John D Shaughnessy

Signal Genetics, New York, New York, United States

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Publications (228)2011.58 Total impact

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    Shweta S Chavan, John D Shaughnessy, Ricky D Edmondson
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    ABSTRACT: Many primary biological databases are dedicated to providing annotation for a specific type of biological molecule such as a clone, transcript, gene or protein, but often with limited cross-references. Therefore, enhanced mapping is required between these databases to facilitate the correlation of independent experimental datasets. For example, molecular biology experiments conducted on samples (DNA, mRNA or protein) often yield more than one type of 'omics' dataset as an object for analysis (eg a sample can have a genomics as well as proteomics expression dataset available for analysis). Thus, in order to map the two datasets, the identifier type from one dataset is required to be linked to another dataset, so preventing loss of critical information in downstream analysis. This identifier mapping can be performed using identifier converter software relevant to the query and target identifier databases. This review presents the publicly available web-based biological database identifier converters, with comparison of their usage, input and output formats, and the types of available query and target database identifier types.
    Human genomics 10/2011; 5(6):703-8. DOI:10.1186/1479-7364-5-6-703
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    ABSTRACT: Despite improvement in therapeutic efficacy, multiple myeloma (MM) remains incurable with a median survival of approximately 10 years. Gene-expression profiling (GEP) can be used to elucidate the molecular basis for resistance to chemotherapy through global assessment of molecular alterations that exist at diagnosis, after therapeutic treatment and that evolve during tumor progression. Unique GEP signatures associated with recurrent chromosomal translocations and ploidy changes have defined molecular classes with differing clinical features and outcomes. When compared to other stratification systems the GEP70 test remained a significant predictor of outcome, reduced the number of patients classified with a poor prognosis, and identified patients at increased risk of relapse despite their standard clinico-pathologic and genetic findings. GEP studies of serial samples showed that risk increases over time, with relapsed disease showing GEP shifts toward a signature of poor outcomes. GEP signatures of myeloma cells after therapy were prognostic for event-free and overall survival and thus may be used to identify novel strategies for overcoming drug resistance. This brief review will focus on the use of GEP of MM to define high-risk myeloma, and elucidate underlying mechanisms that are beginning to change clinical decision-making and inform drug design.
    International journal of hematology 10/2011; 94(4):321-33. DOI:10.1007/s12185-011-0948-y · 1.68 Impact Factor
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    ABSTRACT: It was demonstrated that metallopanstimulin-1 (MPS-1, RPS27) inhibited the growth of tumors formed by head and neck squamous cell carcinoma cells and reduced paxillin gene expression. The present study examined whether and how MPS-1 affects another type of cancer, multiple myeloma (CAG). Enhanced expression of MPS-1 dramatically inhibited CAG in vitro and in vivo. Overexpression of MPS-1 resulted in decreased fibroblast growth factor (FGF2) receptor 3 and impaired endogenous MAPK/ErK signaling. MAPK/ErK signaling was not stimulated by adding recombinant FGF2 to myeloma cells overexpressing MPS-1. These data suggest that MPS-1 suppresses CAG growth and that weakened FGF2 signaling may contribute to this effect.
    Clinical lymphoma, myeloma & leukemia 09/2011; 11(6):490-7. DOI:10.1016/j.clml.2011.06.015 · 1.93 Impact Factor
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    ABSTRACT: Promising new drugs are being evaluated for treatment of multiple myeloma (MM), but their impact should be measured against the expected outcome in patients failing current therapies. However, the natural history of relapsed disease in the current era remains unclear. We studied 286 patients with relapsed MM, who were refractory to bortezomib and were relapsed following, refractory to or ineligible to receive, an IMiD (immunomodulatory drug), had measurable disease, and ECOG PS of 0, 1 or 2. The date patients satisfied the entry criteria was defined as time zero (T0). The median age at diagnosis was 58 years, and time from diagnosis to T0 was 3.3 years. Following T0, 213 (74%) patients had a treatment recorded with one or more regimens (median=1; range 0–8). The first regimen contained bortezomib in 55 (26%) patients and an IMiD in 70 (33%). A minor response or better was seen to at least one therapy after T0 in 94 patients (44%) including partial response in 69 (32%). The median overall survival and event-free survival from T0 were 9 and 5 months, respectively. This study confirms the poor outcome, once patients become refractory to current treatments. The results provide context for interpreting ongoing trials of new drugs.Keywords: multiple myeloma; relapse; natural history; survival
    Leukemia 07/2011; 26(1):149-157. DOI:10.1038/leu.2011.196 · 9.38 Impact Factor
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    ABSTRACT: Gene expression profiling (GEP) of purified plasma cells 48 hours after thalidomide and dexamethasone test doses showed these agents' mechanisms of action and provided prognostic information for untreated myeloma patients on Total Therapy 2 (TT2). Bortezomib was added in Total Therapy 3 (TT3), and 48 hours after bortezomib GEP analysis identified 80 highly survival-discriminatory genes in a training set of 142 TT3A patients that were validated in 128 patients receiving TT3B. The 80-gene GEP model (GEP80) also distinguished outcomes when applied at baseline in both TT3 and TT2 protocols. In context of our validated 70-gene model (GEP70), the GEP80 model identified 9% of patients with a grave prognosis among those with GEP70-defined low-risk disease and 41% of patients with favorable prognosis among those with GEP70-defined high-risk disease. PMSD4 was 1 of 3 genes common to both models. Residing on chromosome 1q21, PSMD4 expression is highly sensitive to copy number. Both higher PSMD4 expression levels and higher 1q21 copy numbers affected clinical outcome adversely. GEP80 baseline-defined high risk, high lactate dehydrogenase, and low albumin were the only independent adverse variables surviving multivariate survival model. We are investigating whether second-generation proteasome inhibitors (eg, carfilzomib) can overcome resistance associated with high PSMD4 levels.
    Blood 05/2011; 118(13):3512-24. DOI:10.1182/blood-2010-12-328252 · 9.78 Impact Factor
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    ABSTRACT: Immunotherapy targeting MAGE-A3 in multiple myeloma (MM) could eradicate highly aggressive and proliferative clonal cell populations responsible for relapse. However, expression of many cancer-testis antigens, including MAGE-A3, can be heterogeneous, leading to the potential for tumor escape despite MAGE-A3-induced immunity. We hypothesized that a combination of the hypomethylating agent 5-azacitidine (5AC) and the histone deacetylase inhibitor (HDACi) MGCD0103 (MGC) could induce MAGE-A3 expression in MAGE-A3-negative MM, resulting in recognition and killing of MM cells by MAGE-A3-specific cytotoxic T lymphocytes (CTL). Gene expression analyses of MAGE-A3 expression in primary MM patient samples at diagnosis and relapse were completed to identify populations that would benefit from MAGE-A3 immunotherapy. MM cell lines were treated with 5AC and MGC. Real-time polymerase chain reaction (PCR) and Western blotting were performed to assess MAGE-A3 RNA and protein levels, respectively. Chromium-release assays and interferon (IFN) secretion assays were employed to ascertain MAGE-A3 CTL specificity against treated targets. Gene expression analysis revealed that MAGE-A3 is expressed in MM patients at diagnosis (25%) and at relapse (49%). We observed de novo expression of MAGE-A3 RNA and protein in MAGE-A3-negative cell lines treated with 5AC. MGC treatment alone did not induce expression but sequential 5AC/MGC treatment led to enhanced expression and augmented recognition by MAGE-A3-specific CTL, as assessed by (51)Cr-release assays (P = 0.047) and enzyme-linked immunosorbent assay (ELISA) for IFN-γ secretion (P = 0.004). MAGE-A3 is an attractive target for immunotherapy of MM and epigenetic modulation by 5AC, and MGC can induce MAGE-A3 expression and facilitate killing by MAGE-A3-specific CTL.
    Cytotherapy 05/2011; 13(5):618-28. DOI:10.3109/14653249.2010.529893 · 3.10 Impact Factor
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    ABSTRACT: Multiple myeloma (MM) is a paradigm for a malignant disease that exploits external stimuli of the microenvironment for growth and survival. A thorough understanding of the complex interactions between malignant plasma cells and their surrounding requires a detailed analysis of the transcriptional response of myeloma cells to environmental signals. We determined the changes in gene expression induced by interleukin (IL)-6, tumor necrosis factor-α, IL-21 or co-culture with bone marrow stromal cells in myeloma cell lines. Among a limited set of genes that were consistently activated in response to growth factors, a prominent transcriptional target of cytokine-induced signaling in myeloma cells was the gene encoding the serine/threonine kinase serum/glucocorticoid-regulated kinase 1 (SGK1), which is a down-stream effector of PI3-kinase. We could demonstrate a rapid, strong and sustained induction of SGK1 in the cell lines INA-6, ANBL-6, IH-1, OH-2 and MM.1S as well as in primary myeloma cells. Pharmacologic inhibition of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway abolished STAT3 phosphorylation and SGK1 induction. In addition, small hairpin RNA (shRNA)-mediated knock-down of STAT3 reduced basal and induced SGK1 levels. Furthermore, downregulation of SGK1 by shRNAs resulted in decreased proliferation of myeloma cell lines and reduced cell numbers. On the molecular level, this was reflected by the induction of cell cycle inhibitory genes, for example, CDKNA1/p21, whereas positively acting factors such as CDK6 and RBL2/p130 were downregulated. Our results indicate that SGK1 is a highly cytokine-responsive gene in myeloma cells promoting their malignant growth.
    Oncogene 04/2011; 30(28):3198-206. DOI:10.1038/onc.2011.79 · 8.56 Impact Factor
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    ABSTRACT: Myeloma survival varies markedly with International Staging System classification, presence of cytogenetic abnormalities, and, especially, gene expression profiling-based risk and delTP53 status, whose collective impact has not been examined in the context of specific therapies. The authors examined overall survival (OS), event-free survival (EFS), and complete response duration (CRD) in Total Therapy 2 with randomization to a control or thalidomide arm and in Total Therapy 3 with added bortezomib. Among 612 patients with complete data sets, multivariate analyses were used to investigate the relative contributions to OS, EFS, and CRD of International Staging System stage, cytogenetic abnormalities, and gene expression profiling-derived risk and delTP53 status, in the context of the 3 Total Therapy regimens. Whereas gene expression profiling risk segregated outcomes within all 3 International Staging System stages, International Staging System 3 conferred inferior prognosis only in low-risk myeloma, whereas the grave prognosis of high-risk disease was International Staging System-independent. After adjusting for gene expression profiling-defined high risk and delTP53 in multivariate analysis, International Staging System 3 and cytogenetic abnormalities both retained independent adverse implications for OS, EFS, and CRD. Among the 86% with low-risk disease, cytogenetic abnormalities and delTP53 both affected all 3 endpoints negatively, whereas the International Staging System 3 effect was limited to OS. Total Therapy 3 improved survival outcomes beyond results obtained with Total Therapy 2. In the genomic era, standard laboratory variables, such as International Staging System stage and presence of cytogenetic abnormalities, continue to impact survival after adjusting for gene expression profiling risk and delTP53 status, providing a basis for stratification in our current practice of gene expression profiling risk-based treatment assignment.
    Cancer 03/2011; 117(5):1001-9. DOI:10.1002/cncr.25535 · 4.90 Impact Factor
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    ABSTRACT: A panel of members of the 2009 International Myeloma Workshop developed guidelines for risk stratification in multiple myeloma. The purpose of risk stratification is not to decide time of therapy but to prognosticate. There is general consensus that risk stratification is applicable to newly diagnosed patients; however, some genetic abnormalities characteristic of poor outcome at diagnosis may suggest poor outcome if only detected at the time of relapse. Thus, in good-risk patients, it is necessary to evaluate for high-risk features at relapse. Although detection of any cytogenetic abnormality is considered to suggest higher-risk disease, the specific abnormalities considered as poor risk are cytogenetically detected chromosomal 13 or 13q deletion, t(4;14) and del17p, and detection by fluorescence in situ hybridization of t(4;14), t(14;16), and del17p. Detection of 13q deletion by fluorescence in situ hybridization only, in absence of other abnormalities, is not considered a high-risk feature. High serum β(2)-microglobulin level and International Staging System stages II and III, incorporating high β(2)-microglobulin and low albumin, are considered to predict higher risk disease. There was a consensus that the high-risk features will change in the future, with introduction of other new agents or possibly new combinations.
    Blood 02/2011; 117(18):4696-700. DOI:10.1182/blood-2010-10-300970 · 9.78 Impact Factor
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    ABSTRACT: Human placenta has emerged as a valuable source of transplantable cells of mesenchymal and hematopoietic origin for multiple cytotherapeutic purposes, including enhanced engraftment of hematopoietic stem cells, modulation of inflammation, bone repair, and cancer. Placenta-derived adherent cells (PDACs) are mesenchymal-like stem cells isolated from postpartum human placenta. Multiple myeloma is closely associated with induction of bone disease and large lytic lesions, which are often not repaired and are usually the sites of relapses. We evaluated the antimyeloma therapeutic potential, in vivo survival, and trafficking of PDACs in the severe combined immunodeficiency (SCID)-rab model of medullary myeloma-associated bone loss. Intrabone injection of PDACs into nonmyelomatous and myelomatous implanted bone in SCID-rab mice promoted bone formation by stimulating endogenous osteoblastogenesis, and most PDACs disappeared from bone within 4 weeks. PDACs inhibitory effects on myeloma bone disease and tumor growth were dose-dependent and comparable with those of fetal human mesenchymal stem cells (MSCs). Intrabone, but not subcutaneous, engraftment of PDACs inhibited bone disease and tumor growth in SCID-rab mice. Intratumor injection of PDACs had no effect on subcutaneous growth of myeloma cells. A small number of intravenously injected PDACs trafficked into myelomatous bone. Myeloma cell growth rate in vitro was lower in coculture with PDACs than with MSCs from human fetal bone or myeloma patients. PDACs also promoted apoptosis in osteoclast precursors and inhibited their differentiation. This study suggests that altering the bone marrow microenvironment with PDAC cytotherapy attenuates growth of myeloma and that PDAC cytotherapy is a promising therapeutic approach for myeloma osteolysis.
    Stem Cells 02/2011; 29(2):263-73. DOI:10.1002/stem.572 · 7.70 Impact Factor
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    S.S. Chavan, J.D. Shaughnessy, B. Barlogie, R.D. Edmondson
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    ABSTRACT: Affymetrix microarrays are widely used in genomics studies. Likewise, International Protein Index (IPI) hosted at European Bioinformatics Institute (EBI) and UniProtKB protein databases are commonly used in proteomics studies, more so in mass spectrometry based proteomics. However, a complete mapping from these protein identifiers (Ids) to Affymetrix Ids is currently unavailable resulting in loss of critical information while inter-converting between proteomics and genomics data-sets. This in turn has the potential to result in inaccurate downstream data analysis. Our objective is to maximize the mapping of IPI protein Ids to their corresponding Affymetrix probe set Id(s) to enable correlation of proteomics and genomics expression datasets. Thus, we have created mapping tables to link IPI Ids to their corresponding Affymetrix probe-set identifier(s). These mappings were obtained by parsing publicly available standard mapping annoannotations for IPI, Affymetrix, and Ensembl in order to establish a link between IPI and Affymetrix Id(s) using all possible identifier types that are common to both respective databases. A web-based tool, 'IPI2Affy' was created to enabletations for IPI, Affymetrix, and Ensembl in order to establish a link between IPI and Affymetrix Id(s) using all possible identifier types that are common to both respective databases. A web-based tool, 'IPI2Affy' was created to enable querying and retrieval of these Id conversions (
    Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on; 01/2011
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    ABSTRACT: Induction of osteolytic bone lesions in multiple myeloma is caused by an uncoupling of osteoclastic bone resorption and osteoblastic bone formation. Current management of myeloma bone disease is limited to the use of antiresorptive agents such as bisphosphonates. We tested the effects of daily administered parathyroid hormone (PTH) on bone disease and myeloma growth, and we investigated molecular mechanisms by analyzing gene expression profiles of unique myeloma cell lines and primary myeloma cells engrafted in SCID-rab and SCID-hu mouse models. PTH resulted in increased bone mineral density of myelomatous bones and reduced tumor burden, which reflected the dependence of primary myeloma cells on the bone marrow microenvironment. Treatment with PTH also increased bone mineral density of uninvolved murine bones in myelomatous hosts and bone mineral density of implanted human bones in nonmyelomatous hosts. In myelomatous bone, PTH markedly increased the number of osteoblasts and bone-formation parameters, and the number of osteoclasts was unaffected or moderately reduced. Pretreatment with PTH before injecting myeloma cells increased bone mineral density of the implanted bone and delayed tumor progression. Human global gene expression profiling of myelomatous bones from SCID-hu mice treated with PTH or saline revealed activation of multiple distinct pathways involved in bone formation and coupling; involvement of Wnt signaling was prominent. Treatment with PTH also downregulated markers typically expressed by osteoclasts and myeloma cells, and altered expression of genes that control oxidative stress and inflammation. PTH receptors were not expressed by myeloma cells, and PTH had no effect on myeloma cell growth in vitro. We conclude that PTH-induced bone formation in myelomatous bones is mediated by activation of multiple signaling pathways involved in osteoblastogenesis and attenuated bone resorption and myeloma growth; mechanisms involve increased osteoblast production of anti-myeloma factors and minimized myeloma induction of inflammatory conditions.
    PLoS ONE 12/2010; 5(12):e15233. DOI:10.1371/journal.pone.0015233 · 3.53 Impact Factor
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    ABSTRACT: We assessed the independent predictive values of the serum markers free prostate specific antigen, proenzyme prostate specific antigen, neuroendocrine marker and Dickkopf-1 compared to serum prostate specific antigen and other standard risk factors for early prostate cancer detection. From the prospectively collected SABOR cohort 250 prostate cancer cases, and 250 mean age matched and proportion of African-American race/ethnicity matched controls were selected who had a prior available prostate specific antigen and digital rectal examination. Serum samples were obtained, and free prostate specific antigen, [-2]proenzyme prostate specific antigen, Dickkopf-1 and neuroendocrine marker were measured. AUC, sensitivities and specificities were calculated, and multivariable logistic regression was used to assess the independent predictive value compared to prostate specific antigen, digital rectal examination, family history, prior biopsy history, race/ethnicity and age. The AUCs (95% CI) were 0.76 (0.71, 0.8) for free prostate specific antigen, 0.72 (0.67, 0.76) for [-2]proenzyme prostate specific antigen, 0.76 (0.72, 0.8) for %free prostate specific antigen, 0.61 (0.56, 0.66) for %[-2]proenzyme prostate specific antigen, 0.73 (0.68, 0.77) for prostate health index, 0.53 (0.48, 0.58) for Dickkopf-1 and 0.53 (0.48, 0.59) for neuroendocrine marker. In the 2 to 10 ng/ml prostate specific antigen range the AUCs (95% CI) were 0.58 (0.49, 0.67) for free prostate specific antigen, 0.53 (0.44, 0.62) for [-2]proenzyme prostate specific antigen, 0.67 (0.59, 0.75) for %free prostate specific antigen, 0.57 (0.49, 0.65) for %[-2]proenzyme prostate specific antigen and 0.59 (0.51, 0.67) for phi. Only %free prostate specific antigen retained independent predictive value compared to the traditional risk factors. Free prostate specific antigen retained independent diagnostic usefulness for prostate cancers detected through prostate specific antigen and digital rectal examination screening. Prostate specific antigen isoforms are highly correlated with prostate specific antigen. Future research is needed to identify new markers associated with prostate cancer through different mechanisms.
    The Journal of urology 11/2010; 185(1):104-10. DOI:10.1016/j.juro.2010.08.088 · 3.75 Impact Factor
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    ABSTRACT: Proliferation of malignant plasma cells is a strong adverse prognostic factor in multiple myeloma and simultaneously targetable by available (e.g. tubulin polymerase inhibitors) and upcoming (e.g. aurora kinase inhibitors) compounds. We assessed proliferation using gene expression-based indices in 757 samples including independent cohorts of 298 and 345 samples of CD138-purified myeloma cells from previously untreated patients undergoing high-dose chemotherapy, together with clinical prognostic factors, chromosomal aberrations, and gene expression-based high-risk scores. In the two cohorts, 43.3% and 39.4% of the myeloma cell samples showed a proliferation index above the median plus three standard deviations of normal bone marrow plasma cells. Malignant plasma cells of patients in advanced stages or those harboring disease progression-associated gain of 1q21 or deletion of 13q14.3 showed significantly higher proliferation indices; patients with gain of chromosome 9, 15 or 19 (hyperdiploid samples) had significantly lower proliferation indices. Proliferation correlated with the presence of chromosomal aberrations in metaphase cytogenetics. It was significantly predictive for event-free and overall survival in both cohorts, allowed highly predictive risk stratification (e.g. event-free survival 12.7 versus 26.2 versus 40.6 months, P < 0.001) of patients, and was largely independent of clinical prognostic factors, e.g. serum β₂-microglobulin, International Staging System stage, associated high-risk chromosomal aberrations, e.g. translocation t(4;14), and gene expression-based high-risk scores. Proliferation assessed by gene expression profiling, being independent of serum-β₂-microglobulin, International Staging System stage, t(4;14), and gene expression-based risk scores, is a central prognostic factor in multiple myeloma. Surrogating a biological targetable variable, gene expression-based assessment of proliferation allows selection of patients for risk-adapted anti-proliferative treatment on the background of conventional and gene expression-based risk factors.
    Haematologica 09/2010; 96(1):87-95. DOI:10.3324/haematol.2010.030296 · 5.87 Impact Factor
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    ABSTRACT: The impact of cumulative dosing and premature drug discontinuation (PMDD) of bortezomib (V), thalidomide (T), and dexamethasone (D) on overall survival (OS), event-free survival (EFS), time to next therapy, and post-relapse survival in Total Therapy 3 were examined, using time-dependent methodology, relevant to induction, peritransplantation, consolidation, and maintenance phases. Univariately, OS and EFS were longer in case higher doses were used of all agents during induction, consolidation (except T), and maintenance (except V and T). The favorable OS and EFS impact of D induction dosing provided the rationale for examining the expression of glucocorticoid receptor NR3C1, top-tertile levels of which significantly prolonged OS and EFS and rendered outcomes independent of D and T dosing, whereas T and D, but not V, dosing was critical to outcome improvement in the bottom-tertile NR3C1 setting. PMDD of V was an independent highly adverse feature for OS (hazard ratio = 6.44; P < .001), whereas PMDD of both T and D independently imparted shorter time to next therapy. The absence of adverse effects on postrelapse survival of dosing of any VTD components and indeed a benefit from V supports the use up-front of all active agents in a dose-dense and dose-intense fashion, as practiced in Total Therapy 3, toward maximizing myeloma survival.
    Blood 08/2010; 116(8):1220-7. DOI:10.1182/blood-2010-01-264333 · 9.78 Impact Factor
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    ABSTRACT: Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
    Nature Biotechnology 08/2010; 28(8):827-38. DOI:10.1038/nbt.1665 · 39.08 Impact Factor
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    ABSTRACT: In Total Therapy 2, after randomly assigning 323 patients with myeloma to thalidomide and 345 to a control arm, no difference was observed in overall survival, with a median follow-up of 42 months, although at 72 months, survival was superior on the thalidomide arm in the one third exhibiting cytogenetic abnormalities (CA). After further follow-up of 87 months, we examined, in reiterative analyses, the effect of increasing time intervals on clinical outcomes relevant to baseline prognostic variables and treatment randomization. We investigated clinical trial end points as a function of increasing time intervals from protocol enrollment to determine consistencies of results by treatment and prognostic variables. The complete congruence of serial survival plots for both study arms combined attested to stable patient characteristics over the time of accrual and the quality of follow-up management. Presence of CA was associated with consistently inferior survival curves from year 3 onward. Although 80% of patients randomly assigned to thalidomide discontinued study drug after 2 years because of toxicity, its clinical benefit did not reach statistical significance until year 10. The relative ranking order in multivariate models of prognostic factors remained stable over time. Decline in initially high hazard ratio values of gene array-defined high risk is consistent with an initial crisis phase that is time limited. Reporting potentially time-sensitive features as a part of clinical trial results will enable the critical reader to judge the robustness of prognostic factors and the time sensitivity of outcome predictors, with important implications for future trial designs.
    Journal of Clinical Oncology 06/2010; 28(18):3023-7. DOI:10.1200/JCO.2009.26.4465 · 17.88 Impact Factor
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    ABSTRACT: The Total Therapy 3 trial 2003-33 enrolled 303 newly diagnosed multiple myeloma patients and was noted to provide superior clinical outcomes compared with predecessor trial Total Therapy 2, especially in gene expression profiling (GEP)-defined low-risk disease. We report here on the results of successor trial 2006-66 with 177 patients, using bortezomib, lenalidomide, and dexamethasone maintenance for 3 years versus bortezomib, thalidomide, and dexamethasone in year 1 and thalidomide/dexamethasone in years 2 and 3 in the 2003-33 protocol. Overall survival (OS) and event-free survival (EFS) plots were super-imposable for the 2 trials, as were onset of complete response and complete response duration (CRD), regardless of GEP risk. GEP-defined high-risk designation, pertinent to 17% of patients, imparted inferior OS, EFS, and CRD in both protocols and, on multivariate analysis, was the sole adverse feature affecting OS, EFS, and CRD. Mathematical modeling of CRD in low-risk myeloma predicted a 55% cure fraction (P < .001). Despite more rapid onset and higher rate of CR than in other molecular subgroups, CRD was inferior in CCND1 without CD20 myeloma, resembling outcomes in MAF/MAFB and proliferation entities. The robustness of the GEP risk model should be exploited in clinical trials aimed at improving the notoriously poor outcome in high-risk disease.
    Blood 05/2010; 115(21):4168-73. DOI:10.1182/blood-2009-11-255620 · 9.78 Impact Factor
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    M Santra, J D Shaughnessy, W T Bellamy
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    ABSTRACT: Immunohistochemistry (IHC) is an important tool used for diagnosis and prognosis of several hematological malignancies, and it frequently is used for quantitative and qualitative analysis of expression of different protein biomarkers in tissue sections. To understand the histopathological alterations in multiple myeloma (MM), IHC analysis of bone marrow (BM) biopsy is commonly used. Owing to the harsh decalcification process generally used for processing of bone marrow biopsies, however, protein epitopes occasionally are rendered unsuitable for IHC detection. We have developed a novel technique for processing BM spicule samples into a fibrin clot matrix that allows IHC detection of MM protein markers. This method does not require decalcification and results in a consistent, reliable assay. Using paired BM spicule-clot and BM core biopsies from patients diagnosed with multiple myeloma, we studied six MM related antibodies including kappa and lambda immunoglobulin light chains, CD56, CD138, CYR61 and DKK1.
    Biotechnic & Histochemistry 05/2010; 86(2):119-23. DOI:10.3109/10520290903565978 · 1.00 Impact Factor
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    ABSTRACT: MicroRNAs (miRNAs) are noncoding RNAs that regulate global gene expression. miRNAs often act synergistically to repress target genes, and their dysregulation can contribute to the initiation and progression of a variety of cancers. The clinical relationship between global expression of miRNA and mRNA in cancer has not been studied in detail. We used whole-genome microarray analyses of CD138-enriched plasma cells from 52 newly diagnosed cases of multiple myeloma to correlate miRNA expression profiles with a validated mRNA-based risk stratification score, proliferation index, and predefined gene sets. In stark contrast to mRNAs, we discovered that all tested miRNAs were significantly up-regulated in high-risk disease as defined by a validated 70-gene risk score (P < 0.01) and proliferation index (P < 0.05). Increased expression of EIF2C2/AGO2, a master regulator of the maturation and function of miRNAs and a component of the 70-gene mRNA risk model, is driven by DNA copy number gains in MM. Silencing of AGO2 dramatically decreased viability in MM cell lines. Genome-wide elevated expression of miRNAs in high-risk MM may be secondary to deregulation of AGO2 and the enzyme complexes that regulate miRNA maturation and function.
    Proceedings of the National Academy of Sciences 04/2010; 107(17):7904-9. DOI:10.1073/pnas.0908441107 · 9.81 Impact Factor

Publication Stats

14k Citations
2,011.58 Total Impact Points


  • 2013–2015
    • Signal Genetics
      New York, New York, United States
  • 1999–2013
    • University of Arkansas at Little Rock
      Little Rock, Arkansas, United States
  • 1999–2012
    • University of Arkansas for Medical Sciences
      • Department of Obstetrics and Gynecology
      Little Rock, Arkansas, United States
  • 2009
    • University of Arkansas
      Fayetteville, Arkansas, United States
    • Cancer Research and Biostatistics
      Seattle, Washington, United States
  • 2008
    • The Ohio State University
      • Department of Internal Medicine
      Columbus, OH, United States
  • 2007
    • Heinrich-Heine-Universität Düsseldorf
      • Institute of Developmental and Molecular Biology of the Animals
      Düsseldorf, North Rhine-Westphalia, Germany
    • The Rockefeller University
      New York, New York, United States
    • Uppsala University
      • Department of Medical Biochemistry and Microbiology
      Uppsala, Uppsala, Sweden
    • SickKids
      • Centre of Applied Genomics (TCAG)
      Toronto, Ontario, Canada
    • University of Alabama at Birmingham
      • Department of Pathology
      Birmingham, AL, United States
  • 2003
    • Harvard University
      Cambridge, Massachusetts, United States
  • 2001
    • Cornell University
      • Department of Medicine
      Итак, New York, United States
  • 1989–1994
    • National Cancer Institute (USA)
      • Laboratory of Population Genetics
      Maryland, United States
  • 1993
    • National Institutes of Health
      • Laboratory of Genetics (LG)
      Bethesda, MD, United States