To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases
Abstract
:1. The Evolution and Usefulness of Random Mutagenesis in Cancers
2. Application of CRISPR Libraries, Optimization of gRNA, and Efficient Next-Generation Libraries
3. CRISPR Screening Focusing on Synthetic Lethality
4. Efficient CRISPR Screening Using the Database to Avoid Pitfalls
5. Use of Database Focusing on Synthetic Lethality
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Name | Advantage | sgRNAS/Gene | Total gRNAs | Ref. |
---|---|---|---|---|
Garnett Lab MinLibCas9 Library | Minimal genome-wide human CRISPR-Cas9 library | 2 | 37,722 | [20] |
Human CRISPR Knockout Pooled Library (Gattinara) | Minimal genome-wide human CRISPR-Cas9 library compatible with the Brunello library | 2 | 40,964 | [21] |
Human GeCKO v2 | Targets early consecutive exons Contains 1000 control (non-targeting) sgRNAs | 3 or 6 | 123,411 | [22] |
Broad GPP genome-wide Brunello | Improved on-target activity predictions and off-target scores compared to the GeCKOv2 library | 4 | 76,441 | [23] |
Human genome-wide library v1 | Targets sites in a region close to the translation initiation site for complete gene disruption | 4 | 77,406 | [24] |
Human improved genome-wide library v1 | gRNAs redesigned using pipeline with a new design Improved on-target sensitivity and reduced off-target effect scaffold | 5 | 90,709 | [25] |
Human genome-wide reduced double-gRNA library | Optimization of guide RNA designs and delivery of two gRNAs with each construct | 3 | 59,576 | [26] |
Human whole genome sgRNA iBAR library | Incorporates four 6-basepair internal barcodes (iBARs) in each sgRNA Efficient and accurate screening at high MOI | 3 | 58,630 | [27] |
Mini-human AsCpf1-based human genome-wide knockout library | Each gene targeted by an AsCpf1(AsCas12a)-based array containing 3–4 guides concatenated in one vector | 3–4 | 17,032 | [28] |
Toronto KnockOut (TKO) version3 | Improved accuracy, efficiency, and scalability for CRISPR screens compared to TKO version 1 | 4 | 70,948 | [29] |
Name | Advantages | sgRNAs/Gene | Total gRNAs | Ref. |
---|---|---|---|---|
Activation | ||||
CRISPRa-v2 | SunTag-VP64 activation system | 5 or 10 | 104,540 or 209,080 | [30] |
SAM (Synergistic Activation Mediator) v1–3 plasmid system | Comprises three plasmids (Cas9-VP64 fusion, gRNA incorporating two MS2 RNA aptamers at the tetraloop and stem-loop 2, and MS2-P65-HST) Efficient gene upregulation | 3 | 70,290 | [13] |
SAM v2–2 plasmid system | Comprises two plasmids (gRNA library–lenti SAM v2 backbone and MS2-P65-HST) Efficient gene upregulation | 3 | 70,290 | [31] |
Human CRISPR lncRNA activation pooled library | SAM library for transcriptional activation of lncRNAs | 10 | 96,458 | [32] |
Broad GPP activation Calabrese p65-HSF | Modified tracrRNA with two MS2 loops and two PP7 loops Better concordance of sgRNAs compared to the SAM v2 library | 3 or 6 | 56,762 (Set A) 56,476 (Set B) | [23] |
Inhibition | ||||
CRISPRi-v2 | dCas9-KRAB represses TSS downstream of TSS sites | 5 or 10 | 104,535 209,070 | [30] |
Broad GPP inhibition Dolcetto | gRNAs redesigned based on FANTOM5 CAGE data Gene regulation equal to the CRISPR KO library | 3 or 6 | 57,050 (Set A) 57,011 (Set B) | [23] |
Cancer Type (Cell Line) | Altered Gene/Drug | CRISPR Type | Library | Synthetic Lethal Hits | Ref. |
---|---|---|---|---|---|
Colorectal cancer (HCT116) | KRAS (G13D) | Knockout | GeCKOv2 | NADK, KHK, INO80C | [39] |
Pancreatic cancer (HPAF-II) | RNF43 | Knockout | TKO | FZD5, Wnt pathway genes | [40] |
Lung squamous cell carcinoma (H226 shp63) | ΔNp63α | Knockout | GeCKOv2 | RHOA, TGFBR2 | [41] |
Small-cell lung cancer (NCI-H82) | RB1−/− | Knockout | Custom | Aurora kinase B | [42] |
Hepatocellular carcinoma (PLC/PRF/5) | ATRX loss | Knockout | GeCKOv2 | WEE1 | [43] |
Chronic myelogenous leukemia (K562) | – | Double knockout | Paired sgRNA | BCL2L1–MCL1 combination | [44] |
T-acute lymphocytic leukemia (CCRF-CEM) | Asparaginase-resistant | Knockout | GeCKO | NKD2, LGR6, ASNS | [45] |
Pancreatic cancer, non-small-cell lung cancer (CFPAC-1, A549, NCIH23) | MEK1/2 inhibition | Knockout | Avana-4 barcoded sgRNA | SHOC2 | [46] |
Colorectal cancer, breast cancer (HCT116, MCF10A) | ATR inhibition | Knockout | TKOv3 | RNASEH2 | [47] |
Triple-negative breast cancer (SUM159, SUM149) | BET bromodomain inhibitor | Knockout | H1 and H2 | CDK4 and BRD2 | [48] |
Murine acute myelogenous leukemia (RN2) | – | Cas12a (Cpf1) multigene knockout | Custom | BRD9 & JMJD6, KAT6A & JMJD6, BRPF1 & JMJD6 | [49] |
Osteosarcoma (U2) | GPX4 (ferroptosis-resistant) | Knockout | Custom | FSP1 (AIFM2) | [50] |
Myc-driven breast cancer model (MYC-ER HMECs) | MYC | Knockout | RNA-binding protein pooled CRISPR knockout | YTHDF2 | [51] |
Colorectal cancer (BRCA2−/− DLD1) | BRCA2 mutation | Knockout | Custom | FEN1, APEX2 | [52] |
Pancreatic cancer (PANC-1) | Gemcitabine | Knockout | Brunello | PSMA6 | [53] |
Pancreatic cancer (PATU8902) | Trametinib | Knockout | GeCKOv2 Avana | CIC, ATXN1L | [54] |
Pancreatic cancer (PDX366) | MEK and CENPE inhibitor | Knockout | Nuclear proteins gRNA sub-pool | CENPE, RRM1 | [55] |
Pancreatic cancer (Mia PaCa-2, A2780) | Gemcitabine, NUC-1031 | Knockout | GeCKOv2 | DCK, DCTPP1 | [56] |
Glioblastoma stem-like cells (2 patient-derived cells) | EGFR+PI3K signaling | Knockout | GeCKOv1 | PKMYT1, WEE1 | [57] |
Primary human retinal pigment epithelial cells (RPE1-hTERT p53−/− Flag-Cas9 cells) | 27 DNA-damaging agents | Knockout | TKO v2 TKO v3 | ERCC6L2, TOP2, ELOF1, STK19 | [58] |
Database | Characteristics | Number of Cell Lines | Usage | Ref. | URL |
---|---|---|---|---|---|
DepMap portal | Integrates CRISPR KO screening databases (DepMap, Sanger, and GeCKO) and unifies cellular model (CCLE) and drug sensitivity (PRISM) databases | 786 cell lines 42 cancer types | Discovering genetic and pharmacological dependenciesPrioritizing tumor contexts and predictive biomarkers Exploring over 2000 cancer models | [60] | https://depmap.org/portal/ (accessed on 24 Octorber 2021) |
Project Score | Genetic screens for identifying cancer dependencies | 914 cell lines 25 tissues 7470 fitness genes | Investigating specific genes, cancer cell models, or tissue types Browsing all gene fitness scores | [61] | https://score.depmap.sanger.ac.uk/ (accessed on 24 Octorber 2021) |
PICKLES (Pooled In-Vitro CRISPR Knockout Library Essentiality Screens) | Cell line essentiality profiles for CRISPR KO library and shRNA datasets | More than 50 cell lines for CRISPR screening and 100 cell lines for shRNA library | Easily exploring cell line essentiality and co-essentiality | [62] | http://pickles.hart-lab.org (accessed on 24 Octorber 2021) |
iCSDB | Integrated DepMap portal and BioGRID ORCS Integrated database of CRISPR-CAS9 screening experiments for human cell lines and clinical information | 976 cell lines | Easily searching for cell line data associated with clinical and molecular data | [63] | https://www.kobic.re.kr/icsdb/ (accessed on 24 Octorber 2021) |
CRISP-view | Data from 167 studies collected from PubMed, Gene Expression Omnibus (GEO), and Ensemble and Cancer Cell Line Encyclopedia (CCLE) | 321 human samples 825 mouse samples | Web interface visualizing datasets, allowing the exploration of interesting genes, cell lines, tissues, studies, or conditions | [64] | http://crispview.weililab.org (accessed on 24 Octorber 2021) |
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Onishi, I.; Yamamoto, K.; Kinowaki, Y.; Kitagawa, M.; Kurata, M. To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases. Int. J. Mol. Sci. 2021, 22, 12322. https://doi.org/10.3390/ijms222212322
Onishi I, Yamamoto K, Kinowaki Y, Kitagawa M, Kurata M. To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases. International Journal of Molecular Sciences. 2021; 22(22):12322. https://doi.org/10.3390/ijms222212322
Chicago/Turabian StyleOnishi, Iichiroh, Kouhei Yamamoto, Yuko Kinowaki, Masanobu Kitagawa, and Morito Kurata. 2021. "To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases" International Journal of Molecular Sciences 22, no. 22: 12322. https://doi.org/10.3390/ijms222212322