genotype predictive ISS stage association. A number of highly significant ethnic genotype associations were noted, and are presented in a separate abstract. Given the likely complex interactions of multiple genetic variations, collective genotype comparisons may be required from larger pooled data sets BOAC is assembling to increase significant associations.
Unconventional Anticancer Agents: A Systematic Review of Clinical Trials
