A novel plasma circular RNA circFARSA is a potential biomarker for non‐small cell lung cancer. (2nd May 2018)

• Record Type: Journal Article
• Authors: Hang, Dong; Zhou, Jing; Qin, Na; Zhou, Wen; Ma, Hongxia; Jin, Guangfu; Hu, Zhibin; Dai, Juncheng; Shen, Hongbing
• Is Part Of: Cancer medicine. Volume 7:Number 6(2018:Jun.)
• Page Start: 2783
• Page End: 2791
• Publication Date: 2018-05-02
• Subjects: Circular RNA -- lung cancer -- plasma -- RNA sequencing; 616.994005
• DOI: 10.1002/cam4.1514
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Emerging evidence indicates that circular RNAs (circRNAs) are implicated in cancer development. This study aimed to evaluate whether circulating circRNAs may serve as novel biomarkers for non‐small cell lung cancer (NSCLC). We used RNA sequencing (RNA‐seq) and quantitative real‐time PCR to explore cancer‐related circRNAs. Bioinformatics and functional analyses were performed to reveal biological effects of circRNAs on lung cancer cells. A total of 5471 distinct circRNAs were identified by total RNA‐seq, in which 185 were differentially expressed between cancerous and adjacent normal tissues. A circRNA derived from exon 5–7 of the FARSA gene, termed circFARSA, was observed to increase in cancerous tissues ( P = 0.016), and was more abundant in patients' plasma than controls ( P < 0.001). Overexpression of circFARSA in A549 cell line significantly promoted cell migration and invasion. In silico analysis suggested that circFARSA might sponge miR‐330‐5p and miR‐326, thereby relieving their inhibitory effects on oncogene fatty acid synthase. Summarily, this study revealed circRNA profile of NSCLC for the first time and provided the evidence of plasma circFARSA as a potential noninvasive biomarker for this malignancy. Abstract : Differences in circRNA expression profiles between NSCLC and adjacent normal tissues. (A) Volcano plots showing differential expression of circRNAs between the two groups. The red points represent the differentially expressed circRNAs with fold change ≥2.0 (log2 scaled) and P < 0.05(−log10 scaled). (B) The distribution of differentially expressed circRNAs in human chromosomes. (C) Hierarchical clustering analysis of the top 10 upregulated and downregulated circRNAs.