Posts Tagged ‘DNA methylation’

Genomics and epigenetics link to DNA structure

Posted in Behavioral Genetics, Biological Networks, Gene Regulation and Evolution, Cancer Informatics, Cell Biology, Signaling & Cell Circuits, Cerebrovascular and Neurodegenerative Diseases, Chemical Genetics, Clinical & Translational, Clinical Genomics, Cognition, Computational Biology/Systems and Bioinformatics, Curation, Developmental biology, Disease Biology, DNA repair, Embryology, Enzyme Induction, Epigenetics and Cardiovascular Risks, Epigenetics and Environmental Factors, Exosomes, Gene Regulation and Evolution, Genome Biology, Genomic Endocrinology, Genomic Expression, Human aging, Mutagenesis, tagged AT-rich DNA duplex, DNA methylation, double stranded DNA, epigenetic modifications, Epigenetics, fluorescence resonance energy transfer, interhelical region, nanoscale, Nucleic acid sequence, sequence-dependent attraction, spermine on April 11, 2016| Leave a Comment »

Genomics and epigenetics link to DNA structure

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Sequence and Epigenetic Factors Determine Overall DNA Structure

http://www.genengnews.com/gen-news-highlights/sequence-and-epigenetic-factors-determine-overall-dna-structure/81252592/

http://www.genengnews.com/Media/images/GENHighlight/Atomiclevelsimulationsshowingelectrostaticforcesbetweeneachatom1259202113.jpg

Atomic-level simulations show electrostatic forces between each atom. [Alek Aksimentiev, University of Illinois at Urbana-Champaign]

 

The traditionally held hypothesis about the highly ordered organization of DNA describes the interaction of various proteins with DNA sequences to mediate the dynamic structure of the molecule. However, recent evidence has emerged that stretches of homologous DNA sequences can associate preferentially with one another, even in the absence of proteins.

Researchers at the University of Illinois Center for the Physics of Living Cells, Johns Hopkins University, and Ulsan National Institute of Science and Technology (UNIST) in South Korea found that DNA molecules interact directly with one another in ways that are dependent on the sequence of the DNA and epigenetic factors, such as methylation.

The researchers described evidence they found for sequence-dependent attractive interactions between double-stranded DNA molecules that neither involve intermolecular strand exchange nor are mediated by DNA-binding proteins.

“DNA molecules tend to repel each other in water, but in the presence of special types of cations, they can attract each other just like nuclei pulling each other by sharing electrons in between,” explained lead study author Hajin Kim, Ph.D., assistant professor of biophysics at UNIST. “Our study suggests that the attractive force strongly depends on the nucleic acid sequence and also the epigenetic modifications.”

The investigators used atomic-level supercomputer simulations to measure the forces between a pair of double-stranded DNA helices and proposed that the distribution of methyl groups on the DNA was the key to regulating this sequence-dependent attraction. To verify their findings experimentally, the scientists were able to observe a single pair of DNA molecules within nanoscale bubbles.

“Here we combine molecular dynamics simulations with single-molecule fluorescence resonance energy transfer experiments to examine the interactions between duplex DNA in the presence of spermine, a biological polycation,” the authors wrote. “We find that AT-rich DNA duplexes associate more strongly than GC-rich duplexes, regardless of the sequence homology. Methyl groups of thymine act as a steric block, relocating spermine from major grooves to interhelical regions, thereby increasing DNA–DNA attraction.”

The findings from this study were published recently in Nature Communications in an article entitled “Direct Evidence for Sequence-Dependent Attraction Between Double-Stranded DNA Controlled by Methylation.”

After conducting numerous further simulations, the research team concluded that direct DNA–DNA interactions could play a central role in how chromosomes are organized in the cell and which ones are expanded or folded up compactly, ultimately determining functions of different cell types or regulating the cell cycle.

“Biophysics is a fascinating subject that explores the fundamental principles behind a variety of biological processes and life phenomena,” Dr. Kim noted. “Our study requires cross-disciplinary efforts from physicists, biologists, chemists, and engineering scientists and we pursue the diversity of scientific disciplines within the group.”

Dr. Kim concluded by stating that “in our lab, we try to unravel the mysteries within human cells based on the principles of physics and the mechanisms of biology. In the long run, we are seeking for ways to prevent chronic illnesses and diseases associated with aging.”

 

Direct evidence for sequence-dependent attraction between double-stranded DNA controlled by methylation

Jejoong Yoo, Hajin Kim, Aleksei Aksimentiev, and Taekjip Ha
Nature Communications 7 11045 (2016)    DOI:10.1038/ncomms11045BibTex

http://bionano.physics.illinois.edu/sites/default/files/styles/large/public/telepathy_figures_0.png?itok=VUJIHX2_

Although proteins mediate highly ordered DNA organization in vivo, theoretical studies suggest that homologous DNA duplexes can preferentially associate with one another even in the absence of proteins. Here we combine molecular dynamics simulations with single-molecule fluorescence resonance energy transfer experiments to examine the interactions between duplex DNA in the presence of spermine, a biological polycation. We find that AT-rich DNA duplexes associate more strongly than GC-rich duplexes, regardless of the sequence homology. Methyl groups of thymine acts as a steric block, relocating spermine from major grooves to interhelical regions, thereby increasing DNA–DNA attraction. Indeed, methylation of cytosines makes attraction between GC-rich DNA as strong as that between AT-rich DNA. Recent genome-wide chromosome organization studies showed that remote contact frequencies are higher for AT-rich and methylated DNA, suggesting that direct DNA–DNA interactions that we report here may play a role in the chromosome organization and gene regulation.

Formation of a DNA double helix occurs through Watson–Crick pairing mediated by the complementary hydrogen bond patterns of the two DNA strands and base stacking. Interactions between double-stranded (ds)DNA molecules in typical experimental conditions containing mono- and divalent cations are repulsive¹, but can turn attractive in the presence of high-valence cations². Theoretical studies have identified the ion–ion correlation effect as a possible microscopic mechanism of the DNA condensation phenomena^{3, 4, 5}. Theoretical investigations have also suggested that sequence-specific attractive forces might exist between two homologous fragments of dsDNA⁶, and this ‘homology recognition’ hypothesis was supported by in vitro atomic force microscopy⁷ and in vivo point mutation assays⁸. However, the systems used in these measurements were too complex to rule out other possible causes such as Watson–Crick strand exchange between partially melted DNA or protein-mediated association of DNA.

Here we present direct evidence for sequence-dependent attractive interactions between dsDNA molecules that neither involve intermolecular strand exchange nor are mediated by proteins. Further, we find that the sequence-dependent attraction is controlled not by homology—contradictory to the ‘homology recognition’ hypothesis⁶—but by a methylation pattern. Unlike the previous in vitro study that used monovalent (Na⁺) or divalent (Mg²⁺) cations⁷, we presumed that for the sequence-dependent attractive interactions to operate polyamines would have to be present. Polyamine is a biological polycation present at a millimolar concentration in most eukaryotic cells and essential for cell growth and proliferation^{9, 10}. Polyamines are also known to condense DNA in a concentration-dependent manner^{2, 11}. In this study, we use spermine⁴⁺(Sm⁴⁺) that contains four positively charged amine groups per molecule.

Sequence dependence of DNA–DNA forces

To characterize the molecular mechanisms of DNA–DNA attraction mediated by polyamines, we performed molecular dynamics (MD) simulations where two effectively infinite parallel dsDNA molecules, 20 base pairs (bp) each in a periodic unit cell, were restrained to maintain a prescribed inter-DNA distance; the DNA molecules were free to rotate about their axes. The two DNA molecules were submerged in 100 mM aqueous solution of NaCl that also contained 20 Sm⁴⁺molecules; thus, the total charge of Sm⁴⁺, 80 e, was equal in magnitude to the total charge of DNA (2 × 2 × 20 e, two unit charges per base pair; Fig. 1a). Repeating such simulations at various inter-DNA distances and applying weighted histogram analysis¹² yielded the change in the interaction free energy (ΔG) as a function of the DNA–DNA distance (Fig. 1b,c). In a broad agreement with previous experimental findings¹³, ΔG had a minimum, ΔG_min, at the inter-DNA distance of 25−30 Å for all sequences examined, indeed showing that two duplex DNA molecules can attract each other. The free energy of inter-duplex attraction was at least an order of magnitude smaller than the Watson–Crick interaction free energy of the same length DNA duplex. A minimum of ΔG was not observed in the absence of polyamines, for example, when divalent or monovalent ions were used instead^{14, 15}.

(a) Set-up of MD simulations. A pair of parallel 20-bp dsDNA duplexes is surrounded by aqueous solution (semi-transparent surface) containing 20 Sm⁴⁺ molecules (which compensates exactly the charge of DNA) and 100 mM NaCl. Under periodic boundary conditions, the DNA molecules are effectively infinite. A harmonic potential (not shown) is applied to maintain the prescribed distance between the dsDNA molecules. (b,c) Interaction free energy of the two DNA helices as a function of the DNA–DNA distance for repeat-sequence DNA fragments (b) and DNA homopolymers (c). (d) Schematic of experimental design. A pair of 120-bp dsDNA labelled with a Cy3/Cy5 FRET pair was encapsulated in a ~200-nm diameter lipid vesicle; the vesicles were immobilized on a quartz slide through biotin–neutravidin binding. Sm⁴⁺ molecules added after immobilization penetrated into the porous vesicles. The fluorescence signals were measured using a total internal reflection microscope. (e) Typical fluorescence signals indicative of DNA–DNA binding. Brief jumps in the FRET signal indicate binding events. (f) The fraction of traces exhibiting binding events at different Sm⁴⁺ concentrations for AT-rich, GC-rich, AT nonhomologous and CpG-methylated DNA pairs. The sequence of the CpG-methylated DNA specifies the methylation sites (CG sequence, orange), restriction sites (BstUI, triangle) and primer region (underlined). The degree of attractive interaction for the AT nonhomologous and CpG-methylated DNA pairs was similar to that of the AT-rich pair. All measurements were done at [NaCl]=50 mM and T=25 °C. (g) Design of the hybrid DNA constructs: 40-bp AT-rich and 40-bp GC-rich regions were flanked by 20-bp common primers. The two labelling configurations permit distinguishing parallel from anti-parallel orientation of the DNA. (h) The fraction of traces exhibiting binding events as a function of NaCl concentration at fixed concentration of Sm⁴⁺ (1 mM). The fraction is significantly higher for parallel orientation of the DNA fragments.

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Unexpectedly, we found that DNA sequence has a profound impact on the strength of attractive interaction. The absolute value of ΔG at minimum relative to the value at maximum separation, |ΔG_min|, showed a clearly rank-ordered dependence on the DNA sequence: |ΔG_min| of (A)₂₀>|ΔG_min| of (AT)₁₀>|ΔG_min| of (GC)₁₀>|ΔG_min| of (G)₂₀. Two trends can be noted. First, AT-rich sequences attract each other more strongly than GC-rich sequences¹⁶. For example, |ΔG_min| of (AT)₁₀ (1.5 kcal mol⁻¹ per turn) is about twice |ΔG_min| of (GC)₁₀ (0.8 kcal mol⁻¹ per turn) (Fig. 1b). Second, duplexes having identical AT content but different partitioning of the nucleotides between the strands (that is, (A)₂₀ versus (AT)₁₀ or (G)₂₀ versus (GC)₁₀) exhibit statistically significant differences (~0.3 kcal mol⁻¹ per turn) in the value of |ΔG_min|.

To validate the findings of MD simulations, we performed single-molecule fluorescence resonance energy transfer (smFRET)¹⁷ experiments of vesicle-encapsulated DNA molecules. Equimolar mixture of donor- and acceptor-labelled 120-bp dsDNA molecules was encapsulated in sub-micron size, porous lipid vesicles¹⁸ so that we could observe and quantitate rare binding events between a pair of dsDNA molecules without triggering large-scale DNA condensation². Our DNA constructs were long enough to ensure dsDNA–dsDNA binding that is stable on the timescale of an smFRET measurement, but shorter than the DNA’s persistence length (~150 bp (ref. 19)) to avoid intramolecular condensation²⁰. The vesicles were immobilized on a polymer-passivated surface, and fluorescence signals from individual vesicles containing one donor and one acceptor were selectively analysed (Fig. 1d). Binding of two dsDNA molecules brings their fluorescent labels in close proximity, increasing the FRET efficiency (Fig. 1e).

FRET signals from individual vesicles were diverse. Sporadic binding events were observed in some vesicles, while others exhibited stable binding; traces indicative of frequent conformational transitions were also observed (Supplementary Fig. 1A). Such diverse behaviours could be expected from non-specific interactions of two large biomolecules having structural degrees of freedom. No binding events were observed in the absence of Sm⁴⁺ (Supplementary Fig. 1B) or when no DNA molecules were present. To quantitatively assess the propensity of forming a bound state, we chose to use the fraction of single-molecule traces that showed any binding events within the observation time of 2 min (Methods). This binding fraction for the pair of AT-rich dsDNAs (AT1, 100% AT in the middle 80-bp section of the 120-bp construct) reached a maximum at ~2 mM Sm⁴⁺(Fig. 1f), which is consistent with the results of previous experimental studies^{2, 3}. In accordance with the prediction of our MD simulations, GC-rich dsDNAs (GC1, 75% GC in the middle 80 bp) showed much lower binding fraction at all Sm⁴⁺ concentrations (Fig. 1b,c). Regardless of the DNA sequence, the binding fraction reduced back to zero at high Sm⁴⁺ concentrations, likely due to the resolubilization of now positively charged DNA–Sm⁴⁺ complexes^{2, 3, 13}.

Because the donor and acceptor fluorophores were attached to the same sequence of DNA, it remained possible that the sequence homology between the donor-labelled DNA and the acceptor-labelled DNA was necessary for their interaction⁶. To test this possibility, we designed another AT-rich DNA construct AT2 by scrambling the central 80-bp section of AT1 to remove the sequence homology (Supplementary Table 1). The fraction of binding traces for this nonhomologous pair of donor-labelled AT1 and acceptor-labelled AT2 was comparable to that for the homologous AT-rich pair (donor-labelled AT1 and acceptor-labelled AT1) at all Sm⁴⁺ concentrations tested (Fig. 1f). Furthermore, this data set rules out the possibility that the higher binding fraction observed experimentally for the AT-rich constructs was caused by inter-duplex Watson–Crick base pairing of the partially melted constructs.

Next, we designed a DNA construct named ATGC, containing, in its middle section, a 40-bp AT-rich segment followed by a 40-bp GC-rich segment (Fig. 1g). By attaching the acceptor to the end of either the AT-rich or GC-rich segments, we could compare the likelihood of observing the parallel binding mode that brings the two AT-rich segments together and the anti-parallel binding mode. Measurements at 1 mM Sm⁴⁺ and 25 or 50 mM NaCl indicated a preference for the parallel binding mode by ~30% (Fig. 1h). Therefore, AT content can modulate DNA–DNA interactions even in a complex sequence context. Note that increasing the concentration of NaCl while keeping the concentration of Sm⁴⁺ constant enhances competition between Na⁺ and Sm⁴⁺ counterions, which reduces the concentration of Sm⁴⁺ near DNA and hence the frequency of dsDNA–dsDNA binding events (Supplementary Fig. 2).

Methylation determines the strength of DNA–DNA attraction

Analysis of the MD simulations revealed the molecular mechanism of the polyamine-mediated sequence-dependent attraction (Fig. 2). In the case of the AT-rich fragments, the bulky methyl group of thymine base blocks Sm⁴⁺ binding to the N7 nitrogen atom of adenine, which is the cation-binding hotspot^{21, 22}. As a result, Sm⁴⁺ is not found in the major grooves of the AT-rich duplexes and resides mostly near the DNA backbone (Fig. 2a,d). Such relocated Sm⁴⁺ molecules bridge the two DNA duplexes better, accounting for the stronger attraction^{16, 23, 24, 25}. In contrast, significant amount of Sm⁴⁺ is adsorbed to the major groove of the GC-rich helices that lacks cation-blocking methyl group (Fig. 2b,e).

(a–c) Representative configurations of Sm⁴⁺ molecules at the DNA–DNA distance of 28 Å for the (AT)₁₀–(AT)₁₀ (a), (GC)₁₀–(GC)₁₀ (b) and (GmC)₁₀–(GmC)₁₀ (c) DNA pairs. The backbone and bases of DNA are shown as ribbon and molecular bond, respectively; Sm⁴⁺ molecules are shown as molecular bonds. Spheres indicate the location of the N7 atoms and the methyl groups. (d–f) The average distributions of cations for the three sequence pairs featured in a–c. Top: density of Sm⁴⁺ nitrogen atoms (d=28 Å) averaged over the corresponding MD trajectory and the z axis. White circles (20 Å in diameter) indicate the location of the DNA helices. Bottom: the average density of Sm⁴⁺ nitrogen (blue), DNA phosphate (black) and sodium (red) atoms projected onto the DNA–DNA distance axis (x axis). The plot was obtained by averaging the corresponding heat map data over y=[−10, 10] Å. See Supplementary Figs 4 and 5 for the cation distributions at d=30, 32, 34 and 36 Å.

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If indeed the extra methyl group in thymine, which is not found in cytosine, is responsible for stronger DNA–DNA interactions, we can predict that cytosine methylation, which occurs naturally in many eukaryotic organisms and is an essential epigenetic regulation mechanism²⁶, would also increase the strength of DNA–DNA attraction. MD simulations showed that the GC-rich helices containing methylated cytosines (mC) lose the adsorbed Sm⁴⁺ (Fig. 2c,f) and that |ΔG_min| of (GC)₁₀ increases on methylation of cytosines to become similar to |ΔG_min| of (AT)₁₀ (Fig. 1b).

To experimentally assess the effect of cytosine methylation, we designed another GC-rich construct GC2 that had the same GC content as GC1 but a higher density of CpG sites (Supplementary Table 1). The CpG sites were then fully methylated using M. SssI methyltransferase (Supplementary Fig. 3; Methods). As predicted from the MD simulations, methylation of the GC-rich constructs increased the binding fraction to the level of the AT-rich constructs (Fig. 1f).

The sequence dependence of |ΔG_min| and its relation to the Sm⁴⁺ adsorption patterns can be rationalized by examining the number of Sm⁴⁺ molecules shared by the dsDNA molecules (Fig. 3a). An Sm⁴⁺ cation adsorbed to the major groove of one dsDNA is separated from the other dsDNA by at least 10 Å, contributing much less to the effective DNA–DNA attractive force than a cation positioned between the helices, that is, the ‘bridging’ Sm⁴⁺ (ref. 23). An adsorbed Sm⁴⁺ also repels other Sm⁴⁺ molecules due to like-charge repulsion, lowering the concentration of bridging Sm⁴⁺. To demonstrate that the concentration of bridging Sm⁴⁺ controls the strength of DNA–DNA attraction, we computed the number of bridging Sm⁴⁺ molecules, N_spm (Fig. 3b). Indeed, the number of bridging Sm⁴⁺ molecules ranks in the same order as |ΔG_min|: N_spm of (A)₂₀>N_spm of (AT)₁₀≈N_spm of (GmC)₁₀>N_spm of (GC)₁₀>N_spm of (G)₂₀. Thus, the number density of nucleotides carrying a methyl group (T and mC) is the primary determinant of the strength of attractive interaction between two dsDNA molecules. At the same time, the spatial arrangement of the methyl group carrying nucleotides can affect the interaction strength as well (Fig. 3c). The number of methyl groups and their distribution in the (AT)₁₀ and (GmC)₁₀ duplex DNA are identical, and so are their interaction free energies, |ΔG_min| of (AT)₁₀≈|ΔG_min| of (GmC)₁₀. For AT-rich DNA sequences, clustering of the methyl groups repels Sm⁴⁺ from the major groove more efficiently than when the same number of methyl groups is distributed along the DNA (Fig. 3b). Hence, |ΔG_min| of (A)₂₀>|ΔG_min| of (AT)₁₀. For GC-rich DNA sequences, clustering of the cation-binding sites (N7 nitrogen) attracts more Sm⁴⁺ than when such sites are distributed along the DNA (Fig. 3b), hence |ΔG_min| is larger for (GC)₁₀ than for (G)₂₀.

(a) Typical spatial arrangement of Sm⁴⁺ molecules around a pair of DNA helices. The phosphates groups of DNA and the amine groups of Sm⁴⁺ are shown as red and blue spheres, respectively. ‘Bridging’ Sm⁴⁺molecules reside between the DNA helices. Orange rectangles illustrate the volume used for counting the number of bridging Sm⁴⁺ molecules. (b) The number of bridging amine groups as a function of the inter-DNA distance. The total number of Sm⁴⁺ nitrogen atoms was computed by averaging over the corresponding MD trajectory and the 10 Å (x axis) by 20 Å (y axis) rectangle prism volume (a) centred between the DNA molecules. (c) Schematic representation of the dependence of the interaction free energy of two DNA molecules on their nucleotide sequence. The number and spatial arrangement of nucleotides carrying a methyl group (T or mC) determine the interaction free energy of two dsDNA molecules.

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Genome-wide investigations of chromosome conformations using the Hi–C technique revealed that AT-rich loci form tight clusters in human nucleus^{27, 28}. Gene or chromosome inactivation is often accompanied by increased methylation of DNA²⁹ and compaction of facultative heterochromatin regions³⁰. The consistency between those phenomena and our findings suggest the possibility that the polyamine-mediated sequence-dependent DNA–DNA interaction might play a role in chromosome folding and epigenetic regulation of gene expression.

1. Rau, D. C., Lee, B. & Parsegian, V. A. Measurement of the repulsive force between polyelectrolyte molecules in ionic solution: hydration forces between parallel DNA double helices. Proc. Natl Acad. Sci. USA 81, 2621–2625 (1984).
   • CAS
   • PubMed
   • Article
   • Show context
2. Raspaud, E., Olvera de la Cruz, M., Sikorav, J. L. & Livolant, F. Precipitation of DNA by polyamines: a polyelectrolyte behavior. Biophys. J. 74, 381–393 (1998).
   • CAS
   • ISI
   • PubMed
   • Article
   • Show context
3. Besteman, K., Van Eijk, K. & Lemay, S. G. Charge inversion accompanies DNA condensation by multivalent ions. Nat. Phys. 3, 641–644 (2007).
   • Article
   • Show context
4. Lipfert, J., Doniach, S., Das, R. & Herschlag, D. Understanding nucleic acid-ion interactions.Annu. Rev. Biochem. 83, 813–841 (2014).
   • CAS
   • PubMed
   • Article
   • Show context
5. Grosberg, A. Y., Nguyen, T. T. & Shklovskii, B. I. The physics of charge inversion in chemical and biological systems. Rev. Mod. Phys. 74, 329–345 (2002).
   • CAS
   • ISI
   • Article
   • Show context
6. Kornyshev, A. A. & Leikin, S. Sequence recognition in the pairing of DNA duplexes. Phys. Rev. Lett. 86, 3666–3669 (2001).
   • CAS
   • PubMed
   • Article
   • Show context
7. Danilowicz, C. et al. Single molecule detection of direct, homologous, DNA/DNA pairing.Proc. Natl Acad. Sci. USA 106, 19824–19829 (2009).
   • PubMed
   • Article
   • Show context
8. Gladyshev, E. & Kleckner, N. Direct recognition of homology between double helices of DNA in Neurospora crassa. Nat. Commun. 5, 3509 (2014).
   • Show context
9. Tabor, C. W. & Tabor, H. Polyamines. Annu. Rev. Biochem. 53, 749–790 (1984).
   • CAS
   • ISI
   • PubMed
   • Article
   • Show context
10. Thomas, T. & Thomas, T. J. Polyamines in cell growth and cell death: molecular mechanisms and therapeutic applications. Cell. Mol. Life Sci. 58, 244–258 (2001).
    • CAS
    • ISI
    • PubMed
    • Article
    • Show context

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The Magic of the Pandora’s Box : Epigenetics and Stemness with Long non-coding RNAs (lincRNA)

Posted in Advanced Drug Manufacturing Technology, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Biomedical Measurement Science, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmacogenomics, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Stem Cells for Regenerative Medicine, tagged Biochemistry and Molecular Biology, Biology, CpG island, DNA, DNA methylation, ENCODE, epigenetic, gene, gene expression, genetics, genome, Genomic imprinting, MicroRNA, Non-coding RNA, RNA, RYBP on June 30, 2013| 8 Comments »

Genome Jigsaws (Photo credit: dullhunk)

Word Cloud By Danielle Smolyar

Sequencing became the household name.  In 2000s, it was thought to be the key of the Pandora’s box for cure.  Then, after completion of Human Genome Projects showed that there are less number of genes than expected.  This outcome induce to originate yet another set of sequencing programs and collaborations around the world, such as Human Protein Project, Human Microorganisms Projects, ENCODE, Transcriptome Sequencing and Consortiums etc.

It is in humankind to believe in magic and illusion.  The strength of biological diversity and complex mechanism of expression may chalanges the set up of a simple but informative specific essay.  Thus, there is a new developing field to mash rules of biology with mathematical formulas to develop the best bioinformatics or also called computational biology.  Predicting transcription start or termination sites, exon boundaries, possible binding sites of transcription regulators for chromatin modification activities, like histone acetylates and enhancer- and insulator-associated factors based on the human genome sequence.  Deep in mind, this assumption supports that the sequence contains signatures for chromatin modifications essential for gene regulation and development.

There are three primary colors, red, yellow and blue, however, an artist can create many shades. Recently, scientists combining and organizing more data to make sense of our blueprint of life to transfer info generation to generation with the hope to cure diseases of human kind.

Analyzing genome and transcriptome open the door.  These studies suggested that all eukaryotic cells has a rich portfolio of RNAs. Among these long non-coding RNAs has impact on protein coding gene expression, regulating multiple processes even including epigenetic gene expression.

Epigenetics, stemness and non-coding RNAs  play a great role to manipulate and correct the gene expression not only at a proper cell type but also location and time within genome without disturbing the host.

Main concern is differentiation of embryonic stem cells under these epigenetics and influencers.  The best known post-transcriptional modifications, which include methylation, acetylation, ubiquination, and SUMOylation of lysine residues, methylation of arginine residues, and phosphorylation of serines, occur on histone tails. “Epi” means “top” or
“above” so this mechanism give a new direction to the genetic pathways as long as the organism live sometime and may lead into evolutions.  It is critical to show the complexity of
mechanism and relativity of a gene role with a single example for each. 

For example,  DNA methylation occurs mostly on cytosine residues on the CpG islands usually located on promoter regions that are associated with tissue-specific gene expression.  However, there are many other forms of DNA methylations, such as  monoallelic methylation in gene imprinting and inactivation of the X chromosome,  in repetitive elements, like transposons.  There are two main mechanisms but this is not our main topic.  Yet, Myc and hypoxia-inducible factor-1α versus certain methyl-CpG-binding proteins, such as MBD1,MBD2, MBD4, MeCP2, and Kaiso works differently.

Stemness is an important factor for an intervention to correct a pathological condition. In terms of epigenetics, regulation and non-coding RNA Vascular endothelial growth factor A (VEGF-A) is an interesting example for differentiation of endothelial cells and morphogenesis of the vascular system during development with several reasons, epigenetics, gene interactions, time and space.  Everything has to be just right, because neither less nor too much can fulfill the destiny to become a complete adult cell or an organism.   For example, both having only one VEGF-A allele and having two-fold excess of VEGF-A results in death during early embryogenesis, since mice can’t develop proper vascular network.  However, explaining diverse mechanisms and functions of VEGF-A is require more information with specific details.  VEGF-A plays many roles in many pathological cases, such as cancer, inflammation, retinopathies, and arthritis because VEGF-A has also function in epigenetic reprogramming of the promoter regions of Rex1 and Oct4 genes, that are critical for a stem cell. Preferred mechanism is anti-angiogeneic state but tumor cells prefer hypermethylation to induce pro-angiogeneic state, thus VEGF-A stimulates PIGF in tumour cells among many other factors.

Now, let’s turn around to observe development of a cell with Polycomb repressive complexes (PRCs) because they are important chromatin regulators of embryonic stem (ES) cell function.  Originally, RYBP shown to function  as transcriptional repressor in reporter assays from both in tissue culture cells and in fruit fly (Drosophila melanogaster ) and as a direct interactor with Ring1A during embryogenesis through methylation. In addition, RYBP in epigenetic resetting during preimplantation development through repression of germ line genes and PcG targets before formation of pluripotent epiblast cells.  However, I do believe that the most important element is efficient repression of endogenous retroviruses (murine endogenous retrovirus called MuERV class),  preimplantation containing zygotic genome activation stage and germ line specific genes. The selective repressor activity of  RYBP  is in the ES cell state. When RYBP^−/− ES cells were analyzed by measuring gene expression during differentiation as embryo bodies formed from mutant and wild-type cells, the result presented that  expression of pluripotency genes Oct4 and Nanog was usually downregulated. However, RYBP is able to bind genomic regions independently of H3K27me3 and there is no relation between altered RYBP binding in Dnmt1-mutant cells to DNA methylation status. In sum, RYBP has a large value in undifferentiated ES cells and may affect or even reset epigenetic landscape during early developmental stages. These are the gaps filled by long non coding RNAs.

We learn more compelling information by comparing and contrasting what is normal and what is abnormal. As a result, pathology is a key learning canvas for basic mechanisms in molecular genetics. Then peppered with functional genomics completes the story for an edible outcome.  We generally refer this as a Translational Research.  For example, recent foundlings suggest that H19 contributes to cancer, including hepatocellular carcinoma (HCC) after reviewing Oncomine resource.  According to these observations, in most HCC cases there is a lower expression of  H19 level is compared to the liver. Thus, in vitro and in vivo studies were undertaken with classical genetic analyzes based on loss- and gain-of-function on H19 to characterize two outcomes depend on H19, that are the effects on gene expression and on HCC metastasis. First, the expression of H19 showed gene expression variation since H19 expression was low in tumor cells than peripheral tumor cells.  Second, the metastasis of cancer based on alteration of miR-200 pathway contributing mesenchymal-to-epithelial transition by H19. Therefore, H19 and miR-200 are targets to be utilized during molecular diagnostics development and establishing targeted therapies in cancer.

Long story short, there is a circle of life where everything is connected even though they look different.  As a result, when we see a sunflower or a baby we remember to smile, because life is still an act to puzzle human.

References and Further Readings:

“Non-coding RNAs as regulators of gene expression and epigenetics” Cardiovascular Res 1 June 2011: 430-440.

“Epigenetic regulation of key vascular genes and growth factors” Cardiovasc Res 1 June 2011: 441-446.

“Epigenetic Regulation by Long Noncoding RNAs” Science 14 December 2012: 1435-1439.

“Epigenetic control of embryonic stem cell fate” JEM 25 October 2010: 2287-2295.

“Transcribed dark matter: meaning or myth?” Hum Mol Genet 15 October 2010: R162-R168.

“Epigenetic activation of the MiR-200 family contributes to H19-mediated metastasis suppression in hepatocellular carcinoma” Carcinogenesis 1 March 2013: 577-586.

“Vernalization-Mediated Epigenetic Silencing by a Long Intronic Noncoding RNA” Science 7 January 2011: 76-79.

“Predicting the probability of H3K4me3 occupation at a base pair from the genome sequence context” Bioinformatics 1 May 2013: 1199-1205.

Further Readings specific to Embryonic Stem Cell Differentiation and Development :

“BMP Induces Cochlin Expression to Facilitate Self-renewal and Suppress Neural Differentiation of Mouse Embryonic Stem Cells” J. Biol. Chem. 2013 288:8053-8060

Abstract

“Regulation of DNA Methylation in Rheumatoid Arthritis Synoviocytes”  J. Immunol. 2013 190:1297-1303

Abstract

“DNA methylome signature in rheumatoid arthritis” Ann Rheum Dis 2013 72:110-117

Abstract

“The histone demethylase Kdm3a is essential to progression through differentiation” Nucleic Acids Res 2012 40:7219-7232

Abstract

“Targeted silencing of the oncogenic transcription factor SOX2 in breast cancer” Nucleic Acids Res 2012 40:6725-6740

Abstract

“Yin Yang 1 extends the Myc-related transcription factors network in embryonic stem cells” Nucleic Acids Res 2012 40:3403-3418

Abstract

“RYBP Represses Endogenous Retroviruses and Preimplantation- and Germ Line-Specific Genes in Mouse Embryonic Stem Cells” Mol. Cell. Biol. 2012 32:1139-1149

Abstract

“Polycomb Repressor Complex-2 Is a Novel Target for Mesothelioma Therapy” Clin. Cancer Res. 2012 18:77-90

Abstract

“OCT4 establishes and maintains nucleosome-depleted regions that provide additional layers of epigenetic regulation of its target genes” Proc. Natl. Acad. Sci. USA 2011 108:14497-14502

Abstract

“Genome-wide promoter DNA methylation dynamics of human hematopoietic progenitor cells during differentiation and aging” Blood 2011 117:e182-e189

Abstract

“The CHD3 Chromatin Remodeler PICKLE and Polycomb Group Proteins Antagonistically Regulate Meristem Activity in the Arabidopsis” RootPlant Cell 2011 23:1047-1060

Abstract

“Chromatin structure of pluripotent stem cells and induced pluripotent stem cells” Briefings in Functional Genomics 2011 10:37-49

Abstract

Abbreviations used:

DNMT       DNA methyl transferase

ES             embryonic stem

JmjC         Jumonji C

lincRNA     long ncRNA

ncRNA       noncoding RNA

PcG          Polycomb group

PRC          Polycomb repressive complex

PRE          Polycomb repressive element

Previous Posts on Stem Cells:

Stem Cell Research — The Frontier is at the Technion in Israel

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…  Aviva Lev-Ari, PhD, RN Stem cells create new heart cells in baby mice, but not in adults, study …  picture on the left shows green c-kit+ precursor stem cells within an infarct (lower right) in a

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14 January 2013  by Dr. Sudipta Saha on Pharmaceutical Intelligence

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…  T-cells, said Dr. Margaret Goodell, director of the Stem Cells and Regenerative Medicine Center of Baylor College of Medicine. …  of pediatrics at BCM and a member of the Center for Cell and Gene Therapy at BCM, Texas Children¹s Hospital and The Methodist …  found that mice lacking the gene for this factor had a T-cell deficiency and in particular, too few of these early progenitor …

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28 March 2013  by ritusaxena on Pharmaceutical Intelligence

…  and Curator: Ritu Saxena, Ph.D Although cancer stem cells constitute only a small percentage of the tumor burden, their …  after therapeutic target in cancer. The post on cancer stem cells published on the 22nd of March, 2013, describes the identity of CSCs, their functional characteristics, possible cell of origin and biomarkers. This post focuses on the therapeutic potential …

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…  programs in the fields of personalized medicine, cell biology, cytogenetics, genotyping, and biobanking drive our …  by playing an important role in induced pluripotent stem (iPS) cell research. Induced pluripotent stem cells are powerful cells which can be made from skin or blood cells, and …

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…  seen in hematologic malignancies such as cutaneous T-cell lymphoma and peripheral T-cell lymphoma and little or no positive outcome …  resistance to chemotherapeutics, and similarity to cancer stem cells(6-10). Figure 1. HDACis led to the induction of EMT phemotype. (A …

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Personalized Medicine and Colon Cancer

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, BioSimilars, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Prevention: Research & Programs, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmaceutical R&D Investment, Population Health Management, Nutrition and Phytochemistry, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Technology Transfer: Biotech and Pharmaceutical, tagged BRAF, CIMP, CIN, colon cancer (CC), Colorectal cancer (CRC), dMMR, DNA methylation, gene expression profiles (GEPs), Immunoregulation, KRAS, Methylation, MSI, TP53, Wnt on May 25, 2013| 5 Comments »

Personalized Medicine and Colon Cancer

Author: Tilda Barliya, PhD

• 

According to Dr. Neil Risch a leading expert in statistical genetics and the director of the UCSF Institute for Human Genetics,  “Personalized medicine, in which a suite of molecules measured in a patient’s lab tests can inform decisions about preventing or treating diseases, is becoming a reality” (7).

Colorectal cancer (CRC) is the third most common cancer and the fourth-leading cause of cancer death worldwide despite advances in screening, diagnosis, and treatment. Staging is the only prognostic classification used in clinical practice to select patients for adjuvant chemotherapy. However, pathological staging fails to predict recurrence accurately in many patients undergoing curative surgery for localized CRC (1,2). Most of the patients who are not eligible for surgery need adjuvant chemotherapy in order to avoid relapse or to increase survival. Unfortunately, only a small portion of them shows an objective response to chemotherapy, becoming problematic to correctly predict patients’ clinical outcome (3).

CRC patients are normally being tested for several known biomarkers which falls into 4 main categories (5):

1. Chromosomal Instability (CIN)
2. Microsatellite Instability (MSI)
3. CpG Island methylator phynotype (CIMP)
4. Global DNA hypomethylation

In the past few years many studies have exploited microarray technology to investigate gene expression profiles (GEPs) in CRC, but no established signature has been found that is useful for clinical practice, especially for predicting prognosis.  Only a subset of CRC patients with MSI tumors have been shown to have better prognosis and probably respond differently to adjuvant chemotherapy compared to microsatellite stable (MSS) cancer patients (6).

Pritchard & Grady have summarized the selected biomarkers that have been evaluated in colon cancer patients (10).

Table 1

Selected Biomarkers That Have Been Evaluated in Colorectal Cancer

Biomarker	Molecular Lesion	Frequency in CRC	Prediction	Prognosis	Diagnosis
KRAS	Codon 12/13 activating mutations; rarely codon 61, 117,146	40%	Yes	Possible	–
BRAF	V600E activating mutation	10%	Probable	Probable	Lynch Syndrome
PIK3CA	Helical and kinase domain mutations	20%	Possible	Possible	–
PTEN	Loss of protein by IHC	30%	Possible	–	–
Microsatellite Instability (MSI)	Defined as >30% unstable loci in the NCI consensus panel or >40% unstable loci in a panel of mononucleotide microsatellite repeats9	15%	Probable	Yes	Lynch Syndrome
Chromosome Instability (CIN)	Aneuploidy	70%	Probable	Yes	–
18qLOH	Deletion of the long arm of chromosome 18	50%	Probable	Probable	–
CpG Island Methylator Phenotype (CIMP)	Methylation of at least three loci from a selected panel of five markers	15%	+/−	+/−	–
Vimentin (VIM)	Methylation	75%	–	–	Early Detection
TGFBR2	Inactivating Mutations	30%	–	–	–
TP53 Mutations	Inactivating Mutations	50%	–	–	–
APC Mutations	Inactivating Mutations	70%	–	–	FAP
CTNNB1 (β-Catenin)	Activating Mutations	2%	–	–	–
Mismatch Repair Genes	Loss of protein by IHC; methylation; inactivating mutations	1–15%	–	–	Lynch Syndrome

CRC- colorectal cancer; IHC- immunohistochemistry; FAP- Familial Adenomatous Polyposis

Examples for the great need of personalized medicine tailored according to the patients’ genetics is clearly seen with two specific drugs for CRC:  Cetuximab and panitumumab are two antibodies that were developed to treat colon cancer. However, at first it seemed as if they were a failure because they did not work in many patients. Then, it was discovered that if a cancer cell has a specific genetic mutation, known as K-ras, these drugs do not work.  This is an excellent example of using individual tumor genetics to predict whether or not treatment will work (8).

According to Marisa L et al, however, the molecular classification of CC currently used, which is based on a few common DNA markers as mentioned above (MSI, CpG island methylator phenotype [CIMP], chromosomal instability [CIN], and BRAF and KRAS mutations), needs to be refined.

Genetic Expression Profiles (GEP)

CRC is composed of distinct molecular entities that may develop through multiple pathways on the basis of different molecular features, as a consequence, there may be several prognostic signatures for CRC, each corresponding to a different entity. GEP studies have recently identified at least three distinct molecular subtypes of CC (4). Dr. Marisa Laetitia and her colleagues from the Boige’s lab however, have conducted a very thorough study and identifies 6 distinct clusters for CC patients. Herein, we’ll describe the majority of this study and their results.

Study  Design:

Marisa L et al (1) performed a consensus unsupervised analysis (using an Affymertix chip) of the GEP on tumor tissue sample from 750 patients with stage I to IV CC. Patients were staged according to the American Joint Committee on Cancer tumor node metastasis (TNM) staging system. Of the 750 tumor samples of the CIT cohort, 566 fulfilled RNA quality requirements for GEP analysis. The 566 samples were split into a discovery set (n = 443) and a validation set (n = 123).

Several known mutations were used as internal controls, including:

• The seven most frequent mutations in codons 12 and 13 of KRAS .
• The BRAF c.1799T>A (p.V600E)
• TP53mutations (exons 4–9)
• MSI was analyzed using a panel of five different microsatellite loci from the Bethesda reference panel
• CIMP status was determined using a panel of five markers (CACNA1G, IGF2, NEUROG1, RUNX3, and SOCS1)

Results:

The results revealed six clusters of samples based on the most variant probe sets. The consensus matrix showed that C2, C3, C4, and C6 appeared as well-individualized clusters, whereas there was more classification overlap between C1 and C5. In other words:

• Tumors classified as C1, C5, and C6 were more frequently CIN+, CIMP−, TP53– mutant, and distal (p<0.001), without any other molecular or clinicopathological features able to discriminate these three clusters clearly.
• Tumors classified as C2, C4, and C3 were more frequently CIMP+ (59%, 34%, and 18%, respectively, versus <5% in other clusters) and proximal.
• C2 was enriched for dMMR (68%) and BRAF- mutant tumors (40%).
• C3 was enriched for KRAS- mutant tumors (87%).

Note: No association between clusters and TNM stage (histopathology) was found, except enrichment for metastatic (31%) tumors in C4.

Figure: These signaling pathways associated with the molecular subtype (by cluster)

Marisa L et al. Signaling pathways associated with each molecular subtype

These clusters fall into several signaling pathways:

• up-regulated immune system and cell growth pathways were found in C2, the subtype enriched for dMMR tumors
• C4 and C6 both showed down-regulation of cell growth and death pathways and up-regulation of the epithelial–mesenchymal transition/motility pathways. displaying “stem cell phenotype–like” GEPs (91%)
• Most signaling pathways were down-regulated in C1 and C3.
• In C1, cell communication and immune pathways were down-regulated.
• In C5, cell communication, Wnt, and metabolism pathways were up-regulated.

These results are further summarized in table 2:

Marisa L et al. Gene Expression Classification of Colon Cancer into Molecular Subtypes

The authors have identified six robust molecular subtypes of CC individualized by distinct clinicobiological characteristics (as summarized in table 2).

This classification successfully identified the dMMR tumor subtype, and also individualized five other distinct subtypes among pMMR tumors, including three CIN+ CIMP− subtypes representing slightly more than half of the tumors. As expected, mutation of BRAF was associated with the dMMR subtype, but was also frequent in the C4 CIMP+ poor prognosis subtype. TP53– andKRAS-mutant tumors were found in all the subtypes; nevertheless, the C3 subtype, highly enriched in KRAS-mutant CC, was individualized and validated, suggesting a specific role of this mutation in this particular subgroup of CC.

Current Treatments for colon cancer- Table 3 (11) .

Constant S et al. Colon Cancer: Current Treatments and Preclinical Models for the Discovery and Development of New Therapies

Exploratory analysis of each subtype GEP with previously published supervised signatures and relevant deregulated signaling pathways improved the biological relevance of the classification.

The biological relevance of our subtypes was highlighted by significant differences in prognosis. In our unsupervised hierarchical clustering, patients whose tumors were classified as C4 or C6 had poorer RFS than the other patients.

Prognostic analyses based solely on common DNA alterations can distinguish between risk groups, but are still inadequate, as most CCs are pMMR CIMP− BRAFwt.

The markers BRAF-mutant, CIMP+, and dMMR may be useful for classifying a small proportion of cases, but are uninformative for a large number of patients.

Unfortunately, 5 of the 9 anti-CRC drugs approved by the FDA today are basic cytotoxic chemotherapeutics that attack cancer cells at a very fundamental level (i.e. the cell division machinery) without specific targets, resulting in poor effectiveness and strong side-effects (Table 3) (11).

An example for side effects induction mechanisms have also been reported in CRC for the BRAF(V600E) inhibitor Vemurafenib that triggers paradoxical EGFR activation (12).

Summary:

The authors of this study “report a new classification of CC into six robust molecular subtypes that arise through distinct biological pathways and represent novel prognostic subgroups. Our study clearly demonstrates that these gene signatures reflect the molecular heterogeneity of CC. This classification therefore provides a basis for the rational design of robust prognostic signatures for stage II–III CC and for identifying specific, potentially targetable markers for the different subtypes”.

These results further underline the urgent need to expand the standard therapy options by turning to more focused therapeutic strategies: a targeted therapy-for specific subtype profile.. Accordingly, the expansion and the development of new path of therapy, like drugs specifically targeting the self-renewal of intestinal cancer stem cells – a tumor cell population from which CRC is supposed to relapse, remains relevant.

Therefore, the complexity of these results supports the arrival of a personalized medicine, where a careful profiling of tumors will be useful to stratify patient population in order to test drugs sensitivity and combination with the ultimate goal to make treatments safer and more effective.

References:

1. Marisa L,  de Reyniès A, Alex Duval A,  Selves J, Pierre Gaub M, Vescovo L, Etienne-Grimaldi MC, Schiappa R, Guenot D, Ayadi M, Kirzin S, Chazal M, Fléjou JF…Boige V. Gene Expression Classification of Colon Cancer into Molecular Subtypes: Characterization, Validation, and Prognostic Value. PLoS Med May 2013 10(5): e1001453. doi:10.1371. http://www.plosmedicine.org/article/info%3Adoi/10.1371/journal.pmed.1001453

2. Villamil BP, Lopez AR, Prieto SH, Campos GL, Calles A, Lopez- Asenjo JA, Sanz Ortega J, Perez CF, Sastre J, Alfonso R, Caldes T, Sanchez FM and Rubio ED. Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior. BMC Cancer 2012, 12:260.  http://www.biomedcentral.com/1471-2407/12/260/

3. Diaz-Rubio E, Tabernero J, Gomez-Espana A, Massuti B, Sastre J, Chaves M, Abad A, Carrato A, Queralt B, Reina JJ, et al.: Phase III study of capecitabine plus oxaliplatin compared with continuous-infusion fluorouracil plus oxaliplatin as first-line therapy in metastatic colorectal cancer: final report of the Spanish Cooperative Group for the Treatment of Digestive Tumors Trial. J Clin Oncol 2007, 25(27):4224-4230. http://jco.ascopubs.org/content/25/27/4224.long

4. Salazar R, Roepman P, Capella G, Moreno V, Simon I, et al. (2011) Gene expression signature to improve prognosis prediction of stage II and III colorectal cancer. J Clin Oncol 29: 17–24. http://www.ncbi.nlm.nih.gov/pubmed?cmd=Search&doptcmdl=Citation&defaultField=Title%20Word&term=Salazar%5Bauthor%5D%20AND%20Gene%20expression%20signature%20to%20improve%20prognosis%20prediction%20of%20stage%20II%20and%20III%20colorectal%20cancer

5.  By: Global Genome Knowledge. Colorectal Cancer- Personalized Medicine, Now a Clinical Reality.  http://www.srlworld.com/innersense/Voice-135-Colorectal-Cancer-Sept-2012-IS.pdf

6. Popat S, Hubner R and Houlston RS. Systematic review of microsatellite instability and colorectal cancer prognosis. J Clin Oncol. 2005 Jan 20;23(3):609-618. http://www.ncbi.nlm.nih.gov/pubmed/15659508

7. By: Jeffrey Norris. Value of Genomics and Personalized Medicine Is Wrongly Downplayed.http://www.ucsf.edu/news/2012/04/11864/value-genomics-and-personalized-medicine-wrongly-downplayed

8. By: James C Salwitz. The Future is now: Personalized Medicine. http://www.cancer.org/cancer/news/expertvoices/post/2012/04/18/the-future-is-now-personalized-medicine.aspx

9. Jeffrey A. Meyerhardt., and Robert J. Mayer. Systemic Therapy for Colorectal Cancer. N Engl J Med 2005;352:476-487. http://www.med.upenn.edu/gastro/documents/NEJMchemotherapycolorectalcancer.pdf

10. Pritchard CC and Grady WM. Colorectal Cancer Molecular Biology Moves Into Clinical Practice. Gut. Jan 2011 60(1): 116-129.  Gut. 2011 January; 60(1): 116–129. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3006043/

11. Constant S, Huang S, Wiszniewski L andMas C. Colon Cancer: Current Treatments and Preclinical Models for the Discovery and Development of New Therapies.  Pharmacology, Toxicology and Pharmaceutical Science » “Drug Discovery”, book edited by Hany A. El-Shemy, ISBN 978-953-51-0906-8.  http://www.intechopen.com/books/drug-discovery/colon-cancer-current-treatments-and-preclinical-models-for-the-discovery-and-development-of-new-ther

12. Prahallad, C. Sun, S. Huang, F. Di Nicolantonio, R. Salazar, D. Zecchin, R. L. Beijersbergen, A. Bardelli, R. Bernards, 2012 Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature Jan 2012 483 (7387): 100-103. http://www.nature.com/nature/journal/v483/n7387/full/nature10868.html

Other related articles on this Open Access Online Scientific Journal include the following:

*. By Tilda Barliya PhD. Colon Cancer. http://pharmaceuticalintelligence.com/2013/04/30/colon-cancer/

**. By: Tilda Barliya PhD. CD47: Target Therapy for Cancer. http://pharmaceuticalintelligence.com/2013/05/07/cd47-target-therapy-for-cancer/

I. By: Aviva Lev-Ari, PhD, RN. Cancer Genomic Precision Therapy: Digitized Tumor’s Genome (WGSA) Compared with Genome-native Germ Line: Flash-frozen specimen and Formalin-fixed paraffin-embedded Specimen Needed. http://pharmaceuticalintelligence.com/2013/04/21/cancer-genomic-precision-therapy-digitized-tumors-genome-wgsa-compared-with-genome-native-germ-line-flash-frozen-specimen-and-formalin-fixed-paraffin-embedded-specimen-needed/

II. By: Aviva Lev-Ari, PhD, RN. Critical Gene in Calcium Reabsorption: Variants in the KCNJ and SLC12A1 genes – Calcium Intake and Cancer Protection. http://pharmaceuticalintelligence.com/2013/04/12/critical-gene-in-calcium-reabsorption-variants-in-the-kcnj-and-slc12a1-genes-calcium-intake-and-cancer-protection/

III.  By: Stephen J. Williams, Ph.D. Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing. http://pharmaceuticalintelligence.com/2013/04/10/issues-in-personalized-medicine-in-cancer-intratumor-heterogeneity-and-branched-evolution-revealed-by-multiregion-sequencing/

IV. By: Ritu Saxena, Ph.D. In Focus: Targeting of Cancer Stem Cells. http://pharmaceuticalintelligence.com/2013/03/27/in-focus-targeting-of-cancer-stem-cells/

V.  By: Ziv Raviv PhD. Cancer Screening at Sourasky Medical Center Cancer Prevention Center in Tel-Aviv. http://pharmaceuticalintelligence.com/2013/03/25/tel-aviv-sourasky-medical-center-cancer-prevention-center-excellent-example-for-adopting-prevention-of-cancer-as-a-mean-of-fighting-it/

VI. By: Ritu Saxena, PhD. In Focus: Identity of Cancer Stem Cells. http://pharmaceuticalintelligence.com/2013/03/22/in-focus-identity-of-cancer-stem-cells/

VII. By: Dror Nir, PhD. State of the art in oncologic imaging of Colorectal cancers. http://pharmaceuticalintelligence.com/2013/02/02/state-of-the-art-in-oncologic-imaging-of-colorectal-cancers/

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