Evidence map›Paper›PMID 36588730›Full record

ReviewFrontiers in pharmacology2022

Small extracellular vesicles in metabolic remodeling of tumor cells: Cargos and translational application.

Hao Yang, Jingyi Wang, Gang Huang

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

3 authors.

Hao YangShanghai Key Laboratory of Molecular Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.
Jingyi WangDepartment of Nuclear Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Gang HuangShanghai Key Laboratory of Molecular Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Warburg effect is characterized by excessive consumption of glucose by the tumor cells under both aerobic and hypoxic conditions. This metabolic reprogramming allows the tumor cells to adapt to the unique microenvironment and proliferate rapidly, and also promotes tumor metastasis and therapy resistance. Metabolic reprogramming of tumor cells is driven by the aberrant expression and activity of metabolic enzymes, which results in the accumulation of oncometabolites, and the hyperactivation of intracellular growth signals. Recent studies suggest that tumor-associated metabolic remodeling also depends on intercellular communication within the tumor microenvironment (TME). Small extracellular vesicles (sEVs), also known as exosomes, are smaller than 200 nm in diameter and are formed by the fusion of multivesicular bodies with the plasma membrane. The sEVs are instrumental in transporting cargoes such as proteins, nucleic acids or metabolites between the tumor, stromal and immune cells of the TME, and are thus involved in reprogramming the glucose metabolism of recipient cells. In this review, we have summarized the biogenesis and functions of sEVs and metabolic cargos, and the mechanisms through they drive the Warburg effect. Furthermore, the potential applications of targeting sEV-mediated metabolic pathways in tumor liquid biopsy, imaging diagnosis and drug development have also been discussed.

Indexed as

drug developmentexosomesglycolysisliquid biopsysmall extracellular vesiclestumor metabolismwarburg effect

Identifiers

PMID36588730
PMCPMC9800502

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.