Evidence mapPaperPMID 42325396Full record

ReviewInternational journal of nanomedicine2026

Exosomes in Ovarian Cancer: Promoters, Biomarkers, and Therapeutic Targets.

Fengyi Wang, Haiyan Dong, Yuli Song, Yi Zhang

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 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

4 authors.

Fengyi WangDepartment of Gynecology, The First Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China.
Haiyan DongDepartment of Gynecology, Guangxi Medical University Affiliated Tumor Hospital, Nanning, Guangxi, People's Republic of China.
Yuli SongDepartment of Gynecology, The First Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China.
Yi ZhangDepartment of Gynecology, The First Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China.ORCID 0000-0003-1150-6042

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is an aggressive malignancy treated primarily with surgery and platinum-based chemotherapy. The high recurrence rate and platinum resistance are the primary reasons for poor prognosis in ovarian cancer. Early screening can improve patient survival, but there are currently no high-precision biomarkers available. Exosomes are nanoscale vesicles that mediate intercellular communication by transferring bioactive molecules, and their composition reflects pathological states. Late diagnosis is the primary cause of poor prognosis in patients with ovarian cancer. Owing to the high stability conferred by their unique structure, exosomes can serve as an efficient, non-invasive approach for early screening. In the context of drug delivery, engineered exosomes using novel advanced technologies can enhance the specificity of clinical pharmacotherapy and reduce adverse toxic reactions. This review summarizes the latest research findings on ovarian cancer-related exosomes and introduces their important roles in exploring the mechanisms of ovarian cancer progression, metastasis, and chemoresistance, as well as their potential as prognostic biomarkers and therapeutic targets.

Indexed as

Biomarkers, TumorExosomesOvarian NeoplasmsAnimalsDrug Resistance, NeoplasmFemaleHumansBiomarkers, Tumorbiomarkercancer metastasischemoresistanceengineered exosomesexosomesextracellular vesiclesovarian cancer

Identifiers

PMID42325396
PMCPMC13282986

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.