Evidence map›Paper›PMID 41751181›Full record

ReviewBiomedicines2026

Metabolic Messengers: Extracellular Vesicles as Central Mediators of Metabolic Reprogramming in Renal Cell Cancer.

Qingshu Meng, Liqun Huang, Zhiguo Chen, Rui Lin, Xiaohui Zhou, Guosheng Yang

Abstract readReview
In one paragraph

Review in Biomedicines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Qingshu MengResearch Center for Translational Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.
Liqun HuangDepartment of Urology, Shanghai Geriatric Medical Center, Zhongshan Hospital Fudan University Minhang Campus, Shanghai 201104, China.
Zhiguo ChenDepartment of Urology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.
Rui LinResearch Center for Translational Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.
Xiaohui ZhouResearch Center for Translational Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.ORCID 0000-0002-9354-3789
Guosheng YangDepartment of Urology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.

Funding

Shanghai Geriatrics Medical Center Institutional Project YM2025-005
6 · The paper itself

Abstract

Renal cell carcinoma (RCC) has been described as a metabolic disease as metabolic alterations are common in disparate RCC etiologies. Extracellular vesicles (EVs), the lipid bilayer-enclosed nanoparticles secreted by all living cells, have emerged as crucial mediators of intercellular and inter-organ communication, capable of shuttling functional proteins, lipids, and nucleic acids between cells. This review summarizes the essential events in tumor-associated metabolic reprogramming with a particular focus on renal cancers. We further explore how EVs released by metabolically deranged cells in cancer with altered cargos reprogram the renal cellular landscape, fostering tumor initiation, proliferation, angiogenesis, immune evasion, and therapy resistance. Understanding this EV-mediated axis not only elucidates the pathophysiological link between these conditions but also helps to unveil novel potential therapeutic targets for RCC patients.

Indexed as

cancerextracellular vesiclesintercellular communicationmetabolic reprogrammingmetabolismrenal cell carcinoma

Identifiers

PMID41751181
PMCPMC12937659

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.