Evidence map›Paper›PMID 33293827›Full record

ArticleOncoTargets and therapy2020

Identification of a Functional ceRNA Network to Explore Potential Biomarkers for Hepatocellular Carcinoma.

Zhijun Jiang, Yu Zhang, Xinyu Liu, Jingchen Liang, Guanhua Qiu, Xiaoqi Zhu, Jie Chen, Lequn Li

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

8 authors at 1 institution in 1 country.

Zhijun Jiang *Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Yu Zhang *Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Xinyu LiuDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Jingchen LiangDepartment of Ultrasound, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Guanhua QiuDepartment of Ultrasound, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Xiaoqi ZhuDepartment of Ultrasound, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Jie ChenDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.
Lequn LiDepartment of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China.ORCID 0000-0002-6655-7472
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo establish a novel circRNA-miRNA-mRNA network associated with the poor prognosis of hepatocellular carcinoma (HCC). MATERIALS AND

methodsQuantitative real-time PCR was used to verify the differentially expressed circRNA. Moreover, the competing endogenous RNA networks were established using bioinformatics methods. Meanwhile, the prognostic value and potential mechanism of ceRNA network in hepatocellular carcinoma (HCC) were analyzed.

resultsThis work found that

conclusionThe ceRNA network proposed here can be used as a novel biomarker for the prognosis of HCC, thereby providing new insights for the targeted therapy of HCC.

Indexed as

biomarkerceRNAscircRNAshepatocellular carcinoma

Identifiers

PMID33293827
PMCPMC7719347
OpenAlexW3108397795

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.