Evidence map›Paper›PMID 37115456›Full record

ArticleHepatology international2023

Synthetic miR-26a mimics delivered by tumor exosomes repress hepatocellular carcinoma through downregulating lymphoid enhancer factor 1.

Jie Hu, Wei-Feng Liu, Xiang-Yu Zhang, Guo-Ming Shi, Xin-Rong Yang, Kai-Qian Zhou, Bo Hu, Fei-Yu Chen, Cheng Zhou, Wan-Yee Lau and 3 more

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in Hepatology international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Designing nucleic acid-based therapeutics for cancer treatment: Updates on the state of the art.Molecular therapy : the journal of the American Society of Gene Therapy · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Exosome miRNA sorting controlled by RNA-binding protein-motif interactions.Extracellular vesicles and circulating nucleic acids · 2025
    Review
  9. Review
  10. Review
  11. Review
  12. miRNAs in HCC, pathogenesis, and targets.Hepatology (Baltimore, Md.) · 2024
    Article
  13. Article
  14. Review
  15. Review
  16. 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

13 authors at 3 institutions in 3 countries.

Jie Hu *Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Wei-Feng Liu *Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xiang-Yu Zhang *Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Guo-Ming ShiKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xin-Rong YangKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Kai-Qian ZhouKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Bo HuKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Fei-Yu ChenKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Cheng ZhouKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Wan-Yee LauFaculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, Hong Kong, China.
Jia FanKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Zheng WangKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. wang.zheng@zs-hospital.sh.cn.
Jian ZhouKey Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. zhou.jian@zs-hospital.sh.cn.ORCID http://orcid.org/0000-0002-2118-1117
Fudan University · CNChinese University of Hong Kong · HKSun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81772578National Natural Science Foundation of China 81830102National Natural Science Foundation of China 82002482National Natural Science Foundation of China o.81401929Natural Science Foundation of Zhejiang Province No. LQ21H160034Science and Technology Innovation Plan Of Shanghai Science and Technology Commission 21Y11912300Science and Technology Innovation Plan Of Shanghai Science and Technology Commission NO. 22S11901100Shanghai Rising-Star Program No.16QA1401000Zhongshan Clinical Research Foundation No. 2020ZSLC48
6 · The paper itself

Abstract

backgroundThe dysregulation of exosomal microRNAs plays an important role in the progression of hepatocarcinogenesis. In this study, we investigated the therapeutic potential of synthetic exosomal miR-26a against HCC cells and explored the feasibility of tumor-derived exosomes as drug delivery vehicles.

methodsProliferation and migration assays were performed to examine the effects of miR-26a on HCC in vitro. The direct target gene of miR-26a was identified through miRecords analysis and target validation. The transferring efficiency and anti-HCC effect of exosomes with different origin were studied and the optimal miR-26a delivery method was established and verified in vitro and in vivo. In addition, the relationships between prognosis of HCC patients and miR-26a expression in HCC serum and exosomes were retrospectively analyzed.

resultsHere, we found that tumor cell-derived exosomes were taken in preferentially by HCC cells and promoted HCC progression through Wnt pathway by low-density lipoprotein receptor-related protein 6 (LRP6). HCC cells with vacuolar protein sorting-associated protein 35 knocked down were adopted to generate engineered LRP6

conclusionsOur findings suggested the exosomal miR-26a could serve as a non-invasive prognostic marker for HCC patients. Genetically modified tumor-derived exosomes showed preferable transfection efficiency but reduced Wnt activity, which provides a novel therapeutic strategy for HCC.

Indexed as

Carcinoma, HepatocellularExosomesLiver NeoplasmsMicroRNAsCell Line, TumorCell ProliferationGene Expression Regulation, NeoplasticHumansRetrospective StudiesMicroRNAsExosomeHepatocellular carcinomaLymphoid enhancer factor 1miR-26a

Identifiers

PMID37115456
OpenAlexW4367299825

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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.