Evidence map›Paper›PMID 41474357›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Profiling of Integrin Isoforms on Lung-Tropic Exosomes by Spectrally and Kinetically Multiplexed Single-Molecule Imaging.

Songlin Liu, Haixin Wang, Qin Shentu, Liang Yuan, Jiangshan Tie, Li Li, Rui Ai, Bochen Ma, Lubin Qi, Yifei Jiang and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Neuro-tumor interactions in peripheral tumors.Cancer metastasis reviews · 2026
    Review
  7. Harnessing Cuproptosis resistance to advance cancer therapeutics.Apoptosis : an international journal on programmed cell death · 2026
    Review
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

11 authors.

Songlin LiuSchool of Chemistry and Materials, University of Science and Technology of China, Hefei, Anhui, 230026, P. R. China.ORCID https://orcid.org/0009-0005-6697-0960
Haixin WangHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Qin ShentuHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Liang YuanHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Jiangshan TieHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Li LiHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Rui AiHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Bochen MaHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.
Lubin QiHangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, 310022, P. R. China.ORCID https://orcid.org/0000-0002-1665-5816
Yifei JiangSchool of Chemistry and Materials, University of Science and Technology of China, Hefei, Anhui, 230026, P. R. China.ORCID https://orcid.org/0000-0003-1818-4541
Xiaohong FangSchool of Chemistry and Materials, University of Science and Technology of China, Hefei, Anhui, 230026, P. R. China.ORCID https://orcid.org/0000-0002-2018-0542

Funding

Hangzhou Institute of Medicine, Chinese Academy of Sciences 2024ZZBS04KEY R&D Program of Zhejiang 2023C03058National Key Scientific Program of China 2022YFA1304500National Key Scientific Program of China 2022YFC3401003National Natural Science Foundation of China 22004123National Natural Science Foundation of China 22374134Natural Science Foundation of Shandong Province ZR2022YQ12"Pioneer" and "Leading Goose" R&D Program of Zhejiang 2023SDYXS0001The Public Welfare Fund from Natural Science Foundation of Zhejiang Province YXD23H0301Zhejiang Leading Innovation and Entrepreneurship Team 2022R01006
6 · The paper itself

Abstract

Since the first report that integrins on exosomes can potentially dictate their organ-tropic transport, there have been great interest in obtaining a better understanding of this phenomenon. However, integrins have many isoforms, which are heterogeneously distributed among individual exosomes with relatively low abundances. As a result, it is difficult to profile their expression landscape at single exosome level and study their relationship with organ specificity. To overcome this limitation, a spectrally and kinetically multiplexed single-molecule imaging method is developed, which for the first time achieved simultaneously imaging of 12 exosomal proteins at an unparalleled single-copy resolution, allowing systematic profiling of integrins on individual exosomes. Using this method, integrin expression profile of various types of cellular exosomes are characterized. Using machine learning algorithms, clustering analysis is performed to identify key subpopulations of each type of exosomes. It is found that co-occurrence integrin α6 and the pairing β counterpart on single exosomes is essential for effective lung targeting. In contrast, exosomes with primary αv dimer or unpaired integrins show almost no lung targeting behavior. Overall, the method allows profiling of integrins on single exosomes with unprecedented resolution. The information gained can facilitate the development of exosome-based biopsies and therapies.

Indexed as

ExosomesIntegrinsLungSingle Molecule ImagingAnimalsHumansKineticsMiceProtein IsoformsIntegrinsProtein IsoformsDNA‐PAINTexosomeintegrinmultiplexed detectionsingle‐molecule imaging

Identifiers

PMID41474357
PMCPMC13042962

What OpenQuestion holds

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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.