Evidence map›Paper›PMID 29158600›Full record

ReviewJournal of human genetics2018

CRISPR/Cas9 library screening for drug target discovery.

Morito Kurata, Kouhei Yamamoto, Branden S Moriarity, Masanobu Kitagawa, David A Largaespada

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of human genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

72 citing papers in PubMed, 109 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Functional Genomics: Principles and Methods.Advances in experimental medicine and biology · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Review

12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Morito KurataDepartment of Comprehensive Pathology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan. kurata.pth2@tmd.ac.jp.
Kouhei YamamotoDepartment of Comprehensive Pathology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
Branden S MoriarityMasonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
Masanobu KitagawaDepartment of Comprehensive Pathology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
David A LargaespadaMasonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
Tokyo Medical and Dental University · JPUniversity of Minnesota · USUniversity of Minnesota Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CRISPR/Cas9-based tools have rapidly developed in recent years. These include CRISPR-based gene activation (CRISPRa) or inhibition (CRISPRi), for which there are libraries. CRISPR libraries for loss of function have been widely used to identify new biological mechanisms, such as drug resistance and cell survival signals. CRISPRa is highly useful in screening for gain of functions, and CRISPRi is a more powerful tool than RNA interference (RNAi) libraries in screening for loss of functions. Positive selection using a CRISPR library can detect survival cells with specific conditions, such as drug treatment, and it can easily clarify drug resistance mechanisms. Negative selection is capable of detecting dead or slow-growing cells efficiently, and it can identify survival-essential genes, which can be promising candidates for molecularly targeted drugs. In addition, negative selection can be applied for synthetic lethality interactions, where the perturbation of both genes simultaneously results in the loss of viability, but that of either gene alone does not affect viability. This mechanism is highly important to identifying the optimal combination of molecularly targeted drugs. Survival-co-essential genes in cancer cells can be identified using new methods, such as the paired guide RNA system and in combination with single-cell RNA sequencing techniques. These efficient methods can clarify interesting biological mechanisms and suggest candidates for molecularly targeted drugs. This review identifies what types of screenings were performed and suggests ideas for the next CRISPR screenings to develop new drugs.

Indexed as

CRISPR-Cas SystemsGene LibraryAnimalsDrug Delivery SystemsDrug DiscoveryHumans

Identifiers

PMID29158600
OpenAlexW2770685832

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.