ArticleMolecular therapy. Nucleic acids2014
Identification and Characterization of an eIF4e DNA Aptamer That Inhibits Proliferation With High Throughput Sequencing.
Article in Molecular therapy. Nucleic acids, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Aptamer and N-Degron Ensemble (AptaGron) as a Target Protein Degradation Strategy.ACS chemical biology · 2024Article
- RNA binding proteins (RBPs) and their role in DNA damage and radiation response in cancer.Advanced drug delivery reviews · 2022Review
- Cellular delivery of dinucleotides by conjugation with small molecules: targeting translation initiation for anticancer applications.Chemical science · 2021Article
- Aptamer-targeting of Aleutian mink disease virus (AMDV) can be an effective strategy to inhibit virus replication.Scientific reports · 2021Article
- Developing anti-neoplastic biotherapeutics against eIF4F.Cellular and molecular life sciences : CMLS · 2017Review
- Ligand-targeted theranostic nanomedicines against cancer.Journal of controlled release : official journal of the Controlled Release Society · 2016Review
- High throughput sequencing analysis of RNA libraries reveals the influences of initial library and PCR methods on SELEX efficiency.Scientific reports · 2016Article
- A Highlight of Recent Advances in Aptamer Technology and Its Application.Molecules (Basel, Switzerland) · 2015Review
- Synthetic biology for pharmaceutical drug discovery.Drug design, development and therapy · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Development of DNA aptamer screens that are both simple and informative can increase the success rate of DNA aptamer selection and induce greater adoption. High eIF4e levels contribute to malignancies, thus eIF4e presents itself as a valuable target for DNA aptamer-based inhibition screen. Here, we demonstrate a method for the rapid selection of looped DNA aptamers against eIF4e by combining negative selection and purification in a single step, followed by characterization with high throughput sequencing. The resulting aptamers show functional binding to eIF4e and inhibit translation initiation in biochemical assays. When transfected into cells, eIF4e aptamers cause a dramatic loss of cell proliferation in tumor cells as seen with eIF4e knockdown with antisense oligonucleotides, shRNAs, and siRNAs, hinting at therapeutic possibilities. With the large data set provided by high throughput sequencing, we demonstrate that selection happens in waves and that sequencing data can be used to infer aptamer structure. Lastly, we show that ligation of looped aptamers can enhance their functional effects. These results demonstrate a rapid protocol to screen and optimize aptamers against macromolecules of interest.
Identifiers
What OpenQuestion holds
Registered trials
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.