ArticleProtein & cell2026
Deciphering the RNA landscapes on mammalian cell surfaces.
Article in Protein & cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Defining cell surface and glycosylated RNAs.Trends in genetics : TIG · 2026Review
- Long non-coding RNAs in colorectal cancer: shaping the tumour microenvironment and advancing precision oncology.Nature reviews. Gastroenterology & hepatology · 2026Review
- Review
- Integrated Bioinformatics and in vivo Validation Identify the MTRNR2L1/MTRNR2L10 Axis as a Candidate Regulator Associated with Cortical NLRP3 Inflammasome-Related Signaling in Experimental Epilepsy.Journal of molecular neuroscience : MN · 2026Article
- PREDICTOR: A Non-Enzymatic Catalytic Cascade Tool for in Situ Visualization of Small Extracellular Vesicle Surface glycoRNAs.Journal of extracellular vesicles · 2026Article
- Lectin-based detection and expression profiling of native glycoRNAs.Scientific reports · 2026Article
- GlycoRNA research: from unknown unknowns to known unknowns.Protein & cell · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Cell surface RNAs, notably glycoRNAs, have been reported, yet the precise compositions of surface RNAs across different primary cell types remain unclear. Here, we introduce a comprehensive suite of methodologies for profiling, imaging, and quantifying specific surface RNAs. We present AMOUR, a method leveraging T7-based linear amplification, to profile surface RNAs while preserving plasma membrane integrity. By integrating fluorescently labeled DNA probes with live primary cells, and employing imaging along with flow cytometry analysis, we can effectively image and quantify representative surface RNAs. Utilizing these techniques, we have identified diverse non-coding RNAs present on mammalian cell surfaces, expanding beyond the known glycoRNAs. We confirm the membrane anchorage and quantify the abundance of several representative surface RNA molecules in cultured HeLa cells and human umbilical cord blood mononuclear cells (hUCB-MNCs). Our imaging and flow cytometry analyses unequivocally confirm the membrane localization of Y family RNAs, spliceosomal snRNA U5, mitochondrial rRNA MTRNR2, mitochondrial tRNA MT-TA, VTRNA1-1, and the long non-coding RNA XIST. Our study not only introduces effective approaches for investigating surface RNAs but also provides a detailed portrayal of the surface RNA landscapes of hUCB-MNCs and murine blood cells, paving the way for future research in the field of surface RNAs.
Indexed as
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.