Open AccessA group of long noncoding RNAs identified by data mining can predict the prognosis of lung adenocarcinoma
Author(s) -
Liao Meijian,
Liu Qing,
Li Bing,
Liao Weijie,
Xie Weidong,
Zhang Yaou
Publication year - 2018
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/cas.13822
Subject(s) - adenocarcinoma , hazard ratio , long non coding rna , lung cancer , proportional hazards model , rna , oncology , medicine , biology , univariate analysis , biomarker , gene expression , non coding rna , survival analysis , carcinoma , confidence interval , gene , multivariate analysis , cancer , genetics
Long noncoding RNAs (lnc RNA ) are reported to be potential cancer biomarkers. This study aims to find new lnc RNA biomarker relevant to lung adenocarcinoma. Gene expression profile and clinical data of lung adenocarcinoma and lung squamous cell carcinoma patients were downloaded from the UCSC Xena database. These data were analyzed to identify potential lnc RNA prognostic biomarkers, and the candidate lnc RNA s were analyzed and verified with association analysis, meta‐analysis, survival analysis, gene ontology analysis, gene set enrichment analysis, and other statistical methods. A group of 5 lnc RNA s was identified from the 1965 differentially expressed (fold‐change >2) genes. Four of these 5 lnc RNA s were expressed at a lower level in lung adenocarcinoma tissues and the other one at a higher level ( P < .0001). A risk score model was constructed using a linear combination of the expression levels of these lnc RNA s. High‐risk patients showed poorer overall survival (hazard ratio [ HR ] = 2.14; 95% confidence interval [ CI ], 1.67‐3.06, P < .0001), disease‐free survival ( HR = 1.84; 95% CI , 1.26‐2.35, P = .0007), and recurrence‐free survival ( HR = 1.51; 95% CI , 1.02‐2.40, P = .04). The 5‐fold cross‐validation and subsequent meta‐analysis further verified that patients in the low‐risk group had better survival (95% CI , 0.74‐1.79, Z = 4.72, P < .00001). Furthermore, both univariate and multivariate Cox regression analyses revealed that the prognostic value of these 5 lnc RNA s was independent of other clinical prognostic factors. Further analysis indicated that these 5 lnc RNA s might be associated with tumor metastasis. Taken together, our study suggests new prognostic lnc RNA biomarkers for lung adenocarcinoma.