Evidence map›Paper›PMID 31148584›Full record

ArticleScientific reports2019

Differential binding cell-SELEX method to identify cell-specific aptamers using high-throughput sequencing.

Karlis Pleiko, Liga Saulite, Vadims Parfejevs, Karlis Miculis, Egils Vjaters, Una Riekstina

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Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

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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

14 citing papers in PubMed.

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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.

Karlis PleikoFaculty of Medicine, University of Latvia, Riga, LV-1004, Latvia. karlis.pleiko@lu.lv.
Liga SauliteFaculty of Medicine, University of Latvia, Riga, LV-1004, Latvia.
Vadims ParfejevsFaculty of Medicine, University of Latvia, Riga, LV-1004, Latvia.
Karlis MiculisPauls Stradins Clinical University Hospital, Riga, LV-1002, Latvia.
Egils VjatersPauls Stradins Clinical University Hospital, Riga, LV-1002, Latvia.
Una RiekstinaFaculty of Medicine, University of Latvia, Riga, LV-1004, Latvia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aptamers have in recent years emerged as a viable alternative to antibodies. High-throughput sequencing (HTS) has revolutionized aptamer research by increasing the number of reads from a few (using Sanger sequencing) to millions (using an HTS approach). Despite the availability and advantages of HTS compared to Sanger sequencing, there are only 50 aptamer HTS sequencing samples available on public databases. HTS data in aptamer research are primarily used to compare sequence enrichment between subsequent selection cycles. This approach does not take full advantage of HTS because the enrichment of sequences during selection can be due to inefficient negative selection when using live cells. Here, we present a differential binding cell-SELEX (systematic evolution of ligands by exponential enrichment) workflow that adapts the FASTAptamer toolbox and bioinformatics tool edgeR, which are primarily used for functional genomics, to achieve more informative metrics about the selection process. We propose a fast and practical high-throughput aptamer identification method to be used with the cell-SELEX technique to increase the aptamer selection rate against live cells. The feasibility of our approach is demonstrated by performing aptamer selection against a clear cell renal cell carcinoma (ccRCC) RCC-MF cell line using the RC-124 cell line from healthy kidney tissue for negative selection.

Indexed as

Aptamers, NucleotideCarcinoma, Renal CellCell LineCell Line, TumorComputational BiologyDrug Delivery SystemsDrug DesignFlow CytometryGene LibraryGenomicsHigh-Throughput Nucleotide SequencingHumansKidney NeoplasmsLigandsMolecular MedicineNucleic Acid ConformationAptamers, NucleotideLigands

Identifiers

PMID31148584
PMCPMC6544647

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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.