The purpose of the Biostatistics and Bioinformatics Core C is to provide consultation and collaboration on quantitative methods on all SPORE Projects, Developmental Projects, and Cores A and B. Successful collaboration between the project leaders and the biostatisticians and computational biologists in this SPORE, as well as members of the other Cores, is essential to achieve the goals of the projects. Members of this core will provide support for the design, analysis, and reporting of laboratory, animal, translational, genomic, and clinical studies. Depending on the project, these collaborations could range from short consultations to large collaborative projects, and will include assistance in preparation of grant applications and manuscripts related to the SPORE projects. The Core members will also provide statistical mentoring to the researchers, with a particular emphasis on Career Development Awardees and Developmental Project Investigators. Important for the success of the SPORE is the coordination of data management and quality control procedures. The biostatisticians and computational biologists are an integral part of this process at the DFCI, and will continue to provide input on the existing procedures, as well as recommendations on additional computational infrastructure, which might be necessary for this SPORE. To achieve the goals of the SPORE, we propose the following specific aims:
Specific Aim 1. To provide biostatistical collaboration for SPORE Projects, Developmental Projects, and Cores. This includes all aspects of design, conduct, analysis, and reporting of laboratory and clinical protocols, including coordination of laboratory results with patient characteristics and outcomes from the clinical studies.
Specific Aim 2. To provide consulting and statistical education to SPORE researchers.
Specific Aim 3. To provide or recommend supporting computational infrastructure. This includes collaboration with the multiple myeloma clinical research coordinators (CRC) and the data specialist at the Quality Assurance Office for Clinical Trials (QACT) on the collection of data, forms development, data processing, and quality assurance of clinical trials data. We will also provide consultation on computer databases, moving data between data bases for laboratory, animal, and relevant clinical studies Specific Aim 4. To provide bioinformatic support for analysis of high throughput transcriptional and genomic studies.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center (P50)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-RPRB-0)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Dana-Farber Cancer Institute
United States
Zip Code
Hu, Y; Song, W; Cirstea, D et al. (2015) CSNK1?1 mediates malignant plasma cell survival. Leukemia 29:474-82
Bae, J; Prabhala, R; Voskertchian, A et al. (2015) A multiepitope of XBP1, CD138 and CS1 peptides induces myeloma-specific cytotoxic T lymphocytes in T cells of smoldering myeloma patients. Leukemia 29:218-29
Suzuki, R; Hideshima, T; Mimura, N et al. (2015) Anti-tumor activities of selective HSP90?/? inhibitor, TAS-116, in combination with bortezomib in multiple myeloma. Leukemia 29:510-4
Campigotto, Federico; Weller, Edie (2014) Impact of informative censoring on the Kaplan-Meier estimate of progression-free survival in phase II clinical trials. J Clin Oncol 32:3068-74
Hideshima, T; Mazitschek, R; Santo, L et al. (2014) Induction of differential apoptotic pathways in multiple myeloma cells by class-selective histone deacetylase inhibitors. Leukemia 28:457-60
Greenberg, A J; Rajkumar, S V; Therneau, T M et al. (2014) Relationship between initial clinical presentation and the molecular cytogenetic classification of myeloma. Leukemia 28:398-403
Lohr, Jens G; Adalsteinsson, Viktor A; Cibulskis, Kristian et al. (2014) Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer. Nat Biotechnol 32:479-84
Anderson, K K; Flora, N; Archie, S et al. (2014) A meta-analysis of ethnic differences in pathways to care at the first episode of psychosis. Acta Psychiatr Scand 130:257-68
Landgren, O; Graubard, B I; Katzmann, J A et al. (2014) Racial disparities in the prevalence of monoclonal gammopathies: a population-based study of 12,482 persons from the National Health and Nutritional Examination Survey. Leukemia 28:1537-42
Yin, Li; Kufe, Turner; Avigan, David et al. (2014) Targeting MUC1-C is synergistic with bortezomib in downregulating TIGAR and inducing ROS-mediated myeloma cell death. Blood 123:2997-3006

Showing the most recent 10 out of 184 publications