Core A combines the solid support of MIRT administration with the innovation of Cancer Research and Biostatistics (CRAB) and the superb attention to detail of our data management team to ensure the efforts of all P01 projects and cores are both tangible and accessible. The structure of this P01 has afforded discoveries that were critically dependent on a large patient referral base with fight, long-term follow-up;integrated basic-clinical investigation;and statistical power to interpret findings in the context of historical patients with comprehensive annotations of clinical course and therapeutic interventions as well as availability of samples and laboratory correlates in our multiple myeloma (MM) database (MMDB) system. We have generated an unprecedented treasure of serially obtained bone marrow samples annotated according to the phase of therapy at the time of procurement as well as serial MRI and PET-CT studies for virtually all patients. This wealth of data requires a solid administrative and data management infrastructure to maintain its validity and utility. Core A provides this through Administration, Biostatistics, and Research Coordination components that have been designed to support 4 projects and 4 additional cores.
Aim 1 will provide administrative support to enable the entire Program Project to function as an integrated whole. Over the previous 15 years of funding, this program has supported, on average, 30 PIs and Co-Is and more than 60 Research Associates/Assistants, Post-doctoral Fellows, and other research personnel. The Administration Component will continue to ensure that support is provided to all projects and cores, so research activities are coordinated and have appropriate interactions to accomplish the goals of this Program Project.
Aim 2 will apply biostatistical principles and data management methods to Program Project studies in an effort to ensure in-depth and timely attention to all aspects of data collection as well as execution of increasingly sophisticated biostatistical analyses and bioinformatics. The Biostatistics component, through the innovative efforts of CRAB, will continue to enable researchers of this program to link study design, data collection, measurement, and analysis to the research hypotheses and research questions being investigated.
Aim 3 will provide research coordination that ensures the timely and accurate identification and retrieval of all data associated with MIRT patients in the context of unique patient characteristics, including prognostic features, therapeutic interventions, and serial GEP and imaging data.
The inter-related activities of Core A will not only provide the necessary infrastructure to ensure that day-today operations of the Program Project run smoothly, but will also allow the rapid identification and dissemination of discoveries by individual projects to the other projects and, where appropriate, assess whether a need exists for adjusting research objectives and treatment approaches pursued in this program. As in the past, our successes will be promptly shared with the research community at large.
|Johnson, Sarah K; Stewart, James P; Bam, Rakesh et al. (2014) CYR61/CCN1 overexpression in the myeloma microenvironment is associated with superior survival and reduced bone disease. Blood 124:2051-60|
|Dhodapkar, Madhav V; Sexton, Rachael; Waheed, Sarah et al. (2014) Clinical, genomic, and imaging predictors of myeloma progression from asymptomatic monoclonal gammopathies (SWOG S0120). Blood 123:78-85|
|Lapteva, Natalia; Szmania, Susann M; van Rhee, Frits et al. (2014) Clinical grade purification and expansion of natural killer cells. Crit Rev Oncog 19:121-32|
|Bam, R; Venkateshaiah, S U; Khan, S et al. (2014) Role of Bruton's tyrosine kinase (BTK) in growth and metastasis of INA6 myeloma cells. Blood Cancer J 4:e234|
|Papanikolaou, X; Rosenbaum, E R; Tyler, L N et al. (2014) Hematopoietic progenitor cell collection after autologous transplant for multiple myeloma: low platelet count predicts for poor collection and sole use of resulting graft enhances risk of myelodysplasia. Leukemia 28:888-93|
|Sawyer, Jeffrey R; Tian, Erming; Heuck, Christoph J et al. (2014) Jumping translocations of 1q12 in multiple myeloma: a novel mechanism for deletion of 17p in cytogenetically defined high-risk disease. Blood 123:2504-12|
|Tian, Erming; Sawyer, Jeffrey R; Heuck, Christoph J et al. (2014) In multiple myeloma, 14q32 translocations are nonrandom chromosomal fusions driving high expression levels of the respective partner genes. Genes Chromosomes Cancer 53:549-57|
|Waheed, Sarah; Mitchell, Alan; Usmani, Saad et al. (2013) Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data. Haematologica 98:71-8|
|Lamy, Laurence; Ngo, Vu N; Emre, N C Tolga et al. (2013) Control of autophagic cell death by caspase-10 in multiple myeloma. Cancer Cell 23:435-49|
|Sousa, Mirta M L; Zub, Kamila Anna; Aas, Per Arne et al. (2013) An inverse switch in DNA base excision and strand break repair contributes to melphalan resistance in multiple myeloma cells. PLoS One 8:e55493|
Showing the most recent 10 out of 227 publications