Evidence map›Paper›PMID 42589707›Full record

ReviewInternational journal of molecular sciences2026

Cancer-Derived Exosomes: A Cross-Cancer Comparative Analysis of Exosomal Proteins and MicroRNAs.

Jong Hyun Kim

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 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

1 author.

Jong Hyun KimDepartment of Biochemistry, School of Medicine, Daegu Catholic University, Daegu 42472, Republic of Korea.ORCID 0000-0002-0031-5737

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomes are small extracellular vesicles that mediate intercellular communication and, in cancer, carry cargo that both reflects the donor tumor cell and influences recipient cells within local and distant microenvironments. Exosomal proteins and microRNAs have been reported individually across many cancer types, but rarely compared on a common basis; in this review, previously reported molecules from eight cancer categories-blood, breast, colon, kidney, liver, lung, prostate, and stomach-were compiled from curated repositories and re-analyzed within a single functional framework. In total, 3643 exosomal proteins (523 hematologic, 3120 solid-tumor) and 627,225 miRNA-target pairs, derived from 350 unique microRNAs, were organized using Gene Ontology, KEGG, and PANTHER annotation. Across cancers, proteins converged on a reproducible core-signaling, transport, cytoskeletal organization, and extracellular interaction-dominated by binding, catalytic, and transporter functions localized to membrane, vesicle, and extracellular compartments. Comparisons between hematologic and solid malignancies revealed both shared cancer-associated functions and context-dependent patterns linked to tissue origin and disease ecology. Together, these findings indicate that integrated protein-and-microRNA profiling offers a useful framework for understanding tumor communication, refining cancer classification, and advancing biomarker discovery, while underscoring that harmonized workflows, independent validation, and mechanistic follow-up remain necessary before descriptive enrichment outputs can support clinically robust applications.

Indexed as

ExosomesMicroRNAsNeoplasm ProteinsNeoplasmsAnimalsBiomarkers, TumorGene Expression Regulation, NeoplasticHumansTumor MicroenvironmentBiomarkers, TumorMicroRNAsNeoplasm Proteinscancer biomarkersexosomesliquid biopsymicroRNAprecision oncologyproteomicstumor microenvironment

Identifiers

PMID42589707
PMCPMC13467121

What OpenQuestion holds

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Registered trials

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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.