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CRISPR/Cas9, Familial Amyloid Polyneuropathy ( FAP) and Neurodegenerative Disease


CRISPR/Cas9, Familial Amyloid Polyneuropathy ( FAP) and Neurodegenerative Disease

Curator: Larry H. Bernstein, MD, FCAP

 

CRISPR/Cas9 and Targeted Genome Editing: A New Era in Molecular Biology

https://www.neb.com/tools-and-resources/feature-articles/crispr-cas9-and-targeted-genome-editing-a-new-era-in-molecular-biology

The development of efficient and reliable ways to make precise, targeted changes to the genome of living cells is a long-standing goal for biomedical researchers. Recently, a new tool based on a bacterial CRISPR-associated protein-9 nuclease (Cas9) from Streptococcus pyogenes has generated considerable excitement (1). This follows several attempts over the years to manipulate gene function, including homologous recombination (2) and RNA interference (RNAi) (3). RNAi, in particular, became a laboratory staple enabling inexpensive and high-throughput interrogation of gene function (4, 5), but it is hampered by providing only temporary inhibition of gene function and unpredictable off-target effects (6). Other recent approaches to targeted genome modification – zinc-finger nucleases [ZFNs, (7)] and transcription-activator like effector nucleases [TALENs (8)]– enable researchers to generate permanent mutations by introducing doublestranded breaks to activate repair pathways. These approaches are costly and time-consuming to engineer, limiting their widespread use, particularly for large scale, high-throughput studies.

The Biology of Cas9

The functions of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and CRISPR-associated (Cas) genes are essential in adaptive immunity in select bacteria and archaea, enabling the organisms to respond to and eliminate invading genetic material. These repeats were initially discovered in the 1980s in E. coli (9), but their function wasn’t confirmed until 2007 by Barrangou and colleagues, who demonstrated that S. thermophilus can acquire resistance against a bacteriophage by integrating a genome fragment of an infectious virus into its CRISPR locus (10).

Three types of CRISPR mechanisms have been identified, of which type II is the most studied. In this case, invading DNA from viruses or plasmids is cut into small fragments and incorporated into a CRISPR locus amidst a series of short repeats (around 20 bps). The loci are transcribed, and transcripts are then processed to generate small RNAs (crRNA – CRISPR RNA), which are used to guide effector endonucleases that target invading DNA based on sequence complementarity (Figure 1) (11).

Figure 1. Cas9 in vivo: Bacterial Adaptive Immunity

https://www.neb.com/~/media/NebUs/Files/Feature%20Articles/Images/FA_Cas9_Fig1_Cas9InVivo.png

In the acquisition phase, foreign DNA is incorporated into the bacterial genome at the CRISPR loci. CRISPR loci is then transcribed and processed into crRNA during crRNA biogenesis. During interference, Cas9 endonuclease complexed with a crRNA and separate tracrRNA cleaves foreign DNA containing a 20-nucleotide crRNA complementary sequence adjacent to the PAM sequence. (Figure not drawn to scale.)

https://www.neb.com/~/media/NebUs/Files/Feature%20Articles/Images/FA_Cas9_GenomeEditingGlossary.png

One Cas protein, Cas9 (also known as Csn1), has been shown, through knockdown and rescue experiments to be a key player in certain CRISPR mechanisms (specifically type II CRISPR systems). The type II CRISPR mechanism is unique compared to other CRISPR systems, as only one Cas protein (Cas9) is required for gene silencing (12). In type II systems, Cas9 participates in the processing of crRNAs (12), and is responsible for the destruction of the target DNA (11). Cas9’s function in both of these steps relies on the presence of two nuclease domains, a RuvC-like nuclease domain located at the amino terminus and a HNH-like nuclease domain that resides in the mid-region of the protein (13).

To achieve site-specific DNA recognition and cleavage, Cas9 must be complexed with both a crRNA and a separate trans-activating crRNA (tracrRNA or trRNA), that is partially complementary to the crRNA (11). The tracrRNA is required for crRNA maturation from a primary transcript encoding multiple pre-crRNAs. This occurs in the presence of RNase III and Cas9 (12).

During the destruction of target DNA, the HNH and RuvC-like nuclease domains cut both DNA strands, generating double-stranded breaks (DSBs) at sites defined by a 20-nucleotide target sequence within an associated crRNA transcript (11, 14). The HNH domain cleaves the complementary strand, while the RuvC domain cleaves the noncomplementary strand.

The double-stranded endonuclease activity of Cas9 also requires that a short conserved sequence, (2–5 nts) known as protospacer-associated motif (PAM), follows immediately 3´- of the crRNA complementary sequence (15). In fact, even fully complementary sequences are ignored by Cas9-RNA in the absence of a PAM sequence (16).

Cas9 and CRISPR as a New Tool in Molecular Biology

The simplicity of the type II CRISPR nuclease, with only three required components (Cas9 along with the crRNA and trRNA) makes this system amenable to adaptation for genome editing. This potential was realized in 2012 by the Doudna and Charpentier labs (11). Based on the type II CRISPR system described previously, the authors developed a simplified two-component system by combining trRNA and crRNA into a single synthetic single guide RNA (sgRNA). sgRNAprogrammed Cas9 was shown to be as effective as Cas9 programmed with separate trRNA and crRNA in guiding targeted gene alterations (Figure 2A).

To date, three different variants of the Cas9 nuclease have been adopted in genome-editing protocols. The first is wild-type Cas9, which can site-specifically cleave double-stranded DNA, resulting in the activation of the doublestrand break (DSB) repair machinery. DSBs can be repaired by the cellular Non-Homologous End Joining (NHEJ) pathway (17), resulting in insertions and/or deletions (indels) which disrupt the targeted locus. Alternatively, if a donor template with homology to the targeted locus is supplied, the DSB may be repaired by the homology-directed repair (HDR) pathway allowing for precise replacement mutations to be made (Figure 2A) (17, 18).

Cong and colleagues (1) took the Cas9 system a step further towards increased precision by developing a mutant form, known as Cas9D10A, with only nickase activity. This means it cleaves only one DNA strand, and does not activate NHEJ. Instead, when provided with a homologous repair template, DNA repairs are conducted via the high-fidelity HDR pathway only, resulting in reduced indel mutations (1, 11, 19). Cas9D10A is even more appealing in terms of target specificity when loci are targeted by paired Cas9 complexes designed to generate adjacent DNA nicks (20) (see further details about “paired nickases” in Figure 2B).

The third variant is a nuclease-deficient Cas9 (dCas9, Figure 2C) (21). Mutations H840A in the HNH domain and D10A in the RuvC domain inactivate cleavage activity, but do not prevent DNA binding (11, 22). Therefore, this variant can be used to sequence-specifically target any region of the genome without cleavage. Instead, by fusing with various effector domains, dCas9 can be used either as a gene silencing or activation tool (21, 23–26). Furthermore, it can be used as a visualization tool. For instance, Chen and colleagues used dCas9 fused to Enhanced Green Fluorescent Protein (EGFP) to visualize repetitive DNA sequences with a single sgRNA or nonrepetitive loci using multiple sgRNAs (27).

Figure 2. CRISPR/Cas9 System Applications

https://www.neb.com/~/media/NebUs/Files/Feature%20Articles/Images/FA_Cas9_Fig2_Cas9forGenomeEditing.png?device=modal

  1. Wild-type Cas9 nuclease site specifically cleaves double-stranded DNA activating double-strand break repair machinery. In the absence of a homologous repair template non-homologous end joining can result in indels disrupting the target sequence. Alternatively, precise mutations and knock-ins can be made by providing a homologous repair template and exploiting the homology directed repair pathway.
    B. Mutated Cas9 makes a site specific single-strand nick. Two sgRNA can be used to introduce a staggered double-stranded break which can then undergo homology directed repair.
    C. Nuclease-deficient Cas9 can be fused with various effector domains allowing specific localization. For example, transcriptional activators, repressors, and fluorescent proteins.

Targeting Efficiency and Off-target Mutations

Targeting efficiency, or the percentage of desired mutation achieved, is one of the most important parameters by which to assess a genome-editing tool. The targeting efficiency of Cas9 compares favorably with more established methods, such as TALENs or ZFNs (8). For example, in human cells, custom-designed ZFNs and TALENs could only achieve efficiencies ranging from 1% to 50% (29–31). In contrast, the Cas9 system has been reported to have efficiencies up to >70% in zebrafish (32) and plants (33), and ranging from 2–5% in induced pluripotent stem cells (34). In addition, Zhou and colleagues were able to improve genome targeting up to 78% in one-cell mouse embryos, and achieved effective germline transmission through the use of dual sgRNAs to simultaneously target an individual gene (35).

A widely used method to identify mutations is the T7 Endonuclease I mutation detection assay (36, 37) (Figure 3). This assay detects heteroduplex DNA that results from the annealing of a DNA strand, including desired mutations, with a wildtype DNA strand (37).

Figure 3. T7 Endonuclease I Targeting Efficiency Assay

https://www.neb.com/~/media/NebUs/Files/Feature%20Articles/Images/FA_Cas9_Fig3_T7Assay_TargetEfficiency.png

Genomic DNA is amplified with primers bracketing the modified locus. PCR products are then denatured and re-annealed yielding 3 possible structures. Duplexes containing a mismatch are digested by T7 Endonuclease I. The DNA is then electrophoretically separated and fragment analysis is used to calculate targeting efficiency.

Another important parameter is the incidence of off-target mutations. Such mutations are likely to appear in sites that have differences of only a few nucleotides compared to the original sequence, as long as they are adjacent to a PAM sequence. This occurs as Cas9 can tolerate up to 5 base mismatches within the protospacer region (36) or a single base difference in the PAM sequence (38). Off-target mutations are generally more difficult to detect, requiring whole-genome sequencing to rule them out completely.

Recent improvements to the CRISPR system for reducing off-target mutations have been made through the use of truncated gRNA (truncated within the crRNA-derived sequence) or by adding two extra guanine (G) nucleotides to the 5´ end (28, 37). Another way researchers have attempted to minimize off-target effects is with the use of “paired nickases” (20). This strategy uses D10A Cas9 and two sgRNAs complementary to the adjacent area on opposite strands of the target site (Figure 2B). While this induces DSBs in the target DNA, it is expected to create only single nicks in off-target locations and, therefore, result in minimal off-target mutations.

By leveraging computation to reduce off-target mutations, several groups have developed webbased tools to facilitate the identification of potential CRISPR target sites and assess their potential for off-target cleavage. Examples include the CRISPR Design Tool (38) and the ZiFiT Targeter, Version 4.2 (39, 40).

Applications as a Genome-editing and Genome Targeting Tool

Following its initial demonstration in 2012 (9), the CRISPR/Cas9 system has been widely adopted. This has already been successfully used to target important genes in many cell lines and organisms, including human (34), bacteria (41), zebrafish (32), C. elegans (42), plants (34), Xenopus tropicalis (43), yeast (44), Drosophila (45), monkeys (46), rabbits (47), pigs (42), rats (48) and mice (49). Several groups have now taken advantage of this method to introduce single point mutations (deletions or insertions) in a particular target gene, via a single gRNA (14, 21, 29). Using a pair of gRNA-directed Cas9 nucleases instead, it is also possible to induce large deletions or genomic rearrangements, such as inversions or translocations (50). A recent exciting development is the use of the dCas9 version of the CRISPR/Cas9 system to target protein domains for transcriptional regulation (26, 51, 52), epigenetic modification (25), and microscopic visualization of specific genome loci (27).

The CRISPR/Cas9 system requires only the redesign of the crRNA to change target specificity. This contrasts with other genome editing tools, including zinc finger and TALENs, where redesign of the protein-DNA interface is required. Furthermore, CRISPR/Cas9 enables rapid genome-wide interrogation of gene function by generating large gRNA libraries (51, 53) for genomic screening.

The Future of CRISPR/Cas9

The rapid progress in developing Cas9 into a set of tools for cell and molecular biology research has been remarkable, likely due to the simplicity, high efficiency and versatility of the system. Of the designer nuclease systems currently available for precision genome engineering, the CRISPR/Cas system is by far the most user friendly. It is now also clear that Cas9’s potential reaches beyond DNA cleavage, and its usefulness for genome locus-specific recruitment of proteins will likely only be limited by our imagination.

 

Scientists urge caution in using new CRISPR technology to treat human genetic disease

By Robert Sanders, Media relations | MARCH 19, 2015
http://news.berkeley.edu/2015/03/19/scientists-urge-caution-in-using-new-crispr-technology-to-treat-human-genetic-disease/

http://news.berkeley.edu/wp-content/uploads/2015/03/crispr350.jpg

The bacterial enzyme Cas9 is the engine of RNA-programmed genome engineering in human cells. (Graphic by Jennifer Doudna/UC Berkeley)

A group of 18 scientists and ethicists today warned that a revolutionary new tool to cut and splice DNA should be used cautiously when attempting to fix human genetic disease, and strongly discouraged any attempts at making changes to the human genome that could be passed on to offspring.

Among the authors of this warning is Jennifer Doudna, the co-inventor of the technology, called CRISPR-Cas9, which is driving a new interest in gene therapy, or “genome engineering.” She and colleagues co-authored a perspective piece that appears in the March 20 issue of Science, based on discussions at a meeting that took place in Napa on Jan. 24. The same issue of Science features a collection of recent research papers, commentary and news articles on CRISPR and its implications.    …..

A prudent path forward for genomic engineering and germline gene modification

David Baltimore1,  Paul Berg2, …., Jennifer A. Doudna4,10,*, et al.
http://science.sciencemag.org/content/early/2015/03/18/science.aab1028.full
Science  19 Mar 2015.  http://dx.doi.org:/10.1126/science.aab1028

 

Correcting genetic defects

Scientists today are changing DNA sequences to correct genetic defects in animals as well as cultured tissues generated from stem cells, strategies that could eventually be used to treat human disease. The technology can also be used to engineer animals with genetic diseases mimicking human disease, which could lead to new insights into previously enigmatic disorders.

The CRISPR-Cas9 tool is still being refined to ensure that genetic changes are precisely targeted, Doudna said. Nevertheless, the authors met “… to initiate an informed discussion of the uses of genome engineering technology, and to identify proactively those areas where current action is essential to prepare for future developments. We recommend taking immediate steps toward ensuring that the application of genome engineering technology is performed safely and ethically.”

 

Amyloid CRISPR Plasmids and si/shRNA Gene Silencers

http://www.scbt.com/crispr/table-amyloid.html

Santa Cruz Biotechnology, Inc. offers a broad range of gene silencers in the form of siRNAs, shRNA Plasmids and shRNA Lentiviral Particles as well as CRISPR/Cas9 Knockout and CRISPR Double Nickase plasmids. Amyloid gene silencers are available as Amyloid siRNA, Amyloid shRNA Plasmid, Amyloid shRNA Lentiviral Particles and Amyloid CRISPR/Cas9 Knockout plasmids. Amyloid CRISPR/dCas9 Activation Plasmids and CRISPR Lenti Activation Systems for gene activation are also available. Gene silencers and activators are useful for gene studies in combination with antibodies used for protein detection.    Amyloid CRISPR Knockout, HDR and Nickase Knockout Plasmids

 

CRISPR-Cas9-Based Knockout of the Prion Protein and Its Effect on the Proteome


Mehrabian M, Brethour D, MacIsaac S, Kim JK, Gunawardana C.G, Wang H, et al.
PLoS ONE 2014; 9(12): e114594. http://dx.doi.org/10.1371/journal.pone.0114594

The molecular function of the cellular prion protein (PrPC) and the mechanism by which it may contribute to neurotoxicity in prion diseases and Alzheimer’s disease are only partially understood. Mouse neuroblastoma Neuro2a cells and, more recently, C2C12 myocytes and myotubes have emerged as popular models for investigating the cellular biology of PrP. Mouse epithelial NMuMG cells might become attractive models for studying the possible involvement of PrP in a morphogenetic program underlying epithelial-to-mesenchymal transitions. Here we describe the generation of PrP knockout clones from these cell lines using CRISPR-Cas9 knockout technology. More specifically, knockout clones were generated with two separate guide RNAs targeting recognition sites on opposite strands within the first hundred nucleotides of the Prnp coding sequence. Several PrP knockout clones were isolated and genomic insertions and deletions near the CRISPR-target sites were characterized. Subsequently, deep quantitative global proteome analyses that recorded the relative abundance of>3000 proteins (data deposited to ProteomeXchange Consortium) were undertaken to begin to characterize the molecular consequences of PrP deficiency. The levels of ∼120 proteins were shown to reproducibly correlate with the presence or absence of PrP, with most of these proteins belonging to extracellular components, cell junctions or the cytoskeleton.

http://journals.plos.org/plosone/article/figure/image?size=inline&id=info:doi/10.1371/journal.pone.0114594.g001

http://journals.plos.org/plosone/article/figure/image?size=inline&id=info:doi/10.1371/journal.pone.0114594.g003

 

Development and Applications of CRISPR-Cas9 for Genome Engineering

Patrick D. Hsu,1,2,3 Eric S. Lander,1 and Feng Zhang1,2,*
Cell. 2014 Jun 5; 157(6): 1262–1278.   doi:  10.1016/j.cell.2014.05.010

Recent advances in genome engineering technologies based on the CRISPR-associated RNA-guided endonuclease Cas9 are enabling the systematic interrogation of mammalian genome function. Analogous to the search function in modern word processors, Cas9 can be guided to specific locations within complex genomes by a short RNA search string. Using this system, DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice. Cas9-mediated genetic perturbation is simple and scalable, empowering researchers to elucidate the functional organization of the genome at the systems level and establish causal linkages between genetic variations and biological phenotypes. In this Review, we describe the development and applications of Cas9 for a variety of research or translational applications while highlighting challenges as well as future directions. Derived from a remarkable microbial defense system, Cas9 is driving innovative applications from basic biology to biotechnology and medicine.

The development of recombinant DNA technology in the 1970s marked the beginning of a new era for biology. For the first time, molecular biologists gained the ability to manipulate DNA molecules, making it possible to study genes and harness them to develop novel medicine and biotechnology. Recent advances in genome engineering technologies are sparking a new revolution in biological research. Rather than studying DNA taken out of the context of the genome, researchers can now directly edit or modulate the function of DNA sequences in their endogenous context in virtually any organism of choice, enabling them to elucidate the functional organization of the genome at the systems level, as well as identify causal genetic variations.

Broadly speaking, genome engineering refers to the process of making targeted modifications to the genome, its contexts (e.g., epigenetic marks), or its outputs (e.g., transcripts). The ability to do so easily and efficiently in eukaryotic and especially mammalian cells holds immense promise to transform basic science, biotechnology, and medicine (Figure 1).

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343198/bin/nihms659174f1.jpg

For life sciences research, technologies that can delete, insert, and modify the DNA sequences of cells or organisms enable dissecting the function of specific genes and regulatory elements. Multiplexed editing could further allow the interrogation of gene or protein networks at a larger scale. Similarly, manipulating transcriptional regulation or chromatin states at particular loci can reveal how genetic material is organized and utilized within a cell, illuminating relationships between the architecture of the genome and its functions. In biotechnology, precise manipulation of genetic building blocks and regulatory machinery also facilitates the reverse engineering or reconstruction of useful biological systems, for example, by enhancing biofuel production pathways in industrially relevant organisms or by creating infection-resistant crops. Additionally, genome engineering is stimulating a new generation of drug development processes and medical therapeutics. Perturbation of multiple genes simultaneously could model the additive effects that underlie complex polygenic disorders, leading to new drug targets, while genome editing could directly correct harmful mutations in the context of human gene therapy (Tebas et al., 2014).

Eukaryotic genomes contain billions of DNA bases and are difficult to manipulate. One of the breakthroughs in genome manipulation has been the development of gene targeting by homologous recombination (HR), which integrates exogenous repair templates that contain sequence homology to the donor site (Figure 2A) (Capecchi, 1989). HR-mediated targeting has facilitated the generation of knockin and knockout animal models via manipulation of germline competent stem cells, dramatically advancing many areas of biological research. However, although HR-mediated gene targeting produces highly precise alterations, the desired recombination events occur extremely infrequently (1 in 106–109 cells) (Capecchi, 1989), presenting enormous challenges for large-scale applications of gene-targeting experiments.

Genome Editing Technologies Exploit Endogenous DNA Repair Machinery

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343198/bin/nihms659174f2.gif

To overcome these challenges, a series of programmable nuclease-based genome editing technologies have been developed in recent years, enabling targeted and efficient modification of a variety of eukaryotic and particularly mammalian species. Of the current generation of genome editing technologies, the most rapidly developing is the class of RNA-guided endonucleases known as Cas9 from the microbial adaptive immune system CRISPR (clustered regularly interspaced short palindromic repeats), which can be easily targeted to virtually any genomic location of choice by a short RNA guide. Here, we review the development and applications of the CRISPR-associated endonuclease Cas9 as a platform technology for achieving targeted perturbation of endogenous genomic elements and also discuss challenges and future avenues for innovation.   ……

Figure 4   Natural Mechanisms of Microbial CRISPR Systems in Adaptive Immunity

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343198/bin/nihms659174f4.gif

……  A key turning point came in 2005, when systematic analysis of the spacer sequences separating the individual direct repeats suggested their extrachromosomal and phage-associated origins (Mojica et al., 2005Pourcel et al., 2005Bolotin et al., 2005). This insight was tremendously exciting, especially given previous studies showing that CRISPR loci are transcribed (Tang et al., 2002) and that viruses are unable to infect archaeal cells carrying spacers corresponding to their own genomes (Mojica et al., 2005). Together, these findings led to the speculation that CRISPR arrays serve as an immune memory and defense mechanism, and individual spacers facilitate defense against bacteriophage infection by exploiting Watson-Crick base-pairing between nucleic acids (Mojica et al., 2005Pourcel et al., 2005). Despite these compelling realizations that CRISPR loci might be involved in microbial immunity, the specific mechanism of how the spacers act to mediate viral defense remained a challenging puzzle. Several hypotheses were raised, including thoughts that CRISPR spacers act as small RNA guides to degrade viral transcripts in a RNAi-like mechanism (Makarova et al., 2006) or that CRISPR spacers direct Cas enzymes to cleave viral DNA at spacer-matching regions (Bolotin et al., 2005).   …..

As the pace of CRISPR research accelerated, researchers quickly unraveled many details of each type of CRISPR system (Figure 4). Building on an earlier speculation that protospacer adjacent motifs (PAMs) may direct the type II Cas9 nuclease to cleave DNA (Bolotin et al., 2005), Moineau and colleagues highlighted the importance of PAM sequences by demonstrating that PAM mutations in phage genomes circumvented CRISPR interference (Deveau et al., 2008). Additionally, for types I and II, the lack of PAM within the direct repeat sequence within the CRISPR array prevents self-targeting by the CRISPR system. In type III systems, however, mismatches between the 5′ end of the crRNA and the DNA target are required for plasmid interference (Marraffini and Sontheimer, 2010).  …..

In 2013, a pair of studies simultaneously showed how to successfully engineer type II CRISPR systems from Streptococcus thermophilus (Cong et al., 2013) andStreptococcus pyogenes (Cong et al., 2013Mali et al., 2013a) to accomplish genome editing in mammalian cells. Heterologous expression of mature crRNA-tracrRNA hybrids (Cong et al., 2013) as well as sgRNAs (Cong et al., 2013Mali et al., 2013a) directs Cas9 cleavage within the mammalian cellular genome to stimulate NHEJ or HDR-mediated genome editing. Multiple guide RNAs can also be used to target several genes at once. Since these initial studies, Cas9 has been used by thousands of laboratories for genome editing applications in a variety of experimental model systems (Sander and Joung, 2014). ……

The majority of CRISPR-based technology development has focused on the signature Cas9 nuclease from type II CRISPR systems. However, there remains a wide diversity of CRISPR types and functions. Cas RAMP module (Cmr) proteins identified in Pyrococcus furiosus and Sulfolobus solfataricus (Hale et al., 2012) constitute an RNA-targeting CRISPR immune system, forming a complex guided by small CRISPR RNAs that target and cleave complementary RNA instead of DNA. Cmr protein homologs can be found throughout bacteria and archaea, typically relying on a 5 site tag sequence on the target-matching crRNA for Cmr-directed cleavage.

Unlike RNAi, which is targeted largely by a 6 nt seed region and to a lesser extent 13 other bases, Cmr crRNAs contain 30–40 nt of target complementarity. Cmr-CRISPR technologies for RNA targeting are thus a promising target for orthogonal engineering and minimal off-target modification. Although the modularity of Cmr systems for RNA-targeting in mammalian cells remains to be investigated, Cmr complexes native to P. furiosus have already been engineered to target novel RNA substrates (Hale et al., 20092012).   ……

Although Cas9 has already been widely used as a research tool, a particularly exciting future direction is the development of Cas9 as a therapeutic technology for treating genetic disorders. For a monogenic recessive disorder due to loss-of-function mutations (such as cystic fibrosis, sickle-cell anemia, or Duchenne muscular dystrophy), Cas9 may be used to correct the causative mutation. This has many advantages over traditional methods of gene augmentation that deliver functional genetic copies via viral vector-mediated overexpression—particularly that the newly functional gene is expressed in its natural context. For dominant-negative disorders in which the affected gene is haplosufficient (such as transthyretin-related hereditary amyloidosis or dominant forms of retinitis pigmentosum), it may also be possible to use NHEJ to inactivate the mutated allele to achieve therapeutic benefit. For allele-specific targeting, one could design guide RNAs capable of distinguishing between single-nucleotide polymorphism (SNP) variations in the target gene, such as when the SNP falls within the PAM sequence.

 

 

CRISPR/Cas9: a powerful genetic engineering tool for establishing large animal models of neurodegenerative diseases

Zhuchi Tu, Weili Yang, Sen Yan, Xiangyu Guo and Xiao-Jiang Li

Molecular Neurodegeneration 2015; 10:35  http://dx.doi.org:/10.1186/s13024-015-0031-x

Animal models are extremely valuable to help us understand the pathogenesis of neurodegenerative disorders and to find treatments for them. Since large animals are more like humans than rodents, they make good models to identify the important pathological events that may be seen in humans but not in small animals; large animals are also very important for validating effective treatments or confirming therapeutic targets. Due to the lack of embryonic stem cell lines from large animals, it has been difficult to use traditional gene targeting technology to establish large animal models of neurodegenerative diseases. Recently, CRISPR/Cas9 was used successfully to genetically modify genomes in various species. Here we discuss the use of CRISPR/Cas9 technology to establish large animal models that can more faithfully mimic human neurodegenerative diseases.

Neurodegenerative diseases — Alzheimer’s disease(AD),Parkinson’s disease(PD), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), and frontotemporal dementia (FTD) — are characterized by age-dependent and selective neurodegeneration. As the life expectancy of humans lengthens, there is a greater prevalence of these neurodegenerative diseases; however, the pathogenesis of most of these neurodegenerative diseases remain unclear, and we lack effective treatments for these important brain disorders.

CRISPR/Cas9,  Non-human primates,  Neurodegenerative diseases,  Animal model

There are a number of excellent reviews covering different types of neurodegenerative diseases and their genetic mouse models [812]. Investigations of different mouse models of neurodegenerative diseases have revealed a common pathology shared by these diseases. First, the development of neuropathology and neurological symptoms in genetic mouse models of neurodegenerative diseases is age dependent and progressive. Second, all the mouse models show an accumulation of misfolded or aggregated proteins resulting from the expression of mutant genes. Third, despite the widespread expression of mutant proteins throughout the body and brain, neuronal function appears to be selectively or preferentially affected. All these facts indicate that mouse models of neurodegenerative diseases recapitulate important pathologic features also seen in patients with neurodegenerative diseases.

However, it seems that mouse models can not recapitulate the full range of neuropathology seen in patients with neurodegenerative diseases. Overt neurodegeneration, which is the most important pathological feature in patient brains, is absent in genetic rodent models of AD, PD, and HD. Many rodent models that express transgenic mutant proteins under the control of different promoters do not replicate overt neurodegeneration, which is likely due to their short life spans and the different aging processes of small animals. Also important are the remarkable differences in brain development between rodents and primates. For example, the mouse brain takes 21 days to fully develop, whereas the formation of primate brains requires more than 150 days [13]. The rapid development of the brain in rodents may render neuronal cells resistant to misfolded protein-mediated neurodegeneration. Another difficulty in using rodent models is how to analyze cognitive and emotional abnormalities, which are the early symptoms of most neurodegenerative diseases in humans. Differences in neuronal circuitry, anatomy, and physiology between rodent and primate brains may also account for the behavioral differences between rodent and primate models.

 

Mitochondrial dynamics–fusion, fission, movement, and mitophagy–in neurodegenerative diseases

Hsiuchen Chen and David C. Chan
Human Molec Gen 2009; 18, Review Issue 2 R169–R176
http://dx.doi.org:/10.1093/hmg/ddp326

Neurons are metabolically active cells with high energy demands at locations distant from the cell body. As a result, these cells are particularly dependent on mitochondrial function, as reflected by the observation that diseases of mitochondrial dysfunction often have a neurodegenerative component. Recent discoveries have highlighted that neurons are reliant particularly on the dynamic properties of mitochondria. Mitochondria are dynamic organelles by several criteria. They engage in repeated cycles of fusion and fission, which serve to intermix the lipids and contents of a population of mitochondria. In addition, mitochondria are actively recruited to subcellular sites, such as the axonal and dendritic processes of neurons. Finally, the quality of a mitochondrial population is maintained through mitophagy, a form of autophagy in which defective mitochondria are selectively degraded. We review the general features of mitochondrial dynamics, incorporating recent findings on mitochondrial fusion, fission, transport and mitophagy. Defects in these key features are associated with neurodegenerative disease. Charcot-Marie-Tooth type 2A, a peripheral neuropathy, and dominant optic atrophy, an inherited optic neuropathy, result from a primary deficiency of mitochondrial fusion. Moreover, several major neurodegenerative diseases—including Parkinson’s, Alzheimer’s and Huntington’s disease—involve disruption of mitochondrial dynamics. Remarkably, in several disease models, the manipulation of mitochondrial fusion or fission can partially rescue disease phenotypes. We review how mitochondrial dynamics is altered in these neurodegenerative diseases and discuss the reciprocal interactions between mitochondrial fusion, fission, transport and mitophagy.

 

Applications of CRISPR–Cas systems in Neuroscience

Matthias Heidenreich  & Feng Zhang
Nature Rev Neurosci 2016; 17:36–44   http://dx.doi.org:/10.1038/nrn.2015.2

Genome-editing tools, and in particular those based on CRISPR–Cas (clustered regularly interspaced short palindromic repeat (CRISPR)–CRISPR-associated protein) systems, are accelerating the pace of biological research and enabling targeted genetic interrogation in almost any organism and cell type. These tools have opened the door to the development of new model systems for studying the complexity of the nervous system, including animal models and stem cell-derived in vitro models. Precise and efficient gene editing using CRISPR–Cas systems has the potential to advance both basic and translational neuroscience research.
Cellular neuroscience
, DNA recombination, Genetic engineering, Molecular neuroscience

Figure 3: In vitro applications of Cas9 in human iPSCs.close

http://www.nature.com/nrn/journal/v17/n1/carousel/nrn.2015.2-f3.jpg

a | Evaluation of disease candidate genes from large-population genome-wide association studies (GWASs). Human primary cells, such as neurons, are not easily available and are difficult to expand in culture. By contrast, induced pluripo…

  1. Genome-editing Technologies for Gene and Cell Therapy

Molecular Therapy 12 Jan 2016

  1. Systematic quantification of HDR and NHEJ reveals effects of locus, nuclease, and cell type on genome-editing

Scientific Reports 31 Mar 2016

  1. Controlled delivery of β-globin-targeting TALENs and CRISPR/Cas9 into mammalian cells for genome editing using microinjection

Scientific Reports 12 Nov 2015

 

Alzheimer’s Disease: Medicine’s Greatest Challenge in the 21st Century

https://www.physicsforums.com/insights/can-gene-editing-eliminate-alzheimers-disease/

The development of the CRISPR/Cas9 system has made gene editing a relatively simple task.  While CRISPR and other gene editing technologies stand to revolutionize biomedical research and offers many promising therapeutic avenues (such as in the treatment of HIV), a great deal of debate exists over whether CRISPR should be used to modify human embryos. As I discussed in my previous Insight article, we lack enough fundamental biological knowledge to enhance many traits like height or intelligence, so we are not near a future with genetically-enhanced super babies. However, scientists have identified a few rare genetic variants that protect against disease.  One such protective variant is a mutation in the APP gene that protects against Alzheimer’s disease and cognitive decline in old age. If we can perfect gene editing technologies, is this mutation one that we should be regularly introducing into embryos? In this article, I explore the potential for using gene editing as a way to prevent Alzheimer’s disease in future generations. Alzheimer’s Disease: Medicine’s Greatest Challenge in the 21st Century Can gene editing be the missing piece in the battle against Alzheimer’s? (Source: bostonbiotech.org) I chose to assess the benefit of germline gene editing in the context of Alzheimer’s disease because this disease is one of the biggest challenges medicine faces in the 21st century. Alzheimer’s disease is a chronic neurodegenerative disease responsible for the majority of the cases of dementia in the elderly. The disease symptoms begins with short term memory loss and causes more severe symptoms – problems with language, disorientation, mood swings, behavioral issues – as it progresses, eventually leading to the loss of bodily functions and death. Because of the dementia the disease causes, Alzheimer’s patients require a great deal of care, and the world spends ~1% of its total GDP on caring for those with Alzheimer’s and related disorders. Because the prevalence of the disease increases with age, the situation will worsen as life expectancies around the globe increase: worldwide cases of Alzheimer’s are expected to grow from 35 million today to over 115 million by 2050.

Despite much research, the exact causes of Alzheimer’s disease remains poorly understood. The disease seems to be related to the accumulation of plaques made of amyloid-β peptides that form on the outside of neurons, as well as the formation of tangles of the protein tau inside of neurons. Although many efforts have been made to target amyloid-β or the enzymes involved in its formation, we have so far been unsuccessful at finding any treatment that stops the disease or reverses its progress. Some researchers believe that most attempts at treating Alzheimer’s have failed because, by the time a patient shows symptoms, the disease has already progressed past the point of no return.

While research towards a cure continues, researchers have sought effective ways to prevent Alzheimer’s disease. Although some studies show that mental and physical exercise may lower ones risk of Alzheimer’s disease, approximately 60-80% of the risk for Alzheimer’s disease appears to be genetic. Thus, if we’re serious about prevention, we may have to act at the genetic level. And because the brain is difficult to access surgically for gene therapy in adults, this means using gene editing on embryos.

Reference https://www.physicsforums.com/insights/can-gene-editing-eliminate-alzheimers-disease/

 

Utilising CRISPR to Generate Predictive Disease Models: a Case Study in Neurodegenerative Disorders


Dr. Bhuvaneish.T. Selvaraj  – Scottish Centre for Regenerative Medicine

http://www.crisprsummit.com/utilising-crispr-to-generate-predictive-disease-models-a-case-study-in-neurodegenerative-disorders

  • Introducing the latest developments in predictive model generation
  • Discover how CRISPR is being used to develop disease models to study and treat neurodegenerative disorders
  • In depth Q&A session to answer your most pressing questions

 

Turning On Genes, Systematically, with CRISPR/Cas9

http://www.genengnews.com/gen-news-highlights/turning-on-genes-systematically-with-crispr-cas9/81250697/

 

Scientists based at MIT assert that they can reliably turn on any gene of their choosing in living cells. [Feng Zhang and Steve Dixon]  http://www.genengnews.com/media/images/GENHighlight/Dec12_2014_CRISPRCas9GeneActivationSystem7838101231.jpg

With the latest CRISPR/Cas9 advance, the exhortation “turn on, tune in, drop out” comes to mind. The CRISPR/Cas9 gene-editing system was already a well-known means of “tuning in” (inserting new genes) and “dropping out” (knocking out genes). But when it came to “turning on” genes, CRISPR/Cas9 had little potency. That is, it had demonstrated only limited success as a way to activate specific genes.

A new CRISPR/Cas9 approach, however, appears capable of activating genes more effectively than older approaches. The new approach may allow scientists to more easily determine the function of individual genes, according to Feng Zhang, Ph.D., a researcher at MIT and the Broad Institute. Dr. Zhang and colleagues report that the new approach permits multiplexed gene activation and rapid, large-scale studies of gene function.

The new technique was introduced in the December 10 online edition of Nature, in an article entitled, “Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex.” The article describes how Dr. Zhang, along with the University of Tokyo’s Osamu Nureki, Ph.D., and Hiroshi Nishimasu, Ph.D., overhauled the CRISPR/Cas9 system. The research team based their work on their analysis (published earlier this year) of the structure formed when Cas9 binds to the guide RNA and its target DNA. Specifically, the team used the structure’s 3D shape to rationally improve the system.

In previous efforts to revamp CRISPR/Cas9 for gene activation purposes, scientists had tried to attach the activation domains to either end of the Cas9 protein, with limited success. From their structural studies, the MIT team realized that two small loops of the RNA guide poke out from the Cas9 complex and could be better points of attachment because they allow the activation domains to have more flexibility in recruiting transcription machinery.

Using their revamped system, the researchers activated about a dozen genes that had proven difficult or impossible to turn on using the previous generation of Cas9 activators. Each gene showed at least a twofold boost in transcription, and for many genes, the researchers found multiple orders of magnitude increase in activation.

After investigating single-guide RNA targeting rules for effective transcriptional activation, demonstrating multiplexed activation of 10 genes simultaneously, and upregulating long intergenic noncoding RNA transcripts, the research team decided to undertake a large-scale screen. This screen was designed to identify genes that confer resistance to a melanoma drug called PLX-4720.

“We … synthesized a library consisting of 70,290 guides targeting all human RefSeq coding isoforms to screen for genes that, upon activation, confer resistance to a BRAF inhibitor,” wrote the authors of the Nature paper. “The top hits included genes previously shown to be able to confer resistance, and novel candidates were validated using individual [single-guide RNA] and complementary DNA overexpression.”

A gene signature based on the top screening hits, the authors added, correlated with a gene expression signature of BRAF inhibitor resistance in cell lines and patient-derived samples. It was also suggested that large-scale screens such as the one demonstrated in the current study could help researchers discover new cancer drugs that prevent tumors from becoming resistant.

More at –  http://www.genengnews.com/gen-news-highlights/turning-on-genes-systematically-with-crispr-cas9/81250697/

 

Susceptibility and modifier genes in Portuguese transthyretin V30M amyloid polyneuropathy: complexity in a single-gene disease
Miguel L. Soares1,2, Teresa Coelho3,6, Alda Sousa4,5, …, Maria Joa˜o Saraiva2,5 and Joel N. Buxbaum1
Human Molec Gen 2005; 14(4): 543–553   http://dx.doi.org:/10.1093/hmg/ddi051
https://www.researchgate.net/profile/Isabel_Conceicao/publication/8081351_Susceptibility_and_modifier_genes_in_Portuguese_transthyretin_V30M_amyloid_polyneuropathy_complexity_in_a_single-gene_disease/links/53e123d70cf2235f352733b3.pdf

Familial amyloid polyneuropathy type I is an autosomal dominant disorder caused by mutations in the transthyretin (TTR ) gene; however, carriers of the same mutation exhibit variability in penetrance and clinical expression. We analyzed alleles of candidate genes encoding non-fibrillar components of TTR amyloid deposits and a molecule metabolically interacting with TTR [retinol-binding protein (RBP)], for possible associations with age of disease onset and/or susceptibility in a Portuguese population sample with the TTR V30M mutation and unrelated controls. We show that the V30M carriers represent a distinct subset of the Portuguese population. Estimates of genetic distance indicated that the controls and the classical onset group were furthest apart, whereas the late-onset group appeared to differ from both. Importantly, the data also indicate that genetic interactions among the multiple loci evaluated, rather than single-locus effects, are more likely to determine differences in the age of disease onset. Multifactor dimensionality reduction indicated that the best genetic model for classical onset group versus controls involved the APCS gene, whereas for late-onset cases, one APCS variant (APCSv1) and two RBP variants (RBPv1 and RBPv2) are involved. Thus, although the TTR V30M mutation is required for the disease in Portuguese patients, different genetic factors may govern the age of onset, as well as the occurrence of anticipation.

Autosomal dominant disorders may vary in expression even within a given kindred. The basis of this variability is uncertain and can be attributed to epigenetic factors, environment or epistasis. We have studied familial amyloid polyneuropathy (FAP), an autosomal dominant disorder characterized by peripheral sensorimotor and autonomic neuropathy. It exhibits variation in cardiac, renal, gastrointestinal and ocular involvement, as well as age of onset. Over 80 missense mutations in the transthyretin gene (TTR ) result in autosomal dominant disease http://www.ibmc.up.pt/~mjsaraiv/ttrmut.html). The presence of deposits consisting entirely of wild-type TTR molecules in the hearts of 10– 25% of individuals over age 80 reveals its inherent in vivo amyloidogenic potential (1).

FAP was initially described in Portuguese (2) where, until recently, the TTR V30M has been the only pathogenic mutation associated with the disease (3,4). Later reports identified the same mutation in Swedish and Japanese families (5,6). The disorder has since been recognized in other European countries and in North American kindreds in association with V30M, as well as other mutations (7).

TTR V30M produces disease in only 5–10% of Swedish carriers of the allele (8), a much lower degree of penetrance than that seen in Portuguese (80%) (9) or in Japanese with the same mutation. The actual penetrance in Japanese carriers has not been formally established, but appears to resemble that seen in Portuguese. Portuguese and Japanese carriers show considerable variation in the age of clinical onset (10,11). In both populations, the first symptoms had originally been described as typically occurring before age 40 (so-called ‘classical’ or early-onset); however, in recent years, more individuals developing symptoms late in life have been identified (11,12). Hence, present data indicate that the distribution of the age of onset in Portuguese is continuous, but asymmetric with a mean around age 35 and a long tail into the older age group (Fig. 1) (9,13). Further, DNA testing in Portugal has identified asymptomatic carriers over age 70 belonging to a subset of very late-onset kindreds in whose descendants genetic anticipation is frequent. The molecular basis of anticipation in FAP, which is not mediated by trinucleotide repeat expansions in the TTR or any other gene (14), remains elusive.

Variation in penetrance, age of onset and clinical features are hallmarks of many autosomal dominant disorders including the human TTR amyloidoses (7). Some of these clearly reflect specific biological effects of a particular mutation or a class of mutants. However, when such phenotypic variability is seen with a single mutation in the gene encoding the same protein, it suggests an effect of modifying genetic loci and/or environmental factors contributing differentially to the course of disease. We have chosen to examine age of onset as an example of a discrete phenotypic variation in the presence of the particular autosomal dominant disease-associated mutation TTR V30M. Although the role of environmental factors cannot be excluded, the existence of modifier genes involved in TTR amyloidogenesis is an attractive hypothesis to explain the phenotypic variability in FAP. ….

ATTR (TTR amyloid), like all amyloid deposits, contains several molecular components, in addition to the quantitatively dominant fibril-forming amyloid protein, including heparan sulfate proteoglycan 2 (HSPG2 or perlecan), SAP, a plasma glycoprotein of the pentraxin family (encoded by the APCS gene) that undergoes specific calcium-dependent binding to all types of amyloid fibrils, and apolipoprotein E (ApoE), also found in all amyloid deposits (15). The ApoE4 isoform is associated with an increased frequency and earlier onset of Alzheimer’s disease (Ab), the most common form of brain amyloid, whereas the ApoE2 isoform appears to be protective (16). ApoE variants could exert a similar modulatory effect in the onset of FAP, although early studies on a limited number of patients suggested this was not the case (17).

In at least one instance of senile systemic amyloidosis, small amounts of AA-related material were found in TTR deposits (18). These could reflect either a passive co-aggregation or a contributory involvement of protein AA, encoded by the serum amyloid A (SAA ) genes and the main component of secondary (reactive) amyloid fibrils, in the formation of ATTR.

Retinol-binding protein (RBP), the serum carrier of vitamin A, circulates in plasma bound to TTR. Vitamin A-loaded RBP and L-thyroxine, the two natural ligands of TTR, can act alone or synergistically to inhibit the rate and extent of TTR fibrillogenesis in vitro, suggesting that RBP may influence the course of FAP pathology in vivo (19). We have analyzed coding and non-coding sequence polymorphisms in the RBP4 (serum RBP, 10q24), HSPG2 (1p36.1), APCS (1q22), APOE (19q13.2), SAA1 and SAA2 (11p15.1) genes with the goal of identifying chromosomes carrying common and functionally significant variants. At the time these studies were performed, the full human genome sequence was not completed and systematic singlenucleotide polymorphism (SNP) analyses were not available for any of the suspected candidate genes. We identified new SNPs in APCS and RBP4 and utilized polymorphisms in SAA, HSPG2 and APOE that had already been characterized and shown to have potential pathophysiologic significance in other disorders (16,20–22). The genotyping data were analyzed for association with the presence of the V30M amyloidogenic allele (FAP patients versus controls) and with the age of onset (classical- versus late-onset patients). Multilocus analyses were also performed to examine the effects of simultaneous contributions of the six loci for determining the onset of the first symptoms.  …..

The potential for different underlying models for classical and late onset is supported by the MDR analysis, which produces two distinct models when comparing each class with the controls. One could view the two onset classes as unique diseases. If this is the case, then the failure to detect a single predictive genetic model is consistent with two related, but different, diseases. This is exactly what would be expected in such a case of genetic heterogeneity (28). Using this approach, a major gene effect can be viewed as a necessary, but not sufficient, condition to explain the course of the disease. Analyzing the cases but omitting from the analysis of phenotype the necessary allele, in this case TTR V30M, can then reveal a variety of important modifiers that are distinct between the phenotypes.

The significant comparisons obtained in our study cohort indicate that the combined effects mainly result from two and three-locus interactions involving all loci except SAA1 and SAA2 for susceptibility to disease. A considerable number of four-site combinations modulate the age of onset with SAA1 appearing in a majority of significant combinations in late-onset disease, perhaps indicating a greater role of the SAA variants in the age of onset of FAP.

The correlation between genotype and phenotype in socalled simple Mendelian disorders is often incomplete, as only a subset of all mutations can reliably predict specific phenotypes (34). This is because non-allelic genetic variations and/or environmental influences underlie these disorders whose phenotypes behave as complex traits. A few examples include the identification of the role of homozygozity for the SAA1.1 allele in conferring the genetic susceptibility to renal amyloidosis in FMF (20) and the association of an insertion/deletion polymorphism in the ACE gene with disease severity in familial hypertrophic cardiomyopathy (35). In these disorders, the phenotypes arise from mutations in MEFV and b-MHC, but are modulated by independently inherited genetic variation. In this report, we show that interactions among multiple genes, whose products are confirmed or putative constituents of ATTR deposits, or metabolically interact with TTR, modulate the onset of the first symptoms and predispose individuals to disease in the presence of the V30M mutation in TTR. The exact nature of the effects identified here requires further study with potential application in the development of genetic screening with prognostic value pertaining to the onset of disease in the TTR V30M carriers.

If the effects of additional single or interacting genes dictate the heterogeneity of phenotype, as reflected in variability of onset and clinical expression (with the same TTR mutation), the products encoded by alleles at such loci could contribute to the process of wild-type TTR deposition in elderly individuals without a mutation (senile systemic amyloidosis), a phenomenon not readily recognized as having a genetic basis because of the insensitivity of family history in the elderly.

 

Safety and Efficacy of RNAi Therapy for Transthyretin Amyloidosis

Coelho T, Adams D, Silva A, et al.
N Engl J Med 2013;369:819-29.    http://dx.doi.org:/10.1056/NEJMoa1208760

Transthyretin amyloidosis is caused by the deposition of hepatocyte-derived transthyretin amyloid in peripheral nerves and the heart. A therapeutic approach mediated by RNA interference (RNAi) could reduce the production of transthyretin.

Methods We identified a potent antitransthyretin small interfering RNA, which was encapsulated in two distinct first- and second-generation formulations of lipid nanoparticles, generating ALN-TTR01 and ALN-TTR02, respectively. Each formulation was studied in a single-dose, placebo-controlled phase 1 trial to assess safety and effect on transthyretin levels. We first evaluated ALN-TTR01 (at doses of 0.01 to 1.0 mg per kilogram of body weight) in 32 patients with transthyretin amyloidosis and then evaluated ALN-TTR02 (at doses of 0.01 to 0.5 mg per kilogram) in 17 healthy volunteers.

Results Rapid, dose-dependent, and durable lowering of transthyretin levels was observed in the two trials. At a dose of 1.0 mg per kilogram, ALN-TTR01 suppressed transthyretin, with a mean reduction at day 7 of 38%, as compared with placebo (P=0.01); levels of mutant and nonmutant forms of transthyretin were lowered to a similar extent. For ALN-TTR02, the mean reductions in transthyretin levels at doses of 0.15 to 0.3 mg per kilogram ranged from 82.3 to 86.8%, with reductions of 56.6 to 67.1% at 28 days (P<0.001 for all comparisons). These reductions were shown to be RNAi mediated. Mild-to-moderate infusion-related reactions occurred in 20.8% and 7.7% of participants receiving ALN-TTR01 and ALN-TTR02, respectively.

ALN-TTR01 and ALN-TTR02 suppressed the production of both mutant and nonmutant forms of transthyretin, establishing proof of concept for RNAi therapy targeting messenger RNA transcribed from a disease-causing gene.

 

Alnylam May Seek Approval for TTR Amyloidosis Rx in 2017 as Other Programs Advance


https://www.genomeweb.com/rnai/alnylam-may-seek-approval-ttr-amyloidosis-rx-2017-other-programs-advance

Officials from Alnylam Pharmaceuticals last week provided updates on the two drug candidates from the company’s flagship transthyretin-mediated amyloidosis program, stating that the intravenously delivered agent patisiran is proceeding toward a possible market approval in three years, while a subcutaneously administered version called ALN-TTRsc is poised to enter Phase III testing before the end of the year.

Meanwhile, Alnylam is set to advance a handful of preclinical therapies into human studies in short order, including ones for complement-mediated diseases, hypercholesterolemia, and porphyria.

The officials made their comments during a conference call held to discuss Alnylam’s second-quarter financial results.

ATTR is caused by a mutation in the TTR gene, which normally produces a protein that acts as a carrier for retinol binding protein and is characterized by the accumulation of amyloid deposits in various tissues. Alnylam’s drugs are designed to silence both the mutant and wild-type forms of TTR.

Patisiran, which is delivered using lipid nanoparticles developed by Tekmira Pharmaceuticals, is currently in a Phase III study in patients with a form of ATTR called familial amyloid polyneuropathy (FAP) affecting the peripheral nervous system. Running at over 20 sites in nine countries, that study is set to enroll up to 200 patients and compare treatment to placebo based on improvements in neuropathy symptoms.

According to Alnylam Chief Medical Officer Akshay Vaishnaw, Alnylam expects to have final data from the study in two to three years, which would put patisiran on track for a new drug application filing in 2017.

Meanwhile, ALN-TTRsc, which is under development for a version of ATTR that affects cardiac tissue called familial amyloidotic cardiomyopathy (FAC) and uses Alnylam’s proprietary GalNAc conjugate delivery technology, is set to enter Phase III by year-end as Alnylam holds “active discussions” with US and European regulators on the design of that study, CEO John Maraganore noted during the call.

In the interim, Alnylam continues to enroll patients in a pilot Phase II study of ALN-TTRsc, which is designed to test the drug’s efficacy for FAC or senile systemic amyloidosis (SSA), a condition caused by the idiopathic accumulation of wild-type TTR protein in the heart.

Based on “encouraging” data thus far, Vaishnaw said that Alnylam has upped the expected enrollment in this study to 25 patients from 15. Available data from the trial is slated for release in November, he noted, stressing that “any clinical endpoint result needs to be considered exploratory given the small sample size and the very limited duration of treatment of only six weeks” in the trial.

Vaishnaw added that an open-label extension (OLE) study for patients in the ALN-TTRsc study will kick off in the coming weeks, allowing the company to gather long-term dosing tolerability and clinical activity data on the drug.

Enrollment in an OLE study of patisiran has been completed with 27 patients, he said, and, “as of today, with up to nine months of therapy … there have been no study drug discontinuations.” Clinical endpoint data from approximately 20 patients in this study will be presented at the American Neurological Association meeting in October.

As part of its ATTR efforts, Alnylam has also been conducting natural history of disease studies in both FAP and FAC patients. Data from the 283-patient FAP study was presented earlier this year and showed a rapid progression in neuropathy impairment scores and a high correlation of this measurement with disease severity.

During last week’s conference call, Vaishnaw said that clinical endpoint and biomarker data on about 400 patients with either FAC or SSA have already been collected in a nature history study on cardiac ATTR. Maraganore said that these findings would likely be released sometime next year.

Alnylam Presents New Phase II, Preclinical Data from TTR Amyloidosis Programs
https://www.genomeweb.com/rnai/alnylam-presents-new-phase-ii-preclinical-data-ttr-amyloidosis-programs

 

Amyloid disease drug approved

Nature Biotechnology 2012; (3http://dx.doi.org:/10.1038/nbt0212-121b

The first medication for a rare and often fatal protein misfolding disorder has been approved in Europe. On November 16, the E gave a green light to Pfizer’s Vyndaqel (tafamidis) for treating transthyretin amyloidosis in adult patients with stage 1 polyneuropathy symptoms. [Jeffery Kelly, La Jolla]

 

Safety and Efficacy of RNAi Therapy for Transthyretin …

http://www.nejm.org/…/NEJMoa1208760?&#8230;

The New England Journal of Medicine

Aug 29, 2013 – Transthyretin amyloidosis is caused by the deposition of hepatocyte-derived transthyretin amyloid in peripheral nerves and the heart.

 

Alnylam’s RNAi therapy targets amyloid disease

Ken Garber
Nature Biotechnology 2015; 33(577)    http://dx.doi.org:/10.1038/nbt0615-577a

RNA interference’s silencing of target genes could result in potent therapeutics.

http://www.nature.com/nbt/journal/v33/n6/images/nbt0615-577a-I1.jpg

The most clinically advanced RNA interference (RNAi) therapeutic achieved a milestone in April when Alnylam Pharmaceuticals in Cambridge, Massachusetts, reported positive results for patisiran, a small interfering RNA (siRNA) oligonucleotide targeting transthyretin for treating familial amyloidotic polyneuropathy (FAP).  …

  1. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases

Nature Biotechnology 11 April 2016

  1. CRISPR-Cas systems for editing, regulating and targeting genomes

Nature Biotechnology 02 March 2014

  1. Near-optimal probabilistic RNA-seq quantification

Nature Biotechnology 04 April 2016

 

Translational Neuroscience: Toward New Therapies

https://books.google.com/books?isbn=0262029863

Karoly Nikolich, ‎Steven E. Hyman – 2015 – ‎Medical

Tafamidis for Transthyretin Familial Amyloid Polyneuropathy: A Randomized, Controlled Trial. … Multiplex Genome Engineering Using CRISPR/Cas Systems.

 

Is CRISPR a Solution to Familial Amyloid Polyneuropathy?

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

Originally published as

https://pharmaceuticalintelligence.com/2016/04/13/is-crispr-a-solution-to-familial-amyloid-polyneuropathy/

 

http://scholar.aci.info/view/1492518a054469f0388/15411079e5a00014c3d

FAP is characterized by the systemic deposition of amyloidogenic variants of the transthyretin protein, especially in the peripheral nervous system, causing a progressive sensory and motor polyneuropathy.

FAP is caused by a mutation of the TTR gene, located on human chromosome 18q12.1-11.2.[5] A replacement of valine by methionine at position 30 (TTR V30M) is the mutation most commonly found in FAP.[1] The variant TTR is mostly produced by the liver.[citation needed] The transthyretin protein is a tetramer.    ….

 

 

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Fat Cells Reprogrammed to Make Insulin

Curator: Larry H. Bernstein, MD, FCAP

 

A New Use for Love Handles, Insulin-Producing Beta Cells

http://www.genengnews.com/gen-news-highlights/a-new-use-for-love-handles-insulin-producing-beta-cells/81252612/

http://www.genengnews.com/Media/images/GENHighlight/112856_web9772135189.jpg

 

Scientists at the Swiss Federal Institute of Technology (ETH) in Zurich have found an exciting new use for the cells that reside in the undesirable flabby tissue—creating pancreatic beta cells. The ETH researchers extracted stem cells from a 50-year-old test subject’s fatty tissue and reprogrammed them into mature, insulin-producing beta cells.

The findings from this study were published recently in Nature Communications in an article entitled “A Programmable Synthetic Lineage-Control Network That Differentiates Human IPSCs into Glucose-Sensitive Insulin-Secreting Beta-Like Cells.”

The investigators added a highly complex synthetic network of genes to the stem cells to recreate precisely the key growth factors involved in this maturation process. Central to the process were the growth factors Ngn3, Pdx1, and MafA; the researchers found that concentrations of these factors change during the differentiation process.

For instance, MafA is not present at the start of maturation. Only on day 4, in the final maturation step, does it appear, its concentration rising steeply and then remaining at a high level. The changes in the concentrations of Ngn3 and Pdx1, however, are very complex: while the concentration of Ngn3 rises and then falls again, the level of Pdx1 rises at the beginning and toward the end of maturation.

Senior study author Martin Fussenegger, Ph.D., professor of biotechnology and bioengineering at ETH Zurich’s department of biosystems science and engineering stressed that it was essential to reproduce these natural processes as closely as possible to produce functioning beta cells, stating that “the timing and the quantities of these growth factors are extremely important.”

The ETH researchers believe that their work is a real breakthrough, in that a synthetic gene network has been used successfully to achieve genetic reprogramming that delivers beta cells. Until now, scientists have controlled such stem cell differentiation processes by adding various chemicals and proteins exogenously.

“It’s not only really hard to add just the right quantities of these components at just the right time, but it’s also inefficient and impossible to scale up,” Dr. Fussenegger noted.

While the beta cells not only looked very similar to their natural counterparts—containing dark spots known as granules that store insulin—the artificial beta cells also functioned in a very similar manner. However, the researchers admit that more work needs to be done to increase the insulin output.

“At the present time, the quantities of insulin they secrete are not as great as with natural beta cells,” Dr. Fussenegger stated. Yet, the key point is that the researchers have for the first time succeeded in reproducing the entire natural process chain, from stem cell to differentiated beta cell.

In future, the ETH scientists’ novel technique might make it possible to implant new functional beta cells in diabetes sufferers that are made from their adipose tissue. While beta cells have been transplanted in the past, this has always required subsequent suppression of the recipient’s immune system—as with any transplant of donor organs or tissue.

“With our beta cells, there would likely be no need for this action since we can make them using endogenous cell material taken from the patient’s own body,” Dr. Fussenegger said. “This is why our work is of such interest in the treatment of diabetes.”

A programmable synthetic lineage-control network that differentiates human IPSCs into glucose-sensitive insulin-secreting beta-like cells

Pratik SaxenaBoon Chin HengPeng BaiMarc FolcherHenryk Zulewski & Martin Fussenegger
Nature Communications7,Article number:11247
         doi:10.1038/ncomms11247

Synthetic biology has advanced the design of standardized transcription control devices that programme cellular behaviour. By coupling synthetic signalling cascade- and transcription factor-based gene switches with reverse and differential sensitivity to the licensed food additive vanillic acid, we designed a synthetic lineage-control network combining vanillic acid-triggered mutually exclusive expression switches for the transcription factors Ngn3 (neurogenin 3; OFF-ON-OFF) and Pdx1 (pancreatic and duodenal homeobox 1; ON-OFF-ON) with the concomitant induction of MafA (V-maf musculoaponeurotic fibrosarcoma oncogene homologue A; OFF-ON). This designer network consisting of different network topologies orchestrating the timely control of transgenic and genomic Ngn3, Pdx1 and MafA variants is able to programme human induced pluripotent stem cells (hIPSCs)-derived pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells, whose glucose-stimulated insulin-release dynamics are comparable to human pancreatic islets. Synthetic lineage-control networks may provide the missing link to genetically programme somatic cells into autologous cell phenotypes for regenerative medicine.

Cell-fate decisions during development are regulated by various mechanisms, including morphogen gradients, regulated activation and silencing of key transcription factors, microRNAs, epigenetic modification and lateral inhibition. The latter implies that the decision of one cell to adopt a specific phenotype is associated with the inhibition of neighbouring cells to enter the same developmental path. In mammals, insights into the role of key transcription factors that control development of highly specialized organs like the pancreas were derived from experiments in mice, especially various genetically modified animals1, 2, 3, 4. Normal development of the pancreas requires the activation of pancreatic duodenal homeobox protein (Pdx1) in pre-patterned cells of the endoderm. Inactivating mutations of Pdx1 are associated with pancreas agenesis in mouse and humans5, 6. A similar cell fate decision occurs later with the activation of Ngn3 that is required for the development of all endocrine cells in the pancreas7. Absence of Ngn3 is associated with the loss of pancreatic endocrine cells, whereas the activation of Ngn3 not only allows the differentiation of endocrine cells but also induces lateral inhibition of neighbouring cells—via Delta-Notch pathway—to enter the same pancreatic endocrine cell fate8. This Ngn3-mediated cell-switch occurs at a specific time point and for a short period of time in mice9. Thereafter, it is silenced and becomes almost undetectable in postnatal pancreatic islets. Conversely, Pdx1-positive Ngn3-positive cells reduce Pdx1 expression, as Ngn3-positive cells are Pdx1 negative10. They re-express Pdx1, however, as they go on their path towards glucose-sensitive insulin-secreting cells with parallel induction of MafA that is required for proper differentiation and maturation of pancreatic beta cells11. Data supporting these expression dynamics are derived from mice experiments1, 11, 12. A synthetic gene-switch governing cell fate decision in human induced pluripotent stem cells (hIPSCs) could facilitate the differentiation of glucose-sensitive insulin-secreting cells.

In recent years, synthetic biology has significantly advanced the rational design of synthetic gene networks that can interface with host metabolism, correct physiological disturbances13 and provide treatment strategies for a variety of metabolic disorders, including gouty arthritis14, obesity15 and type-2 diabetes16. Currently, synthetic biology principles may provide the componentry and gene network topologies for the assembly of synthetic lineage-control networks that can programme cell-fate decisions and provide targeted differentiation of stem cells into terminally differentiated somatic cells. Synthetic lineage-control networks may therefore provide the missing link between human pluripotent stem cells17 and their true impact on regenerative medicine18, 19, 20. The use of autologous stem cells in regenerative medicine holds great promise for curing many diseases, including type-1 diabetes mellitus (T1DM), which is characterized by the autoimmune destruction of insulin-producing pancreatic beta cells, thus making patients dependent on exogenous insulin to control their blood glucose21, 22. Although insulin therapy has changed the prospects and survival of T1DM patients, these patients still suffer from diabetic complications arising from the lack of physiological insulin secretion and excessive glucose levels23. The replacement of the pancreatic beta cells either by pancreas transplantation or by transplantation of pancreatic islets has been shown to normalize blood glucose and even improve existing complications of diabetes24. However, insulin independence 5 years after islet transplantation can only be achieved in up to 55% of the patients even when using the latest generation of immune suppression strategies25, 26. Transplantation of human islets or the entire pancreas has allowed T1DM patients to become somewhat insulin independent, which provides a proof-of-concept for beta-cell replacement therapies27, 28. However, because of the shortage of donor pancreases and islets, as well as the significant risk associated with transplantation and life-long immunosuppression, the rational differentiation of stem cells into functional beta-cells remains an attractive alternative29, 30. Nevertheless, a definitive cure for T1DM should address both the beta-cell deficit and the autoimmune response to cells that express insulin. Any beta-cell mimetic should be able to store large amounts of insulin and secrete it on demand, as in response to glucose stimulation29, 31. The most effective protocols for the in vitro generation of bonafide insulin-secreting beta-like cells that are suitable for transplantation have been the result of sophisticated trial-and-error studies elaborating timely addition of complex growth factor and small-molecule compound cocktails to human pancreatic progenitor cells32, 33, 34. The differentiation of pancreatic progenitor cells to beta-like cells is the most challenging part as current protocols provide inconsistent results and limited success in programming pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells35, 36, 37. One of the reasons for these observations could be the heterogeneity in endocrine differentiation and maturation towards a beta cell phenotype. Here we show that a synthetic lineage-control network programming the dynamic expression of the transcription factors Ngn3, Pdx1 and MafA enables the differentiation of hIPSC-derived pancreatic progenitor cells to glucose-sensitive insulin-secreting beta-like cells (Supplementary Fig. 1).

 

Vanillic acid-programmable positive band-pass filter

The differentiation pathway from pancreatic progenitor cells to glucose-sensitive insulin-secreting pancreatic beta-cells combines the transient mutually exclusive expression switches of Ngn3 (OFF-ON-OFF) and Pdx1 (ON-OFF-ON) with the concomitant induction of MafA (OFF-ON) expression10,11. Since independent control of the pancreatic transcription factors Ngn3, Pdx1 and MafA by different antibiotic transgene control systems responsive to tetracycline, erythromycin and pristinamycin did not result in the desired differential control dynamics (Supplementary Fig. 2), we have designed a vanillic acid-programmable synthetic lineage-control network that programmes hIPSC-derived pancreatic progenitor cells to specifically differentiate into glucose-sensitive insulin-secreting beta-like cells in a seamless and self-sufficient manner. The timely coordination of mutually exclusive Ngn3 and Pdx1 expression with MafA induction requires the trigger-controlled execution of a complex genetic programme that orchestrates two overlapping antagonistic band-pass filter expression profiles (OFF-ON-OFF and ON-OFF-ON), a positive band-pass filter for Ngn3 (OFF-ON-OFF) and a negative band-pass filter, also known as band-stop filter, for Pdx1 (ON-OFF-ON), the ramp-up expression phase of which is linked to a graded induction of MafA (OFF-ON).

The core of the synthetic lineage-control network consists of two transgene control devices that are sensitive to the food component and licensed food additive vanillic acid. These devices are a synthetic vanillic acid-inducible (ON-type) signalling cascade that is gradually induced by increasing the vanillic acid concentration and a vanillic acid-repressible (OFF-type) gene switch that is repressed in a vanillic acid dose-dependent manner (Fig. 1a,b). The designer cascade consists of the vanillic acid-sensitive mammalian olfactory receptor MOR9-1, which sequentially activates the G protein Sα (GSα) and adenylyl cyclase to produce a cyclic AMP (cAMP) second messenger surge38 that is rewired via the cAMP-responsive protein kinase A-mediated phospho-activation of the cAMP-response element-binding protein 1 (CREB1) to the induction of synthetic promoters (PCRE) containing CREB1-specific cAMP response elements (CRE; Fig. 1a). The co-transfection of pCI-MOR9-1 (PhCMV-MOR9-1-pASV40) and pCK53 (PCRE-SEAP-pASV40) into human mesenchymal stem cells (hMSC-TERT) confirmed the vanillic acid-adjustable secreted alkaline phosphatase (SEAP) induction of the designer cascade (>10nM vanillic acid; Fig. 1a). The vanillic acid-repressible gene switch consists of the vanillic acid-dependent transactivator (VanA1), which binds and activates vanillic acid-responsive promoters (for example, P1VanO2) at low and medium vanillic acid levels (<2μM). At high vanillic acid concentrations (>2μM), VanA1 dissociates from P1VanO2, which results in the dose-dependent repression of transgene expression39 (Fig. 1b). The co-transfection of pMG250 (PSV40-VanA1-pASV40) and pMG252 (P1VanO2-SEAP-pASV40) into hMSC-TERT corroborated the fine-tuning of the vanillic acid-repressible SEAP expression (Fig. 1b).

Figure 1: Design of a vanillic acid-responsive positive band-pass filter providing an OFF-ON-OFF expression profile.

Design of a vanillic acid-responsive positive band-pass filter providing an OFF-ON-OFF expression profile.

http://www.nature.com/ncomms/2016/160411/ncomms11247/images_article/ncomms11247-f1.jpg

a) Vanillic acid-inducible transgene expression. The constitutively expressed vanillic acid-sensitive olfactory G protein-coupled receptor MOR9-1 (pCI-MOR9-1; PhCMV-MOR9-1-pA) senses extracellular vanillic acid levels and triggers G protein (Gs)-mediated activation of the membrane-bound adenylyl cyclase (AC) that converts ATP into cyclic AMP (cAMP). The resulting intracellular cAMP surge activates PKA (protein kinase A), whose catalytic subunits translocate into the nucleus to phosphorylate cAMP response element-binding protein 1 (CREB1). Activated CREB1 binds to synthetic promoters (PCRE) containing cAMP-response elements (CRE) and induces PCRE-driven expression of human placental secreted alkaline phosphatase (SEAP; pCK53, PCRE-SEAP-pA). Co-transfection of pCI-MOR9-1 and pCK53 into human mesenchymal stem cells (hMSC-TERT) grown for 48h in the presence of increasing vanillic acid concentrations results in a dose-inducible SEAP expression profile. (b) Vanillic acid-repressible transgene expression. The constitutively expressed, vanillic acid-dependent transactivator VanA1(pMG250, PSV40-VanA1-pA, VanA1, VanR-VP16) binds and activates the chimeric promoter P1VanO2 (pMG252, P1VanO2-SEAP-pA) in the absence of vanillic acid. In the presence of increasing vanillic acid concentrations, VanA1 is released from P1VanO2, and transgene expression is shut down. Co-transfection of pMG250 and pMG252 into hMSC-TERT grown for 48h in the presence of increasing vanillic acid concentrations results in a dose-repressible SEAP expression profile. (c) Positive band-pass expression filter. Serial interconnection of the synthetic vanillic acid-inducible signalling cascade (a) with the vanillic acid-repressible transcription factor-based gene switch (b) by PCRE-mediated expression of VanA1 (pSP1, PCRE-VanA1-pA) results in a two-level feed-forward cascade. Owing to the opposing responsiveness and differential sensitivity to vanillic acid, this synthetic gene network programmes SEAP expression with a positive band-pass filter profile (OFF-ON-OFF) as vanillic acid levels are increased. Medium vanillic acid levels activate MOR9-1, which induces PCRE-driven VanA1 expression. VanA1remains active and triggers P1VanO2-mediated SEAP expression in feed-forward manner, which increases to maximum levels. At high vanillic acid concentrations, MOR9-1 maintains PCRE-driven VanA1 expression, but the transactivator dissociates from P1VanO2, which shuts SEAP expression down. Co-transfection of pCI-MOR9-1, pSP1 and pMG252 into hMSC-TERT grown for 48h in the presence of increasing vanillic acid concentrations programmes SEAP expression with a positive band-pass profile (OFF-ON-OFF). Data are the means±s.d. of triplicate experiments (n=9).

The opposing responsiveness and differential sensitivity of the control devices to vanillic acid are essential to programme band-pass filter expression profiles. Upon daisy-chaining the designer cascade (pCI-MOR9-1; PhCMV-MOR9-1-pASV40; pSP1, PCRE-VanA1-pASV40) and the gene switch (pSP1, PCRE-VanA1-pASV40; pMG252, P1VanO2-SEAP-pASV40) in the same cell, the network executes a band-pass filter SEAP expression profile when exposed to increasing concentrations of vanillic acid (Fig. 1c). Medium vanillic acid levels (10nM to 2μM) activate MOR9-1, which induces PCRE-driven VanA1 expression. VanA1 remains active within this concentration range and, in a feed-forward amplifier manner, triggers P1VanO2-mediated SEAP expression, which gradually increases to maximum levels (Fig. 1c). At high vanillic acid concentrations (2μM to 400μM), MOR9-1 maintains PCRE-driven VanA1 expression, but the transactivator is inactivated and dissociates from P1VanO2, which results in the gradual shutdown of SEAP expression (Fig. 1c).

Vanillic acid-programmable lineage-control network

For the design of the vanillic acid-programmable synthetic lineage-control network, constitutive MOR9-1 expression and PCRE-driven VanA1 expression were combined with pSP12 (pASV40-Ngn3cm←P3VanO2right arrowmFT-miR30Pdx1g-shRNA-pASV40) for endocrine specification and pSP17(PCREm-Pdx1cm-2A-MafAcm-pASV40) for maturation of developing beta-cells (Fig. 2a,b). ThepSP12-encoded expression unit enables the VanA1-controlled induction of the optimized bidirectional vanillic acid-responsive promoter (P3VanO2) that drives expression of a codon-modified Ngn3cm, the nucleic acid sequence of which is distinct from its genomic counterpart (Ngn3g) to allow for quantitative reverse transcription–PCR (qRT–PCR)-based discrimination. In the opposite direction, P3VanO2 transcribes miR30Pdx1g-shRNA, which exclusively targets genomicPdx1 (Pdx1g) transcripts for RNA interference-based destruction and is linked to the production of a blue-to-red medium fluorescent timer40 (mFT) for precise visualization of the unit’s expression dynamics in situ. pSP17 contains a dicistronic expression unit in which the modified high-tightness and lower-sensitivity PCREm promoter (see below) drives co-cistronic expression of Pdx1cm andMafAcm, which are codon-modified versions producing native transcription factors that specifically differ from their genomic counterparts (Pdx1g, MafAg) in their nucleic acid sequence. After individual validation of the vanillic acid-controlled expression and functionality of all network components (Supplementary Figs 2–9), the lineage-control network was ready to be transfected into hIPSC-derived pancreatic progenitor cells. These cells are characterized by high expression of Pdx1g and Nkx6.1 levels and the absence of Ngn3g and MafAg production32, 33, 34 (day 0:Supplementary Figs 10–16).

 

Figure 2: Synthetic lineage-control network programming differential expression dynamics of pancreatic transcription factors.

Synthetic lineage-control network programming differential expression dynamics of pancreatic transcription factors.

 

http://www.nature.com/ncomms/2016/160411/ncomms11247/images/ncomms11247-f2.jpg

(a) Schematic of the synthetic lineage-control network. The constitutively expressed, vanillic acid-sensitive olfactory G protein-coupled receptor MOR9-1 (pCI-MOR9-1; PhCMV-MOR9-1-pA) senses extracellular vanillic acid levels and triggers a synthetic signalling cascade, inducing PCRE-driven expression of the transcription factor VanA1 (pSP1, PCRE-VanA1-pA). At medium vanillic acid concentrations (purple arrows), VanA1 binds and activates the bidirectional vanillic acid-responsive promoter P3VanO2 (pSP12, pA-Ngn3cm←P3VanO2right arrowmFT-miR30Pdx1g-shRNA-pA), which drives the induction of codon-modified Neurogenin 3 (Ngn3cm) as well as the coexpression of both the blue-to-red medium fluorescent timer (mFT) for precise visualization of the unit’s expression dynamics and miR30pdx1g-shRNA (a small hairpin RNA programming the exclusive destruction of genomic pancreatic and duodenal homeobox 1 (Pdx1g) transcripts). Consequently, Ngn3cm levels switch from low to high (OFF-to-ON), and Pdx1g levels toggle from high to low (ON-to-OFF). In addition, Ngn3cm triggers the transcription of Ngn3g from its genomic promoter, which initiates a positive-feedback loop. At high vanillic acid levels (orange arrows), VanA1 is inactivated, and both Ngn3cm and miR30pdx1g-shRNA are shut down. At the same time, the MOR9-1-driven signalling cascade induces the modified high-tightness and lower-sensitivity PCREm promoter that drives the co-cistronic expression of the codon-modified variants of Pdx1 (Pdx1cm) and V-maf musculoaponeurotic fibrosarcoma oncogene homologue A (MafAcm; pSP17, PCREm-Pdx1cm-2A-MafAcm-pA). Consequently, Pdx1cm and MafAcm become fully induced. As Pdx1cm expression ramps up, it initiates a positive-feedback loop by inducing the genomic counterparts Pdx1g and MafAg. Importantly, Pdx1cm levels are not affected by miR30Pdx1g-shRNA because the latter is specific for genomic Pdx1g transcripts and because the positive feedback loop-mediated amplification of Pdx1gexpression becomes active only after the shutdown of miR30Pdx1g-shRNA. Overall, the synthetic lineage-control network provides vanillic acid-programmable, transient, mutually exclusive expression switches for Ngn3 (OFF-ON-OFF) and Pdx1 (ON-OFF-ON) as well as the concomitant induction of MafA (OFF-ON) expression, which can be followed in real time (Supplementary Movies 1 and 2). (b) Schematic illustrating the individual differentiation steps from human IPSCs towards beta-like cells. The colours match the cell phenotypes reached during the individual differentiation stages programmed by the lineage-control network shown in a.

Following the co-transfection of pCI-MOR9-1 (PhCMV-MOR9-1-pASV40), pSP1 (PCRE-VanA1-pASV40), pSP12 (pASV40-Ngn3cm←P3VanO2right arrowmFT-miR30Pdx1g-shRNA-pASV40) and pSP17(PCREm-Pdx1cm-2A-MafAcm-pASV40) into hIPSC-derived pancreatic progenitor cells, the synthetic lineage-control network should override random endogenous differentiation activities and execute the pancreatic beta-cell-specific differentiation programme in a vanillic acid remote-controlled manner. To confirm that the lineage-control network operates as programmed, we cultivated network-containing and pEGFP-N1-transfected (negative-control) cells for 4 days at medium (2μM) and then 7 days at high (400μM) vanillic acid concentrations and profiled the differential expression dynamics of all of the network components and their genomic counterparts as well as the interrelated transcription factors and hormones in both whole populations and individual cells at days 0, 4, 11 and 14 (Figs 2 and 3 and Supplementary Figs 11–17).

 

Figure 3: Dynamics of the lineage-control network.

Dynamics of the lineage-control network.

http://www.nature.com/ncomms/2016/160411/ncomms11247/images/ncomms11247-f3.jpg

(a,b) Quantitative RT–PCR-based expression profiling of the pancreatic transcription factors Ngn3cm/g, Pdx1cm/g and MafAcm/g in hIPSC-derived pancreatic progenitor cells containing the synthetic lineage-control network at days 4 and 11. Data are the means±s.d. of triplicate experiments (n=9). (cg) Immunocytochemistry of pancreatic transcription factors Ngn3cm/g, Pdx1cm/g and MafAcm/g in hIPSC-derived pancreatic progenitor cells containing the synthetic lineage-control network at days 4 and 11. hIPSC-derived pancreatic progenitor cells were co-transfected with the lineage-control vectors pCI-MOR9-1 (PhCMV-MOR9-1-pA), pSP1 (PCRE-VanA1-pA), pSP12 (pA-Ngn3cm←P3VanO2right arrowmFT-miR30Pdx1g-shRNA-pA) and pSP17 (PCREm-Pdx1cm-2A-MafAcm) and immunocytochemically stained for (c) VanA1 and Pdx1 (day 4), (d) VanA1 and Ngn3 (day 4), (e) VanA1 and Pdx1 (day 11), (f) MafA and Pdx1 (day 11) as well as (g) VanA1 and insulin (C-peptide) (day 11). The cells staining positive for VanA1 are containing the lineage-control network. DAPI, 4′,6-diamidino-2-phenylindole. Scale bar, 100μm.

…….

Multicellular organisms, including humans, consist of a highly structured assembly of a multitude of specialized cell phenotypes that originate from the same zygote and have traversed a preprogrammed multifactorial developmental plan that orchestrates sequential differentiation steps with high precision in space and time19, 51. Because of the complexity of terminally differentiated cells, the function of damaged tissues can for most medical indications only be restored via the transplantation of donor material, which is in chronically short supply52.

Despite significant progress in regenerative medicine and the availability of stem cells, the design of protocols that replicate natural differentiation programmes and provide fully functional cell mimetics remains challenging29, 53. For example, efforts to generate beta-cells from human embryonic stem cells (hESCs) have led to reliable protocols involving the sequential administration of growth factors (activin A, bone morphogenetic protein 4 (BMP-4), basic fibroblast growth factor (bFGF), FGF-10, Noggin, vascular endothelial growth factor (VEGF) and Wnt3A) and small-molecule compounds (cyclopamine, forskolin, indolactam V, IDE1, IDE2, nicotinamide, retinoic acid, SB−431542 and γ-secretase inhibitor) that modulate differentiation-specific signalling pathways31, 54, 55. In vitro differentiation of hESC-derived pancreatic progenitor cells into beta-like cells is more challenging and has been achieved recently by a complex media formulation with chemicals and growth factors32, 33, 34.

hIPSCs have become a promising alternative to hESCs; however, their use remains restricted in many countries56. Most hIPSCs used for directed differentiation studies were derived from a juvenescent cell source that is expected to show a higher degree of differentiation potential compared with older donors that typically have a higher need for medical interventions37, 57, 58. We previously succeeded in producing mRNA-reprogrammed hIPSCs from adipose tissue-derived mesenchymal stem cells of a 50-year-old donor, demonstrating that the reprogramming of cells from a donor of advanced age is possible in principle59.

Recent studies applying similar hESC-based differentiation protocols to hIPSCs have produced cells that release insulin in response to high glucose32, 33, 34. This observation suggests that functional beta-like cells can eventually be derived from hIPSCs32, 33. In our hands, the growth-factor/chemical-based technique for differentiating human IPSCs resulted in beta-like cells with poor glucose responsiveness. Recent studies have revealed significant variability in the lineage specification propensity of different hIPSC lines35, 60 and substantial differences in the expression profiles of key transcription factors in hIPSC-derived beta-like cells33. Therefore, the growth-factor/chemical-based protocols may require further optimization and need to be customized for specific hIPSC lines35. Synthetic lineage-control networks providing precise dynamic control of transcription factor expression may overcome the challenges associated with the programming of beta-like cells from different hIPSC lines.

Rather than exposing hIPSCs to a refined compound cocktail that triggers the desired differentiation in a fraction of the stem cell population, we chose to design a synthetic lineage-control network to enable single input-programmable differentiation of hIPSC-derived pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells. In contrast with the use of growth-factor/chemical-based cocktails, synthetic lineage-control networks are expected to (i) be more economical because of in situ production of the required transcription factors, (ii) enable simultaneous control of ectopic and chromosomally encoded transcription factor variants, (iii) tap into endogenous pathways and not be limited to cell-surface input, (iv) display improved reversibility that is not dependent on the removal of exogenous growth factors via culture media replacement, (v) provide lateral inhibition, thereby reducing the random differentiation of neighbouring cells and (vi) enable trigger-programmable and (vii) precise differential transcription factor expression switches.

The synthetic lineage-control network that precisely replicates the endogenous relative expression dynamics of the transcription factors Pdx-1, Ngn3 and MafA required the design of a new network topology that interconnects a synthetic signalling cascade and a gene switch with differential and opposing sensitivity to the food additive vanillic acid. This differentiation device provides different band-pass filter, time-delay and feed-forward amplifier topologies that interface with endogenous positive-feedback loops to orchestrate the timely expression and repression of heterologous and chromosomally encoded Ngn3, Pdx1 and MafA variants. The temporary nature of the engineering intervention, which consists of transient transfection of the genetic lineage-control components in the absence of any selection, is expected to avoid stable modification of host chromosomes and alleviate potential safety concerns. In addition, the resulting beta-cell mass could be encapsulated inside vascularized microcontainers28, a proven containment strategy in prototypic cell-based therapies currently being tested in animal models of prominent human diseases14, 15, 16, 61, 62 as well as in human clinical trials28.

The hIPSC-derived beta-like cells resulting from this trigger-induced synthetic lineage-control network exhibited glucose-stimulated insulin-release dynamics and capacity matching the human physiological range and transcriptional profiling, flow cytometric analysis and electron microscopy corroborated the lineage-controlled stem cells reached a mature beta-cell phenotype. In principle, the combination of hIPSCs derived from the adipose tissue of a 50-year-old donor59 with a synthetic lineage-control network programming glucose-sensitive insulin-secreting beta-like cells closes the design cycle of regenerative medicine63. However, hIPSCs that are derived from T1DM patients, differentiated into beta-like cells and transplanted back into the donor would still be targeted by the immune system, as demonstrated in the transplantation of segmental pancreatic grafts from identical twins64. Therefore, any beta-cell-replacement therapy will require complementary modulation of the immune system either via drugs30, 65, engineering or cell-based approaches66, 67 or packaging inside vascularizing, semi-permeable immunoprotective microcontainers28.

Capitalizing on the design principles of synthetic biology, we have successfully constructed and validated a synthetic lineage-control network that replicates the differential expression dynamics of critical transcription factors and mimicks the native differentiation pathway to programme hIPSC-derived pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells that compare with human pancreatic islets at a high level. The design of input-triggered synthetic lineage-control networks that execute a preprogrammed sequential differentiation agenda coordinating the timely induction and repression of multiple genes could provide a new impetus for the advancement of developmental biology and regenerative medicine.

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

Adipocyte Derived Stroma Cells: Their Usage in Regenerative Medicine and Reprogramming into Pancreatic Beta-Like Cells

Curator: Evelina Cohn, Ph.D.

https://pharmaceuticalintelligence.com/2016/03/03/adipocyte-derived-stroma-cells-their-usage-in-regenerative-medicine-and-reprogramming-into-pancreatic-beta-like-cells/

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Lipids link to breast cancer

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Lipids Found Critical to Breast Cancer Cell Proliferation

http://www.genengnews.com/gen-news-highlights/lipids-found-critical-to-breast-cancer-cell-proliferation/81252572/

http://www.genengnews.com/Media/images/GENHighlight/112523_webApr6_2016_IRBBarcelona_BreastTumorsLIPD3119618425.jpg

 

Scientists in Spain report finding that breast cancer cells need to take up lipids from the extracellular environment so that they can continue to proliferate. The main protein involved in this process is LIPG, an enzyme found in the cell membrane and without which tumor cell growth is arrested. Analyses of more than 500 clinical samples from patients with various kinds of breast tumors reveal that 85% have high levels of LIPG expression.

The research (“FoxA and LIPG Endothelial Lipase Control the Uptake of Extracellular Lipids for Breast Cancer Growth”) is published in Nature Communications.

In Spain, breast cancer is the most common tumor in women and the fourth most common type in both sexes (data from the Spanish Society of Medical Oncology, 2012), registering more than 25,000 new diagnoses each year. According to figures from the World Health Organization, every year 1.38 million new cases of breast cancer are diagnosed and 458,000 people die from this disease (International Agency for Research on Cancer Globocan, 2008).

It was already known that cancer cells require extracellular glucose to grow and that they reprogram their internal machinery to produce greater amounts of lipids. The relevance of this study is that it reveals for the first time that tumor cells must import extracellular lipids to grow.

“This new knowledge related to metabolism could be the Achilles heel of breast cancer,” explains ICREA researcher and Institute for Research in Biomedicine–Barcelona group leader Roger Gomis, Ph.D., co-leader of the study together with Joan J. Guinovart, Ph.D., director of IRB Barcelona and professor at the University of Barcelona. Using animal models and cancer cell cultures, the scientists have demonstrated that blocking of LIPG activity arrests tumor growth.

“What is promising about this new therapeutic target is that LIPG function does not appear to be indispensable for life, so its inhibition may have fewer side effects than other treatments,” explains the first author of the study, Felipe Slebe, a Ph.D. Fellow at IRB Barcelona.

According to Dr. Guinovart, “because LIPG is a membrane protein, it is potentially easier to design a pharmacological agent to block its activity.”

“If a drug were found to block its activity, it could be used to develop more efficient chemotherapy treatments that are less toxic than those currently available,” adds Dr. Gomis.

The scientists are now looking into international collaborations for developing LIPG inhibitors.

FoxA and LIPG endothelial lipase control the uptake of extracellular lipids for breast cancer growth

Felipe SlebeFederico RojoMaria Vinaixa,…Joan AlbanellJoan J. Guinovart & Roger R. Gomis

Nature Communications7,Article number:11199      http://dx.doi.org:/10.1038/ncomms11199

The mechanisms that allow breast cancer (BCa) cells to metabolically sustain rapid growth are poorly understood. Here we report that BCa cells are dependent on a mechanism to supply precursors for intracellular lipid production derived from extracellular sources and that the endothelial lipase (LIPG) fulfils this function. LIPG expression allows the import of lipid precursors, thereby contributing to BCa proliferation. LIPG stands out as an essential component of the lipid metabolic adaptations that BCa cells, and not normal tissue, must undergo to support high proliferation rates. LIPG is ubiquitously and highly expressed under the control of FoxA1 or FoxA2 in all BCa subtypes. The downregulation of either LIPG or FoxA in transformed cells results in decreased proliferation and impaired synthesis of intracellular lipids.

FoxA1 and FoxA2 in BCa growth

The importance of FoxA1 in BCa cells differentiation and its contribution to controlling the expression of metabolic genes in several other tissues makes this transcription factor a highly attractive target to explain the metabolic alterations reported in BCa. For these reason, we decided to ascertain the metabolic processes controlled by FoxA1 in BCa. We first confirmed the association between high FoxA1 expression (mRNA and protein) and luminal subtype (Fig. 1a). To this end, we used two cohorts of primary breast tumours with annotated clinical features and follow-up. The MSKCC/EMC BCa data set is based on gene expression profiles from an original series of 560 cases10, whereas the Spanish BCa data set (n=439) is a tissue microarray of formalin-fixed paraffin-embedded stage I–III breast tumour specimens11 (details provided in Methods Section). High FoxA1 gene expression significantly correlated with high expression of well-established luminal markers, such as GATA3 and ESR1, in primary tumours (Supplementary Fig. 1a). Next we explored FoxA1 expression beyond the luminal subtype. Lower FoxA1 expression was observed in non-luminal tumours (Fig. 1a,b); however, a subset also expressed higher FoxA1 levels (Supplementary Fig. 1b and Supplementary Table 1). Given that FoxA2, in conjunction with FoxA1, is also involved in the regulation of several metabolic pathways, we determined the expression of this factor in BCa samples. Unfortunately, no FoxA2 probes in the Affymetrix platform used in the MSKCC/EMC data set provided a reliable interpretation. To overcome this limitation, we used tissue arrays of early BCa samples (Spanish BCa set). Histological examination of FoxA2-stained tissue microarray slides from the Spanish BCa set revealed the expression of this factor in six non-luminal samples, which were scored as FoxA1 (examples in Fig. 1b and summarized inSupplementary Table 1). Collectively, the number of FoxA+ BCa samples detected by immunohistochemistry accounted for 81.3% of all samples in the Spanish BCa set (Supplementary Table 1), which represent a significant proportion of BCa and point to the participation of FoxA in this disease, beyond to its involvement in differentiation and control of hormonal responses.

Figure 1: FoxA1 and FoxA2 in BCa growth.

http://www.nature.com/ncomms/2016/160405/ncomms11199/images_article/ncomms11199-f1.jpg

(a, top) FoxA1 mRNA expression in the MSKCC/EMC set. BCa samples were stratified in Luminal A, Luminal B, Her2, triple negative and unknown subgroups. The unknown group represents specimens that were not classified in any group. (bottom) FoxA1 protein levels by IHC staining in Luminal, Her2 and triple negative samples in the Spanish BCa set (cohort of 439 BCa patients). Data is average±s.d. (b) FoxA1 and FoxA2 IHC staining in FFPE human specimens representative of the different BCa subtypes. Six independent cases are depicted. FoxA1 and FoxA2 are expressed mainly in the nuclei of tumour cells. Scale bar, 50μm. (c) FoxA1 and FoxA2 mRNA expression analysis by qRT-PCR and protein expression by western blot in human BCa cell lines compared with HMECs. T-test was used. Data are average±s.e.m.; n= 3. Of note, MDA435 are of melanoma origin. (d) FoxA1 and FoxA2 expression in MCF7, MDA231 and their derivatives cells by qRT-PCR and western blot. FoxA1 and FoxA2 depletion was achieved with a doxycycline-inducible short hairpin vector. FoxA-depleted cells were rescued by expression of FoxA2 in MCF7 cells or FoxA1 in MDA231 cells. Cell populations were cultured in the presence or absence of doxycycline for 6 days. P value is the result of T-test. Data are average±s.e.m.;n=3. *P≤0.05, ***P≤0.001 (e, left) Schematic representation of MDA231 and MCF7 cells grown without doxycycline and inoculated in Balb/c nude mice treated with or without doxycycline to induce the expression of the indicated FoxA short hairpins. All tumour cell lines have GFP constitutive expression, and tRFP concomitantly with the short hairpin were expressed in doxycycline treated tumours. (right) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points. P value is the result of T-test. Data are average±s.e.m.; n= 5–8 tumours. *P≤0.05,**P≤0.01, ***P≤0.001. FFPE, formalin-fixed paraffin-embedded.

Next, we extended our analysis to BCa cell lines for further mechanistic studies. We compared FoxA1 and FoxA2 mRNA expression in four estrogen receptor positive (ER+) (MCF7, T47D, BT474 and ZR75) and four estrogen receptor negative (ER−) (SKBR3, MDA468, BT20 and MDA231) BCa cell lines, a cell line of melanoma origin (MDA435), and human mammary epithelial cells (HMECs). Of note, two of the BCa lines tested were HER2+ (BT474 and SKBR3) (Fig. 1c). All ER+ BCa cells (MCF7, T47D, BT474 and ZR75), the ER−/HER2+ SKBR3 and both triple negative-like MDA468 and BT20 cell lines expressed FoxA1. Interestingly, MDA231 triple negative-like cells expressed high levels of FoxA2 but not FoxA1, and the non-tumour HMECs did not express these factors (Fig. 1c). No BCa cells co-expressed these two proteins (Fig. 1c). Our results suggest that the expression of FoxA transcription factors is a common feature of breast tumours, as well as of BCa cell lines. This notion implies that FoxA factors play a major role in BCa growth, independently of luminal fate specification.

To examine the molecular basis of the contribution of FoxA1 and FoxA2 to BCa growth, we engineered constitutive GFP-luciferase-expressing MCF7 and MDA231 cells with a doxycycline-inducible short-hairpin RNA (sh-RNA) vector targeting either FoxA1 or FoxA2. Doxycycline addition to the cell culture media decreased FoxA expression in both cell lines compared with control cells (ShControl (Dox+) and Sh FoxA1 or Sh FoxA2 (Dox−))(Fig. 1d), with the concomitant expression of tRFP (Supplementary Fig. 1c). Of note, there was no gain of expression of FoxA2 in FoxA1-depleted cells or vice versa (Fig. 1d). Interestingly, cancer cell proliferation was impaired in vitroupon depletion of either FoxA1 or FoxA2 in MCF7 and MDA231 cells, respectively (Supplementary Fig. 1d,e). Similarly, when Balb/c nude mice implanted with xenograft tumours from the above described cellular populations were treated with doxycycline and the short hairpins were induced, striking differences in tumour growth were observed. FoxA1-depleted MCF7 and FoxA2-depleted MDA231 tumour growth was blunted (Fig. 1e and additional controls in Supplementary Fig. 1f. Experimental details in the Supplementary Methods Section). Collectively, these observations confirm that FoxA1 or FoxA2 expression is required for BCa growth.

Previous studies indicate that FoxA1 and FoxA2 transcriptionally regulate common genes in the liver and pancreas that are central to development and metabolism. We therefore hypothesized that crossed expression of FoxA factors could rescue tumour growth by restoring the expression of essential metabolic genes. To this end, we engineered doxycycline-driven shFoxA1 MCF7 cells to express exogenous FoxA2 and doxycycline-driven shFoxA2 MDA231 cells to express exogenous FoxA1 (Fig. 1d). Interestingly, when these BCa modified cells were implanted in Balb/c nude mice and FoxA depletion was induced with doxycycline, the sustained expression of another FoxA factor (FoxA2 in MCF7 and FoxA1 in MDA231 cells) was sufficient for tumours to continuously grow (Fig. 1e and additional controls in Supplementary Fig. 1f). Quantitative real-time PCR (qRT-PCR) analysis confirmed FoxA expression in the distinct tumour populations ex-vivo (Supplementary Fig. 1g). These results showed that retention of minimal levels of FoxA1 or FoxA2 expression is necessary for BCa cell growth.

FoxA1- and FoxA2-regulated transcripts for BCa growth

Figure 2: A genomic approach to identify FoxA1- and FoxA2-regulated transcripts in MCF7 and MDA231 cells.

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(a) FACS profiling of MCF7 and MDA231 cells derived from tumours isolated from mice on the basis of the expression of GFP+ and RFP− (control group) or GFP+ and tRFP+ (knockdown and rescue groups). (b) Representation of the transcripts up- and downregulated by FoxA in MCF7 and MDA231 cells isolated from tumours. Up- and downregulated transcripts present a Bayesian false discovery rate below 5% and fold change >2.5. (c) LIPG, Bcl2 and Cdh11OB mRNA levels of the indicated genetically modified MCF7 and MDA231 tumour xenografts analysed by qRT-PCR. P value is the result of T-test. Data are average±s.e.m.; n= 5–8 tumours. *P≤0.05, ***P≤0.001. (d) LIPG protein expression in constitutive shFoxA1 MCF7 or shFoxA2 MDA231 cells. (e) Promoter reporter assay in HEK 293 cells. Cells were transfected with LIPG promoter reporter and FoxA1 or FoxA2 expressing vectors when indicated. P value is the result of T-test. Data are average±s.e.m.; n=3. ****P≤0.0001.

LIPG expression in BCa

Next, we showed that LIPG expression in primary tumours was specific to BCa tumour cells and not to other stroma cellular entities (Fig. 3a). Subsequently, we tested LIPG expression in normal breast epithelia and interrogated 20 samples from mammoplasty reductions. Normal breast epithelial cells showed a lower expression of LIPG than cells from tumour specimens (Fig. 3b). Similar results were obtained for LIPG protein levels in a panel from BCa lines compared with HMEC cells. Of the cellular populations tested, the eight BCa cell lines expressing FoxA1 or FoxA2 had very high levels of LIPG protein compared with the melanoma MDA435 cell line and the human epithelial cell (Fig. 3c). Consistent with this observation, 83.8% of BCa samples in the Spanish tumour cohort were LIPG+ (Fig. 3d and Supplementary Table 3), and LIPG expression correlated with FoxA expression (Spearman correlation; r=0.477, P=0.000001; Fig. 3e). Further analysis showed that LIPG expression levels in primary tumours do not have the capacity to stratify patients for differential risk of overall or disease-free survival (Supplementary Fig. 2a) and are not dependent on estrogen signalling (Supplementary Fig. 2b), thus reinforcing the notion that LIPG is essential for BCa growth.

Figure 3: LIPG contributes to BCa growth.

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a) Representative LIPG IHC staining on primary BCa tissues (cohort of 439 BCa patients). LIPG is expressed in the cytoplasm of tumour cells. Faint staining is also detected in the extracellular area. Scale bar, 50μm. (b) Representative LIPG IHC staining in normal breast tissue from mammoplasty reductions. Weak LIPG expression occurs in epithelial cells from ducts and lobuli. Scale bar, 50μm. (c) LIPG protein expression in human cancer cell lines compared with HMECs. Actin was used as loading control.*Unspecific band. Of note, MDA435 are of melanoma origin. (d) LIPG protein levels by IHC staining in Luminal, Her2, and triple negative samples in the Spanish BCa set (cohort of 439 BCa patients). Data is average±s.d. (e) Spearman correlation (P=0.000001) between FoxA and LIPG IHC staining intensities in Spanish BCa set (cohort of 439 BCa patients). (f) Left panel, in vitro proliferation curves of MCF7 and MDA231 cells transduced with a control or a LIPG short hairpin. Data are average±s.e.m.; n=3. (right) LIPG protein expression in shLIPG MCF7 and shLIPG MDA231 cells. The blot shown is representative of three independent experiments. P value is the result of T-test.**P≤0.01, ***P≤0.001. (g) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points.P value is the result of T-test. Data are average±s.e.m.; n= 6–8 tumours. *P≤0.05.

LIPG is a phospholipase located in the cytosol and cellular membrane and has been shown to hydrolyse extracellular phospholipids from high-density lipoprotein that are afterwards incorporated into intracellular lipid species thus providing lipid precursors of cell metabolism17, 18. Thus we questioned whether LIPG regulates essential lipid intake in BCa and whether it is necessary for proliferation. To validate this hypothesis, we genetically downregulated the expression of this protein in MCF7 and MDA231 cells by means of sh-RNA (Fig. 3f and Supplementary Fig. 2c). LIPG depletion blunted BCa cell capacity to proliferate in vitro (Fig. 3f), as previously observed in FoxA-depleted cells (Supplementary Fig. 1d,e), and caused a reduction in invasion and self-renewal properties (Supplementary Fig. 3a–d). Similarly, LIPG-depleted cells were unable to grow tumours in vivo (Fig. 3g).

LIPG induces BCa cells lipid metabolic reprograming

Figure 4: LIPG regulates the uptake of lipids in BCa cells inducing a lipid metabolic reprograming.

LIPG regulates the uptake of lipids in BCa cells inducing a lipid metabolic reprograming.

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(a) Schematic representation of LIPG action. (b) Heat map representation of the downregulated (blue) lipids identified by MS/MS in the cell homogenates of MCF7 or MDA231 LIPG-depleted cells compared with shControl cells. Depicted lipids have a fold change >1.5 and P value<0.05 using the Welch’s t-testn=5. (c) Downregulated lipid species (previously identified in b) that are common to LIPG-depleted MCF7 and LIPG-depleted MDA231 cells. ShControl cells (red box), and shLIPG (blue box). P values are <0.05 and calculated using Welch’s t-test, n=5. Whiskers extend to a maximum of 1.5 × IQR beyond the box. (d) Heat map representation of the upregulated (red) lipids identified by MS/MS in the media of MCF7 or MDA231 LIPG-depleted cells compared with the corresponding shControl cells. Characterized lipids have a fold change >1.5 and P value<0.05 using the Welch’s t-test n=5. (e) Upregulated lipid species in the media (previously identified in d) that are common to LIPG-depleted MCF7 and LIPG-depleted MDA231 cells. ShControl cells (red box), and shLIPG cells (blue box). P values are <0.05 and calculated using Welch’s t-test, n=5. Whiskers extend to a maximum of 1.5 × IQR beyond the box. (f) Heat map representation of the MS/MS downregulated (blue) lipids in the cell media of MCF7/MDA231 LIPG-depleted or shControl cells (as described in d) compared with fresh medium (without cell incubation). Depicted lipid species have a log2 fold change>1.5 and P value<0.05 using the Welch’s t-test n=5. (g) MDA231 and MCF7 cell growth for 48h in complete medium: medium containing 10% FBS 10%); lipoprotein-free medium: medium containing 10% free lipoprotein FBS; and LPC (18:0): medium containing 10% free lipoprotein FBS and 20μM of LPC (18:0). P value is the result of T-test. Data are average±s.e.m.; n=3. **P≤0.01, ***P≤0.001, ****P≤0.0001. (h) Above, schematic representation of the experimental protocol used. (bottom) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice treated with high-fat diet (HFD) are determined at the indicated time points. P value is the result of T-test. Data are average±s.e.m.; n= 6–8 tumours. *P≤0.05, **P≤0.01. Inside graph, plasma cholesterol levels of animals treated with standard diet (SD) or HFD. P value is the result of T-test. Data are average±s.e.m.; n= 4 animals per group. **P≤0.01, ***P≤0.001.

LIPG location has been shown to be functional on the outer face of the cellular membrane (Fig. 4a)18, thus we postulated the possibility that BCa cells are dependent on LIPG function to access extracellular lipids to support their growth needs. To test this notion, we profiled the media of control and LIPG-depleted MCF7 and MDA231 cells following the same liquid chromatography-mass spectrometry-based untargeted lipidomic approach as for cell homogenates. LIPG depletion prevented the absorption of particular lipids from the media (Supplementary Fig. 4a). The structural identification of the lipids by MS/MS confirms the absence of degradation of glycerophospholipids belonging to the LPC class in both MCF7 and MDA231 cells, which is depicted by higher levels in the media of these species in LIPG-depleted when compared with control cells (Fig. 4d,e). Interestingly when we analysed the LPCs species in the media of control and LIPG-depleted cells and compared with fresh media (without cells), all LPC species from control cell media were decreased. This reduction was weaker in the media of Sh LIPG cells, indicating that LIPG-depleted cells have a defect in processing and importing of pre-existing lipid species from the medium (Fig. 4f).

Finally, we evaluated which of the commonly identified potential substrates of LIPG sustains BCa cell proliferation. Initially, we confirmed that the growth of MCF7 and MDA231 cells is impaired when grown in vitro in lipoprotein-depleted media (Fig. 4g). Next we tested the capacity of LPC (18:0) to rescue BCa cell growth in the absence of lipoproteins and confirmed that this lysophosphatidylcholine was able to restore the cells’ capacity to proliferate (Fig. 4g). In accordance, this process was dependent on LIPG expression (Fig. 4g). Similarly, LIPG-depleted cells were not able to grow in vivo in animals fed with high-fat diet (Fig. 4h) indicating that LIPG is indispensable to process the extracellular lipids and mediate their uptake by the cells, irrespectively of the concentration of lipid substrates in circulation, a phenotype also observed in FoxA-depleted cells (Fig. 4h).

LIPG activity supports BCa growth

Figure 5: LIPG activity is essential for BCa growth.

LIPG activity is essential for BCa growth.

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(a, top) Homology 3D structural model of LIPG (backbone coloured according to the QMEANlocal parameter values; red residues with low error). The heavy atoms of the three catalytic residues are shown explicitly and the residue mutated in this study is shown in green (Asp 193). (b) FoxA1, FoxA2 and LIPG protein expression in MCF7, MDA231 and their derivative cells determine by western blot. FoxA1 and FoxA2 depletion was achieved with a doxycycline-inducible short hairpin vector. FoxA-depleted cells were rescued by expression of a WT or Inactive LIPG. Cell populations were cultured in the presence or absence of doxycycline for 6 days. *blots represent different exposition times. (c) Tumour growth of the indicated cell populations inoculated in Balb/c nude mice are determined at the indicated time points. Pvalue is the result of T-test. Data are average±s.e.m.; n=5–8 tumours. *P≤0.05, **P≤0.01. (d) MDA231 and MCF7 cell growth for 48h treated with DMSO (control), FAS inhibitor (C75) and/or lipase inhibitor (Orlistat). For MDA231 cells C75 was used at a final concentration of 10μgml−1 and for MCF7 cells 8μgml−1. Orlistat was used at a final concentration of 30 or 10μgml−1 in MCF7 or MD231 respectively. Pvalue is the result of T-test. Data are average±s.e.m.; n=3.*P≤0.05, **P≤0.01, ***P≤0.001. (e) Forty-eight hours cell growth of MDA231 or MCF7 cells overexpressing exogenous WT or Inactive LIPG. Cells were treated with DMSO (control) and FAS inhibitor (C75) at a final concentration of 20μgml−1. P value is the result of T-test. Data are average±s.e.m.; n=3.***P≤0.001, ****P≤0.0001 (f) Schematic representation showing how FoxA controls LIPG and lipid metabolism to support tumour growth.

As previous reports showed that de novo lipid metabolism is necessary for BCa growth3, 22, we next questioned whether this lipid synthesis was sufficient or, instead, whether exogenous sources are also required to support BCa cell growth and proliferation, as suggested by our experimental data. To this end, we inhibited the activity of fatty acid synthase (FAS) in BCa cells by means of the chemical inhibitor C75 (ref. 23). FAS activity is crucial for de novo lipid synthesis in cancer cells3,22. To test the complementarity of both de novo and/or exogenous lipid supplies, we used a C75 concentration causing a 50% reduction in BCa cell growth in vitro 48h post incubation (Fig. 5d andSupplementary Fig. 5d). Similarly, we tested the contribution of LIPG inhibition by means of treatment with a lipase inhibitor, Orlistat21. A specific dose causing a 50% reduction in the growth of each BCa cell line was further used (Fig. 5d and Supplementary Fig. 5d). Interestingly, concomitant treatment with FAS and LIPG inhibitors caused an additive effect, blunting BCa cell growth (Fig. 5d). Next, we evaluated whether LIPG activity was sufficient to rescue the chemical inhibition of FAS. To this end, we overexpressed WT and inactive LIPG and grew MCF7 and MDA231 cells in the presence or absence of a high dose of C75 (20mgml−1), which blocks cell growth (Supplementary Fig. 5d). Complete blockade of FAS was not rescued by LIPG (Fig. 5e). Collectively, our results suggest that both exogenous lipid precursors provided by means of LIPG activity and de novo lipid synthesis mediated by FAS are necessary for BCa cell growth.

 

Here we reveal that FoxA factors provide a central metabolic growth function by specifically regulating LIPG expression, thereby allowing the acquisition of indispensable extracellular lipids for BCa tumour proliferation. FoxA family of transcription factors are expressed in the vast majority of BCa and FoxA1 is expressed across various BCa subtypes. Moreover we show that, in some cases, its absence is associated with the expression of FoxA2. Interestingly, in addition of FoxA1 contribution to luminal commitment24, 25, 26, 27 the factor may drive BCa growth by specifically regulating LIPG levels.

The catalytic activity of LIPG generates extracellular lipid precursors that are imported to fulfill the intracellular production of lipid species (Fig. 5f). LIPG downregulation blocks BCa cell growth, thereby indicating that the import of extracellular lipid precursors is important for the proliferation of these cells. This is a striking observation given that it is generally believed that de novo fatty acid synthesis is the main driver of tumour growth22. Indeed, our experimental data with LIPG-depleted BCa cells revealed a massive decrease of most intracellular glycerolipid intermediates in the synthesis of TG (PC, PE, PG and DG) and their derivatives (LPC and LPE). Accordingly, certain lipid species (LPC) in the media were not decreased in LIPG-depleted cells as much as in control cells, thus indicating that extracellular lipids are the substrates for intracellular lipid production. In particular, we demonstrate the relevance of extracellular LPC (18:0) for BCa cell proliferation in a lipoprotein-depleted medium, a process dependent on LIPG. In this context, a high-fat diet was shown to rescue the absence of a critical intracellular lipase, Monoacylglycerol lipase, for cancer pathogenesis given cancer cells ability to uptake lipids from the extracellular compartment was functional19. Herein, we showed that this rescue mechanism is not functional in BCa cells in the absence of FoxA2 or LIPG. In support of this notion, it is worth noting that extracellular LIPG activity releases fatty acids from high-density lipoprotein phospholipids and these acids are further employed for intracellular lipid production in the human hepatic cell line HepG2 (refs 28, 29).

In conclusion, BCa cells are dependent on a mechanism to supply precursors derived from extracellular sources for intracellular lipid production, and LIPG fulfills this function. Therefore, LIPG stands out as an important component of the lipid metabolic adaptations that BCa cells, and not normal tissue, must undergo to support high proliferation rates. Our results also suggest thatde novo lipid synthesis is necessary but not sufficient to support lipid production for BCa tumour growth. Accordingly, recent clinical studies demonstrate the association between lipids and lipoproteins in circulation and risk of BCa in women with extensive mammographic density. This observation implies that interventions aimed to reduce them may have effect on BCa risk30. All together, these observations make LIPG activity an Achilles heel of luminal and, more importantly, of triple negative/basal-like breast tumours, for which limited therapeutic options are currently available.

In normal cells, the glucose carbon flow is directed into a de novo lipogenic pathway that is regulated, in part, via phosphoinositide-3 kinase (PI-3K)-dependent activation of ATP citrate lyase (ACL), a key rate-limiting, enzyme in de novo lipogenesis. ACL is a cytosolic enzyme that catalyzes the generation of acetyl CoA from citrate. Inhibition of ACL results in a loss of B-cell growth and cell viability [10] .
The plasma membrane and its constituent phosphoinositides form the basis of the phosphatidylinositol 3-kinase (PI3-K) signaling pathway, which is crucial for cell proliferation and survival. Phosphatase and tensin-homolog deleted on chromosome 10 (PTEN) is a tumor-suppressor protein that regulates phosphatidylinositol 3-kinase (PI3-K) signaling by binding to the plasma membrane and hydrolyzing the 3′ phosphate from phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3) to form phosphatidylinositol (4,5)-bisphosphate (PI(4,5)P2). Several loss-of-function mutations in PTEN that impair lipid phosphatase activity and membrane binding are oncogenic, leading to the development of a variety of cancers. Of these three residues, R335 was observed to interact with the membrane to the greatest extent across all of the simulations. R335L, in common with several other germline mutations, has been associated with the inherited cancer [11] .
ACLY is up-regulated or activated in several types of cancers, and its inhibition is known to induce proliferation arrest in cancer cells both in vitro and in vivo. The last studies were showed that BCR-mediated signaling is regulated in part by the amount of membrane cholesterol. It was observed that statins (Lovostatin), the pharmacological inhibitors of cholesterol synthesis, induce apoptosis of CLL cells in vitro and in vivo. Also the ectopic expression of CD5 in a B-cell line stimulates the transcription of genes involved in the synthesis of cholesterol [12] .

[10] Zaidi N, Swinnen JV, Smans K. ATP-citrate lyase: a key player in cancer metabolism Cancer Res; 2012 (11): 3709-14.

[11] Craig N, Mark S.P. Sansom. Defining the Membrane-Associated State of the PTEN Tumor Suppressor Protein. Biophys J 2013; 5; 104(3: 613–21.

[12] Tomowiak C, Kennel A, Gary-Gouy, Hadife N. High Membrane Cholesterol in CLL B-Cells and Differential Expression of Cholesterol Synthesis Genes in IG GENE Unmutated vs Mutated Cells. British Journal of Medicine & Medical Research 2012; 2(3): 313-26.

 

Cancer’s Vanguard

Exosomes are emerging as key players in metastasis.

By Catherine Offord | April 1, 2016   http://www.the-scientist.com/?articles.view/articleNo/45577/title/Cancer-s-Vanguard/

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PREPARING THE TURF: Before tumor cells arrive at their metastatic destination, part of the site is readied for them. One recent study of liver metastasis in mice found that resident macrophages called Kupffer cells take up exosomes from the original tumor (1). Additionally, macrophages from the bone marrow show up upon the release of fibronectin by other liver cells called stellate cells (2). A current proposal for additional steps in metastatic niche development includes the recruitment of epithelial cells and fibroblasts, which contribute to angiogenesis, and, finally, the arrival of tumor cells themselves (3).© IKUMI KAYAMA/STUDIO KAYAMA

In 2005, David Lyden noticed something unexpected. He and his colleagues at Weill Cornell Medical College had been researching metastasis—the spread of cancer from one part of the body to another. The team had shown that bone marrow–derived cells (BMDCs) were recruited to future metastatic sites before the arrival of tumor cells, confirming that metastasis occurred after a habitable microenvironment, or “premetastatic niche,” had been prepared.1

But carefully studying images of this microenvironment in the lung tissue of mice, Lyden saw something else. Amongst the BMDCs, the micrographs showed tiny specks, far too small to be cells, gathering at the future site of metastasis. “I said, ‘What are these viruses doing here?’” recalls Lyden. “I had no idea about exosomes, microvesicles, and microparticles.”

Those specks, Lyden would come to realize, were in fact primary tumor–derived exosomes. These membrane-enclosed vesicles packed full of molecules are now attracting growing attention as important mediators of intercellular communication, particularly when it comes to cancer’s insidious capacity to spread from one organ to another.

Preparing the ground

Tumors require a community of support cells, including fibroblasts, BMDCs, and endothelial cells, to provide functional and structural assistance and to modulate immune system behavior. Bringing together the first members of this community before the arrival of tumor cells is all part of cancer’s survival strategy, says Joshua Hood, a cancer researcher at the University of Louisville.

“It wouldn’t be efficient for tumor cells to strike out on their own, and just say, ‘Oh, here we are!’” he says. “They would run the risk of being destroyed.” Preparing a “nest” in advance makes the process much safer. “Then the tumor can just efficiently come along and set up shop without ever having to fight much of a battle with the immune system.”

But although Lyden’s group had shown that this preparation was taking place, it remained unclear how such a process might be regulated. For the next few years, many cancer researchers believed that tumor cells must communicate with the premetastatic niche primarily through tumor-secreted signaling molecules such as cytokines.

Meanwhile, research into extracellular vesicles, previously considered biological garbage bags, was revealing new modes of intercellular communication. In 2007, a group of scientists in Sweden discovered that exosomes, tiny vesicles measuring just 30 nanometers to 100 nanometers across, transport mRNA and microRNAs intercellularly, with the potential to effect changes in protein synthesis in recipient cells.2 A new means for tumors to regulate distant cellular environments came into focus, and research on exosomes exploded. In 2011, Hood and his colleagues showed that exosomes facilitate melanoma metastasis through the lymphatic system.3 The following year, Lyden’s group demonstrated that tumor-derived exosomes can direct BMDCs to one of melanoma’s most common sites of metastasis, the lung.4 Exosomes, it seemed, had been underestimated.

Tiny terraformers

Armed with the knowledge that exosomes are involved in multiple stages of melanoma metastasis, Lyden’s lab went searching for the vesicles’ potential role in the metastasis of other cancers. Turning to pancreatic ductal adenocarcinoma (PDAC)—one of the most lethal cancers in humans—postdoctoral researcher Bruno Costa-Silva led a series of exhaustive in vitro and in vivo experiments in mouse models to detail the process of premetastatic niche formation in the liver, PDAC’s most common destination. The team’s results, published last May, reveal an intricate series of sequential steps—mediated by PDAC-derived exosomes (Nature Cell Biol, 17:816-26, 2015).

Using fluorescence labeling, Lyden’s group observed that PDAC-derived exosomes are taken up by Kupffer cells, specialized macrophages lining the outer walls of blood vessels in the liver. There, the exosomes trigger the cells’ secretion of transforming growth factor β (a type of cytokine involved in cell proliferation), plus the production of fibronectin by neighboring hepatic stellate cells, and the recruitment of BMDCs.

The researchers also showed that this cascade of events could be inhibited by depleting exosomal macrophage migratory inhibitory factor (MIF), an abundant protein in PDAC exosomes. “If you target the specific proteins of exosomes, you can reduce metastasis,” explains coauthor Héctor Peinado, leader of the microenvironment and metastasis group at the Spanish National Cancer Research Center.

For Hood, the findings add to a developing picture of exosomes’ vital role as “vanguard” in the progression of cancer. “It’s like the colonization of a new planet,” he says. “They’re terraforming the environment to make it hospitable.”

MOLECULAR & CELLULAR BIOLOGY

THE PAPERS

  • B. Costa-Silva et al., “Pancreatic cancer exosomes initiate pre-metastatic niche formation in the liver,”Nature Cell Biol, 17:816-26, 2015.
  • A. Hoshino et al., “Tumour exosome integrins determine organotropic metastasis,” Nature, 527:329-35, 2015.
  • L. Zhang et al., “Microenvironment-induced PTEN loss by exosomal microRNA primes brain metastasis outgrowth,”Nature, 527:100-04, 2015.

Internal mail

Although research was revealing the steps involved in forming premetastatic sites, it was less clear how these sites were being selected. “This has always been a great mystery in cancer,” says Ayuko Hoshino, a research associate in Lyden’s lab. “Why do certain cancers metastasize to certain organs?”

One theory, proposed in 1928 by pathologist James Ewing, suggested that anatomical and mechanical factors explained organ specificity in metastasis. The premetastatic niche, then, might form wherever exosomes are likely to land. But this couldn’t be the whole story, says Hoshino. “For instance, there’s eye melanoma. Thinking about that site, you could imagine it metastasizing to the brain. But actually, it almost only metastasizes to the liver.”

Because exosomes arrive at metastatic sites before tumor cells, the team reasoned, perhaps the exosomes themselves were organotropic (i.e., attracted to particular organs or tissues). Sure enough, Lyden says, when Hoshino and Costa-Silva began injecting tumor-derived exosomes into mice, “their preliminary findings were that wherever they injected the exosomes, the pancreatic cancer ones were ending up in the liver and the breast metastasis exosomes would end up in the lung.”

Using mass spectrometry, the researchers analyzed the protein content of exosomes from lung-tropic, liver-tropic, and brain-tropic tumors. They found that the composition of exosomes’ integrins—membrane proteins involved in cell adhesion—was destination-specific (Nature, 527:329-35, 2015). Exosomes bearing integrin α6β4, for example, were directed to the lung, where they could prepare a premetastatic niche potent enough even for normally bone-tropic tumor cells to colonize. Integrin αvβ5, meanwhile, directed metastasis to the liver.

The researchers also showed that exosomal integrins didn’t necessarily correspond to the parent-cell proteins, making exosomes potentially better indicators of where a cancer will spread than the tumor cells themselves. “We can show that an integrin that’s high in the tumor cell might be completely absent in the tumor exosome or vice versa,” says Lyden, adding that, taken together, the results point to a role for exosomes in “dictating the future sites of metastasis.”

“It’s a beautiful story,” says Dihua Yu, a molecular and cellular oncologist at the University of Texas MD Anderson Cancer Center. “This is a very novel finding that gives really good indicators for potential strategies to intervene in metastasis.”

Metastatic crosstalk

In the same month that Lyden’s group published its work on organotropism, Yu’s own lab published a different exosome study—one that told another side of the story.

Yu and her colleagues had found that when tumor cells in mice metastasized to the brain, they downregulated expression of a tumor suppressor gene called PTEN, and became primed for growth at the metastatic site. When the tumor cells were taken out of the microenvironment and put in culture, however, they restored normal PTEN expression.

The researchers demonstrated that a microRNA from astrocytes—star-shape glial cells in the brain—reversibly downregulated the levels of PTEN transcripts in the tumor cells, but they couldn’t figure out how the microRNA was getting into the tumor. Blocking “obvious signaling pathways,” such as gap junctions, failed to have an effect, Yu says.

Scrutinizing astrocyte-conditioned media using electron microscopy, the researchers identified spherical vesicles between 30 nanometers and 100 nanometers in diameter—the defining size of exosomes. Exposing mouse tumor cells to these vesicles increased cell microRNA content and reduced PTENexpression (Nature, 527:100-04, 2015). The study revealed yet another role for exosomes in the communication between tumors and their microenvironment.

The findings were a surprise, says Yu, not least because they showed a different perspective from the bulk of recent research. “We’re talking about astrocytes in the brain secreting exosomes to give welcome help to the cancer cells,” she says.

“I find it an extremely interesting paper because it shows that the astrocytes can change the whole phenotype of the tumor in the brain,” says Lyden. He adds that the results underline the importance of studying the mutational status of tumors at various sites. “All this work in exosomes, it adds to the complexity,” he says. “We can’t just target tumor cells at the primary site. We’ll have to understand all the details of metastasis if we’re really going to tackle it.”

What’s next?

The discovery of multiple roles for exosomes in metastasis has generated excitement about the potential for their use in diagnostics and treatment. As protective containers of tumor-derived genetic material, exosomes could provide information about the status of cancer progression. And as mediators of premetastatic niche formation, they make obvious targets for inhibition. (See “Banking on Blood Tests,”here.)

Exosomes might even be useful as vehicles to deliver drugs because they’re patient-matched and “naturally designed to function in a biocompatible way with living systems,” says Hood. “You could take them out of people, and at some point down the road try to have patients be their own nanofactory, using their own particles for treatment purposes.”

Pancreatic cancer exosomes initiate pre-metastatic nihe formation in the liver

Bruno Costa-SilvaNicole M. AielloAllyson J. Ocean, et al.   Nature Cell Biology 2015; 17,816–826   http://dx.doi.org:/10.1038/ncb3169

Pancreatic ductal adenocarcinomas (PDACs) are highly metastatic with poor prognosis, mainly due to delayed detection. We hypothesized that intercellular communication is critical for metastatic progression. Here, we show that PDAC-derived exosomes induce liver pre-metastatic niche formation in naive mice and consequently increase liver metastatic burden. Uptake of PDAC-derived exosomes by Kupffer cells caused transforming growth factor β secretion and upregulation of fibronectin production by hepatic stellate cells. This fibrotic microenvironment enhanced recruitment of bone marrow-derived macrophages. We found that macrophage migration inhibitory factor (MIF) was highly expressed in PDAC-derived exosomes, and its blockade prevented liver pre-metastatic niche formation and metastasis. Compared with patients whose pancreatic tumours did not progress, MIF was markedly higher in exosomes from stage I PDAC patients who later developed liver metastasis. These findings suggest that exosomal MIF primes the liver for metastasis and may be a prognostic marker for the development of PDAC liver metastasis.

Ayuko HoshinoBruno Costa-SilvaTang-Long ShenGoncalo RodriguesAyako HashimotoMilica Tesic Mark, et al. Nature Nov 2015; 527,329–335  http://dx.doi.org:/10.1038/nature15756

Ever since Stephen Paget’s 1889 hypothesis, metastatic organotropism has remained one of cancer’s greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.

  1. Paget, S. The distribution of secondary growths in cancer of the breast. 1889. Cancer Metastasis Rev. 8, 98101 (1989)
  2. Hart, I. R. & Fidler, I. J. Role of organ selectivity in the determination of metastatic patterns of B16 melanoma. Cancer Res. 40, 22812287 (1980)
  3. Müller, A. et al. Involvement of chemokine receptors in breast cancer metastasis. Nature410, 5056 (2001)
  4. Weilbaecher, K. N., Guise, T. A. & McCauley, L. K. Cancer to bone: a fatal attraction. Nature Rev. Cancer 11, 411425 (2011)
  5. Zhou, W. et al. Cancer-secreted miR-105 destroys vascular endothelial barriers to promote metastasis. Cancer Cell 25, 501515 (2014)
  6. Chang, Q. et al. The IL-6/JAK/Stat3 feed-forward loop drives tumorigenesis and metastasis.Neoplasia 15, 848862 (2013)
  7. Lu, X. & Kang, Y. Organotropism of breast cancer metastasis. J. Mammary Gland Biol. Neoplasia 12, 153162 (2007)

…….

Microenvironment-induced PTEN loss by exosomal microRNA primes brain metastasis outgrowth

Lin ZhangSiyuan ZhangJun YaoFrank J. LoweryQingling ZhangWen-Chien Huang, et al.  Nature  Nov 2015; 527,100–104   http://dx.doi.org:/10.1038/nature15376

The development of life-threatening cancer metastases at distant organs requires disseminated tumour cells’ adaptation to, and co-evolution with, the drastically different microenvironments of metastatic sites1. Cancer cells of common origin manifest distinct gene expression patterns after metastasizing to different organs2. Clearly, the dynamic interaction between metastatic tumour cells and extrinsic signals at individual metastatic organ sites critically effects the subsequent metastatic outgrowth3, 4. Yet, it is unclear when and how disseminated tumour cells acquire the essential traits from the microenvironment of metastatic organs that prime their subsequent outgrowth. Here we show that both human and mouse tumour cells with normal expression of PTEN, an important tumour suppressor, lose PTEN expression after dissemination to the brain, but not to other organs. The PTEN level in PTEN-loss brain metastatic tumour cells is restored after leaving the brain microenvironment. This brain microenvironment-dependent, reversible PTEN messenger RNA and protein downregulation is epigenetically regulated by microRNAs from brain astrocytes. Mechanistically, astrocyte-derived exosomes mediate an intercellular transfer of PTEN-targeting microRNAs to metastatic tumour cells, while astrocyte-specific depletion of PTEN-targeting microRNAs or blockade of astrocyte exosome secretion rescues the PTEN loss and suppresses brain metastasis in vivo. Furthermore, this adaptive PTEN loss in brain metastatic tumour cells leads to an increased secretion of the chemokine CCL2, which recruits IBA1-expressing myeloid cells that reciprocally enhance the outgrowth of brain metastatic tumour cells via enhanced proliferation and reduced apoptosis. Our findings demonstrate a remarkable plasticity of PTEN expression in metastatic tumour cells in response to different organ microenvironments, underpinning an essential role of co-evolution between the metastatic cells and their microenvironment during the adaptive metastatic outgrowth. Our findings signify the dynamic and reciprocal cross-talk between tumour cells and the metastatic niche; importantly, they provide new opportunities for effective anti-metastasis therapies, especially of consequence for brain metastasis patients.

  1. Quail, D. F. & Joyce, J.A. Microenvironmental regulation of tumor progression and metastasis. Nature Med. 19, 14231437 (2013)
  2. Park, E. S. et al. Cross-species hybridization of microarrays for studying tumor transcriptome of brain metastasis. Proc. Natl Acad. Sci. USA 108, 1745617461 (2011)
  3. Joyce, J. A. & Pollard, J. W. Microenvironmental regulation of metastasis. Nature Rev. Cancer 9, 239252 (2009)
  4. Vanharanta, S. & Massagué, J. Origins of metastatic traits. Cancer Cell 24, 410421 (2013)
  5. Gray, J. Cancer: genomics of metastasis. Nature 464, 989990 (2010)
  6. Friedl, P. & Alexander, S. Cancer invasion and the microenvironment: plasticity and reciprocity. Cell 147, 9921009 (2011)

Banking on Blood Tests

How close are liquid biopsies to replacing current diagnostics?

By Jyoti Madhusoodanan | April 1, 2016  http://www.the-scientist.com/?articles.view/articleNo/45584/title/Banking-on-Blood-Tests/

No matter where a tumor lurks in the body, its secrets circulate in the blood. Stray tumor cells begin metastatic migrations by slipping into the vasculature. Vesicles secreted by cancer cells and free-floating DNA are also released into the bloodstream. Because these bits of cellular debris are a grab-bag of biomarkers that could both signal a cancer’s presence and predict its progression and response to treatment, the use of blood-based tests, or liquid biopsies, to detect and evaluate them is now drawing significant commercial interest.

Last year, San Diego–based Pathway Genomics began advertising a screen “for the early detection of up to 10 different cancer types in high-risk populations.” But the screen had only been tested in already-diagnosed patients, not in at-risk individuals, and within weeks of making it commercially available, the company received an FDA notice to provide more information about their promotional claims before further marketing. “We . . . have not found any published evidence that this test or any similar test has been clinically validated as a screening tool for early detection of cancer in high risk individuals,” the agency wrote.

The Forces of Cancer

A tumor’s physical environment fuels its growth and causes treatment resistance.

By Lance L. Munn and Rakesh K. Jain | April 1, 2016   http://www.the-scientist.com/?articles.view/articleNo/45603/title/The-Forces-of-Cancer/

Ahelium balloon tugs gently at the end of its string. The tension in the string resists the buoyant force of the helium, and the elastic nature of the balloon’s rubber contains the helium gas as it tries   to expand. Cutting the string or poking the rubber with a pin reveals the precarious balance between the forces, upsets the equilibrium, and sets the system into motion.

Some biological tissues also exist in such a state of offsetting forces. The most familiar example is the balance between blood pressure and the elastic tension in the cardiovascular system that contains and conveys blood without bursting or collapsing. And in tumors, both solid and fluid forces are generated that make the cancerous tissue a lot like that helium balloon: cut a tumor with a scalpel and it rapidly swells and deforms as pent-up forces break free from structural elements that are severed.1

One force that is notably higher in tumors than in healthy tissues is fluid pressure, resulting from hyperpermeable, leaky blood vessels and a dearth of draining lymphatic vessels. Researchers have known since the 1950s that tumors exhibit elevated fluid pressure, but the implications for tumor progression and drug delivery were not realized until the late 1980s. That was when we (R.K.J. and colleagues) used a mathematical model to predict—and subsequently validate in animal and human tumors—that a precipitous drop in fluid pressure at the tumor–normal tissue interface causes interstitial fluid to ooze out of the tumor.2 This seeping fluid pushes drugs, growth factors, and cancer cells into the surrounding tissue and lymphatics, reducing drug delivery and facilitating local tumor invasion and distant metastasis.

Based on this insight, we suggested in 2001 that anti-angiogenic drugs could be used to lower a tumor’s fluid pressure and improve treatment outcome.3 This hypothesis changed the thinking about how existing anti-angiogenesis therapies actually work and spurred research into other physical forces acting in cancer.4 In the last 15 years, researchers have identified diverse sources of increased pressure in tumors, which may serve as possible targets for cancer therapy.5 For example, solid forces exerted by the extracellular matrix can be reduced by treatment with drugs approved by the US Food and Drug Administration (FDA) for controlling hypertension (angiotensin blockers) or diabetes (metformin). Retrospective clinical studies have found improved survival in cancer patients who were treated with these agents, which are now being tested in prospective trials for a variety of solid tumors.6,7

Tumors under pressure

In vitro experiments showing that cancer cells actively migrate in response to fluid flow have supported the hypothesis that fluid escaping from the boundary of a tumor may guide the invasive migration of cancer cells toward lymphatic or blood vessels, potentially encouraging metastasis. There remains controversy over how the fluid forces induce the migration; the cells may respond to chemical gradients created by the cells and distorted by the flowing fluid,8 or the fluid may activate cell mechanosensors.9 Because of the potential for new therapeutic interventions, the transduction of mechanical fluid forces into biochemical signals by cell mechanosensors is an active area of investigation. In a more direct manner, the fluid flow can physically carry cancer cells to lymph nodes.

Fluid forces may also promote tumor progression by recruiting blood vessels into the cancerous mass.10 Because tumor blood vessels are leaky, plasma can pass freely between vessels that have different pressures. When this happens at the periphery of a tumor, where angiogenic growth factors are prevalent, there can be synergistic induction of new vessel sprouts.

UNDER PRESSURE    See full infographic: WEB | PDF© N.R.FULLER, SAYO-ART LLC

And fluid pressure is just one of the many forces in a tumor that can influence its development and progression. Tumors also develop increased solid pressure, as compared with normal tissue, stemming from the uncontrolled division of cancer cells and from the infiltration and proliferation of stromal and immune cells from the surrounding tissue and circulation. High-molecular-weight polysaccharides known as hydrogels found in the extracellular matrix (ECM) also add pressure on a tumor. The most well-studied of these hydrogels is hyaluronan; when the polysaccharide absorbs water, it swells, pressing on surrounding cells and structural elements of the tissue.

The ECM contains a highly interconnected network of collagen and other fibers and is normally very good at resisting and containing such tension. It also has support from infiltrating myofibroblasts, which detect areas where the ECM density or tension is not normal and initiate actomyosin-based contraction of collagen and elastin matrix structures to restore tensional homeostasis. But while this repair effort is typically effective in healthy tissues, uncooperative tumor cells interfere with these efforts, both by themselves generating pressure and by hyperactivating cancer-associated fibroblasts to produce more ECM and thus produce even more force.11

Because cell growth and ECM composition are not spatially uniform in cancer, tumors are subjected to multiple, dispersed sources of pressure associated with matrix “containers” of various sizes. This solid pressure from within the tumor deforms the surrounding normal tissue, potentially facilitating the metastatic escape of cancer cells. The physical forces also compress blood vessels and lymphatic vessels in the tumor and adjacent normal tissue,12 increasing the fluid pressure in the tumor13  and interrupting the delivery of nutrients, removal of waste, and entry of tumor-targeted drugs via the blood.4 Insufficient blood flow also results in poor oxygenation, which has been linked to immunosuppression, inflammation, invasion, and metastasis, as well as lowered efficacy of chemo-, radio-, and immunotherapies.4 These are all indirect consequences of solid stresses in and on tumors.

Such forces can also have direct effects on cancer cells, and may serve as independent triggers for tumor invasion. Mechanical forces are central to many of our sense systems, such as hearing, touch, and pain, and to tissue maintenance programs, such as bone regeneration and blood vessel remodeling. In these systems, mechanical forces are transduced by mechanosensors to activate downstream biochemical and genetic pathways. (See “Full Speed Ahead,” The Scientist, December 2009.) Cancer cells may similarly be able to sense and respond to dynamic forces in tumors. We have shown, for example, that metastatic cancer cells exposed to compressive stresses in a culture dish undergo a phenotypic transformation to become more invasive,14 and others have shown that compressive forces applied in vivo can also induce oncogenes in normal epithelium of the mouse colon.15

It is thus becoming quite clear that the physical environment can influence a tumor’s development and spread, and it may even be possible for physical forces to kick-start cancerous growth.

…..

Full Speed Ahead

Physical forces acting in and around cells are fast—and making waves in the world of molecular biology.

By Jef Akst | December 1, 2009    http://www.the-scientist.com/?articles.view/articleNo/27816/title/Full-Speed-Ahead/

When it comes to survival, few things are more important than being able to respond quickly to a change of circumstances. And when it comes to fast-acting indicators, it turns out that signals induced by physical forces acting in and around cells, appropriately dubbed biomechanical signals, are the champions of the cellular world.

“If you look at this mechanical signaling, it’s about 30 meters per second—that’s very fast,” says bioengineer Ning Wang of the University of Illinois at Urbana-Champaign. That’s faster than most family-owned speedboats, and second only to electrical (e.g., nerve) impulses in biological signaling. By comparison, small chemicals moving by diffusion average a mere 2 micrometers per second—a speed even the slowest row boater could easily top.

Indeed, when the two signal types were pitted against each other in a cellular race last year, the mechanical signals left chemical signals in their wake, activating proteins at distant sites in the cytoplasm in just a fraction of a second, at least 40 times faster than their growth factor opponent.1 Mechanical signals are so fast, Wang adds, they are “beyond our resolution,” meaning that current imaging techniques cannot capture the very first cellular changes that result from mechanical stress, which occur within nanoseconds.

For centuries, scientists have scrutinized the molecular inner workings of the body, with little or no regard to the physical environment in which these biological reactions take place. But the growing realization that physical forces have a pervasive presence in physiology (operating in a variety of bodily systems in thebone, blood, kidney, and ear, for instance), and act with astonishing speed, has caused many to consider the possibility that mechanical signaling may be just as important as chemical communication in the life of a cell.

“Biologists have traditionally ignored the role of mechanics in biology,” says biomechanical engineer Mohammad Mofrad of the University of California, Berkley, “[but] biomechanics is becoming increasingly accepted, and people are recognizing its role in development, in disease, and in general cellular and tissue function.”

The wave within: Mechanical forces acting inside the cell

Once believed to be little more than sacks of chemically active goop, cells didn’t seem capable of transmitting physical forces into their depths, and researchers largely limited their search for molecules or structures that respond to physical forces, or mechanosensors, to the plasma membrane.

Mechanical signaling may be just as important as chemical communication in the life of a cell.

In the late 1990s, however, closer examination revealed that the cell’s interior is in fact a highly structured environment, composed of a network of filaments.2 Pull on one side of the cell, and these filaments will transmit the force all the way to other side, tugging on and bumping into a variety of cellular structures along the way—similar to how a boat’s wake sends a series of small waves lapping up on a distant and otherwise peaceful shoreline. Scientists are now realizing the potential of such intracellular jostling to induce molecular changes throughout the cell, and the search for mechanosensing molecules has escalated dramatically in scope, including, for example, several proteins of the nucleus.

It’s a search that will likely last a while, predicts cell biologist Donald Ingber, director of the Wyss Institute for Biologically Inspired Engineering at Harvard University. “To try to find out what’s the mechanosensor is kind of crazy at this point,” he says. As scientists are now learning, “the whole cell is the mechanosensor.”

A key player, most agree, is the cytoskeleton, which is comprised of a variety of microfilaments, including rigid actin filaments and active myosin motors—the two principle components of muscle. Activation of the so-called nonmuscle myosins causes the cytoskeleton to contract, much like an arm muscle does when it lifts a heavy object.

The first intimation that the cytoskeleton could go beyond its established inner-cell duties (molecule transport and cell movement and division) came in 1997, when Ingber did the logical (in hindsight, at least) experiment of pulling on the cells to see what happened inside.2 Using a tiny glass micropipette coated in ligands, Ingber and his team gently probed the surface proteins known as integrins, which secure the cell to the extracellular matrix. When they quickly pulled the micropipette away, they saw an immediate cellular makeover: cytoskeletal elements turned 90 degrees, the nucleus distorted, and the nucleolus—a small, dense structure within the nucleus that functions primarily in ribosome assembly—aligned itself with the direction of the applied force.

“That kind of blew people away,” Ingber recalls. “It revealed that cells have incredible levels of structure not only in the cytoplasm but in the nucleus as well.”

Wang (once a postdoc in Ingber’s lab at the Harvard School of Public Health) and other collaborators combined a similar technique with fluorescent imaging technology to visualize how these forces were channeled within the cell’s interior. Upping the resolution and further refining these techniques, Wang began mapping these intracellular forces as they made their way through the cell. In 2005, the maps confirmed the physical connection between the cell-surface integrins and the nucleus, and showed that these external forces follow a nonrandom path dictated by the tension of the cytoskeletal elements.3

“Biomechanics is becoming increasingly accepted, and people are recognizing its role in development, in disease, and in general cellular and tissue function.”
–Mohammad Mofrad

The end point of these mechanical pathways is likely a mechanosensitive protein, which changes shape in response to the force, thereby exposing new binding areas or otherwise changing the protein’s function. In mitochondria, for example, mechanical forces may trigger the release of reactive oxygen species and activation of signaling molecules that contribute to inflammation and atherosclerosis.

Similarly, proteins on the nuclear membrane may pass mechanical signals into the nucleus by way of a specialized structure known as LINC (linker of nucleoskeleton and cytoskeleton), which physically links the actin cytoskeleton to proteins important in nuclear organization and gene function. To determine if mechanical forces directly affect gene expression, last year scientists began exploiting the increasingly popular fluorescence resonance energy transfer (FRET) technology,1 in which energy emitted by one fluorescent molecule can stimulate another, resulting in a visible energy transfer that can track enzymatic activities in live cells. By combining FRET technology with the techniques that apply physical forces to specific cell membrane proteins, scientists can visualize entire mechanochemical transduction pathways, Wang says.

“The big issue right now in the field of mechanotransduction is whether the genes in the nucleus can be directly activated by forces applied to the cell surface,” Wang explains. While the physical maps of the cytoskeleton tentatively sketch out a path that supports this possibility, confirmatory data is lacking. This combination of new technologies will be “tremendously” helpful in answering that question, he says, and “push the field” towards a more complete understanding of how mechanical forces can influence cellular life.

An early start: Mechanical forces in development

In the world of developmental biology, the cytoskeleton’s role in biomechanics really comes into its own. As the embryo develops, the cells themselves are the force generators, and by contracting at critical times, the cytoskeleton can initiate many key developmental steps, from invagination and gastrulation to proliferation and differentiation, and overall cellular organization.

The idea that physical forces play a role in development is not a new one. In the early 20th century, back when Albert Einstein was first developing the molecular basis of viscosity and scientists were realizing molecules are distinct particles, biologist and mathematician D’Arcy Thompson of the University of Dundee in Scotland suggested that mechanical strain is a key player in morphogenesis. Now, nearly a century later, biologists are finally beginning to agree.

Because Thompson “couldn’t measure [the forces] at that time, that kind of thinking got pushed to the wayside as genetic thinking took over biology,” says bioengineer Christopher Chen of the University of Pennsylvania. That is, until 2003, when Emmanuel Farge of the Curie Institute in France squeezedDrosophila embryos to mimic the compression experienced during early development and activated twist—a critical gene in the formation of the digestive tract.4 These results gave weight to Thompson’s idea that stress in the embryo stimulates development and growth, and inspired developmental scientists to begin considering mechanical effects, Chen says. “Now we’re at the stage where there’s a lot of interest and willingness to consider the fact that mechanical forces are not only shaping the embryo, but are linked to the differentiation programs that are going on.”

Again, the cytoskeleton is a key player in this process. In fruit flies and frogs, for example, nonmuscle myosins contract the actin filaments to generate the compressive forces necessary for successful gastrulation—the first major shape-changing event of development. Myosins similarly influence proliferation in the development of the Drosophila egg chamber, with increased myosin activity resulting in increased cell division.

Cytoskeleton contractility also appears to direct stem cell differentiation. In 2006, Dennis Discher of the University of Pennsylvania demonstrated that the tension of the substrate on which cells are grown in culture is important for determining what type of tissue the cells will form.5 Cells grown on soft matrices that mimic brain tissue tended to grow into neural cells, while cells grown on stiffer matrices grew into muscle cell precursors, and hard matrices yielded bone. In this case, it seems that stiffer substrates increased the expression of nonmuscle myosin, generating greater tension in the actin cytoskeleton and affecting differentiation. (Altering or inhibiting myosin contraction can also affect differentiation.)

“To try to find out what’s the mechanosensor is kind of crazy at this point. As scientists are now learning, the whole cell is the mechanosensor.”
–Donald Ingber
……..
Shaping a tumor

In addition to the influence of physical forces on cancer growth and invasion, forces can alter a tumor’s mechanical properties, and vice versa. Tumors are more rigid, or stiffer, than surrounding tissues, usually because they contain excess collagen in the ECM,5 and this can contain and amplify local forces produced by proliferating cancer cells. On the other hand, tumor rigidity can be further enhanced if the cells exert tension on ECM collagen fibers by pulling on them, or by stretching them, as occurs when tumors grow uncontrollably. Fluid forces can also influence the assembly of collagen fibers within and around tumors,8potentially increasing stiffness.

Importantly, tumor stiffness tends to be associated with poor prognoses, though the reasons for this are not fully understood. Cells are known to differentiate into different lineages depending on the local rigidity;16 for example, stem cells differentiate into bone on stiff substrates, but make adipose (fat) cells on softer substrates. Similar mechanisms are thought to affect tumor progression when the ECM changes rigidity, inducing cancer cells to become more invasive as well as more likely to metastasize. Indeed, longer collagen fibers in the matrix are associated with increased invasion and metastasis, as well as reduced survival, in mice.17

In addition, the abnormal ECM in tumors can affect cancer progression by activating normal stromal cells, such as macrophages and fibroblasts, that accelerate tumor growth and treatment resistance. These activated stromal cells further strengthen and stretch the ECM, causing a snowball effect.

The biochemical composition and organization of the ECM also influences tumor biology. Dysregulation of normal matrix signals can lead to tumor progression, characterized by excessive cell proliferation, immortality, enhanced migration, changes in metabolism, and evasion of the immune response. More research is needed to dissect the relationships between the ECM’s mechanical properties, forces, and cell signaling pathways.

Targeting the ECM

Because unchecked proliferation of cancer cells increases solid stress in the tumor, anticancer therapies should decrease the compressive forces in tumors and reopen collapsed blood and lymphatic vessels.11 This is exactly what happens when tumors are treated with certain doses of paclitaxel or docetaxel, two widely used cancer drugs. Shrinking tumors increases blood flow and allows more efficient fluid movement through the extravascular space, lowering the tumor interstitial fluid pressure in mouse models and in patients with breast cancer.5 However, cancer cells invariably develop resistance to treatment and begin to regrow, increasing solid stress again. As a result, other targets for reducing solid stresses are needed.

Because of its role in containing and concentrating the forces in a tumor, the collagen matrix within and around the tumor is another potential target for relieving tumor-related stresses. Indeed, solid stress in tumors can be reduced by drugs that selectively reprogram activated fibroblasts or modify the assembly of matrix components such as collagen and hyaluronan. In rodent studies, targeting these force-altering components in the tumor microenvironment has been shown to decrease solid stress, improve blood perfusion and drug delivery, and improve tumor response to chemotherapy and animal survival.6 We have found, for example, that injecting tumors with a collagen-digesting enzyme increases the diffusion of antibodies and viral particles and improves drug penetration in the tumor. Similarly, treatments that target transforming growth factor–beta (TGF-β), which controls the production of collagen by myofibroblasts, increase perfusion, improve the delivery of drugs of all sizes in mammary tumors, and improve treatment outcomes in mice.5

A class of drugs that is widely used to control blood pressure in hypertensive patients also blocks the TGF-β pathway. These drugs, known as angiotensin receptor 1 blockers, can reduce collagen production in and around the tumor by reducing the activity of TGF-β, as well as by blocking the function of connective tissue growth factor (CTGF), which is involved in stabilizing collagen and inducing resistance to chemotherapy.6Losartan and other angiotensin inhibitors reduce levels of collagen in various experimental models of fibrosis, and decrease renal and cardiac fibrosis in hypertensive patients. When given to mice with one of four different types of tumors characterized by high levels of cancer-associated fibroblasts (CAFs) and excess extracellular matrix—pancreatic ductal adenocarcinoma, breast cancer, sarcoma, and melanoma—losartan treatment caused a decrease in collagen content in a dose-dependent manner, enhanced penetration of nanoparticles into the tumor, and improved efficacy of diverse anticancer drugs. This is supported by a number of retrospective studies in patients with pancreatic, lung, and kidney cancers.6Researchers at Massachusetts General Hospital are now running a Phase 1/2 clinical trial to test losartan in pancreatic cancer patients.

http://www.the-scientist.com/images/April2016/forces_cancer_2.jpg

THE TUMOR ENVIRONMENT: The extracellular matrix and stromal cells within a tumor’s microenvironment influence the physical forces a tumor experiences. Left: The immunofluorescent image shows stromal cells (red and green) surrounding tumor cells (red cluster with blue nuclei); the cells were isolated from a mouse model of lung adenocarcinoma. Right: In this immunofluorescent image of triple-negative breast cancer, tumor cells (blue) are in close contact with matrix collagen (purple). Immune cells are labeled in red and green.VASILENA GOCHEVA, JACKS LAB, KOCH INSTITUTE AT MIT; DONGMEI ZUO, LABORATORY DR. MORAG PARK

Another potential cancer treatment target is hyaluronan, which is abundant in 20 percent to 30 percent of human tumors, most notably breast, colon, and prostate cancers. In addition to its role as a pressure-creating gel, hyaluronan can sequester growth factors and inhibit interstitial fluid movement within the tumor. Hyaluronidase, an enzyme that digests hyaluronan, reduces mechanical stress in tumors grown in mice.1 And San Diego–based Halozyme Therapeutics’s PEGPH20, a formulation of hyaluronidase coated with polyethylene glycol to enhance bioavailability, can decompress blood vessels and improve treatment outcome in genetically engineered mouse models of pancreatic ductal adenocarcinoma. Based on these studies, Halozyme researchers are now testing PEGPH20 in a randomized clinical trial of pancreatic cancer patients. Another matrix-altering drug is the widely-prescribed antidiabetic drug metformin, which has been shown to decrease collagen and hyaluronan levels in pancreatic tumors in obese mice and patients.7 Metformin is currently being tested in more than 200 clinical trials worldwide as a treatment for different types of cancer.

Clearly, tumors should be studied not only in light of their biochemical processes and genetic underpinnings, but also for the specific physical forces and mechanical properties that may influence progression. Understanding the physical microenvironment of tumors, as well as its interplay with the biochemical environment, is necessary to improve cancer detection, prevention, and treatment.

  1. T. Stylianopoulos et al., “Causes, consequences, and remedies for growth-induced solid stress in murine and human tumors,” PNAS, 109:15101-08, 2012.
  2. R.K. Jain, L.T. Baxter, “Mechanisms of heterogeneous distribution of monoclonal antibodies and other macromolecules in tumors: Significance of elevated interstitial pressure,” Cancer Res, 48:7022-32, 1988.
  3. R.K. Jain, “Normalization of tumor vasculature: An emerging concept in antiangiogenic therapy,”Science, 307:58-62, 2005.
  4. R.K. Jain, “Antiangiogenesis strategies revisited: From starving tumors to alleviating hypoxia,”Cancer Cell, 26:605-22, 2014.
  5. R.K. Jain et al., “The role of mechanical forces in tumor growth and therapy,” Annu Rev Biomed Eng, 16:321-46, 2014.
  6. V.P. Chauhan et al., “Angiotensin inhibition enhances drug delivery and potentiates chemotherapy by decompressing tumour blood vessels,” Nat Commun, 4:2516, 2013.
  7. J. Incio et al., “Metformin reduces desmoplasia in pancreatic cancer by reprogramming stellate cells and tumor-associated macrophages,” PLOS ONE, 10:e0141392, 2015.
  8. M.A. Swartz, A.W. Lund, “Lymphatic and interstitial flow in the tumour microenvironment: linking mechanobiology with immunity,” Nat Rev Cancer, 12:210-19, 2012.
  9. H. Qazi et al., “Cancer cell glycocalyx mediates mechanotransduction and flow-regulated invasion,”Integr Biol, 5:1334-43, 2013.
  10. J.W. Song, L.L. Munn, “Fluid forces control endothelial sprouting,” PNAS, 108:15342-47, 2011.

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New Frontiers in Gene Editing
Gene editing is rapidly progressing from being a research/screening tool to one that promises important applications downstream in drug development, cell therapy and bioprocessing. Cambridge Healthtech Institute’s second annual symposium on New Frontiers in Gene Editing will bring together experts from all aspects of basic science and clinical research to talk about the progress being made in gene editing and how it’s being applied. Knowing the strengths and limitations of the different tools, how does one decide when to use the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas system, as opposed to Transcription Activator-Like Effector Nucleases (TALENs), zinc finger nucleases (ZFNs) and other systems? What is being done to overcome some of the inherent challenges with design, delivery and off-target effects, associated with each of these techniques? Experts from pharma/biotech, academic and government labs will share their experiences leveraging the utility of gene editing for diverse applications. REGISTER
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Prologue to Cancer – e-book Volume One – Where are we in this journey?


Prologue to Cancer – e-book Volume One – Where are we in this journey?

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

Consulting Reviewer and Contributor:  Jose Eduardo de Salles Roselino, MD

 

LH Bernstein

LH Bernstein

Jose Eduardo de Salles Roselino

LES Roselino

 

 

This is a preface to the fourth in the ebook series of Leaders in Pharmaceutical Intelligence, a collaboration of experienced doctorate medical and pharmaceutical professionals.  The topic is of great current interest, and it entails a significant part of current medical expenditure by a group of neoplastic diseases that may develop at different periods in life, and have come to supercede infections or even eventuate in infectious disease as an end of life event.  The articles presented are a collection of the most up-to-date accounts of the state of a now rapidly emerging field of medical research that has benefitted enormously by progress in immunodiagnostics,  radiodiagnostics, imaging, predictive analytics, genomic and proteomic discovery subsequent to the completion of the Human Genome Project, advances in analytic methods in qPCR, gene sequencing, genome mapping, signaling pathways, exome identification, identification of therapeutic targets in inhibitors, activators, initiators in the progression of cell metabolism, carcinogenesis, cell movement, and metastatic potential.  This story is very complicated because we are engaged in trying to evoke from what we would like to be similar clinical events, dissimilar events in their expression and classification, whether they are within the same or different anatomic class.  Thus, we are faced with constructing an objective evidence-based understanding requiring integration of several disciplinary approaches to see a clear picture.  The failure to do so creates a high risk of failure in biopharmaceutical development.

The chapters that follow cover novel and important research and development in cancer related research, development, diagnostics and treatment, and in balance, present a substantial part of the tumor landscape, with some exceptions.  Will there ever be a unifying concept, as might be hoped for? I certainly can’t see any such prediction on the horizon.  Part of the problem is that disease classification is a human construct to guide us, and so are treatments that have existed and are reexamined for over 2,000 years.  In that time, we have changed, our afflictions have been modified, and our environment has changed with respect to the microorganisms within and around us, viruses, the soil, and radiation exposure, and the impacts of war and starvation, and access to food.  The outline has been given.  Organic and inorganic chemistry combined with physics has given us a new enterprise in biosynthetics that is and will change our world.  But let us keep in mind that this is a human construct, just as drug target development is such a construct, workable with limitations.

What Molecular Biology Gained from Physics

We need greater clarity and completeness in defining the carcinogenetic process.  It is the beginning, but not the end.  But we must first examine the evolution of the scientific structure that leads to our present understanding. This was preceded by the studies of anatomy, physiology, and embryology that had to occur as a first step, which was followed by the researches into bacteriology, fungi, sea urchins and the evolutionary creatures that could be studied having more primary development in scale.  They are still major objects of study, with the expectation that we can derive lessons about comparative mechanisms that have been passed on through the ages and have common features with man.  This became the serious intent of molecular biology, the discipline that turned to find an explanation for genetics, and to carry out controlled experiments modelled on the discipline that already had enormous success in physics, mathematics, and chemistry. In 1900, when Max Planck hypothesized that the frequency of light emitted by the black body depended on the frequency of the oscillator that emitted it, it had important ramifications for chemistry and biology (See Appendix II and Footnote 1, Planck equation, energy and oscillation).  The leading idea is to search below the large-scale observations of classical biology.

The central dogma of molecular biology where genetic material is transcribed into RNA and then translated into protein, provides a starting point, but the construct is undergoing revision in light of emerging novel roles for RNA and signaling pathways.   The term, coined by Warren Weaver (director of Natural Sciences for the Rockefeller Foundation), who observed an emergence of significant change given recent advances in fields such as X-ray crystallography. Molecular biology also plays important role in understanding formations, actions, regulations of various parts of cellswhich can be used efficiently for targeting new drugs, diagnosis of disease, physiology of the Cell. The Nobel Prize in Physiology or Medicine in 1969 was shared by Max Delbrück, Alfred D. Hershey, Salvador E. Luria, whose work with viral replication gave impetus to the field.  Delbruck was a physicist who trained in Copenhagen under Bohr, and specifically committed himself to a rigor in biology, as was in physics.

Dorothy Hodgkin  protein crystallography

Dorothy Hodgkin protein crystallography

Rosalind Franlin crystallographer double helix

Rosalind Franlin
crystallographer
double helix

 Max Delbruck         molecular biology

Max Delbruck        
molecular biology

Max Planck

Max Planck Quantum Physics

 

 

 

We then stepped back from classical (descriptive) physiology, with the endless complexity, to molecular biology.  This led us to the genetic code, with a double helix model.  It has recently been found insufficiently explanatory, with the recent construction of triplex and quadruplex models. They have a potential to account for unaccounted for building blocks, such as inosine, and we don’t know whether more than one model holds validity under different conditions .  The other major field of development has been simply unaccounted for in the study of proteomics, especially in protein-protein interactions, and in the energetics of protein conformation, first called to our attention by the work of Jacob, Monod, and Changeux (See Footnote 2).  Proteins are not just rigid structures stamped out by the monotonously simple DNA to RNA to protein concept.  Nothing is ever quite so simple. Just as there are epigenetic events, there are posttranslational events, and yet more.

JPChangeux-150x170

JP Changeux

 

 

 

 

 

 

 

 

The Emergence of Molecular Biology

I now return the discussion to the topic of medicine, the emergence of molecular biology and the need for convergence with biochemistry in the mid-20th century. Jose Eduardo de Salles Roselino recalls “I was previously allowed to make of the conformational energy as made by R Marcus in his Nobel lecture revised (J. of Electroanalytical  Chemistry 438:(1997) p251-259. (See Footnote 1) His description of the energetic coordinates of a landscape of a chemical reaction is only a two-dimensional cut of what in fact is a volcano crater (in three dimensions) (each one varies but the sum of the two is constant. Solvational+vibrational=100% in ordinate) nuclear coordinates in abcissa. In case we could represent it by research methods that allow us to discriminate in one by one degree of different pairs of energy, we would most likely have 360 other similar representations of the same phenomenon. The real representation would take into account all those 360 representations together. In case our methodology was not that fine, for instance it discriminates only differences of minimal 10 degrees in 360 possible, will have 36 partial representations of something that to be perfectly represented will require all 36 being taken together. Can you reconcile it with ATGC?  Yet, when complete genome sequences were presented they were described as though we will know everything about this living being. The most important problems in biology will be viewed by limited vision always and the awareness of this limited is something we should acknowledge and teach it. Therefore, our knowledge is made up of partial representations. If we had the entire genome data for the most intricate biological problems, they are still not amenable to this level of reductionism. But going from general views of signals andsymptoms we could get to the most detailed molecular view and in this case genome provides an anchor.”

“Warburg Effect” describes the preference of glycolysis and lactic acid fermentation rather than oxidative phosphorylation for energy production in cancer cells. Mitochondrial metabolism is an important and necessary component in the functioning and maintenance of the cell, and accumulating evidence suggests that dysfunction of mitochondrial metabolism plays a role in cancer. Progress has demonstrated the mechanisms of the mitochondrial metabolism-to-glycolysis switch in cancer development and how to target this metabolic switch.

 

 

Glycolysis

glycolysis

 

Otto Heinrich Warburg (1883-  )

Otto Warburg

435px-Louis_Pasteur,_foto_av_Félix_Nadar_Crisco_edit

Louis Pasteur

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The expression “Pasteur effect” was coined by Warburg when inspired by Pasteur’s findings in yeast cells, when he investigated this metabolic observation (Pasteur effect) in cancer cells. In yeast cells, Pasteur had found that the velocity of sugar used was greatly reduced in presence of oxygen. Not to be confused, in the “Crabtree effect”, the velocity of sugar metabolism was greatly increased, a reversal, when yeast cells were transferred from the aerobic to an anaerobic condition. Thus, the velocity of sugar metabolism of yeast cells was shown to be under metabolic regulatory control in response to change in environmental oxygen conditions in growth. Warburg had to verify whether cancer cells and tissue related normal mammalian cells also have a similar control mechanism. He found that this control was also found in normal cells studied, but was absent in cancer cells. Strikingly, cancer cells continue to have higher anaerobic gycolysis despite the presence of oxygen in their culture media (See Footnote 3).

Taking this a step further, food is digested and supplied to cells In vertebrates mainly in the form of glucose, which is metabolized producing Adenosine Triphosphate (ATP) by two pathways. Glycolysis, occurs via anaerobic metabolism in the cytoplasm, and is of major significance for making ATP quickly, but in a minuscule amount (2 molecules).  In the presence of oxygen, the breakdown process continues in the mitochondria via the Krebs’s cycle coupled with oxidative phosphorylation, which is more efficient for ATP production (36 molecules). Cancer cells seem to depend on glycolysis. In the 1920s, Otto Warburg first proposed that cancer cells show increased levels of glucose consumption and lactate fermentation even in the presence of ample oxygen (known as “Warburg Effect”). Based on this theory, oxidative phosphorylation switches to glycolysis which promotes the proliferation of cancer cells. Many studies have demonstrated glycolysis as the main metabolic pathway in cancer cells.

Albert Szent Gyogy (Warburg’s student) and Otto Meyerhof both studied striated skeletal muscle metabolism invertebrates, and they found those changes observed in yeast by Pasteur. The description of the anaerobic pathway was largely credited to Emden and Meyerhof. Whenever there is increase in muscle work, energy need is above what can be provided by blood supply, the cell metabolism changes from aerobic (where  Acetyl CoA  provides the chemical energy for aerobic production of ATP) to anaerobic metabolism of glucose. In this condition, glucose is obtained directly from its muscle glycogen stores (not from hepatic glycogenolysis).  This is the sole source of chemical energy that is independent of oxygen supplied to the cell. It is a physiological change on muscle metabolism that favors autonomy. It does not depend upon the blood oxygen for aerobic metabolim or blood sources of carbon metabolites borne out from adipose tissue (free fatty acids) or muscle proteins (branched chain amino acids), or vascular delivery of glucose. On that condition, the muscle can perform contraction by its internal source of ATP and uses conversion of pyruvate to lactate in order to regenerate much-needed NAD (by hydride transfer from pyruvate) as a replacement for this mitochondrial function. This regulatory change, keeps glycolysis going at fast rate in order to meet ATP needs of the cell under low yield condition (only two or three ATP for each glucose converted into two lactate molecules). Therefore, it cannot last for long periods of time. This regulatory metabolic change is made in seconds, minutes and therefore happens with the proteins that are already presented in the cell. It does not requires the effect of transcription factors and/or changes in gene expression (See Footnote 1, 2).

In other types mammalian cells, like those from the lens of the eye (86% gycolysis + pentose shunt),  and red blood cells (RBC)[both lacking mitochondria], and also in the deep medullary layer of the kidneys, for lack of mitochondria in the first two cases and normally reduced blood perfusion in the third – A condition required for the counter current mechanism and our ability to concentrate urine also have, permanent higher anaerobic metabolism. In the case of RBC, it includes the ability to produce in a shunt of glycolytic pathway 2,3 diphospho- glycerate that is required to place the hemogloblin macromolecule in an unstable equilibrium between its two forms (R and T – Here presented as simplified accordingly to the model of Monod, Wyman and Changeux. The final model would be even much complex (see for instance, H-W and K review Nature 2007 vol 450: p 964-972 )

Any tissue under a condition of ischemia that is required for some medical procedures (open heart surgery, organ transplants, etc) displays this fast regulatory mechanism (See Footnote 1, 2). A display of these regulatory metabolic changes can be seen in: Cardioplegia: the protection of the myocardium during open heart surgery: a review. D. J. Hearse J. Physiol., Paris, 1980, 76, 751-756 (Fig 1).  The following points are made:

1-       It is a fast regulatory response. Therefore, no genetic mechanism can be taken into account.

2-       It moves from a reversible to an irreversible condition, while the cells are still alive. Death can be seen at the bottom end of the arrow. Therefore, it cannot be reconciled with some of the molecular biology assumptions:

A-       The gene and genes reside inside the heart muscle cells but, in order to preserve intact, the source of coded genetic information that the cell reads and transcribes, DNA must be kept to a minimal of chemical reactivity.

B-       In case sequence determines conformation, activity and function , elevated potassium blood levels could not cause cardiac arrest.

In comparison with those conditions here presented, cancer cells keep the two metabolic options for glucose metabolism at the same time. These cells can use glucose that our body provides to them or adopt temporarily, an independent metabolic form without the usual normal requirement of oxygen (one or another form for ATP generation).  ATP generation is here, an over-simplification of the metabolic status since the carbon flow for building blocks must also be considered and in this case oxidative metabolism of glucose in cancer cells may be viewed as a rich source of organic molecules or building blocks that dividing cells always need.

JES Roselino has conjectured that “most of the Krebs cycle reaction works as ideal reversible thermodynamic systems that can supply any organic molecule that by its absence could prevent cell duplication.” In the vision of Warburg, cancer cells have a defect in Pasteur-effect metabolic control. In case it was functioning normally, it will indicate which metabolic form of glucose metabolism is adequate for each condition. What more? Cancer cells lack differentiated cell function. Any role for transcription factors must be considered as the role of factors that led to the stable phenotypic change of cancer cells. The failure of Pasteur effect must be searched for among the fast regulatory mechanisms that aren’t dependent on gene expression (See Footnote 3).

Extending the thoughts of JES Roselino (Hepatology 1992;16: 1055-1060), reduced blood flow caused by increased hydrostatic pressure in extrahepatic cholestasis decreases mitochondrial function (quoted in Hepatology) and as part of Pasteur effect normal response, increased glycolysis in partial and/or functional anaerobiosis and therefore blocks the gluconeogenic activity of hepatocytes that requires inhibited glycolysis. In this case, a clear energetic link can be perceived between the reduced energetic supply and the ability to perform differentiated hepatic function (gluconeogenesis). In cancer cells, the action of transcription factors that can be viewed as different ensembles of kaleidoscopic pieces (with changing activities as cell conditions change) are clearly linked to the new stable phenotype. In relation to extrahepatic cholestasis mentioned above it must be reckoned that in case a persistent chronic condition is studied a secondary cirrhosis is installed as an example of persistent stable condition, difficult to be reversed and without the requirement for a genetic mutation. (See Footnote 4).

 The Rejection of Complexity

Most of our reasoning about genes was derived from scientific work in microorganisms. These works have provided great advances in biochemistry.

250px-DNA_labeled  DNA diagram showing base pairing

double helix

 

hgp_hubris_220x288_72  genome cartoon

Dna triplex pic

Triple helix

 

formation of a triplex DNA structure

formation of triple helix

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1-      The “Gelehrter idea”: No matter what you are doing you will always be better off, in case you have a gene (In chapter 7 Principles of Medical Genetics Gelehrter and Collins Williams & Wilkins 1990).

2-      The idea that everything could be found following one gene one enzyme relationship that works fine for our understanding of the metabolism, in all biological problems.

3-      The idea that everything that explains biochemistry in microorganisms explains also for every living being (J Nirenberg).

4-      The idea that biochemistry may not require that time should be also taken into account. Time must be considered only for genetic and biological evolution studies (S Luria. In Life- The unfinished experiment 1977 C Scribner´s sons NY).

5-      Finally, the idea that everything in biology, could be found in the genome. Since all information in biology goes from DNA through RNA to proteins. Alternatively, are in the DNA, in case the strict line that includes RNA is not included.

This last point can be accepted in case it is considered that ALL GENETIC information is in our DNA. Genetics as part of life and not as its total expression.

For example, when our body is informed that the ambient temperature is too low or alternatively is too high, our body is receiving an information that arrives from our environment. This external information will affect our proteins and eventually, in case of longer periods in a new condition will cause adaptive response that may include conformational changes in transcription factors (proteins) that will also, produce new readings on the DNA. However, it is an information that moves from outside, to proteins and not from DNA to proteins. The last pathway, when transcription factors change its conformation and change DNA reading will follow the dogmatic view as an adaptive response (See Footnotes 1-3).

However, in case, time is taken into account, the first reactions against cold or warmer temperatures will be the ones that happen through change in protein conformation, activities and function before any change in gene expression can be noticed at protein level. These fast changes, in seconds, minutes cannot be explained by changes in gene expression and are strongly linked to what is needed for the maintenance of life.

“It is possible”, says Roselino, “desirable, to explain all these fast biochemical responses to changes in a living being condition as the sound foundation of medical practices without a single mention to DNA. In case a failure in any mechanism necessary to life is found to be genetic in its origin, the genome in context with with this huge set of transcription factors must be taken into account. This is the biochemical line of reasoning that I have learned with Houssay and Leloir. It would be an honor to see it restored in modern terms.”

More on the Mechanism of Metabolic Control

It was important that genomics would play such a large role in medical research for the last 70 years. There is also good reason to rethink the objections of the Nobelists James Watson and Randy Schekman in the past year, whatever discomfort it brings.  Molecular biology has become a tautology, and as a result deranged scientific rigor inside biology.

Crick & Watson with their DNA model, 1953

Eatson and Crick

Randy-Schekman Berkeley

Randy-Schekman Berkeley

 

 

According to JES Roselino, “consider that glycolysis is oscillatory thanks to the kinetic behavior of Phosphofructokinase. Further, by its effect upon Pyruvate kinase through Fructose 1,6 diphosphate oscillatory levels, the inhibition of gluconeogenesis is also oscillatory. When the carbon flow through glycolysis is led to a maximal level gluconeogenesis will be almost completely blocked. The reversal of the Pyruvate kinase step in liver requires two enzymes (Pyruvate carboxylase (maintenance of oxaloacetic levels) + phosphoenolpyruvate carboxykinase (E.C. 4.1.1.32)) and energy requiring reactions that most likely could not as an ensemble, have a fast enough response against pyruvate kinase short period of inhibition during high frequency oscillatory periods of glycolytic flow. Only when glycolysis oscillates at low frequency the opposite reaction could enable gluconeogenic carbon flow.”

In case it can be shown in a rather convincing way, the same reasoning could be applied to understand how simple replicative signals inducing Go to G1 transition in cells, could easily overcome more complex signals required for cell differentiation and differentiated function.

Perhaps the problem of overextension of the equivalence of the DNA and what happens to the organism is also related to the initial reliance on a single cell model to relieve the complexity (which isn’t fully the case).

For instance, consider this fragment:
“Until only recently it was assumed that all proteins take on a clearly defined three-dimensional structure – i.e. they fold in order to be able to assume these functions.”
Cold Spring Harbour Symp. Quant. Biol. 1973  p 187-193 J.C Seidel and J Gergely – Investigation of conformational changes in Spin-Labeled Myosin Model for muscle contraction:
Huxley, A. F. 1971 Proc. Roy. Soc (London) (B) 178:1
Huxley, A.F and R. M. Simmons,1971. Nature 233:633
J.C Haselgrove X ray Evidence for a conformational Change in the Actin-containing filaments…Cold Spring Harbour Symp Quant Biol.1972 v 37: p 341-352

Only a very small sample indicating otherwise. Proteins were held as interacting macromolecules, changing their conformation in regulatory response to changes in the microenvironment (See Footnote 2). DNA was the opposite, non-interacting macromolecules to be as stable as a library must be.

The dogma held that the property of proteins could be read in DNA alone. Consequenly, the few examples quoted above, must be ignored and all people must believe that DNA alone, without environmental factors roles, controls protein amino acid sequence (OK), conformation (not true), activity (not true) and function (not true).

It appeared naively to be correct from the dogma to conclude from interpreting your genome: You have a 50% increased risk of developing the following disease (deterministic statement).  The correct form must be: You belong to a population that has a 50% increase in the risk of….followed by –  what you must do to avoid increase in your personal risk and the care you should take in case you want to have longer healthy life.  Thus, genetics and non-genetic diseases were treated as the same and medical foundations were reinforced by magical considerations (dogmas) in a very profitable way for those involved besides the patient.

 Footnotes:

  1. There is a link of electricity with ions in biology and the oscillatory behavior of some electrical discharges.  In addition, the oscillatory form of electrical discharged may have allowed Planck to relate high energy content with higher frequencies and conversely, low energy content in low frequency oscillatory events.  One may think of high density as an indication of great amount of matter inside a volume in space.  This helps the understanding of Planck’s idea as a high-density-energy in time for a high frequency phenomenon.
  1. Take into account a protein that may have its conformation restricted by an S-S bridge. This protein also, may move to another more flexible conformation in case it is in HS HS condition when the S-S bridge is broken. Consider also that, it takes some time for a protein to move from one conformation for instance, the restricted conformation (S-S) to other conformations. Also, it takes a few seconds or minutes to return to the S-S conformation (This is the Daniel Koshland´s concept of induced fit and relaxation time used by him in order to explain allosteric behavior of monomeric proteins- Monod, Wyman and Changeux requires tetramer or at least, dimer proteins).
  1. In case you have glycolysis oscillating in a frequency much higher than the relaxation time you could lead to the prevalence of high NADH effect leading to high HS /HS condition and at low glycolytic frequency, you could have predominance of S-S condition affecting protein conformation. In case you have predominance of NAD effect upon protein S-S you would get the opposite results.  The enormous effort to display the effect of citrate and over Phosphofructokinase conformation was made by others. Take into account that ATP action as an inhibitor in this case, is a rather unusual one. It is a substrate of the reaction, and together with its action as activator  F1,6 P (or its equivalent F2,6 P) is also unusual. However, it explains oscillatory behaviour of glycolysis. (Goldhammer , A.R, and Paradies: PFK structure and function, Curr. Top Cell Reg 1979; 15:109-141).
  1. The results presented in our Hepatology work must be viewed in the following way: In case the hepatic (oxygenated) blood flow is preserved, the bile secretory cells of liver receive well-oxygenated blood flow (the arterial branches bath secretory cells while the branches originated from portal vein irrigate the hepatocytes.  During extra hepatic cholestasis the low pressure, portal blood flow is reduced and the hepatocytes do not receive enough oxygen required to produce ATP that gluconeogenesis demands. Hepatic artery do not replace this flow since, its branches only join portal blood fluxes after the previous artery pressure  is reduced to a low pressure venous blood – at the point where the formation of hepatic vein is. Otherwise, the flow in the portal vein would be reversed or, from liver to the intestine. It is of no help to take into account possible valves for this reasoning since minimal arterial pressure is well above maximal venous pressure and this difference would keep this valve in permanent close condition. In low portal blood flow condition, the hepatocyte increases pyruvate kinase activity and with increased pyruvate kinase activity Gluconeogenesis is forbidden (See Walsh & Cooper revision quoted in the Hepatology as ref 23). For the hemodynamic considerations, role of artery and veins in hepatic portal system see references 44 and 45 Rappaport and Schneiderman and Rappapaport.

 

 Appendix I.

metabolic pathways

metabolic pathways

Signals Upstream and Targets Downstream of Lin28 in the Lin28 Pathway

Signals Upstream and Targets Downstream of Lin28 in the Lin28 Pathway

 

 

 

 

 

 

 

 

1.  Functional Proteomics Adds to Our Understanding

Ben Schuler’s research group from the Institute of Biochemistry of the University of Zurich has now established that an increase in temperature leads to folded proteins collapsing and becoming smaller. Other environmental factors can trigger the same effect. The crowded environments inside cells lead to the proteins shrinking. As these proteins interact with other molecules in the body and bring other proteins together, understanding of these processes is essential “as they play a major role in many processes in our body, for instance in the onset of cancer”, comments study coordinator Ben Schuler.

Measurements using the “molecular ruler”

“The fact that unfolded proteins shrink at higher temperatures is an indication that cell water does indeed play an important role as to the spatial organisation eventually adopted by the molecules”, comments Schuler with regard to the impact of temperature on protein structure. For their studies the biophysicists use what is known as single-molecule spectroscopy. Small colour probes in the protein enable the observation of changes with an accuracy of more than one millionth of a millimetre. With this “molecular yardstick” it is possible to measure how molecular forces impact protein structure.

With computer simulations the researchers have mimicked the behaviour of disordered proteins. They want to use them in future for more accurate predictions of their properties and functions.

Correcting test tube results

That’s why it’s important, according to Schuler, to monitor the proteins not only in the test tube but also in the organism. “This takes into account the fact that it is very crowded on the molecular level in our body as enormous numbers of biomolecules are crammed into a very small space in our cells”, says Schuler. The biochemists have mimicked this “molecular crowding” and observed that in this environment disordered proteins shrink, too.

Given these results many experiments may have to be revisited as the spatial organisation of the molecules in the organism could differ considerably from that in the test tube according to the biochemist from the University of Zurich. “We have, therefore, developed a theoretical analytical method to predict the effects of molecular crowding.” In a next step the researchers plan to apply these findings to measurements taken directly in living cells.

Explore further: Designer proteins provide new information about the body’s signal processesMore information: Andrea Soranno, Iwo Koenig, Madeleine B. Borgia, Hagen Hofmann, Franziska Zosel, Daniel Nettels, and Benjamin Schuler. Single-molecule spectroscopy reveals polymer effects of disordered proteins in crowded environments. PNAS, March 2014. DOI: 10.1073/pnas.1322611111

 

Effects of Hypoxia on Metabolic Flux

  1. Glucose-6-phosphate dehydrogenase regulation in the hepatopancreas of the anoxia-tolerantmarinemollusc, Littorina littorea

JL Lama , RAV Bell and KB Storey

Glucose-6-phosphate dehydrogenase (G6PDH) gates flux through the pentose phosphate pathway and is key to cellular antioxidant defense due to its role in producing NADPH. Good antioxidant defenses are crucial for anoxia-tolerant organisms that experience wide variations in oxygen availability. The marine mollusc, Littorina littorea, is an intertidal snail that experiences daily bouts of anoxia/hypoxia with the tide cycle and shows multiple metabolic and enzymatic adaptations that support anaerobiosis. This study investigated the kinetic, physical and regulatory properties of G6PDH from hepatopancreas of L. littorea to determine if the enzyme is differentially regulated in response to anoxia, thereby providing altered pentose phosphate pathway functionality under oxygen stress conditions.

Several kinetic properties of G6PDH differed significantly between aerobic and 24 h anoxic conditions; compared with the aerobic state, anoxic G6PDH (assayed at pH 8) showed a 38% decrease in K G6P and enhanced inhibition by urea, whereas in pH 6 assays Km NADP and maximal activity changed significantly.

All these data indicated that the aerobic and anoxic forms of G6PDH were the high and low phosphate forms, respectively, and that phosphorylation state was modulated in response to selected endogenous protein kinases (PKA or PKG) and protein phosphatases (PP1 or PP2C). Anoxia-induced changes in the phosphorylation state of G6PDH may facilitate sustained or increased production of NADPH to enhance antioxidant defense during long term anaerobiosis and/or during the transition back to aerobic conditions when the reintroduction of oxygen causes a rapid increase in oxidative stress.

Lama et al.  Peer J 2013.   http://dx.doi.org/10.7717/peerj.21

 

  1. Structural Basis for Isoform-Selective Inhibition in Nitric Oxide Synthase

    TL. Poulos and H Li

In the cardiovascular system, the important signaling molecule nitric oxide synthase (NOS) converts L-arginine into L-citrulline and releases nitric oxide (NO). NO produced by endothelial NOS (eNOS) relaxes smooth muscle which controls vascular tone and blood pressure. Neuronal NOS (nNOS) produces NO in the brain, where it influences a variety of neural functions such as neural transmitter release. NO can also support the immune system, serving as a cytotoxic agent during infections. Even with all of these important functions, NO is a free radical and, when overproduced, it can cause tissue damage. This mechanism can operate in many neurodegenerative diseases, and as a result the development of drugs targeting nNOS is a desirable therapeutic goal.

However, the active sites of all three human isoforms are very similar, and designing inhibitors specific for nNOS is a challenging problem. It is critically important, for example, not to inhibit eNOS owing to its central role in controlling blood pressure. In this Account, we summarize our efforts in collaboration with Rick Silverman at Northwestern University to develop drug candidates that specifically target NOS using crystallography, computational chemistry, and organic synthesis. As a result, we have developed aminopyridine compounds that are 3800-fold more selective for nNOS than eNOS, some of which show excellent neuroprotective effects in animal models. Our group has solved approximately 130 NOS-inhibitor crystal structures which have provided the structural basis for our design efforts. Initial crystal structures of nNOS and eNOS bound to selective dipeptide inhibitors showed that a single amino acid difference (Asp in nNOS and Asn in eNOS) results in much tighter binding to nNOS. The NOS active site is open and rigid, which produces few large structural changes when inhibitors bind. However, we have found that relatively small changes in the active site and inhibitor chirality can account for large differences in isoform-selectivity. For example, we expected that the aminopyridine group on our inhibitors would form a hydrogen bond with a conserved Glu inside the NOS active site. Instead, in one group of inhibitors, the aminopyridine group extends outside of the active site where it interacts with a heme propionate. For this orientation to occur, a conserved Tyr side chain must swing out of the way. This unanticipated observation taught us about the importance of inhibitor chirality and active site dynamics. We also successfully used computational methods to gain insights into the contribution of the state of protonation of the inhibitors to their selectivity. Employing the lessons learned from the aminopyridine inhibitors, the Silverman lab designed and synthesized symmetric double-headed inhibitors with an aminopyridine at each end, taking advantage of their ability to make contacts both inside and outside of the active site. Crystal structures provided yet another unexpected surprise. Two of the double-headed inhibitor molecules bound to each enzyme subunit, and one molecule participated in the generation of a novel Zn site that required some side chains to adopt alternate conformations. Therefore, in addition to achieving our specific goal, the development of nNOS selective compounds, we have learned how subtle differences in and structure can control proteinligand interactions and often in unexpected ways.

 

300px-Nitric_Oxide_Synthase

Nitric oxide synthase

arginine-NO-citulline cycle

arginine-NO-citulline cycle

active site of eNOS (PDB_1P6L) and nNOS (PDB_1P6H).

active site of eNOS (PDB_1P6L) and nNOS (PDB_1P6H).

 

 

NO - muscle, vasculature, mitochondria

NO – muscle, vasculature, mitochondria

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure:  (A) Structure of one of the early dipeptide lead compounds, 1, that exhibits excellentisoform selectivity. (B, C) show the crystal structures of the dipeptide inhibitor 1 in the active site of eNOS (PDB: 1P6L) and nNOS (PDB: 1P6H). In nNOS, the inhibitor “curls” which enables the inhibitor R-amino group to interact with both Glu592 and Asp597. In eNOS, Asn368 is the homologue to nNOS Asp597.

Accounts in Chem Res 2013; 46(2): 390-98.

  1. Jamming a Protein Signal

Interfering with a single cancer-promoting protein and its receptor can open this resistance mechanism by initiating autophagy of the affected cells,  according to researchers at The University of Texas MD Anderson Cancer Center  in the journal Cell Reports.  According to Dr. Anil Sood and Yunfei Wen, lead and first authors, blocking  prolactin, a potent growth factor for ovarian cancer, sets off downstream events that result in cell by autophagy, the process  recycles damaged organelles and proteins for new use by the cell through the phagolysozome. This in turn, provides a clinical rationale for blocking prolactin and its receptor to initiate sustained autophagy as an alternative strategy for treating cancers.

Steep reductions in tumor weight

Prolactin (PRL) is a hormone previously implicated in ovarian, endometrial and other cancer development andprogression. When PRL binds to its cell membrane receptor, PRLR, activation of cancer-promoting cell signaling pathways follows.  A variant of normal prolactin called G129R blocks the reaction between prolactin and its receptor. Sood and colleagues treated mice that had two different lines of human ovarian cancer, both expressing the prolactin receptor, with G129R. Tumor weights fell by 50 percent for mice with either type of ovarian cancer after 28 days of treatment with G129R, and adding the taxane-based chemotherapy agent paclitaxel cut tumor weight by 90 percent. They surmise that higher doses of G129R may result in even greater therapeutic benefit.

 

3D experiments show death by autophagy

 

[video width=”1280″ height=”720″ mp4=”https://pharmaceuticalintelligence.files.wordpress.com/2014/04/1741-7007-11-65-s1-macromolecular-juggling-by-ubiquitylation-enzymes1.mp4″][/video]

 

Next the team used the prolactin-mimicking peptide to treat cultures of cancer spheroids which sharply reduced their numbers, and blocked the activation of JAK2 and STAT signaling pathways.

Protein analysis of the treated spheroids showed increased presence of autophagy factors and genomic analysis revealed increased expression of a number of genes involved in autophagy progression and cell death.  Then a series of experiments using fluorescence and electron microscopy showed that the cytosol of treated cells had large numbers of cavities caused by autophagy.

The team also connected the G129R-induced autophagy to the activity of PEA-15, a known cancer inhibitor. Analysis of tumor samples from 32 ovarian cancer patients showed that tumors express higher levels of the prolactin receptor and lower levels of phosphorylated PEA-15 than normal ovarian tissue. However, patients with low levels of the prolactin receptor and higher PEA-15 had longer overall survival than those with high PRLR and low PEA-15.

Source: MD Anderson Cancer Center

 

  1. Chemists’ Work with Small Peptide Chains of Enzymes

Korendovych and his team designed seven simple peptides, each containing seven amino acids. They then allowed the molecules of each peptide to self-assemble, or spontaneously clump together, to form amyloids. (Zinc, a metal with catalytic properties, was introduced to speed up the reaction.) What they found was that four of the seven peptides catalyzed the hydrolysis of molecules known as esters, compounds that react with water to produce water and acids—a feat not uncommon among certain enzymes.

“It was the first time that a peptide this small self-assembled to produce an enzyme-like catalyst,” says Korendovych. “Each enzyme has to be an exact fit for its respective substrate,” he says, referring to the molecule with which an enzyme reacts. “Even after millions of years, nature is still testing all the possible combinations of enzymes to determine which ones can catalyze metabolic reactions. Our results make an argument for the design of self-assembling nanostructured catalysts.”

Source: Syracuse University

Here are three articles emphasizing the value of combinatorial analysis, which can be formed from genomic, clinical, and proteomic data sets.

 

  1. Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks

    F Islam , M Hoque , RS Banik , S Roy , SS Sumi, et al.

As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e.g. detection of molecular complexes (potential modules or clusters) and identification of crucial nodes forming the overlapping modules have been considered in this regard.

The computational analysis of previously published protein interaction networks (PINs) has been conducted to identify the molecular complexes and crucial nodes of the networks. Protein molecules involved in ten major cancer signal transduction pathways were used to construct the networks based on expression data of five tissues e.g. bone, breast, colon, kidney and liver in both normal and cancer conditions.

Cancer PINs show higher level of clustering (formation of molecular complexes) than the normal ones. In contrast, lower level modular overlapping is found in cancer PINs than the normal ones. Thus a proposition can be made regarding the formation of some giant nodes in the cancer networks with very high degree and resulting in reduced overlapping among the network modules though the predicted molecular complex numbers are higher in cancer conditions.

Islam et al. Journal of Clinical Bioinformatics 2013, 3:19-32

  1. A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

    Wanting Liu , Yonghong Peng and Desmond J. Tobin
    PeerJ 1:e49;        http://dx.doi.org/10.7717/peerj.49

Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca2+, and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, andWNT4).We have begun to experimentally validate a subset of these genes involved inMAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be overexpressed inmetastatic and primarymelanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin.

 

catalytic amyloid forming particle

catalytic amyloid forming particle

 

 

 

 

 

 

 

        8.    PanelomiX: A threshold-based algorithm to create panels of biomarkers

X Robin , N Turck , A Hainard , N Tiberti, et al.
               Translational Proteomics 2013.    http://dx.doi.org/10.1016/j.trprot.2013.04.003

The PanelomiX toolbox combines biomarkers and evaluates the performance of panels to classify patients better than singlemarkers or other classifiers. The ICBTalgorithm proved to be an efficient classifier, the results of which can easily be interpreted.

Here are two current examples of the immense role played by signaling pathways in carcinogenic mechanisms and in treatment targeting, which is also confounded by acquired resistance.

 

  1. Triple-Negative Breast Cancer

  1. epidermal growth factor receptor (EGFR or ErbB1) and
  2. high activity of the phosphatidylinositol 3-kinase (PI3K)–Akt pathway

are both targeted in triple-negative breast cancer (TNBC).

  • activation of another EGFR family member [human epidermal growth factor receptor 3 (HER3) (or ErbB3)] may limit the antitumor effects of these drugs.

This study found that TNBC cell lines cultured with the EGFR or HER3 ligand EGF or heregulin, respectively, and treated with either an Akt inhibitor (GDC-0068) or a PI3K inhibitor (GDC-0941) had increased abundance and phosphorylation of HER3.

The phosphorylation of HER3 and EGFR in response to these treatments

  1. was reduced by the addition of a dual EGFR and HER3 inhibitor (MEHD7945A).
  2. MEHD7945A also decreased the phosphorylation (and activation) of EGFR and HER3 and
  3. the phosphorylation of downstream targets that occurred in response to the combination of EGFR ligands and PI3K-Akt pathway inhibitors.

In culture, inhibition of the PI3K-Akt pathway combined with either MEHD7945A or knockdown of HER3

  1. decreased cell proliferation compared with inhibition of the PI3K-Akt pathway alone.
  2. Combining either GDC-0068 or GDC-0941 with MEHD7945A inhibited the growth of xenografts derived from TNBC cell lines or from TNBC patient tumors, and
  3. this combination treatment was also more effective than combining either GDC-0068 or GDC-0941 with cetuximab, an EGFR-targeted antibody.
  4. After therapy with EGFR-targeted antibodies, some patients had residual tumors with increased HER3 abundance and EGFR/HER3 dimerization (an activating interaction).

Thus, we propose that concomitant blockade of EGFR, HER3, and the PI3K-Akt pathway in TNBC should be investigated in the clinical setting.

Reference: Antagonism of EGFR and HER3 Enhances the Response to Inhibitors of the PI3K-Akt Pathway in Triple-Negative Breast Cancer. JJ Tao, P Castel, N Radosevic-Robin, M Elkabets, et al.  Sci. Signal., 25 March 2014;
7(318), p. ra29   http://dx.doi.org/10.1126/scisignal.2005125

 

                  10.   Metastasis in RAS Mutant or Inhibitor-Resistant Melanoma Cells

The protein kinase BRAF is mutated in about 40% of melanomas, and BRAF inhibitors improve progression-free and overall survival in these patients. However, after a relatively short period of disease control, most patients develop resistance because of reactivation of the RAF–ERK (extracellular signal–regulated kinase) pathway, mediated in many cases by mutations in RAS. We found that BRAF inhibition induces invasion and metastasis in RAS mutant melanoma cells through a mechanism mediated by the reactivation of the MEK (mitogen-activated protein kinase kinase)–ERK pathway.

Reference: BRAF Inhibitors Induce Metastasis in RAS Mutant or Inhibitor-Resistant Melanoma Cells by Reactivating MEK and ERK Signaling. B Sanchez-Laorden, A Viros, MR Girotti, M Pedersen, G Saturno, et al., Sci. Signal., 25 March 2014;  7(318), p. ra30  http://dx.doi.org/10.1126/scisignal.2004815

Appendix II.

The world of physics in the twentieth century saw the end of determinism established by Newton. This is characterized by discrete laws that describe natural observations. These are in gravity and in eletricity. In an early phase of investigation, an era of galvanic or voltaic electricity represented a revolutionary break from the historical focus on frictional electricity. Alessandro Voltadiscovered that chemical reactions could be used to create positively charged anodes and negatively charged cathodes.  In 1790, Prof. Luigi Alyisio Galvani of Bologna, while conducting experiments on “animal electricity“, noticed the twitching of a frog’s legs in the presence of an electric machine. He observed that a frog’s muscle, suspended on an iron balustrade by a copper hook passing through its dorsal column, underwent lively convulsions without any extraneous cause, the electric machine being at this time absent.  Volta communicated a description of his pile to the Royal Society of London and shortly thereafter Nicholson and Cavendish (1780) produced the decomposition of water by means of the electric current, using Volta’s pile as the source of electromotive force.

Siméon Denis Poisson attacked the difficult problem of induced magnetization, and his results provided  a first approximation. His innovation required the application of mathematics to physics.  His memoirs on the theory of electricity and magnetism created a new branch of mathematical physics.  The discovery of electromagnetic induction was made almost simultaneously and independently by Michael Faraday and Joseph Henry. Michael Faraday, the successor of Humphry Davy, began his epoch-making research relating to electric and electromagnetic induction in 1831. In his investigations of the peculiar manner in which iron filings arrange themselves on a cardboard or glass in proximity to the poles of a magnet, Faraday conceived the idea of magnetic “lines of force” extending from pole to pole of the magnet and along which the filings tend to place themselves. On the discovery being made that magnetic effects accompany the passage of an electric current in a wire, it was also assumed that similar magnetic lines of force whirled around the wire. He also posited that iron, nickel, cobalt, manganese, chromium, etc., are paramagnetic (attracted by magnetism), whilst other substances, such as bismuth, phosphorus, antimony, zinc, etc., are repelled by magnetism or are diamagnetic.

Around the mid-19th century, Fleeming Jenkin‘s work on ‘ Electricity and Magnetism ‘ and Clerk Maxwell’s ‘ Treatise on Electricity and Magnetism ‘ were published. About 1850 Kirchhoff published his laws relating to branched or divided circuits. He also showed mathematically that according to the then prevailing electrodynamic theory, electricity would be propagated along a perfectly conducting wire with the velocity of light. Herman Helmholtz investigated the effects of induction on the strength of a current and deduced mathematical equations, which experiment confirmed. In 1853 Sir William Thomson (later Lord Kelvin) predicted as a result of mathematical calculations the oscillatory nature of the electric discharge of a condenser circuit.  Joseph Henry, in 1842 discerned  the oscillatory nature of the Leyden jardischarge.

In 1864 James Clerk Maxwell announced his electromagnetic theory of light, which was perhaps the greatest single step in the world’s knowledge of electricity. Maxwell had studied and commented on the field of electricity and magnetism as early as 1855/6 when On Faraday’s lines of force was read to the Cambridge Philosophical Society. The paper presented a simplified model of Faraday’s work, and how the two phenomena were related. He reduced all of the current knowledge into a linked set of differential equations with 20 equations in 20 variables. This work was later published as On Physical Lines of Force in1861. In order to determine the force which is acting on any part of the machine we must find its momentum, and then calculate the rate at which this momentum is being changed. This rate of change will give us the force. The method of calculation which it is necessary to employ was first given by Lagrange, and afterwards developed, with some modifications, by Hamilton’s equations. Now Maxwell logically showed how these methods of calculation could be applied to the electro-magnetic field. The energy of a dynamical systemis partly kinetic, partly potential. Maxwell supposes that the magnetic energy of the field is kinetic energy, the electric energy potential.  Around 1862, while lecturing at King’s College, Maxwell calculated that the speed of propagation of an electromagnetic field is approximately that of the speed of light.   Maxwell’s electromagnetic theory of light obviously involved the existence of electric waves in free space, and his followers set themselves the task of experimentally demonstrating the truth of the theory. By 1871, he presented the Remarks on the mathematical classification of physical quantities.

A Wave-Particle Dilemma at the Century End

In 1896 J.J. Thomson performed experiments indicating that cathode rays really were particles, found an accurate value for their charge-to-mass ratio e/m, and found that e/m was independent of cathode material. He made good estimates of both the charge e and the mass m, finding that cathode ray particles, which he called “corpuscles”, had perhaps one thousandth of the mass of the least massive ion known (hydrogen). He further showed that the negatively charged particles produced by radioactive materials, by heated materials, and by illuminated materials, were universal.  In the late 19th century, the Michelson–Morley experiment was performed by Albert Michelson and Edward Morley at what is now Case Western Reserve University. It is generally considered to be the evidence against the theory of a luminiferous aether. The experiment has also been referred to as “the kicking-off point for the theoretical aspects of the Second Scientific Revolution.” Primarily for this work, Albert Michelson was awarded theNobel Prize in 1907.

Wave–particle duality is a theory that proposes that all matter exhibits the properties of not only particles, which have mass, but also waves, which transfer energy. A central concept of quantum mechanics, this duality addresses the inability of classical concepts like “particle” and “wave” to fully describe the behavior of quantum-scale objects. Standard interpretations of quantum mechanics explain this paradox as a fundamental property of the universe, while alternative interpretations explain the duality as an emergent, second-order consequence of various limitations of the observer. This treatment focuses on explaining the behavior from the perspective of the widely used Copenhagen interpretation, in which wave–particle duality serves as one aspect of the concept of complementarity, that one can view phenomena in one way or in another, but not both simultaneously.  Through the work of Max PlanckAlbert EinsteinLouis de BroglieArthur Compton, Niels Bohr, and many others, current scientific theory holds that all particles also have a wave nature (and vice versa).

Beginning in 1670 and progressing over three decades, Isaac Newton argued that the perfectly straight lines of reflection demonstrated light’s particle nature, but Newton’s contemporaries Robert Hooke and Christiaan Huygens—and later Augustin-Jean Fresnel—mathematically refined the wave viewpoint, showing that if light traveled at different speeds in different, refraction could be easily explained. The resulting Huygens–Fresnel principle was supported by Thomas Young‘s discovery of double-slit interference, the beginning of the end for the particle light camp.  The final blow against corpuscular theory came when James Clerk Maxwell discovered that he could combine four simple equations, along with a slight modification to describe self-propagating waves of oscillating electric and magnetic fields. When the propagation speed of these electromagnetic waves was calculated, the speed of light fell out. While the 19th century had seen the success of the wave theory at describing light, it had also witnessed the rise of the atomic theory at describing matter.

Matter and Light

In 1789, Antoine Lavoisier secured chemistry by introducing rigor and precision into his laboratory techniques. By discovering diatomic gases, Avogadro completed the basic atomic theory, allowing the correct molecular formulae of most known compounds—as well as the correct weights of atoms—to be deduced and categorized in a consistent manner. The final stroke in classical atomic theory came when Dimitri Mendeleev saw an order in recurring chemical properties, and created a table presenting the elements in unprecedented order and symmetry.   Chemistry was now an atomic science.

Black-body radiation, the emission of electromagnetic energy due to an object’s heat, could not be explained from classical arguments alone. The equipartition theorem of classical mechanics, the basis of all classical thermodynamic theories, stated that an object’s energy is partitioned equally among the object’s vibrational modes. This worked well when describing thermal objects, whose vibrational modes were defined as the speeds of their constituent atoms, and the speed distribution derived from egalitarian partitioning of these vibrational modes closely matched experimental results. Speeds much higher than the average speed were suppressed by the fact that kinetic energy is quadratic—doubling the speed requires four times the energy—thus the number of atoms occupying high energy modes (high speeds) quickly drops off. Since light was known to be waves of electromagnetism, physicists hoped to describe this emission via classical laws. This became known as the black body problem. The Rayleigh–Jeans law which, while correctly predicting the intensity of long wavelength emissions, predicted infinite total energy as the intensity diverges to infinity for short wavelengths.

The solution arrived in 1900 when Max Planck hypothesized that the frequency of light emitted by the black body depended on the frequency of the oscillator that emitted it, and the energy of these oscillators increased linearly with frequency (according to his constant h, where E = hν). By demanding that high-frequency light must be emitted by an oscillator of equal frequency, and further requiring that this oscillator occupy higher energy than one of a lesser frequency, Planck avoided any catastrophe; giving an equal partition to high-frequency oscillators produced successively fewer oscillators and less emitted light. And as in the Maxwell–Boltzmann distribution, the low-frequency, low-energy oscillators were suppressed by the onslaught of thermal jiggling from higher energy oscillators, which necessarily increased their energy and frequency. Planck had intentionally created an atomic theory of the black body, but had unintentionally generated an atomic theory of light, where the black body never generates quanta of light at a given frequency with energy less than .

In 1905 Albert Einstein took Planck’s black body model in itself and saw a wonderful solution to another outstanding problem of the day: the photoelectric effect, the phenomenon where electrons are emitted from atoms when they absorb energy from light.   Only by increasing the frequency of the light, and thus increasing the energy of the photons, can one eject electrons with higher energy. Thus, using Planck’s constant h to determine the energy of the photons based upon their frequency, the energy of ejected electrons should also increase linearly with frequency; the gradient of the line being Planck’s constant. These results were not confirmed until 1915, when Robert Andrews Millikan, produced experimental results in perfect accord with Einstein’s predictions. While  the energy of ejected electrons reflected Planck’s constant, the existence of photons was not explicitly proven until the discovery of the photon antibunching effect  When Einstein received his Nobel Prizein 1921, it was  for the photoelectric effect, the suggestion of quantized light. Einstein’s “light quanta” represented the quintessential example of wave–particle duality. Electromagnetic radiation propagates following  linear wave equations, but can only be emitted or absorbed as discrete elements, thus acting as a wave and a particle simultaneously.

Radioactivity Changes the Scientific Landscape

The turn of the century also features radioactivity, which later came to the forefront of the activities of World War II, the Manhattan Project, the discovery of the chain reaction, and later – Hiroshima and Nagasaki.

Marie Curie

Marie Curie

 

 

 

Marie Skłodowska-Curie was a Polish and naturalized-French physicist and chemist who conducted pioneering research on radioactivity. She was the first woman to win a Nobel Prize, the only woman to win in two fields, and the only person to win in multiple sciences. She was also the first woman to become a professor at the University of Paris, and in 1995 became the first woman to be entombed on her own merits in the Panthéon in Paris. She shared the 1903 Nobel Prize in Physics with her husband Pierre Curie and with physicist Henri Becquerel. She won the 1911 Nobel Prize in Chemistry.  Her achievements included a theory of radioactivity (a term that she coined, techniques for isolating radioactive isotopes, and the discovery of polonium and radium. She named the first chemical element that she discovered – polonium, which she first isolated in 1898 – after her native country. Under her direction, the world’s first studies were conducted into the treatment of neoplasms using radioactive isotopes. She founded the Curie Institutes in Paris and in Warsaw, which remain major centres of medical research today. During World War I, she established the first military field radiological centres.  Curie died in 1934 due to aplastic anemia brought on by exposure to radiation – mainly, it seems, during her World War I service in mobile X-ray units created by her.

 

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Author: Tilda Barliya PhD

Metastasis is a complex series of steps in which cancer cells leave the original tumor site and migrate to a distant organ. Certain cancers tend to spread to specific organ sites; however, the underlying mechanism is not completely understood. After lymph nodes, the liver is the most common site for colorectal cancer metastasis, and liver metastasis is a common cause of cancer-related mortality. Understanding the mechanisms and genetic alterations that predispose to the metastatic phenotype in colorectal cancer is imperative for early detection, prevention and treatment (1). Studies reveal that genomic instability in cancer cells leads to cellular heterogeneity, which may guide tumor cell aggression and specific organ colonization during the metastatic process.

Nat Clin Pract Oncol. 2008;5(4):206-219.

In 2008, Patricia S Steeg, Dan Theodorescu have published a great overview on the cancer metastases (1a).  Figure 1 represents Molecular distinctions between primary colorectal carcinomas and their liver metastases.

Studies have identified distinct expression trends at the RNA or protein levels in primary tumors and metastases, including genes that control metastasis (MTA1, N-Wasp, NCAML1), extracellular matrix function (fibronectin, collagens), microtubule dynamics (stathmin), transcription (Snail), drug-processing enzymes (DPD, TS) and kinases (Yes1).

It is worth mentioning that not every overexpressed or mutated gene is directly and primarily correlated with tumor metastases.

In order to answer this question, Ding Q and colleagues (1b) have done a great job identifying the gene expression signature for colorectal cancer liver metastases. Using an orthotopic colorectal cancer mouse model and transcriptomic microarray analysis, they found that 4 major genes are essential in mediating CRC-liver metastasesAPOBEC3GCD133LIPC, and S100P.

APOBEC3G– Is an apolipoprotein B mRNA-editing enzyme that has been suggested to play a role in the innate anti-viral immune system. Notably, this is the first time it has been shown that APOBEC3G, a gene involved in RNA editing, is able to promote tumor metastasis. APOBEC3G may downregulate miR-29 expression and hamper miR-29 activity in repressing MMP2.

CD133 – is a glycoprotein that is expressed in hematopoetic stem cells, endothelial progenitor cells, intestinal stem cells as well as saeveral types of tumor stem cells. It was related to a high incidence of metastasis in cholangiocarcinoma and melanoma has been indicated, However, questions regarding how CD133 is involved in metastasis and in which cancer stages, how CD133 expression is regulated, and what controls the transition of CD133+ to CD133– cells remain to be addressed.

LIPC –  is Hepatic Triacylglycerol Lipase. It is expressed in the liver and adrenal gland. One of the principal functions of hepatic lipase is to convert intermediate-low density lipoprotein (IDL) to low-density lipoprotein (LDL). A recent study also implicates a role for monoacylglycerol lipase in promoting tumor growth, migration, and invasion, as this lipase translates lipogenic phenotype to oncogenic signals in tumor cells.

S100P –  S100 proteins are localized in the cytoplasm and/or nucleus of a wide range of cells, and involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation.  This protein may paly a role in the etiology of prostate cancer.

The authors (1b) found that overexpressing of these 4 genes increases the invasion and migration abilities of the SW620-control cells (= lymph node metastatic cell line) in vitro and also significantly enhances the frequency of hepatic metastasis in vivo (1b).

To determine the clinical correlation of our identified gene signatures with colorectal cancer hepatic metastasis, the authors examined the protein levels of APOBEC3GCD133LIPC, and S100P in 7 freshly isolated human colorectal cancer hepatic metastatic tumors and 7 nonmetastatic primary colorectal carcinomas. We showed that expression levels of these 4 genes are significantly increased in the metastatic tumors compared with the nonmetastatic primary tumors (1b).

Knocking down either one of these genes was not sufficient to decrease the liver metastasis rate in the orthotopic animal model, if compared with knocking down all 4 genes, indicating that the process of liver metastasis may require the cooperation/synergism of the 4 genes.

EGFR  was also identified to be a potential key player for liver metastases. There is somewhat conflicting data regarding the importance or use of EGF as an indicator for liver metasteses.  While some clinical protocols suggest patients with KRAS wild-type should be considered for combination therapy with EGFR inhibitors, because this strategy has led to promising results with improved R0 resection (2), others have shown that EGFR expression in the primary tumor site was not predictive of its level in the metastasis. EGFR expression levels in the primaries and in the metastases do not appear to be useful prognostic markers (3).

Additionally, recent studies also revealed that certain genes and signaling pathways might play a role in colon cancer liver metastasis. Metastasis-associated in colon cancer-1 (Macc1) was identified as a key regulator of HGF-MET signaling and is able to enhance colon cancer cell migration in vitro and liver metastasis in mouse model. TGF-β/Smad4 signaling was found to suppresses colon cancer metastasis in mice and the balance between Smad4/Smad7 and the TGF-β pathway in colorectal cancer may be critical for the metastatic process (1b).

Wulfkuhle and colleagues recently published an innovative study comparing the proteomic profiles of hepatic metastases generated by tumors from different primary organ sites. They strongly suggest that the microenviornment of the host organ plays a pivotal role in the activation of specific survival pathways (4).

The role of microenvironment and heterogeneity is reviewed by Bert Vogelstein  and colleagues in their outstanding paper on the Cancer Genome Landscape (5). They outline the multiplex orchestra of genes and their mutations that play role in cancer initiation, progressions and invasion into new metastatic niches,

In summary:

Many of the molecular pathways that promote tumorigenesis also promote metastasis and are important in the treatment of both aspects of cancer progression. This is a multiplex process that involves alternations/mutations in many genes and metastases, much like primary tumors, varies within a single patient and between patient.  The biology of liver metastases has been intensively investigated and several  genes where identified yet, one must remember that these set of gene may be true to one source of primary tumor origin and not not to another.  From a technical standpoint, the development of new and improved methods for early detection and prevention will not be easy, but there is no reason to assume that it will be more difficult than the development of new therapies aimed at treating widely metastatic disease. For further review on concurrent treatments for colorectal liver metastases, please go to liver metastases_treatments (I)

References:

1a. Patricia S Steeg, Dan Theodorescu. Metastasis: A Therapeutic Target for Cancer. Nat Clin Pract Oncol. 2008;5(4):206-219. http://www.medscape.com/viewarticle/571455_2.

1b. Qingqing Ding, Chun-Ju Chang, Xiaoming Xie, Weiya Xia, Jer-Yen Yang ,Shao-Chun Wang, Yan Wang, Jiahong Xia, Libo Chen, Changchun Cai, Huabin Li, Chia-Jui Yen, Hsu-Ping Kuo, Dung-Fang Lee, Jingyu Lang, Longfei Huo,Xiaoyun Cheng, Yun-Ju Chen, Chia-Wei Li, Long-Bin Jeng, Jennifer L. Hsu, Long-Yuan Li , Alai Tan, Steven A. Curley, Lee M. Ellis, Raymond N. DuBois and Mien-Chie Hung. APOBEC3G promotes liver metastasis in an orthotopic mouse model of colorectal cancer and predicts human hepatic metastasis. J Clin Invest. 2011;121(11):4526–4536. doi:10.1172/JCI45008. http://www.jci.org/articles/view/45008

2. Macelo R.S Cruz and Gilberto de Lima Lopes. Colon Cancer Liver Metastasis: Addition of Antiangiogenesis or EGFR Inhibitors to Chemotherapy. Current Colorectal Cancer Reports March 2013, 9(1); pp 68-73. http://link.springer.com/article/10.1007%2Fs11888-012-0148-z

3. Nirit Yarom N, Celia Marginean, Terence Moyana, Ivan Gorn-Hondermann , H. Chaim Birnboim, Horia Marginean, Rebecca C. Auer, Micheal Vickers, Timothy R. Asmis, Jean Maroun, Derek Jonker EGFR expression variance in paired colorectal cancer primary and metastatic tumors. Cancer Biol Ther 2010 Sep 1;10(5):416-421. https://www.landesbioscience.com/journals/cbt/article/12610/

4. Wulfkuhle J, Espina V, Liotta L, Petricoin E. Genomic and proteomic technologies for individualisation and improvement of cancer treatment. Eur J Cancer. 2004 Nov;40(17):2623-2632. http://www.ncbi.nlm.nih.gov/pubmed/15541963.

5. Bert Vogelstein, Nickolas Papadopoulos, Victor E. Velculescu, Shibin Zhou, Luis A. Diaz Jr., Kenneth W. Kinzler. Cancer Genome Landscapes. Science 29 March 2013:  Vol. 339 no. 6127 pp. 1546-1558  http://www.sciencemag.org/content/339/6127/1546.full

Other articles from our open access journal:

I. By Tilda Barliya PhD. Liver metastases_treatments. https://pharmaceuticalintelligence.com/2013/08/10/liver-metastasis/

II. By Tilda Barliya PhD. Cancer metastasis. https://pharmaceuticalintelligence.com/2013/07/06/cancer-metastasis/

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

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

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CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics – Part IIB

Curator: Larry H Bernstein, MD, FCAP

Part I: The Initiation and Growth of Molecular Biology and Genomics – Part I From Molecular Biology to Translational Medicine: How Far Have We Come, and Where Does It Lead Us?

https://pharmaceuticalintelligence.wordpress.com/wp-admin/post.php?post=8634&action=edit&message=1

Part II: CRACKING THE CODE OF HUMAN LIFE is divided into a three part series.

Part IIA. “CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way” reviews the Human Genome Project and the decade beyond.

https://pharmaceuticalintelligence.com/2013/02/12/cracking-the-code-of-human-life-milestones-along-the-way/

Part IIB. “CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics” lays the manifold multivariate systems analytical tools that has moved the science forward to a groung that ensures clinical application.

https://pharmaceuticalintelligence.com/2013/02/13/cracking-the-code-of-human-life-the-birth-of-bioinformatics-and-computational-genomics/

Part IIC. “CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease “ will extend the discussion to advances in the management of patients as well as providing a roadmap for pharmaceutical drug targeting.

https://pharmaceuticalintelligence.com/2013/02/14/cracking-the-code-of-human-life-recent-advances-in-genomic-analysis-and-disease/

To be followed by:
Part III will conclude with Ubiquitin, it’s role in Signaling and Regulatory Control.

Part IIB. “CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics” is a continuation of a previous discussion on the role of genomics in discovery of therapeutic targets titled, Directions for Genomics in Personalized Medicinewhich focused on:

  • key drivers of cellular proliferation,
  • stepwise mutational changes coinciding with cancer progression, and
  • potential therapeutic targets for reversal of the process.

It is a direct extension of The Initiation and Growth of Molecular Biology and Genomics – Part I 

These articles review a web-like connectivity between inter-connected scientific discoveries, as significant findings have led to novel hypotheses and many expectations over the last 75 years. This largely post WWII revolution has driven our understanding of biological and medical processes at an exponential pace owing to successive discoveries of
  • chemical structure,
  • the basic building blocks of DNA  and proteins, of
  • nucleotide and protein-protein interactions,
  • protein folding,
  • allostericity,
  • genomic structure,
  • DNA replication,
  • nuclear polyribosome interaction, and
  • metabolic control.

Nucleotides_1.svg

In addition, the emergence of methods for

  • copying,
  • removal
  • insertion, and
  • improvements in structural analysis
  • developments in applied mathematics have transformed the research framework.

This last point,

  • developments in applied mathematics have transformed the research framework, is been developed in this very article

CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics – Part IIB

Computational Genomics

1. Three-Dimensional Folding and Functional Organization Principles of The Drosophila Genome

Sexton T, Yaffe E, Kenigeberg E, Bantignies F,…Cavalli G. Institute de Genetique Humaine, Montpelliere GenomiX, and Weissman Institute, France and Israel. Cell 2012; 148(3): 458-472.
http://dx.doi.org/10.1016/j.cell.2012.01.010/
http://www.cell.com/retrieve/pii/S0092867412000165
http://www.ncbi.nlm.nih.gov/pubmed/22265598

Chromosomes are the physical realization of genetic information and thus form the basis for its readout and propagation.

250px-DNA_labeled  DNA diagram showing base pairing      circular genome map

Here we present a high-resolution chromosomal contact map derived from

  • a modified genome-wide chromosome conformation capture approach applied to Drosophila embryonic nuclei.
  • the entire genome is linearly partitioned into well-demarcated physical domains that overlap extensively with active and repressive epigenetic marks.
  • Chromosomal contacts are hierarchically organized between domains.
  • Global modeling of contact density and clustering of domains show that inactive
  • domains are condensed and confined to their chromosomal territories, whereas
  • active domains reach out of the territory to form remote intra- and interchromosomal contacts.

Moreover, we systematically identify

  • specific long-range intrachromosomal contacts between Polycomb-repressed domains.

Together, these observations

  • allow for quantitative prediction of the Drosophila chromosomal contact map,
  • laying the foundation for detailed studies of chromosome structure and function in a genetically tractable system.

fractal-globule

2A. Architecture Reveals Genome’s Secrets

Three-dimensional genome maps – Human chromosome

Genome sequencing projects have provided rich troves of information about

  • stretches of DNA that regulate gene expression, as well as
  • how different genetic sequences contribute to health and disease.

But these studies miss a key element of the genome—its spatial organization—which has long been recognized as an important regulator of gene expression.

  • Regulatory elements often lie thousands of base pairs away from their target genes, and recent technological advances are allowing scientists to begin examining
  • how distant chromosome locations interact inside a nucleus.
  • The creation and function of 3-D genome organization, some say, is the next frontier of genetics.

Mapping and sequencing may be completely separate processes. For example, it’s possible to determine the location of a gene—to “map” the gene—without sequencing it. Thus, a map may tell you nothing about the sequence of the genome, and a sequence may tell you nothing about the map.  But the landmarks on a map are DNA sequences, and mapping is the cousin of sequencing. A map of a sequence might look like this:
On this map, GCC is one landmark; CCCC is another. Here we find, the sequence is a landmark on a map. In general, particularly for humans and other species with large genomes,

  • creating a reasonably comprehensive genome map is quicker and cheaper than sequencing the entire genome.
  • mapping involves less information to collect and organize than sequencing does.

Completed in 2003, the Human Genome Project (HGP) was a 13-year project. The goals were:

  • identify all the approximately 20,000-25,000 genes in human DNA,
  • determine the sequences of the 3 billion chemical base pairs that make up human DNA,
  • store this information in databases,
  • improve tools for data analysis,
  • transfer related technologies to the private sector, and
  • address the ethical, legal, and social issues (ELSI) that may arise from the project.

Though the HGP is finished, analyses of the data will continue for many years. By licensing technologies to private companies and awarding grants for innovative research, the project catalyzed the multibillion-dollar U.S. biotechnology industry and fostered the development of new medical applications. When genes are expressed, their sequences are first converted into messenger RNA transcripts, which can be isolated in the form of complementary DNAs (cDNAs). A small portion of each cDNA sequence is all that is needed to develop unique gene markers, known as sequence tagged sites or STSs, which can be detected using the polymerase chain reaction (PCR). To construct a transcript map, cDNA sequences from a master catalog of human genes were distributed to mapping laboratories in North America, Europe, and Japan. These cDNAs were converted to STSs and their physical locations on chromosomes determined on one of two radiation hybrid (RH) panels or a yeast artificial chromosome (YAC) library containing human genomic DNA. This mapping data was integrated relative to the human genetic map and then cross-referenced to cytogenetic band maps of the chromosomes. (Further details are available in the accompanying article in the 25 October issue of SCIENCE).

Tremendous progress has been made in the mapping of human genes, a major milestone in the Human Genome Project. Apart from its utility in advancing our understanding of the genetic basis of disease, it  provides a framework and focus for accelerated sequencing efforts by highlighting key landmarks (gene-rich regions) of the chromosomes. The construction of this map has been possible through the cooperative efforts of an international consortium of scientists who provide equal, full and unrestricted access to the data for the advancement of biology and human health.

There are two types of maps: genetic linkage map and physical map. The genetic linkage map shows the arrangement of genes and genetic markers along the chromosomes as calculated by the frequency with which they are inherited together. The physical map is representation of the chromosomes, providing the physical distance between landmarks on the chromosome, ideally measured in nucleotide bases. Physical maps can be divided into three general types: chromosomal or cytogenetic maps, radiation hybrid (RH) maps, and sequence maps.
 ch10f3  radiation hybrid maps   ch10f2  subchromosomal mapping

2B. Genome-nuclear lamina interactions and gene regulation.

Kind J, van Steensel B. Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, The Netherlands.
The nuclear lamina, a filamentous protein network that coats the inner nuclear membrane, has long been thought to interact with specific genomic loci and regulate their expression. Molecular mapping studies have now identified
  • large genomic domains that are in contact with the lamina.
Genes in these domains are typically repressed, and artificial tethering experiments indicate that
  • the lamina can actively contribute to this repression.
Furthermore, the lamina indirectly controls gene expression in the nuclear interior by sequestration of certain transcription factors.
Mol Cell. 2010; 38(4):603-13.          http://dx.doi.org/10.1016/j.molcel.2010.03.016
Peric-Hupkes D, Meuleman W, Pagie L, Bruggeman SW, Solovei I,  …., van Steensel B.  Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, The Netherlands.
To visualize three-dimensional organization of chromosomes within the nucleus, we generated high-resolution maps of genome-nuclear lamina interactions during subsequent differentiation of mouse embryonic stem cells via lineage-committed neural precursor cells into terminally differentiated astrocytes.  A basal chromosome architecture present in embryonic stem cells is cumulatively altered at hundreds of sites during lineage commitment and subsequent terminal differentiation. This remodeling involves both
  • individual transcription units and multigene regions and
  • affects many genes that determine cellular identity.
  •  genes that move away from the lamina are concomitantly activated;
  • others, remain inactive yet become unlocked for activation in a next differentiation step.

lamina-genome interactions are widely involved in the control of gene expression programs during lineage commitment and terminal differentiation.

 view the full text on ScienceDirect.
Graphical Summary
PDF 1.54 MB
Referred to by: The Silence of the LADs: Dynamic Genome-…
Authors:  Daan Peric-Hupkes, Wouter Meuleman, Ludo Pagie, Sophia W.M. Bruggeman, et al.
Highlights
  • Various cell types share a core architecture of genome-nuclear lamina interactions
  • During differentiation, hundreds of genes change their lamina interactions
  • Changes in lamina interactions reflect cell identity
  • Release from the lamina may unlock some genes for activation

Fractal “globule”

About 10 years ago—just as the human genome project was completing its first draft sequence—Dekker pioneered a new technique, called chromosome conformation capture (C3) that allowed researchers to get a glimpse of how chromosomes are arranged relative to each other in the nucleus. The technique relies on the physical cross-linking of chromosomal regions that lie in close proximity to one another. The regions are then sequenced to identify which regions have been cross-linked. In 2009, using a high throughput version of this basic method, called Hi-C, Dekker and his collaborators discovered that the human genome appears to adopt a “fractal globule” conformation—

  • a manner of crumpling without knotting.

gabst_EK.pptx

In the last 3 years, Jobe Dekker and others have advanced technology even further, allowing them to paint a more refined picture of how the genome folds—and how this influences gene expression and disease states.  Dekker’s 2009 findings were a breakthrough in modeling genome folding, but the resolution—about 1 million base pairs— was too crude to allow scientists to really understand how genes interacted with specific regulatory elements. The researchers report two striking findings.

First, the human genome is organized into two separate compartments, keeping

  • active genes separate and accessible
  • while sequestering unused DNA in a denser storage compartment.
  • Chromosomes snake in and out of the two compartments repeatedly
  • as their DNA alternates between active, gene-rich and inactive, gene-poor stretches.

Second, at a finer scale, the genome adopts an unusual organization known in mathematics as a “fractal.” The specific architecture the scientists found, called

  • a “fractal globule,” enables the cell to pack DNA incredibly tightly —

the information density in the nucleus is trillions of times higher than on a computer chip — while avoiding the knots and tangles that might interfere with the cell’s ability to read its own genome. Moreover, the DNA can easily Unfold and Refold during

  • gene activation,
  • gene repression, and
  • cell replication.

Dekker and his colleagues discovered, for example, that chromosomes can be divided into folding domains—megabase-long segments within which

  • genes and regulatory elements associate more often with one another than with other chromosome sections.

The DNA forms loops within the domains that bring a gene into close proximity with a specific regulatory element at a distant location along the chromosome. Another group, that of molecular biologist Bing Ren at the University of California, San Diego, published a similar finding in the same issue of Nature.  Dekker thinks the discovery of [folding] domains will be one of the most fundamental [genetics] discoveries of the last 10 years. The big questions now are

  • how these domains are formed, and
  • what determines which elements are looped into proximity.

“By breaking the genome into millions of pieces, we created a spatial map showing how close different parts are to one another,” says co-first author Nynke van Berkum, a postdoctoral researcher at UMass Medical School in Dekker‘s laboratory. “We made a fantastic three-dimensional jigsaw puzzle and then, with a computer, solved the puzzle.”

Lieberman-Aiden, van Berkum, Lander, and Dekker’s co-authors are Bryan R. Lajoie of UMMS; Louise Williams, Ido Amit, and Andreas Gnirke of the Broad Institute; Maxim Imakaev and Leonid A. Mirny of MIT; Tobias Ragoczy, Agnes Telling, and Mark Groudine of the Fred Hutchison, Cancer Research Center and the University of Washington; Peter J. Sabo, Michael O. Dorschner, Richard Sandstrom, M.A. Bender, and John Stamatoyannopoulos of the University of Washington; and Bradley Bernstein of the Broad Institute and Harvard Medical School.

2C. three-dimensional structure of the human genome

Lieberman-Aiden et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 2009; DOI: 10.1126/science.1181369.
Harvard University (2009, October 11). 3-D Structure Of Human Genome: Fractal Globule Architecture Packs Two Meters Of DNA Into Each Cell. ScienceDaily.   Retrieved February 2, 2013, from        http://www.sciencedaily.com/releases/2009/10/091008142957

Using a new technology called Hi-C and applying it to answer the thorny question of how each of our cells stows some three billion base pairs of DNA while maintaining access to functionally crucial segments. The paper comes from a team led by scientists at Harvard University, the Broad Institute of Harvard and MIT, University of Massachusetts Medical School, and the Massachusetts Institute of Technology. “We’ve long known that on a small scale, DNA is a double helix,” says co-first author Erez Lieberman-Aiden, a graduate student in the Harvard-MIT Division of Health Science and Technology and a researcher at Harvard’s School of Engineering and Applied Sciences and in the laboratory of Eric Lander at the Broad Institute. “But if the double helix didn’t fold further, the genome in each cell would be two meters long. Scientists have not really understood how the double helix folds to fit into the nucleus of a human cell, which is only about a hundredth of a millimeter in diameter. This new approach enabled us to probe exactly that question.”

The mapping technique that Aiden and his colleagues have come up with bridges a crucial gap in knowledge—between what goes on at the smallest levels of genetics (the double helix of DNA and the base pairs) and the largest levels (the way DNA is gathered up into the 23 chromosomes that contain much of the human genome). The intermediate level, on the order of thousands or millions of base pairs, has remained murky.  As the genome is so closely wound, base pairs in one end can be close to others at another end in ways that are not obvious merely by knowing the sequence of base pairs. Borrowing from work that was started in the 1990s, Aiden and others have been able to figure out which base pairs have wound up next  to one another. From there, they can begin to reconstruct the genome—in three dimensions.

4C profiles validate the Hi-C Genome wide map

Even as the multi-dimensional mapping techniques remain in their early stages, their importance in basic biological research is becoming ever more apparent. “The three-dimensional genome is a powerful thing to know,” Aiden says. “A central mystery of biology is the question of how different cells perform different functions—despite the fact that they share the same genome.” How does a liver cell, for example, “know” to perform its liver duties when it contains the same genome as a cell in the eye? As Aiden and others reconstruct the trail of letters into a three-dimensional entity, they have begun to see that “the way the genome is folded determines which genes were

2D. “Mr. President; The Genome is Fractal !”

Eric Lander (Science Adviser to the President and Director of Broad Institute) et al. delivered the message on Science Magazine cover (Oct. 9, 2009) and generated interest in this by the International HoloGenomics Society at a Sept meeting.

First, it may seem to be trivial to rectify the statement in “About cover” of Science Magazine by AAAS.

  • The statement “the Hilbert curve is a one-dimensional fractal trajectory” needs mathematical clarification.

The mathematical concept of a Hilbert space, named after David Hilbert, generalizes the notion of Euclidean space. It extends the methods of vector algebra and calculus from the two-dimensional Euclidean plane and three-dimensional space to spaces with any finite or infinite number of dimensions. A Hilbert space is an abstract vector space possessing the structure of an inner product that allows length and angle to be measured. Furthermore, Hilbert spaces must be complete, a property that stipulates the existence of enough limits in the space to allow the techniques of calculus to be used. A Hilbert curve (also known as a Hilbert space-filling curve) is a continuous fractal space-filling curve first described by the German mathematician David Hilbert in 1891,[1] as a variant of the space-filling curves discovered by Giuseppe Peano in 1890.[2] For multidimensional databases, Hilbert order has been proposed to be used instead of Z order because it has better locality-preserving behavior.

Representation as Lindenmayer system
The Hilbert Curve can be expressed by a rewrite system (L-system).

Alphabet : A, B

Constants : F + –                                                                                                                                      119px-Hilbert3d-step3                             120px-Hilbert512

Axiom : A

Production rules:

A → – B F + A F A + F B –

B → + A F – B F B – F A +

Here, F means “draw forward”, – means “turn left 90°”, and + means “turn right 90°” (see turtle graphics).

620px-Harmonic_partials_on_strings.svg

While the paper itself does not make this statement, the new Editorship of the AAAS Magazine might be even more advanced if the previous Editorship did not reject (without review) a Manuscript by 20+ Founders of (formerly) International PostGenetics Society in December, 2006.

Second, it may not be sufficiently clear for the reader that the reasonable requirement for the DNA polymerase to crawl along a “knot-free” (or “low knot”) structure does not need fractals. A “knot-free” structure could be spooled by an ordinary “knitting globule” (such that the DNA polymerase does not bump into a “knot” when duplicating the strand; just like someone knitting can go through the entire thread without encountering an annoying knot): Just to be “knot-free” you don’t need fractals. Note, however, that

  • the “strand” can be accessed only at its beginning – it is impossible to e.g. to pluck a segment from deep inside the “globulus”.

This is where certain fractals provide a major advantage – that could be the “Eureka” moment for many readers. For instance,

  • the mentioned Hilbert-curve is not only “knot free” –
  • but provides an easy access to “linearly remote” segments of the strand.

If the Hilbert curve starts from the lower right corner and ends at the lower left corner, for instance

  • the path shows the very easy access of what would be the mid-point
  • if the Hilbert-curve is measured by the Euclidean distance along the zig-zagged path.

Likewise, even the path from the beginning of the Hilbert-curve is about equally easy to access – easier than to reach from the origin a point that is about 2/3 down the path. The Hilbert-curve provides an easy access between two points within the “spooled thread”; from a point that is about 1/5 of the overall length to about 3/5 is also in a “close neighborhood”.

This may be the “Eureka-moment” for some readers, to realize that

  • the strand of “the Double Helix” requires quite a finess to fold into the densest possible globuli (the chromosomes) in a clever way
  • that various segments can be easily accessed. Moreover, in a way that distances between various segments are minimized.

This marvellous fractal structure is illustrated by the 3D rendering of the Hilbert-curve. Once you observe such fractal structure, you’ll never again think of a chromosome as a “brillo mess”, would you? It will dawn on you that the genome is orders of magnitudes more finessed than we ever thought so.

Those embarking at a somewhat complex review of some historical aspects of the power of fractals may wish to consult the ouvre of Mandelbrot (also, to celebrate his 85th birthday). For the more sophisticated readers, even the fairly simple Hilbert-curve (a representative of the Peano-class) becomes even more stunningly brilliant than just some “see through density”. Those who are familiar with the classic “Traveling Salesman Problem” know that “the shortest path along which every given n locations can be visited once, and only once” requires fairly sophisticated algorithms (and tremendous amount of computation if n>10 (or much more). Some readers will be amazed, therefore, that for n=9 the underlying Hilbert-curve helps to provide an empirical solution.

refer to pellionisz@junkdna.com

Briefly, the significance of the above realization, that the (recursive) Fractal Hilbert Curve is intimately connected to the (recursive) solution of TravelingSalesman Problem, a core-concept of Artificial Neural Networks can be summarized as below.

Accomplished physicist John Hopfield (already a member of the National Academy of Science) aroused great excitement in 1982 with his (recursive) design of artificial neural networks and learning algorithms which were able to find reasonable solutions to combinatorial problems such as the Traveling SalesmanProblem. (Book review Clark Jeffries, 1991, see also 2. J. Anderson, R. Rosenfeld, and A. Pellionisz (eds.), Neurocomputing 2: Directions for research, MIT Press, Cambridge, MA, 1990):

“Perceptions were modeled chiefly with neural connections in a “forward” direction: A -> B -* C — D. The analysis of networks with strong backward coupling proved intractable. All our interesting results arise as consequences of the strong back-coupling” (Hopfield, 1982).

The Principle of Recursive Genome Function surpassed obsolete axioms that blocked, for half a Century, entry of recursive algorithms to interpretation of the structure-and function of (Holo)Genome.  This breakthrough, by uniting the two largely separate fields of Neural Networks and Genome Informatics, is particularly important for

  • those who focused on Biological (actually occurring) Neural Networks (rather than abstract algorithms that may not, or because of their core-axioms, simply could not
  • represent neural networks under the governance of DNA information).

DNA base triplets

3A. The FractoGene Decade

from Inception in 2002 to Proofs of Concept and Impending Clinical Applications by 2012

  1. Junk DNA Revisited (SF Gate, 2002)
  2. The Future of Life, 50th Anniversary of DNA (Monterey, 2003)
  3. Mandelbrot and Pellionisz (Stanford, 2004)
  4. Morphogenesis, Physiology and Biophysics (Simons, Pellionisz 2005)
  5. PostGenetics; Genetics beyond Genes (Budapest, 2006)
  6. ENCODE-conclusion (Collins, 2007)

The Principle of Recursive Genome Function (paper, YouTube, 2008)

  1. Cold Spring Harbor presentation of FractoGene (Cold Spring Harbor, 2009)
  2. Mr. President, the Genome is Fractal! (2009)
  3. HolGenTech, Inc. Founded (2010)
  4. Pellionisz on the Board of Advisers in the USA and India (2011)
  5. ENCODE – final admission (2012)
  6. Recursive Genome Function is Clogged by Fractal Defects in Hilbert-Curve (2012)
  7. Geometric Unification of Neuroscience and Genomics (2012)
  8. US Patent Office issues FractoGene 8,280,641 to Pellionisz (2012)

http://www.junkdna.com/the_fractogene_decade.pdf
http://www.scribd.com/doc/116159052/The-Decade-of-FractoGene-From-Discovery-to-Utility-Proofs-of-Concept-Open-Genome-Based-Clinical-Applications
http://fractogene.com/full_genome/morphogenesis.html

When the human genome was first sequenced in June 2000, there were two pretty big surprises. The first was thathumans have only about 30,000-40,000 identifiable genes, not the 100,000 or more many researchers were expecting. The lower –and more humbling — number

  • means humans have just one-third more genes than a common species of worm.

The second stunner was

  • how much human genetic material — more than 90 percent — is made up of what scientists were calling “junk DNA.”

The term was coined to describe similar but not completely identical repetitive sequences of amino acids (the same substances that make genes), which appeared to have no function or purpose. The main theory at the time was that these apparently non-working sections of DNA were just evolutionary leftovers, much like our earlobes.

If biophysicist Andras Pellionisz is correct, genetic science may be on the verge of yielding its third — and by far biggest — surprise.

With a doctorate in physics, Pellionisz is the holder of Ph.D.’s in computer sciences and experimental biology from the prestigious Budapest Technical University and the Hungarian National Academy of Sciences. A biophysicist by training, the 59-year-old is a former research associate professor of physiology and biophysics at New York University, author of numerous papers in respected scientific journals and textbooks, a past winner of the prestigious Humboldt Prize for scientific research, a former consultant to NASA and holder of a patent on the world’s first artificial cerebellum, a technology that has already been integrated into research on advanced avionics systems. Because of his background, the Hungarian-born brain researcher might also become one of the first people to successfully launch a new company by using the Internet to gather momentum for a novel scientific idea.

The genes we know about today, Pellionisz says, can be thought of as something similar to machines that make bricks (proteins, in the case of genes), with certain junk-DNA sections providing a blueprint for the different ways those proteins are assembled. The notion that at least certain parts of junk DNA might have a purpose for example, many researchers now refer to with a far less derogatory term: introns.

In a provisional patent application filed July 31, Pellionisz claims to have unlocked a key to the hidden role junk DNA plays in growth — and in life itself. His patent application covers all attempts to count, measure and compare the fractal properties of introns for diagnostic and therapeutic purposes.

3B. The Hidden Fractal Language of Intron DNA

To fully understand Pellionisz’ idea, one must first know what a fractal is.

Fractals are a way that nature organizes matter. Fractal patterns can be found in anything that has a nonsmooth surface (unlike a billiard ball), such as coastal seashores, the branches of a tree or the contours of a neuron (a nerve cell in the brain). Some, but not all, fractals are self-similar and stop repeating their patterns at some stage; the branches of a tree, for example, can get only so small. Because they are geometric, meaning they have a shape, fractals can be described in mathematical terms. It’s similar to the way a circle can be described by using a number to represent its radius (the distance from its center to its outer edge). When that number is known, it’s possible to draw the circle it represents without ever having seen it before.

Although the math is much more complicated, the same is true of fractals. If one has the formula for a given fractal, it’s possible to use that formula

  • to construct, or reconstruct,
  • an image of whatever structure it represents,
  • no matter how complicated.

The mysteriously repetitive but not identical strands of genetic material are in reality building instructions organized in a special type

  • of pattern known as a fractal.  It’s this pattern of fractal instructions, he says, that
  • tells genes what they must do in order to form living tissue,
  • everything from the wings of a fly to the entire body of a full-grown human.

In a move sure to alienate some scientists, Pellionisz has chosen the unorthodox route of making his initial disclosures online on his own Web site. He picked that strategy, he says, because it is the fastest way he can document his claims and find scientific collaborators and investors. Most mainstream scientists usually blanch at such approaches, preferring more traditionally credible methods, such as publishing articles in peer-reviewed journals.

Basically, Pellionisz’ idea is that a fractal set of building instructions in the DNA plays a similar role in organizing life itself. Decode the way that language works, he says, and in theory it could be reverse engineered. Just as knowing the radius of a circle lets one create that circle, the more complicated fractal-based formula would allow us to understand how nature creates a heart or simpler structures, such as disease-fighting antibodies. At a minimum, we’d get a far better understanding of how nature gets that job done.

The complicated quality of the idea is helping encourage new collaborations across the boundaries that sometimes separate the increasingly intertwined disciplines of biology, mathematics and computer sciences.

Hal Plotkin, Special to SF Gate. Thursday, November 21, 2002.                          http://www.junkdna.com/Special to SF Gate/plotkin.htm (1 of 10)2012.12.13. 12:11:58/

fractogene_2002

3C. multifractal analysis

The human genome: a multifractal analysis. Moreno PA, Vélez PE, Martínez E, et al.

BMC Genomics 2011, 12:506. http://www.biomedcentral.com/1471-2164/12/506

Background: Several studies have shown that genomes can be studied via a multifractal formalism. Recently, we used a multifractal approach to study the genetic information content of the Caenorhabditis elegans genome. Here we investigate the possibility that the human genome shows a similar behavior to that observed in the nematode.
Results: We report here multifractality in the human genome sequence. This behavior correlates strongly on the

  • presence of Alu elements and
  • to a lesser extent on CpG islands and (G+C) content.

In contrast, no or low relationship was found for LINE, MIR, MER, LTRs elements and DNA regions poor in genetic information.

  • Gene function,
  • cluster of orthologous genes,
  • metabolic pathways, and
  • exons tended to increase their frequencies with ranges of multifractality and
  • large gene families were located in genomic regions with varied multifractality.

Additionally, a multifractal map and classification for human chromosomes are proposed.

Conclusions

we propose a descriptive non-linear model for the structure of the human genome,

This model reveals

  • a multifractal regionalization where many regions coexist that are far from equilibrium and
  • this non-linear organization has significant molecular and medical genetic implications for understanding the role of
  • Alu elements in genome stability and structure of the human genome.

Given the role of Alu sequences in

  • gene regulation,
  • genetic diseases,
  • human genetic diversity,
  • adaptation
  • and phylogenetic analyses,

these quantifications are especially useful.

MiIP: The Monomer Identification and Isolation Program

Bun C, Ziccardi W, Doering J and Putonti C.Evolutionary Bioinformatics 2012:8 293-300.    http://dx.goi.org/10.4137/EBO.S9248

Repetitive elements within genomic DNA are both functionally and evolutionarilly informative. Discovering these sequences ab initio is

  • computationally challenging, compounded by the fact that
  • sequence identity between repetitive elements can vary significantly.

Here we present a new application, the Monomer Identification and Isolation Program (MiIP), which provides functionality to both

  • search for a particular repeat as well as
  • discover repetitive elements within a larger genomic sequence.

To compare MiIP’s performance with other repeat detection tools, analysis was conducted for

  • synthetic sequences as well as
  • several a21-II clones and
  • HC21 BAC sequences.

The primary benefit of MiIP is the fact that it is a single tool capable of searching for both

  • known monomeric sequences as well as
  • discovering the occurrence of repeats ab initio, per the user’s required sensitivity of the search.

Methods for Examining Genomic and Proteomic Interactions

1. An Integrated Statistical Approach to Compare Transcriptomics Data Across Experiments: A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARα

Ullah MO, Müller M and Hooiveld GJEJ. Bioinformatics and Biology Insights 2012:6 145–154.       http://dx.doi.org/10.4137/BBI.S9529

http://www.la- press.com/
http://bionformaticsandBiologyInsights.com/An_Integrated_Statistical_Approach_to_Compare_ transcriptomic_Data_Across_Experiments-A-Case_Study_on_the_Identification_ of_Candidate_Target_Genes_of_the Transcription_Factor_PPARα/
Corresponding author email: guido.hooiveld@wur.nl

An effective strategy to elucidate the signal transduction cascades activated by a transcription factor is to compare the transcriptional profiles of wild type and transcription factor knockout models. Many statistical tests have been proposed for analyzing gene expression data, but most

  • tests are based on pair-wise comparisons. Since the analysis of microarrays involves the testing of multiple hypotheses within one study, it is
  • generally accepted that one should control for false positives by the false discovery rate (FDR). However, it has been reported that
  • this may be an inappropriate metric for comparing data across different experiments.

Here we propose an approach that addresses the above mentioned problem by the simultaneous testing and integration of the three hypotheses (contrasts) using the cell means ANOVA model.

These three contrasts test for the effect of

  • a treatment in wild type,
  • gene knockout, and
  • globally over all experimental groups.

We illustrate our approach on microarray experiments that focused on the identification of candidate target genes and biological processes governed by the fatty acid sensing transcription factor PPARα in liver. Compared to the often applied FDR based across experiment comparison, our approach identified a conservative but less noisy set of candidate genes with same sensitivity and specificity. However, our method had the advantage of

  • properly adjusting for multiple testing while
  • integrating data from two experiments, and
  • was driven by biological inference.

We present a simple, yet efficient strategy to compare

  • differential expression of genes across experiments
  • while controlling for multiple hypothesis testing.

2. Managing biological complexity across orthologs with a visual knowledgebase of documented biomolecular interactions

Vincent VanBuren & Hailin Chen.   Scientific Reports 2, Article number: 1011  Received 02 October 2012 Accepted 04 December 2012 Published 20 December 2012
http://dx.doi.org/10.1038/srep01011

The complexity of biomolecular interactions and influences is a major obstacle to their comprehension and elucidation. Visualizing knowledge of biomolecular interactions increases comprehension and facilitates the development of new hypotheses. The rapidly changing landscape of high-content experimental results also presents a challenge for the maintenance of comprehensive knowledgebases. Distributing the responsibility for maintenance of a knowledgebase to a community of subject matter experts is an effective strategy for large, complex and rapidly changing knowledgebases.
Cognoscente serves these needs by

  • building visualizations for queries of biomolecular interactions on demand,
  • by managing the complexity of those visualizations, and
  • by crowdsourcing to promote the incorporation of current knowledge from the literature.

Imputing functional associations between biomolecules and imputing directionality of regulation for those predictions each

  • require a corpus of existing knowledge as a framework to build upon. Comprehension of the complexity of this corpus of knowledge
  • will be facilitated by effective visualizations of the corresponding biomolecular interaction networks.

Cognoscente

http://vanburenlab.medicine.tamhsc.edu/cognoscente.html
was designed and implemented to serve these roles as

  • a knowledgebase and
  • as an effective visualization tool for systems biology research and education.

Cognoscente currently contains over 413,000 documented interactions, with coverage across multiple species.  Perl, HTML, GraphViz1, and a MySQL database were used in the development of Cognoscente. Cognoscente was motivated by the need to

  • update the knowledgebase of biomolecular interactions at the user level, and
  • flexibly visualize multi-molecule query results for heterogeneous interaction types across different orthologs.

Satisfying these needs provides a strong foundation for developing new hypotheses about regulatory and metabolic pathway topologies.  Several existing tools provide functions that are similar to Cognoscente, so we selected several popular alternatives to

  • assess how their feature sets compare with Cognoscente ( Table 1 ). All databases assessed had
  • easily traceable documentation for each interaction, and
  • included protein-protein interactions in the database.

Most databases, with the exception of BIND,

  • provide an open-access database that can be downloaded as a whole.

Most databases, with the exceptions of EcoCyc and HPRD, provide

  • support for multiple organisms.

Most databases support web services for interacting with the database contents programatically, whereas this is a planned feature for Cognoscente.

  • INT, STRING, IntAct, EcoCyc, DIP and Cognoscente provide built-in visualizations of query results,
  • which we consider among the most important features for facilitating comprehension of query results.
  • BIND supports visualizations via Cytoscape. Cognoscente is among a few other tools that support multiple organisms in the same query,
  • protein->DNA interactions, and
  • multi-molecule queries.

Cognoscente has planned support for small molecule interactants (i.e. pharmacological agents).  MINT, STRING, and IntAct provide a prediction (i.e. score) of functional associations, whereas
Cognoscente does not currently support this. Cognoscente provides support for multiple edge encodings to visualize different types of interactions in the same display,

  • a crowdsourcing web portal that allows users to submit interactions
  • that are then automatically incorporated in the knowledgebase, and displays orthologs as compound nodes to provide clues about potential
  • orthologous interactions.

The main strengths of Cognoscente are that

  1. it provides a combined feature set that is superior to any existing database,
  2. it provides a unique visualization feature for orthologous molecules, and relatively unique support for
  3. multiple edge encodings,
  4. crowdsourcing, and
  5. connectivity parameterization.

The current weaknesses of Cognoscente relative to these other tools are

  • that it does not fully support web service interactions with the database,
  • it does not fully support small molecule interactants, and
  • it does not score interactions to predict functional associations.

Web services and support for small molecule interactants are currently under development.

Other related articles on thie Open Access Online Sceintific Journal, include the following:

Big Data in Genomic Medicine                    lhb                          https://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair S Saha                                                                                   https://pharmaceuticalintelligence.com/2012/12/04/brca1-a-tumour-suppressor-in-breast-and-ovarian-cancer-functions-in-transcription-ubiquitination-and-dna-repair/

Computational Genomics Center: New Unification of Computational Technologies at Stanford A Lev-Ari    https://pharmaceuticalintelligence.com/2012/12/03/computational-genomics-center-new-unification-of-computational-technologies-at-stanford/

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1 (pharmaceuticalintelligence.com) A Lev-Ari https://pharmaceuticalintelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2 A Lev-Ari
https://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-drug-selection-in-cancer-personalized-treatment-part-2/

Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3 A Lev-Ari https://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-research-part-3/

GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico effect of the inhibitor in its “virtual clinical trial” A Lev-Ari    https://pharmaceuticalintelligence.com/2012/11/14/gsk-for-personalized-medicine-using-cancer-drugs-needs-alacris-systems-biology-model-to-determine-the-in-silico-effect-of-the-inhibitor-in-its-virtual-clinical-trial/

Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in serous endometrial tumors S Saha
https://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-and-ubiquitin-ligase-complex-genes-in-serous-endometrial-tumors/

Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence A Lev-Ari

https://pharmaceuticalintelligence.com/2012/11/24/human-variome-project-encyclopedic-catalog-of-sequence-variants-indexed-to-the-human-genome-sequence/

Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition sjwilliams
https://pharmaceuticalintelligence.com/2012/11/30/histone-deacetylase-inhibitors-induce-epithelial-to-mesenchymal-transition-in-prostate-cancer-cells/

https://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-of-dna-wcrick-41953/

Directions for genomics in personalized medicine lhb https://pharmaceuticalintelligence.com/2013/01/27/directions-for-genomics-in-personalized-medicine/

How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis. Sjwilliams
https://pharmaceuticalintelligence.com/2012/10/31/how-mobile-elements-in-junk-dna-prote-cancer-part1-transposon-mediated-tumorigenesis/

Mitochondrial fission and fusion: potential therapeutic targets? Ritu saxena    https://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

Mitochondrial mutation analysis might be “1-step” away ritu saxena  https://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

mRNA interference with cancer expression lhb https://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

Expanding the Genetic Alphabet and linking the genome to the metabolome https://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-metabolome/

Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression Analysis A Lev-Ari

https://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-histopathology-and-gene-expression-analysis/

Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis lhb https://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-proteolysis-and-cell-apoptosis/

Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology A Lev-Ari https://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-agricultural-biotechnology/

2013 Genomics: The Era Beyond the Sequencing Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.  https://pharmaceuticalintelligence.com/2013_Genomics

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1 https://pharmaceuticalintelligence.com/Paradigm Shift in Human Genomics_/

English: DNA replication or DNA synthesis is t...

English: DNA replication or DNA synthesis is the process of copying a double-stranded DNA molecule. This process is paramount to all life as we know it. (Photo credit: Wikipedia)

Français : Deletion chromosomique

Français : Deletion chromosomique (Photo credit: Wikipedia)

A slight mutation in the matched nucleotides c...

A slight mutation in the matched nucleotides can lead to chromosomal aberrations and unintentional genetic rearrangement. (Photo credit: Wikipedia)

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