Stem Cell Hydrogel, Jump-Starting Zika Drug Discovery, and Engineering RNA Recognition.

Cell Chem Biol. 2016 Aug 18;23(8):885-886

Authors: Kostic M

Abstract
Every month the editors of Cell Chemical Biology bring you highlights of the most recent chemical biology literature that impressed them with creativity and potential for follow up work. Our August 2016 selection includes a description of hydrogels with self-tunable stiffness that are used to profile lipid metabolites during stems cell differentiation, a look at whether we can find a drug repurposing solution to Zika virus infection, and an engineered RNA recognition motif (RRM).

PMID: 27541191 [PubMed - as supplied by publisher]

Extraction of a group-pair relation: problem-solving relation from web-board documents.

Springerplus. 2016;5(1):1265

Authors: Pechsiri C, Piriyakul R

Abstract
This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.

PMID: 27540498 [PubMed]

Prevalence of CYP2D6*2, CYP2D6*4, CYP2D6*10, and CYP3A5*3 in Thai breast cancer patients undergoing tamoxifen treatment.

Breast Cancer (Dove Med Press). 2016;8:149-55

Authors: Charoenchokthavee W, Panomvana D, Sriuranpong V, Areepium N

Abstract
BACKGROUND: Tamoxifen (TAM) is used in breast cancer treatment, but interindividual variabilities in TAM-metabolizing enzymes exist and have been linked to single nucleotide polymorphisms in the respective encoding genes. The different alleles and genotypes of these genes have been presented for Caucasians and Asians. This study aimed to explore the prevalence of the incomplete functional alleles and genotypes of the CYP2D6 and CYP3A5 genes in Thai breast cancer patients undergoing TAM treatment.
PATIENTS AND METHODS: In total, 134 Thai breast cancer patients were randomly invited to join the Thai Tamoxifen Project. Their blood samples were collected and extracted for individual DNA. The alleles and genotypes were determined by real-time polymerase chain reaction with TaqMan(®) Drug Metabolism Genotyping Assays.
RESULTS: The patients were aged from 27.0 years to 82.0 years with a body mass index range from 15.4 to 40.0, with the majority (103/134) in the early stage (stages 0-II) of breast cancer. The median duration of TAM administration was 17.2 months (interquartile range 16.1 months). Most (53%) of the patients were premenopausal with an estrogen receptor (ER) and progesterone receptor (PR) status of ER+/PR+ (71.7%), ER+/PR- (26.9%), ER-/PR+ (0.7%), and ER-/PR- (0.7%). The allele frequencies of CYP2D6*1, CYP2D6*2, CYP2D6*4, CYP2D6*10, CYP3A5*1, and CYP3A5*3 were 72.9%, 3.2%, 1.1%, 22.8%, 37.3%, and 62.7%, respectively, while the genotype frequencies of CYP2D6*1/*1, CYP2D6*1/*2, CYP2D6*2/*2, CYP2D6*4/*4, CYP2D6*1/*10, CYP2D6*2/*10, CYP2D6*4/*10, CYP2D6*10/*10, CYP3A5*1/*1, CYP3A5*1/*3, and CYP3A5*3/*3 were 9.7%, 2.2%, 3.7%, 1.5%, 15.7%, 9.7%, 3.7%, 53.7%, 13.4%, 47.8%, and 38.8%, respectively.
CONCLUSION: The majority (97.8%) of Thai breast cancer patients undergoing TAM treatment carry at least one incomplete functional allele, including 20.9% of the patients who carry only incomplete functional alleles for both the CYP2D6 and CYP3A5 genes. This research indicates the high prevalence of these defective alleles that are involved in TAM-metabolic pathways that might further affect TAM treatment.

PMID: 27540311 [PubMed]

Robust de novo pathway enrichment with KeyPathwayMiner 5.

F1000Res. 2016;5:1531

Authors: Alcaraz N, List M, Dissing-Hansen M, Rehmsmeier M, Tan Q, Mollenhauer J, Ditzel HJ, Baumbach J

Abstract
Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network.

PMID: 27540470 [PubMed]

Not low hanging but still sweet: Metabolic proteomes in cardiovascular disease.

J Mol Cell Cardiol. 2016 Jan;90:70-3

Authors: Monte E, Lopez R, Vondriska TM

Abstract
The application of proteomics in biology and medicine has reached a moment of truth. The demand of biologists for transformative insights into how cells work, plus the mandate of basic science research to ultimately impact clinical medicine, crystallize as a test on the rigor and reproducibility of any 'omics measurement. Studies like that by Boylston et al. indicate that proteomics can pass that test.

PMID: 26611885 [PubMed - indexed for MEDLINE]

Coexpression Network Analysis of miRNA-142 Overexpression in Neuronal Cells.

Biomed Res Int. 2015;2015:921517

Authors: Thapa I, Fox HS, Bastola D

Abstract
MicroRNAs are small noncoding RNA molecules, which are differentially expressed in diverse biological processes and are also involved in the regulation of multiple genes. A number of sites in the 3' untranslated regions (UTRs) of different mRNAs allow complimentary binding for a microRNA, leading to their posttranscriptional regulation. The miRNA-142 is one of the microRNAs overexpressed in neurons that is found to regulate SIRT1 and MAOA genes. Differential analysis of gene expression data, which is focused on identifying up- or downregulated genes, ignores many relationships between genes affected by miRNA-142 overexpression in a cell. Thus, we applied a correlation network model to identify the coexpressed genes and to study the impact of miRNA-142 overexpression on this network. Combining multiple sources of knowledge is useful to infer meaningful relationships in systems biology. We applied coexpression model on the data obtained from wild type and miR-142 overexpression neuronal cells and integrated miRNA seed sequence mapping information to identify genes greatly affected by this overexpression. Larger differences in the enriched networks revealed that the nervous system development related genes such as TEAD2, PLEKHA6, and POGLUT1 were greatly impacted due to miRNA-142 overexpression.

PMID: 26539539 [PubMed - indexed for MEDLINE]

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Mol Biosyst. 2015 Dec;11(12):3362-77

Authors: Randhawa V, Kumar Singh A, Acharya V

Abstract
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

PMID: 26467789 [PubMed - indexed for MEDLINE]

Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control.

Sci Rep. 2015;5:14577

Authors: Kagami H, Akutsu T, Maegawa S, Hosokawa H, Nacher JC

Abstract
Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(-109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies.

PMID: 26459019 [PubMed - indexed for MEDLINE]

An integrated pathway interaction network for the combination of four effective compounds from ShengMai preparations in the treatment of cardio-cerebral ischemic diseases.

Acta Pharmacol Sin. 2015 Nov;36(11):1337-48

Authors: Li F, Lv YN, Tan YS, Shen K, Zhai KF, Chen HL, Kou JP, Yu BY

Abstract
AIM: SMXZF (a combination of ginsenoside Rb1, ginsenoside Rg1, schizandrin and DT-13) derived from Chinese traditional medicine formula ShengMai preparations) is capable of alleviating cerebral ischemia-reperfusion injury in mice. In this study we used network pharmacology approach to explore the mechanisms of SMXZF in the treatment of cardio-cerebral ischemic diseases.
METHODS: Based upon the chemical predictors, such as chemical structure, pharmacological information and systems biology functional data analysis, a target-pathway interaction network was constructed to identify potential pathways and targets of SMXZF in the treatment of cardio-cerebral ischemia. Furthermore, the most related pathways were verified in TNF-α-treated human vascular endothelial EA.hy926 cells and H2O2-treated rat PC12 cells.
RESULTS: Three signaling pathways including the NF-κB pathway, oxidative stress pathway and cytokine network pathway were demonstrated to be the main signaling pathways. The results from the gene ontology analysis were in accordance with these signaling pathways. The target proteins were found to be associated with other diseases such as vision, renal and metabolic diseases, although they exerted therapeutic actions on cardio-cerebral ischemic diseases. Furthermore, SMXZF not only dose-dependently inhibited the phosphorylation of NF-κB, p50, p65 and IKKα/β in TNF-α-treated EA.hy926 cells, but also regulated the Nrf2/HO-1 pathway in H2O2-treated PC12 cells.
CONCLUSION: NF-κB signaling pathway, oxidative stress pathway and cytokine network pathway are mainly responsible for the therapeutic actions of SMXZF against cardio-cerebral ischemic diseases.

PMID: 26456587 [PubMed - indexed for MEDLINE]

19 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

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"Cystic Fibrosis"

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"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

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Bazedoxifene as a Novel GP130 Inhibitor for Pancreatic Cancer Therapy.

Mol Cancer Ther. 2016 Aug 17;

Authors: Wu X, Cao Y, Xiao H, Li C, Lin J

Abstract
The IL-6/GP130/STAT3 pathway is crucial for tumorigenesis in multiple cancer types, including pancreatic cancer and presents as a viable target for cancer therapy. We reported Bazedoxifene, which is approved as a selective estrogen modulator by FDA, as a novel inhibitor of IL-6/GP130 protein-protein interactions using multiple ligand simultaneous docking and drug repositioning approaches. STAT3 is one of the major downstream effectors of IL-6/GP130. Here, we observed Bazedoxifene inhibited STAT3 phosphorylation and STAT3 DNA binding, induced apoptosis, and suppressed tumor growth in pancreatic cancer cells with persistent IL-6/GP130/STAT3 signaling in vitro and in vivo. In addition, IL-6 but not INF-γ rescued Bazedoxifene-mediated reduction of cell viability. Bazedoxifene also inhibited STAT3 phosphorylation induced by IL-6 and IL-11, but not by OSM or STAT1 phosphorylation induced by INF-γ in pancreatic cancer cells, suggesting that Bazedoxifene inhibits GP130/STAT3 pathway mediated by IL-6 and IL-11. Furthermore, Bazedoxifene combined with paclitaxel or gemcitabine synergistically inhibited cell viability and cell migration in pancreatic cancer cells. These results indicate that Bazedoxifene is a potential agent and can generate synergism when combined with conventional chemotherapy in human pancreatic cancer cells and tumor Xenograft in mice. Therefore, our results support that Bazedoxifene as a novel inhibitor of GP130 signaling and may be a potential and safe therapeutic agent for human pancreatic cancer therapy.

PMID: 27535971 [PubMed - as supplied by publisher]

Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies.

Biomed Res Int. 2015;2015:976272

Authors: Sinaci AA, Laleci Erturkmen GB, Gonul S, Yuksel M, Invernizzi P, Thakrar B, Pacaci A, Cinar HA, Cicekli NK

Abstract
Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

PMID: 26543873 [PubMed - indexed for MEDLINE]

Admixture and ethno-specific alleles: missing links for global pharmacogenomics.

Pharmacogenomics. 2016 Aug 18;

Authors: Duconge J, Ruaño G

PMID: 27537834 [PubMed - as supplied by publisher]

Assessing the capability of massively parallel sequencing for opportunistic pharmacogenetic screening.

Genet Med. 2016 Aug 18;

Authors: Ng D, Hong CS, Singh LN, Johnston JJ, Mullikin JC, Biesecker LG

Abstract
PURPOSE: The aim of the study was to assess exome data for preemptive pharmacogenetic screening for 203 clinically relevant pharmacogenetic variant positions from the Pharmacogenomics Knowledgebase and Clinical Pharmacogenetics Implementation Consortium and identify copy-number variants (CNVs) in CYP2D6.
METHODS: We examined the coverage and genotype quality of 203 pharmacogenetic variant positions in 973 exomes compared with five genomes and with five genotyping chip data sets. Then, we determined the agreement of exome and chip genotypes by evaluating concordance in a three-way comparison of exome, genome, and chip-based genotyping at 1,929 variant positions in five individuals. Finally, we evaluated the utility of exomes for detecting CYP2D6 CNVs.
RESULTS: For 5 individuals examined for 203 pharmacogenetic variants (5 × 203 = 1,015), 998/1,015 were identified by genome, 849/1,015 were identified by exome, and 295/1,015 by genotyping chip. Thirty-six pharmacogenetic star allele variants with moderate to strong Clinical Pharmacogenetics Implementation Consortium (CPIC) therapeutic recommendations were identified in 973 exomes. Exomes had high (98%) genotype concordance with chip-based genotyping. CYP2D6 CNVs were identified in 57/973 exomes.
CONCLUSIONS: Exomes outperformed the current chip-based assay in detecting more important pharmacogenetic variant positions and CYP2D6 CNVs for preemptive pharmacogenetic screening. Tools should be developed to derive pharmacogenetic variants from exomes.Genet Med advance online publication 11 August 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.105.

PMID: 27537706 [PubMed - as supplied by publisher]

Linezolid Induced Adverse Drug Reactions - An Update.

Curr Drug Metab. 2015;16(7):553-9

Authors: Kishor K, Dhasmana N, Kamble SS, Sahu RK

Abstract
Treatment regimen recommended for resistant tuberculosis consists of various drugs and these drugs are prescribed for at least 12-15 months. Such a long duration therapy and high dose of antibiotics result in adverse drug reactions (ADRs). ADRs may lead to various complications in disease management like replacement of drugs, dose increment, therapy withdrawal, etc. Linezolid is one of those drugs, practiced as an anti-mycobacterial agent and it is an important member of drug regimen for MDR and XDR tuberculosis. Linezolid is a broad spectrum antibiotic known for its unique mechanism of inhibition of resistant pathogenic strains. However, it causes serious adverse effects like thrombocytopenia, optic neuropathy, peripheral neuropathy, lactic acidosis, etc. Literature suggests that Linezolid can cause severe ADRs which affect patient compliance and hinder in therapy to a larger extent. Recent studies confirm the possibility of ADRs to be predicted with genetic make-up of individuals. To effectively deliver the available treatment regimen and ensure patient compliance, it is important to manage ADRs more efficiently. The role of pharmacogenomics in reducing adverse drug effects has been recently explored. In the present review, we discussed about Linezolid induced adverse drug reactions, mechanisms and genetic associations.

PMID: 26424176 [PubMed - indexed for MEDLINE]

Adverse Drug Reactions to Anti-TB Drugs: Pharmacogenomics Perspective for Identification of Host Genetic Markers.

Curr Drug Metab. 2015;16(7):538-52

Authors: Sahu RK, Singh K, Subodh S

Abstract
Adverse drug reactions (ADRs) are associated with clinical morbidity and, in severe cases, even mortality. Globally billions of dollars are spent on managing these ADRs for common and uncommon diseases. The developing world suffers from a high burden of tuberculosis, which requires 6-8 months of multi-drug treatment. In spite of most cases being treatable the problem persists mainly due to a high attrition rate associated with ADR mediated complications. Due to these reasons drug resistant strains have emerged and are now a serious challenge to TB eradication. To effectively deliver the available treatment regimen and ensure patient compliance it is important to manage ADRs more efficiently. Recent studies have demonstrated that drug outcomes are patient-specific and can, therefore be predicted. A few of these drugs, including a few administered for TB, have shown excellent correlation with response rates and development of ADRs. In this review, we profile information available in public domain for existing anti-TB drugs to understand the genesis of ADRs and patient response. Additionally, human genome variation databases have been used to correlate the frequency of these markers and their genomic variants in different populations.

PMID: 26264201 [PubMed - indexed for MEDLINE]

A clinical approach to solving discrepancies in therapeutic drug monitoring results for patients on sirolimus or tacrolimus: Towards personalized medicine, immunosuppression and pharmacogenomics.

Clin Chim Acta. 2015 Oct 23;450:15-8

Authors: Millner L, Rodriguez C, Jortani SA

Abstract
BACKGROUND: Unexpected clinical laboratory concentrations often need to be investigated before they are acted upon in a clinical setting. Therapeutic drug monitoring (TDM) frequently involves drugs with narrow therapeutic windows and can be harmful to the patient if changes are made based on erroneous serum drug concentrations. Too little of the drug will result in ineffective therapy and too much of the drug can cause life threatening toxicities. There are many factors that can result in unexpected serum drug concentrations including differences in analytical methods being used, diet, timing of blood draw, genotype and compliance. All these factors should all be considered before deciding if changes should be made in a patient's therapeutic course.
CASE REPORT: We determined the cause of 2 patient's unexpected TDM concentrations for sirolimus and tacrolimus. Using this approach in 2 patient cases, we describe how co-treatment and uncommon genotypes result in unexpected drug concentrations.
CONCLUSIONS: Both cases involved unexpected drug values. In the first case, the cause was revealed to be a drug that was added to the patient's treatment regimen (posaconazole) that inhibits CYP3A4 which is responsible for sirolimus metabolism. In the second case, the patient was revealed to have an uncommon genotype for CYP3A5, causing higher metabolism and lower serum tacrolimus concentrations than the general population.

PMID: 26232156 [PubMed - indexed for MEDLINE]

Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews.

Syst Rev. 2016;5(1):140

Authors: Shemilt I, Khan N, Park S, Thomas J

Abstract
BACKGROUND: Meta-research studies investigating methods, systems, and processes designed to improve the efficiency of systematic review workflows can contribute to building an evidence base that can help to increase value and reduce waste in research. This study demonstrates the use of an economic evaluation framework to compare the costs and effects of four variant approaches to identifying eligible studies for consideration in systematic reviews.
METHODS: A cost-effectiveness analysis was conducted using a basic decision-analytic model, to compare the relative efficiency of 'safety first', 'double screening', 'single screening' and 'single screening with text mining' approaches in the title-abstract screening stage of a 'case study' systematic review about undergraduate medical education in UK general practice settings. Incremental cost-effectiveness ratios (ICERs) were calculated as the 'incremental cost per citation 'saved' from inappropriate exclusion' from the review. Resource use and effect parameters were estimated based on retrospective analysis of 'review process' meta-data curated alongside the 'case study' review, in conjunction with retrospective simulation studies to model the integrated use of text mining. Unit cost parameters were estimated based on the 'case study' review's project budget. A base case analysis was conducted, with deterministic sensitivity analyses to investigate the impact of variations in values of key parameters.
RESULTS: Use of 'single screening with text mining' would have resulted in title-abstract screening workload reductions (base case analysis) of >60 % compared with other approaches. Across modelled scenarios, the 'safety first' approach was, consistently, equally effective and less costly than conventional 'double screening'. Compared with 'single screening with text mining', estimated ICERs for the two non-dominated approaches (base case analyses) ranged from £1975 ('single screening' without a 'provisionally included' code) to £4427 ('safety first' with a 'provisionally included' code) per citation 'saved'. Patterns of results were consistent between base case and sensitivity analyses.
CONCLUSIONS: Alternatives to the conventional 'double screening' approach, integrating text mining, warrant further consideration as potentially more efficient approaches to identifying eligible studies for systematic reviews. Comparable economic evaluations conducted using other systematic review datasets are needed to determine the generalisability of these findings and to build an evidence base to inform guidance for review authors.

PMID: 27535658 [PubMed - in process]