Globally increased ultraconserved noncoding RNA expression in pancreatic adenocarcinoma

This is the final version of the article. Available from the publisher via the DOI in this record.Transcribed ultraconserved regions (T-UCRs) are a class of non-coding RNAs with 100% sequence conservation among human, rat and mouse genomes. T-UCRs are differentially expressed in several cancers, however their expression in pancreatic adenocarcinoma (PDAC) has not been studied. We used a qPCR array to profile all 481 T-UCRs in pancreatic cancer specimens, pancreatic cancer cell lines, during experimental pancreatic desmoplasia and in the pancreases of P48Cre/wt; KrasLSL-G12D/wt mice. Fourteen, 57 and 29% of the detectable T-UCRs were differentially expressed in the cell lines, human tumors and transgenic mouse pancreases, respectively. The vast majority of the differentially expressed T-UCRs had increased expression in the cancer. T-UCRs were monitored using an in vitro model of the desmoplastic reaction. Twenty-five % of the expressed T-UCRs were increased in the HPDE cells cultured on PANC-1 cellular matrix. UC.190, UC.233 and UC.270 were increased in all three human data sets. siRNA knockdown of each of these three T-UCRs reduced the proliferation of MIA PaCa-2 cells up to 60%. The expression pattern among many T-UCRs in the human and mouse pancreases closely correlated with one another, suggesting that groups of T-UCRs are co-activated in PDAC. Successful knockout of the transcription factor EGR1 in PANC-1 cells caused a reduction in the expression of a subset of T-UCRs suggesting that EGR1 may control T-UCR expression in PDAC. We report a global increase in expression of T-UCRs in both human and mouse PDAC. Commonalties in their expression pattern suggest a similar mechanism of transcriptional upregulation for T-UCRs in PDAC.Supported by grants R21/R33CA114304 and U01CA111294. G.A.C. is supported as a Fellow at The University of Texas MD Anderson Research Trust, as a University of Texas System Regents Research Scholar and by the CLL Global Research Foundation. Work in Dr. Calin’s laboratory is supported in part by a 2009 Seena Magowitz–Pancreatic Cancer Action Network AACR Pilot Grant, the Laura and John Arnold Foundation, the RGK Foundation and the Estate of C. G. Johnson, Jr. A.C.P.A.P. was supported by NIH fellowship 5F31CA142238

Synthetic long non-coding RNAs [SINEUPs] rescue defective gene expression in vivo

Non-coding RNAs provide additional regulatory layers to gene expression as well as the potential to being exploited as therapeutic tools. Non-coding RNA-based therapeutic approaches have been attempted in dominant diseases, however their use for treatment of genetic diseases caused by insufficient gene dosage is currently more challenging. SINEUPs are long antisense non-coding RNAs that up-regulate translation in mammalian cells in a gene-specific manner, although, so far evidence of SINEUP efficacy has only been demonstrated in in vitro systems. We now show that synthetic SINEUPs effectively and specifically increase protein levels of a gene of interest in vivo. We demonstrated that SINEUPs rescue haploinsufficient gene dosage in a medakafish model of a human disorder leading to amelioration of the disease phenotype. Our results demonstrate that SINEUPs act through mechanisms conserved among vertebrates and that SINEUP technology can be successfully applied in vivo as a new research and therapeutic tool for gene-specific up-regulation of endogenous functional proteins

Selection of optimal reference genes for normalization in quantitative RT-PCR

<p>Abstract</p> <p>Background</p> <p>Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.</p> <p>Results</p> <p>We propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.</p> <p>Conclusions</p> <p>The proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.</p

Transgenic plants of Petunia hybrida harboring the CYP2E1 gene efficiently remove benzene and toluene pollutants and improve resistance to formaldehyde

The CYP2E1 protein belongs to the P450 enzymes family and plays an important role in the metabolism of small molecular and organic pollutants. In this study we generated CYP2E1 transgenic plants of Petunia using Agrobacterium rhizogenes K599. PCR analysis confirmed that the regenerated plants contained the CYP2E1 transgene and the rolB gene of the Ri plasmid. Southern blotting revealed the presence of multiple copies of CYP2E1 in the genome of transgenic plants. Fluorescent quantitative PCR revealed exogenous CYP2E1 gene expression in CYP2E1 transgenic plants at various levels, whereas no like expression was detected in either GUS transgenic plants or wild-types. The absorption of benzene and toluene by transgenic plants was analyzed through quantitative gas chromatography. Transgenic plants with high CYP2E1 expression showed a significant increase in absorption capacity of environmental benzene and toluene, compared to control GUS transgenic and wild type plants. Furthermore, these plants also presented obvious improved resistance to formaldehyde. This study, besides being the first to reveal that the CYP2E1 gene enhances plant resistance to formaldehyde, also furnishes a new method for reducing pollutants, such as benzene, toluene and formaldehyde, by using transgenic flowering horticultural plants

Inhibition of GATA2 restrains cell proliferation and enhances apoptosis and chemotherapy mediated apoptosis in human GATA2 overexpressing AML cells

GATA2, a zinc finger transcription factor predominantly expressed in hematopoietic cells, acts as an essential regulator of hematopoietic stem cell generation, survival and functionality. Loss and gain of GATA2 expression has been implicated in myelodysplastic syndrome and acute myeloid leukemia (AML) yet the precise biological impact of GATA2 expression on human AML cell fate decisions remains ambiguous. Herein, we performed large-scale bioinformatics that demonstrated relatively frequent GATA2 overexpression in AML patients as well as select human AML (or AML-like) cell lines. By using shRNAi to target GATA2 in these AML cell lines, and an AML cell line expressing normal levels of GATA2, we found that inhibition of GATA2 caused attenuated cell proliferation and enhanced apoptosis exclusively in AML cell lines that overexpress GATA2. We proceeded to pharmacologically inhibit GATA2 in concert with AML chemotherapeutics and found this augmented cell killing in AML cell lines that overexpress GATA2, but not in an AML cell line expressing normal levels of GATA2. These data indicate that inhibition of GATA2 enhances chemotherapy-mediated apoptosis in human AML cells overexpressing GATA2. Thus, we define novel insights into the oncogenic role of GATA2 in human AML cells and suggest the potential utilization of transient GATA2 therapeutic targeting in AML

The alpha 7 nicotinic receptor agonist PHA-543613 hydrochloride inhibits <i>Porphyromonas gingivalis</i>-induced expression of interleukin-8 by oral keratinocytes

Objective: The alpha 7 nicotinic receptor (α7nAChR) is expressed by oral keratinocytes. α7nAChR activation mediates anti-inflammatory responses. The objective of this study was to determine if α7nAChR activation inhibited pathogen-induced interleukin-8 (IL-8) expression by oral keratinocytes.&lt;p&gt;&lt;/p&gt; Materials and methods: Periodontal tissue expression of α7nAChR was determined by real-time PCR. OKF6/TERT-2 oral keratinocytes were exposed to &lt;i&gt;Porphyromonas gingivalis&lt;/i&gt; in the presence and absence of a α7nAChR agonist (PHA-543613 hydrochloride) alone or after pre-exposure to a specific α7nAChR antagonist (α-bungarotoxin). Interleukin-8 (IL-8) expression was measured by ELISA and real-time PCR. Phosphorylation of the NF-κB p65 subunit was determined using an NF-κB p65 profiler assay and STAT-3 activation by STAT-3 in-cell ELISA. The release of ACh from oral keratinocytes in response to &lt;i&gt;P. gingivalis&lt;/i&gt; lipopolysaccharide was determined using a GeneBLAzer M3 CHO-K1-blacell reporter assay.&lt;p&gt;&lt;/p&gt; Results: Expression of α7nAChR mRNA was elevated in diseased periodontal tissue. PHA-543613 hydrochloride inhibited &lt;i&gt;P. Gingivalis&lt;/i&gt;-induced expression of IL-8 at the transcriptional level. This effect was abolished when cells were pre-exposed to a specific α7nAChR antagonist, α-bungarotoxin. PHA-543613 hydrochloride downregulated NF-κB signalling through reduced phosphorylation of the NF-κB p65-subunit. In addition, PHA-543613 hydrochloride promoted STAT-3 signalling by maintenance of phosphorylation. Furthermore, oral keratinocytes upregulated ACh release in response to &lt;i&gt;P. Gingivalis&lt;/i&gt; lipopolysaccharide.&lt;p&gt;&lt;/p&gt; Conclusion: These data suggest that α7nAChR plays a role in regulating the innate immune responses of oral keratinocytes.&lt;p&gt;&lt;/p&gt

A Non-coding RNA of Insect HzNV-1 Virus Establishes Latent Viral Infection through MicroRNA

Heliothis zea nudivirus-1 (HzNV-1) is an insect virus previously known as Hz-1 baculovirus. One of its major early genes, hhi1, is responsible for the establishment of productive viral infection; another gene, pag1, which expresses a non-coding RNA, is the only viral transcript detectable during viral latency. Here we showed that this non-coding RNA was further processed into at least two distinct miRNAs, which targeted and degraded hhi1 transcript. This is a result strikingly similar to a recent report that herpes simplex virus produces tightly-regulated latent specific miRNAs to silence its own key early transcripts. Nevertheless, proof for the establishment of viral latency by miRNA is still lacking. We further showed that HzNV-1 latency could be directly induced by pag1-derived miRNAs in cells infected with a pag1-deleted, latency-deficient virus. This result suggests the existence of a novel mechanism, where miRNAs can be functional for the establishment of viral latency

TRIB2 confers resistance to anti-cancer therapy by activating the serine/threonine protein kinase AKT.

Intrinsic and acquired resistance to chemotherapy is the fundamental reason for treatment failure for many cancer patients. The identification of molecular mechanisms involved in drug resistance or sensitization is imperative. Here we report that tribbles homologue 2 (TRIB2) ablates forkhead box O activation and disrupts the p53/MDM2 regulatory axis, conferring resistance to various chemotherapeutics. TRIB2 suppression is exerted via direct interaction with AKT a key signalling protein in cell proliferation, survival and metabolism pathways. Ectopic or intrinsic high expression of TRIB2 induces drug resistance by promoting phospho-AKT (at Ser473) via its COP1 domain. TRIB2 expression is significantly increased in tumour tissues from patients correlating with an increased phosphorylation of AKT, FOXO3a, MDM2 and an impaired therapeutic response. This culminates in an extremely poor clinical outcome. Our study reveals a novel regulatory mechanism underlying drug resistance and suggests that TRIB2 functions as a regulatory component of the PI3K network, activating AKT in cancer cells

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens