A comprehensive approach to the molecular determinants of lifespan using a Boolean model of geroconversion.

Aging Cell. 2016 Sep 9;

Authors: Verlingue L, Dugourd A, Stoll G, Barillot E, Calzone L, Londoño-Vallejo A

Abstract
Altered molecular responses to insulin and growth factors (GF) are responsible for late-life shortening diseases such as type-2 diabetes mellitus (T2DM) and cancers. We have built a network of the signaling pathways that control S-phase entry and a specific type of senescence called geroconversion. We have translated this network into a Boolean model to study possible cell phenotype outcomes under diverse molecular signaling conditions. In the context of insulin resistance, the model was able to reproduce the variations of the senescence level observed in tissues related to T2DM's main morbidity and mortality. Furthermore, by calibrating the pharmacodynamics of mTOR inhibitors, we have been able to reproduce the dose-dependent effect of rapamycin on liver degeneration and lifespan expansion in wild-type and HER2-neu mice. Using the model, we have finally performed an in silico prospective screen of the risk-benefit ratio of rapamycin dosage for healthy lifespan expansion strategies. We present here a comprehensive prognostic and predictive systems biology tool for human aging.

PMID: 27613445 [PubMed - as supplied by publisher]

Systems biology integration of proteomic data in rodent models of depression reveals involvement of the immune response and glutamatergic signalling.

Proteomics Clin Appl. 2016 Sep 10;

Authors: Carboni L, Nguyen TP, Caberlotto L

Abstract
PURPOSE: The pathophysiological basis of major depression is incompletely understood. Recently, numerous proteomic studies have been performed in rodent models of depression to investigate the molecular underpinnings of depressive-like behaviours with an unbiased approach. The objective of the study was to integrate the results of these proteomic studies in depression models to shed light on the most relevant molecular pathways involved in the disease.
EXPERIMENTAL DESIGN: Network analysis was performed integrating pre-existing proteomic data from rodent models of depression. The IntAct mouse and the HRPD were used as reference protein-protein interaction databases. The functionality analyses of the networks were then performed by testing over-represented GO biological process terms and pathways.
RESULTS: Functional enrichment analyses of the networks revealed an association with molecular processes related to depression in humans, such as those involved in the immune response. Pathways impacted by clinically effective antidepressants were modulated, including glutamatergic signalling and neurotrophic responses. Moreover, dysregulations of proteins regulating energy metabolism and circadian rhythms were implicated. The comparison with protein pathways modulated in depressive patients revealed significant overlapping.
CONCLUSIONS AND CLINICAL RELEVANCE: This systems biology study supports the notion that animal models could contribute to the research into the biology and therapeutics of depression. This article is protected by copyright. All rights reserved.

PMID: 27612656 [PubMed - as supplied by publisher]

Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.

J Biomed Semantics. 2016;7(1):52

Authors: Funk CS, Cohen KB, Hunter LE, Verspoor KM

Abstract
BACKGROUND: Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and how they are expressed in natural language text. The construction of highly specific GO terms is formulaic, consisting of parts and pieces from more simple terms.
RESULTS: We present two different types of manually generated rules to help capture the variation of how GO terms can appear in natural language text. The first set of rules takes into account the compositional nature of GO and recursively decomposes the terms into their smallest constituent parts. The second set of rules generates derivational variations of these smaller terms and compositionally combines all generated variants to form the original term. By applying both types of rules, new synonyms are generated for two-thirds of all GO terms and an increase in F-measure performance for recognition of GO on the CRAFT corpus from 0.498 to 0.636 is observed. Additionally, we evaluated the combination of both types of rules over one million full text documents from Elsevier; manual validation and error analysis show we are able to recognize GO concepts with reasonable accuracy (88 %) based on random sampling of annotations.
CONCLUSIONS: In this work we present a set of simple synonym generation rules that utilize the highly compositional and formulaic nature of the Gene Ontology concepts. We illustrate how the generated synonyms aid in improving recognition of GO concepts on two different biomedical corpora. We discuss other applications of our rules for GO ontology quality assurance, explore the issue of overgeneration, and provide examples of how similar methodologies could be applied to other biomedical terminologies. Additionally, we provide all generated synonyms for use by the text-mining community.

PMID: 27613112 [PubMed - as supplied by publisher]

Review and Literature Mining on Proteostasis Factors and Cancer.

Methods Mol Biol. 2016;1449:71-84

Authors: Carvalho AS, Rodríguez MS, Matthiesen R

Abstract
Automatic analysis of increasingly growing literature repositories including data integration to other databases is a powerful tool to propose hypothesis that can be used to plan experiments to validate or disprove the hypothesis. Furthermore, it provides means to evaluate the redundancy of research line in comparison to the published literature. This is potentially beneficial for those developing research in a specific disease which are interested in exploring a particular pathway or set of genes/proteins. In the scope of the integrating book a case will be made addressing proteostasis factors in cancer. The maintenance of proteome homeostasis, known as proteostasis, is a process by which cells regulate protein translation, degradation, subcellular localization, and protein folding and consists of an integrated network of proteins. The ubiquitin-proteasome system plays a key role in essential biological processes such as cell cycle, DNA damage repair, membrane trafficking, and maintaining protein homeostasis. Cells maintain proteostasis by regulating protein translation, degradation, subcellular localization, and protein folding. Aberrant proteostasis leads to loss-of-function diseases (cystic fibrosis) and gain-of-toxic-function diseases (Alzheimer's, Parkinson's, and Huntington's disease). Cancer therapy on the other hand explores inhibition of proteostasis factors to trigger endoplasmic reticulum stress with subsequent apoptosis. Alternatively therapies target deubiquitinases and thereby regulate tumor promoters or suppressors. Furthermore, mutations in specific proteostasis factors are associated with higher risk for specific cancers, e.g., BRCA mutations in breast cancer. This chapter discusses proteostasis protein factors' association with cancer from a literature mining perspective.

PMID: 27613028 [PubMed - in process]

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Highlights from the 1st Latin American meeting on metronomic chemotherapy and drug repositioning in oncology, 27-28 May, 2016, Rosario, Argentina.

Ecancermedicalscience. 2016;10:672

Authors: Rosé A, André N, Rozados VR, Mainetti LE, Márquez MM, Rico MJ, Schaiquevich P, Villarroel M, Gregianin L, Graupera JM, García WG, Epelman S, Alasino C, Alonso D, Chantada G, Scharovsky OG

Abstract
Following previous metronomic meetings in Marseille (2011), Milano (2014), and Mumbai (2016), the first Latin American metronomic meeting was held in the School of Medical Sciences, National University of Rosario, Rosario, Argentina on 27 and 28 of May, 2016. For the first time, clinicians and researchers with experience in the field of metronomics, coming from different countries in Latin America, had the opportunity of presenting and discussing their work. The talks were organised in three main sessions related to experience in the pre-clinical, and clinical (paediatric and adult) areas. The different presentations demonstrated that the fields of metronomic chemotherapy and repurposing drugs in oncology, known as metronomics, constitute a branch of cancer therapy in permanent evolution, which have strong groups working in Latin America, both in the preclinical and the clinical settings including large, adequately designed randomised studies. It was shown that metronomics offers treatments, which, whether they are combined or not with the standard therapeutic approaches, are not only effective but also minimally toxic, with the consequent improvement of the patient's quality of life, and inexpensive, a feature very important in low resource clinical settings. The potential use of metronomic chemotherapy was proposed as a cost/effective treatment in low-/middle-income countries, for adjuvant therapy in selected tumours. The fundamental role of the governmental agencies and non-governmental alliances, as the Metronomic Global Health Initiative, in supporting this research with public interest was underlined.

PMID: 27610198 [PubMed]

Protein aggregation, structural disorder and RNA-binding ability: a new approach for physico-chemical and gene ontology classification of multiple datasets.

BMC Genomics. 2015;16:1071

Authors: Klus P, Ponti RD, Livi CM, Tartaglia GG

Abstract
BACKGROUND: Comparison between multiple protein datasets requires the choice of an appropriate reference system and a number of variables to describe their differences. Here we introduce an innovative approach to discriminate multiple protein datasets (multiCM) and to measure enrichments in gene ontology terms (cleverGO) using semantic similarities.
RESULTS: We illustrate the powerfulness of our approach by investigating the links between RNA-binding ability and other protein features, such as structural disorder and aggregation, in S. cerevisiae, C. elegans, M. musculus and H. sapiens. Our results are in striking agreement with available experimental evidence and unravel features that are key to understand the mechanisms regulating cellular homeostasis.
CONCLUSIONS: In an intuitive way, multiCM and cleverGO provide accurate classifications of physico-chemical features and annotations of biological processes, molecular functions and cellular components, which is extremely useful for the discovery and characterization of new trends in protein datasets. The multiCM and cleverGO can be freely accessed on the Web at http://www.tartaglialab.com/cs_multi/submission and http://www.tartaglialab.com/GO_analyser/universal . Each of the pages contains links to the corresponding documentation and tutorial.

PMID: 26673865 [PubMed - indexed for MEDLINE]

Pharmacogenomics in psychiatry - Clinical innovation utilised by the Therapeutic Goods Administration and Food and Drug Administration.

Aust N Z J Psychiatry. 2016 Sep 8;

Authors: Kulkarni J

PMID: 27609939 [PubMed - as supplied by publisher]

Validating the pharmacogenomics of chemotherapy-induced cardiotoxicity: What is missing?

Pharmacol Ther. 2016 Sep 5;

Authors: Magdy T, Burmeister BT, Burridge PW

Abstract
The cardiotoxicity of certain chemotherapeutic agents is now well-established, and has led to the development the field cardio-oncology, increased cardiac screening of cancer patients, and limitation of patients' maximum cumulative chemotherapeutic dose. The effect of chemotherapeutic regimes on the heart largely involves cardiomyocyte death, leading to cardiomyopathy and heart failure, or the induction of arrhythmias. Of these cardiotoxic drugs, those resulting in clinical cardiotoxicity can range from 8 to 26% for doxorubicin, 7-28% for trastuzumab, or 5-30% for paclitaxel. For tyrosine kinase inhibitors, QT prolongation and arrhythmia, ischemia and hypertension has been reported in 2-35% of patients. Furthermore, newly introduced chemotherapeutic agents are commonly used as part of changed combinational regimens with significantly increased cardiotoxicity incidence. It is widely believed that the mechanism of action of these drugs is often independent of their cardiotoxicity, and the basis for why these drugs specifically affect the heart has yet to be established. The genetic rationale for why certain patients experience cardiotoxicity whilst other patients can tolerate high chemotherapy doses has proven highly illusive. This has led to significant genomic efforts using targeted and genome-wide association studies (GWAS) to divine the pharmacogenomic cause of this predilection. With the advent of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), the putative risk and protective role of single nucleotide polymorphisms (SNPs) can now be validated in a human model. Here we review the state of the art knowledge of the genetic predilection to chemotherapy-induced cardiotoxicity and discuss the future for establishing and validating the role of the genome in this disease.

PMID: 27609196 [PubMed - as supplied by publisher]

Folate metabolic pathway single nucleotide polymorphisms: a predictive pharmacogenetic marker of methotrexate response in Indian (Asian) patients with rheumatoid arthritis.

Pharmacogenomics. 2015 Dec;16(18):2019-34

Authors: Ghodke-Puranik Y, Puranik AS, Shintre P, Joshi K, Patwardhan B, Lamba J, Niewold TB, Chopra A

Abstract
AIM: We evaluated the pharmacogenetic influence of genetic polymorphisms in folate pathway genes in Indian rheumatoid arthritis patients receiving methotrexate (MTX).
PATIENTS & METHODS: Twelve polymorphisms within nine folate pathway genes were analyzed for association with MTX response in 322 Indian rheumatoid arthritis (RA) patients and MTX pharmacokinetics in 94 RA patients.
RESULTS: Polymorphisms in GGH, SHMT1 and TS were associated with MTX-related adverse events while SNPs in MTHFR and RFC1/SLC19A1 were associated with MTX efficacy. TS5'UTR and SHMT1 polymorphisms were associated with higher plasma levels of MTX.
CONCLUSION: Polymorphisms in folate-MTX pathway genes contribute to MTX response and affect MTX concentrations in Indian RA patients. A toxicogenetic index could identify patients who develop adverse events to MTX.

PMID: 26616421 [PubMed - indexed for MEDLINE]

The role of ADME pharmacogenomics in early clinical trials: perspective of the Industry Pharmacogenomics Working Group (I-PWG).

Pharmacogenomics. 2015 Dec;16(18):2055-67

Authors: Tremaine L, Brian W, DelMonte T, Francke S, Groenen P, Johnson K, Li L, Pearson K, Marshall JC

Abstract
Genetic polymorphisms in metabolizing enzymes and drug transporters have been shown to significantly impact the exposure of drugs having a high dependence on a single mechanism for their absorption, distribution or clearance, such that genotyping can lead to actionable steps in disease treatment. Recently, global regulatory agencies have provided guidance for assessment of pharmacogenomics during early stages of drug development, both in the form of formal guidance and perspectives published in scientific journals. The Industry Pharmacogenomics Working Group (I-PWG), conducted a survey among member companies to assess the practices relating to absorption, distribution, metabolism, excretion pharmacogenomics) during early stages of clinical development, to assess the impact of the recent Regulatory Guidance issued by the US FDA and EMA on Industry practices.

PMID: 26616152 [PubMed - indexed for MEDLINE]

Associations between genetic variants and the effect of letrozole and exemestane on bone mass and bone turnover.

Breast Cancer Res Treat. 2015 Nov;154(2):263-73

Authors: Oesterreich S, Henry NL, Kidwell KM, Van Poznak CH, Skaar TC, Dantzer J, Li L, Hangartner TN, Peacock M, Nguyen AT, Rae JM, Desta Z, Philips S, Storniolo AM, Stearns V, Hayes DF, Flockhart DA

Abstract
Adjuvant therapy for hormone receptor (HR) positive postmenopausal breast cancer patients includes aromatase inhibitors (AI). While both the non-steroidal AI letrozole and the steroidal AI exemestane decrease serum estrogen concentrations, there is evidence that exemestane may be less detrimental to bone. We hypothesized that single nucleotide polymorphisms (SNP) predict effects of AIs on bone turnover. Early stage HR-positive breast cancer patients were enrolled in a randomized trial of exemestane versus letrozole. Effects of AI on bone mineral density (BMD) and bone turnover markers (BTM), and associations between SNPs in 24 candidate genes and changes in BMD or BTM were determined. Of the 503 enrolled patients, paired BMD data were available for 123 and 101 patients treated with letrozole and exemestane, respectively, and paired BTM data were available for 175 and 173 patients, respectively. The mean change in lumbar spine BMD was significantly greater for letrozole-treated (-3.2 %) compared to exemestane-treated patients (-1.0 %) (p = 0.0016). Urine N-telopeptide was significantly increased in patients treated with exemestane (p = 0.001) but not letrozole. Two SNPs (rs4870061 and rs9322335) in ESR1 and one SNP (rs10140457) in ESR2 were associated with decreased BMD in letrozole-treated patients. In the exemestane-treated patients, SNPs in ESR1 (Rs2813543) and CYP19A1 (Rs6493497) were associated with decreased bone density. Exemestane had a less negative impact on bone density compared to letrozole, and the effects of AI therapy on bone may be impacted by genetic variants in the ER pathway.

PMID: 26536870 [PubMed - indexed for MEDLINE]

Inoculation density and nutrient level determine the formation of mushroom-shaped structures in Pseudomonas aeruginosa biofilms.

Sci Rep. 2016;6:32097

Authors: Ghanbari A, Dehghany J, Schwebs T, Müsken M, Häussler S, Meyer-Hermann M

Abstract
Pseudomonas aeruginosa often colonises immunocompromised patients and the lungs of cystic fibrosis patients. It exhibits resistance to many antibiotics by forming biofilms, which makes it hard to eliminate. P. aeruginosa biofilms form mushroom-shaped structures under certain circumstances. Bacterial motility and the environment affect the eventual mushroom morphology. This study provides an agent-based model for the bacterial dynamics and interactions influencing bacterial biofilm shape. Cell motility in the model relies on recently published experimental data. Our simulations show colony formation by immotile cells. Motile cells escape from a single colony by nutrient chemotaxis and hence no mushroom shape develops. A high number density of non-motile colonies leads to migration of motile cells onto the top of the colonies and formation of mushroom-shaped structures. This model proposes that the formation of mushroom-shaped structures can be predicted by parameters at the time of bacteria inoculation. Depending on nutrient levels and the initial number density of stalks, mushroom-shaped structures only form in a restricted regime. This opens the possibility of early manipulation of spatial pattern formation in bacterial colonies, using environmental factors.

PMID: 27611778 [PubMed - as supplied by publisher]

Different next generation sequencing platforms produce different microbial profiles and diversity in cystic fibrosis sputum.

J Microbiol Methods. 2016 Sep 5;

Authors: Hahn A, Sanyal A, Perez G, Colberg-Poley AM, Campos J, Rose M, Pérez-Losada M

Abstract
BACKGROUND: Cystic fibrosis (CF) is an autosomal recessive disease characterized by recurrent lung infections. Studies of the lung microbiome have shown an association between decreasing diversity and progressive disease. 454 pyrosequencing has frequently been used to study the lung microbiome in CF, but will no longer be supported. We sought to identify the benefits and drawbacks of using two state-of-the-art next generation sequencing (NGS) platforms, MiSeq and PacBio RSII, to characterize the CF lung microbiome. Each has its advantages and limitations.
METHODS: Twelve samples of extracted bacterial DNA were sequenced on both MiSeq and PacBio NGS platforms. DNA was amplified for the V4 region of the 16S rRNA gene and libraries were sequenced on the MiSeq sequencing platform, while the full 16S rRNA gene was sequenced on the PacBio RSII sequencing platform. Raw FASTQ files generated by the MiSeq and PacBio platforms were processed in mothur v1.35.1.
RESULTS: There was extreme discordance in alpha-diversity of the CF lung microbiome when using the two platforms. Because of its depth of coverage, sequencing of the 16S rRNA V4 gene region using MiSeq allowed for the observation of many more operational taxonomic units (OTUs) and higher Chao1 and Shannon indices than the PacBio RSII. Interestingly, several patients in our cohort had Escherichia, an unusual pathogen in CF. Also, likely because of its coverage of the complete 16S rRNA gene, only PacBio RSII was able to identify Burkholderia, an important CF pathogen.
CONCLUSION: When comparing microbiome diversity in clinical samples from CF patients using 16S sequences, MiSeq and PacBio NGS platforms may generate different results in microbial community composition and structure. It may be necessary to use different platforms when trying to correctly identify dominant pathogens versus measuring alpha-diversity estimates, and it would be important to use the same platform for comparisons to minimize errors in interpretation.

PMID: 27609714 [PubMed - as supplied by publisher]

Different strategies of metabolic regulation in cyanobacteria: from transcriptional to biochemical control.

Sci Rep. 2016;6:33024

Authors: Jablonsky J, Papacek S, Hagemann M

Abstract
Cyanobacteria Synechococcus sp. PCC 7942 and Synechocystis sp. PCC 6803 show similar changes in the metabolic response to changed CO2 conditions but exhibit significant differences at the transcriptomic level. This study employs a systems biology approach to investigate the difference in metabolic regulation of Synechococcus sp. PCC 7942 and Synechocystis sp. PCC 6803. Presented multi-level kinetic model for Synechocystis sp. PCC 6803 is a new approach integrating and analysing metabolomic, transcriptomic and fluxomics data obtained under high and ambient CO2 levels. Modelling analysis revealed that higher number of different isozymes in Synechocystis 6803 improves homeostatic stability of several metabolites, especially 3PGA by 275%, against changes in gene expression, compared to Synechococcus sp. PCC 7942. Furthermore, both cyanobacteria have the same amount of phosphoglycerate mutases but Synechocystis 6803 exhibits only ~20% differences in their mRNA levels after shifts from high to ambient CO2 level, in comparison to ~500% differences in the case of Synechococcus sp. PCC 7942. These and other data imply that the biochemical control dominates over transcriptional regulation in Synechocystis 6803 to acclimate central carbon metabolism in the environment of variable inorganic carbon availability without extra cost carried by large changes in the proteome.

PMID: 27611502 [PubMed - as supplied by publisher]

A systems biology approach reveals major metabolic changes in the thermoacidophilic archaeon Sulfolobus solfataricus in response to the carbon source L-fucose versus D-glucose.

Mol Microbiol. 2016 Sep 9;

Authors: Wolf J, Stark H, Fafenrot K, Albersmeier A, Pham TK, Müller KB, Meyer B, Hoffmann L, Shen L, Albaum SP, Kouril T, Schmidt-Hohagen K, Neumann-Schaal M, Bräsen C, Kalinowski J, Wright PC, Albers SV, Schomburg D, Siebers B

Abstract
Archaea are characterised by a complex metabolism with many unique enzymes that differ from their bacterial and eukaryotic counterparts. The thermoacidophilic archaeon Sulfolobus solfataricus is known for its metabolic versatility and is able to utilize a great variety of different carbon sources. However, the underlying degradation pathways and their regulation are often unknown. In this work, we analyse growth on different carbon sources using an integrated systems biology approach. The comparison of growth on L-fucose and D-glucose allows first insights into the genome-wide changes in response to the two carbon sources and revealed a new pathway for L-fucose degradation in S. solfataricus. During growth on L-fucose we observed major changes in the central carbon metabolic network, as well as an increased activity of the glyoxylate bypass and the 3-hydroxypropionate/4-hydroxybutyrate cycle. Within the newly discovered pathway for L-fucose degradation the following key reactions were identified: (i) L-fucose oxidation to L-fuconate via a dehydrogenase, (ii) dehydration to 2-keto-3-deoxy-L-fuconate via dehydratase, (iii) 2-keto-3-deoxy-L-fuconate cleavage to pyruvate and L-lactaldehyde via aldolase and (iv) L-lactaldehyde conversion to L-lactate via aldehyde dehydrogenase. This pathway as well as L-fucose transport shows interesting overlaps to the D-arabinose pathway, representing another example for pathway promiscuity in Sulfolobus species. This article is protected by copyright. All rights reserved.

PMID: 27611014 [PubMed - as supplied by publisher]

TNIP2 is a hub protein in the NF-&(kappa)B network with both protein and RNA mediated interactions.

Mol Cell Proteomics. 2016 Sep 8;

Authors: Banks CA, Boanca G, Lee ZT, Eubanks CG, Hattem GL, Peak A, Weems LE, Conkright JJ, Florens L, Washburn MP

Abstract
The NF-κB family of transcription factors is pivotal in controlling cellular responses to environmental stresses; abnormal NF-κB signaling features in many autoimmune diseases and cancers. Several components of the NF-κB signaling pathway have been reported to interact with the protein TNIP2 (also known as ABIN2), and TNIP2 can both positively and negatively regulate NF-κB- dependent transcription of target genes. However, the function of TNIP2 remains elusive and the cellular machinery associating with TNIP2 has not been systematically defined. Here we first used a broad MudPIT/Halo AP-MS approach to map the network of proteins associated with the NF-κB transcription factors, and establish TNIP2 as an NF-κB network hub protein. We then combined AP-MS with biochemical approaches in a more focused study of truncated and mutated forms of TNIP2 to map protein associations with distinct regions of TNIP2. NF-κB interacted with the N-terminal region of TNIP2. A central region of TNIP2 interacted with the endosomal sorting complex ESCRT-I via its TSG101 subunit, a protein essential for HIV-1 budding, and a single point mutant in TNIP2 disrupted this interaction. The major gene ontology category for TNIP2 associated proteins was mRNA metabolism, and several of these associations, like KHDRBS1, were lost upon depletion of RNA. Given the major association of TNIP2 with mRNA metabolism proteins, we analyzed the RNA content of affinity purified TNIP2 using RNA-Seq. Surprisingly, a specific limited number of mRNAs was associated with TNIP2. These RNAs were enriched for transcription factor binding, transcription factor co-factor activity, and transcription regulator activity. They included mRNAs of genes in the Sin3A complex, the Mediator complex, JUN, HOXC6, and GATA2. Taken together, our findings suggest an expanded role for TNIP2, establishing a link between TNIP2, cellular transport machinery, and RNA transcript processing.

PMID: 27609421 [PubMed - as supplied by publisher]

Q&A: Gordon Mills on Neomorphs in Cancer.

Cancer Discov. 2016 Sep 8;

Authors:

Abstract
Gordon Mills, MD, PhD, chair of systems biology at The University of Texas MD Anderson Cancer Center in Houston, discusses a third category of genomic aberrations besides oncogene activation or tumor suppressor inactivation: neomorphs, or mutations that rewire cellular signaling in unexpected ways, with important functional consequences.

PMID: 27609219 [PubMed - as supplied by publisher]

Hydrogen peroxide and central redox theory for aerobic life: A tribute to Helmut Sies: Scout, trailblazer, and redox pioneer.

Arch Biochem Biophys. 2016 Apr 1;595:13-8

Authors: Jones DP

Abstract
When Rafael Radi and I wrote about Helmut Sies for the Redox Pioneer series, I was disappointed that the Editor restricted us to the use of "Pioneer" in the title. My view is that Helmut was always ahead of the pioneers: He was a scout discovering paths for exploration and a trailblazer developing strategies and methods for discovery. I have known him for nearly 40 years and greatly enjoyed his collegiality as well as brilliance in scientific scholarship. He made monumental contributions to 20th century physiological chemistry beginning with his first measurement of H2O2 in rat liver. While continuous H2O2 production is dogma today, the concept of H2O2 production in mammalian tissues was largely buried for half a century. He continued this leadership in research on oxidative stress, GSH, selenium, and singlet oxygen, during the timeframe when physiological chemistry and biochemistry transitioned to contemporary 21st century systems biology. His impact has been extensive in medical and health sciences, especially in nutrition, aging, toxicology and cancer. I briefly summarize my interactions with Helmut, stressing our work together on the redox code, a set of principles to link mitochondrial respiration, bioenergetics, H2O2 metabolism, redox signaling and redox proteomics into central redox theory.

PMID: 27095208 [PubMed - indexed for MEDLINE]

A Systems Biology-Based Investigation into the Pharmacological Mechanisms of Sheng-ma-bie-jia-tang Acting on Systemic Lupus Erythematosus by Multi-Level Data Integration.

Sci Rep. 2015;5:16401

Authors: Huang L, Lv Q, Liu F, Shi T, Wen C

Abstract
Sheng-ma-bie-jia-tang (SMBJT) is a Traditional Chinese Medicine (TCM) formula that is widely used for the treatment of Systemic Lupus Erythematosus (SLE) in China. However, molecular mechanism behind this formula remains unknown. Here, we systematically analyzed targets of the ingredients in SMBJT to evaluate its potential molecular mechanism. First, we collected 1,267 targets from our previously published database, the Traditional Chinese Medicine Integrated Database (TCMID). Next, we conducted gene ontology and pathway enrichment analyses for these targets and determined that they were enriched in metabolism (amino acids, fatty acids, etc.) and signaling pathways (chemokines, Toll-like receptors, adipocytokines, etc.). 96 targets, which are known SLE disease proteins, were identified as essential targets and the rest 1,171 targets were defined as common targets of this formula. The essential targets directly interacted with SLE disease proteins. Besides, some common targets also had essential connections to both key targets and SLE disease proteins in enriched signaling pathway, e.g. toll-like receptor signaling pathway. We also found distinct function of essential and common targets in immune system processes. This multi-level approach to deciphering the underlying mechanism of SMBJT treatment of SLE details a new perspective that will further our understanding of TCM formulas.

PMID: 26560501 [PubMed - indexed for MEDLINE]