P975: THREE-DIMENSIONAL TELOMERE PROFILING PREDICTS RISK OF RELAPSE IN NEWLY DIAGNOSED MULTIPLE MYELOMA PATIENTS

Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: Multiple myeloma (MM) is a challenging and potentially deadly blood cancer that involves plasma cells. It is the second most common blood cancer with an incidence of approximately 35,000 new cases per year in the US, and 180,000 additional patients receiving treatment at any given time. Although the introduction of new generation therapy, including targeted immunotherapy, has increased the median survival rate to over 5 years, MM is still considered incurable due to the significant heterogeneity of the disease from patient to patient. MM treatment includes various combinations of drugs as most patients will develop resistance to treatment and relapse within a median of 2 years. Identifying newly diagnosed MM (NDMM) patients who will develop resistance to treatment prior to relapse will allow switching these patients to an alternative treatment regimen and potentially avoiding the relapse event. To date, identifying NDMM patients with high risk of developing drug resistance remains an important clinical need. Genomic instability has been shown to be a dynamic indicator of disease progression in genetic diseases, particularly cancer. Telomere dysfunction is an early event in genomic instability. The 3-dimensional spatial profiling of telomeres allowing for the quantification of telomere dysfunction using TeloView technology was shown to be effective in stratifying patients into their respective risk groups in several cancers, including multiple myeloma. In a recent study were NDMM patients were followed longitudinally for up to 5 years, TeloView analysis was able to identify several MM risk groups, suggesting a clinical utility for TeloView analysis to predict the risk to develop drug resistance and relapse for MM patients up to ~13 months prior to the relapse event. Aims: In this study we analyzed a cohort of 178 NDMM patients. All patients received initial treatment using a regimen containing bortezomib or lenalidomide. The patient cohort included 2 patient groups, one group relapsed within 12 months and the other group remained in remission for over 3 years. Methods: Using TeloView technology we quantified 6 molecular and spatial telomeric parameters. We then conducted univariate and bivariate analyses using nested methodologies to identify telomere parameters that are significantly different between the 2 patient groups, suitable to be used as predictors in regression analysis. We then employed these significant parameters as predictors in multivariate analysis. Results: Four out of the measured telomere parameters were found significant with p-values <0.04 and equality of variance <0.01. The significant parameters included telomere length, number of detectable telomeres, % of telomere stumps and the a/c ratio (a measure of cell cycle progression). We generated ROC curves to develop a predictive scoring model able to predict risk of relapse on the level of the individual patient. The ROC curve analysis revealed AUC of 0.82 (82% accuracy) and corresponding specificity of 0.85 (85%) and sensitivity of 0.72 (72%). We examined the confidence of the generated predictive model using the Likelihood ratio, Wald and Scoring tests. The model showed confidence with p-values of <0.001 in all 3 tests. Summary/Conclusion: The result of this study presents TeloView as an accurate prognostic biomarker which appears able to predict the risk of NDMM patients to develop resistance to first-line therapy combinations that include bortezomib and/ or lenalidomide. Further validation of the developed scoring model using an independent patient cohort is underway. Keywords: Multiple myeloma, Telomere, Drug resistance, Relapse

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