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Wake Forest, NC, United States

Zhang D.,Chongqing Medical University | Zhang D.,Wake Forest Institute for Regenerative Medicine | Wei G.,Chongqing Medical University | Li P.,Wake Forest Institute for Regenerative Medicine | And 3 more authors.
Genes and Diseases

Engineered functional organs or tissues, created with autologous somatic cells and seeded on biodegradable or hydrogel scaffolds, have been developed for use in individuals with tissue damage suffered from congenital disorders, infection, irradiation, or cancer. However, in those patients, abnormal cells obtained by biopsy from the compromised tissue could potentially contaminate the engineered tissues. Thus, an alternative cell source for construction of the neo-organ or functional recovery of the injured or diseased tissues would be useful. Recently, we have found stem cells existing in the urine. These cells are highly expandable, and have self-renewal capacity, paracrine properties, and multi-differentiation potential. As a novel cell source, urine-derived stem cells (USCs) provide advantages for cell therapy and tissue engineering applications in regeneration of various tissues, particularly in the genitourinary tract, because they originate from the urinary tract system. Importantly, USCs can be obtained via a non-invasive, simple, and low-cost approach and induced with high efficiency to differentiate into three dermal cell lineages. © 2014 Chongqing Medical University. Source

Zhao X.-M.,Tongji University | Liu K.-Q.,Center for Bioinformatics and Systems Biology | Liu K.-Q.,University of Angers | Zhu G.,Shanghai University | And 7 more authors.

Motivation: MicroRNAs (miRNAs) are short non-coding RNAs that play important roles in post-transcriptional regulations as well as other important biological processes. Recently, accumulating evidences indicate that miRNAs are extensively involved in cancer. However, it is a big challenge to identify which miRNAs are related to which cancer considering the complex processes involved in tumors, where one miRNA may target hundreds or even thousands of genes and one gene may regulate multiple miRNAs. Despite integrative analysis of matched gene and miRNA expression data can help identify cancer-associated miRNAs, such kind of data is not commonly available. On the other hand, there are huge amount of gene expression data that are publicly accessible. It will significantly improve the efficiency of characterizing miRNA' s function in cancer if we can identify cancer miRNAs directly from gene expression data. Results: We present a novel computational framework to identify the cancer-related miRNAs based solely on gene expression profiles without requiring either miRNA expression data or the matched gene and miRNA expression data. The results on multiple cancer datasets show that our proposed method can effectively identify cancer-related miRNAs with higher precision compared with other popular approaches. Furthermore, some of our novel predictions are validated by both differentially expressed miRNAs and evidences from literature, implying the predictive power of our proposed method. In addition, we construct a cancer-miRNA-pathway network, which can help explain how miRNAs are involved in cancer. Availability and implementation: The R code and data files for the proposed method are available at http://comp-sysbio.org/miR-Path/. © 2014 The Author. Source

Peng H.,Center for Bioinformatics and Systems Biology | Peng T.,Methodist Hospital Research Institute | Wen J.,Methodist Hospital Research Institute | Engler D.A.,Methodist Hospital Research Institute | And 6 more authors.

Motivation: p38 mitogen-activated protein kinase activation plays an important role in resistance to chemotherapeutic cytotoxic drugs in treating multiple myeloma (MM). However, how the p38 mitogenactivated protein kinase signaling pathway is involved in drug resistance, in particular the roles that the various p38 isoforms play, remains largely unknown. Method: To explore the underlying mechanisms, we developed a novel systems biology approach by integrating liquid chromatography- mass spectrometry and reverse phase protein array data from human MM cell lines with computational pathway models in which the unknown parameters were inferred using a proposed novel algorithm called modularized factor graph. Results: New mechanisms predicted by our models suggest that combined activation of various p38 isoforms may result in drug resistance in MM via regulating the related pathways including extracellular signalregulated kinase (ERK) pathway and NFκB pathway. ERK pathway regulating cell growth is synergistically regulated by p38δ isoform, whereas nuclear factor kappa B (NFκB) pathway regulating cell apoptosis is synergistically regulated by p38α isoform. This finding that p38- isoform promotes the phosphorylation of ERK1/2 in MM cells treated with bortezomib was validated by western blotting. Based on the predicted mechanisms, we further screened drug combinations in silico and found that a promising drug combination targeting ERK1/2 and NFκB might reduce the effects of drug resistance in MM cells. This study provides a framework of a systems biology approach to studying drug resistance and drug combination selection. © The Author 2014. Source

Liu L.,Center for Bioinformatics and Systems Biology | Zhao W.,Center for Bioinformatics and Systems Biology | Zhou X.,Center for Bioinformatics and Systems Biology
Nucleic Acids Research

Regulation of gene expression requires both transcription factor (TFs) and epigenetic modifications, and interplays between the two types of factors have been discovered. However study of relationships between chromatin features and TF-TF co-occupancy remains limited. Here, we revealed the relationship by first illustrating distinct profile patterns of chromatin features related to different binding events, including single TF binding and TF-TF co-occupancy of 71 TFs from five human cell lines. We further implemented statistical analyses to demonstrate the relationship by accurately predicting co-occupancy genome-widely using chromatin features including DNase I hypersensitivity, 11 histone modifications (HMs) and GC content. Remarkably, our results showed that the combination of chromatin features enables accurate predictions across the five cells. For individual chromatin features, DNase I enables high and consistent predictions. H3K27ac, H3K4me 2, H3K4me3 and H3K9ac are more reliable predictors than other HMs. Although the combination of 11 HMs achieves accurate predictions, their predictive ability varies considerably when a model obtained from one cell is applied to others, indicating relationship between HMs and TF-TF co-occupancy is cell type dependent. GC content is not a reliable predictor, but the addition of GC content to any other features enhances their predictive ability. Together, our results elucidate a strong relationship between TF-TF co-occupancy and chromatin features. © 2016 The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Source

Liu L.,Center for Bioinformatics and Systems Biology | Jin G.,Center for Bioinformatics and Systems Biology | Zhou X.,Center for Bioinformatics and Systems Biology
Nucleic Acids Research

Transcription factors (TFs) and epigenetic modifications play crucial roles in the regulation of gene expression, and correlations between the two types of factors have been discovered. However, methods for quantitatively studying the correlations remain limited. Here, we present a computational approach to systematically investigating how epigenetic changes in chromatin architectures or DNA sequences relate to TF binding. We implemented statistical analyses to illustrate that epigenetic modifications are predictive of TF binding affinities, without the need of sequence information. Intriguingly, by considering genome locations relative to transcription start sites (TSSs) or enhancer midpoints, our analyses show that different locations display various relationship patterns. For instance, H3K4me3, H3k9ac and H3k27ac contribute more in the regions near TSSs, whereas H3K4me1 and H3k79me2 dominate in the regions far from TSSs. DNA methylation plays relatively important roles when close to TSSs than in other regions. In addition, the results show that epigenetic modification models for the predictions of TF binding affinities are cell line-specific. Taken together, our study elucidates highly coordinated, but location- and cell type-specific relationships between epigenetic modifications and binding affinities of TFs. © 2015 © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Source

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