Protein Acetylation as an Integral Part of Metabolism in Cancer Development and Progression

Acetylation of lysine is one of the major post-translational modifications of histone and non-histone proteins of eukaryotic cells. Acetylation has been indicated as an avenue for cellular response to environmental, nutritional and behavioral factors. At the same time, aberrant protein acetylation has been related to cancer as well as many other diseases. Abnormal expression of some classes of histone deacetylases and histone acetyl transferases has been documented for the majority of cancers. These observations have led to extensive efforts in the development of inhibitors for these enzymes for the treatment of cancer as well as other diseases as well as pathogen control.Regulation of protein activities and gene expression by acetylation influences many processes relevant for cancer development, including metabolism. At the same time acetylation depends on a number of metabolic co-factors and a variety of metabolites act as inhibitors of acetylation proteins making acetylation enzymes an integral part of metabolism. Cancer metabolic phenotype is generally understood as one of the major hallmarks of cancer and thus the interplay between acetylation, anabolism and catabolism provides a very interesting forum for exploration of cancer development and for novel treatments. An ever increasing pool of publications shows relationships between the acetylation process and related enzymes with metabolites in cancerous and non-cancerous systems. In this review we are presenting previously established relationships between acetylation/deacetylation, metabolites and enzyme regulation particularly in relation to cancer development, progression and treatment

“Omics”-Informed drug and biomarker discovery : opportunities, challenges and future perspectives

The pharmaceutical industry faces unsustainable program failure despite significant increases in investment. Dwindling discovery pipelines, rapidly expanding R&D budgets and increasing regulatory control, predict significant gaps in the future drug markets. The cumulative duration of discovery from concept to commercialisation is unacceptably lengthy, and adds to the deepening crisis. Existing animal models predicting clinical translations are simplistic, highly reductionist and, therefore, not fit for purpose. The catastrophic consequences of ever-increasing attrition rates are most likely to be felt in the developing world, where resistance acquisition by killer diseases like malaria, tuberculosis and HIV have paced far ahead of new drug discovery. The coming of age of Omics-based applications makes available a formidable technological resource to further expand our knowledge of the complexities of human disease. The standardisation, analysis and comprehensive collation of the “data-heavy” outputs of these sciences are indeed challenging. A renewed focus on increasing reproducibility by understanding inherent biological, methodological, technical and analytical variables is crucial if reliable and useful inferences with potential for translation are to be achieved. The individual Omics sciences—genomics, transcriptomics, proteomics and metabolomics—have the singular advantage of being complimentary for cross validation, and together could potentially enable a much-needed systems biology perspective of the perturbations underlying disease processes. If current adverse trends are to be reversed, it is imperative that a shift in the R&D focus from speed to quality is achieved. In this review, we discuss the potential implications of recent Omics-based advances for the drug development process

Effects of Atmospheric CO2 Level on the Metabolic Response of Resistant and Susceptible Wheat to Fusarium graminearum Infection.

Rising atmospheric CO2 concentrations and associated climate changes are thought to have contributed to the steady increase of Fusarium head blight (FHB) on wheat. However, our understanding of precisely how elevated CO2 influences the defense response of wheat against Fusarium graminearum remains limited. In this study, we evaluated the metabolic profiles of susceptible (Norm) and moderately resistant (Alsen) spring wheat in response to whole-head inoculation with two deoxynivalenol (DON)-producing F. graminearum isolates (DON+), isolates 9F1 and Gz3639, and a DON-deficient (DON−) isolate (Gzt40) at ambient (400 ppm) and elevated (800 ppm) CO2 concentrations. The effects of elevated CO2 were dependent on both the Fusarium strain and the wheat variety, but metabolic differences in the host can explain the observed changes in F. graminearum biomass and DON accumulation. The complexity of abiotic and biotic stress interactions makes it difficult to determine if the observed metabolic changes in wheat are a result of CO2-induced changes in the host, the pathogen, or a combination of both. However, the effects of elevated CO2 were not dependent on DON production. Finally, we identified several metabolic biomarkers for wheat that can reliably predict FHB resistance or susceptibility, even as atmospheric CO2 levels rise

Influence of washing and quenching in profiling the metabolome of adherent mammalian cells: A case study with the metastatic breast cancer cell line MDA-MB-231

Metabolome characterisation is a powerful tool in oncology. To obtain a valid description of the intracellular metabolome, two of the preparatory steps are crucial, namely washing and quenching. Washing must effectively remove the extracellular media components and quenching should stop the metabolic activities within the cell, without altering the membrane integrity of the cell. Therefore, it is important to evaluate the efficiency of the washing and quenching solvents. In this study, we employed two previously optimised protocols for simultaneous quenching and extraction, and investigated the effects of a number of washing steps/solvents and quenching solvent additives, on metabolite leakage from the adherent metastatic breast cancer cell line MDA-MB-231. We explored five washing protocols and five quenching protocols (including a control for each), and assessed for effectiveness by detecting ATP in the medium and cell morphology changes through scanning electron microscopy (SEM) analyses. Furthermore, we studied the overall recovery of eleven different metabolite classes using the GC-MS technique and compared the results with those obtained from the ATP assay and SEM analysis. Our data demonstrate that a single washing step with PBS and quenching with 60% methanol supplemented with 70 mM HEPES (−50 °C) results in minimum leakage of intracellular metabolites. Little or no interference of PBS (used in washing) and methanol/HEPES (used in quenching) on the subsequent GC-MS analysis step was noted. Together, these findings provide for the first time a systematic study into the washing and quenching steps of the metabolomics workflow for studying adherent mammalian cells, which we believe will improve reliability in the application of metabolomics technology to study adherent mammalian cell metabolism

Transcriptional Alterations in Hereditary and Sporadic Nonfunctioning Pancreatic Neuroendocrine Tumors According to Genotype.

BACKGROUND Nonfunctioning pancreatic neuroendocrine tumors (NFPanNETs) may be sporadic or inherited because of germline mutations associated with von Hippel-Lindau disease (VHL) or multiple endocrine neoplasia type 1 (MEN1). The clinical behavior of NFPanNETs is difficult to predict, even in tumors of the same stage and grade. The authors analyzed genotype-specific patterns of transcriptional messenger RNA (mRNA) levels of NFPanNETs to understand the molecular features that determine PanNET phenotype. METHODS Thirty-two samples were included for genome-wide mRNA gene expression analysis (9 VHL-associated, 10 MEN1-associated, and 9 sporadic NFPanNETs and 4 purified normal islet cell [NIC] samples). Validation of genes was performed by real-time polymerase chain reaction analysis and immunohistochemistry. Gene expression profiles were analyzed by tumor genotype, and pathway analysis was curated. RESULTS Consensus clustering of mRNA expression revealed separate clustering of NICs, VHL-associated NFPanNETs, and MEN1-associated NFPanNETs; whereas some sporadic tumors clustered with MEN1. Four of 5 MEN1-like sporadic PanNET subtypes had loss of heterozygosity at the MEN1 gene locus. Pathway analysis demonstrated subtype-specific pathway activation, comprising angiogenesis and immune response in VHL; neuronal development in MEN1; protein ubiquitination in the new MEN1/sporadic subtype; and cytokinesis and cilium/microtubule development in sporadic NFPanNETs. Among many genes, platelet-derived growth factor receptor β (PDGFRB), lymphoid enhancer-binding factor-1 (Lef-1), cyclin-dependent kinase 4 (CDK4), and CDK6 were upregulated in VHL or MEN1 NFPanNETs, providing potential subtype-specific treatment targets. CONCLUSIONS Distinct mRNA expression patterns were identified in sporadic-associated, VHL-associated, and MEN1-associated NFPanNETs. The current results uncover new pathways involved in NFPanNETs that are subtype-specific and provide potential new diagnostic or therapeutic targets based on tumor subtype. Cancer 2017. © 2017 American Cancer Society

Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq

Tissue-specific alternative splicing is a key mechanism for generating tissue-specific proteomic diversity in eukaryotes. Splicing regulatory elements (SREs) in pre-mature messenger RNA play a very important role in regulating alternative splicing. In this article, we use mouse RNA-Seq data to determine a positive data set where SREs are over-represented and a reliable negative data set where the same SREs are most likely under-represented for a specific tissue and then employ a powerful discriminative approach to identify SREs. We identified 456 putative splicing enhancers or silencers, of which 221 were predicted to be tissue-specific. Most of our tissue-specific SREs are likely different from constitutive SREs, since only 18% of our exonic splicing enhancers (ESEs) are contained in constitutive RESCUE-ESEs. A relatively small portion (20%) of our SREs is included in tissue-specific SREs in human identified in two recent studies. In the analysis of position distribution of SREs, we found that a dozen of SREs were biased to a specific region. We also identified two very interesting SREs that can function as an enhancer in one tissue but a silencer in another tissue from the same intronic region. These findings provide insight into the mechanism of tissue-specific alternative splicing and give a set of valuable putative SREs for further experimental investigations

Orthodontics in the era of big data analytics

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149344/1/ocr12279_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149344/2/ocr12279.pd

Statistical HOmogeneous Cluster SpectroscopY (SHOCSY): an optimized statistical approach for clustering of ¹H NMR spectral data to reduce interference and enhance robust biomarkers selection.

We propose a novel statistical approach to improve the reliability of (1)H NMR spectral analysis in complex metabolic studies. The Statistical HOmogeneous Cluster SpectroscopY (SHOCSY) algorithm aims to reduce the variation within biological classes by selecting subsets of homogeneous (1)H NMR spectra that contain specific spectroscopic metabolic signatures related to each biological class in a study. In SHOCSY, we used a clustering method to categorize the whole data set into a number of clusters of samples with each cluster showing a similar spectral feature and hence biochemical composition, and we then used an enrichment test to identify the associations between the clusters and the biological classes in the data set. We evaluated the performance of the SHOCSY algorithm using a simulated (1)H NMR data set to emulate renal tubule toxicity and further exemplified this method with a (1)H NMR spectroscopic study of hydrazine-induced liver toxicity study in rats. The SHOCSY algorithm improved the predictive ability of the orthogonal partial least-squares discriminatory analysis (OPLS-DA) model through the use of "truly" representative samples in each biological class (i.e., homogeneous subsets). This method ensures that the analyses are no longer confounded by idiosyncratic responders and thus improves the reliability of biomarker extraction. SHOCSY is a useful tool for removing irrelevant variation that interfere with the interpretation and predictive ability of models and has widespread applicability to other spectroscopic data, as well as other "omics" type of data

Alternative splicing enriched cDNA libraries identify breast cancer-associated transcripts

<p>Abstract</p> <p>Background</p> <p>Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by <it>ERBB2</it> (<it>HER-2/neu</it>) oncogene expression.</p> <p>Results</p> <p>The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of <it>ERBB2</it>-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of <it>ERBB2</it>. The relative expression balance between AS variants from 3 genes was differentially modulated by <it>ERBB2</it> in this model system.</p> <p>Conclusions</p> <p>In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts that were differently modulated by <it>ERBB2</it>-mediated expression and that can be tested as molecular markers for breast cancer. Such a methodology will be useful for completely deciphering the cancer cell transcriptome diversity resulting from AS and for finding more precise molecular markers.</p