Evidence map›Paper›PMID 34967552›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2021

lncRNA Expression-Based Risk Scoring System Can Predict Survival of Tumor-Positive Patients with Hepatocellular Carcinoma.

Siyao Wu, Yayan Deng, Yue Luo, Jiaxiang Ye, Zhihui Liu

Open access · goldAbstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 60% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Siyao WuDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning 530021, People's Republic of China.
Yayan DengDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning 530021, People's Republic of China.
Yue LuoDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning 530021, People's Republic of China.
Jiaxiang YeDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning 530021, People's Republic of China.
Zhihui LiuDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning 530021, People's Republic of China.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong non-coding RNAs (lncRNAs) play critical roles in the progression of hepatocellular carcinoma (HCC). The aim of this study was to explore whether lncRNA expression profiles can predict prognosis of HCC patients with tumors.

methodsExpression of lncRNAs in HCC patients based on data in The Cancer Genome Atlas (TCGA) was examined by uni- and multivariate cox analysis to identify associations between clinical features and overall survival (OS) or recurrence-free survival (RFS). Based on our finding that both were independently associated with tumor status, we examined lncRNAs differentially expressed between patients with or without tumors. An lncRNA-based risk scoring system was developed to predict OS and RFS in tumor-positive patients, and it was assessed using uni- and multivariate cox analyses. Potential functions of the prognostic lncRNAs were explored.

resultsA risk scoring system to predict OS for HCC patients with tumors was developed based on the expression of six lncRNAs (AC090921.1, AC012640.1, AL158839.1, AL356056.1, AL359853.1 and C10orf91), and a corresponding scoring system to predict RFS was developed from nine lncRNAs (AL356056.1, AL158839.1, MIR7-3HG, AL445493.2, AP000808.1, AP003354.2, PLCE1-AS1, TH2LCRR and LINC01447). Both risk scoring systems gave areas under receiver operating characteristic curves >0.7. Uni- and multivariate cox analyses showed that both risk scoring systems independently predicted survival even after adjusting for clinical factors. The lncRNAs related to OS may be involved in complement and coagulation cascades, while those related to RFS may be involved in the cell cycle.

conclusionRisk scoring system based on these lncRNAs may be useful for predicting prognosis of tumor-positive HCC patients.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularDisease ProgressionFemaleHumansLiver NeoplasmsMaleMiddle AgedPredictive Value of TestsPrognosisProportional Hazards ModelsRisk AssessmentRisk FactorsRNA, Long NoncodingROC CurveBiomarkers, TumorRNA, Long NoncodingHepatocellular carcinomalong non-coding RNArisk scoring systemsurvival

Identifiers

PMID34967552
PMCPMC9080350
OpenAlexW4200057229

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LicenceCC BY-NC
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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.