Evidence map›Paper›PMID 32957376›Full record

ArticleMedicine2020

A panel of 8 miRNAs as a novel diagnostic biomarker in pancreatic cancer.

Benyuan Deng, Ming Wang, Zhongwu Liu

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 46% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Molecular Targets for the Diagnosis and Treatment of Pancreatic Cancer.International journal of molecular sciences · 2024
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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

3 authors at 2 institutions in 1 country.

Benyuan DengDepartment of General Surgery, West China Health care Hospital of Sichuan University.
Ming WangDepartment of General Surgery, The Third People's Hospital of Chengdu, Chengdu, China.
Zhongwu LiuDepartment of General Surgery, West China Health care Hospital of Sichuan University.
Sichuan University · CNChengdu Third People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer (PC) is one of the major causes of cancer mortality in developed countries. Therefore, there is an urgent need to derive biomarkers for early diagnosis of PC patients at high risk.This study was designed to identify a panel of miRNAs that might serve as biomarkers for the early diagnosis of PC.The data containing both PC and control samples were extracted from the Gene Expression Omnibus (GEO) database. EdgeR was applied to identify the differentially expressed miRNAs and genes between PC patients and healthy controls. Then a miRNA-mRNA network was constructed based on the differentially expressed miRNAs and genes. The miRNAs-based biomarker for PC was finally constructed by random forest. Finally, AUC was used to evaluate the performance of miRNAs to classify PC and control samples.A total of 33 differentially expressed miRNAs, 753 differentially expressed genes, and 8 miRNAs (hsa-mir-139, hsa-mir-31, hsa-mir-196b, hsa-mir-221, hsa-mir-203b, hsa-mir-215, hsa-mir-144, and hsa-mir-4433b) that play important roles in PC were identified. The target genes of these miRNAs were found to be mainly enriched in negative regulation of acute inflammatory response cell-substrate responses, and o-glycan processing pathways. The constructed biomarkers based on these 8 miRNAs could distinguish samples coming from PC and healthy controls.We identified a panel of eight-miRNAs that would serve as early diagnostic biomarkers for PC patients.

Indexed as

Early Detection of CancerBiomarkers, TumorGene Expression ProfilingHumansMicroRNAsPancreatic NeoplasmsPrognosisRNA, MessengerBiomarkers, TumorMicroRNAsRNA, Messenger

Identifiers

PMID32957376
PMCPMC7505395
OpenAlexW3087423517

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.