Evidence map›Paper›PMID 36250017›Full record

ReviewFrontiers in molecular biosciences2022

Natural antisense transcripts as drug targets.

Olga Khorkova, Jack Stahl, Aswathy Joji, Claude-Henry Volmar, Zane Zeier, Claes Wahlestedt

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 17 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

6 authors at 1 institution in 1 country.

Olga KhorkovaCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
Jack StahlCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
Aswathy JojiCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
Claude-Henry VolmarCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
Zane ZeierCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
Claes WahlestedtCenter for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States.
University of Miami · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent discovery of vast non-coding RNA-based regulatory networks that can be easily modulated by nucleic acid-based drugs has opened numerous new therapeutic possibilities. Long non-coding RNA, and natural antisense transcripts (NATs) in particular, play a significant role in networks that involve a wide variety of disease-relevant biological mechanisms such as transcription, splicing, translation, mRNA degradation and others. Currently, significant efforts are dedicated to harnessing these newly emerging NAT-mediated biological mechanisms for therapeutic purposes. This review will highlight the recent clinical and pre-clinical developments in this field and survey the advances in nucleic acid-based drug technologies that make these developments possible.

Indexed as

anisense oligonucleotideslong nocoding RNAnatural antisense transcript (NAT)nucleic acid based therapeuticsposttranscriptional regulation

Identifiers

PMID36250017
PMCPMC9563854
OpenAlexW4297311845

What OpenQuestion holds

Textmetadata
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.