Project description:Despite their unprecedented density, current SNP genotyping arrays contain large amounts of redundancy, with up to 40 oligonucleotide features used to query each SNP. By using publicly available reference genotype data from the International HapMap, we show that 93.6% sensitivity at <5% false positive rate can be obtained with only four probes per SNP, compared with 98.3% with the full data set. Removal of this redundancy will allow for more comprehensive whole-genome association studies with increased SNP density and larger sample sizes.
Project description:Multiple myeloma still remains incurable in the majority of cases prompting a further search for new and better prognostic markers. Emerging evidence has suggested that circulating microRNAs can serve as minimally invasive biomarkers for multiple myeloma and monoclonal gammopathy of undetermined significance. In this study, a global analysis of serum microRNAs by TaqMan Low Density Arrays was performed, followed by quantitative real-time PCR. The analyses revealed five deregulated microRNAs: miR-744, miR-130a, miR-34a, let-7d and let-7e in monoclonal gammopathy of undetermined significance, newly diagnosed and relapsed multiple myeloma when compared to healthy donors. Multivariate logistical regression analysis showed that a combination of miR-34a and let-7e can distinguish multiple myeloma from healthy donors with a sensitivity of 80.6% and a specificity of 86.7%, and monoclonal gammopathy of undetermined significance from healthy donors with a sensitivity of 91.1% and a specificity of 96.7%. Furthermore, lower levels of miR-744 and let-7e were associated with shorter overall survival and remission of myeloma patients. One-year mortality rates for miR-744 and let-7e were 41.9% and 34.6% for the 'low' expression and 3.3% and 3.9% for the 'high' expression groups, respectively. Median time of remission for both miR-744 and let-7e was approximately 11 months for the 'low' expression and approximately 47 months for the 'high' expression groups of myeloma patients These data demonstrate that expression patterns of circulating microRNAs are altered in multiple myeloma and monoclonal gammopathy of undetermined significance and miR-744 with let-7e are associated with survival of myeloma patients.
Project description:Arrays for screening metabolite-generated toxicity utilizing spots containing DNA, enzyme, and electroluminescent (ECL) polymer ([Ru(bpy)(2)PVP(10)](2+)) were extended to include a fully representative set of metabolic enzymes from human and rat liver microsomes, human and rat liver cytosol, and mouse liver S9 fractions. Array use involves two steps: (1) enzyme activation of the test chemical and metabolite reaction with DNA, and then, (2) capture of ECL resulting from DNA damage using a charge coupled device (CCD) camera. Plots of ECL increase vs enzyme reaction time monitor relative rates of DNA damage and were converted into turnover rates for enzymic production of DNA-reactive metabolites. ECL turnover rates were defined by R, the initial slope of ECL increase versus enzyme reaction time normalized for amounts of enzyme and test chemical. R-values were used to establish correlations for 11 toxic compounds with the standard toxicity metrics rodent liver TD(50) and lethal dose (LD(50)), Ames tests, and Comet assays for in vitro DNA damage. Results support the value of the ECL genotoxicity arrays together with toxicity bioassays for early screening of new chemicals and drug candidates.
Project description:To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level.
Project description:Recent studies suggest that circulating tumor cells and cell-free DNA may represent powerful non-invasive tools for monitoring disease in patients with solid and hematologic malignancies. Here, we conducted a pilot study in 27 myeloma patients to explore the clonotypic V(D)J rearrangement for monitoring circulating myeloma cells and cell-free myeloma DNA. Next-generation sequencing was used to define the myeloma V(D)J rearrangement and for subsequent peripheral blood tracking after treatment initiation. Positivity for circulating myeloma cells/cell-free myeloma was associated with conventional remission status (<i>P</i><0.001) and 91% of non-responders/progressors <i>versus</i> 41% of responders had evidence of persistent circulating myeloma cells/cell-free myeloma DNA (<i>P</i><0.001). About half of the partial responders showed complete clearance of circulating myeloma cells/cell-free myeloma DNA despite persistent M-protein, suggesting that these markers are less inert than the M-protein, rely more on cell turnover and, therefore, decline more rapidly after initiation of effective treatment. Positivity for circulating myeloma cells and for cell-free myeloma DNA were associated with each other (<i>P</i>=0.042), but discordant in 30% of cases. This indicates that cell-free myeloma DNA may not be generated entirely by circulating myeloma cells and may reflect overall tumor burden. Prospective studies need to define the predictive potential of high-sensitivity determination of circulating myeloma cells and DNA in the monitoring of multiple myeloma.
Project description:<h4>Background</h4>It is well known that the normalization step of microarray data makes a difference in the downstream analysis. All normalization methods rely on certain assumptions, so differences in results can be traced to different sensitivities to violation of the assumptions. Illustrating the lack of robustness, in a striking spike-in experiment all existing normalization methods fail because of an imbalance between up- and down-regulated genes. This means it is still important to develop a normalization method that is robust against violation of the standard assumptions<h4>Results</h4>We develop a new algorithm based on identification of the least-variant set (LVS) of genes across the arrays. The array-to-array variation is evaluated in the robust linear model fit of pre-normalized probe-level data. The genes are then used as a reference set for a non-linear normalization. The method is applicable to any existing expression summaries, such as MAS5 or RMA.<h4>Conclusion</h4>We show that LVS normalization outperforms other normalization methods when the standard assumptions are not satisfied. In the complex spike-in study, LVS performs similarly to the ideal (in practice unknown) housekeeping-gene normalization. An R package called lvs is available in http://www.meb.ki.se/~yudpaw.
Project description:BACKGROUND:Multiple myeloma SET domain (MMSET)/nuclear receptor binding SET domain 2 (NSD2) is a lysine histone methyltransferase (HMTase) and bona fide oncoprotein found aberrantly expressed in several cancers, suggesting potential role for novel therapeutic strategies. In particular, MMSET/NSD2 is emerging as a target for therapeutic interventions against multiple myeloma, especially t(4;14) myeloma that is associated with a significantly worse prognosis than other biological subgroups. Multiple myeloma is the second most common hematological malignancy in the United States, after non-Hodgkin lymphoma and remains an incurable malignancy. Thus, effective therapeutic strategies are greatly needed. HMTases inhibitors are scarce and no NSDs inhibitors have been isolated. METHODS:We used homology modeling, molecular modeling simulations, virtual ligand screening, computational chemistry software for structure-activity relationship and performed in vitro H3K36 histone lysine methylation inhibitory assay using recombinant human NSD2-SET and human H3.1 histone. RESULTS:Here, we report the discovery of LEM-06, a hit small molecule inhibitor of NSD2, with an IC50 of 0.8 mM against H3K36 methylation in vitro. CONCLUSIONS:We propose LEM-06 as a hit inhibitor that is useful to further optimize for exploring the biology of NSD2. LEM-06 derivatives may pave the way to specific NSD2 inhibitors suitable for therapeutic efforts against malignancies.
Project description:Bladder cancer is a common malignancy requiring a high degree of surveillance because of the frequent recurrences and the poor clinical outcome of invasive disease. To date, serum biomarkers for bladder cancer lack optimal sensitivity and specificity to assist in diagnosis and disease categorization. Here, we designed antibody arrays for bladder cancer by selecting antibodies against targets differentially expressed in bladder tumors. Serum protein profiles measured by an antibody array containing 254 antibodies discriminated bladder cancer patients from controls (n = 95) with a correct classification rate of 93.7%. A second independent antibody array containing 144 antibodies revealed that protein profiles provide predictive information by stratifying patients with bladder tumors (n = 37) based on their overall survival (P = 0.0479). In addition, serum proteins, such as c-met, that were top ranked at identifying bladder cancer patients were associated with pathological stage, tumor grade, and survival when validated by immunohistochemistry of tissue microarrays containing bladder tumors (n = 173). This study provides experimental evidence for the use of several integrated technologies strengthening the process of biomarker discovery. Serum protein profiles obtained by antibody arrays represent comprehensive means for bladder cancer diagnosis and clinical outcome stratification, which could potentially assist in selection of cancer patients who would benefit from early, individualized therapeutic intervention.
Project description:Poor outcome of extramedullary disease in multiple myeloma patients and lack of outcome predictors prompt continued search for new markers of the disease. In this report, we show circulating microRNA distinguishing multiple myeloma patients with extramedullary disease from myeloma patients without such manifestation and from healthy donors. MicroRNA-130a was identified by TaqMan Low Density Arrays and verified by quantitative PCR on 144 serum samples (59 multiple myeloma, 55 myeloma with extramedullary disease, 30 healthy donors) in test and validation cohorts as being down-regulated in myeloma patients with extramedullary disease. Circulating microRNA-130a distinguished myeloma patients with extramedullary disease from healthy donors with specificity of 90.0% and sensitivity of 77.1%, patients with extramedullary disease from newly diagnosed multiple myeloma patients with specificity of 77.1% and sensitivity of 34.3% in the test cohort and with specificity of 91.7% and sensitivity of 30.0% in the validation cohort of patients. Circulating microRNA-130a in patients with extramedullary myeloma was associated with bone marrow plasma cells infiltration. Further, microRNA-130a was decreased in bone marrow plasma cells obtained from patients with extramedullary myeloma in comparison to bone marrow plasma cells of myeloma patients without such manifestation, but it was increased in tumor site plasma cells of patients with extramedullary disease compared to bone marrow plasma cells of such patients (p<0.0001). Together, our data suggest connection between lower level of microRNA-130a and extramedullary disease and prompt further work to evaluate this miRNA as a marker of extramedullary disease in multiple myeloma.
Project description:Liquid biopsies come of age offering unexploited potential to monitor and react to tumor evolution. We developed a cost-effective assay to non-invasively determine the immune status of glioblastoma (GBM) patients. Employing newly developed printed peptide microarrays we assessed the B-cell response against tumor-associated antigens (TAAs) in 214 patients. Firstly, sera of long-term (36+ months, LTS, n=10) and short-term (6-10 months, STS, n=14) surviving patients were screened for prognostic antibodies against 1745 13-mer peptides covering known TAAs (TNC, EGFR, GLEA2, PHF3, FABP5, MAGEA3). Next, survival associations were investigated in two retrospective independent multicenter validation sets (n=61, n=129, all IDH1-wildtype). Reliability of measurements was tested using a second array technology (spotted arrays). LTS/STS screening analyses identified 106 differential antibody responses. Evaluating the Top30 peptides in validation set 1 revealed three prognostic peptides. Prediction of TNC peptide VCEDGFTGPDCAE was confirmed in a second set (p=0.043, HR=0.66 [0.44-0.99]) and was unrelated to TNC protein expression. Median signals of printed arrays correlated with pre-synthesized spotted microarrays (p<0.0002, R=0.33). Multiple survival analysis revealed independence of age, gender, KPI and MGMT status. We present a novel peptide microarray immune assay that identified increased anti-TNC VCEDGFTGPDCAE serum antibody titer as a promising non-invasive biomarker for prolonged survival.