Evidence map›Paper›PMID 40355722›Full record

ReviewDiscover oncology2025

Role of M2 macrophage-derived exosomes in cancer drug resistance via noncoding RNAs.

Xiaopeng Hu, Yanhua Li, Xisheng Wang, Xingkui Xue

Abstract readReview
In one paragraph

Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
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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.

Xiaopeng Hu *Medical Research Center, People's Hospital of Longhua, Shenzhen, 518000, China.
Yanhua Li *Department of Pathology, Shenzhen Longhua Maternity and Child Healthcare Hospital, Shenzhen, 518000, China.
Xisheng WangMedical Research Center, People's Hospital of Longhua, Shenzhen, 518000, China.
Xingkui XueMedical Research Center, People's Hospital of Longhua, Shenzhen, 518000, China. xuexk@outlook.com.

Funding

Shenzhen Longhua District Medical Association Medical Scientific Research Special Project 2023LHMA16Shenzhen Longhua District Science and Technology Innovation Fund Project 11501A20211203BBFE2DAShenzhen (Public platform of Technique service of molecular Immunology and Molecular Diagnostics); Guangdong Medical Science and Technology Research Foundation A2024386The Scientific Research Projects of Medical and Health Institutions of Longhua District, Shenzhen 2023004, 2024002
6 · The paper itself

Abstract

This review summarizes recent findings on the role of M2 tumor-associated macrophages (TAMs) and their exosome-derived non-coding RNAs (ncRNAs) in cancer cell resistance to therapeutics. M2 TAMs promote angiogenesis, suppress immune responses, and facilitate metastasis, thereby creating a tumor-supporting microenvironment. A range of antitumor drugs, including 5-FU, cisplatin, and gemcitabine, are mediated by M2 exosomes, each with distinct mechanisms of action. M2 exosomes transfer drug resistance capabilities via extracellular vesicles, especially exosomes containing miRNAs, lncRNAs, and circRNAs. These exosome mediate the development of tumor drug resistance by regulating signaling pathways such as PI3K/AKT, MAPK/ERK, Wnt/β-catenin M2 exosomes can regulate cellular responses by delivering bioactive molecules, including proteins, lipids, and ncRNA, which can also modulate cellular reactions to ionizing radiation, ultraviolet light, and chemotherapeutic agents. Targeting M2 TAMs and their exosome-mediated ncRNAs may offer new strategies to overcome drug resistance in cancer.

Indexed as

Cancer TherapeuticsDrug resistanceExosomesM2 MacrophagesncRNAs

Identifiers

PMID40355722
PMCPMC12069209

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.