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 Table of Contents  
REVIEW ARTICLE
Year : 2017  |  Volume : 2  |  Issue : 2  |  Page : 44-49

Application of clustered regularly interspersed short palindromic repeats/cas9 editing technologies in breast cancer research


1 Department of Internal Medicine, University Hospital of Basel, Basel, Switzerland; Basic Medical College, Shanghai University of Medicine and Health Sciences, Shanghai, China
2 Department of Breast Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
3 Department of Internal Medicine, University Hospital of Basel, Basel, Switzerland

Date of Submission19-Jan-2017
Date of Acceptance29-Mar-2017
Date of Web Publication22-Jun-2017

Correspondence Address:
Fengfeng Cai
Department of Breast Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai 200090
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ts.ts_2_17

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  Abstract 

Breast cancer (BC) is one of the most heterogeneous diseases. The specific clinical and pathological features of each patient's BC diagnosis determine the response to specific agents and thus the prognosis. There is a great need for personalized management approaches to avoid over- or under-treatment. Recently, a novel method revolutionized the world of cancer research: the clustered regularly interspersed short palindromic repeats (CRISPR)-Cas9, an RNA-programmable system. The advantages of CRISPR Cas9 system mean simple and effective. It is increasingly being used in the field of BC research, including evaluation of the established therapies.

Keywords: Breast cancer, clustered regularly interspersed short palindromic repeats/Cas9, somatic gene editing


How to cite this article:
Ewelina B, Cai L, Lin X, Kingston C, Cai F. Application of clustered regularly interspersed short palindromic repeats/cas9 editing technologies in breast cancer research. Transl Surg 2017;2:44-9

How to cite this URL:
Ewelina B, Cai L, Lin X, Kingston C, Cai F. Application of clustered regularly interspersed short palindromic repeats/cas9 editing technologies in breast cancer research. Transl Surg [serial online] 2017 [cited 2017 Sep 24];2:44-9. Available from: http://www.translsurg.com/text.asp?2017/2/2/44/208867


  Introduction Top


Breast cancer (BC) is the most common noncutaneous cancer, accounting for 30% of all female cancers and is the leading cause of cancer deaths among women (15%).[1],[2] It is also one of the most heterogeneous diseases.[3] Despite great therapeutic and diagnostic progress, the understanding and implementation of individualized screening and management of BC are still in their infancy.[4],[5],[6],[7],[8],[9] Oncologists aim to identify high-risk individuals, detect cancer at an early stage, predict outcome, monitor treatment, and screen for disease recurrence.[10],[11],[12],[13],[14],[15] Tumor/node/metastasis classification of malignant tumors features such as tumor size, lymph node stage, histological grade, type, and lymphovascular invasion are still the dominant variables in predicting the course of the disease. However, the specific clinical and pathological features of each patient's BC diagnosis determine the response to specific agents and thus the prognosis. Some therapeutic targets (e.g., estrogen receptor [ER], progesterone receptor or human epidermal receptor 2) are also known predictive factors. Prognostic factors, however, are still not sufficiently elaborated.[10],[11],[12],[16],[17],[18],[19] In addition, as the tumor progresses and/or metastasizes, cancer's molecular features change, making marker proteins not always suitable for follow-up.[20],[21],[22],[23],[24],[25],[26],[27],[28] There is a tremendous need for personalized management approaches to avoid an over- or under-treatment.[28] Accordingly, gene-expression analyses are evolving. A number of methods for an effective and efficient quantification of specific gene expression status have been established.[29],[30],[31],[32],[33] Still, proving a statistical correlation between the gene expression and the overall disease-free-survival is merely the first hurdle in finding clinical application for this system.[34],[35],[36],[37],[38],[39]

Recently, a novel method revolutionized the world of cancer research: the clustered regularly interspersed short palindromic repeats (CRISPR)-Cas9, an RNA-programmable system,[40],[41],[42],[43],[44],[45],[46] which allows rapid generation of any desired modification to the genome in cellular and animal models at low cost.


  Physiogenetic Background Top


CRISPR are found in most bacteria and archaea. They are segments of DNA with short, repetitive base sequences, divided by short segments of spacer DNA from foreign DNA (e.g., viruses or plasmids).[47],[48],[49] CRISPR-associated system (Cas) is found in small clusters, next to CRISPR sequences. CRISPR/Cas is believed to be distinctive for the genome of most prokaryotic DNA and play an important role in the prokaryotic immune system, particularly in providing resistance to bacteriophages. The system allows bacteria to acquire immunity against viruses and develop resistance to them based on a specific spacer, which has been integrated during a viral challenge. A repeated attack of the virus activates the Cas system, which recognizes the exogenous DNA based on the specific RNA in the spacer sequence. Cas proteins cut foreign RNA and protect bacteria from viral replication.[50],[51],[52]


  New Development of Clustered Regularly Interspersed Short Palindromic Repeats/cas9 System Top


More recent developments have brought CRISPR to a new, even more simplified level with only two components: a single synthetic single guide RNA (sgRNA, from fusing trRNA and crRNA).[53],[54],[55],[56] In addition, further Cas9 nucleases have been modified and made more adaptable for targeted gene alterations. The prototype was the wild-type Cas9 that cleaves the DNA at specific sites, which are then repaired by double-strand break repair machinery. A newer model is Cas9D10A, a nickase, which cleaves only one DNA strand, and repairs are conducted in a more precise way.[53],[54],[57],[58],[59],[60],[61],[62] Another option is a nuclease-deficient Cas9 (dCas9), which does not have a cleavage function, but leads to a sequence-specific gene silencing or activation.[57],[58],[63],[64],[65],[66],[67] More strikingly, by fusing dCas9 with an enhanced green fluorescent protein (EGFP), dCas9 has been used for visualization of repetitive DNA sequences or nonrepetitive loci.[68],[69],[70] Most recently, the CRISPR-Cas9 system is increasingly used for repression, activation, and loci imaging.[71],[72],[73] This is offering new options for biomedical, therapeutic, industrial, and biotechnological application.[73]

New Implications for Cancer Research

During the development and progression of cancers, there are numerous mutations taking place. Until now, it was practically impossible to track the mutations occurring (and shaping) the cancer. Precise models, for example, homologous recombination, are limited, time-consuming, involve multiple steps, and are vulnerable to human factor bias. With CRISPR-Cas9, multiple alterations of genes are possible in one generation, whereas multigenerative processes would be necessary to create a vaguely similar result. In addition, CRISPR is advantageous in terms of speed: using the very specific zinc finger nuclease or transcription activator-like effector nucleases approach requires a laborious design, which is more complex than creating RNA-sequences.[40],[74],[75],[76]

Known esterases usually recognize a short sequence, slicing specifically at their locations all along the genome. Cas9 can recognize a sequence of ca. 20 bases. Therefore, CRISPS-Cas9 has provided researchers with a new tool to create highly specific chromosomal rearrangements.[77],[78],[79] Some of them have been reconstructed in cancers, for example, CD74-ROS1 translocation event and the EML4-ALK and KIF5B-RET inversion events in lung cancer.[80],[81],[82],[83],[84],[85] Similar reports have been made for bladder cancer, where circuits against cellular functional genes, including hBAX, p21, and E-cadherin have been constructed, effectively inhibiting cancer cell growth, inducing apoptosis and decreasing cell motility.[86] In animals models, the CRISPR/Cas9 system was used to develop hepatocellular carcinoma in mice tail veins.[87] Constructs have also been achieved for brain cancer and pancreatic cancer.[88],[89],[90]

Significant implications were made in leukemia research: using the CRISPR/Cas9 system, BRD4 protein domain inhibitors were identified as one of the major antitumor agents. Further, screens in mice with acute myeloid leukemia (AML) identified 25 domains, which influence survival-6 known therapeutic domains and 19 new targets.[91],[92]

Clustered Regularly Interspersed Short Palindromic Repeats/Cas9 in Breast Cancer Research

The advantages of CRISPR Cas9 system, such as its simplicity and efficacy, could lead to wider scientific application of this system in modern-day research. Considering the current array of information on the variety of BC-driving mutations and their impact on cancer characteristics, CRISPR could provide crucial insights, in turn, leading to tailored therapeutic approaches.[93],[94],[95]

Annunziato et al.[96] developed a method to model invasive lobular breast carcinoma. They used intraductal injection of creencoding lentiviral vectors to mammary glands, which lead to multifocal tumorigenesis in mice carrying Cdh1/Akt-E17K mutation or conditional Pten alleles. Similarly, injection of lentiviruses with sgRNA targeting Pten resulted in ILC formation without an immune response. Wang et al.[97] aimed to investigate whether CRISPR/Cas9-mediated interruption of transcription in triple-negative BC (TNBC) would have a strong impact on cancer development. Since TNBC is the most aggressive type of BC, bearing the most multifold mutation structure, it is quite stable in the transcriptional program. Disruption of transcription processes could, therefore, lead to a significant instability of the cancer cells. It was shown that TNBC cells were indeed dependent on CDK7 and undergo apoptosis when this transcription kinase is being inhibited. This observation opens a new frontier of therapeutic options for TNBC, potentially with a CRISPR/Cas9-CDK7-cluster.

As in any other CRISPR/Cas9 approach, the initial step is to design sgRNAs for specific cancer cells CRISPR/Cas9 cassette.[98],[99],[100],[101] Scientists now have the ability to generate a number of potential sgRNAs, which have to be evaluated in designed in vitro experiments.In vivo trials would, of course, be the ultimate objective.

Research into the epigenetic identity of estrogen positive BC leads to the discovery that noncoding mutations and inherited single-nucleotide variants outside of genes in ER-positive breast tumors are dominant culprits and promote ESR1 expression. Moreover, the researchers were able to alter the functional regulatory components.[102]

CRISPR/Cas9 has also been applied to investigate whether BCL2-associated X protein (BAX), a proapoptotic protein, could be inserted into human BC cells.In vitro experiments have been conducted, which monitored cell growth and protein expression rate in cells at regular intervals.[86],[103] Scientists assume that adding the BAX gene into the mitochondrial COI gene would decrease ATP production in the cells and increase the BAX protein quantitatively and lead to an increased apoptosis or at least a significant loss of function. The results are still pending but if they turn out to be positive, it will open a new frontier of BC therapies, allowing a cost-effective and specific approach, with potentially far less side effects in comparison to current therapies. The proposed reason for fewer side effects is based on the system's mechanism: Cas9 activity requires a guide RNA (gRNA) to mediate the cleavage specificity. The amount of how much Cas9 will show an off-target activity is dependent on the gRNA substrate.[104] The crucial step in this regard will be the development of cancer cell-specific delivery systems.

Another important step in its development was using CRISPR/Cas9 to study genetic constellation and driver mutations in TNBC in African-American and Caucasian women. BRCA1 or BRCA2 DNA repair genes and R248Q (TP53) wild type were introduced in TNBC on these two distinct genetic backgrounds, anticipating BRCA1/2, and R248Q (TP53) mutations as manifest characteristics of TNBC. TNBC cells were then exposed to radiation and bleomycin. Results of the study are still pending, but it will almost certainly provide significant insights into novel, personalized TNBC treatment options.[105]

Buchholz's team used the expression of Cas9 together with the cancer-specific guide (g) RNAs. In that way, they were able to identify driver mutations of cell growth and viability in BC. The scientists screened over 500,000 reported BC mutations. More than 80% could theoretically be targeted and specifically cleaved with CRISPR/Cas9, without significantly targeting the healthy, wildtype alleles.

CRISPR/Cas9 also has implications for the investigation of some of the established therapies of BC, for example, taxol (paclitaxel).[106],[107] It is frequently and broadly used, with mediocre results. However, more than half of the patients face developing resistance to this chemotherapeutic agent.

Since BC is a heterogeneous neoplasia, new developments of CRISPR/Cas9 aiming to target multiple genes are most promising in the search for new therapeutic approaches. In addition, the epigenetic implication of CRISPR/Cas9 is very promising, as it will prompt further investigation of the epigenetic profile of various BC types to allow their characteristic expression states to be specifically targeted. When a specific combination of mutations in a particular BC type is known, the CRISPR/Cas9 system can also assist in cancer diagnostics, before an individualized therapy could be initiated.


  Conclusion Top


CRISPR-Cas9 system is a great leap forward in the era of cancer genetics, providing simple and effective genomic manipulation with possible use in personalized medicine and future therapies. Since it can potentially be applied to any cancer cell, it is associated with an enthusiasm rarely seen in oncological research, aiming at modeling cancer, finding tumor suppressor genes or oncogenes, and exploring therapeutic strategies. In the era of whole genome sequencing, we have gained insights into tumorigenetic mutation. However, CRISPR/Cas9 has allowed a functional ratification of tumor mutations. Translating this new knowledge into usable clinical information requires the development of precise, practical tests for clinical diagnostics, monitoring and management of cancer patients.

In simpler models, such as leukemia, the system has already been widely used and was essential in discovering new driver mutations in AML. In solid tumors, especially in extremely heterogeneous ones, such as BC, the research is progressing somewhat slower and faces more challenges. The main obstacle, which is also the main research objective in the CRISPR/Cas9 field, is the delivery of Cas9 into in vivo models. Another main point is the safety aspect-studies needed to make the system applicable to human trials.

The ultimate goal is to use CRISPR-Cas9 as a treatment in cancer by cutting out malignant mutations and replacing them with normal DNA sequences. In the meantime, important knowledge will be gained en route about the pathophysiology and biology of cancers.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Bos R, Zhong H, Hanrahan CF, Mommers EC, Semenza GL, Pinedo HM, Abeloff MD, Simons JW, van Diest PJ, van der Wall E. Levels of hypoxia-inducible factor-1 alpha during breast carcinogenesis. J Natl Cancer Inst 2001;93(4):309-14.  Back to cited text no. 1
    
2.
William L. McGuire Memorial Lecture. In: Winer EP, editor. The Long and Winding Road: Glancing Back, but Moving Forward. Boston, MA: Dana-Farber Cancer Institute; 2016. [ML1].  Back to cited text no. 2
    
3.
Dawson SJ, Rueda OM, Aparicio S, Caldas C. A new genome-driven integrated classification of breast cancer and its implications. EMBO J 2013;32(5):617-28.  Back to cited text no. 3
    
4.
Mohamed A, Krajewski K, Cakar B, Ma CX. Targeted therapy for breast cancer. Am J Pathol 2013;183(4):1096-112.  Back to cited text no. 4
    
5.
Schneider KA. All About Breast Cancer, in Counseling About Cancer: Strategies for Genetic Counseling. 3rd ed. NJ, USA: John Wiley & Sons, Inc., Hoboken; 2011. p. 151-85.  Back to cited text no. 5
    
6.
Liu SV, Melstrom L, Yao K, Russell CA, Sener SF. Neoadjuvant therapy for breast cancer. J Surg Oncol 2010;101(4):283-91.  Back to cited text no. 6
    
7.
Smalley M, Piggott L, Clarkson R. Breast cancer stem cells: Obstacles to therapy. Cancer Lett 2013;338(1):57-62.  Back to cited text no. 7
    
8.
den Hollander P, Savage MI, Brown PH. Targeted therapy for breast cancer prevention. Front Oncol 2013;23(3):250.  Back to cited text no. 8
    
9.
Gray J, Druker B. Genomics: The breast cancer landscape. Nature 2012;486(7403):2-3.  Back to cited text no. 9
    
10.
Bedognetti D, Hendrickx W, Marincola FM, Miller LD. Prognostic and predictive immune gene signatures in breast cancer. Curr Opin Oncol 2015;27(6):433-44.  Back to cited text no. 10
    
11.
van der Leij F, Elkhuizen PH, Bartelink H, van de Vijver MJ. Predictive factors for local recurrence in breast cancer. Semin Radiat Oncol 2012;22(2):100-7.  Back to cited text no. 11
    
12.
Cianfrocca M, Goldstein LJ. Prognostic and predictive factors in early-stage breast cancer. Oncologist 2004;9(6):606-16.  Back to cited text no. 12
    
13.
Whittle JR, Lewis MT, Lindeman GJ, Visvader JE. Patient-derived xenograft models of breast cancer and their predictive power. Breast Cancer Res 2015;17:17.  Back to cited text no. 13
    
14.
Holliday DL, Speirs V. Choosing the right cell line for breast cancer research. Breast Cancer Res 2011;13(4):215.  Back to cited text no. 14
    
15.
Payne SJ, Bowen RL, Jones JL, Wells CA. Predictive markers in breast cancer – The present. Histopathology 2008;52(1):82-90.  Back to cited text no. 15
    
16.
Masood S. Prognostic/predictive factors in breast cancer. Clin Lab Med 2005;25(4):809-25.  Back to cited text no. 16
    
17.
Yersal O, Barutca S. Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J Clin Oncol 2014;5(3):412-24.  Back to cited text no. 17
    
18.
Bundred NJ. Prognostic and predictive factors in breast cancer. Cancer Treat Rev 2001;27(3):137-42.  Back to cited text no. 18
    
19.
Stuckey A. Breast cancer: Epidemiology and risk factors. Clin Obstet Gynecol 2011;54(1):96-102.  Back to cited text no. 19
    
20.
Iwatani T, Matsuda A, Kawabata H, Miura D, Matsushima E. Predictive factors for psychological distress related to diagnosis of breast cancer. Psychooncology 2013;22(3):523-9.  Back to cited text no. 20
    
21.
van la Parra RF, Peer PG, Ernst MF, Bosscha K. Meta-analysis of predictive factors for non-sentinel lymph node metastases in breast cancer patients with a positive SLN. Eur J Surg Oncol 2011;37(4):290-9.  Back to cited text no. 21
    
22.
Lee SM, Park JH, Park HJ. Breast cancer risk factors in Korean women: A literature review. Int Nurs Rev 2008;55(3):355-9.  Back to cited text no. 22
    
23.
Schnitt SJ. Classification and prognosis of invasive breast cancer: From morphology to molecular taxonomy. Mod Pathol 2010;23(2):S60-4.  Back to cited text no. 23
    
24.
De Placido S, De Laurentiis M, Carlomagno C, Gallo C, Perrone F, Pepe S, Ruggiero A, Marinelli A, Pagliarulo C, Panico L, Pettinato G, Petrella G, Bianco AR. Twenty-year results of the Naples GUN randomized trial: Predictive factors of adjuvant tamoxifen efficacy in early breast cancer. Clin Cancer Res 2003;9(3):1039-46.  Back to cited text no. 24
    
25.
Kröger N, Milde-Langosch K, Riethdorf S, Schmoor C, Schumacher M, Zander AR, Löning T. Prognostic and predictive effects of immunohistochemical factors in high-risk primary breast cancer patients. Clin Cancer Res 2006;12(1):159-68.  Back to cited text no. 25
    
26.
Bozhok AA, Semiglazov VF, Semiglazov VV, Arzumanov AS, Klettsel AE. Prognostic and predictive factors in breast cancer. Vopr Onkol 2005;51(4):434-43.  Back to cited text no. 26
    
27.
Allred DC. Issues and updates: Evaluating estrogen receptor-alpha, progesterone receptor, and HER2 in breast cancer. Mod Pathol 2010;23 Suppl 2:S52-9.  Back to cited text no. 27
    
28.
Rocco N, Rispoli C, Pagano G, Ascione S, Compagna R, Danzi M, Accurso A, Amato B. Undertreatment of breast cancer in the elderly. BMC Surg 2013;13 Suppl 2:S26.  Back to cited text no. 28
    
29.
Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H, Chen H, Omeroglu G, Meterissian S, Omeroglu A, Hallett M, Park M. Stromal gene expression predicts clinical outcome in breast cancer. Nat Med 2008;14(5):518-27.  Back to cited text no. 29
    
30.
Reis-Filho JS, Pusztai L. Gene expression profiling in breast cancer: Classification, prognostication, and prediction. Lancet 2011;378(9805):1812-23.  Back to cited text no. 30
    
31.
Ringnér M, Fredlund E, Häkkinen J, Borg Š, Staaf J. GOBO: Gene expression-based outcome for breast cancer online. PLoS One 2011;6(3):e17911.  Back to cited text no. 31
    
32.
Venet D, Dumont JE, Detours V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput Biol 2011;7(10):e1002240.  Back to cited text no. 32
    
33.
Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med 2009;360(8):790-800.  Back to cited text no. 33
    
34.
Yang Y, Han L, Yuan Y, Li J, Hei N, Liang H. Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types. Nat Commun 2014;5:3231.  Back to cited text no. 34
    
35.
Teng YH, Tan WJ, Thike AA, Cheok PY, Tse GM, Wong NS, Yip GW, Bay BH, Tan PH. Mutations in the epidermal growth factor receptor (EGFR) gene in triple negative breast cancer: Possible implications for targeted therapy. Breast Cancer Res 2011;13(2):R35.  Back to cited text no. 35
    
36.
Birgisdottir V, Stefansson OA, Bodvarsdottir SK, Hilmarsdottir H, Jonasson JG, Eyfjord JE. Epigenetic silencing and deletion of the BRCA1 gene in sporadic breast cancer. Breast Cancer Res 2006;8(4):R38.  Back to cited text no. 36
    
37.
De Francesco EM, Lappano R, Santolla MF, Marsico S, Caruso A, Maggiolini M. HIF-1α/GPER signaling mediates the expression of VEGF induced by hypoxia in breast cancer associated fibroblasts (CAFs). Breast Cancer Res 2013;15(4):R64.  Back to cited text no. 37
    
38.
Khetchoumian K, Teletin M, Tisserand J, Mark M, Herquel B, Ignat M, Zucman-Rossi J, Cammas F, Lerouge T, Thibault C, Metzger D, Chambon P, Losson R. Loss of Trim24 (Tif1alpha) gene function confers oncogenic activity to retinoic acid receptor alpha. Nat Genet 2007;39(12):1500-6.  Back to cited text no. 38
    
39.
Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, Demeter J, Perou CM, Lønning PE, Brown PO, Børresen-Dale AL, Botstein D. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 2003;100(14):8418-23.  Back to cited text no. 39
    
40.
Dow LE, Fisher J, O'Rourke KP, Muley A, Kastenhuber ER, Livshits G, Tschaharganeh DF, Socci ND, Lowe SW. Inducible in vivo genome editing with CRISPR-Cas9. Nat Biotechnol 2015;33(4):390-4.  Back to cited text no. 40
    
41.
Liang P, Xu Y, Zhang X, Ding C, Huang R, Zhang Z, Lv J, Xie X, Chen Y, Li Y, Sun Y, Bai Y, Songyang Z, Ma W, Zhou C, Huang J. CRISPR/Cas9-mediated gene editing in human tripronuclear zygotes. Protein Cell 2015;6(5):363-72.  Back to cited text no. 41
    
42.
Belhaj K, Chaparro-Garcia A, Kamoun S, Patron NJ, Nekrasov V. Editing plant genomes with CRISPR/Cas9. Curr Opin Biotechnol 2015;32:76-84.  Back to cited text no. 42
    
43.
Shalem O, Sanjana NE, Zhang F. High-throughput functional genomics using CRISPR-Cas9. Nat Rev Genet 2015;16(5):299-311.  Back to cited text no. 43
    
44.
Ma Y, Zhang L, Huang X. Genome modification by CRISPR/Cas9. FEBS J 2014;281(23):5186-93.  Back to cited text no. 44
    
45.
Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR, Dahlman JE, Parnas O, Eisenhaure TM, Jovanovic M, Graham DB, Jhunjhunwala S, Heidenreich M, Xavier RJ, Langer R, Anderson DG, Hacohen N, Regev A, Feng G, Sharp PA, Zhang F. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 2014;159(2):440-55.  Back to cited text no. 45
    
46.
Bortesi L, Fischer R. The CRISPR/Cas9 system for plant genome editing and beyond. Biotechnol Adv 2015;33(1):41-52.  Back to cited text no. 46
    
47.
Cui Y, Li Y, Gorgé O, Platonov ME, Yan Y, Guo Z, Pourcel C, Dentovskaya SV, Balakhonov SV, Wang X, Song Y, Anisimov AP, Vergnaud G, Yang R. Insight into microevolution of Yersinia pestis by clustered regularly interspaced short palindromic repeats. PLoS One 2008;3(7):e2652.  Back to cited text no. 47
    
48.
Beloglazova N, Brown G, Zimmerman MD, Proudfoot M, Makarova KS, Kudritska M, Kochinyan S, Wang S, Chruszcz M, Minor W, Koonin EV, Edwards AM, Savchenko A, Yakunin AF. A novel family of sequence-specific endoribonucleases associated with the clustered regularly interspaced short palindromic repeats. J Biol Chem 2008;283(29):20361-71.  Back to cited text no. 48
    
49.
Richter C, Chang JT, Fineran PC. Function and regulation of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated (Cas) systems. Viruses 2012;4(10):2291-311.  Back to cited text no. 49
    
50.
Wang L, He J, Wang J. Advances in clustered regularly interspaced short palindromic repeats – A review. Wei Sheng Wu Xue Bao 2011;51(8):1007-13. (in Chinese)  Back to cited text no. 50
    
51.
Grissa I, Vergnaud G, Pourcel C. Clustered regularly interspaced short palindromic repeats (CRISPRs) for the genotyping of bacterial pathogens. Methods Mol Biol 2009;551:105-16.  Back to cited text no. 51
    
52.
Pride DT, Salzman J, Relman DA. Comparisons of clustered regularly interspaced short palindromic repeats and viromes in human saliva reveal bacterial adaptations to salivary viruses. Environ Microbiol 2012;14(9):2564-76.  Back to cited text no. 52
    
53.
Schmidt T, Schmid-Burgk JL, Hornung V. Synthesis of an arrayed sgRNA library targeting the human genome. Sci Rep 2015;8(5):14987.  Back to cited text no. 53
    
54.
Hashimoto M, Yamashita Y, Takemoto T. Electroporation of Cas9 protein/sgRNA into early pronuclear zygotes generates non-mosaic mutants in the mouse. Dev Biol 2016;418(1):1-9.  Back to cited text no. 54
    
55.
Radzisheuskaya A, Shlyueva D, Muller I, Helin K. Optimizing sgRNA position markedly improves the efficiency of CRISPR/dCas9-mediated transcriptional repression. Nucleic Acids Res 2016;44(18):e141.  Back to cited text no. 55
    
56.
Xu H, Xiao T, Chen CH, Li W, Meyer CA, Wu Q, Wu D, Cong L, Zhang F, Liu JS, Brown M, Liu XS. Sequence determinants of improved CRISPR sgRNA design. Genome Res 2015;25(8):1147-57.  Back to cited text no. 56
    
57.
Chiang TW, le Sage C, Larrieu D, Demir M, Jackson SP. CRISPR-Cas9(D10A) nickase-based genotypic and phenotypic screening to enhance genome editing. Sci Rep 2016;15(6):24356.  Back to cited text no. 57
    
58.
Truong DJ, Kühner K, Kühn R, Werfel S, Engelhardt S, Wurst W, Ortiz O. Development of an intein-mediated split-Cas9 system for gene therapy. Nucleic Acids Res 2015;43(13):6450-8.  Back to cited text no. 58
    
59.
Li K, Wang G, Andersen T, Zhou P, Pu WT. Optimization of genome engineering approaches with the CRISPR/Cas9 system. PLoS One 2014;9(8):e105779.  Back to cited text no. 59
    
60.
Frock RL, Hu J, Meyers RM, Ho YJ, Kii E, Alt FW. Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases. Nat Biotechnol 2015;33(2):179-86.  Back to cited text no. 60
    
61.
Renouf B, Piganeau M, Ghezraoui H, Jasin M, Brunet E. Creating cancer translocations in human cells using Cas9 DSBs and nCas9 paired nicks. Methods Enzymol 2014;546:251-71.  Back to cited text no. 61
    
62.
Shetty DK, Inamdar MS. Generation of a heterozygous knockout human embryonic stem cell line for the OCIAD1 locus using CRISPR/CAS9 mediated targeting: BJNhem20-OCIAD1-CRISPR-20. Stem Cell Res 2016;16(2):207-9.  Back to cited text no. 62
    
63.
Hess GT, Frésard L, Han K, Lee CH, Li A, Cimprich KA, Montgomery SB, Bassik MC. Directed evolution using dCas9-targeted somatic hypermutation in mammalian cells. Nat Methods 2016;13(12):1036-42.  Back to cited text no. 63
    
64.
Braun CJ, Bruno PM, Horlbeck MA, Gilbert LA, Weissman JS, Hemann MT. Versatile in vivo regulation of tumor phenotypes by dCas9-mediated transcriptional perturbation. Proc Natl Acad Sci U S A 2016;113(27):E3892-900.  Back to cited text no. 64
    
65.
Ma D, Peng S, Xie Z. Integration and exchange of split dCas9 domains for transcriptional controls in mammalian cells. Nat Commun 2016;3(7):13056.  Back to cited text no. 65
    
66.
Gao Y, Xiong X, Wong S, Charles EJ, Lim WA, Qi LS. Complex transcriptional modulation with orthogonal and inducible dCas9 regulators. Nat Methods 2016;13(12):1043-9.  Back to cited text no. 66
    
67.
Balboa D, Weltner J, Eurola S, Trokovic R, Wartiovaara K, Otonkoski T. Conditionally stabilized dCas9 activator for controlling gene expression in human cell reprogramming and differentiation. Stem Cell Reports 2015;5(3):448-59.  Back to cited text no. 67
    
68.
Ma H, Tu LC, Naseri A, Huisman M, Zhang S, Grunwald D, Pederson T. Multiplexed labeling of genomic loci with dCas9 and engineered sgRNAs using CRISPRainbow. Nat Biotechnol 2016;34(5):528-30.  Back to cited text no. 68
    
69.
Gao X, Tsang JC, Gaba F, Wu D, Lu L, Liu P. Comparison of TALE designer transcription factors and the CRISPR/dCas9 in regulation of gene expression by targeting enhancers. Nucleic Acids Res 2014;42(20):e155.  Back to cited text no. 69
    
70.
Wyvekens N, Topkar VV, Khayter C, Joung JK, Tsai SQ. Dimeric CRISPR RNA-Guided FokI-dCas9 nucleases directed by truncated gRNAs for highly specific genome editing. Hum Gene Ther 2015;26(7):425-31.  Back to cited text no. 70
    
71.
Chung ME, Yeh IH, Sung LY, Wu MY, Chao YP, Ng IS, Hu YC. Enhanced integration of large DNA into E. coli chromosome by CRISPR/Cas9. Biotechnol Bioeng 2017;114(1):172-83.  Back to cited text no. 71
    
72.
Mcdade JR, Waxmonsky NC, Swanson LE, Fan M. Practical considerations for using pooled lentiviral CRISPR libraries. Curr Protoc Mol Biol 2016;115:31.5.1-31.5.13.  Back to cited text no. 72
    
73.
Singh V, Braddick D, Dhar PK. Exploring the potential of genome editing CRISPR-Cas9 technology. Gene 2017;30(599):1-18.  Back to cited text no. 73
    
74.
Sternberg SH, Redding S, Jinek M, Greene EC, Doudna JA. DNA interrogation by the CRISPR RNA-guided endonuclease Cas9. Nature 2014;507(7490):62-7.  Back to cited text no. 74
    
75.
Nishimasu H, Ran FA, Hsu PD, Konermann S, Shehata SI, Dohmae N, Ishitani R, Zhang F, Nureki O. Crystal structure of Cas9 in complex with guide RNA and target DNA. Cell 2014;156(5):935-49.  Back to cited text no. 75
    
76.
Wu X, Kriz AJ, Sharp PA. Target specificity of the CRISPR-Cas9 system. Quant Biol 2014;2(2):59-70.  Back to cited text no. 76
    
77.
Shalem O, Sanjana NE, Hartenian E, Shi X, Scott DA, Mikkelsen TS, Heckl D, Ebert BL, Root DE, Doench JG, Zhang F. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 2014;343(6166):84-7.  Back to cited text no. 77
    
78.
Doudna JA, Charpentier E. Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 2014;346(6213):1258096.  Back to cited text no. 78
    
79.
Biolabs NE. CRISPR/Cas9 and targeted genome editing: A new era in molecular biology. MA 01938-2723, USA: New Engl BioLabs; 2007. p. 1-4.  Back to cited text no. 79
    
80.
Bergethon K, Shaw AT, Ou SH, Katayama R, Lovly CM, McDonald NT, Massion PP, Siwak-Tapp C, Gonzalez A, Fang R, Mark EJ, Batten JM, Chen H, Wilner KD, Kwak EL, Clark JW, Carbone DP, Ji H, Engelman JA, Mino-Kenudson M, Pao W, Iafrate AJ. ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol 2012;30(8):863-70.  Back to cited text no. 80
    
81.
Rimkunas VM, Crosby KE, Li D, Hu Y, Kelly ME, Gu TL, Mack JS, Silver MR, Zhou X, Haack H. Analysis of receptor tyrosine kinase ROS1-positive tumors in non-small cell lung cancer: Identification of a FIG-ROS1 fusion. Clin Cancer Res 2012;18(16):4449-57.  Back to cited text no. 81
    
82.
Pennisi E. The CRISPR Craze. Science 2013;341(6148):833-6.  Back to cited text no. 82
    
83.
Awad MM, Katayama R, McTigue M, Liu W, Deng YL, Brooun A, Friboulet L, Huang D, Falk MD, Timofeevski S, Wilner KD, Lockerman EL, Khan TM, Mahmood S, Gainor JF, Digumarthy SR, Stone JR, Mino-Kenudson M, Christensen JG, Iafrate AJ, Engelman JA, Shaw AT. Acquired resistance to crizotinib from a mutation in CD74-ROS1. N Engl J Med 2013;368(25):2395-401.  Back to cited text no. 83
    
84.
Katayama R, Kobayashi Y, Friboulet L, Lockerman EL, Koike S, Shaw AT, Engelman JA, Fujita N. Cabozantinib overcomes crizotinib resistance in ROS1 fusion-positive cancer. Clin Cancer Res 2015;21(1):166-74.  Back to cited text no. 84
    
85.
Matsuura S, Shinmura K, Kamo T, Igarashi H, Maruyama K, Tajima M, Ogawa H, Tanahashi M, Niwa H, Funai K, Kohno T, Suda T, Sugimura H. CD74-ROS1 fusion transcripts in resected non-small cell lung carcinoma. Oncol Rep 2013;30(4):1675-80.  Back to cited text no. 85
    
86.
Liu Y, Zeng Y, Liu L, Zhuang C, Fu X, Huang W, Cai Z. Synthesizing AND gate genetic circuits based on CRISPR-Cas9 for identification of bladder cancer cells. Nat Commun 2014;6(5):5393.  Back to cited text no. 86
    
87.
Xue W, Chen S, Yin H, Tammela T, Papagiannakopoulos T, Joshi NS, Cai W, Yang G, Bronson R, Crowley DG, Zhang F, Anderson DG, Sharp PA, Jacks T. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 2014;514(7522):380-4.  Back to cited text no. 87
    
88.
Weber J, Öllinger R, Friedrich M, Ehmer U, Barenboim M, Steiger K, Heid I, Mueller S, Maresch R, Engleitner T, Gross N, Geumann U, Fu B, Segler A, Yuan D, Lange S, Strong A, de la Rosa J, Esposito I, Liu P, Cadiñanos J, Vassiliou GS, Schmid RM, Schneider G, Unger K, Yang F, Braren R, Heikenwälder M, Varela I, Saur D, Bradley A, Rad R. CRISPR/Cas9 somatic multiplex-mutagenesis for high-throughput functional cancer genomics in mice. Proc Natl Acad Sci U S A 2015;112(45):13982-7.  Back to cited text no. 88
    
89.
Zuckermann M, Hovestadt V, Knobbe-Thomsen CB, Zapatka M, Northcott PA, Schramm K1, Belic J, Jones DT, Tschida B, Moriarity B, Largaespada D, Roussel MF, Korshunov A, Reifenberger G, Pfister SM, Lichter P, Kawauchi D, Gronych J. Somatic CRISPR/Cas9-mediated tumour suppressor disruption enables versatile brain tumour modelling. Nat Commun 2015;11(6):7391.  Back to cited text no. 89
    
90.
Chiou SH, Winters IP, Wang J, Naranjo S, Dudgeon C, Tamburini FB, Brady JJ, Yang D, Grüner BM, Chuang CH, Caswell DR, Zeng H, Chu P, Kim GE, Carpizo DR, Kim SK, Winslow MM. Pancreatic cancer modeling using retrograde viral vector delivery and in vivo CRISPR/Cas9-mediated somatic genome editing. Genes Dev 2015;29(14):1576-85.  Back to cited text no. 90
    
91.
Heckl D, Kowalczyk MS, Yudovich D, Belizaire R, Puram RV, McConkey ME, Thielke A, Aster JC, Regev A, Ebert BL. Generation of mouse models of myeloid malignancy with combinatorial genetic lesions using CRISPR-Cas9 genome editing. Nat Biotechnol 2014;32(9):941-6.  Back to cited text no. 91
    
92.
Shi J, Wang E, Milazzo JP, Wang Z, Kinney JB, Vakoc CR. Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains. Nat Biotechnol 2015;33(6):661-7.  Back to cited text no. 92
    
93.
Ciriello G, Gatza ML, Beck AH, Wilkerson MD, Rhie SK, Pastore A, Zhang H, McLellan M, Yau C, Kandoth C, Bowlby R, Shen H, Hayat S, Fieldhouse R, Lester SC, Tse GM, Factor RE, Collins LC, Allison KH, Chen YY, Jensen K, Johnson NB, Oesterreich S, Mills GB, Cherniack AD, Robertson G, Benz C, Sander C, Laird PW, Hoadley KA, King TA. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 2015;163(2):506-19.  Back to cited text no. 93
    
94.
Morganella S, Alexandrov LB, Glodzik D, Zou X, Davies H, Staaf J, Sieuwerts AM, Brinkman AB, Martin S, Ramakrishna M, Butler A, Kim HY, Borg Š, Sotiriou C, Futreal PA, Campbell PJ, Span PN, Van Laere S, Lakhani SR, Eyfjord JE, Thompson AM, Stunnenberg HG, van de Vijver MJ, Martens JW, Børresen-Dale AL, Richardson AL, Kong G, Thomas G, Sale J, Rada C, Stratton MR, Birney E, Nik-Zainal S. The topography of mutational processes in breast cancer genomes. Nat Commun 2016;2(7):11383.  Back to cited text no. 94
    
95.
Nik-Zainal S, Davies H, Staaf J, Ramakrishna M, Glodzik D, Zou X, Martincorena I, Alexandrov LB, Martin S, Wedge DC, Van Loo P, Ju YS, Smid M, Brinkman AB, Morganella S, Aure MR, Lingjærde OC, Langerød A, Ringnér M, Ahn SM, Boyault S, Brock JE, Broeks A, Butler A, Desmedt C, Dirix L, Dronov S, Fatima A, Foekens JA, Gerstung M, Hooijer GK, Jang SJ, Jones DR, Kim HY, King TA, Krishnamurthy S, Lee HJ, Lee JY, Li Y, McLaren S, Menzies A, Mustonen V, O'Meara S, Pauporté I, Pivot X, Purdie CA, Raine K, Ramakrishnan K, Rodríguez-González FG, Romieu G, Sieuwerts AM, Simpson PT, Shepherd R, Stebbings L, Stefansson OA, Teague J, Tommasi S, Treilleux I, Van den Eynden GG, Vermeulen P, Vincent-Salomon A, Yates L, Caldas C, van't Veer L, Tutt A, Knappskog S, Tan BK, Jonkers J, Borg Š, Ueno NT, Sotiriou C, Viari A, Futreal PA, Campbell PJ, Span PN, Van Laere S, Lakhani SR, Eyfjord JE, Thompson AM, Birney E, Stunnenberg HG, van de Vijver MJ, Martens JW, Børresen-Dale AL, Richardson AL, Kong G, Thomas G, Stratton MR. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 2016;534(7605):47-54.  Back to cited text no. 95
    
96.
Annunziato S, Kas SM, Nethe M, Yucel H, Del Bravo J, Pritchard C, Bin Ali R, van Gerwen B, Siteur B, Drenth AP, Schut E, van de Ven M, Boelens MC, Klarenbeek S, Huijbers IJ, van Miltenburg MH, Jonkers J. Modeling invasive lobular breast carcinoma by CRISPR/Cas9-mediated somatic genome editing of the mammary gland. Genes Dev 2016;30(12):1470-80.  Back to cited text no. 96
    
97.
Wang Y, Zhang T, Kwiatkowski N, Abraham BJ, Lee TI, Xie S, Yuzugullu H, Von T, Li H, Lin Z, Stover DG, Lim E, Wang ZC, Iglehart JD, Young RA, Gray NS, Zhao JJ. CDK7-dependent transcriptional addiction in triple-negative breast cancer. Cell 2015;163(1):174-86.  Back to cited text no. 97
    
98.
Port F, Bullock SL. Augmenting CRISPR applications in Drosophila with tRNA-flanked sgRNAs. Nat Methods 2016;13(10):852-4.  Back to cited text no. 98
    
99.
Moreno-Mateos MA, Vejnar CE, Beaudoin JD, Fernandez JP, Mis EK, Khokha MK, Giraldez AJ. CRISPRscan: Designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo. Nat Methods 2015;12(10):982-8.  Back to cited text no. 99
    
100.
Liang G, Zhang H, Lou D, Yu D. Selection of highly efficient sgRNAs for CRISPR/Cas9-based plant genome editing. Sci Rep 2016;19(6):21451.  Back to cited text no. 100
    
101.
Zhou J, Wang J, Shen B, Chen L, Su Y, Yang J, Zhang W, Tian X, Huang X. Dual sgRNAs facilitate CRISPR/Cas9-mediated mouse genome targeting. FEBS J 2014;281(7):1717-25.  Back to cited text no. 101
    
102.
Bailey SD, Desai K, Kron KJ, Mazrooei P, Sinnott-Armstrong NA, Treloar AE, Dowar M, Thu KL, Cescon DW, Silvester J, Yang SY1, Wu X, Pezo RC, Haibe-Kains B, Mak TW, Bedard PL, Pugh TJ, Sallari RC, Lupien M. Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer. Nat Genet 2016;48(10):1260-6.  Back to cited text no. 102
    
103.
Bax JJ, Lamb HJ, Poldermans D, Schalij MJ, de Roos A, van der Wall EE. Non-compaction cardiomyopathy-echocardiographic diagnosis. Eur J Echocardiogr 2002;3(4):301-2.  Back to cited text no. 103
    
104.
Jiang W, Brueggeman AJ, Horken KM, Plucinak TM, Weeks DP. Successful transient expression of Cas9 and single guideRNA genes in Chlamydomonas reinhardtii. Eukaryot Cell 2014;13(11):1465-9.  Back to cited text no. 104
    
105.
Jerome C. Model for Induced Apoptosis in Breast Cancer via CRISPR/Cas9 Gene Editing. Poster. Available from: https://www.sfcollege.edu/Assets/sf/rue/pdfs/2016/jerome_craig.pdf.  Back to cited text no. 105
    
106.
Doudna JA, Charpentier E. The new frontier of genome engineering with CRISPR-Cas9. Science 2014;346(6213):1258096.  Back to cited text no. 106
    
107.
Frasci G, Comella P, Rinaldo M, Iodice G, Di Bonito M, D'Aiuto M, Petrillo A, Lastoria S, Siani C, Comella G, D'Aiuto G. Preoperative weekly cisplatin-epirubicin-paclitaxel with G-CSF support in triple-negative large operable breast cancer. Ann Oncol 2009;20(7):1185-92.  Back to cited text no. 107
    




 

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