The broad long term objective is to use genotypic and clinical characteristics to improve individualized healthcare. Severe mucositis is a dose limiting toxicity of high dose melphalan (MEL) with autologous stem cell transplant (ASCT), the cornerstone of treatment of myeloma and other cancers including leukemias and lymphomas and in both autologous and allogeneic transplant settings. Genetic variability in the enzymes/proteins involved in drug metabolism, inflammation and immune function is likely a major underlying contributor to mucositis incidence and progression. Known genetic variability would improve a current mucositis prediction model. Using genome wide association study (GWAS) combined with a pathway candidate gene approach and a modified case-control study method, this hypothesis will be investigated in a sample of 1168 myeloma patients treated with MEL-ASCT as part of Total Therapy and for whom clinical samples and data are already collected.
The specific aims of this interdisciplinary team study are to: 1) Discover genes associated with the development of severe chemotherapy-induced mucositis, 2) Evaluate the interaction between genotypic and clinical characteristics associated with severe chemotherapy-induced mucositis, and 3) Develop a mucositis predictive model by integrating genotypic and clinical characteristics. Data analysis will include chi-squared, logistic regression, and multifactor dimensionality reduction. Development of the prediction model will consist of selection of predictors and a classification algorithm to develop the prediction rule, followed by performance assessment. A precise prediction model will provide a more personalized risk-adapted treatment to prevent severe mucositis, the dose-limiting toxicity of MEL, extend quality and years of life, and reduce the burdens of illness and disability. In addition, the data could yield other biomarkers of treatment-associated toxicities and germ-line mutations associated with myeloma that could assist in determining the etiology of this disease, as yet unknown. The proposed study addresses the following NINR areas of research interest: promoting health and preventing disease, improving QOL, and symptom management. This study will accelerate nursing advancements to the """"""""Science of Health"""""""" by developing biomarkers, identifying susceptibility genes for at-risk individuals, delineating causative mechanisms underlying symptoms of mucositis, and developing strategies for assessment and intervention to improve health-related QOL in persons with chronic and life-threatening illness and will lead to improving recognition of symptoms by health care providers. Thus, this study will accelerate nursing advancements to the """"""""Science of Health"""""""".
Chemotherapy-induced mucositis is such an important problem that the NIH has made it a targeted focus of needed research. The research team at the Myeloma Institute for Research and Therapy, patient population and clinical database are ideal to address this important problem. Results of this study could yield a precise mucositis predictive model that could effectively stratify patients according to their risk for severe mucositis and prevent a dose-limiting toxicity. In addition, the data could yield other biomarkers of treatment- associated toxicities and germ-line mutations associated with myeloma that could assist in determining the etiology of this disease, yet unknown. Thus, this study will accelerate nursing advancements to the """"""""Science of Health"""""""".
| Erickson, Stephen W; Stephens, Owen W; Chavan, Shweta S et al. (2016) A common genetic variant in 19q13ยท3 is associated with outcome of multiple myeloma patients treated with Total Therapy 2 and 3. Br J Haematol 174:991-3 |
| Coleman, Elizabeth Ann; Lee, Jeannette Y; Erickson, Stephen W et al. (2015) GWAS of 972 autologous stem cell recipients with multiple myeloma identifies 11 genetic variants associated with chemotherapy-induced oral mucositis. Support Care Cancer 23:841-9 |
| Erickson, S W; Stephens, O W; Chavan, S S et al. (2015) Common genetic variants in 11q13.3 and 9q22.33 are associated with molecular subgroups of multiple myeloma. Leukemia 29:2418-21 |
| Erickson, Stephen W; Raj, Vinay R; Stephens, Owen W et al. (2014) Genome-wide scan identifies variant in 2q12.3 associated with risk for multiple myeloma. Blood 124:2001-3 |
