Posts Tagged ‘rRNA’

What is the meaning of so many RNAs?

Writer and Curator: Larry H. Bernstein, MD, FCAP


The following is a third in the 2nd series that is focused on the topic of the impact of genomics and transcriptomics in the evolution of 21st century of medicine, We have already visited the transcription process, by which an RNA sequence is read.  This is essential for protein synthesis through the ordering of the amino acids in the primary structure. However, there are microRNAs and noncoding RNAs, and there are transcription factors.  The transcription factors bind to chromatin, and the RNAs also have some role in regulating the transcription process. We shall examine this further.

  • RNA and the transcription the genetic code

Larry H. Bernstein, MD, FCAP, Writer and Curator

  • The role and importance of transcription factors?

Larry H. Bernstein, MD, FCAP, Writer and Curator

  • What is the meaning of so many RNAs?

Larry H. Bernstein, MD, FCAP, Writer and Curator

  • Pathology Emergence in the 21st Century

Larry Bernstein, MD, FCAP, Author and Curator

  • The Arnold Relman Challenge: US HealthCare Costs vs US HealthCare Outcomes

Larry H. Bernstein, MD, FCAP, Reviewer and Curator; and Aviva Lev-Ari, PhD, RN, Curator

Exploring the Roles of Enhancer RNAs Scientists have recently discovered that enhancers are often transcribed into RNAs. But they’re still not sure what, if anything, these eRNAs do.

By Ashley P. Taylor | May 7, 2014

Four mechanisms by which eRNAs can function

Four mechanisms by which eRNAs can function

Four mechanisms by which eRNAs can function Wikimedia, PClermont There’s a lot that scientists don’t yet know about enhancers, genetic elements first described almost 35 years ago that, unlike promoters,

  • can upregulate genes from some distance.

That distance, while generally under 100 kilobases, can vary greatly. Usually,

  • enhancers regulate the genes closest to them,

but not always; the enhancer for the developmental gene Sonic hedgehog is a megabase away from its promoter in the human genome. What scientists do know is that enhancers seem to play key roles in human biology. One recently published atlas of enhancer expression in the human genome suggested that

  • enhancers, which are expressed differently across cell types,

could help explain how one genome encodes so many different kinds of cells. The same paper reported that

  • single-nucleotide changes associated with human diseases are
  • over-represented in enhancers and promoters relative to exons.

In a 2010 Nature paper, researchers in the lab of neurobiologist Michael Greenberg at Harvard Medical School reported that enhancers can produce RNA. Working with cultured mouse neurons, the scientists found that

  • enhancers activated by neuron depolarization were transcribed all over the genome
  • and that levels of enhancer RNAs (eRNAs)
  • correlated with the production of messenger RNA (mRNA)
  • from genes near the enhancers.

Researchers had observed enhancer RNAs before, but this was the first evidence of widespread enhancer transcription. In the years since, several other groups have reported finding eRNAs in various biological systems. While eRNAs promise to help researchers understand how enhancers work, they also raise many questions of their own. ERNAs are fairly short, ranging in length from 500 basepairs to 5 kilobases. Most of the time, although not always,

  • enhancer RNAs are transcribed from both DNA strands, producing what are called bidirectional transcripts.

As the Greenberg lab originally found,

  • eRNA production correlates with the production of mRNA from the genes that enhancers regulate.

“Perhaps the best mark of an active enhancer is the induction of an enhancer RNA,” said M. Geoffrey Rosenfeld from the University of California, San Diego, whose group studies genome-wide regulation of gene expression and has been probing eRNA function. Of course, correlation does not equal causation, he warned. “The next question is whether the enhancer RNA is just a mark of an active enhancer or if it could have function, per se.” What might those functions be? Scientists have crafted a few hypotheses, although most agree that the mechanisms by which eRNAs function remain a mystery. One thought is that eRNAs represent transcriptional noise. That’s a view held by Albin Sandelin at the Bioinformatics Centre of Copenhagen University, who led the aforementioned enhancer atlas project. “Something that most people believe is that the enhancer, when it’s active, it loops in to the promoter, and then the concentration of RNA polymerase II will be a lot higher,” Sandelin told The Scientist. He referred to the idea that

  • enhancers upregulate genes by physically interacting with target promoters;
  • as enhancers and the promoters they regulate are usually on the same chromosome,
  • this interaction creates a loop of DNA between the two genetic elements.

“I think that most of the eRNAs are due to this: you have piece of open DNA, which is the enhancer, near a promoter with high concentrations of RNA polymerase II, and

  • then you will get transcription of the enhancer.”

This idea is supported by the fact that, because they are so short, eRNAs tend to degrade rather quickly. “There are a few cases where [enhancer RNAs] are proven to be functional; I just personally don’t think that the majority work that way,” Sandelin said. “[But] it seems to me that this [supposed function] is a byproduct of proximity to some sites that have a lot of polymerase II.” Another hypothesis suggests that

  • the act of transcription trumps the importance of the transcripts themselves.

Experiments in macrophages, led by the University of California, San Diego’s Chris Glass, support this idea. “I don’t think that transcription at enhancers is noise,” said Vittorio Sartorelli, a researcher at the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) who has studied eRNAs in the context of myogenesis. “Whether eRNAs are absolutely required in every situation or the act of transcription at enhancers is the major determinant, I think that it’s still open for debate,” he said. Several studies have presented evidence to suggest that eRNAs do play a key role. As described in a 2013 Nature paper, the Rosenfeld lab found that estrogen bound to its receptor in breast cancer cells increases expression of particular genes by binding to enhancers and inducing the transcription of eRNAs. Eliminating the eRNAs using both RNA interference (RNAi) and antisense oligonucleotides—

  • which bind to the RNA and lead to its degradation by an RNase—
  • reduced the ability of enhancers to upregulate gene expression.

Depletion of eRNAs in this system also

  • reduced looping between enhancers and promoters.

“Using two different strategies, there [was] evidence that

  • the presence of the interrogated eRNA is important for activation of the target gene
  • and for the interaction between the enhancer and the cognate regulated promoter,” said Rosenfeld.

Taking the reverse approach, the researchers also tested whether eRNAs could upregulate transcription independent of the enhancer itself. Rosenfeld and his colleagues experimentally

  • tethered eRNAs to a promoter driving expression of a luciferase reporter gene in a plasmid construct. When this construct was
  • transfected into cultured breast cancer cells,
    • luciferase expression was upregulated about 2.5-fold.

“These data indicate that

  • the interrogated eRNA plays a functional role, at least in this system,
  • in activation of the coding target gene,”

said Rosenfeld. “But it does not distinguish between the alternative possibilities that this is because of a specific sequence in the eRNA that might interact with a regulatory factor or that some other function of the eRNA …” Scientists, such as Reuven Agami from the Netherlands Cancer Institute, the NIAMS’s Sartorelli, and San Diego’s Glass, have reported similar results in other systems. Greenberg said that some eRNAs could have functions unrelated to the promoters activated by their associated enhancers while others could play direct roles in gene expression. “I think that we need to keep an open mind as to what the functions are; there are likely to be multiple functions.” Tags: transcriptional       regulationtranscriptionRNAipromotersmRNAEnhancers and DNA   SiRNA-Mediated Down-Regulation of Livin Expression in Breast Cancer Cells Hussein Sabit, Mohamed M.M. Ibrahim and Nabil S. Awad 1College of Biotechnology, Misr University for Science and Technology, Egypt 2Scientific Research Deanship, Taif University, KSA Academic Journal of Cancer Research 6 (2): 69-73, 2013   Livin, also called melanoma inhibitor of apoptosis protein (IAP) or kidney IAP, is an anti-apoptotic protein belonging to the IAP family which consists of eight members. The genes of this family render cancer cells insensitive to apoptotic stimulation. The aim of the present study was to investigate and assess the role of siRNA

  • in the regulation of livin gene expression in two breast cancer cell lines (4Ti and MCF-7).

Lipofection was carried out to introduce the livin-specific small interference RNA (siRNA) segment (19 mer) into the cancerous cells and the livin expression was determined using RT-PCR. Trypan blue assay was conducted to assess the integrity of the cell membranes after being transfected. 3-(4, 5-dimethylthiazol-2-yl)-2-5-diphenyltetrazolium bromide (MTT) assay was also implemented to assess the cell viability through the mitochondrial reductase enzymes activity. The obtained results concluded that

  • transfecting the cancerous cells with livin-specific siRNA have
  • led to the down regulation of livin expression.

RNA interference (RNAi) targeting the anti-apoptotic genes such as livin is a promising approach and may help as a future therapeutic tool for breast cancer. Key words: SiRNA Livin Down-regulation Breast cancer     Endogenous RNA interference is driven by copy number Cristina Cruz, Jonathan Houseley* Epigenetics Programme, The Babraham Institute, Cambridge, United Kingdom Cell biology | Genomics and evolutionary biology cruz and Houseley. eLife 2014;3:e01581   A plethora of non-protein coding RNAs are produced throughout eukaryotic genomes, many of which are transcribed antisense to protein-coding genes and could potentially instigate

  • RNA interference (RNAi) responses.

Here we have used a synthetic RNAi system to show that

  • gene copy number is a key factor controlling RNAi for transcripts from endogenous loci,

since transcripts from multi-copy loci form double stranded RNA more efficiently than transcripts from equivalently expressed single-copy loci.

  • Selectivity towards transcripts from high-copy DNA

is therefore an emergent property of a minimal RNAi system. The ability of RNAi to

  • selectively degrade transcripts from high-copy loci
  • would allow suppression of newly emerging transposable elements,

but such a surveillance system requires transcription. We show that

  • low-level genome-wide pervasive transcription
  • is sufficient to instigate RNAi, and propose that
  • pervasive transcription is part of a defense mechanism capable of directing a
  • sequence-independent RNAi response against
  • transposable elements amplifying within the genome.     Over the past decade, our understanding of the complexity of the eukaryotic transcriptome has been revolutionized. Genome-wide sequencing studies in many organisms have revealed that protein-coding mRNAs are augmented by a multitude of non-protein coding RNAs (ncRNAs), many produced from regions of the genome traditionally considered to be transcriptionally silent (Brummelkamp et al., 2002; Bertone et al., 2004; Cheng et al., 2005; David et al., 2006; Birney et al., 2007). Functional data for the vast majority of ncRNAs are currently lacking, with only a few examples characterized in any detail; however, the diversity of mechanisms by which these act suggests that ncRNAs have a rich and varied biology that is largely still to be sampled. Long ncRNAs which overlap protein-coding genes have the potential to modulate the expression of their cognate coding RNA. Early characterized examples in yeast were thought to work by directly disrupting transcription factor or polymerase binding to the promoter of the coding RNA (Martens et al., 2004; Hongay et al., 2006); however, more recent data implicate specific chromatin structure changes in repression (Gelfand et al., 2011; Hainer et al., 2011), and many other cases of ncRNAs that alter chromatin modifications have been described (Camblong et al., 2007; Berretta et al., 2008; Houseley et al., 2008; Pinskaya et al., 2009; van Werven et al., 2012). Chromatin modifications are not necessarily repressive, and ncRNAs that enhance expression of their overlapping coding gene have also been described (Uhler et al., 2007; Hirota et al., 2008).

Frequency of annotated antisense non-protein coding RNAs

Frequency of annotated antisense non-protein coding RNAs

Figure 1. Frequency of annotated antisense non-protein coding RNAs (ncRNAs) and effects on mRNA abundance. (A) Schematic of an example sense mRNA-antisense (ncRNA) system. (B) Number of annotated open reading frames (ORFs) with antisense transcripts. Positions of CUTs, SUTs, and XUTs were collated with expressed ORFs (Xu et al., 2009; van Dijk et al., 2011), SUTs were later re-classified as XUTs were removed. Overlaps between ORFs expressed in glucose media (total 5171, Xu et al., 2009) and other RNAs were calculated and summed for increasing minimum overlaps of 50–500 bp. ORF–ORF overlaps and ORF–ncRNA overlaps were analyzed separately as ORF–ORF overlaps are consistently smaller. Detailed figures are given in Table 1. (C) Abundance of short interfering RNAs (siRNAs) in RNA interference (RNAi)+ strain produced from expressed ORFs with and without an annotated overlapping antisense ncRNA, based on read counts from published high-throughput sequencing data (Drinnenberg et al., 2011). Minimum antisense overlap with ORF was set at 250 bp; only ORFs with >100 reads in the wild-type poly(A)+ library were assessed to remove noise. Stated p value calculated by Student’s t test. (D) Abundance of mRNA in RNAi+ cells relative to wild-type; data source and categories as in C, differences were not significant.

Multi-copy loci are preferentially targeted by RNA interference (RNAi).

Multi-copy loci are preferentially targeted by RNA interference (RNAi).

Figure 4. Multi-copy loci are preferentially targeted by RNA interference (RNAi). (A) Short interfering RNA (siRNA) (Drinnenberg et al., 2011) and total RNA (Silva et al., 2002) abundance for loci with copy number <2 (left, single-copy) or ≥2 (right, multi-copy). (B) Quantification of data from A binned into categories of increasing total RNA level, with p values for pairwise comparisons of siRNA abundance in single-copy and multi-copy datasets using the Wilcoxon Rank Sum test. (C) Copy number distribution of the 1% of loci with the highest siRNA:total RNA ratio compared with other loci; difference is significant by Wilcoxon Rank Sum test, p<2.2 × 10−16, loci scoring below noise threshold (0–2 category in B) were removed. n values for tests in B and C are given in Table 2. (D) Comparison of copy number with siRNA:total RNA ratio across chromosome I. Cruz and Houseley. eLife 2014;3:e01581.   eLife digest Genes contain the codes that are needed to make the proteins used by cells. This code is transcribed to make a messenger RNA molecule that is then translated to make a protein. However, other types of RNA called

  • non-coding RNA molecules can disrupt this process
  • by binding to messenger RNA molecules,
  • with matching sequences, before translation begins.

RNA interference involves enzymes called Dicer and Argonaute. Many cells contain large numbers of non-coding RNA molecules—

  • so called because they are not translated to produce proteins—
  • and many of these are capable of starting the process of RNA interference.

However, most do not, and the reasons for this are not understood. Now, work by Cruz and Houseley has provided new insight into this phenomenon by showing that

  • it is related to the number of copies of the gene encoding such RNAs in the genome.

Yeast cells normally do not have the genes for RNA interference, but Cruz and Houseley used

  • genetically engineered yeast cells containing Dicer and Argonaute.

Although most of the messenger RNA molecules in these cells showed no change,

  • the expression of some genes with high ‘copy numbers’ was reduced.

Further experiments that involved adding more and more copies of other genes showed that

  • RNA interference could selectively target messenger RNA molecules produced from genes with an increased copy number—
  • particularly if the copies of the genes were clustered in one location in the genome.

RNA interference is also used to defend against DNA sequences that invade and multiply within a genome, such as viruses and other ‘genetic parasites’. As such, the effect observed by Cruz and Houseley could explain why entire genomes are often continuously copied to RNA at low levels. This activity would allow the monitoring of the genome for the invasion of any genetic parasites that had multiplied to high numbers. Following on from this work, the next challenge will be to understand how gene copy number and location are balanced to achieve a selective RNA interference system.   RNA in unexpected places: long non-coding RNA functions in diverse cellular contexts Sarah Geisler1,2 and Jeff Coller1 1Center for RNA Molecular Biology, Case Western Reserve, Cleveland , OH 2Present address: Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, 4058 Basel, Switzerland. NATURE REVIEWS | MOLECULAR CELL BIOLOGY


Abstract | The increased application of transcriptome-wide profiling approaches has led to an explosion in the number of documented long non-coding RNAs (lncRNAs). While these new and enigmatic players in the complex transcriptional milieu are encoded by a significant proportion of the genome, their functions are mostly unknown. Early discoveries support a paradigm in which   lncRNAs regulate transcription via chromatin modulation, but

  • new functions are steadily emerging.

Given the biochemical versatility of RNA, lncRNAs may be used for various tasks, including

  • post-transcriptional regulation,
  • organization of protein complexes,
  • cell-cell signalling and
  • allosteric regulation of proteins.

Nature Reviews – Molecular Cell Biology | 9 Oct 2013;   In this Review, we focus on the functional attrib­utes of RNA and highlight the unconventional, and perhaps underappreciated, biological contributions of lncRNAs, including the diverse mechanisms through which lncRNAs participate in transcriptional regu­lation. We touch briefly on the roles of lncRNAs in regulating chromatin states, as this has been explored in several recent reviews (see REFS 8,9,13–15). In addi­tion, we highlight roles beyond transcription whereby lncRNAs function in various cellular contexts, includ­ing

  1. post-transcriptional regulation,
  2. post-translational regulation of protein activity,
  3. organization of protein complexes,
  4. cell–cell signalling, as well as
  5. recombination

Transcription activator-like effectors (TALEs). Naturally found in some bacteria, TALEs are proteins that bind DNA through repeat domains, and their code for sequence specificity has been elucidated allowing sequence specific TALEs to be engineered.

  • PUF proteins

A family of sequence-specific RNA-binding proteins, which bind 3ʹ untranslated regions within mRNAs to repress target mRNA translation.

  • Pseudogenes

Dysfunctional relatives of normal genes thought to arise from duplication or retrotransposition.

  • Chromatin-modifying complexes

Protein complexes that catalyse the covalent chemical modification of chromatin

  • Adaptive immune system

A system of specialized cells that create immunological memory via specific antibodies after an initial response to a pathogen.   A biochemically versatile polymer   Figure 1 | RNA is a biochemically versatile polymer. a | RNA is particularly well suited for sequence-specific nucleic acid targeting through base pairing interactions over a short region (for example, eight nucleotides). By contrast, proteins require repeat motifs comprising 35–39 amino acids (105–117 base pairs of genomic sequence) to recognize a single RNA base with specificity. Therefore, to recognize eight nucleotides, 280–312 amino acids (840–936 base pairs of genomic sequence) would be required. Compared to the eight base pairs required for an RNA, protein-based nucleic acid recognition requires substantially more genomic sequence17. b | RNA can fold into complex three-dimensional structures that can specifically bind various ligands, including small molecules and peptides18. c | RNA is suitable for transient expression, because a fully functional RNA can be generated immediately following transcription and processing but can also be rapidly degraded. Together, this allows RNA effectors to be produced in quick pulses. Proteins, however, require additional steps, including mRNA export and translation, to produce a functional peptide. Likewise, both the mRNA and the protein need to be degraded to turn off expression. d | RNA is malleable and, therefore, more tolerant of mutations. Although some mutations in protein-coding genes are silent, many are deleterious such as nonsense mutations that generate truncated polypeptides. RNA, however, can tolerate mutations even within the regions responsible for target recognition. e | RNA-dependent events can be heritable. For instance, processed pseudogenes were once RNA transcripts that have been genomically integrated. In addition, telomerase uses an RNA template to add telomeric repeats to the ends of chromosomes. ORF, open reading frame; Pol II, RNA polymerase II.   lncRNAs as regulators of transcription   Figure 2 | lncRNAs regulate transcription through several mechanisms. ac | Long non-coding RNAs (lncRNAs) can modulate chromatin through transcription-independent (part a) and transcription-dependent mechanisms (parts b and c). lncRNAs can bind one or more chromatin-modifying complexes and target their activities to specific DNA loci (part a). Depending on the nature of the enzymes bound, lncRNA-mediated chromatin modifications can activate or repress gene expression22,23,26,27,120. Chromatin-modifying complexes bound to the RNA polymerase II (Pol II) carboxy-terminal domain (CTD) can modify chromatin during transcription of lncRNAs33–35 (part b). Transcription of lncRNAs can also result in chromatin remodelling that can either favour or inhibit the binding of regulatory factors (part c). Depending on the nature of the factors that bind during remodelling, gene expression is activated or repressed 37–40. dg | lncRNAs can modulate both the general transcription machinery (parts d and e) as well as specific regulatory factors (parts f and g). lncRNAs can bind Pol II directly to inhibit transcription47 (part d). Formation of lncRNA–DNA triplex structures can also inhibit the assembly of the pre-initiation complex48 (part e). lncRNAs can fold into structures that mimic DNA-binding sites (left) or that generally inhibit or enhance the activity of specific transcription factors (right)50–53 (part f). lncRNAs can also regulate gene expression by binding specific transport factors to inhibit the nuclear localization of specific transcription factors54 (part g). Regulators of mRNA processing Modulators of post-transcriptional control   Figure 3 | lncRNAs influence mRNA processing and post-transcriptional regulation. a,b | Long non-coding RNAs (lncRNAs) can modulate mRNA processing. Splicing patterns can be influenced by lncRNAs that associate with the pre-mRNA (part a). For example, splicing of the first intron of neuroblastoma MYC mRNA is prevented by a natural antisense transcript61. Antisense lncRNAs that associate with an mRNA could direct mRNA editing, perhaps through association of the duplex with ADAR (adenosine deaminase acting on RNA) enzymes that catalyse adenosine to inosine conversion in double-stranded RNA63,66 (part b). cf | lncRNAs modulate post-transcriptional regulatory events. lncRNAs containing SINEB2 repeat elements can upregulate translation through association with the 5ʹ region of an mRNA68 (part c). lncRNAs containing Alu repeat elements associate with the Alu elements in the 3ʹ untranslated region (UTR) of an mRNA, and this double-stranded structure can direct Staufen-mediated decay through a pathway that is molecularly similar to nonsense-mediated decay70 (part d). lncRNAs can mask miRNA-binding sites on a target mRNA to block miRNA-induced silencing through the RNA-induced silencing complex (RISC)72 (part e). Linear or circular lncRNAs can function as miRNA decoys to sequester miRNAs from their target mRNAs74,75 (part f).                   Regulators of protein activity                 Scaffolds for higher-order complexes                 Signaling molecules   Figure 4 | lncRNAs are involved in various cellular contexts. Long non-coding RNAs (lncRNAs) modulate protein activity by post-translational mechanisms (parts ac). a | Small nucleolar lncRNAs (sno-lncRNAs) generated from the 15q11‑q13 locus bind and modulate the activity of the FOX2 alternative splicing factor, and this can inhibit FOX2‑mediated splicing80. b | The highly structured rncs‑1 lncRNA binds Dicer to inhibit the processing of small RNAs81. c | The gadd7 lncRNA binds and modulates the ability of TDP43 (TAR DNA-binding protein 43) to target and process specific mRNAs84. d | lncRNAs can act as scaffolds to organize several complexes24. e | As the cargo of exosomes that mediate transfer of material between cells, exosomal shuttle RNAs (exRNAs) may act as signalling molecules during cell–cell communication; exosomal cargo includes mRNAs, microRNAs (miRNAs) and lncRNAs102. f | lncRNAs expressed from the switch region of genes encoding antibodies form R‑loops to direct class switch recombination via activation-induced deaminase (AID) recruitment111                   Vehicles for increasing genetic diversity                 Conclusions and perspectives                 lncRNAs have now been demonstrated to regulate all aspects of gene expression, including transcription (FIG. 2), processing and post-transcriptional control path­ways (FIG. 3). Likewise, lncRNAs have also been shown to regulate protein function and organize multiprotein com­plex assembly. Now with hints that lncRNAs might par­ticipate in cell–cell communication and recombination, the possible reach of lncRNA functions seems endless (FIG. 4).   Targeting Noncoding RNAs in Disease: Challenges and Opportunities Science/AAAS technology webinar   4 Sept 2013  

  • Noncoding RNAs serve a wide range of functions in cellular and developmental processes and are therefore likely involved in the development and pathophysiology of many diseases.

Thanks to the effective inhibition of micro RNAs in vivo, scientists have already made groundbreaking discoveries about the contribution of short regulating RNAs in human diseases in areas such as cancer, heart disease, and diabetes. Dr. David Corey from the Department of Pharmacology at the University of Texas Southwestern Medical Campus in Dallas, Texas; Dr. Stefanie Dimmeler from the Institute of Cardiovascular Regeneration at Goethe‐University in Frankfurt, Germany; Dr. Jan‐Wilhelm Kornfeld from the Department of Mouse Genetics and Metabolism, University of Cologne in Germany.   Dr. Corey’s group is interested in antigene oligonucleotides, antisense oligonucleotides, nucleic acids, RNAi, and telomerase.   I have two goals for my presentation today.

  • give a brief introduction to the concept of using nucleic acids as dugs.
  • show the boundaries of using nucleic acids to affect gene expression


  • a search for new methods to develop drugs includes nucleic acids that can bind to RNA and affect gene expression. The advantages of this approach are that one can identify an active oligomer, a lead compound very quickly in weeks rather than years.
  • the medicinal chemistry and pharmacology of all of these nucleic acids is similar
  • by affecting gene expression, one has the ability to treat almost any disease

the two main strategies for using nucleic acid to affect gene expression are

  • use single cell stranded oligonucleotides to bind directly to an RNA target and block their action.
  • use double stranded RNA. Double stranded RNA then goes through the RNA silencing process. That machinery
  • helps it to find a messenger RNA target and efficiently inhibit gene expression.

What kind of cellular RNAs can be targeted by nucleic acids?

  • they could be the RNA domains of ribonucleoproteins and the classic example of that is telomerase.
  • One could also target messenger RNA.
  • You could block translation or you could affect splicing so for example upregulate an isoform that might be useful in treating a disease.
  • Today, we focus mainly on targetingnoncodingRNAs and one of thosenoncodingRNAs ismicroRNAs and by
    • blocking the microRNA you can affect its action.

I’m going to discuss targeting long noncoding RNAs, which can be used to either up or down regulate gene transcription. Earlier this year Kynamro, an antisense oligonucleotide that targets Ap‐B1 messenger RNA, was approved by the food and drug administration. This is a systemically administered oligonucleotide that’s been shown to reduce LDL cholesterol. So it’s the strongest proof to date that synthetic oligonucleotides can be made on the scale that’s large enough to be used as drugs and be administered to patients and get through the FDA approval process.

  • Now I’d like to show you just how the boundaries of regulation can be pushed by using noncoding RNAs to regulate transcription of an operon within the icosanoid signaling pathway. Messenger RNAs are often overlapped by long RNAs at both their 3’ and the 5’ termini as well as within the gene providing a new realm of potential targets for addressing gene expression.


  • examples of the important ones include XIST and HOTAIR
  • These are genes that are known to regulate x chromosome inactivation or transcriptional multigene regulation programs. one might think that with RNA that RNAi factors that are so successful in regulating messenger RNA might be involved. But today they haven’t really been strongly implicated in mammalian cells.


  •  we know that microRNAs are in the nucleus.
  • we also know that RNAi factors like argonaute 2 are in the nucleus.
  • we also know that noncoding RNAs are in the nucleus.

The hypothesis that we’ve built up over that time is that these RNAi factors can interact with small RNAs

  • to form what are essentially ribonucleoprotein complexes that can act to control either gene transcription or gene splicing.
  • The RNA domain protects the RNA and promotes binding to the target. The RNA domain directs specificity to a particular RNA target inside the cell, for example a long noncoding RNA.

in about 2010 working with my colleague Bethany Janowski, we decided to go very deeply into an important physiology pathway — the eicosanoid production pathway and cyclooxygenase‐2 and PLA2G4a

  • we began by asking whether or not there was noncoding expression at the COX‐2 promoter
  • we characterized this expression by RNA sequencing by quantitative PCI and 5’ RACE and
  • we discovered that there were transcripts overlapping the COX-promoter in both the antisense and the sense direction –
  • we now have the noncoding RNA raw material that might allow recognition to control gene expression of COX‐2 messenger RNA.


  • there were a substantial number of microRNAs with complementarity to the COX‐2 promoter.
  • small RNA sequencing to identify microRNAs in the nucleus and
  • microRNAs that were both in the nucleus and complementary to the

COX‐2 promoter became candidates for regulating COX‐2.

  • The most promising of these microRNAs was microRNA‐
  • It had strong complementarity to two adjacent sequences within the COX‐2

promoter. So that resembles how micro‐RNAs recognize typically 3’ untranslated regions.

  • it became our prime candidate for investigating for potential regulation of COX‐2 expression through regulating its transcription by binding a noncoding RNA.
  •  we used a microRNA inhibitor
  • When we add these inhibitors into cells COX‐2 expression goes down.
  • consistent with a microRNA binding to the noncoding RNA and activating COX‐2 expression

This is as far as this reviewer wishes to prodeed in the presentation(s)   Explore microRNA as therapeutic targets Efficient [in vivo] silencing using LNA™-enhanced inhibitors   Nature Reprint Collection MicroRNAs from bench to clinic   Progress in the microRNA fi eld over the last 12 years has been nothing but remarkable. MicroRNAs were only discovered in humans in 2001, but since then they have revolutionized cell biology and completely changed the way we view the regulation of gene expression. They are now known to be involved, at some level, in all cellular and developmental pathways and all major types of disease, including all cancers, as well as metabolic, cardiovascular, neuronal and immune-related disorders. Exiqon’s LNA™- based microRNA research tools have been instrumental in many of the groundbreaking discoveries in the field. In this collection, we are thrilled to present some of the recent advances in moving microRNAs from basic research into the clinic both as biomarkers and therapeutic targets. Since the discovery of circulating or extracellular microRNAs, their potential as minimally invasive diagnostic and prognostic markers for disease has been actively investigated. Here we feature two articles where qPCR profiling of microRNAs in biofluids have been shown to have diagnostic potential. Another promising area with clinical prospects is microRNA in situ hybridization (ISH) in FFPE samples. We have included an article detailing the prognostic potential of microRNA ISH in this collection. Due to their extensive involvement in human disease, microRNAs are naturally interesting targets for therapeutic intervention. One of the most advanced areas in this respect is the potential of microRNAs as therapeutic targets in cardiovascular disease and we have included a review of this area. In addition, two very recent and groundbreaking studies that have shown the exciting potential for microRNA inhibition in diabetes and epilepsy are also included.   Identification of serum microRNA profiles in colon cancer E Hofsli*,1,2,7, W Sjursen3,4,7, W S Prestvik5, J Johansen2, M Rye2, G Tranø6, et al. 1Department of Oncology, St Olavs Hospital, Trondheim University Hospital, 2Faculty of Medicine, Department of Cancer and Molecular Medicine, Norwegian University of Science and Technology,  3Department of Laboratory Medicine Children’s and Women’s Health, Norwegian University of Science and Technology, 4Department of Pathology and Medical Genetics, St Olavs Hospital, Trondheim University Hospital, 5 Faculty of Technology, Sør-Trøndelag University College, and 6Department of Gastrointestinal Surgery, St Olavs Hospital, Trondheim University Hospital, Olav Kyrresgt 17, Trondheim 7006, Norway British Journal of Cancer (2013) 108, 1712–1719 | Background: microRNAs (miRNAs) exist in blood in an apparently stable form. We have explored whether serum miRNAs can be used as non-invasive early biomarkers of colon cancer. Methods: Serum samples from 30 patients with colon cancer stage IV and 10 healthy controls were examined for the expression of 375 cancer-relevant miRNAs. Based on the miRNA profile in this study, 34 selected miRNAs were measured in serum from 40 patients with stage I–II colon cancer and from 10 additional controls. Results: Twenty miRNAs were differentially expressed in serum from stage IV patients compared with controls (Po0.01). Unsupervised clustering revealed four subgroups; one corresponding mostly to the control group and the three others to the patient groups. Of the 34 miRNAs measured in the follow-up study of stage I–II patients, 21 showed concordant expression between stage IV and stage I–II patient. Based on the profiles of these 21 miRNAs, a supervised linear regression analysis (Partial Least Squares Regression) was performed. Using this model we correctly assigned stage I–II colon cancer patients based on miRNA profiles of stage IV patients. Conclusion: Serum miRNA expression profiling may be utilised in early detection of colon cancer. MicroRNAs from bench to clinic   Figure 2. Differentially expressed miRNAs in stage IV (red bars) vs stage I–II (blue bars) colon cancer. The expression of 34 miRNAs was compared, and 26 miRNAs were detected. In all, 21 of 26 detected miRNAs showed the same expression profile in early-stage I–II vs metastatic stage IV colon cancer.     Figure 3. Prediction analysis of early-stage colon cancer patients. Controls are shown in red and cancer samples in blue. 9 out of 10 healthy controls were correctly predicted as true negatives and 35 out of 40 patients with cancer as true positives.     MicroRNA profiling of diagnostic needle aspirates from patients with pancreatic cancer S Ali1, H Saleh2,3, S Sethi2, FH Sarkar1,2 and PA Philip*,1 1Department of Oncology; 2Department of Pathology; 3Karmanos Cancer Institute, Detroit Medical Center, Wayne State University School of Medicine, Detroit, MI   BACKGROUND: A major challenge to the development of biomarkers for pancreatic cancer (PC) is the small amount of tissue obtained at the time of diagnosis. Single-gene analyses may not reliably predict biology of PC because of its complex molecular makeup.MicroRNA (miRNA) profiling may provide a more informative molecular interrogation of tumours. The primary objective of this study was to determine the feasibility of performing miRNA arrays and quantitative real-time PCR (qRT– PCR) from archival formalin fixed paraffin-embedded (FFPE) cell blocks obtained from fine-needle aspirates (FNAs) that is the commonest diagnostic procedure for suspected PC. METHODS: MicroRNA expression profiling was performed on FFPE from FNA of suspicious pancreatic masses. Subjects included those who had a pathological diagnosis of pancreatic adenocarcinoma and others with a non-malignant pancreatic histology. Exiqon assay was used to quantify miRNA levels and qRT–PCR was used to validate abnormal expression of selected miRNAs. RESULTS: A total of 29 and 15 subjects had pancreatic adenocarcinoma and no evidence of cancer, respectively. The RNA yields per patient varied from 25 to 100 ng. Profiling demonstrated deregulation of over 228 miRNAs in pancreatic adenocarcinoma of which the top 7 were further validated by qRT–PCR. The expression of let-7c, let-7 f, and miR-200c were significantly reduced in most patients whereas the expression of miR-486-5p and miR-451 were significantly elevated in all pancreas cancer patients. MicroRNAs let-7d and miR-423-5p was either downregulated or upregulated with a significant inter-individual variation in their expression. CONCLUSION: This study demonstrated the feasibility of using archival FFPE cell blocks from FNAs to establish RNA-based molecular signatures unique to pancreatic adenocarcinoma with potential applications in clinical trials for risk stratification, patient selection, and target validation. British Journal of Cancer (2012) 107, 1354–1360.  http://dx.doi,org:/10.1038/bjc.2012.383 Comparative expression of seven miRNAs tested in FNA samples   Figure 1 Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs analysed by miRNA profiling in PC and their targeted genes.

miRNAs analysed by miRNA profiling in PC and their targeted genes

miRNAs analysed by miRNA profiling in PC and their targeted genes

Figure 2 Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes (A). The solid lines connecting genes represent a direct relation and dotted lines indirect relation. We also observed 15 bio functional network groups that included cancer, genetic disorder, and gastrointestinal disease (B).

Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes

Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes

Figure 6 Box plot representing the expression of 7 miRNAs as assessed by qRT–PCR in 29 FNA cell blocks from PC patients analysed individually compared with FNA cell blocks obtained from 15 normal controls by using qRT–PCR. The graph is presented in log2 values and 1.0 represents average of normal subjects (n¼15). [not shown]   The prognostic importance of miR-21 in stage II colon cancer:a population-based study S Kjaer-Frifeldt*,1,2, TF Hansen1, BS Nielsen3, S Joergensen3, J Lindebjerg4, …on behalf of Danish Colorectal Cancer Group 1Department of Oncology, Danish Colorectal Cancer Group South, Vejle Hospital; 2University of Southern Denmark, Odense, Denmark; 3Diagnostic Product Development, Exiqon A/S, Vedbæk 2950, Denmark; 4Department of Clinical Pathology, Vejle Hospital, Vejle, Denmark British Journal of Cancer (2012) 107, 1169–1174   BACKGROUND: Despite several years of research and attempts to develop prognostic models a considerable fraction of stage II colon cancer patients will experience relapse within few years from their operation. The aim of the present study was to investigate the prognostic importance of miRNA-21 (miR-21), quantified by in situ hybridisation, in a unique, large population-based cohort. PATIENTS AND METHODS: The study included 764 patients diagnosed with stage II colon cancer in Denmark in the year 2003. One section from a representative paraffin-embedded tumour tissue specimen from each patient was processed for analysis of miR-21 and quantitatively assessed by image analysis. RESULTS: The miR-21 signal was predominantly observed in fibroblast-like cells located in the stromal compartment of the tumours. We found that patients expressing high levels of miR-21 had significantly inferior recurrence-free cancer-specific survival (RF-CSS): HR¼1.26; 95% CI: 1.15–1.60; Po0.001. In Cox regression analysis, a high level of miR-21 retained its prognostic importance and was found to be significantly related to poor RF-CSS: HR¼1.41; 95% CI: 1.19–1.67; Po0.001. CONCLUSION: The present study showed that increasing miR-21 expression levels were significantly correlated to decreasing RF-CSS. Further investigations of the clinical importance of miR-21 in the selection of high-risk stage II colon cancer patients are merited. British Journal of Cancer (2012) 107, 1169–1174.


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