The mechanisms of multiple myeloma (MM) initiation, evolution, and resistance/relapse are enigmatic. By defining common changes in the gene expression profile (GEP) of tumor cells and the microenvironment (ME), critical pathways involved in disease evolution may be identified. Project 3 will define molecular signatures of disease initiation, evolution, and resistance/relapse by studying the GEP of ME and MM and by examining molecular consequences of MM-ME interactions. Because the stromal cells of the bone ME may be transiently or permanently modified in MM and contribute to tumorigenesis, we will test the hypothesis that GEP of the ME component of the MM bone marrow will enable us to identify key molecular mechanisms through which the ME contributes to the disease phenotype.
Two aims will rely on samples obtained through clinical research performed in Projects 1 and 2.
Aim 1 : Identify and validate candidate genes involved in pathogenetic crosstalk between the MM and ME that contribute to the MM phenotype. This will be accomplished by (a) identifying ME-associated GEP changes that are linked to tumor development and plasma cell dyscrasia, (b) correlating ME-associated genes (MAGs) with MM PC GEP-defined or disease characteristic-defined subgroups to identify potential tumor cell-ME crosstalk mechanisms, and (c) identifying common drug-specific qualitative or quantitative changes in the MM PC and ME GEP after short-term (48-hour) drug treatment.
Aim 2 : Develop and validate GEP as a prognostic indicator of clinical outcome to form a rational basis for selecting treatment in the future. Patient outcomes (complete response, event-free and overall survival) will be correlated with GEP of the MM and ME. Specifically, through Aim 2 we will (a) determine whether the GEP changes found in Aim 1c after short-term (48-hour) drug treatment correlate with clinical outcome; (b) assess whether baseline GEP signatures of ME, MM PCs, or both predict outcome; and (c) compare GEP of ME and MM PCs at baseline, remission, and relapse to identify molecular determinants of resistance and pathways associated with disease progression. The bone marrow ME is a complex heterogenous mixture of cells with each having a distinct GEP. However, with the large sample groups available through the P01, recurring patterns found in MM combined with validation studies will provide insight into the key molecular signals contributing to disease progression originate. Elucidating the key GEP signatures in MM disease evolution will provide clinically relevant information that can be used to develop targeted therapies and ultimately improve treatment.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA055819-12
Application #
7278218
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2006-07-01
Budget End
2007-06-30
Support Year
12
Fiscal Year
2006
Total Cost
$185,747
Indirect Cost
Name
University of Arkansas for Medical Sciences
Department
Type
DUNS #
122452563
City
Little Rock
State
AR
Country
United States
Zip Code
72205
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
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
Mohan, Meera; Samant, Rohan S; Yoon, Donghoon et al. (2017) Extensive Remineralization of Large Pelvic Lytic Lesions Following Total Therapy Treatment in Patients With Multiple Myeloma. J Bone Miner Res 32:1261-1266
Sawyer, J R; Tian, E; Shaughnessy Jr, J D et al. (2017) Hyperhaploidy is a novel high-risk cytogenetic subgroup in multiple myeloma. Leukemia 31:637-644
Rasche, Leo; Angtuaco, Edgardo; McDonald, James E et al. (2017) Low expression of hexokinase-2 is associated with false-negative FDG-positron emission tomography in multiple myeloma. Blood 130:30-34
Mikulasova, Aneta; Wardell, Christopher P; Murison, Alexander et al. (2017) The spectrum of somatic mutations in monoclonal gammopathy of undetermined significance indicates a less complex genomic landscape than that in multiple myeloma. Haematologica 102:1617-1625

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