Publications by authors named "Rebecca Tagett"

27 Publications

  • Page 1 of 1

Assessment of the Cytoprotective Effects of High-Dose Valproic Acid Compared to a Clinically Used Lower Dose.

J Surg Res 2021 May 11;266:125-141. Epub 2021 May 11.

Department of Surgery, University of Michigan Health System, Ann Arbor, Michigan; Department of Surgery, Feinberg School of Medicine/Northwestern University, Chicago, Illinois. Electronic address:

Objective: Valproic acid (VPA) treatment improves survival in animal models of injuries on doses higher than those allowed by Food and Drug Administration (FDA). We investigated the proteomic alterations induced by a single high-dose (140mg/kg) of VPA (VPA140) compared to the FDA-approved dose of 30mg/kg (VPA30) in healthy humans. We also describe the proteomic and transcriptomic changes induced by VPA140 in an injured patient. We hypothesized that VPA140 would induce cytoprotective changes in the study participants.

Methods: Serum samples were obtained from healthy subjects randomized to two groups; VPA140 and VPA30 at 3 timepoints: 0h(baseline), 2h, and 24h following infusion(n = 3/group). Samples were also obtained from an injured patient that received VPA140 at 0h, 6h and 24h following infusion. Proteomic analyses were performed using liquid chromatography-mass spectrometry (LC-MS/MS), and transcriptomic analysis was performed using RNA-sequencing. Differentially expressed (DE) proteins and genes were identified for functional annotation and pathway analysis using iPathwayGuide and gene set enrichment analysis (GSEA), respectively.

Results: For healthy individuals, a dose comparison was performed between VPA140 and VPA30 groups at 2 and 24 h. Functional annotation showed that top biological processes in VPA140 versus VPA30 analysis at 2 h included regulation of fatty acid (P = 0.002) and ATP biosynthesis (P = 0.007), response to hypoxia (P = 0.017), cell polarity regulation (P = 0.031), and sequestration of calcium ions (P = 0.031). Top processes at 24 h in VPA140 versus VPA30 analysis included amino acid metabolism (P = 0.023), collagen catabolism (P = 0.023), and regulation of protein breakdown (P = 0.023). In the injured patient, annotation of the DE proteins in the serum showed that top biological processes at 2 h included neutrophil chemotaxis (P = 0.002), regulation of cellular response to heat (P = 0.008), regulation of oxidative stress (P = 0.008) and regulation of apoptotic signaling pathway (P = 0.008). Top biological processes in the injured patient at 24 h included autophagy (P = 0.01), glycolysis (P = 0.01), regulation of apoptosis (P = 0.01) and neuron apoptotic processes (P = 0.02).

Conclusions: VPA140 induces cytoprotective changes in human proteome not observed in VPA30. These changes may be responsible for its protective effects in response to injuries.
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http://dx.doi.org/10.1016/j.jss.2021.03.025DOI Listing
May 2021

Pilot deep RNA sequencing of worker blood samples from Singapore printing industry for occupational risk assessment.

NanoImpact 2020 Jul 13;19. Epub 2020 Aug 13.

Center for Nanotechnology and Nanotoxicology, Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.

Several engineered nanomaterials (ENMs) are used in toner-based printing equipment (TPE) including laser printers and photocopiers to improve toner performance. High concentration of airborne nanoparticles due to TPE emissions has been documented in copy centers and chamber studies. Recent animal inhalation studies by our group suggested exposure to laser printer-emitted nanoparticles (PEPs) increased cardiovascular risk by impairing ventricular performance and inducing hypertension and arrhythmia, consistent with global transcriptomic and metabolomic profiling results. There has been no genome-wide transcriptomic analysis of workers exposed to TPE emissions to systematically assess the occupational exposure health risks. In this pilot study, deep RNA sequencing of blood samples of workers in two printing companies in Singapore was performed. The genome-scale analysis of the blood samples from TPE exposed workers revealed perturbed transcriptional activities related to inflammatory and immune responses, metabolism, cardiovascular impairment, neurological diseases, oxidative stress, physical morphogenesis/deformation, and cancer, when compared with the control peers (office workers). Many of these disease risks associated with particle inhalation exposures in such work environments were consistent with the observation from the PEPs rat inhalation studies. In particular, the cell adhesion molecules (CAMs) was a top significantly perturbed pathway in blood samples from exposed workers compared with the office workers in both companies. The protein expression of sICAM was verified in plasma of exposed workers, showing a positive correlation with daily average nanoparticle concentration in indoor air measured in these two companies. Larger scale genomic and molecular epidemiology studies in copier operators are warranted in order to assess potential risks from such particulate matter exposures.
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http://dx.doi.org/10.1016/j.impact.2020.100248DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840153PMC
July 2020

Modulation of Brain Transcriptome by Combined Histone Deacetylase Inhibition and Plasma Treatment Following Traumatic Brain Injury and Hemorrhagic Shock.

Shock 2021 01;55(1):110-120

Department of Surgery, University of Michigan, Ann Arbor, Michigan.

Introduction: We previously showed that the addition of valproic acid (VPA), a histone deacetylase inhibitor, to fresh frozen plasma (FFP) resuscitation attenuates brain lesion size and swelling following traumatic brain injury (TBI) and hemorrhagic shock (HS). The goal of this study was to use computational biology tools to investigate the effects of FFP+VPA on the brain transcriptome following TBI+HS.

Methods: Swine underwent TBI+HS, kept in shock for 2 h, and resuscitated with FFP or FFP + VPA (n = 5/group). After 6 h of observation, brain RNA was isolated and gene expression was analyzed using a microarray. iPathwayGuide, Gene Ontology (GO), Gene-Set Enrichment Analysis, and Enrichment Mapping were used to identify significantly impacted genes and transcriptomic networks.

Results: Eight hundred differentially expressed (DE) genes were identified out of a total of 9,118 genes. Upregulated genes were involved in promotion of cell division, proliferation, and survival, while downregulated genes were involved in autophagy, cell motility, neurodegenerative diseases, tumor suppression, and cell cycle arrest. Seven hundred ninety-one GO terms were significantly enriched. A few major transcription factors, such as TP53, NFKB3, and NEUROD1, were responsible for modulating hundreds of other DE genes. Network analysis revealed attenuation of interconnected genes involved in inflammation and tumor suppression, and an upregulation of those involved in cell proliferation and differentiation.

Conclusion: Overall, these results suggest that VPA treatment creates an environment that favors production of new neurons, removal of damaged cells, and attenuation of inflammation, which could explain its previously observed neuroprotective effects.
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http://dx.doi.org/10.1097/SHK.0000000000001605DOI Listing
January 2021

Kinome Profiling Reveals Abnormal Activity of Kinases in Skeletal Muscle From Adults With Obesity and Insulin Resistance.

J Clin Endocrinol Metab 2020 Mar;105(3)

Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.

Context: Obesity-related insulin resistance (OIR) is one of the main contributors to type 2 diabetes and other metabolic diseases. Protein kinases are implicated in insulin signaling and glucose metabolism. Molecular mechanisms underlying OIR involving global kinase activities remain incompletely understood.

Objective: To investigate abnormal kinase activity associated with OIR in human skeletal muscle.

Design: Utilization of stable isotopic labeling-based quantitative proteomics combined with affinity-based active enzyme probes to profile in vivo kinase activity in skeletal muscle from lean control (Lean) and OIR participants.

Participants: A total of 16 nondiabetic adults, 8 Lean and 8 with OIR, underwent hyperinsulinemic-euglycemic clamp with muscle biopsy.

Results: We identified the first active kinome, comprising 54 active protein kinases, in human skeletal muscle. The activities of 23 kinases were different in OIR muscle compared with Lean muscle (11 hyper- and 12 hypo-active), while their protein abundance was the same between the 2 groups. The activities of multiple kinases involved in adenosine monophosphate-activated protein kinase (AMPK) and p38 signaling were lower in OIR compared with Lean. On the contrary, multiple kinases in the c-Jun N-terminal kinase (JNK) signaling pathway exhibited higher activity in OIR vs Lean. The kinase-substrate-prediction based on experimental data further confirmed a potential downregulation of insulin signaling (eg, inhibited phosphorylation of insulin receptor substrate-1 and AKT1/2).

Conclusions: These findings provide a global view of the kinome activity in OIR and Lean muscle, pinpoint novel specific impairment in kinase activities in signaling pathways important for skeletal muscle insulin resistance, and may provide potential drug targets (ie, abnormal kinase activities) to prevent and/or reverse skeletal muscle insulin resistance in humans.
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http://dx.doi.org/10.1210/clinem/dgz115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6991621PMC
March 2020

IDH1-R132H acts as a tumor suppressor in glioma via epigenetic up-regulation of the DNA damage response.

Sci Transl Med 2019 02;11(479)

Department of Pediatrics, Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA 30322, USA.

Patients with glioma whose tumors carry a mutation in isocitrate dehydrogenase 1 (IDH1) are younger at diagnosis and live longer. mutations co-occur with other molecular lesions, such as 1p/19q codeletion, inactivating mutations in the tumor suppressor protein 53 ) gene, and loss-of-function mutations in alpha thalassemia/mental retardation syndrome X-linked gene (). All adult low-grade gliomas (LGGs) harboring ATRX loss also express the IDH1 mutation. The current molecular classification of LGGs is based, partly, on the distribution of these mutations. We developed a genetically engineered mouse model harboring IDH1, and inactivating mutations, and activated NRAS G12V. Previously, we established that ATRX deficiency, in the context of wild-type IDH1, induces genomic instability, impairs nonhomologous end-joining DNA repair, and increases sensitivity to DNA-damaging therapies. In this study, using our mouse model and primary patient-derived glioma cultures with IDH1 mutations, we investigated the function of IDH1 in the context of TP53 and ATRX loss. We discovered that IDH1 expression in the genetic context of and gene inactivation (i) increases median survival in the absence of treatment, (ii) enhances DNA damage response (DDR) via epigenetic up-regulation of the ataxia-telangiectasia-mutated (ATM) signaling pathway, and (iii) elicits tumor radioresistance. Accordingly, pharmacological inhibition of ATM or checkpoint kinases 1 and 2, essential kinases in the DDR, restored the tumors' radiosensitivity. Translation of these findings to patients with IDH1 glioma harboring TP53 and ATRX loss could improve the therapeutic efficacy of radiotherapy and, consequently, patient survival.
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http://dx.doi.org/10.1126/scitranslmed.aaq1427DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400220PMC
February 2019

T Helper 1 Cellular Immunity Toward Recoverin Is Enhanced in Patients With Active Autoimmune Retinopathy.

Front Med (Lausanne) 2018 13;5:249. Epub 2018 Sep 13.

Department of Ophthalmology and Visual Sciences-Kellogg Eye Center, University of Michigan Medical School, Ann Arbor, MI, United States.

Autoimmune retinopathy (AIR) causes rapidly progressive vision loss that is treatable but often is confused with other forms of retinal degeneration including retinitis pigmentosa (RP). Measurement of anti-retinal antibodies (ARA) by Western blot is a commonly used laboratory assay that supports the diagnosis yet does not reflect current disease activity. To search for better diagnostic indicators, this study was designed to compare immune biomarkers and responses toward the retinal protein, recoverin, between newly diagnosed AIR patients, slow progressing RP patients and healthy controls. All individuals had measurable anti-recoverin IgG and IgM antibodies by ELISA regardless of disease status or Western blot results. Many AIR patients had elevated anti-recoverin IgG1 levels and a strong cellular response toward recoverin dominated by IFNγ. RP patients and controls responded to recoverin with a lower IFNγ response that was balanced by IL-10 production. Both AIR and RP patients displayed lower levels of total peripheral blood mononuclear cells that were due to reductions of CD4 T cells. A comparison of messenger RNA (mRNA) for immune-related genes in whole blood of AIR patients versus RP patients or controls indicated lower expression of ATG5 and PTPN22 and higher expression of several genes involved in T cell signaling/transcription and adhesion. These data indicate that an immune response toward recoverin is normal in humans, but that in AIR patients the balance shifts dramatically toward higher IFNγ production and cellular activation.
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http://dx.doi.org/10.3389/fmed.2018.00249DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146138PMC
September 2018

DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis.

Proc IEEE Inst Electr Electron Eng 2017 Mar 31;105(3):496-515. Epub 2016 Mar 31.

Department of Computer Science and the Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48202.

Identifying the pathways and mechanisms that are significantly impacted in a given phenotype is challenging. Issues include patient heterogeneity and noise. Many experiments do not have a large enough sample size to achieve the statistical power necessary to identify significantly impacted pathways. Meta-analysis based on combining p-values from individual experiments has been used to improve power. However, all classical meta-analysis approaches work under the assumption that the p-values produced by experiment-level statistical tests follow a uniform distribution under the null hypothesis. Here we show that this assumption does not hold for three mainstream pathway analysis methods, and significant bias is likely to affect many, if not all such meta-analysis studies. We introduce DANUBE, a novel and unbiased approach to combine statistics computed from individual studies. Our framework uses control samples to construct empirical null distributions, from which empirical p-values of individual studies are calculated and combined using either a Central Limit Theorem approach or the additive method. We assess the performance of DANUBE using four different pathway analysis methods. DANUBE is compared with five meta-analysis approaches, as well as with a pathway analysis approach that employs multiple datasets (MetaPath). The 25 approaches have been tested on 16 different datasets related to two human diseases, Alzheimer's disease (7 datasets) and acute myeloid leukemia (9 datasets). We demonstrate that DANUBE overcomes bias in order to consistently identify relevant pathways. We also show how the framework improves results in more general cases, compared to classical meta-analysis performed with common experiment-level statistical tests such as Wilcoxon and t-test.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919277PMC
http://dx.doi.org/10.1109/jproc.2015.2507119DOI Listing
March 2017

Dural Cells Release Factors Which Promote Cancer Cell Malignancy and Induce Immunosuppressive Markers in Bone Marrow Myeloid Cells.

Neurosurgery 2018 12;83(6):1306-1316

Veterans Affairs Medical Center, Ann Arbor, Michigan.

Background: Thirty per cent of cancer patients develop spine metastases with a substantial number leading to spinal cord compression and neurological deficits. Many demonstrate a propensity toward metastasis to the posterior third of the vertebral body. The dura, the outer layer of the meninges, lies in intimate contact with the posterior border of the vertebral body and has been shown to influence adjacent bone. The effects of the dura on bone marrow and cancer cells have not been examined. Understanding the biology of spinal metastasis will provide insights into mechanisms of cancer growth and allow for new treatment strategies.

Objective: To examine the extent to which dura influences bone marrow/tumor cell metastatic characteristics.

Methods: Dura conditioned media (DCM) from primary dura was examined for the ability to stimulate tumor cell proliferation/invasion and to alter bone marrow cell populations. RNA sequencing of dural fibroblasts was performed to examine expression of cytokines and growth factors.

Results: DCM induced a significant increase in invasion and proliferation of multiple tumor cell lines, and of patient-derived primary spinal metastatic cells. DCM also increased the proliferation of bone marrow myeloid cells, inducing expression of immunosuppressive markers. RNA sequencing of dural fibroblasts demonstrated abundant expression of cytokines and growth factors involved in cancer/immune pathways.

Conclusion: Factors released by primary dural cells induce proliferation of tumor cells and alter bone marrow to create a fertile environment for tumor growth. The dura therefore may play an important role in the increased incidence of metastases to adjacent bone.
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http://dx.doi.org/10.1093/neuros/nyx626DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7191887PMC
December 2018

A novel approach for data integration and disease subtyping.

Genome Res 2017 12 24;27(12):2025-2039. Epub 2017 Oct 24.

Department of Computer Science, Wayne State University, Detroit, Michigan 48202, USA.

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called erturbation clustering for data tegration and disease ubtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data.
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http://dx.doi.org/10.1101/gr.215129.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741060PMC
December 2017

A novel pathway analysis approach based on the unexplained disregulation of genes.

Proc IEEE Inst Electr Electron Eng 2017 Mar 24;105(3):482-495. Epub 2016 Mar 24.

Department of Computer Science, Wayne State University, Detroit, MI, USA.

A crucial step in the understanding of any phenotype is the correct identification of the signaling pathways that are significantly impacted in that phenotype. However, most current pathway analysis methods produce both false positives as well as false negatives in certain circumstances. We hypothesized that such incorrect results are due to the fact that the existing methods fail to distinguish between the primary dis-regulation of a given gene itself and the effects of signaling coming from upstream. Furthermore, a modern whole-genome experiment performed with a next-generation technology spends a great deal of effort to measure the entire set of 30,000-100,000 transcripts in the genome. This is followed by the selection of a few hundreds differentially expressed genes, step that literally discards more than 99% of the collected data. We also hypothesized that such a drastic filtering could discard many genes that play crucial roles in the phenotype. We propose a novel topology-based pathway analysis method that identifies significantly impacted pathways using the entire set of measurements, thus allowing the full use of the data provided by NGS techniques. The results obtained on 24 real data sets involving 12 different human diseases, as well as on 8 yeast knock-out data sets show that the proposed method yields significant improvements with respect to the state-of-the-art methods: SPIA, GSEA and GSA.

Availability: Primary dis-regulation analysis is implemented in R and included in ROntoTools Bioconductor package (versions ≥ 2.0.0). https://www.bioconductor.org/packages/release/bioc/html/ROntoTools.html.
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http://dx.doi.org/10.1109/JPROC.2016.2531000DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190577PMC
March 2017

Overcoming the matched-sample bottleneck: an orthogonal approach to integrate omic data.

Sci Rep 2016 07 12;6:29251. Epub 2016 Jul 12.

Wayne State University, Department of Computer Science, Detroit, 48202, Michigan, USA.

MicroRNAs (miRNAs) are small non-coding RNA molecules whose primary function is to regulate the expression of gene products via hybridization to mRNA transcripts, resulting in suppression of translation or mRNA degradation. Although miRNAs have been implicated in complex diseases, including cancer, their impact on distinct biological pathways and phenotypes is largely unknown. Current integration approaches require sample-matched miRNA/mRNA datasets, resulting in limited applicability in practice. Since these approaches cannot integrate heterogeneous information available across independent experiments, they neither account for bias inherent in individual studies, nor do they benefit from increased sample size. Here we present a novel framework able to integrate miRNA and mRNA data (vertical data integration) available in independent studies (horizontal meta-analysis) allowing for a comprehensive analysis of the given phenotypes. To demonstrate the utility of our method, we conducted a meta-analysis of pancreatic and colorectal cancer, using 1,471 samples from 15 mRNA and 14 miRNA expression datasets. Our two-dimensional data integration approach greatly increases the power of statistical analysis and correctly identifies pathways known to be implicated in the phenotypes. The proposed framework is sufficiently general to integrate other types of data obtained from high-throughput assays.
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http://dx.doi.org/10.1038/srep29251DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941544PMC
July 2016

SPATIAL: A System-level PAThway Impact AnaLysis approach.

Nucleic Acids Res 2016 06 18;44(11):5034-44. Epub 2016 May 18.

Department of Computer Science, Wayne State University, Detroit, MI 48202, USA Department of Obstetrics & Gynecology, Wayne State University, Detroit, MI 48202, USA.

The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P-values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
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http://dx.doi.org/10.1093/nar/gkw429DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914126PMC
June 2016

Quantitative proteomics reveals novel protein interaction partners of PP2A catalytic subunit in pancreatic β-cells.

Mol Cell Endocrinol 2016 Mar 9;424:1-11. Epub 2016 Jan 9.

Department of Pharmaceutical Sciences, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI, 48201, USA. Electronic address:

Protein phosphatase 2A (PP2A) is one of the major serine/threonine phosphatases. We hypothesize that PP2A regulates signaling cascades in pancreatic β-cells in the context of glucose-stimulated insulin secretion (GSIS). Using co-immunoprecipitation (co-IP) and tandem mass spectrometry, we globally identified the protein interaction partners of the PP2A catalytic subunit (PP2Ac) in insulin-secreting pancreatic β-cells. Among the 514 identified PP2Ac interaction partners, 476 were novel. This represents the first global view of PP2Ac protein-protein interactions caused by hyperglycemic conditions. Additionally, numerous PP2Ac partners were found involved in a variety of signaling pathways in the β-cell function, such as insulin secretion. Our data suggest that PP2A interacts with various signaling proteins necessary for physiological insulin secretion as well as signaling proteins known to regulate cell dysfunction and apoptosis in the pancreatic β-cells.
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http://dx.doi.org/10.1016/j.mce.2016.01.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779412PMC
March 2016

A novel bi-level meta-analysis approach: applied to biological pathway analysis.

Bioinformatics 2016 Feb 14;32(3):409-16. Epub 2015 Oct 14.

Department of Computer Science and Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48202, USA.

Motivation: The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study.

Results: We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis.

Availability And Implementation: The R scripts are available on demand from the authors.

Contact: [email protected]

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btv588DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006307PMC
February 2016

Gene-expression Profiling in Non-small Cell Lung Cancer with Invasion of Mediastinal Lymph Nodes for Prognosis Evaluation.

Cancer Genomics Proteomics 2015 Sep-Oct;12(5):231-42

Center of Digestive Diseases and Liver Transplantation, Fundeni Clinical Institute, Bucharest, Romania.

Background/aim: The aim of the study was to determine the pathways and expression profile of the genes that might predict response to neoadjuvant chemotherapy in patients with stage IIIA non-small cell lung cancer (NSCLC).

Materials And Methods: We evaluated, by microarray, the gene-expression profile of tumoral mediastinal lymph node samples surgically removed from 27 patients with stage IIIA NSCLC before neoadjuvant chemotherapy treatment. Depending on the response to the induction treatment, the patients were divided in two groups: group A: patients whose disease evolved, stabilized or who had minor response to chemotherapy, and group B: patients whose disease stabilized or had major response to chemotherapy.

Results: The microarray experiments identified 1,127 genes with a modified expression in the tumoral tissue compared to normal tissue with p≤0.05 and 44 genes with p≤0.01. The identified up-regulated genes between tumoral versus normal tissue included collagen, type I, alpha 1 (COL1A1), inhibin beta A (INHBA) and thioredoxin interacting protein (TXNIP). Pathways identified with a false-discovery rate of <0.005 included: cytokine pathways, focal adhesion or extracellular matrix receptor interaction.

Conclusion: Our approach identified important characteristics of NSCLC and pointed-out molecular differences between sub-groups of patients based on their response to therapy.
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June 2016

Increased interaction with insulin receptor substrate 1, a novel abnormality in insulin resistance and type 2 diabetes.

Diabetes 2014 Jun 28;63(6):1933-47. Epub 2014 Feb 28.

Department of Pharmaceutical Sciences, Eugene Applebaum College of Pharmacy/Health Sciences, Wayne State University, Detroit, MI

Insulin receptor substrate 1 (IRS1) is a key mediator of insulin signal transduction. Perturbations involving IRS1 complexes may lead to the development of insulin resistance and type 2 diabetes (T2D). Surprisingly little is known about the proteins that interact with IRS1 in humans under health and disease conditions. We used a proteomic approach to assess IRS1 interaction partners in skeletal muscle from lean healthy control subjects (LCs), obese insulin-resistant nondiabetic control subjects (OCs), and participants with T2D before and after insulin infusion. We identified 113 novel endogenous IRS1 interaction partners, which represents the largest IRS1 interactome in humans and provides new targets for studies of IRS1 complexes in various diseases. Furthermore, we generated the first global picture of IRS1 interaction partners in LCs, and how they differ in OCs and T2D patients. Interestingly, dozens of proteins in OCs and/or T2D patients exhibited increased associations with IRS1 compared with LCs under the basal and/or insulin-stimulated conditions, revealing multiple new dysfunctional IRS1 pathways in OCs and T2D patients. This novel abnormality, increased interaction of multiple proteins with IRS1 in obesity and T2D in humans, provides new insights into the molecular mechanism of insulin resistance and identifies new targets for T2D drug development.
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http://dx.doi.org/10.2337/db13-1872DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4030113PMC
June 2014

Methods and approaches in the topology-based analysis of biological pathways.

Front Physiol 2013 Oct 10;4:278. Epub 2013 Oct 10.

Department of Computer Science, Wayne State University Detroit, MI, USA.

The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as "third generation," have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity.
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http://dx.doi.org/10.3389/fphys.2013.00278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3794382PMC
October 2013

A survey of small RNAs in human sperm.

Hum Reprod 2011 Dec 11;26(12):3401-12. Epub 2011 Oct 11.

Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, USA.

Background: There has been substantial interest in assessing whether RNAs (mRNAs and sncRNAs, i.e. small non-coding) delivered from mammalian spermatozoa play a functional role in early embryo development. While the cadre of spermatozoal mRNAs has been characterized, comparatively little is known about the distribution or function of the estimated 24,000 sncRNAs within each normal human spermatozoon.

Methods: RNAs of <200 bases in length were isolated from the ejaculates from three donors of proved fertility. RNAs of 18-30 nucleotides in length were then used to construct small RNA Digital Gene Expression libraries for Next Generation Sequencing. Known sncRNAs that uniquely mapped to a single location in the human genome were identified.

Results: Bioinformatic analysis revealed the presence of multiple classes of small RNAs in human spermatozoa. The primary classes resolved included microRNA (miRNAs) (≈ 7%), Piwi-interacting piRNAs (≈ 17%), repeat-associated small RNAs (≈ 65%). A minor subset of short RNAs within the transcription start site/promoter fraction (≈ 11%) frames the histone promoter-associated regions enriched in genes of early embryonic development. These have been termed quiescent RNAs.

Conclusions: A complex population of male derived sncRNAs that are available for delivery upon fertilization was revealed. Sperm miRNA-targeted enrichment in the human oocyte is consistent with their role as modifiers of early post-fertilization. The relative abundance of piRNAs and repeat-associated RNAs suggests that they may assume a role in confrontation and consolidation. This may ensure the compatibility of the genomes at fertilization.
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http://dx.doi.org/10.1093/humrep/der329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212879PMC
December 2011

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

BMC Genomics 2006 Sep 20;7:240. Epub 2006 Sep 20.

IPSOGEN SAS, Luminy Biotech Entreprises, 163 avenue de Luminy, Case 923, 13009 Marseille, France.

Background: High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported.

Results: MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF.

Conclusion: MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.
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http://dx.doi.org/10.1186/1471-2164-7-240DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1592093PMC
September 2006

Gene expression profiling for molecular characterization of inflammatory breast cancer and prediction of response to chemotherapy.

Cancer Res 2004 Dec;64(23):8558-65

Département d'Oncologie Moléculaire, Institut Paoli-Calmettes and UMR599 Institut National de la Santé et de la Recherche Médicale, IFR137, Marseille, France.

Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer with a 5-year survival limited to approximately 40%. Diagnosis, based on clinical and/or pathological criteria, may be difficult. Optimal systemic neoadjuvant therapy and accurate predictors of pathological response have yet to be defined for increasing response rate and survival. Using DNA microarrrays containing approximately 8,000 genes, we profiled breast cancer samples from 81 patients, including 37 with IBC and 44 with noninflammatory breast cancer (NIBC). Global unsupervised hierarchical clustering was able to some extent to distinguish IBC and NIBC cases and revealed subclasses of IBC. Supervised analysis identified a 109-gene set the expression of which discriminated IBC from NIBC samples. This molecular signature was validated in an independent series of 26 samples, with an overall performance accuracy of 85%. Discriminator genes were associated with various cellular processes possibly related to the aggressiveness of IBC, including signal transduction, cell motility, adhesion, and angiogenesis. A similar approach, with leave-one-out cross-validation, identified an 85-gene set that divided IBC patients with significantly different pathological complete response rate (70% in one group and 0% in the other group). These results show the potential of gene expression profiling to contribute to a better understanding of IBC, and to provide new diagnostic and predictive factors for IBC, as well as for potential therapeutic targets.
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http://dx.doi.org/10.1158/0008-5472.CAN-04-2696DOI Listing
December 2004

Basal and luminal breast cancers: basic or luminous? (review).

Int J Oncol 2004 Aug;25(2):249-58

Laboratoire d'Oncologie Moléculaire, Institut Paoli-Calmettes and UMR599 Inserm, 13009 Marseille, France.

Three major, fast developing lines of research are elucidating the biology of the mammary gland and its malignant transformation: phenotypical analyses of epithelial cells and mammary proliferative lesions, the identification, purification and characterization of mammary stem cells and breast cancer-initiating cells, and gene expression profiling studies using high-throughput microarray technologies. These three approaches are providing a flux of new, increasingly coherent information and are improving cellular and molecular models of breast epithelium and its malignancies. A new conceptual framework is emerging, altering viewpoints on the differentiation and transformation of the mammary epithelial cells. The combined effects of these progresses on our understanding of breast cancer biology should have major consequences on the way this disease is managed.
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August 2004

Gene expression profiling of breast carcinomas using nylon DNA arrays.

C R Biol 2003 Oct-Nov;326(10-11):1031-9

Departement d'oncologie moléculaire, TAGC, Institut Paoli-Calmettes (IPC), IFR57, 232, bd Ste-Marguerite, 13273 Marseille cedex 9, France.

Clinically very heterogeneous, breast cancer prognosis and treatment response are difficult to predict with the current prognostic histoclinical parameters. Mammary oncogenesis remains poorly understood. DNA array technology allows the simultaneous analysis of the mRNA expression levels of thousands of genes in biological samples. Applied to breast tumours, expression profiles will boost our knowledge of oncogenesis, will offer new potential therapeutic targets and new prognostic and predictive markers. Today, the most accessible approach for academic research teams is that of Nylon DNA arrays with radioactive detection, which in addition allows profiling of small clinical samples.
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http://dx.doi.org/10.1016/j.crvi.2003.09.010DOI Listing
May 2004

DNA arrays in clinical oncology: promises and challenges.

Lab Invest 2003 Mar;83(3):305-16

Department of Molecular Oncology (FB, DB), Institut Paoli-Calmettes, Marseille, France.

Cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. Current diagnostic and prognostic classifications, based on clinical and pathologic factors, are insufficient to reflect the whole clinical heterogeneity of tumors. Most current anticancer agents do not differentiate between cancerous and normal cells, leading sometimes to disastrous adverse effects. Recent advances in human genome research and high-throughput molecular technologies make it possible finally to tackle the molecular complexity of malignant tumors. With DNA array technology, mRNA expression levels of thousands of genes can be measured simultaneously in a single assay. Oncology is benefiting on multiple fronts. Gene expression profiles are revealing new biologically and clinically relevant tumor subclasses previously indistinguishable and are identifying new diagnostic and prognostic biomarkers as well as new potential therapeutic targets. Here, we review the technology and present clinical applications for which promising results have been obtained. Finally, we discuss issues that must be resolved in the near future to allow DNA arrays to translate into benefits for cancer patients.
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http://dx.doi.org/10.1097/01.lab.0000059936.28369.19DOI Listing
March 2003

Expression profiling in mouse fetal thymus reveals clusters of coordinately expressed genes that mark individual stages of T-cell ontogeny.

Immunogenetics 2002 Oct 10;54(7):469-78. Epub 2002 Aug 10.

Centre d'Immunologie de Marseille-Luminy (CIML), INSERM - CNRS - Université de la Méditerranée, 13288 Marseille, France.

To search for genes that participate in regulatory networks sustaining mouse embryonic T-cell development, we have performed expression profiling using nylon macroarrays. Labeled samples representative of individual developmental stages were utilized, taking advantage of cell homogeneity during early thymus ontogeny. cDNAs revealing differential expression were further selected using labeled samples derived from lymphoid versus non-lymphoid tissues, and from mutant thymi exhibiting T-cell developmental defects. We thus identified clusters of coexpressed genes during T-cell embryogenesis and characterized their sequences through bioinformatics. We compare our results with those from other profiling analyses in the immune system, and discuss their implications for the definition of genes whose products are involved in T-cell development.
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http://dx.doi.org/10.1007/s00251-002-0488-yDOI Listing
October 2002

Gene expression profiles of poor-prognosis primary breast cancer correlate with survival.

Hum Mol Genet 2002 Apr;11(8):863-72

Département d'Oncologie Moléculaire TAGC, U.119 Inserm, Marseille, France.

The extensive heterogeneity of breast cancer complicates the precise assessment of tumour aggressiveness, making therapeutic decisions difficult and treatments inappropriate in some cases. Consequently, the long-term metastasis-free survival rate of patients receiving adjuvant chemotherapy is only 60%. There is a genuine need to identify parameters that might accurately predict the effectiveness of this treatment for each patient. Using cDNA arrays, we profiled tumour samples from 55 women with poor-prognosis breast cancer treated with adjuvant anthracycline-based chemotherapy. Gene expression monitoring was applied to a set of about 1000 candidate cancer genes. Differences in expression profiles provided molecular evidence of the clinical heterogeneity of disease. First, we confirmed the capacity of a 23-gene predictor set, identified in a previous study, to distinguish between tumours associated with different survival. Second, using a refined gene set derived from the previous one, we distinguished, among the 55 clinically homogeneous tumours, three classes with significantly different clinical outcome: 5-year overall survival and metastasis-free survival rates were respectively 100% and 75% in the first class, 65% and 56% in the second and 40% and 20% in the third. This discrimination resulted from the differential expression of two clusters of genes encoding proteins with diverse functions, including the estrogen receptor (ER). Another finding was the identification of two ER-positive tumour subgroups with different survival. These results indicate that gene expression profiling can predict clinical outcome and lead to a more precise classification of breast tumours. Furthermore, the characterization of discriminator genes might accelerate the development of new specific and alternative therapies, allowing more rationally tailored treatments that are potentially more efficient and less toxic.
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http://dx.doi.org/10.1093/hmg/11.8.863DOI Listing
April 2002

Wdr12, a mouse gene encoding a novel WD-Repeat Protein with a notchless-like amino-terminal domain.

Genomics 2002 Jan;79(1):77-86

Centre d'Immunologie de Marseille-Luminy (CIML), INSERM-CNRS-Université de la Méditerranée, 13288 Marseille, France.

The WD-repeat protein family consists of a large group of structurally related yet functionally diverse proteins found predominantly in eukaryotic cells. These factors contain several (4-16) copies of a recognizable amino-acid sequence motif (the WD unit) thought to be organized into a "propeller-like" structure involved in protein-protein regulatory interactions. Here, we report the cloning of a mouse cDNA, referred to as Wdr12, which encodes a novel WD-repeat protein of 423 amino acids. The WDR12 protein was predicted to contain seven WD units and a nuclear localization signal located within a protruding peptide between the third and fourth WD domains. The amino-terminal region shows similarity to that of the Notchless WD repeat protein. Sequence comparisons revealed WDR12 orthologs in various eukaryotic species. Wdr12 seems to correspond to a single-copy gene in the mouse genome, located within the C1-C2 bands of chromosome 1. These data, together with the results of Wdr12 gene expression studies and evidence of in vitro binding of WDR12 to the cytoplasmic domain of Notch1, led us to postulate a function for the WDR12 protein in the modulation of Notch signaling activity.
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http://dx.doi.org/10.1006/geno.2001.6682DOI Listing
January 2002