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Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

ABSTRACT: Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan-Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC?=?0.752, 95% confidence intervals (CI): 0.651-0.854) and the microarray dataset (AUC?=?0.714, 95%CI: 0.615-0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs.

SUBMITTER: Guo W

PROVIDER: S-EPMC4919625 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

Guo Wenna W Wang Qiang Q Zhan Yueping Y Chen Xijia X Yu Qi Q Zhang Jiawei J Wang Yi Y Xu Xin-Jian XJ Zhu Liucun L

Scientific reports 20160624

Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT10 ...[more]

PMID: 27338266

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Project description:Background Long noncoding RNAs (lncRNAs) are found to be novel biomarkers for hepatocellular carcinoma (HCC) and play an important role in tumor progression. We established a genomic instability-related long noncoding RNA signature (GIlncSig) as an independent prognosis factor and also investigated its impact on prognosis significance. Method Somatic mutation profiles, clinical characteristics, and RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database. Lasso regression was used to construct GIlncSig. KEGG was used to identify the possible biological pathways. ESTIMATE and CIBERSORT algorithms were used to calculate the immune microenvironment scores and proportion of immune cells in HCC patients. The expression of LINC00501 was conducted by qRT-PCR. Cell proliferation was measured by EdU, CCK-8, and colony formation assay, and cell migration and invasion ability were measured by wound healing and transwell assay. Results 135 genomic instability-related lncRNAs were identified, and GIlncSig was constructed using 13 independent lncRNAs with significant prognosis values. Based on the GIlncSig, high-risk group had worse clinical outcomes than low-risk group, while high-risk group also had higher UBQLN4, KRAS, ARID1A, and PIK3CA expression. Moreover, the efficiency of GIlncSig combining single-gene mutation was higher than single-gene mutation alone such as TP53. The results of CIBERSORT and ESTIMATE showed that GS group and GU group had significantly different immune infiltration. In addition, LINC00501 was identified as a potential biomarker in HCC with strong relationship with clinical characteristics. In vitro assays validated that LINC00501 promoted proliferation and migration of HCC cell lines. Conclusion Our results showed that GIlncSig serves as a potential independent prognosis factor to predict HCC patients' prognosis for exploring potential mechanism and therapy strategy. Besides, LINC00501 plays an important role in the progression of HCC, which may be a potential therapy target.

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Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

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Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

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