Evidence map›Paper›PMID 35894132›Full record

ArticleMolecular medicine reports2022

Characterization of plasma exosomal microRNAs in responding to radiotherapy of human esophageal squamous cell carcinoma.

Nan Miao, Wenjie Cai, Sijia Ding, Yajuan Liu, Wanhua Chen, Tao Sun

Abstract read
In one paragraph

Article in Molecular medicine reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Exosomes in esophageal cancer: function and therapeutic prospects.Medical oncology (Northwood, London, England) · 2024
    Review
  4. Review
  5. Article
  6. 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.

Nan MiaoCenter for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, Fujian 361021, P.R. China.
Wenjie CaiDepartment of Radiation Oncology, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
Sijia DingCenter for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, Fujian 361021, P.R. China.
Yajuan LiuCenter for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, Fujian 361021, P.R. China.
Wanhua ChenDepartment of Clinical Laboratory, First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
Tao SunCenter for Precision Medicine, School of Medicine and School of Biomedical Sciences, Huaqiao University, Xiamen, Fujian 361021, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiotherapy is one of the main treatment methods for esophageal squamous cell carcinoma (ESCC). Previous research has shown that plasma exosomal microRNAs (miRNAs) can predict therapeutic outcome. In the present study, to identify potential exosomal miRNAs that respond to radiotherapy, plasma exosomal miRNAs from ESCC patients undergoing radiotherapy were isolated and sequenced. Upregulated and downregulated miRNAs were detected from patients pre‑ and post‑radiotherapy, and it was found that they play distinct roles in DNA damage process and endosomal mediated transport. Based on wound healing and Cell Counting Kit‑8 assays in TE‑1 human esophageal cancer cells, it was identified that representative miRNA

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaMicroRNAsGene Expression Regulation, NeoplasticHumansMicroRNAsMIRN30a microRNA, humanMIRN652 microRNA, humanesophageal squamous cell carcinomaexosomemiRNAsradiotherapy

Identifiers

PMID35894132
PMCPMC9366155

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.