Evidence map›Paper›PMID 36925702›Full record

ReviewBioengineering & translational medicine2023

Optimization of CRISPR-Cas system for clinical cancer therapy.

Xiang Meng, Tian-Gang Wu, Qiu-Yue Lou, Kai-Yuan Niu, Lei Jiang, Qing-Zhong Xiao, Tao Xu, Lei Zhang

Open access · goldFull text readReview
In one paragraph

Review in Bioengineering & translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Optimization of CRISPR-Cas system for clinical cancer therapy.Bioengineering & translational medicine · 2023
    Review
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

8 authors at 3 institutions in 2 countries.

Xiang MengCollege & Hospital of Stomatology Anhui Medical University, Key Laboratory of Oral Diseases Research of Anhui Province Hefei People's Republic of China.
Tian-Gang WuCollege & Hospital of Stomatology Anhui Medical University, Key Laboratory of Oral Diseases Research of Anhui Province Hefei People's Republic of China.
Qiu-Yue LouAnhui Provincial Center for Disease Control and Prevention Hefei People's Republic of China.
Kai-Yuan NiuClinical Pharmacology, William Harvey Research Institute (WHRI), Barts and The London School of Medicine and Dentistry Queen Mary University of London (QMUL) Heart Centre (G23) London UK.
Lei JiangCollege & Hospital of Stomatology Anhui Medical University, Key Laboratory of Oral Diseases Research of Anhui Province Hefei People's Republic of China.
Qing-Zhong XiaoClinical Pharmacology, William Harvey Research Institute (WHRI), Barts and The London School of Medicine and Dentistry Queen Mary University of London (QMUL) Heart Centre (G23) London UK.
Tao XuSchool of Pharmacy, Anhui Key Laboratory of Bioactivity of Natural Products Anhui Medical University Hefei China.
Lei ZhangCollege & Hospital of Stomatology Anhui Medical University, Key Laboratory of Oral Diseases Research of Anhui Province Hefei People's Republic of China.ORCID https://orcid.org/0000-0003-2424-7019
Anhui Medical University · CNQueen Mary University of London · GBAnhui Provincial Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems. Currently, the applications of CRISPR-Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR-Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR-Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR-Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR-Cas systems. By modifying the CRISPR-Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR-Cas system are emerging.

Indexed as

cancerCRISPR–Casgene editingsynthetic biologyvector delivery

Identifiers

PMID36925702
PMCPMC10013785
OpenAlexW4312118180

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read30
identifiers read32
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.