Evidence map›Paper›PMID 34329340›Full record

ArticlePloS one2021

Identification of serum prognostic marker miRNAs and construction of microRNA-mRNA networks of esophageal cancer.

Yue Jiang, Chengda Zhang, Wenbin Shen, Yiming Li, Yun Wang, Jianjun Han, Tao Liu, Li Jia, Fei Gao, Xiaojun Liu and 4 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 1 country.

Yue JiangDepartment of Clinical Medicine, Southwest Medical University, Luzhou, China.
Chengda ZhangDepartment of Gastroenterology, The Third Hospital of Mian Yang (Sichuan Mental Health Center), Mianyang, China.
Wenbin ShenDepartment of Oncology, The Third Hospital of Mianyang (Sichuan Mental Health Center), Mianyang, China.
Yiming LiDepartment of Gastroenterology, The Third Hospital of Mian Yang (Sichuan Mental Health Center), Mianyang, China.
Yun WangDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Jianjun HanDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Tao LiuDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Li JiaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Fei GaoDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Xiaojun LiuDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Mi ChenDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Guangming YiDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Hongchun DaiDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Jun HeDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.ORCID 0000-0003-1602-7761
First Affiliated Hospital of Chengdu Medical College · CNMianyang Third People's Hospital · CNSouthwest Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal cancer is a common tumor of the digestive system with poor prognosis. This study was to gain a better understanding of the mechanisms involved in esophageal cancer and to identify new prognostic markers. We downloaded the esophageal cancer miRNA expression profile microarray data (GSE113740, GSE112264, GSE122497, GSE113486, and GSE106817) from the GEO database, extracted the esophageal cancer miRNA sequencing data from The Cancer Genome Atlas (TCGA) database, and then used a bioinformatics approach to select common differentially expressed miRNAs (DEMs). Differentially expressed genes (DEGs) were selected by predicting DEM target genes using the miRWalk database and intersecting with differential genes obtained from TCGA database for esophageal cancer. The STRING database was used to obtain protein-protein interaction (PPI) relationships to construct the DEM-DEG network. Furthermore, we selected core genes and core miRNAs associated with esophageal cancer prognosis by performing survival and univariate/multivariate COX analysis on DEMs and DEGs in the network and performed GSEA analysis on core genes alone, and finally the expression of the markers was verified by qPCR in esophageal cancer cell lines Eca109, SKGT-4 and normal esophageal epithelial cells HEEC. Nine DEMs were obtained, of which three were upregulated and six were downregulated, and 326 DEGs were obtained, of which 105 were upregulated and 221 were downregulated. Survival univariate/multivariate COX analysis revealed that five genes, ZBTB16, AQP4, ADCYAP1R1, PDGFD, and VIPR2, and two microRNAs, miR-99a-5p, and miR-508-5p, were related to esophageal cancer prognosis. GSEA analysis showed that the following genes may be involved in esophageal cancer prognosis: ZBTB16 may through the MTOR signaling pathway, AQP4 through the GNRH signaling pathway, ADCYAP1R1 through the PPAR signaling pathway, VIPR2 through the P53 signaling pathway and PDGFD through the PENTOSE-PHOSPHATE signaling pathway.

Indexed as

Circulating MicroRNADatabases, Nucleic AcidEsophageal NeoplasmsGene Regulatory NetworksRNA, MessengerRNA, NeoplasmCell Line, TumorFemaleHumansMaleNeoplasm ProteinsPrognosisSignal TransductionCirculating MicroRNANeoplasm ProteinsRNA, MessengerRNA, Neoplasm

Identifiers

PMID34329340
PMCPMC8323927
OpenAlexW3185760723

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.