4.7 Article

RNA sequencing reveals the expression profiles of circRNA and identifies a four-circRNA signature acts as a prognostic marker in esophageal squamous cell carcinoma

期刊

CANCER CELL INTERNATIONAL
卷 21, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12935-021-01852-9

关键词

Esophageal squamous cell carcinoma; Prognostic biomarker; circRNA; Signature; Survival

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资金

  1. National Natural Science Foundation of China [U1904148, 81272371]
  2. Henan Programs for Science and Technology Development [212102310134]
  3. National Science and Technology Major Project of China [2018ZX10302205]
  4. Zhengzhou Major Project for Collaborative Innovation (Zhengzhou University) [18XTZX12007]

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A four-circRNA signature associated with ESCC prognosis was identified through RNA sequencing and bioinformatics analysis, which showed better predictive performance than TNM stage. These findings suggest that the circRNA signature could serve as a valuable prognostic biomarker for ESCC.
BackgroundCircRNAs with tissue-specific expression and stable structure may be good tumor prognostic markers. However, the expression of circRNAs in esophageal squamous cell carcinoma (ESCC) remain unknown. We aim to identify prognostic circRNAs and construct a circRNA-related signature in ESCC.MethodsRNA sequencing was used to test the circRNA expression profiles of 73 paired ESCC tumor and normal tissues after RNase R enrichment. Bioinformatics methods, such as principal component analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm, unsupervised clustering and hierarchical clustering were performed to analyze the circRNA expression characteristics. Univariate cox regression analysis, random survival forests-variable hunting (RSFVH), Kaplan-Meier analysis, multivariable Cox regression and ROC (receiver operating characteristic) curve analysis were used to screen the prognostic circRNA signature. Real-time quantitative PCR (qPCR) and fluorescence in situ hybridization(FISH) in 125 ESCC tissues were performed.ResultsCompared with normal tissues, there were 11651 differentially expressed circRNAs in cancer tissues. A total of 1202 circRNAs associated with ESCC prognosis (P<0.05) were identified. Through bioinformatics analysis, we screened a circRNA signature including four circRNAs (hsa_circ_0000005, hsa_circ_0007541, hsa_circ_0008199, hsa_circ_0077536) which can classify the ESCC patients into two groups with significantly different survival (log rank P<0.001), and found its predictive performance was better than that of the TNM stage(0.84 vs. 0.66; 0.65 vs. 0.62). Through qPCR and FISH experiment, we validated the existence of the screened circRNAs and the predictive power of the circRNA signature.ConclusionThe prognostic four-circRNA signature could be a new prognostic biomarker for ESCC, which has high clinical application value.

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