Evidence map›Paper›PMID 34589286›Full record

ArticleMolecular therapy. Nucleic acids2021

Chimeric RNA-binding protein-based killing switch targeting hepatocellular carcinoma cells.

Jiong Yang, Shigang Ding

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Host factorFrontiers in immunology · 2024
    Article
  4. Article
  5. Review
  6. Article
  7. Aptamer-Array-Guided Protein Assembly Enhances Synthetic mRNA Switch Performance.Angewandte Chemie (International ed. in English) · 2022
    Article
  8. Review
  9. 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

2 authors at 1 institution in 1 country.

Jiong YangDepartment of Gastroenterology, Peking University Third Hospital, Beijing 100191, China.
Shigang DingDepartment of Gastroenterology, Peking University Third Hospital, Beijing 100191, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cell-specific killing switches are synthetic circuits developed as an intelligent weapon to specifically eliminate malignant cells. RNA-delivered synthetic circuits provide safer means to control oncolytic functions, in which proteolysis-responding capsid-cNOT7 is developed to enable logic computation and modular design. Unfortunately, although circuits containing these capsid-cNOT7s exhibited good performance when introduced as replicons, in modified mRNA (modRNA) delivery, the performance was not quite as good. To improve this situation, alternative modules suitable for modRNA delivery need to be developed. An attractive option is RNA-binding protein (RBP)/riboswitches. In this study, RBPs were engineered by fusing with degron and cleavage sites. The compatibility of these chimeric RBPs with proteolysis-based sensing units were tested. Eight two-input logic gates and four three-input logic gates were implemented. After building this chimeric RBP-based system, we constructed a hepatocellular carcinoma (HCC) cell-specific killing circuit using two proteolysis-based sensing units, a two-input logic OR gate, and a leakproof apoptosis-inducing actuator, which distinguished HCC cells and induced apoptosis in a mixed IMR90-PLC/PRF/5 population.

Indexed as

HCCmodRNA deliveryproteaseRNA-binding proteinsynthetic circuit

Identifiers

PMID34589286
PMCPMC8463442
OpenAlexW3194552982

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.