Evidence map›Paper›PMID 28729955›Full record

ArticlePeerJ2017

Identification of four prognostic LncRNAs for survival prediction of patients with hepatocellular carcinoma.

Zhonghao Wang, Qian Wu, Shu Feng, Yanhua Zhao, Chuanmin Tao

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

27 citing papers in PubMed, 55 citations in OpenAlex.

  1. mCancer cell international · 2025
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  18. Characterization of mRNA Expression and Endogenous RNA Profiles in Bladder Cancer Based on The Cancer Genome Atlas (TCGA) Database.Medical science monitor : international medical journal of experimental and clinical research · 2019
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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

5 authors at 1 institution in 1 country.

Zhonghao WangDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China.
Qian WuMicrobiology and Metabolic Engineering Key Laboratory of Sichuan Province, School of Life Sciences, Sichuan University, Chengdu, China.
Shu FengDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China.
Yanhua ZhaoDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China.
Chuanmin TaoDepartment of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the fifth most common cancer worldwide, Hepatocellular carcinoma (HCC) is also the third most common cause of cancer-related death in China. Several lncRNAs have been demonstrated to be associated with occurrence and prognosis of HCC. However, identification of prognostic lncRNA signature for HCC with expression profiling data has not been conducted yet.

methodsWith the reuse of public available TCGA data, expression profiles of lncRNA for 371 patients with HCC were obtained and analyzed to find the independent prognostic lncRNA. Based on the expression of lncRNA, we developed a risk score model, which was evaluated by survival analysis and ROC (receiver operating characteristic) curve. Enrichment analysis was performed to predict the possible role of the identified lncRNA in HCC prognosis.

resultsFour lncRNAs ( DISCUSSION: Our study recognized four lncRNAs to be significantly associated with prognosis of liver cancer, and could provide novel insights into the potential mechanisms of HCC progression. Additionally,

Indexed as

HCCLncRNAPrognosticSurvival

Identifiers

PMID28729955
PMCPMC5518732
OpenAlexW2738271904

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.