Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events.

BMC Syst Biol. 2015;9 Suppl 6:S5

Authors: Wu C, Schwartz JM, Brabant G, Peng SL, Nenadic G

Abstract
BACKGROUND: Biomedical studies need assistance from automated tools and easily accessible data to address the problem of the rapidly accumulating literature. Text-mining tools and curated databases have been developed to address such needs and they can be applied to improve the understanding of molecular pathogenesis of complex diseases like thyroid cancer.
RESULTS: We have developed a system, PWTEES, which extracts pathway interactions from the literature utilizing an existing event extraction tool (TEES) and pathway named entity recognition (PathNER). We then applied the system on a thyroid cancer corpus and systematically extracted molecular interactions involving either genes or pathways. With the extracted information, we constructed a molecular interaction network taking genes and pathways as nodes. Using curated pathway information and network topological analyses, we highlight key genes and pathways involved in thyroid carcinogenesis.
CONCLUSIONS: Mining events involving genes and pathways from the literature and integrating curated pathway knowledge can help improve the understanding of molecular interactions of complex diseases. The system developed for this study can be applied in studies other than thyroid cancer. The source code is freely available online at https://github.com/chengkun-wu/PWTEES.

PMID: 26679379 [PubMed - indexed for MEDLINE]

Pharmacovigilance through the development of text mining and natural language processing techniques.

J Biomed Inform. 2015 Dec;58:288-91

Authors: Segura-Bedmar I, Martínez P

PMID: 26547007 [PubMed - indexed for MEDLINE]

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports.

J Biomed Inform. 2015 Dec;58:268-79

Authors: Liu X, Chen H

Abstract
Social media offer insights of patients' medical problems such as drug side effects and treatment failures. Patient reports of adverse drug events from social media have great potential to improve current practice of pharmacovigilance. However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research. In this study, we develop a research framework with advanced natural language processing techniques for integrated and high-performance patient reported adverse drug event extraction. The framework consists of medical entity extraction for recognizing patient discussions of drug and events, adverse drug event extraction with shortest dependency path kernel based statistical learning method and semantic filtering with information from medical knowledge bases, and report source classification to tease out noise. To evaluate the proposed framework, a series of experiments were conducted on a test bed encompassing about postings from major diabetes and heart disease forums in the United States. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Our framework significantly outperforms prior work.

PMID: 26518315 [PubMed - indexed for MEDLINE]

Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification.

J Biomed Inform. 2015 Dec;58:122-32

Authors: Ben Abacha A, Chowdhury MF, Karanasiou A, Mrabet Y, Lavelli A, Zweigenbaum P

Abstract
Pharmacovigilance (PV) is defined by the World Health Organization as the science and activities related to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. An essential aspect in PV is to acquire knowledge about Drug-Drug Interactions (DDIs). The shared tasks on DDI-Extraction organized in 2011 and 2013 have pointed out the importance of this issue and provided benchmarks for: Drug Name Recognition, DDI extraction and DDI classification. In this paper, we present our text mining systems for these tasks and evaluate their results on the DDI-Extraction benchmarks. Our systems rely on machine learning techniques using both feature-based and kernel-based methods. The obtained results for drug name recognition are encouraging. For DDI-Extraction, our hybrid system combining a feature-based method and a kernel-based method was ranked second in the DDI-Extraction-2011 challenge, and our two-step system for DDI detection and classification was ranked first in the DDI-Extraction-2013 task at SemEval. We discuss our methods and results and give pointers to future work.

PMID: 26432353 [PubMed - indexed for MEDLINE]

Exploring Splicing-Switching Molecules For Seckel Syndrome Therapy.

Biochim Biophys Acta. 2016 Sep 14;

Authors: Scalet D, Balestra D, Rohban S, Bovolenta M, Perrone D, Bernardi F, Campaner S, Pinotti M

Abstract
The c.2101A>G synonymous change (p.G674G) in the gene for ATR, a key player in the DNA-damage response, has been the first identified genetic cause of Seckel Syndrome (SS), an orphan disease characterized by growth and mental retardation. This mutation mainly causes exon 9 skipping, through an ill-defined mechanism. Through ATR minigene expression studies, we demonstrated that the detrimental effect of this mutation (6±1% of correct transcripts only) depends on the poor exon 9 definition (47±4% in the ATR(wt) context), because the change was ineffective when the weak 5' or the 3' splice sites (ss) were strengthened (scores from 0.54 to 1) by mutagenesis. Interestingly, the exonic c.2101A nucleotide is conserved across species, and the SS-causing mutation is predicted to concurrently strengthen a Splicing Silencer (ESS) and weaken a Splicing Enhancer (ESE). Consistently, the artificial c.2101A>C change, predicted to weaken the ESE only, moderately impaired exon inclusion (28±7% of correct transcripts). The observation that an antisense oligonucleotide (AON(ATR)) targeting the c.2101A position recovers exon inclusion in the mutated context supports a major role of the underlying ESS. A U1snRNA variant (U1(ATR)) designed to perfectly base-pair the weak 5'ss, rescued exon inclusion (63±3%) in the ATR(SS)-allele. Most importantly, upon lentivirus-mediated delivery, the U1(ATR) partially rescued ATR mRNA splicing (from ~19% to ~54%) and protein (from negligible to ~6%) in embryonic fibroblasts derived from humanized ATR(SS) mice. Altogether these data elucidate the molecular mechanisms of the ATR c.2101A>G mutation and identify two potential complementary RNA-based therapies for Seckel syndrome.

PMID: 27639833 [PubMed - as supplied by publisher]

Onset of persistent pseudomonas aeruginosa infection in children with cystic fibrosis with interval censored data.

BMC Med Res Methodol. 2016;16(1):122

Authors: Wang W, Chen MH, Chiou SH, Lai HC, Wang X, Yan J, Zhang Z

Abstract
BACKGROUND: Persistent Pseudomonas aeruginosa (PPA) infection promotes lung function deterioration in children with cystic fibrosis (CF). Although early CF diagnosis through newborn screening (NBS) has been shown to provide nutritional/growth benefit, it is unclear whether NBS lowers the risk of PPA infection and how the effect of NBS vary with age. Modeling the onset age of PPA infection is challenging because 1) the onset age of PPA infection is interval censored in patient registry data; and 2) some risk factors such as NBS may have time-varying effects.
METHODS: This problem fits into the framework of a recently developed Bayesian dynamic Cox model for interval censored data, where each regression coefficient is allowed to be time-varying to an extent determined by the data.
RESULTS: Application of the methodology to data from the CF Foundation Patient Registry revealed interesting findings. Compared with patients with meconium ileus or diagnosed through signs or symptoms, patients diagnosed through NBS had significantly lower risks of acquiring PPA infection between age 1 and 2 years, and the benefit in survival rate was found to last up to age 4 years. Two cohorts of five years apart were compared. Patients born in cohort 2003-2004 had significantly lower risks of the PPA infections at any age up to 4 years than those born in 1998-1999.
CONCLUSIONS: The study supports benefits of NBS on PPA infection in early childhood. In addition, our analyses demonstrate that patients in the more recent cohort had significantly lower risks of acquiring PPA infection up to age 4 years, which suggests improved CF treatment and care over time.

PMID: 27639560 [PubMed - as supplied by publisher]

Non-linear interactions between candidate genes of myocardial infarction revealed in mRNA expression profiles.

BMC Genomics. 2016;17(1):738

Authors: Hartmann K, Seweryn M, Handleman SK, Rempała GA, Sadee W

Abstract
BACKGROUND: Alterations in gene expression are key events in disease etiology and risk. Poor reproducibility in detecting differentially expressed genes across studies suggests individual genes may not be sufficiently informative for complex diseases, such as myocardial infarction (MI). Rather, dysregulation of the 'molecular network' may be critical for pathogenic processes. Such a dynamic network can be built from pairwise non-linear interactions.
RESULTS: We investigate non-linear interactions represented in mRNA expression profiles that integrate genetic background and environmental factors. Using logistic regression, we test the association of individual GWAS-based candidate genes and non-linear interaction terms (between these mRNA expression levels) with MI. Based on microarray data in CATHGEN (CATHeterization in GENetics) and FHS (Framingham Heart Study), we find individual genes and pairs of mRNAs, encoded by 41 MI candidate genes, with significant interaction terms in the logistic regression model. Two pairs replicate between CATHGEN and FHS (CNNM2|GUCY1A3 and CNNM2|ZEB2). Analysis of RNAseq data from GTEx (Genotype-Tissue Expression) shows that 20 % of these disease-associated RNA pairs are co-expressed, further prioritizing significant interactions. Because edges in sparse co-expression networks formed solely by the 41 candidate genes are unlikely to represent direct physical interactions, we identify additional RNAs as links between network pairs of candidate genes. This approach reveals additional mRNAs and interaction terms significant in the context of MI, for example, the path CNNM2|ACSL5|SCARF1|GUCY1A3, characterized by the common themes of magnesium and lipid processing.
CONCLUSIONS: The results of this study support a role for non-linear interactions between genes in MI and provide a basis for further study of MI systems biology. mRNA expression profiles encoded by a limited number of candidate genes yield sparse networks of MI-relevant interactions that can be expanded to include additional candidates by co-expression analysis. The non-linear interactions observed here inform our understanding of the clinical relevance of gene-gene interactions in the pathophysiology of MI, while providing a new strategy in developing clinical biomarker panels.

PMID: 27640124 [PubMed - as supplied by publisher]

6 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")

These pubmed results were generated on 2016/09/18

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

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

"Cystic Fibrosis"

These pubmed results were generated on 2016/09/18

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Modulating carbohydrate-protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiology.

Curr Opin Struct Biol. 2016 Sep 14;40:104-111

Authors: Chiang AW, Li S, Spahn PN, Richelle A, Kuo CC, Samoudi M, Lewis NE

Abstract
Diverse glycans on proteins impact cell and organism physiology, along with drug activity. Since many protein-based biotherapeutics are glycosylated and these glycans have biological activity, there is a desire to engineer glycosylation for recombinant protein-based biotherapeutics. Engineered glycosylation can impact the recombinant protein efficacy and also influence many cell pathways by first changing glycan-protein interactions and consequently modulating disease physiologies. However, its complexity is enormous. Recent advances in glycoengineering now make it easier to modulate protein-glycan interactions. Here, we discuss how engineered glycans contribute to therapeutic monoclonal antibodies (mAbs) in the treatment of cancers, how these glycoengineered therapeutic mAbs affect the transformed phenotypes and downstream cell pathways. Furthermore, we suggest how systems biology can help in the next generation mAb glycoengineering process by aiding in data analysis and guiding engineering efforts to tailor mAb glycan and ultimately drug efficacy, safety and affordability.

PMID: 27639240 [PubMed - as supplied by publisher]

GPS for QSP: A Summary of the ACoP6 Symposium on Quantitative Systems Pharmacology and a Stage for Near-Term Efforts in the Field.

CPT Pharmacometrics Syst Pharmacol. 2016 Sep 17;

Authors: Musante CJ, Abernethy DR, Allerheiligen SR, Lauffenburger DA, Zager MG

Abstract
Quantitative Systems Pharmacology (QSP) is experiencing increased application in the drug discovery and development process. Like its older sibling, systems biology, the QSP field is comprised of a mix of established disciplines and methods, from molecular biology to engineering to pharmacometrics. As a result, there exist critical segments of the discipline that differ dramatically in approach and a need to bring these groups together toward a common goal.

PMID: 27639191 [PubMed - as supplied by publisher]

A decade of Central and Eastern European Proteomic Conference (CEEPC): Credibility, cohesion and vision for the next decade.

J Proteomics. 2016 Sep 13;

Authors: Gadher SJ, Kovarova H

Abstract
The Central and Eastern European Proteomic Conference (CEEPC), has reached a special milestone as it celebrates its 10th anniversary. Today, an expansive network of proteomics in Central and Eastern Europe stands established to facilitate scientific interactions and collaborations in and around Central and Eastern Europe, as well as with international research institutions worldwide. Currently, when many conferences are struggling to attract participants, CEEPC is thriving in its status and stature as well as expanding by attracting newer member countries. CEEPC's success is driven by mutual respect between scientists sharing interest in proteomics and its applications in multidisciplinary research areas related to biological systems. This effort when interwoven with exciting ambience steeped with culture, and tradition is also a reason why participants enjoy it. CEEPC's careful balance between excellence and cohesion holds the key to its success. It is evident that CEEPC is ready for the next decade of excitement and expectations of multifaceted proteomics in Central and Eastern Europe. Additionally, in the era of emerging personalized medicine where treatment selection for each patient is becoming individualized, CEEPC and proteomics is expected to play a significant role moving forward for the benefit of mankind.

PMID: 27638426 [PubMed - as supplied by publisher]

9 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")

These pubmed results were generated on 2016/09/17

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

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

"Cystic Fibrosis"

These pubmed results were generated on 2016/09/17

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Lithium Pharmacogenetics: Where Do We Stand?

Drug Dev Res. 2016 Sep 16;

Authors: Pisanu C, Melis C, Squassina A

Abstract
Preclinical Research Bipolar disorder (BPD) is a chronic and disabling psychiatric disorder with a prevalence of 0.8-1.2% in the general population. Although lithium is considered the first-line treatment, a large percentage of patients do not respond sufficiently. Moreover, lithium can induce severe side effects and has poor tolerance and a narrow therapeutic index. The genetics of lithium response has been largely investigated, but findings have so far failed to identify reliable biomarkers to predict clinical response. This has been largely determined by the highly complex phenotipic and genetic architecture of lithium response. To this regard, collaborative initiatives hold the promise to provide robust and standardized methods to disantenagle this complexity, as well as the capacity to collect large samples of patietnts, a crucial requirement to study the genetics of complex phenotypes. The International Consortium on Lithium Genetics (ConLiGen) has recently published the largest study so far on lithium response reporting significant associations for two long noncoding RNAs (lncRNAs). This result provides relevant insights into the pharmacogenetics of lithium supporting the involvement of the noncoding portion of the genome in modulating clinical response. Although a vast body of research is engaged in dissecting the genetic bases of response to lithium, the several drawbacks of lithium therapy have also stimulated multiple efforts to identify new safer treatments. A drug repurposing approach identified ebselen as a potential lithium mimetic, as it shares with lithium the ability to inhibit inositol monophosphatase. Ebselen, an antioxidant glutathione peroxidase mimetic, represents a valid and promising example of new potential therapeutic interventions for BD, but the paucity of data warrant further investigation to elucidate its potential efficacy and safety in the management of BPD. Nevertheless, findings provided by the growing field of pharmacogenomic research will ultimately lead to the identification of new molecular targets and safer treatments for BPD. Drug Dev Res, 2016. © 2016 Wiley Periodicals, Inc.

PMID: 27633500 [PubMed - as supplied by publisher]

A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics.

PLoS One. 2016;11(9):e0162866

Authors: Mizzi C, Dalabira E, Kumuthini J, Dzimiri N, Balogh I, Başak N, Böhm R, Borg J, Borgiani P, Bozina N, Bruckmueller H, Burzynska B, Carracedo A, Cascorbi I, Deltas C, Dolzan V, Fenech A, Grech G, Kasiulevicius V, Kádaši Ľ, Kučinskas V, Khusnutdinova E, Loukas YL, Macek M, Makukh H, Mathijssen R, Mitropoulos K, Mitropoulou C, Novelli G, Papantoni I, Pavlovic S, Saglio G, Setric J, Stojiljkovic M, Stubbs AP, Squassina A, Torres M, Turnovec M, van Schaik RH, Voskarides K, Wakil SM, Werk A, Del Zompo M, Zukic B, Katsila T, Lee MT, Motsinger-Rief A, Mc Leod HL, van der Spek PJ, Patrinos GP

Abstract
Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

PMID: 27636550 [PubMed - as supplied by publisher]

An Expert Review of Pharmacogenomics of Sickle Cell Disease Therapeutics: Not Yet Ready for Global Precision Medicine.

OMICS. 2016 Sep 16;

Authors: Mnika K, Pule GD, Dandara C, Wonkam A

Abstract
Sickle cell disease (SCD) is a blood disease caused by a single nucleotide substitution (T > A) in the beta globin gene on chromosome 11. The single point mutation (Glu6Val) promotes polymerization of hemoglobin S (HbS) and causes sickling of erythrocytes. Vaso-occlusive painful crises are associated with recurrent and long-term use of analgesics/opioids and hydroxyurea (HU) by people living with SCD. The present analysis offers a state-of-the-art expert review of the effectiveness of pharmacogenomics/genetics of pain management in SCD, with specific focus on HU and opioids. The literature search used the following keywords: SCD, pharmacogenomics, pharmacogenetics, pain, antalgics, opioids, morphine, and HU. The literature was scanned until March 2016, with specific inclusion of targeted landmark and background articles on SCD. Surprisingly, our review identified only a limited number of studies that addressed the genetic/genomic basis of variable responses to pain (e.g., variants in OPRM1, HMOX-1, GCH1, VEGFA COMT genes), and pharmacogenomics of antalgics and opioids (e.g., variants in OPRM1, STAT6, ABCB1, and COMT genes) in SCD. There has been greater progress made toward identifying the key genomic variants, mainly in BCL11A, HBS1L-MYB, or SAR1, which contribute to response to HU treatment. However, the complete picture on pharmacogenomic determinants of the above therapeutic phenotypes remains elusive. Strikingly, no study has been conducted in sub-Saharan Africa where majority of the patients with SCD live. This alerts the broader global life sciences community toward the existing disparities in optimal and ethical targeting of research and innovation investments for SCD specifically and precision medicine and pharmacology research broadly.

PMID: 27636225 [PubMed - as supplied by publisher]

Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities.

OMICS. 2016 Sep 16;

Authors: Dalvie S, Koen N, McGregor N, O'Connell K, Warnich L, Ramesar R, Nievergelt CM, Stein DJ

Abstract
Mental disorders represent a major public health burden worldwide. This is likely to rise in the next decade, with the highest increases predicted to occur in low- and middle-income countries. Current psychotropic medication treatment guidelines focus on uniform approaches to the treatment of heterogeneous disorders and achieve only partial therapeutic success. Developing a global precision medicine approach in psychiatry appears attractive, given the value of this approach in other fields of medicine, such as oncology and infectious diseases. In this horizon scanning analysis, we review the salient opportunities and challenges for precision medicine in psychiatry over the next decade. Variants within numerous genes involved in a range of pathways have been implicated in psychotropic drug response and might ultimately be used to guide choice of pharmacotherapy. Multipronged approaches such as multi-omics (genomics, proteomics, metabolomics) analyses and systems diagnostics together with high-throughput sequencing and genotyping technologies hold promise for identifying precise and targeted treatments in mental disorders. To date, however, the vast majority of pharmacogenomics work has been undertaken in high-income countries on a relatively small proportion of the global population, and many other challenges face the field. Opportunities and challenges for establishing a global roadmap for precision medicine in psychiatry are discussed in this article.

PMID: 27636104 [PubMed - as supplied by publisher]

Pharmacogenetic research activity in Central America and the Caribbean: a systematic review.

Pharmacogenomics. 2016 Sep 16;

Authors: Céspedes-Garro C, Naranjo MG, Rodrigues-Soares F, LLerena A, Duconge J, Montané-Jaime LK, Roblejo H, Fariñas H, Campos ML, Ramírez R, Serrano V, Villagrán CI, Peñas-LLedó EM

Abstract
AIM: The present review was aimed at analyzing the pharmacogenetic scientific activity in Central America and the Caribbean.
MATERIALS & METHODS: A literature search for pharmacogenetic studies in each country of the region was conducted on three databases using a list of the most relevant pharmacogenetic biomarkers including 'phenotyping probe drugs' for major drug metabolizing enzymes. The review included 132 papers involving 47 biomarkers and 35,079 subjects (11,129 healthy volunteers and 23,950 patients).
RESULTS: The country with the most intensive pharmacogenetic research was Costa Rica. The most studied medical therapeutic area was oncology, and the most investigated biomarkers were CYP2D6 and HLA-A/B. Conclusion: Research activity on pharmacogenetics in Central American and the Caribbean populations is limited or absent. Therefore, strategies to promote effective collaborations, and foster interregional initiatives and research efforts among countries from the region could help for the rational clinical implementation of pharmacogenetics and personalized medicine.

PMID: 27633613 [PubMed - as supplied by publisher]

Clinical Implications of Opioid Pharmacogenomics in Patients With Cancer.

Cancer Control. 2015 Oct;22(4):426-32

Authors: Bell GC, Donovan KA, McLeod HL

Abstract
BACKGROUND: Pain can be a significant burden for patients with cancer and may have negative effects on their quality of life. Opioids are potent analgesics and serve as a foundation for pain management. The variation in response to opioid analgesics is well characterized and is partly due to genetic variability.
METHODS: We reviewed the results of clinical studies to evaluate the relationships between genetic variants and select genes involved in the pharmacokinetics and pharmacodynamics of opioids, with an emphasis on patients with cancer.
RESULTS: In patients with cancer-related pain, genetic variation in OPRM1, COMT, and ABCB1 is associated with response to morphine, which is the most well-studied opioid. Although it has not been studied in patients with cancer-related pain, the effect of CYP2D6 variation is well characterized with codeine and tramadol. Evidence is limited for associating the genetic variation and pain response of oxycodone, hydrocodone, and fentanyl in patients with cancer.
CONCLUSION: The clinical availability of pharmacogenomic testing and research findings related to these polymorphic genes suggest that genotyping patients for these genetic variants may allow health care professionals to better predict patient response to pain and, thus, personalize pain treatment.

PMID: 26678969 [PubMed - indexed for MEDLINE]