Evidence map›Paper›PMID 37620295›Full record

ArticleClinical and translational medicine2023

Split-Cas9-based targeted gene editing and nanobody-mediated proteolysis-targeting chimeras optogenetically coordinated regulation of Survivin to control the fate of cancer cells.

Changping Deng, Shihui Li, Yuping Liu, Wen Bao, Chengnan Xu, Wenyun Zheng, Meiyan Wang, Xingyuan Ma

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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 2 institutions in 1 country.

Changping DengState Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, P. R. China.ORCID 0000-0001-9623-4503
Shihui LiState Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, P. R. China.
Yuping LiuShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, P. R. China.
Wen BaoShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, P. R. China.
Chengnan XuShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, P. R. China.
Wenyun ZhengShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, P. R. China.
Meiyan WangSynthetic Biology and Biomedical Engineering Laboratory, Biomedical Synthetic Biology Research Center, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical, Sciences and School of Life Sciences, East China Normal University, Shanghai, P. R. China.ORCID 0000-0002-2118-6647
Xingyuan MaState Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, P. R. China.ORCID 0000-0002-8740-7748
East China University of Science and Technology · CNEast China Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrecise regulation of partial critical proteins in cancer cells, such as anti-apoptotic proteins, is one of the crucial strategies for treating cancer and discovering related molecular mechanisms. Still, it is also challenging in actual research and practice. The widely used CRISPR/Cas9-based gene editing technology and proteolysis-targeting chimeras (PROTACs) have played an essential role in regulating gene expression and protein function in cells. However, the accuracy and controllability of their targeting remain necessary.

methodsConstruction of UMUC-3-EGFP stable transgenic cell lines using the Sleeping Beauty system, Flow cytometry, quantitative real-time PCR, western blot, fluorescence microplate reader and fluorescence inverted microscope analysis of EGFP intensity. Characterization of Survivin inhibition was done by using Annexin V-FITC/PI apoptosis, calcein/PI/DAPI cell viability/cytotoxicity assay, cloning formation assay and scratch assay. The cell-derived xenograft (CDX) model was constructed to assess the in vivo effects of reducing Survivin expression.

resultsHerein, we established a synergistic control platform that coordinated photoactivatable split-Cas9 targeted gene editing and light-induced protein degradation, on which the Survivin gene in the nucleus was controllably edited by blue light irradiation (named paCas9-Survivin) and simultaneously the Survivin protein in the cytoplasm was degraded precisely by a nanobody-mediated target (named paProtacL-Survivin). Meanwhile, in vitro experiments demonstrated that reducing Survivin expression could effectively promote apoptosis and decrease the proliferation and migration of bladder cancerous cells. Furthermore, the CDX model was constructed using UMUC-3 cell lines, results from animal studies indicated that both the paCas9-Survivin system and paProtacL-Survivin significantly inhibited tumour growth, with higher inhibition rates when combined.

conclusionsIn short, the coordinated regulatory strategies and combinable technology platforms offer clear advantages in controllability and targeting, as well as an excellent reference value and universal applicability in controlling the fate of cancer cells through multi-level regulation of key intracellular factors.

Indexed as

CRISPR-Cas SystemsNeoplasmsAnimalsApoptosisDisease Models, AnimalGene EditingHumansProteolysisSurvivinSurvivinCoordinated regulating to SurvivinFate of cancer cellsNanobody targeted degradationPhotoactivatable proteolysis and editing

Identifiers

PMID37620295
PMCPMC10449816
OpenAlexW4386153872

What OpenQuestion holds

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LicenceCC BY
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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.