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Identification and verification of an immune-related lncRNA signature for predicting the prognosis of patients with bladder cancer.

Abstract：

BACKGROUND:Recent studies have revealed the significant roles of immune-related long noncoding RNAs (lncRNAs) in cancer development and progression. The identification of biomarkers that contribute to early detection and risk stratification provides significant benefits for bladder cancer (BC) patients. The current study aimed to determine an immune-related lncRNA signature for predicting the prognosis of BC patients. METHODS:Based on The Cancer Genome Atlas (TCGA) database, we identified seven immune-related lncRNAs with prognostic value. The predictive value of the prognostic signature developed from immune-related lncRNAs was assessed by survival and nomogram analyses. Principal component analysis (PCA) was performed to visualize gene expression patterns in the groups defined by the risk score, and the immune composition and purity of the tumor were evaluated by the ESTIMATE algorithm. RESULTS:Based on the Pearson correlation analysis results, 765 immune-related lncRNAs were filtered (|R| > 0.4, P < 0.001), and seven immune-related lncRNAs (Z84484.1, AC009120.2, AL450384.2, AC024060.1, TNFRSF14-AS1, AL354919.2, OCIAD1-AS1) with prognostic value were finally identified. Patients in the low-risk group had a better prognosis than those in the high-risk group. Multivariate Cox regression analysis showed that the signature was an independent prognostic factor. A prognostic nomogram with clinical features and the signature of seven immune-related lncRNAs was also constructed. According to the PCA and ESTIMATE algorithm results, we found different immune statuses in the low-and high-risk groups. CONCLUSIONS:Our study shows that the signature of seven immune-related lncRNAs can be used as a prognostic marker for BC.

journal_name

Int Immunopharmacol

journal_title

International immunopharmacology

authors

Wang J,Shen C,Dong D,Zhong X,Wang Y,Yang X

doi

10.1016/j.intimp.2020.107146

subject

Has Abstract

pub_date

2021-01-01 00:00:00

pages

107146

eissn

1567-5769

issn

1878-1705

pii

S1567-5769(20)33613-4

journal_volume

90

pub_type

杂志文章

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