Abstract

The cell culture, cell characterization and cytokine core will play a central role in the Program project """"""""Growth Control of Multiple Myeloma"""""""". This facility will facilitate all other projects by providing tumor banking and tissue triaging services. In addition they will provide basic data to the Myeloma Data Bank by phenotyping all patients' myeloma cells and measuring the expression of a variety of cytokines in myeloma cells and patients' sera. These assays will be accomplished by flow cytometry, immunocytochemistry and in situ hybridization. In addition, the laboratory will measure expression of a number of biological molecules which may be significant in myeloma including multiple drug resistance, glucocorticoid receptor, GSH, Ki67, as well as proliferative activity. this core will provide important data on factors involved in control of myeloma cells and how these molecules change during the clinical course of the disease. In addition, it will provide biological specimens which are well characterized for all other projects.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA055819-04
Application #
5209157
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
1996
Total Cost
Indirect Cost

  Publications

Rasche, L; Alapat, D; Kumar, M et al. (2018) Combination of flow cytometry and functional imaging for monitoring of residual disease in myeloma. Leukemia :
Went, Molly; Sud, Amit; Försti, Asta et al. (2018) Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma. Nat Commun 9:3707
Mehdi, Syed J; Johnson, Sarah K; Epstein, Joshua et al. (2018) Mesenchymal stem cells gene signature in high-risk myeloma bone marrow linked to suppression of distinct IGFBP2-expressing small adipocytes. Br J Haematol :
Rasche, Leo; Angtuaco, Edgardo J; Alpe, Terri L et al. (2018) The presence of large focal lesions is a strong independent prognostic factor in multiple myeloma. Blood 132:59-66
Went, M; Sud, A; Law, P J et al. (2017) Assessing the effect of obesity-related traits on multiple myeloma using a Mendelian randomisation approach. Blood Cancer J 7:e573
McDonald, James E; Kessler, Marcus M; Gardner, Michael W et al. (2017) Assessment of Total Lesion Glycolysis by 18F FDG PET/CT Significantly Improves Prognostic Value of GEP and ISS in Myeloma. Clin Cancer Res 23:1981-1987
Rasche, Leo; Weinhold, Niels; Morgan, Gareth J et al. (2017) Immunologic approaches for the treatment of multiple myeloma. Cancer Treat Rev 55:190-199
Rasche, L; Chavan, S S; Stephens, O W et al. (2017) Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun 8:268
Jethava, Yogesh S; Mitchell, Alan; Epstein, Joshua et al. (2017) Adverse Metaphase Cytogenetics Can Be Overcome by Adding Bortezomib and Thalidomide to Fractionated Melphalan Transplants. Clin Cancer Res 23:2665-2672
Schinke, Carolina; Hoering, Antje; Wang, Hongwei et al. (2017) The prognostic value of the depth of response in multiple myeloma depends on the time of assessment, risk status and molecular subtype. Haematologica 102:e313-e316

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