Evidence map›Paper›PMID 39957900›Full record

ReviewJournal of pharmaceutical analysis2025

Exosomal circRNAs: Deciphering the novel drug resistance roles in cancer therapy.

Xi Li, Hanzhe Liu, Peiyu Xing, Tian Li, Yi Fang, Shuang Chen, Siyuan Dong

Abstract readReview
In one paragraph

Review in Journal of pharmaceutical analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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  5. 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

7 authors.

Xi LiDepartment of Vascular and Thyroid Surgery, The First Hospital of China Medical University, Shenyang, 110001, China.
Hanzhe LiuDepartment of Critical Care Medicine, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, 110042, China.
Peiyu XingDepartment of Ophthalmology, China Medical University the Fourth People's Hospital of Shenyang, Shenyang, 110031, China.
Tian LiSchool of Basic Medicine, The Fourth Military Medical University, Xi'an, 710032, China.
Yi FangDepartment of Ultrasound, The First Hospital of China Medical University, Shenyang, 110001, China.
Shuang ChenDepartment of Cardiology, The First Hospital of China Medical University, Shenyang, 110001, China.
Siyuan DongDepartment of Thoracic Surgery, The First Hospital of China Medical University, Shenyang, 110001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomal circular RNA (circRNAs) are pivotal in cancer biology, and tumor pathophysiology. These stable, non-coding RNAs encapsulated in exosomes participated in cancer progression, tumor growth, metastasis, drug sensitivity and the tumor microenvironment (TME). Their presence in bodily fluids positions them as potential non-invasive biomarkers, revealing the molecular dynamics of cancers. Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication. Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities. Therefore, ongoing exploration of exosomal circRNAs in cancer research is poised to revolutionize clinical management of cancer. This emerging field offers hope for significant breakthroughs in cancer care. This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance, highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

Indexed as

Cancer biomarkersExosomal circRNAsTumor microenvironment

Identifiers

PMID39957900
PMCPMC11830318

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.