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Archive for the ‘Drug Toxicity’ Category


Real Time Coverage and eProceedings of Presentations on 9/19-9/21 @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

Curator: Aviva Lev-Ari, PhD, RN

 

LIVE 9/19 8AM – 10AM USING CRISPR/Cas9 FOR FUNCTIONAL SCREENING at CHI’s 2nd Annual Symposium CRISPR: Mechanisms and Applications @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/19/live-919-8am-10am-using-crisprcas9-for-functional-screening-at-chis-2nd-annual-symposium-crispr-mechanisms-and-applications-chis-14th-discovery-on-target-919-9222/

 

LIVE 9/19 9:40 – noon CRISPR Engineering Lymphoma Lines & Will Interference from CRISPR Silence RNAi? CHI’s 2nd Annual Symposium CRISPR: Mechanisms and Applications @ CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/19/live-919-940-noon-crispr-engineering-lymphoma-lines-will-interference-from-crispr-silence-rnai-chis-2nd-annual-symposium-crispr-mechanisms-and-applications-chis-14th/

 

LIVE 9/19 1:40 – 3:20 EMERGING APPLICATIONS OF CRISPR/CAS9 at CHI’s 2nd Annual Symposium CRISPR: Mechanisms and Applications @ CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/19/live-919-140-320-emerging-applications-of-crisprcas9-at-chis-2nd-annual-symposium-crispr-mechanisms-and-applications-chis-14th-discovery-on-target-919-9222016/

 

LIVE 9/19 4PM – 5:30PM NK CELL-BASED CANCER IMMUNOTHERAPY @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/19/live-919-4pm-530pm-nk-cell-based-cancer-immunotherapy-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-boston/

 

LIVE 9/20 8AM to noon GENE THERAPIES BREAKTHROUGHS at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/20/live-920-8am-to-noon-gene-therapies-breakthroughs-at-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-boston/

 

LIVE 9/20 2PM to 5:30PM New Viruses for Therapeutic Gene Delivery at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/20/live-920-2pm-to-530pm-new-viruses-for-therapeutic-gene-delivery-at-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-boston/

 

LIVE 9/21 8AM to 10:55 AM Expoloring the Versatility of CRISPR/Cas9 at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/21/live-921-8am-to-1055-am-expoloring-the-versatility-of-crisprcas9-at-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-boston/

 

LIVE 9/21 8AM to 2:40PM Targeting Cardio-Metabolic Diseases: A focus on Liver Fibrosis and NASH Targets at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/21/live-921-8am-to-240pm-targeting-cardio-metabolic-diseases-a-focus-on-liver-fibrosis-and-nash-targets-at-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-b/

 

LIVE 9/21 12:50 pm Plenary Keynote Program at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/21/live-921-1250-pm-plenary-keynote-program-at-chis-14th-discovery-on-target-919-9222016-westin-boston-waterfront-boston/

 

LIVE 9/21 3:20PM to 6:40PM KINASE INHIBITORS FOR CANCER IMMUNOTHERAPY COMBINATIONS & KINASE INHIBITORS FOR AUTOIMMUNE AND INFLAMMATORY DISEASES at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

https://pharmaceuticalintelligence.com/2016/09/21/live-921-320pm-to-640pm-kinase-inhibitors-for-cancer-immunotherapy-combinations-kinase-inhibitors-for-autoimmune-and-inflammatory-diseases-at-chis-14th-discovery-on-target-919/

 

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GE Healthcare has acquired Biosafe Group SA, a supplier of Integrated Cell Bioprocessing Systems for Cell Therapy and Regenerative Medicine Industry

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Researchers of University of Texas at San Antonio, USA, have developed a new, non-invasive method which can kill cancer cells in two hours, an advance that may significantly help people with inoperable or hard-to-reach tumours, as well as young children stricken with the deadly disease.

 

The method involves injecting a chemical compound, nitrobenzaldehyde, into the tumour and allowing it to diffuse into the tissue. A beam of light is then aimed at the tissue, causing the cells to become very acidic inside and, essentially, commit suicide. Within two hours, up to 95 per cent of the targeted cancer cells are estimated to be dead.

 

The method was tested against triple negative breast cancer, one of the most aggressive types of cancer and one of the hardest to treat. The prognosis for triple negative breast cancer is usually very poor. One treatment in the laboratory was able to stop the tumour from growing and doubled the chances of survival in the mice.

 

According to the researchers all forms of cancer attempt to make cells acidic on the outside and attract the attention of blood vessels as an attempt to get rid of the acid. But, instead, the cancer cells latches onto the blood vessel and uses it to make the tumour grow bigger.

 

Chemotherapy treatments target all cells in the body, and certain chemotherapeutics try to keep cancer cells acidic as a way to kill the cancer. This is what causes many cancer patients to lose their hair and become weak. This method however, is more precise and can target just the tumour.

 

This research is presently extended on drug-resistant cancer cells to make this therapy as strong as possible. The researchers also started to develop a nanoparticle that can be injected into the body to target metastasised cancer cells. The nanoparticle is activated with a wavelength of light which can pass harmlessly through skin, flesh and bone and still activate the nanoparticle.

 

This non-invasive method will help cancer patients with tumours in areas that have proven problematic for surgeons, such as the brain stem, aorta or spine. It could also help people who have received the maximum amount of radiation treatment and can no longer cope with the scarring and pain that goes along with it, or children who are at risk of developing mutations from radiation as they grow older.

 

References:

 

http://www.ndtv.com/health/researchers-develop-new-method-to-kill-cancer-cells-in-2-hours-1424509

 

https://www.consumeraffairs.com/news/new-non-invasive-cancer-therapy-shows-promise-062916.html

 

http://www.mirror.co.uk/science/new-cancer-treatment-can-kill-8341452

 

https://www.sciencedaily.com/releases/2016/06/160627214423.htm

 

http://reliawire.com/photodynamic-acidification-therapy/

 

http://www.gizmag.com/making-cancer-cells-acidic/44070/

 

 

http://www.oncologynurseadvisor.com/general-oncology/initial-photodynamic-therapy-tests-promising/article/508292/

 

https://www.sciencedaily.com/releases/2016/06/160627214423.htm

 

http://www.thehindu.com/sci-tech/health/new-method-can-kill-cancer-cells-in-two-hours-shows-study/article8785315.ece

 

http://www.aol.com/article/2016/07/06/new-cancer-treatment-method-causes-cells-to-commit-suicide/21424984/

 

http://zeenews.india.com/news/health/diseases-conditions/new-method-that-can-kill-cancer-cells-in-2-hours-developed_1901377.html

 

http://www.digitaltrends.com/health-fitness/ultraviolet-light-kills-cancer-cells/

 

https://www.thesun.co.uk/news/1385404/light-can-kill-cancer-in-just-two-hours/

 

http://www.techtimes.com/articles/168268/20160704/new-cancer-therapy-method-ultraviolet-light-may-soon-replace-chemotherapy.htm

 

https://www.engadget.com/2016/07/01/scientists-use-light-to-nuke-cancer-cells-in-mice/

 

Nuha Buchanan Kadri, Matthew Gdovin, Nizar Alyassin, Justin Avila, Aryana Cruz, Louis Cruz, Steve Holliday, Zachary Jordan, Cameron Ruiz and Jennifer Watts. Photodynamic acidification therapy to reduce triple negative breast cancer growth in vivo. Journal of Clinical Oncology, Vol 34, No 15_suppl (May 20 Supplement), 2016: e12574.

 

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Toxicities Associated with Immuno-oncology Treatment

Larry H. Bernstein, MD, FCAP

Curator: LPBI

 

ICLIO: Be Aware of Novel Toxicities With New Ca Drugs  

Advent of new immunotherapies warrants education for non-oncologists

by Eric T. Rosenthal
Special Correspondent, MedPage Today
http://www.medpagetoday.com/HematologyOncology/Chemotherapy/58582

CHICAGO — A new class of cancer immunotherapies, led by pembrolizumab (Keytruda), has taken the oncology world by storm. But with this novel type of treatment comes a new challenge.

The Association of Community Cancer Centers (ACCC) wants to ensure that non-oncologist physicians know how to take care of their patients receiving these agents since doctors in other specialties may not be aware of the side effects related to the immunotherapies.

The initiative is one of the steps taken by the association’s Institute of Clinical Immuno-Oncology’s (ICLIO) in making immunotherapy available in the community.

ICLIO was launched 1 year ago to help prepare community cancer teams and centers to deal with the clinical, coverage, and reimbursement issues related to immunotherapy.

During the American Society of Clinical Oncology annual meeting here MedPage Todayspoke with ACCC President Jennie R. Crews, MD, and ICLIO Chair Lee S. Schwartzberg, MD, about the institute’s growth and future plans.

Schwartzberg, chief of the division of hematology and oncology at the University of Tennessee, as well as executive director of the West Cancer Center in Memphis, said that the field of immunotherapy “is moving so fast that we can’t have enough education.”

“Needs change over time and last year many cancer practices became familiar with immuno-oncology and now we have to go deeper and broader.”

The broadening, he explained, involves educating other medical subspecialists about immune-related toxicities from the new agents.

“The problem is that we see related toxicities that are not managed well, and we’re having trouble with this.”

He cited as two primary examples toxic side effects such as colitis and pneumonitis and the necessity of educating gastroenterologists and pulmonologists about their relationship to immunotherapy.

Many times these subspecialists, as well as dermatologists, endocrinologists, emergency physicians, and internists see autoimmune-related toxicities and first think they are from chemotherapy or infection, according to Schwartzberg.

“But they are going to be going down a very bad path with these patients if they think this way,” noting that a colleague from a leading cancer center had recently mentioned that the institution’s emergency room staff didn’t always understand about immunotherapy reactions.

He said that, although ICLIO does not have direct access to reaching many other subspecialists, it was beginning to develop educational materials that oncologists could share with other medical colleagues, as well as to work with some of the subspecialty societies.

“Education, however, has to be across the board, and has to include patients as well,” he said, adding that many cancer immunotherapy patients were being provided with cards that explained their immunotherapy and could be handed to nurses and physicians at the outset of their medical intervention, saving time and the risk of undergoing the wrong treatment.

In a separate interview, Crews, medical director for Cancer Services PeaceHealth at St. Joseph Medical Center in Bellingham, Wash., said that ACCC members include both academic centers and community practices including both hospital-based and private. (An ACCC public relations representative monitored the interview.)

“We are not focused on what the science is, but rather on how do we take this technology out to the community to bring cancer to where patients are,” she said, adding that she and others are very passionate in the belief that cancer care should be delivered wherever cancer patients live.

She said since ICLIO started in June 2015, much of its infrastructure and programs have been established, including a webinar series, eNewsletters, eLearning Modules, tumor subcommittee working groups, an on-site preceptorship program, an ICLIO stakeholder summit, and an upcoming second national conference this fall in Philadelphia.

That conference will be preceded by a stakeholder summit bringing together providers, patient advocates, payers, pharmaceutical producers, and others, which the ACCC hopes will produce a white paper.

The last year has seen the growth of the initiative’s Scholars Program to about 50 oncologists who have received training through ICLIO’s learning modules.

These scholars will in turn eventually be able to serve as mentors to the 2,000 cancer programs with some 20,000 individual members that make up ACCC’s membership.

Crews said that to date about 700 cancer programs involving some 1,900 individuals have participated in the webinars, and about 100 people attended ICLIO’s first annual conference last October.

She said that in addition to the charitable contribution initially made by Bristol-Myers Squibb last year to help launch ICLIO, Merck has also provided an educational grant, but she would not disclose the amount of the funding.

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Drug Structural Effects on Living Cells

Author: Danut Dragoi, PhD

Most drugs have the chemical composition of light chemical elements, C, H, N, O, S in such combination that determines a unique molecular structures for a given molecular weight value. It is interesting that drug structures include chiral handedness which plays an important role in therapeutics.

Drugs development went in advanced stages in which the therapeutic effects can be predicted and matched with any disease before it is made. However, the science of matching a drug to a curable disease is pretty much a pragmatic activity that is based on trials and observations. The medical trails are needed as a safe method before the drug is released to the public. Drug’s structures, and their fragments are discusses in here.

An interesting example of drug chirality effects on human living cells is Ethambutol, which exists in two chiral forms, the (S,S)-(+)-enantiomer that is used to treat tuberculosis, and the (R,R)-(–)-ethambutol that causes blindness, a significant side effect [1] .

The picture below shows the two enantiomers of Ethambutol, L and D forms, adapted to illustrate the mirror symmetry on a plan placed between the two molecules.

L and D ethambutol

Image  SOURCE: adapted from http://www.chemspider.com/Chemical-Structure.412943.html?rid=f51c3f22-3f31-4a7e-9d55-64469464ccf4. NB: the envelope on each enantiomer is a molecular orbital representation of electron density which plays an important role on metabolic reactions in human body.

About 56% of the drugs currently in use are chiral products, showing the importance of chirality on designing drugs today.

Chiral S- and R- drugs

Examples of other enantiomers with important action effects on human body is abundant in literature. For example enantiomers of a chiral drug have identical physical and chemical properties in an achiral environment. In a chiral environment, one enantiomer may display different chemical and pharmacological behavior than the other enantiomer. Because living systems are themselves chiral, each of the enantiomers of a chiral drug can behave very differently in vivo. In other words, the R-enantiomer of a drug will not necessarily behave the same way as the S-enantiomer of the same drug when taken by a patient. For a given chiral drug, it is appropriate to consider the 2 enantiomers as 2 separate drugs with different properties unless proven otherwise.

The increasing availability of single-enantiomer drugs promises to provide clinicians with safer, better-tolerated, and more efficacious medications for treating patients. It is incumbent upon the practicing physician to be familiar with the basic characteristics of chiral pharmaceuticals discussed in this article. In particular, each enantiomer of a given chiral drug may have its own particular pharmacological profile, and a single-enantiomer formulation of a drug may possess different properties than the racemic formulation of the same drug. When both a single-enantiomer and a racemic formulation of a drug are available, the information from clinical trials and clinical experience should be used to decide which formulation is most appropriate.

Source

http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1870-249X2013000300013

https://www.tipharma.com/fileadmin/user_upload/Theses/PDF/Eelke_van_der_Horst_D1-105.pdf.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC353039/

[1] Padmanabhan, Deepak. “A review of drug isomerism and its significance”. US National Library of Medicine National Institutes of Health. pp. 16–18. doi:10.4103/2229-516X.112233. Retrieved 16 April 2016.

http://www.chemspider.com/Chemical-Structure.412943.html?rid=f51c3f22-3f31-4a7e-9d55-64469464ccf4

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC353039/

 

 

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Merck Might End DPP-4 Drug Development Program Due to Serious Adverse Events

Stephen J. Williams, PhD.: Reporter/Curator

As Reported From FiercePharma

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Imaging of Cancer Cells

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Microscope uses nanosecond-speed laser and deep learning to detect cancer cells more efficiently

April 13, 2016

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.

In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.

Time-stretch quantitative phase imaging (TS-QPI) and analytics system

The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one.

The new technique combines two components that were invented at UCLA:

A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.

A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.

The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.

The research was supported by NantWorks, LLC.

 

Abstract of Deep Learning in Label-free Cell Classification

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

references:

Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang, Kayvan Reza Niazi & Bahram Jalali. Deep Learning in Label-free Cell Classification. Scientific Reports 6, Article number: 21471 (2016); doi:10.1038/srep21471 (open access)

Supplementary Information

 

Deep Learning in Label-free Cell Classification

Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang,Kayvan Reza Niazi & Bahram Jalali

Scientific Reports 6, Article number: 21471 (2016)    http://dx.doi.org:/10.1038/srep21471

Deep learning extracts patterns and knowledge from rich multidimenstional datasets. While it is extensively used for image recognition and speech processing, its application to label-free classification of cells has not been exploited. Flow cytometry is a powerful tool for large-scale cell analysis due to its ability to measure anisotropic elastic light scattering of millions of individual cells as well as emission of fluorescent labels conjugated to cells1,2. However, each cell is represented with single values per detection channels (forward scatter, side scatter, and emission bands) and often requires labeling with specific biomarkers for acceptable classification accuracy1,3. Imaging flow cytometry4,5 on the other hand captures images of cells, revealing significantly more information about the cells. For example, it can distinguish clusters and debris that would otherwise result in false positive identification in a conventional flow cytometer based on light scattering6.

In addition to classification accuracy, the throughput is another critical specification of a flow cytometer. Indeed high throughput, typically 100,000 cells per second, is needed to screen a large enough cell population to find rare abnormal cells that are indicative of early stage diseases. However there is a fundamental trade-off between throughput and accuracy in any measurement system7,8. For example, imaging flow cytometers face a throughput limit imposed by the speed of the CCD or the CMOS cameras, a number that is approximately 2000 cells/s for present systems9. Higher flow rates lead to blurred cell images due to the finite camera shutter speed. Many applications of flow analyzers such as cancer diagnostics, drug discovery, biofuel development, and emulsion characterization require classification of large sample sizes with a high-degree of statistical accuracy10. This has fueled research into alternative optical diagnostic techniques for characterization of cells and particles in flow.

Recently, our group has developed a label-free imaging flow-cytometry technique based on coherent optical implementation of the photonic time stretch concept11. This instrument overcomes the trade-off between sensitivity and speed by using Amplified Time-stretch Dispersive Fourier Transform12,13,14,15. In time stretched imaging16, the object’s spatial information is encoded in the spectrum of laser pulses within a pulse duration of sub-nanoseconds (Fig. 1). Each pulse representing one frame of the camera is then stretched in time so that it can be digitized in real-time by an electronic analog-to-digital converter (ADC). The ultra-fast pulse illumination freezes the motion of high-speed cells or particles in flow to achieve blur-free imaging. Detection sensitivity is challenged by the low number of photons collected during the ultra-short shutter time (optical pulse width) and the drop in the peak optical power resulting from the time stretch. These issues are solved in time stretch imaging by implementing a low noise-figure Raman amplifier within the dispersive device that performs time stretching8,11,16. Moreover, warped stretch transform17,18can be used in time stretch imaging to achieve optical image compression and nonuniform spatial resolution over the field-of-view19. In the coherent version of the instrument, the time stretch imaging is combined with spectral interferometry to measure quantitative phase and intensity images in real-time and at high throughput20. Integrated with a microfluidic channel, coherent time stretch imaging system in this work measures both quantitative optical phase shift and loss of individual cells as a high-speed imaging flow cytometer, capturing 36 million images per second in flow rates as high as 10 meters per second, reaching up to 100,000 cells per second throughput.

Figure 1: Time stretch quantitative phase imaging (TS-QPI) and analytics system; A mode-locked laser followed by a nonlinear fiber, an erbium doped fiber amplifier (EDFA), and a wavelength-division multiplexing (WDM) filter generate and shape a train of broadband optical pulses. http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f1.jpg

 

Box 1: The pulse train is spatially dispersed into a train of rainbow flashes illuminating the target as line scans. The spatial features of the target are encoded into the spectrum of the broadband optical pulses, each representing a one-dimensional frame. The ultra-short optical pulse illumination freezes the motion of cells during high speed flow to achieve blur-free imaging with a throughput of 100,000 cells/s. The phase shift and intensity loss at each location within the field of view are embedded into the spectral interference patterns using a Michelson interferometer. Box 2: The interferogram pulses were then stretched in time so that spatial information could be mapped into time through time-stretch dispersive Fourier transform (TS-DFT), and then captured by a single pixel photodetector and an analog-to-digital converter (ADC). The loss of sensitivity at high shutter speed is compensated by stimulated Raman amplification during time stretch. Box 3: (a) Pulse synchronization; the time-domain signal carrying serially captured rainbow pulses is transformed into a series of one-dimensional spatial maps, which are used for forming line images. (b) The biomass density of a cell leads to a spatially varying optical phase shift. When a rainbow flash passes through the cells, the changes in refractive index at different locations will cause phase walk-off at interrogation wavelengths. Hilbert transformation and phase unwrapping are used to extract the spatial phase shift. (c) Decoding the phase shift in each pulse at each wavelength and remapping it into a pixel reveals the protein concentration distribution within cells. The optical loss induced by the cells, embedded in the pulse intensity variations, is obtained from the amplitude of the slowly varying envelope of the spectral interferograms. Thus, quantitative optical phase shift and intensity loss images are captured simultaneously. Both images are calibrated based on the regions where the cells are absent. Cell features describing morphology, granularity, biomass, etc are extracted from the images. (d) These biophysical features are used in a machine learning algorithm for high-accuracy label-free classification of the cells.

On another note, surface markers used to label cells, such as EpCAM21, are unavailable in some applications; for example, melanoma or pancreatic circulating tumor cells (CTCs) as well as some cancer stem cells are EpCAM-negative and will escape EpCAM-based detection platforms22. Furthermore, large-population cell sorting opens the doors to downstream operations, where the negative impacts of labels on cellular behavior and viability are often unacceptable23. Cell labels may cause activating/inhibitory signal transduction, altering the behavior of the desired cellular subtypes, potentially leading to errors in downstream analysis, such as DNA sequencing and subpopulation regrowth. In this way, quantitative phase imaging (QPI) methods24,25,26,27 that categorize unlabeled living cells with high accuracy are needed. Coherent time stretch imaging is a method that enables quantitative phase imaging at ultrahigh throughput for non-invasive label-free screening of large number of cells.

In this work, the information of quantitative optical loss and phase images are fused into expert designed features, leading to a record label-free classification accuracy when combined with deep learning. Image mining techniques are applied, for the first time, to time stretch quantitative phase imaging to measure biophysical attributes including protein concentration, optical loss, and morphological features of single cells at an ultrahigh flow rate and in a label-free fashion. These attributes differ widely28,29,30,31 among cells and their variations reflect important information of genotypes and physiological stimuli32. The multiplexed biophysical features thus lead to information-rich hyper-dimensional representation of the cells for label-free classification with high statistical precision.

We further improved the accuracy, repeatability, and the balance between sensitivity and specificity of our label-free cell classification by a novel machine learning pipeline, which harnesses the advantages of multivariate supervised learning, as well as unique training by evolutionary global optimization of receiver operating characteristics (ROC). To demonstrate sensitivity, specificity, and accuracy of multi-feature label-free flow cytometry using our technique, we classified (1) OT-IIhybridoma T-lymphocytes and SW-480 colon cancer epithelial cells, and (2) Chlamydomonas reinhardtii algal cells (herein referred to as Chlamydomonas) based on their lipid content, which is related to the yield in biofuel production. Our preliminary results show that compared to classification by individual biophysical parameters, our label-free hyperdimensional technique improves the detection accuracy from 77.8% to 95.5%, or in other words, reduces the classification inaccuracy by about five times.     ……..

 

Feature Extraction

The decomposed components of sequential line scans form pairs of spatial maps, namely, optical phase and loss images as shown in Fig. 2 (see Section Methods: Image Reconstruction). These images are used to obtain biophysical fingerprints of the cells8,36. With domain expertise, raw images are fused and transformed into a suitable set of biophysical features, listed in Table 1, which the deep learning model further converts into learned features for improved classification.

The new technique combines two components that were invented at UCLA:

A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.

A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.

The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.

The research was supported by NantWorks, LLC.

 

http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f2.jpg

The optical loss images of the cells are affected by the attenuation of multiplexed wavelength components passing through the cells. The attenuation itself is governed by the absorption of the light in cells as well as the scattering from the surface of the cells and from the internal cell organelles. The optical loss image is derived from the low frequency component of the pulse interferograms. The optical phase image is extracted from the analytic form of the high frequency component of the pulse interferograms using Hilbert Transformation, followed by a phase unwrapping algorithm. Details of these derivations can be found in Section Methods. Also, supplementary Videos 1 and 2 show measurements of cell-induced optical path length difference by TS-QPI at four different points along the rainbow for OT-II and SW-480, respectively.

Table 1: List of extracted features.

Feature Name    Description         Category

 

Figure 3: Biophysical features formed by image fusion.

(a) Pairwise correlation matrix visualized as a heat map. The map depicts the correlation between all major 16 features extracted from the quantitative images. Diagonal elements of the matrix represent correlation of each parameter with itself, i.e. the autocorrelation. The subsets in box 1, box 2, and box 3 show high correlation because they are mainly related to morphological, optical phase, and optical loss feature categories, respectively. (b) Ranking of biophysical features based on their AUCs in single-feature classification. Blue bars show performance of the morphological parameters, which includes diameter along the interrogation rainbow, diameter along the flow direction, tight cell area, loose cell area, perimeter, circularity, major axis length, orientation, and median radius. As expected, morphology contains most information, but other biophysical features can contribute to improved performance of label-free cell classification. Orange bars show optical phase shift features i.e. optical path length differences and refractive index difference. Green bars show optical loss features representing scattering and absorption by the cell. The best performed feature in these three categories are marked in red.

Figure 4: Machine learning pipeline. Information of quantitative optical phase and loss images are fused to extract multivariate biophysical features of each cell, which are fed into a fully-connected neural network.

The neural network maps input features by a chain of weighted sum and nonlinear activation functions into learned feature space, convenient for classification. This deep neural network is globally trained via area under the curve (AUC) of the receiver operating characteristics (ROC). Each ROC curve corresponds to a set of weights for connections to an output node, generated by scanning the weight of the bias node. The training process maximizes AUC, pushing the ROC curve toward the upper left corner, which means improved sensitivity and specificity in classification.

….   How to cite this article: Chen, C. L. et al. Deep Learning in Label-free Cell Classification.

Sci. Rep. 6, 21471; http://dx.doi.org:/10.1038/srep21471

 

Computer Algorithm Helps Characterize Cancerous Genomic Variations

http://www.genengnews.com/gen-news-highlights/computer-algorithm-helps-characterize-cancerous-genomic-variations/81252626/

To better characterize the functional context of genomic variations in cancer, researchers developed a new computer algorithm called REVEALER. [UC San Diego Health]

Scientists at the University of California San Diego School of Medicine and the Broad Institute say they have developed a new computer algorithm—REVEALER—to better characterize the functional context of genomic variations in cancer. The tool, described in a paper (“Characterizing Genomic Alterations in Cancer by Complementary Functional Associations”) published in Nature Biotechnology, is designed to help researchers identify groups of genetic variations that together associate with a particular way cancer cells get activated, or how they respond to certain treatments.

REVEALER is available for free to the global scientific community via the bioinformatics software portal GenePattern.org.

“This computational analysis method effectively uncovers the functional context of genomic alterations, such as gene mutations, amplifications, or deletions, that drive tumor formation,” said senior author Pablo Tamayo, Ph.D., professor and co-director of the UC San Diego Moores Cancer Center Genomics and Computational Biology Shared Resource.

Dr. Tamayo and team tested REVEALER using The Cancer Genome Atlas (TCGA), the NIH’s database of genomic information from more than 500 human tumors representing many cancer types. REVEALER revealed gene alterations associated with the activation of several cellular processes known to play a role in tumor development and response to certain drugs. Some of these gene mutations were already known, but others were new.

For example, the researchers discovered new activating genomic abnormalities for beta-catenin, a cancer-promoting protein, and for the oxidative stress response that some cancers hijack to increase their viability.

REVEALER requires as input high-quality genomic data and a significant number of cancer samples, which can be a challenge, according to Dr. Tamayo. But REVEALER is more sensitive at detecting similarities between different types of genomic features and less dependent on simplifying statistical assumptions, compared to other methods, he adds.

“This study demonstrates the potential of combining functional profiling of cells with the characterizations of cancer genomes via next-generation sequencing,” said co-senior author Jill P. Mesirov, Ph.D., professor and associate vice chancellor for computational health sciences at UC San Diego School of Medicine.

 

Characterizing genomic alterations in cancer by complementary functional associations

Jong Wook Kim, Olga B Botvinnik, Omar Abudayyeh, Chet Birger, et al.

Nature Biotechnology (2016)              http://dx.doi.org:/10.1038/nbt.3527

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

 

Figure 2: REVEALER results for transcriptional activation of β-catenin in cancer.close

(a) This heatmap illustrates the use of the REVEALER approach to find complementary genomic alterations that match the transcriptional activation of β-catenin in cancer. The target profile is a TCF4 reporter that provides an estimate of…

 

An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models

Jonathan P. Celli, Imran Rizvi, Adam R. Blanden, Iqbal Massodi, Michael D. Glidden, Brian W. Pogue & Tayyaba Hasan

Scientific Reports 4; 3751  (2014)    http://dx.doi.org:/10.1038/srep03751

While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.

The attrition rates for preclinical development of oncology therapeutics are particularly dismal due to a complex set of factors which includes 1) the failure of pre-clinical models to recapitulate determinants of in vivo treatment response, and 2) the limited ability of available assays to extract treatment-specific data integral to the complexities of therapeutic responses1,2,3. Three-dimensional (3D) tumour models have been shown to restore crucial stromal interactions which are missing in the more commonly used 2D cell culture and that influence tumour organization and architecture4,5,6,7,8, as well as therapeutic response9,10, multicellular resistance (MCR)11,12, drug penetration13,14, hypoxia15,16, and anti-apoptotic signaling17. However, such sophisticated models can only have an impact on therapeutic guidance if they are accompanied by robust quantitative assays, not only for cell viability but also for providing mechanistic insights related to the outcomes. While numerous assays for drug discovery exist18, they are generally not developed for use in 3D systems and are often inherently unsuitable. For example, colorimetric conversion products have been noted to bind to extracellular matrix (ECM)19 and traditional colorimetric cytotoxicity assays reduce treatment response to a single number reflecting a biochemical event that has been equated to cell viability (e.g. tetrazolium salt conversion20). Such approaches fail to provide insight into the spatial patterns of response within colonies, morphological or structural effects of drug response, or how overall culture viability may be obscuring the status of sub-populations that are resistant or partially responsive. Hence, the full benefit of implementing 3D tumour models in therapeutic development has yet to be realized for lack of analytical methods that describe the very aspects of treatment outcome that these systems restore.

Motivated by these factors, we introduce a new platform for quantitative in situ treatment assessment (qVISTA) in 3D tumour models based on computational analysis of information-dense biological image datasets (bioimage-informatics)21,22. This methodology provides software end-users with multiple levels of complexity in output content, from rapidly-interpreted dose response relationships to higher content quantitative insights into treatment-dependent architectural changes, spatial patterns of cytotoxicity within fields of multicellular structures, and statistical analysis of nodule-by-nodule size-dependent viability. The approach introduced here is cognizant of tradeoffs between optical resolution, data sampling (statistics), depth of field, and widespread usability (instrumentation requirement). Specifically, it is optimized for interpretation of fluorescent signals for disease-specific 3D tumour micronodules that are sufficiently small that thousands can be imaged simultaneously with little or no optical bias from widefield integration of signal along the optical axis of each object. At the core of our methodology is the premise that the copious numerical readouts gleaned from segmentation and interpretation of fluorescence signals in these image datasets can be converted into usable information to classify treatment effects comprehensively, without sacrificing the throughput of traditional screening approaches. It is hoped that this comprehensive treatment-assessment methodology will have significant impact in facilitating more sophisticated implementation of 3D cell culture models in preclinical screening by providing a level of content and biological relevance impossible with existing assays in monolayer cell culture in order to focus therapeutic targets and strategies before costly and tedious testing in animal models.

Using two different cell lines and as depicted in Figure 1, we adopt an ECM overlay method pioneered originally for 3D breast cancer models23, and developed in previous studies by us to model micrometastatic ovarian cancer19,24. This system leads to the formation of adherent multicellular 3D acini in approximately the same focal plane atop a laminin-rich ECM bed, implemented here in glass-bottom multiwell imaging plates for automated microscopy. The 3D nodules resultant from restoration of ECM signaling5,8, are heterogeneous in size24, in contrast to other 3D spheroid methods, such as rotary or hanging drop cultures10, in which cells are driven to aggregate into uniformly sized spheroids due to lack of an appropriate substrate to adhere to. Although the latter processes are also biologically relevant, it is the adherent tumour populations characteristic of advanced metastatic disease that are more likely to be managed with medical oncology, which are the focus of therapeutic evaluation herein. The heterogeneity in 3D structures formed via ECM overlay is validated here by endoscopic imaging ofin vivo tumours in orthotopic xenografts derived from the same cells (OVCAR-5).

 

Figure 1: A simplified schematic flow chart of imaging-based quantitative in situ treatment assessment (qVISTA) in 3D cell culture.

(This figure was prepared in Adobe Illustrator® software by MD Glidden, JP Celli and I Rizvi). A detailed breakdown of the image processing (Step 4) is provided in Supplemental Figure 1.

A critical component of the imaging-based strategy introduced here is the rational tradeoff of image-acquisition parameters for field of view, depth of field and optical resolution, and the development of image processing routines for appropriate removal of background, scaling of fluorescence signals from more than one channel and reliable segmentation of nodules. In order to obtain depth-resolved 3D structures for each nodule at sub-micron lateral resolution using a laser-scanning confocal system, it would require ~ 40 hours (at approximately 100 fields for each well with a 20× objective, times 1 minute/field for a coarse z-stack, times 24 wells) to image a single plate with the same coverage achieved in this study. Even if the resources were available to devote to such time-intensive image acquisition, not to mention the processing, the optical properties of the fluorophores would change during the required time frame for image acquisition, even with environmental controls to maintain culture viability during such extended imaging. The approach developed here, with a mind toward adaptation into high throughput screening, provides a rational balance of speed, requiring less than 30 minutes/plate, and statistical rigour, providing images of thousands of nodules in this time, as required for the high-content analysis developed in this study. These parameters can be further optimized for specific scenarios. For example, we obtain the same number of images in a 96 well plate as for a 24 well plate by acquiring only a single field from each well, rather than 4 stitched fields. This quadruples the number conditions assayed in a single run, at the expense of the number of nodules per condition, and therefore the ability to obtain statistical data sets for size-dependent response, Dfrac and other segmentation-dependent numerical readouts.

 

We envision that the system for high-content interrogation of therapeutic response in 3D cell culture could have widespread impact in multiple arenas from basic research to large scale drug development campaigns. As such, the treatment assessment methodology presented here does not require extraordinary optical instrumentation or computational resources, making it widely accessible to any research laboratory with an inverted fluorescence microscope and modestly equipped personal computer. And although we have focused here on cancer models, the methodology is broadly applicable to quantitative evaluation of other tissue models in regenerative medicine and tissue engineering. While this analysis toolbox could have impact in facilitating the implementation of in vitro 3D models in preclinical treatment evaluation in smaller academic laboratories, it could also be adopted as part of the screening pipeline in large pharma settings. With the implementation of appropriate temperature controls to handle basement membranes in current robotic liquid handling systems, our analyses could be used in ultra high-throughput screening. In addition to removing non-efficacious potential candidate drugs earlier in the pipeline, this approach could also yield the additional economic advantage of minimizing the use of costly time-intensive animal models through better estimates of dose range, sequence and schedule for combination regimens.

 

Microscope Uses AI to Find Cancer Cells More Efficiently

Thu, 04/14/2016 – by Shaun Mason

http://www.mdtmag.com/news/2016/04/microscope-uses-ai-find-cancer-cells-more-efficiently

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.

In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses.

There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.

The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one. It combines two components that were invented at UCLA: a photonic time stretch microscope, which is capable of quickly imaging cells in blood samples, and a deep learning computer program that identifies cancer cells with over 95 percent accuracy.

Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data with the goal of achieving accurate decision making.

The study, which was published in the journal Nature Scientific Reports, was led by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral fellow.

Photonic time stretch was invented by Jalali, and he holds a patent for the technology. The new microscope is just one of many possible applications; it works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly — in nanoseconds, or billionths of a second — that the images would be too weak to be detected and too fast to be digitized by normal instrumentation.

The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitized at a rate of 36 million images per second. It then uses deep learning to distinguish cancer cells from healthy white blood cells.

“Each frame is slowed down in time and optically amplified so it can be digitized,” Mahjoubfar said. “This lets us perform fast cell imaging that the artificial intelligence component can distinguish.”

Normally, taking pictures in such minuscule periods of time would require intense illumination, which could destroy live cells. The UCLA approach also eliminates that problem.

“The photonic time stretch technique allows us to identify rogue cells in a short time with low-level illumination,” Chen said.

The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.   …..  see also http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f1.jpg

Chen, C. L. et al. Deep Learning in Label-free Cell Classification.    Sci. Rep. 6, 21471;   http://dx.doi.org:/10.1038/srep21471

 

 

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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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