Impact of statistical models on the prediction of type 2 diabetes using non-targeted metabolomics profiling.

OBJECTIVE: Characterizing specific metabolites in sub-clinical phases preceding the onset of type 2 diabetes to enable efficient preventive and personalized interventions. RESEARCH DESIGN AND METHODS: We developed predictive models of type 2 diabetes using two strategies. One strategy focused on the probability of incidence only and was based on logistic regression (MRS1); the other strategy accounted for the age at diagnosis of diabetes and was based on Cox regression (MRS2). We assessed 293 metabolites using non-targeted metabolomics in fasting plasma samples of 1,044 participants (including 231 incident cases over 9 years) used as training population; and fasting serum samples of 128 participants (64 incident cases versus 64 controls) used as validation population. We applied a LASSO-based variable selection aiming at maximizing the out-of-sample area under the receiver operating characteristic curve (AROC) and integrated AROC. RESULTS: Sixteen and 17 metabolites were selected for MRS1 and MRS2, respectively, with AROC = 90% and 73% in the training and validation populations, respectively for MRS1. MRS2 had a similar performance and was significantly associated with a younger age of onset of type 2 diabetes (ß = -3.44 years per MRS2 SD in the training population, p = 1.56 × 10(-7); ß = -4.73 years per MRS2 SD in the validation population, p = 4.04 × 10(-3)). CONCLUSIONS: Overall, this study illustrates that metabolomics improves prediction of type 2 diabetes incidence of 4.5% on top of known clinical and biological markers, reaching 90% in total AROC, which is considered the threshold for clinical validity, suggesting it may be used in targeting interventions to prevent type 2 diabetes.

Coevolution Analysis of HIV-1 Envelope Glycoprotein Complex.

The HIV-1 Env spike is the main protein complex that facilitates HIV-1 entry into CD4+ host cells. HIV-1 entry is a multistep process that is not yet completely understood. This process involves several protein-protein interactions between HIV-1 Env and a variety of host cell receptors along with many conformational changes within the spike. HIV-1 Env developed due to high mutation rates and plasticity escape strategies from immense immune pressure and entry inhibitors. We applied a coevolution and residue-residue contact detecting method to identify coevolution patterns within HIV-1 Env protein sequences representing all group M subtypes. We identified 424 coevolving residue pairs within HIV-1 Env. The majority of predicted pairs are residue-residue contacts and are proximal in 3D structure. Furthermore, many of the detected pairs have functional implications due to contributions in either CD4 or coreceptor binding, or variable loop, gp120-gp41, and interdomain interactions. This study provides a new dimension of information in HIV research. The identified residue couplings may not only be important in assisting gp120 and gp41 coordinate structure prediction, but also in designing new and effective entry inhibitors that incorporate mutation patterns of HIV-1 Env.

Tackling cancer control in the Gulf Cooperation Council Countries.

Cancer is a major health problem in both high income and middle-to-low income countries, and is the second leading cause of death in the world. Although more than a third of cancer could be prevented and another third could be cured if diagnosed early, it remains a huge challenge to health-care systems worldwide. Despite substantial improvements in health services some of the countries in the Gulf region, the burden of non-communicable diseases is a major threat, primarily due to the rapid socioeconomic shifts that have led to unfavourable changes in lifestyle such as increased tobacco use, decreased physical activity, and consumption of unhealthy food. In the Gulf Cooperation Council states (United Arab Emirates, Bahrain, Saudi Arabia, Oman, Qatar, and Kuwait), advanced breast cancer, colorectal cancer, leukaemia, thyroid cancer, and non-Hodgkin lymphomas are the most common cancers affecting younger populations compared with other countries. By contrast with cancer prevalence in developed countries, prostate, lung, and cervical cancers are not among the most common cancers in the Gulf region. In view of the increased cost of cancer management worldwide, integrated approaches between primary, secondary, and tertiary health-care systems with special focus on prevention and early detection is an essential step in the countries' efforts in the fight against cancer.

Exploiting human CD34+ stem cell-conditioned medium for tissue repair.

Despite the progress in our understanding of genes essential for stem cell regulation and development, little is known about the factors secreted by stem cells and their effect on tissue regeneration. In particular, the factors secreted by human CD34+ cells remain to be elucidated. We have approached this challenge by performing a cytokine/growth factor microarray analysis of secreted soluble factors in medium conditioned by adherent human CD34+ cells. Thirty-two abundantly secreted factors have been identified, all of which are associated with cell proliferation, survival, tissue repair, and wound healing. The cultured CD34+ cells expressed known stem cell genes such as Nanog, Oct4, Sox2, c-kit, and HoxB4. The conditioned medium containing the secreted factors prevented cell death in liver cells exposed to liver toxin in vitro via inhibition of the caspase-3 signaling pathway. More importantly, in vivo studies using animal models of liver damage demonstrated that injection of the conditioned medium could repair damaged liver tissue (significant reduction in the necroinflammatory activity), as well as enable the animals to survive. Thus, we demonstrate that medium conditioned by human CD34+ cells has the potential for therapeutic repair of damaged tissue in vivo.

Novel RNA oligonucleotide improves liver function and inhibits liver carcinogenesis in vivo.

UNLABELLED: Hepatocellular carcinoma (HCC) occurs predominantly in patients with liver cirrhosis. Here we show an innovative RNA-based targeted approach to enhance endogenous albumin production while reducing liver tumor burden. We designed short-activating RNAs (saRNA) to enhance expression of C/EBPα (CCAAT/enhancer-binding protein-α), a transcriptional regulator and activator of albumin gene expression. Increased levels of both C/EBPα and albumin mRNA in addition to a 3-fold increase in albumin secretion and 50% decrease in cell proliferation was observed in C/EBPα-saRNA transfected HepG2 cells. Intravenous injection of C/EBPα-saRNA in a cirrhotic rat model with multifocal liver tumors increased circulating serum albumin by over 30%, showing evidence of improved liver function. Tumor burden decreased by 80% (P = 0.003) with a 40% reduction in a marker of preneoplastic transformation. Since C/EBPα has known antiproliferative activities by way of retinoblastoma, p21, and cyclins, we used messenger RNA (mRNA) expression liver cancer-specific microarray in C/EBPα-saRNA-transfected HepG2 cells to confirm down-regulation of genes strongly enriched for negative regulation of apoptosis, angiogenesis, and metastasis. Up-regulated genes were enriched for tumor suppressors and positive regulators of cell differentiation. A quantitative polymerase chain reaction (PCR) and western blot analysis of C/EBPα-saRNA-transfected cells suggested that in addition to the known antiproliferative targets of C/EBPα, we also observed suppression of interleukin (IL)6R, c-Myc, and reduced STAT3 phosphorylation. CONCLUSION: A novel injectable saRNA-oligonucleotide that enhances C/EBPα expression successfully reduces tumor burden and simultaneously improves liver function in a clinically relevant liver cirrhosis/HCC model.

A Short-activating RNA Oligonucleotide Targeting the Islet ß-cell Transcriptional Factor MafA in CD34(+) Cells.

Upon functional loss of insulin producing islet ß-cells, some patients with diabetes become dependent on life-long insulin supplementation therapy. Bioengineering surrogate insulin producing cells is an alternative replacement strategy. We have developed a novel approach using short-activating RNA oligonucleotides to differentiate adult human CD34(+) cells into insulin-secreting cells. By transfecting RNA to increase transcript levels of the master regulator of insulin biosynthesis, v-maf musculoaponeurotic fibrosarcoma oncogene homolog A (MafA), several pancreatic endodermal genes were upregulated during the differentiation procedure. These included Pancreatic and duodenal homeobox gene-1 (PDX1), Neurogenin 3, NeuroD, and NK6 homeobox 1 (NKx6-1). Differentiated CD34(+) cells also expressed glucokinase, glucagon-like peptide 1 receptor (GLP1R), sulfonylurea receptor-1 (SUR1) and phogrin-all essential for glucose sensitivity and insulin secretion. The differentiated cells appropriately processed C-peptide and insulin in response to increasing glucose stimulation as shown by enzyme-linked immunosorbent assay (ELISA), fluorescence-activated cell sorting analysis, western blotting, and immunofluorescence staining. We provide a new approach using short-activating RNA in developing insulin producing surrogate cells for treating diabetes.Molecular Therapy - Nucleic Acids (2013) 2, e97; doi:10.1038/mtna.2013.23; advance online publication 4 June 2013.

Tackling cancer burden in the Middle East: Qatar as an example.

Cancer prevalence is increasing in the Middle East, partly because of increased life expectancy and adoption of western lifestyle habits. Suboptimum delivery of health care also contributes to late diagnosis and poor survival of people with cancer. Public awareness of cancer risk is frequently low and misconceptions high, thereby preventing patients from seeking treatment early and constituting a substantial barrier to improvement of cancer outcomes. Screening programmes might have low uptake in Arab populations because of social and health beliefs about cancer. This review outlines the opportunities available to Middle Eastern countries and their emerging economies to learn from global experiences in cancer care, service provision, and research partnerships. The Middle East has begun to develop several health-care transformation programmes. Qatar, in particular, has published a National Health Strategy, in which cancer is one of the main commitments; this Strategy provides the focus of this review. The development of effective health-care strategies and evidence-based medicine directly linked to innovative cancer research is needed to improve cancer care. Although the full extent of the proposed solutions are not necessarily implementable in all Middle Eastern countries, wealthy states can lead derivation of population-specific approaches that could have effects throughout the region. Key challenges are outlined-namely, human capacity and training, subspecialisation of services, building on international cancer research initiatives, and the need for earlier diagnosis and awareness in the population. Countries in the Gulf Region (ie, countries bordering the Persian Gulf, including Iran, Iraq, Kuwait, Saudi Arabia, Bahrain, Qatar, UAE, and Oman) need to address these challenges to be at the forefront of integrated cancer care and research and ensure that the latest innovations and best possible care are delivered to their populations.

MicroRNA-181a* Targets Nanog in a Subpopulation of CD34(+) Cells Isolated From Peripheral Blood.

Exploiting the properties of stem cells by microRNA (miRNA) profiling offers an attractive approach to identify new regulators of stem cell fate. Although numerous miRNA have been screened from hematopoietic stem cells (HSC), the targets corresponding to many of these miRNA have not yet been fully elucidated. By miRNA profiling in a subpopulation of CD34+ cells isolated from peripheral blood, we have identified eight clusters of miRNA that were differentially expressed. Further analysis of one of the clusters by bioinformatics revealed that a miRNA, miR-181a*, which is highly expressed in the adherent CD34+ cells, affects the expression levels of Nanog, a stem cell surrogate marker. We show specifically by reporter assay and mutational analysis that miR-181a* targets a seedless 3' compensatory site in the 3'UTR of Nanog and affects gene expression. We demonstrate that inhibiting miR-181a* upregulates the Nanog expression level, in addition to an increase in alkaline phosphatase activity. Our studies suggest that miR-181a* may be important in controlling the expression level of Nanog in a subpopulation of CD34+ cells.

HTLV-1 Tax oncoprotein subverts the cellular DNA damage response via binding to DNA-dependent protein kinase.

Human T-cell leukemia virus type-1 is the causative agent for adult T-cell leukemia. Previous research has established that the viral oncoprotein Tax mediates the transformation process by impairing cell cycle control and cellular response to DNA damage. We showed previously that Tax sequesters huChk2 within chromatin and impairs the response to ionizing radiation. Here we demonstrate that DNA-dependent protein kinase (DNA-PK) is a member of the Tax.Chk2 nuclear complex. The catalytic subunit, DNA-PKcs, and the regulatory subunit, Ku70, were present. Tax-containing nuclear extracts showed increased DNA-PK activity, and specific inhibition of DNA-PK prevented Tax-induced activation of Chk2 kinase activity. Expression of Tax induced foci formation and phosphorylation of H2AX. However, Tax-induced constitutive signaling of the DNA-PK pathway impaired cellular response to new damage, as reflected in suppression of ionizing radiation-induced DNA-PK phosphorylation and gammaH2AX stabilization. Tax co-localized with phospho-DNA-PK into nuclear speckles and a nuclear excluded Tax mutant sequestered endogenous phospho-DNA-PK into the cytoplasm, suggesting that Tax interaction with DNA-PK is an initiating event. We also describe a novel interaction between DNA-PK and Chk2 that requires Tax. We propose that Tax binds to and stabilizes a protein complex with DNA-PK and Chk2, resulting in a saturation of DNA-PK-mediated damage repair response.

Bioinformatics and data mining in proteomics.

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.

Human LINE-1 retrotransposon induces DNA damage and apoptosis in cancer cells.

BACKGROUND: Long interspersed nuclear elements (LINEs), Alu and endogenous retroviruses (ERVs) make up some 45% of human DNA. LINE-1 also called L1, is the most common family of non-LTR retrotransposons in the human genome and comprises about 17% of the genome. L1 elements require the integration into chromosomal target sites using L1-encoded endonuclease which creates staggering DNA breaks allowing the newly transposed L1 copies to integrate into the genome. L1 expression and retrotransposition in cancer cells might cause transcriptional deregulation, insertional mutations, DNA breaks, and an increased frequency of recombinations, contributing to genome instability. There is however little evidence on the mechanism of L1-induced genetic instability and its impact on cancer cell growth and proliferation. RESULTS: We report that L1 has genome-destabilizing effects indicated by an accumulation of gamma-H2AX foci, an early response to DNA strand breaks, in association with an abnormal cell cycle progression through a G2/M accumulation and an induction of apoptosis in breast cancer cells. In addition, we found that adjuvant L1 activation may lead to supra-additive killing when combined with radiation by enhancing the radiation lethality through induction of apoptosis that we have detected through Bax activation. CONCLUSION: L1 retrotransposition is sensed as a DNA damaging event through the creation DNA breaks involving L1-encoded endonuclease. The apparent synergistic interaction between L1 activation and radiation can further be utilized for targeted induction of cancer cell death. Thus, the role of retrotransoposons in general, and of L1 in particular, in DNA damage and repair assumes larger significance both for the understanding of mutagenicity and, potentially, for the control of cell proliferation and apoptosis.

PDZ binding motif of HTLV-1 Tax promotes virus-mediated T-cell proliferation in vitro and persistence in vivo.

HTLV-1 cellular transformation and disease induction is dependent on expression of the viral Tax oncoprotein. PDZ is a modular protein interaction domain used in organizing signaling complexes in eukaryotic cells through recognition of a specific binding motif in partner proteins. Tax-1, but not Tax-2, contains a PDZ-binding domain motif (PBM) that promotes the interaction with several cellular PDZ proteins. Herein, we investigate the contribution of the Tax-1 PBM in HTLV-induced proliferation and immortalization of primary T cells in vitro and viral survival in an infectious rabbit animal model. We generated several HTLV-1 and HTLV-2 Tax viral mutants, including HTLV-1deltaPBM, HTLV-2+C22(+PBM), and HTLV-2+ C18(deltaPBM). All Tax mutants maintained the ability to significantly activate the CREB/ATF or NFkappaB signaling pathways. Microtiter proliferation assays revealed that the Tax-1 PBM significantly increases both HTLV-1- and HTLV-2-induced primary T-cell proliferation. In addition, Tax-1 PBM was responsible for the micronuclei induction activity of Tax-1 relative to that of Tax-2. Viral infection and persistence were severely attenuated in rabbits inoculated with HTLV-1deltaPBM. Our results provide the first direct evidence suggesting that PBM-mediated associations between Tax-1 and cellular proteins play a key role in HTLV-induced cell proliferation and genetic instability in vitro and facilitate viral persistence in vivo.

Functional clustering algorithm for high-dimensional proteomics data.

Clustering proteomics data is a challenging problem for any traditional clustering algorithm. Usually, the number of samples is largely smaller than the number of protein peaks. The use of a clustering algorithm which does not take into consideration the number of features of variables (here the number of peaks) is needed. An innovative hierarchical clustering algorithm may be a good approach. We propose here a new dissimilarity measure for the hierarchical clustering combined with a functional data analysis. We present a specific application of functional data analysis (FDA) to a high-throughput proteomics study. The high performance of the proposed algorithm is compared to two popular dissimilarity measures in the clustering of normal and human T-cell leukemia virus type 1 (HTLV-1)-infected patients samples.

A novel approach for clustering proteomics data using Bayesian fast Fourier transform.

MOTIVATION: Bioinformatics clustering tools are useful at all levels of proteomic data analysis. Proteomics studies can provide a wealth of information and rapidly generate large quantities of data from the analysis of biological specimens. The high dimensionality of data generated from these studies requires the development of improved bioinformatics tools for efficient and accurate data analyses. For proteome profiling of a particular system or organism, a number of specialized software tools are needed. Indeed, significant advances in the informatics and software tools necessary to support the analysis and management of these massive amounts of data are needed. Clustering algorithms based on probabilistic and Bayesian models provide an alternative to heuristic algorithms. The number of clusters (diseased and non-diseased groups) is reduced to the choice of the number of components of a mixture of underlying probability. The Bayesian approach is a tool for including information from the data to the analysis. It offers an estimation of the uncertainties of the data and the parameters involved. RESULTS: We present novel algorithms that can organize, cluster and derive meaningful patterns of expression from large-scaled proteomics experiments. We processed raw data using a graphical-based algorithm by transforming it from a real space data-expression to a complex space data-expression using discrete Fourier transformation; then we used a thresholding approach to denoise and reduce the length of each spectrum. Bayesian clustering was applied to the reconstructed data. In comparison with several other algorithms used in this study including K-means, (Kohonen self-organizing map (SOM), and linear discriminant analysis, the Bayesian-Fourier model-based approach displayed superior performances consistently, in selecting the correct model and the number of clusters, thus providing a novel approach for accurate diagnosis of the disease. Using this approach, we were able to successfully denoise proteomic spectra and reach up to a 99% total reduction of the number of peaks compared to the original data. In addition, the Bayesian-based approach generated a better classification rate in comparison with other classification algorithms. This new finding will allow us to apply the Fourier transformation for the selection of the protein profile for each sample, and to develop a novel bioinformatic strategy based on Bayesian clustering for biomarker discovery and optimal diagnosis.

Retrotransposition-Competent Human LINE-1 Induces Apoptosis in Cancer Cells With Intact p53.

Retrotransposition of human LINE-1 (L1) element, a major representative non-LTR retrotransposon in the human genome, is known to be a source of insertional mutagenesis. However, nothing is known about effects of L1 retrotransposition on cell growth and differentiation. To investigate the potential for such biological effects and the impact that human L1 retrotransposition has upon cancer cell growth, we examined a panel of human L1 transformed cell lines following a complete retrotransposition process. The results demonstrated that transposition of L1 leads to the activation of the p53-mediated apoptotic pathway in human cancer cells that possess a wild-type p53. In addition, we found that inactivation of p53 in cells, where L1 was undergoing retrotransposition, inhibited the induction of apoptosis. This suggests an association between active retrotransposition and a competent p53 response in which induction of apoptosis is a major outcome. These data are consistent with a model in which human retrotransposition is sensed by the cell as a "genetic damaging event" and that massive retrotransposition triggers signaling pathways resulting in apoptosis.