Evidence map›Paper›PMID 36153384›Full record

ArticleCommunications biology2022

Targeting non-coding RNA family members with artificial endonuclease XNAzymes.

Maria J Donde, Adam M Rochussen, Saksham Kapoor, Alexander I Taylor

Abstract read
In one paragraph

Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
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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

4 authors.

Maria J DondeCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.ORCID 0000-0003-4216-4719
Adam M RochussenCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.ORCID 0000-0001-9439-1206
Saksham KapoorCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
Alexander I TaylorCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK. ait29@cam.ac.uk.ORCID 0000-0001-7684-1437

Funding

Wellcome TrustWellcome Trust 215453/Z/19/Z
6 · The paper itself

Abstract

Non-coding RNAs (ncRNAs) offer a wealth of therapeutic targets for a range of diseases. However, secondary structures and high similarity within sequence families make specific knockdown challenging. Here, we engineer a series of artificial oligonucleotide enzymes (XNAzymes) composed of 2'-deoxy-2'-fluoro-β-D-arabino nucleic acid (FANA) that specifically or preferentially cleave individual ncRNA family members under quasi-physiological conditions, including members of the classic microRNA cluster miR-17~92 (oncomiR-1) and the Y RNA hY5. We demonstrate self-assembly of three anti-miR XNAzymes into a biostable catalytic XNA nanostructure, which targets the cancer-associated microRNAs miR-17, miR-20a and miR-21. Our results provide a starting point for the development of XNAzymes as a platform technology for precision knockdown of specific non-coding RNAs, with the potential to reduce off-target effects compared with other nucleic acid technologies.

Indexed as

MicroRNAsNucleic AcidsAntagomirsEndonucleasesHumansOligonucleotidesRNA, UntranslatedAntagomirsEndonucleasesMicroRNAsNucleic AcidsOligonucleotidesRNA, Untranslated

Identifiers

PMID36153384
PMCPMC9509326

What OpenQuestion holds

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LicenceCC BY
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.