Evidence map›Paper›PMID 42049234›Full record

ArticleNucleic acids research2026

In situ tracking of glycoRNAs on single-cell surface to reveal RNA heterogeneity and transport mechanism.

Meilin Gong, Xiaoqi Tang, Zuowei Xie, Ben Niu, Ruijia Deng, Wenjuan Fu, Yingjie Yang, Yu Tang, Jie Luo, Jing Sheng and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Meilin GongDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Xiaoqi TangDepartment of Laboratory Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
Zuowei XieDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Ben NiuDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Ruijia DengDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Wenjuan FuDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Yingjie YangDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Yu TangDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Jie LuoDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Jing ShengDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Ying ZhangDeputy Director and Associate Professor of the Joint Surgery Center at Southwest Hospital, Third Military Medical University, 30 Gaotanyan, Shapingba, Chongqing 400038, China.
Ming ChenDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.
Kai ChangDepartment of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), 30 Gaotanyan, Shapingba District, Chongqing 400038, China.ORCID 0009-0001-1665-8697

Funding

National Natural Science Foundation of China 82122042National Natural Science Foundation of China 82372352National Natural Science Foundation of China 82502825National Natural Science Foundation of China U23A2047National Science and Technology Major Project 2025ZD0551102
6 · The paper itself

Abstract

Cell-surface glycoRNA plays a crucial role in cellular behavior, yet its RNA substrate signatures and membrane transport mechanism remain unclear. Here, we developed GlycoRNA-Lighted In situ Nano-Tracking (GLINT), an approach for the visualization of distinct RNA-specific glycosignatures. GLINT employs a modular, localized concatenated DNA circuit based on a proximity ligation-mediated dual hierarchical hybridization chain reaction (HCR). Metabolically labeled sialic acid probe and RNA-specific probes are combined into a dual-recognition module through proximity ligation. The module subsequently initiates a dual hierarchical HCR cascade, enabling ultrasensitive in situ tracking of U1, U3, U35a, Y5, and U8 glycoRNAs at the single-cell level. Leveraging GLINT technology, glycoRNAs were confirmed to be transported intracellularly via a SNARE protein-mediated secretory extracellular mechanism. Furthermore, the identification of ten subtypes of breast cancer cells was achieved based on the level of distinct RNA-specific glycosignatures on the cell surface. GLINT demonstrates great potential for tracking RNA-specific glycosignatures, offering a powerful tool for in situ cell subtyping and exploration of RNA-related glycosylation processes.

Indexed as

Single-Cell AnalysisCell Line, TumorCell MembraneHumansRNARNA

Identifiers

PMID42049234
PMCPMC13122174

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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.