Category Archives: CRISPR

Novel Immunotherapeutic Approaches to the Treatment of Cancer: Drug Development and Clinical Application

Our new immunotherapy book has been published by Springer:

http://www.springer.com/us/book/9783319298252

I want to take a moment to acknowledge the stunning group of authors who made the book a success. I’d also like to promote our fund raising effort in memory of Holbrook Kohrt, to whom the volume is dedicated – 5% of net sales will be donated by me, on behalf of all of our authors, the the Cancer Research Institute in New York. So please consider buying the book or just the chapters you want (they can be purchased individually through the link given above.

Now, the authors:

from Arlene Sharpe and her lab (Harvard Medical School, Boston):

Enhancing the Efficacy of Checkpoint Blockade Through Combination Therapies

from Taylor Schreiber (Pelican Therapeutics, Heat Biologics):

Parallel Costimulation of Effector and Regulatory T Cells by OX40, GITR, TNFRSF25, CD27, and CD137: Implications for Cancer Immunotherapy

from Russell Pachynski (Washington University St Louis) and Holbrook Kohrt (Stanford University Medical Center)

NK Cell Responses in Immunotherapy: Novel Targets and Applications

from Larry Kane and Greg Delgoffe (University of Pittsburgh School of Medicine):

Reversing T Cell Dysfunction for Tumor Immunotherapy

from Josh Brody and Linda Hammerich (Icahn School of Medicine, Mt Sinai, NYC)

Immunomodulation Within a Single Tumor Site to Induce Systemic Antitumor Immunity: In Situ Vaccination for Cancer

From Sheila Ranganath and AnhCo (Cokey) Nguyen (Enumeral Inc, Cambridge MA)

Novel Targets and Their Assessment for Cancer Treatment

From Thomas (TJ) Cradick, CRISPR Therapeutics, Cambridge MA):

Cellular Therapies: Gene Editing and Next-Gen CAR T Cells

From Chris Thanos (Halozyme Inc, San Diego) and myself:

The New Frontier of Antibody Drug Conjugates: Targets, Biology, Chemistry, Payload

and a second topic covered by Chris Thanos (Halozyme):

Targeting the Physicochemical, Cellular, and Immunosuppressive Properties of the Tumor Microenvironment by Depletion of Hyaluronan to Treat Cancer

and finally, my solo chapter (and representing Aleta Biotherapeutics, Natick MA and SugarCone Biotech, Holliston MA):

Novel Immunomodulatory Pathways in the Immunoglobulin Superfamily

Please spread the word that all sales benefit cancer research and more specifically, cancer clinical trial development and execution through the Cancer research Institute, and as I said, consider buying the book, or the chapters you want to read.

cheers-

Paul

The Tumor Ecosystem: some thoughts stirred up at the NY International Immunotherapy meeting

Ecosystems in tumor immunity

The buzzword ‘ecosystem’ has popped like a spring dandelion, and it is now used everywhere in biotech. I’m as guilty as anyone of rapid adoption: the term does capture essential elements of modern biomedical science. Complex and interlaced, with key control nodes at work at all levels – scientific, financial, clinical, commercial – and also dynamic, constantly driving adaptation, and, we hope, innovation. Scientifically the ecosystem connections are easily spotted. CRISPR technology appears in cellular therapies including TCRs and CAR-Ts as we simultaneously learn that the mechanisms of immune checkpoint suppression deployed by tumor cells can derail genetically engineered CAR T cells as readily as normal T cells. Further, those genetically engineered CAR T cells and TCRs owe their existence in large measure to our newly developed ability to sequence tumors at the individual level, with great sensitivity, to identify novel targets. The whole enterprise in turn requires ever faster, cheaper, smaller and more reliable equipment (RNA spin columns and PCR cyclers and cloning kits and desktop sequencers and on and on) and software to handle the data. Enterprises like these in turn drive discovery and innovation.

Within the tumor is another ecosystem – the tumor microenvironment or TME. While TME is a fine term it does blur the notion that this microenvironment is in nearly all cases part of a larger environment and not a walled-off terrarium (perhaps primary pancreatic cancer is an exception, within its fibrous fortress). The tumor ecosystem is a more encompassing term, allowing for the ebb and flow of vastly different elements: waves of immune cells attempting attack, dead zones of necrotic tissue being remodeled, tendrils of newly forming blood vessels, a fog of lactate, a drizzle of adenosine, energy, builders, destroyers, progenitors, phagocytes, parasites, predators. When viewed this way we might wonder how any single drug could treat a tumor, since it is not a singular thing that we attack with a drug, but an ever-changing world we are seeking to destroy.

So it’s hard to do.

Our understanding of the tumor as a complex entity was first informed by pathology, then microscopy, then histology and immunohistochemistry, myriad other techniques and of course genetics, the latter leading to the identification of tumor oncogenes, tumor epigenetics, tumor mutations (referred to above) etc, etc. This ecosystem – that of the cell and it’s mutational hardware and software (genome and exome, or genotype and phenotype) we can hardly claim to understand at all, not matter how many arrows we might draw on a figure for a paper or a review. A few recent examples: we think that tumor cells adapt to immune infiltration in part by engaging CTLA4 expressed on T cells, and when that fails they secrete IDO1, or express PD-L1 on their cell surface, or the tumor cells direct tumor associated cells to do the work for them – maybe monocytes, or macrophages, perhaps fibroblasts, perhaps the endothelium, i.e. the ecosystem. As we know from studying patterns of response to PD-1 and PD-L1 therapeutics, it is hardly so simple, as patients who don’t express the therapeutic target will respond to therapy and patients who express the therapeutic target sometimes, in fact often, will not respond. Which just says we don’t know what we don’t know, but we’ll learn, the hard way, in clinical trials.

The abundance of therapeutic targets and our lack of knowledge is best displayed, with some irony, when we try to show what we do know, as in this figure from our recent paper on immune therapeutic targets:

 Screen Shot 2015-10-07 at 4.29.43 PM

from http://www.nature.com/nrd/journal/v14/n8/full/nrd4591.html 

The picture is static, and fails to represent or visualize complexity (spatial, temporal, random, quantum), and we therefore cannot formulate meaningful hypotheses from the representation. Without meaningful hypotheses we just have observations. With observations we can only flail away hopefully, and be happy when we are right 15 or 20% of the time, as is the case with most PD-1 and PD-L1-directed immune therapeutics in most tumor indications, at least as monotherapies. Why focus so on the PD-1 pathway? Because at least for now, it is the singular benchmark immune therapeutic, stunning really in inducing anti-tumor immunity in subsets of cancer patients.

The success of the “PD-1″ franchise has created another ecosystem, clinical and commercial. The key approved drugs, and the 3 or 4 moving quickly toward approval, are held by some of the world’s largest drug companies (BMS, Merck, Astra Zeneca, Sanofi, Pfizer, Roche). Playing in that sandbox has proven very lucrative for some small companies, and very difficult for many others. There is competition for resources, for patients, for assets and ideas. This has created new niches in the commercial ecosystem, as companies try to differentiate from each other and carve out their own turf – Eli Lilly for example has focused on TME targets, distinguishing itself from other oncology pharmaceutical companies in choice of targets, followed closely of course by smaller contenders – Jounce, with a T cell program directed at ICOS but perhaps more buzz around their macrophage targeting programs, and Surface, whose targets are kept subterranean for now. Tesaro and others are betting on anti-PD-1 antibodies paired rationally with antibodies to second targets in bispecific format. Enumeral is focused on building rationale for specific combinations of immune therapeutics in specific indications, perhaps even for the right subset of patients within that indication. And so on.

It’s complicated.

Lets imagine you are right now pondering an interesting idea, have a small stake, and want to engage this landscape of shifting ecosystems. What might you do?

Lets start with a novel target. You’ve read some papers, woven together some interesting ideas, formulated some useful hypotheses. The protein has been around, maybe there are patents, but not in the immune oncology space, so you think you might have some freedom to operate. Good, best of both worlds. You dig around, find you can buy your target as purified protein, or find a cell line that expresses the target. Now what? Maybe you would hire an Adimab or Morphosys or X-Body to perform an antibody screen. Different companies, varied technologies, but all directed at antibody discovery. My favorite of this group was X-Body, who had an extraordinary platform to screen human antibody sequences and produce antibodies with really stunning activity and diversity. Juno bought them in early 2015, seeking the antibody platform and a TCR screening platform built with the same technology. I hadn’t seen anything quite so powerful until recently, with the introduction of a novel screening technology from Vaccinex. This platform is about as diverse as the X-Body platform (i.e. ~108 Vh sequences and up to 106 Vl sequences; that’s a lot of possible Vh-Vl pairs). What sets them apart is that the entire selection process happens as full length IgG in mammalian cells rather than surrogates like bacteria or yeast.  The net result is a reduction in risk associated with manufacturing.  They’ve used it to power their own clinical programs and have selection deals with some big names including Five Prime Therapeutics. Remarkably (I think) you can access their platform to screen targets for your own, i.e. external, use. Their website explains the platform further (http://www.vaccinex.com/activmab/) but here is one nice sample of their work on FZD4 (a nice target by the way):

 Screen Shot 2015-10-07 at 4.18.17 PM

So now via Vaccinex or someone else you’ve acquired a panel of antibodies that you are ready to test for immune modulatory activity in models that are relevant to immune oncology. You can build out a lab (expensive, time-consuming), find a collaborator with a lab, or find a skilled CRO. The immune checkpoint space was until recently devoid of really focused CRO activity, that is, having diverse modelling capability and careful benchmarking. However, Aquila BioMedical in Scotland, UK placed a solid bet on developing these capabilities around a year ago, and that effort is yielding a terrific suite of assays in both mouse and human cell systems, with multiple readouts, solid benchmarking (e.g. to nivolumab) and careful controls. I like this very much, rich in functional data in a way that a binding assay simply can’t reproduce. Aquila BioMedical seeks to become a driving force in this area, and I like their chances very much: see http://www.aquila-bm.com/research-development/immuno-oncology/ for more information on assays like this IFNgamma secretion assay:

 Screen Shot 2015-10-07 at 4.40.04 PM

Those are clean and robust data.

Now you come to the point of translation to actual use, that is, targeting an indication. How does one proceed? We can probe the TCGA and other databanks for clues, stare at the IHC data online (not recommended), try to cobble together enough samples to do our own analyses (highly recommended but difficult). The goal is to make some educated guesses about two distinct features of the tumor ecosystem: First, is your target expressed on a relevant cell within the ecosystem (tumor, TME, vasculature, draining lymph nodes, etc) in a specific indication or indications, and second, is that ecosystem likely to respond in a clinically meaningful way to manipulation of your target with your antibody?

That second question is a troubling one. What we are really asking is that we deconstruct the ecosystem and look for clues as to how the therapeutic might impact that ecosystem. What are we looking for during deconstruction? Several things, and they are assessed using diverse techniques, adding to the challenge. First, a highly mutated tumor is more likely to respond to immune therapy, and there are several aspects to these phenomena. One is to understand the underlying genomic changes underpinning the oncogenetics of the tumor: what is driving its ability to outcompete the natural surroundings – in our ecosystem analogy perhaps the tumor can be considered starting out life as an invasive species. Genomic sequencing can accurately identify the mutations that support the tumor, but also a potentially vast array of “passenger” mutations that accumulate when tumors turn off the usual mutation repair machinery. Various algorithms exists that can predict which mutated proteins may be immunogenic, that is, capable of stimulating an anti-tumor immune response. Another method designed to determine if an immune response has in fact be stimulated (and has stalled) is to sequence the mRNA expressed in the tumor: exome sequencing. This will reveal, among other things, what the TCR usage is within the tumor, and that in turn will inform you if there is a very narrow anti-tumor response and a broad one, based on the breadth of TCR clonality. That sounds complex, but really isn’t – suffice to say that a broader TCR response in suggestive of immune potential, leashed T cells awaiting clear orders to attack.

More complex is the nature of those orders, and counter-orders. Various methods are being developed to measure the “quality” of the immune response that confronts the tumor. Are key costimulatory molecules present on T cells that would allow stimulation? Are the T cells instead coated with immunosuppressive receptors? Are the tumor cells masked with inhibitory proteins, are they secreting immunosuppressive factors, have they hidden themselves from immune view by downregulating the proteins that T cells “see” (i.e. the MHC complex). What are the cells within the TME doing? Are they monocytes, macrophages, fibroblasts? Where are the T cells? Within the tumor, or shunted off to the side, at the margin between the tumor and normal tissue? Are NK cells present? And on and on it goes. It seems impossible to answer all these diverse questions.

You might try IHC, as mentioned, or targeted PCR for select genes, and Flow Cytometry to look at the distribution of proteins on various cells, or try deep sequencing. All of this is achievable with equipment, labs and people, or by assembling various collaborators, but all in all, quite a challenge. Very recently an interesting company called MedGenome came to my attention, offering a diverse range of services, starting with neo-epitope prioritization and immune response analyses. These offerings, plus some routine IHC, should give most researchers a comprehensive look into tumor ecosystems, informing indication selection, mechanism of action studies and patient profiling. They explain the technology at http://medgenome.com/oncomd/. This is a schematic they sent me showing their neoepitope prioritization scheme that enriches for peptides that trigger anti-tumor immunity, e.g. in a vaccine setting or perhaps in a cellular therapeutic format.

 Screen Shot 2015-10-07 at 4.22.16 PM

It’s a good start on democratizing a suite of assays typically available only to specialty academic labs and well-funded biotechs and pharma companies.

So now you’ve gotten your antibodies (Vaccinex), performed critical in vitro (and soon, in vivo) assays (Aquila Biomedical), and analyzed the tumor immune ecosystem for indication mapping (Medgenome).

You’ll have spent some money but moved quickly and confidently forward with your preclinical development program. Your seed stake is diminished though, and it’s time to raise real money. Now what? … now you face the financial/clinical/commercial ecosystem.

stay tuned.

Holiday Reading

some of the stuff we’re reviewing over the holiday break. N.b. paywalls ahead!  And at the very end, some current non-science favorites.

Tumor Mutational Landscape

Age related variants of variants occurred in three genes (DNMT3A, TET2, and ASXL1) are associated with hematological malignancy risk  http://www.nejm.org/doi/full/10.1056/NEJMoa1408617 and  http://www.nejm.org/doi/full/10.1056/NEJMoa1409405

News and Views on the NEJM papers  http://www.nature.com/nrg/journal/vaop/ncurrent/full/nrg3889.html

using siRNA to identify driver genes in breast cancer  http://www.nature.com/nrg/journal/v16/n1/full/nrg3875.html

Immunotherapy

a primer on the role of PD-1 pathway inhibitors in Hodgkin’s Lymphoma, from Nat Rev Clin Oncol  http://www.nature.com/nrclinonc/journal/vaop/ncurrent/full/nrclinonc.2014.227.html

the role of TILs and TIL-associated TNF in the survival of CRC patients  http://www.jci.org/articles/view/74894

nivolumab in metastatic RCC, published data  http://jco.ascopubs.org/content/early/2014/12/22/JCO.2014.59.0703.abstract

resistance to T cells in melanoma (hint: they lose MHC expression)  http://clincancerres.aacrjournals.org/content/20/24/6593.abstract

interesting look at PD-L1 expression of the response of RCC to targeted therapies  http://clincancerres.aacrjournals.org/content/early/2014/12/23/1078-0432.CCR-14-1993.abstract

it’s hard to control ipilimumab-induced tox  http://clincancerres.aacrjournals.org/content/early/2014/12/23/1078-0432.CCR-14 2353.abstract

IO combination review  http://clincancerres.aacrjournals.org/content/20/24/6258.abstract

tumor/microenvironment cross-talk mediated by microRNAs  http://clincancerres.aacrjournals.org/content/20/24/6247.abstract

functional blockade of miR-23a releases TILs in an ex vivo NSCLC assay  http://www.jci.org/articles/view/69094

neutrophils, T cells and lung cancer  http://www.jci.org/articles/view/77053

Given the new immunotherapy data in bladder cancer, a review of the molecular drivers of this tumor type is most welcome  http://www.nature.com/nrc/journal/v15/n1/abs/nrc3817.html

MDSC requirements for survival  http://www.cell.com/immunity/abstract/S1074-7613(14)00436-1

Gene Therapy and CAR T

Novel gene therapy methods puts a safety brake on a retrovirus-based vector  http://www.nature.com/nrd/journal/v13/n12/full/nrd4495.html

a new review of the CRISPR, Talen, and ZFN technologies for gene editing  http://www.jci.org/articles/view/72992

NY-ESO-1 CAR T P1 results in solid tumors: long term follow-up and correlates of response  http://clincancerres.aacrjournals.org/content/early/2014/12/23/1078-0432.CCR-14-2708.abstract

Targeted Therapies

A very timely primer of the role of different PI3K isoforms in diverse cancers  http://www.nature.com/nrc/journal/v15/n1/abs/nrc3860.html

a Notch in the cancer treatment belt? Nope, a bit of a toxic mess made with anti-DLL4 antibody Demcizumab from OncoMed  http://clincancerres.aacrjournals.org/content/20/24/6295.abstract

IL-17 and colon cancer?  http://www.cell.com/immunity/abstract/S1074-7613(14)00446-4

Hematological Malignancies

von Adrian and Sharpe tease apart Follicular Lymphoma  http://www.jci.org/articles/view/76861

the role of one of gp130 in multiple myeloma  http://www.jci.org/articles/view/69094

Fibrosis, Inflammation, Metabolism, MS

a brand new fibrosis review  http://www.jci.org/articles/view/74368

the TRPV4 pathway, TGFbeta and IPF  http://www.jci.org/articles/view/75331

The role of novel branched fatty acid esters of hydroxy fatty acids in Type 2 diabetes  http://www.nature.com/nrd/journal/v13/n12/full/nrd4501.html

will STING finally yield a useful target in lupus?  http://www.jci.org/articles/view/79100

an animal model of JCV infection and PML  http://www.jci.org/articles/view/79186

Investment and Deals

Pharma funding to pull programs out of the academic space  http://www.nature.com/nrd/journal/vaop/ncurrent/full/nrd3078-c2.html

some color from NRDD on the Genentech + NewLink IDO-1 inhibitor deal  http://www.nature.com/nrd/journal/v13/n12/full/nrd4502.html

Also notable

300,000,000. A violent graphic lurid hypnotic novel of the dissolution of consciousness and the consequence of multiple realities converging within our unprepared empty minds and upon our decadent culture. Horrific and wonderful, but not for the squeamish.

Thug Kitchen – eat like you give a #$%@^. Fun, but you get the idea.

Death & Co: Modern Classic Cocktails. Drink like an adult.

CRISPR Technology and Therapeutic Gene Editing – TJ Cradick

A Guest Post from Thomas (TJ) Cradick, Director of the Protein Engineering Facility, Georgia Institute of Technology; @NucleaseLab

Genome editing has remained a therapeutic goal since before specific, disease-causing mutations were discovered. Introducing mutations into cell lines and model organisms have also created very useful research reagents. The rate of both processes is greatly enhanced by creating nearby DNA breaks. These effects were first shown with meganucleases, which are very specific but have proved very difficult to convert to targeting novel sequences. The first readily engineered nuclease group was ZFNs (zinc-finger nucleases), followed by TALENs (transcription activator-like effector nucleases), and most recently CRISPRs (clustered regularly interspersed short palindromic repeats). The DNA breaks caused by these nucleases are repaired by the cellular DNA repair machinery and can lead to precise modification. Genome editing is no longer science fiction, though issues remain on delivery and specificity.

TALENs are easier to design than Zinc Finger Nucleases due to straightforward rules linking DNA binding repeats to a target sequence [1,2]. These rules don’t help pick the highest activity sites, though a new program, SAPTA, helps pick sites that can be targeted with high activity and specificity [3]. Several groups have developed high-throughput cloning methods to assemble the DNA binding repeats in TALENs, though new proteins must be assembled for each target [4,5].

For each target, CRISPR systems have the advantage of using identical proteins identified as a means for bacteria to fend off pathogens. These gene-editing systems are called clustered regularly interspaced short palindromic repeats (CRISPR) and pronounced “crisper”. Cas (CRISPR-associated) proteins clone a piece of the foreign DNA into the CRISPR genomic locus between the repeats. Many of these foreign DNAs are saved in the daughter cells. One bacterial protein called Cas9 and a guide strand RNA expressed from these saved DNA pieces allow targeting complementary sequences if the foreign DNA is encountered again. The key is that CRISPR works by cutting DNA complementary to the “guide strand” RNA. Directing cleavage to a new target site only requires cloning a pair of annealed oligos into the guide strand expression cassette [6,7]. This saves the very difficult step of designing and cloning new DNA binding proteins, as are required for ZFNs or TALENs.

In the beginning of 2013 papers began describing genome editing in mammalian cells [7,8]. A number of labs made their plasmids available on Addgene and several created websites and online forums to spread the word. A new company, Editas Medicine, founded by five world leaders in genome editing was founded to use CRISPR and TALENS as treatments for genetic diseases.

One of the big concerns with each type of nuclease is “off-target mutation” in different region of the genome. Several programs help verify and optimize specificity by listing putative off-target cleavage sites, including PROGNOS for ZFNs and TALENs [9]. Others have also found ZFN and TALEN off-target sites, primarily through experimentally guided off-target searches. Currently, there are limited data indicating that TALENs have improved specificity over ZFNs and lower cytotoxicity [10-12]. A number of publications have described the high level of off-target cleavage possible using CRISPR [13,14] and chromosomal deletions or re-arrangements [15]. Although ZFNs and TALENs have off-target cleavage as well, the high levels seen with current CRISPR methods has many groups scurrying to develop newer, safer methods. Use of pairs of Cas proteins that each cut only one strand holds promise, though has yet to be optimized for gene repair [16,17]. It is also likely that improved CRISPR systems will be developed that provide more specificity, though they may have decreased targeting efficiency. For many applications, the ease and speed of the current generation of CRISPR systems will provide a valuable research tool while the work on CRISPR 2.0 continues.

References
1. Boch J, Scholze H, Schornack S, Landgraf A, Hahn S, et al. (2009) Breaking the code of DNA binding specificity of TAL-type III effectors. Science 326: 1509-1512.
2. Moscou MJ, Bogdanove AJ (2009) A simple cipher governs DNA recognition by TAL effectors. Science 326: 1501.
3. Lin Y, Fine EJ, Zheng Z, Antico CJ, Voit RA, et al. (2014) SAPTA: a new design tool for improving TALE nuclease activity. Nucleic Acids Research: gkt1363.
4. Reyon D, Tsai SQ, Khayter C, Foden JA, Sander JD, et al. (2012) FLASH assembly of TALENs for high-throughput genome editing. Nat Biotechnol 30: 460-465.
5. Schmid-Burgk JL, Schmidt T, Kaiser V, Höning K, Hornung V (2013) A ligation-independent cloning technique for high-throughput assembly of transcription activator–like effector genes. Nat Biotechnol 31: 76-81.
6. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, et al. (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337: 816-821.
7. Cong L, Ran FA, Cox D, Lin S, Barretto R, et al. (2013) Multiplex genome engineering using CRISPR/Cas systems. Science 339: 819-823.
8. Mali P, Yang L, Esvelt KM, Aach J, Guell M, et al. (2013) RNA-guided human genome engineering via Cas9. Science 339: 823-826.
9. Fine EJ, Cradick TJ, Zhao CL, Lin Y, Bao G (2013) An online bioinformatics tool predicts zinc finger and TALE nuclease off-target cleavage. Nucleic acids research: gkt1326.
10. Tesson L, Usal C, Ménoret S, Leung E, Niles BJ, et al. (2011) Knockout rats generated by embryo microinjection of TALENs. Nature Biotechnology 29: 695-696.
11. Hockemeyer D, Wang H, Kiani S, Lai CS, Gao Q, et al. (2011) Genetic engineering of human pluripotent cells using TALE nucleases. Nature Biotechnology 29: 731-734.
12. Mussolino C, Morbitzer R, Lutge F, Dannemann N, Lahaye T, et al. (2011) A novel TALE nuclease scaffold enables high genome editing activity in combination with low toxicity. Nucleic Acids Res 39: 9283-9293.
13. Fu Y, Foden JA, Khayter C, Maeder ML, Reyon D, et al. (2013) High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat Biotechnol.
14. Hsu PD, Scott DA, Weinstein JA, Ran FA, Konermann S, et al. (2013) DNA targeting specificity of RNA-guided Cas9 nucleases. Nat Biotechnol.
15. Cradick TJ, Fine EJ, Antico CJ, Bao G (2013) CRISPR/Cas9 systems targeting β-globin and CCR5 genes have substantial off-target activity. Nucleic Acids Research 41: 9584-9592.
16. Mali P, Aach J, Stranges PB, Esvelt KM, Moosburner M, et al. (2013) CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat Biotechnol.
17. Ran FA, Hsu PD, Lin CY, Gootenberg JS, Konermann S, et al. (2013) Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154: 1380-1389.