Eckel, Jeanette E.

Abstract It appears that a number of recent manuscripts using protein microarray technology are using equivalent analysis procedures that the gene-expression microarray community implemented in their infancy. That is, utilizing a classic reference design such that the ratio of the sample of interest to a reference sample is the response of interest and assessing fold change to determine differential expression. For example, recent publications have concluded that proteins with a fold change less than 0.7 or greater than 1.3 demonstrate significant down- or up-regulated differential expression, respectively. However, fold change is an unreliable measure of differential expression and statistical models that distinguish true signal from random noise should be utilized instead of fold changes. Over the last half decade a tremendous amount of research has been devoted to gene-expression microarrays to vastly improve on the areas of experimental design, normalization and statistical analyses to assess differential expression and classification and these methods are directly applicable to protein microarray technology. Thus, the objective is to review the statistical methodology that has been developed for two-color cDNA arrays that is directly applicable to protein arrays. Examples are provided from a mantle-cell lymphoma protein-array experiment.

Abstract The objective of this study was to analyze protein changes that occur a the molecular level with novel therapeutic agents used in MM in order to identify potential combinations for clinical trials. We employed antibody protein microarrays (BD Clonetech, CA) to measure changes in the patterns of protein expression in Kas 6/1 MM cell line after treatment with bortezomib, dexamethasone, CC-5013, and 17-AAG. The antibody array is a new technique that assays protein differences directly by hybridizing fluorescently labeled protein mixtures from cell extracts onto glass slides spotted with 512 different monoclonal antibodies specific for human proteins. Induction of apoptosis was assessed by Annexin/Propidium iodide FACS analysis at 24 and 48 hours using different concentrations of the inhibitors. Protein arrays were performed at concentrations and treatment times that did not induce more than 25% apoptosis to ensure adequate analysis of early changes in signaling pathways. Bortezomib 5nM at 10 hours, dexamethasone 100mM, CC-5013 250nM, and 17-AAG 1mM at 24 hours were used. Control cells were treated with vehicles ETOH or DMSO at the same concentrations as the inhibitors. To assess differential protein expression, the mean of the Cy5/Cy3 ratios for each sample and its control were analyzed using the Clontech software and an internally normalized ratio (INR) was calculated. INR values >1.3 or <0.77 were considered as valid changes in protein abundance for this study. All inhibitors induced the upregulation of apoptosis proteins including BAK, BIK, SMAC/DIABLO, and caspase 14. Several proteins were inhibited by all 4 inhibitors indicating common pathways affected by these agents. These included members of the PI3K pathway (PI3K-p85a, p70S6kinase, and cyclin dependent kinases), MAPKinases (ERK1 and 2), antiapoptotic protein Bclx, heat shock proteins Hsp70 and HSP60, and ubiqutin/NFkB pathway (Ubch6, IKKalpha, and IKBe). These results indicate that inhibitors of the PI3K pathway such as mTOR inhibitors, IKK inhibitors or MAPkinase inhibitors may be used in the future in combination with bortezomib, dexamethasone, CC-5013 or 17-AAG. Fatty acid synthetase was downregulated by bortezomib and dexamethasone indicating potential use of fatty acid synthase inhibitors in combination with bortezomib or dexamethasone in future clinical trials. These results suggest that antibody protein arrays may be used in the rational design of combinations of targeted therapies in MM.

Abstract The objective of this study was to investigate the underlying molecular alteration in multiple myeloma at the protein level in order to identify regulators of pathogenesis, discover novel targets of therapy, and compare genetic and proteomic alterations. We employed antibody protein microarrays (BD Clonetech, CA) to measure changes in the patterns of protein expression between MM and normal plasma cells. The antibody array is a new technique enabling protein differences to be assayed directly by hybridizing fluorescently labeled protein mixtures from cell extracts onto glass slides spotted with 512 different monoclonal antibodies. CD138+purified plasma cells were obtained from cryopreserved bone marrow samples of 12 newly diagnosed patients with MM. The labeling index was high (1% cutoff) in 7 samples and low in the other 5. Control plasma cells were obtained from 9 pooled CD138+ purified normal donor bone marrow plasma cells. Interphase FISH analysis for 17p deletion, 13q deletion, and t(11:14) were performed. To assess differential expression, the mean of the ratios of Cy5/Cy3 for each sample were analyzed using the Clontech software to calculate an internally normalized ratio. The normalized data were analyzed by the Genespring software. Unsupervised clustering identified 4 groups of MM. Changes of protein expression ≥2 fold in 70% of the samples as compared to control were identified. There were 6 proteins differentially expressed between all MM samples and control cells including proteins in the ras signaling pathway (KSR-1), the ubiquitin pathway (Ubc-H6), cyclin-dependent kinases (CDK4), cytokines (IL-6), DNA toposisomerase II, and the rho-interacting serine-threonine kinase CRIK. Proteins differentially expressed in MM groups 1 and 2 compared to normal control included cell cycle regulators (cul-2, MCM6, PCNA, TGFb1), kinases (p70S6K, PKC), and chromatin regulators (Ran, AKAP450, Rad50). Protiens differentially expressed in MM group 3 included cell cycle regulators (CDK2, CLK1, MENA), apoptosis regulators (XIAP, caspase 4, perforin) kinases (IKKa and RAC1 in the Wnt signaling pathway) and P53 regulators, while proteins identified in MM group 4 included NFkB/ubiquitin proteins (IKKa and Ubch6), cell cycle regulators (c-myc, CDK4), p53 pathway proteins (53bp2), ras-signaling proteins (KSR1), and the kinase CRIK. There were no differences in protein expression between the high and low labeling index groups. 13q was identified in 5 (42%), 17 p in 1(8%) and t(11:14) in 1(8%) patients. 80% of the 13 q deletion cases clustered in MM group 1 and 2 patients. Cyclin D-1 was upregulated in 5 (42%) patients including the patient with (11:14) translocation. This is the first proteomic study of patients with MM. The results are consistent with previously identified genetic alterations in MM indicating that this novel technique could be used in identifying molecular changes in MM. It identifies novel proteins dysregulated in MM that differ between the 4 MM groups. These results may be used in the future to individualize therapy based on the proteins dysregulated in each group. For example, IKK inhibitors may be useful in group 3 MM patients, while mTOR inhibitors (upstream of p70S6K) could be used in groups 1 and 2 patients. Future correlations with gene expression arrays and prognosis in a larger cohort of patients is warranted.

Abstract The objective of this study was to analyze molecular changes that occur at the protein level in WM and IgM-MGUS in order to identify proteins dysregulated at disease progression and design new therapies. We employed antibody protein microarrays (BD Clonetech, CA) to measure changes in the patterns of protein expression between WM, IgM-MGUS and normal lymphoplasmacytic cells as control. The antibody array is a novel technique that assays protein differences directly by hybridizing fluorescently labeled protein mixtures from cell extracts onto a glass slide spotted with 512 different monoclonal antibodies specific for human proteins. CD 19+ and CD138+ purified lymphoplasmacytic cells were obtained from cryopreserved bone marrow samples of 5 newly diagnosed patients with WM and 5 patients with IgM-MGUS. Control plasma cells were obtained from 3 pooled CD19+ and CD138+ purified normal donor bone marrow cells. To assess differential expression, the mean of the ratios of Cy5/Cy3 for each sample were analyzed using the Clontech software to calculate an internally normalized ratio. The normalized data were analyzed by the Genespring software and changes of protein expression ≥2 fold in 60% of the samples as compared to normal control were identified in both WM and MGUS groups. There were 20 proteins upregulated in WM and 21 proteins in MGUS as compared to normal control cells These included proteins from the small GTPases such as the Ras, Rho and Ran families (Rab 4, MONA, RCC1, and CDC42GAP), Kinases/signaling proteins (ROK alpha, p62 dok, JAK, 14-3-3e), cyclin dependent kinase (CDK2), fatty acid synthase (HDAC3), NFkB pathway (IKKalpha, IKBe), and histone deacetylase. The WM and IgM MGUS differed in only 3 proteins using the 2-fold threshold. The WM samples showed overexpression of the heat shock protein Hsp90, the Ras family protein CDC25C, and the chemotaxis protein p43/EMAPII as compared to the MGUS samples. This is the first proteomic study of WM and MGUS patients. It identifies novel proteins dysregulated in WM that may serve in future clinical trials as targets for therapy such as Hsp90, NFkB, HDAC and fatty acid synthase. In addition, it identifies 3 proteins that identify disease progression from MGUS to WM, which could be useful for monitoring MGUS patients and designing targeted therapies to prevent progression to WM.