Network fingerprint: a knowledge-based characterization of biomedical networks

Modulation of neurotrophic factors in the treatment of dementia, stroke and TBI: Effects of Cerebrolysin

Neurotrophic factors (NTFs) are involved in the pathophysiology of neurological disorders such as dementia, stroke and traumatic brain injury (TBI), and constitute molecular targets of high interest for the therapy of these pathologies. In this review we provide an overview of current knowledge of the definition, discovery and mode of action of five NTFs, nerve growth factor, insulin-like growth factor 1, brain derived NTF, vascular endothelial growth factor and tumor necrosis factor alpha; as well as on their contribution to brain pathology and potential therapeutic use in dementia, stroke and TBI. Within the concept of NTFs in the treatment of these pathologies, we also review the neuropeptide preparation Cerebrolysin, which has been shown to resemble the activities of NTFs and to modulate the expression level of endogenous NTFs. Cerebrolysin has demonstrated beneficial treatment capabilities in vitro and in clinical studies, which are discussed within the context of the biochemistry of NTFs. The review focuses on the interactions of different NTFs, rather than addressing a single NTF, by outlining their signaling network and by reviewing their effect on clinical outcome in prevalent brain pathologies. The effects of the interactions of these NTFs and Cerebrolysin on neuroplasticity, neurogenesis, angiogenesis and inflammation, and their relevance for the treatment of dementia, stroke and TBI are summarized.

Human microRNA similarity in breast cancer

MicroRNAs (miRNAs) play important roles in a variety of human diseases, including breast cancer. A number of miRNAs are up- and down-regulated in breast cancer. However, little is known about miRNA similarity and similarity network in breast cancer. Here, a collection of 272 breast cancer-associated miRNA precursors (pre-miRNAs) were utilized to calculate similarities of sequences, target genes, pathways and functions and construct a combined similarity network. Well-characterized miRNAs and their similarity network were highlighted. Interestingly, miRNA sequence-dependent similarity networks were not identified in spite of sequence–target gene association. Similarity networks with minimum and maximum number of miRNAs originate from pathway and mature sequence, respectively. The breast cancer-associated miRNAs were divided into seven functional classes (classes I–VII) followed by disease enrichment analysis and novel miRNA-based disease similarities were found. The finding would provide insight into miRNA similarity, similarity network and disease heterogeneity in breast cancer.

Neuroendocrine immunomodulation network dysfunction in SAMP8 mice and PrP-hAβPPswe/PS1ΔE9 mice: potential mechanism underlying cognitive impairment

Senescence-accelerated mouse prone 8 strain (SAMP8) and PrP-hAβPPswe/PS1ΔE9 (APP/PS1) mice are classic animal models of sporadic Alzheimer's disease and familial AD respectively. Our study showed that object recognition memory, spatial learning and memory, active and passive avoidance were deteriorated and neuroendocrine immunomodulation (NIM) network was imbalance in SAMP8 and APP/PS1 mice. SAMP8 and APP/PS1 mice had their own specific phenotype of cognition, neuroendocrine, immune and NIM molecular network. The endocrine hormone corticosterone, luteinizing hormone and follicle-stimulating hormone, chemotactic factor monocyte chemotactic protein-1, macrophage inflammatory protein-1β, regulated upon activation normal T cell expressed and secreted factor and eotaxin, pro-inflammatory factor interleukin-23, and the Th1 cell acting as cell immunity accounted for cognitive deficiencies in SAMP8 mice, while adrenocorticotropic hormone and gonadotropin-releasing hormone, colony stimulating factor granulocyte colony stimulating factor, and Th2 cell acting as humoral immunity in APP/PS1 mice. On the pathway level, chemokine signaling and T cell receptor signaling pathway played the key role in cognition impairments of two models, while cytokine-cytokine receptor interaction and natural killer cell mediated cytotoxicity were more important in cognitive deterioration of SAMP8 mice than APP/PS1 mice. This mechanisms of NIM network underlying cognitive impairment is significant for further understanding the pathogenesis of AD and can provide useful information for development of AD therapeutic drug.

paraGSEA: a scalable approach for large-scale gene expression profiling

More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA.

MicroRNA Profiling in Aging Brain of PSEN1/PSEN2 Double Knockout Mice

MicroRNAs are small non-coding RNAs that function as regulators of gene expression. The altered expression of microRNAs influences the pathogenesis of Alzheimer's disease. Many researchers have focused on studies based on the relatively distinctive etiology of familial Alzheimer's disease due to the absence of risk factors in the pathogenesis of sporadic Alzheimer's disease. Although there is a limitation in Alzheimer's disease studies, both Alzheimer's disease types have a common risk factor-aging. No study to date has examined the aging factor in Alzheimer's disease animal models with microRNAs. To investigate the effect of aging on the changes in microRNA expressions in the Alzheimer's disease animal model, we selected 37 hippocampal microRNAs whose expression in 12- and 18-month aged mice changed significantly using microRNA microarray. On the basis of bioinformatics databases, 30 hippocampal microRNAs and their putative targets of PSEN1/PSEN2 double knockout mice were included in 28 pathways such as the wnt signaling pathway and ubiquitin-mediated proteolysis pathway. Cortical microRNAs and its putative targets involved in pathological aging were included in only four pathways such as the heparin sulfate biosynthesis. The altered expressions of these hippocampal microRNAs were associated to the imbalance between neurotoxic and neuroprotective functions and seemed to affect neurodegeneration in PSEN1/PSEN2 double knockout mice more severely than in wild-type mice. This microRNA profiling suggests that microRNAs play potential roles in the normal aging process, as well as in the Alzheimer's disease process.

Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through targeting critical genes in cellular system. However, it is unclear about which miRNAs play central roles in CRC’s pathogenesis and how they interact with transcription factors (TFs) to regulate the cancer-related genes.

Results

To address this issue, we systematically explored the major regulation motifs, namely feed-forward loops (FFLs), that consist of miRNAs, TFs and CRC-related genes through the construction of a miRNA-TF regulatory network in CRC. First, we compiled CRC-related miRNAs, CRC-related genes, and human TFs from multiple data sources. Second, we identified 13,123 3-node FFLs including 25 miRNA-FFLs, 13,005 TF-FFLs and 93 composite-FFLs, and merged the 3-node FFLs to construct a CRC-related regulatory network. The network consists of three types of regulatory subnetworks (SNWs): miRNA-SNW, TF-SNW, and composite-SNW. To enhance the accuracy of the network, the results were filtered by using The Cancer Genome Atlas (TCGA) expression data in CRC, whereby we generated a core regulatory network consisting of 58 significant FFLs. We then applied a hub identification strategy to the significant FFLs and found 5 significant components, including two miRNAs (hsa-miR-25 and hsa-miR-31), two genes (ADAMTSL3 and AXIN1) and one TF (BRCA1). The follow up prognosis analysis indicated all of the 5 significant components having good prediction of overall survival of CRC patients.

Conclusions

In summary, we generated a CRC-specific miRNA-TF regulatory network, which is helpful to understand the complex CRC regulatory mechanisms and guide clinical treatment. The discovered 5 regulators might have critical roles in CRC pathogenesis and warrant future investigation.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1796-4) contains supplementary material, which is available to authorized users.

NFPscanner: a webtool for knowledge-based deciphering of biomedical networks

Background

Many biological pathways have been created to represent different types of knowledge, such as genetic interactions, metabolic reactions, and gene-regulating and physical-binding relationships. Biologists are using a wide range of omics data to elaborately construct various context-specific differential molecular networks. However, they cannot easily gain insight into unfamiliar gene networks with the tools that are currently available for pathways resource and network analysis. They would benefit from the development of a standardized tool to compare functions of multiple biological networks quantitatively and promptly.

Results

To address this challenge, we developed NFPscanner, a web server for deciphering gene networks with pathway associations. Adapted from a recently reported knowledge-based framework called network fingerprint, NFPscanner integrates the annotated pathways of 7 databases, 4 algorithms, and 2 graphical visualization modules into a webtool. It implements 3 types of network analysis:

Fingerprint: Deciphering gene networks and highlighting inherent pathway modules

Alignment: Discovering functional associations by finding optimized node mapping between 2 gene networks

Enrichment: Calculating and visualizing gene ontology (GO) and pathway enrichment for genes in networks

Users can upload gene networks to NFPscanner through the web interface and then interactively explore the networks’ functions.

Conclusions

NFPscanner is open-source software for non-commercial use, freely accessible at http://biotech.bmi.ac.cn/nfs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1673-1) contains supplementary material, which is available to authorized users.

Tuning of major signaling networks (TGF-β, Wnt, Notch and Hedgehog) by miRNAs in human stem cells commitment to different lineages: Possible clinical application

Two distinguishing characteristics of stem cells, their continuous division in the undifferentiated state and growth into any cell types, are orchestrated by a number of cell signaling pathways. These pathways act as a niche factor in controlling variety of stem cells. The core stem cell signaling pathways include Wingless-type (Wnt), Hedgehog (HH), and Notch. Additionally, they critically regulate the self-renewal and survival of cancer stem cells. Conversely, stem cells' main properties, lineage commitment and stemness, are tightly controlled by epigenetic mechanisms such as DNA methylation, histone modifications and non-coding RNA-mediated regulatory events. MicroRNAs (miRNAs) are cellular switches that modulate stem cells outcomes in response to diverse extracellular signals. Numerous scientific evidences implicating miRNAs in major signal transduction pathways highlight new crosstalks of cellular processes. Aberrant signaling pathways and miRNAs levels result in developmental defects and diverse human pathologies. This review discusses the crosstalk between the components of main signaling networks and the miRNA machinery, which plays a role in the context of stem cells development and provides a set of examples to illustrate the extensive relevance of potential novel therapeutic targets.

The Molecular Revolution in Cutaneous Biology: Emerging Landscape in Genomic Dermatology: New Mechanistic Ideas, Gene Editing, and Therapeutic Breakthroughs

Stunning technological advances in genomics have led to spectacular breakthroughs in the understanding of the underlying defects, biological pathways and therapeutic targets of skin diseases leading to new therapeutic interventions. Next-generation sequencing has revolutionized the identification of disease-causing genes and has a profound impact in deciphering gene and protein signatures in rare and frequent skin diseases. Gene addition strategies have shown efficacy in junctional EB and in recessive dystrophic EB (RDEB). TALENs and Cripsr/Cas9 have emerged as highly efficient new tools to edit genomic sequences to creat new models and to correct or disrupt mutated genes to treat human diseases. Therapeutic approaches have not been limited to DNA modification and strategies at the mRNA, protein and cellular levels have also emerged, some of which have already proven clinical efficacy in RDEB. Improved understanding of the pathogenesis of skin disorders has led to the development of specific drugs or repurposing of existing medicines as in basal cell nevus syndrome, alopecia areata, melanoma and EB simplex. These discoveries pave the way for improved targeted personalized medicine for rare and frequent diseases. It is likely that a growing number of orphan skin diseases will benefit from combinatory new therapies in a near future.

NFP: An R Package for Characterizing and Comparing of Annotated Biological Networks

Large amounts of various biological networks exist for representing different types of interaction data, such as genetic, metabolic, gene regulatory, and protein-protein relationships. Recent approaches on biological network study are based on different mathematical concepts. It is necessary to construct a uniform framework to judge the functionality of biological networks. We recently introduced a knowledge-based computational framework that reliably characterized biological networks in system level. The method worked by making systematic comparisons to a set of well-studied "basic networks," measuring both the functional and topological similarities. A biological network could be characterized as a spectrum-like vector consisting of similarities to basic networks. Here, to facilitate the application, development, and adoption of this framework, we present an R package called NFP. This package extends our previous pipeline, offering a powerful set of functions for Network Fingerprint analysis. The software shows great potential in biological network study. The open source NFP R package is freely available under the GNU General Public License v2.0 at CRAN along with the vignette.