Evidence map›Paper›PMID 33981850›Full record

ArticleOpen medicine (Warsaw, Poland)2021

Four long noncoding RNAs act as biomarkers in lung adenocarcinoma.

Zhihui Zhang, Liu Yang, Yujiang Li, Yunfei Wu, Xiang Li, Xu Wu

Abstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhihui ZhangDepartment of Thoracic and Cardiovascular Surgery/Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Jingxi Street, Guangzhou, Guangdong 510515, China.
Liu YangDepartment of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Yujiang LiDepartment of Thoracic and Cardiovascular Surgery/Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Jingxi Street, Guangzhou, Guangdong 510515, China.
Yunfei WuDepartment of Thoracic and Cardiovascular Surgery/Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Jingxi Street, Guangzhou, Guangdong 510515, China.
Xiang LiDepartment of Emergency Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Xu WuDepartment of Thoracic and Cardiovascular Surgery/Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Jingxi Street, Guangzhou, Guangdong 510515, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLung adenocarcinoma (LUAD) is currently one of the most common malignant tumors worldwide. However, there is a lack of long noncoding RNA (lncRNA)-based effective markers for predicting the prognosis of LUAD patients. We identified four lncRNAs that can effectively predict the prognosis of LUAD patients.

methodsWe used data gene expression profile for 446 patients from The Cancer Genome Atlas database. The patients were randomly divided into a training set and a test set. Significant lncRNAs were identified by univariate regression. Then, multivariate regression was used to identify lncRNAs significantly associated with the survival rate. We constructed four-lncRNA risk formulas for LUAD patients and divided patients into high-risk and low-risk groups. Identified lncRNAs subsequently verified in the test set, and the clinical independence of the lncRNA model was evaluated by stratified analysis. Then mutated genes were identified in the high-risk and low-risk groups. Enrichment analysis was used to determine the relationships between lncRNAs and co-expressed genes. Finally, the accuracy of the model was verified using external database.

resultsA four-lncRNA signature (AC018629.1, AC122134.1, AC119424.1, and AL138789.1) has been verified in the training and test sets to be significantly associated with the overall survival of LUAD patients.

conclusionsThe present study demonstrated that identified four-lncRNA signature can be used as an independent prognostic biomarker for the prediction of survival of LUAD patients.

Indexed as

bioinformaticsbiomarkerlncRNAlung adenocarcinomaprognosis

Identifiers

PMID33981850
PMCPMC8082473

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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.