The goal of the research projects in this program is to understand the oncogenomic changes in myeloma central to disease pathogenesis which impact clinical outcome using data from two large clinical trials To support this effort, the Bioinformatics and Biostatistics Core E will provide 1) support and direction on the formatting, quality control and annotation procedures of clinical and research data as well as the process of transferring the research data a data warehouse for integrative analysis, 2) bioinformatics support for primary and integrative analysis of the high-throughput data on genetic lesions, gene expression and transcriptome modification by differential miRNA expression and alternative splicing and 3) biostatistics support in terms of design and analysis for all projects. Core members will work closely with project members as well as Cores A and B with regard to quality control, specimen tracking and data warehouse procedures as well as Cores C and D which will perform microarray based gene and miRNA expression profiling, and SNP genotyping and next generation sequencing for identifying genomic and transcriptomic changes. Bioinformatics and biostatistics support and analysis is not only required for individual projects, but it is crucial for the integrative analysis from data across the projects and thus overall success of the program.
This core will help analyze both clinical data to identify role of transplantation in myeloma in the era of novel agents and identify correlates of clinical out come. The bioinformatic support will unravel genomic changes to better understand disease biology, features predictive of progression to myeloma and define those changes that will predict outcome and will form the basis for development of novel therapeutics.
|GullÃ , Annamaria; Di Martino, Maria Teresa; Gallo Cantafio, Maria Eugenia et al. (2016) A 13 mer LNA-i-miR-221 Inhibitor Restores Drug Sensitivity in Melphalan-Refractory Multiple Myeloma Cells. Clin Cancer Res 22:1222-33|
|Prabhala, R H; Fulciniti, M; Pelluru, D et al. (2016) Targeting IL-17A in multiple myeloma: a potential novel therapeutic approach in myeloma. Leukemia 30:379-89|
|Magrangeas, Florence; Kuiper, Rowan; Avet-Loiseau, HervÃ© et al. (2016) A Genome-Wide Association Study Identifies a Novel Locus for Bortezomib-Induced Peripheral Neuropathy in European Patients with Multiple Myeloma. Clin Cancer Res 22:4350-5|
|Ohguchi, Hiroto; Hideshima, Teru; Bhasin, Manoj K et al. (2016) The KDM3A-KLF2-IRF4 axis maintains myeloma cell survival. Nat Commun 7:10258|
|Dimopoulos, Meletios A; Orlowski, Robert Z; Facon, Thierry et al. (2015) Retrospective matched-pairs analysis of bortezomib plus dexamethasone versus bortezomib monotherapy in relapsed multiple myeloma. Haematologica 100:100-6|
|Bianchi, Giada; Munshi, Nikhil C (2015) Pathogenesis beyond the cancer clone(s) in multiple myeloma. Blood 125:3049-58|
|Jagannathan, S; Vad, N; Vallabhapurapu, S et al. (2015) MiR-29b replacement inhibits proteasomes and disrupts aggresome+autophagosome formation to enhance the antimyeloma benefit of bortezomib. Leukemia 29:727-38|
|Hu, Y; Song, W; Cirstea, D et al. (2015) CSNK1Î±1 mediates malignant plasma cell survival. Leukemia 29:474-82|
|Hebraud, Benjamin; Magrangeas, Florence; Cleynen, Alice et al. (2015) Role of additional chromosomal changes in the prognostic value of t(4;14) and del(17p) in multiple myeloma: the IFM experience. Blood 125:2095-100|
|Mitsiades, Constantine S (2015) Therapeutic landscape of carfilzomib and other modulators of the ubiquitin-proteasome pathway. J Clin Oncol 33:782-5|
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