Evidence map›Paper›PMID 37731947›Full record

ArticleMedComm2023

Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma.

Yaojie Wang, Xiaoya Li, Xiaojian Wei, Lei Li, Hanyu Bai, Xi Yan, Hongtao Zhang, Libo Zhao, Wei Zhou, Lianmei Zhao

Abstract read
In one paragraph

Article in MedComm, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

10 authors.

Yaojie WangResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Xiaoya LiResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Xiaojian WeiResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Lei LiResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Hanyu BaiResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Xi YanKey Laboratory of Tumor Gene Diagnosis, Prevention and Therapy of Hebei Province Shijiazhuang China.
Hongtao ZhangUniversity of Pennsylvania School of Medicine Philadelphia Philadelphia Pennsylvania USA.
Libo ZhaoResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.
Wei ZhouHangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Hangzhou China.
Lianmei ZhaoResearch Center The Fourth Hospital of Hebei Medical University Shijiazhuang China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are relatively stable in blood, emerging as one of the most promising biomarkers in tumor liquid biopsy. Both total and extracellular vesicles (EVs) encapsulated miRNA have been studied for prognostic potential in a variety of cancers. Here, we systematically compared and verified the total and vesicle-derived miRNA expression profiles from plasma samples in healthy controls and patients with esophageal squamous cell carcinoma (ESCC). In the present study, four miRNA species miR-636, miR-7641, miR-28-3p, and miR-1246 that were differentially expressed in ESCC patients were chosen for further study. We first elucidated their essential function in ESCC progression and further explored their preliminary mechanism by identifying target proteins and involving signal pathways. Subsequently, the prognostic miRNA panels including miR-636, miR-7641, miR-1246, and miR-28-3p for ESCC diagnosis were constructed and validated using different cohort. Our results showed that the panel including the above four miRNAs derived from plasma EVs was most effective in distinguishing tumor patients from normal subjects, while integrated plasma EVs-derived miR-1246, miR-28-3p and total plasma miRNAs miR-636, miR-7641 showed the best capability in predicting lymph node metastasis. In summary, our studies revealed that plasma EVs-derived miRNAs could be emerged as promising biomarkers for ESCC diagnosis.

Indexed as

esophageal squamous cell carcinomaextracellular vesicleliquid biopsylymph node metastasismiRNAs

Identifiers

PMID37731947
PMCPMC10507283

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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.