Circular RNAs as biomarkers in liquid biopsy in colorectal cancer.

Abstract

230 Background: Circular RNAs (circRNAs) are emerging as essential regulators of cancer- related biological hallmarks, as cell proliferation, apoptosis, differentiation, immune regulation and angiogenesis. CircRNAs are abundant, conserved, and have a tissue‐specific expression pattern. These characteristics make them candidate to serve as biomarkers in liquid biopsy (LB) in cancer. The aim of this study is to analyse differential expression of circRNAs in the colorectal cancer (CRC) scenario. Methods: To comprehensively understand the expression patterns of circRNAs we characterized 13,617 circRNAs using a microarray [Arraystar v2 (8x15K)] in 10 human samples, five CRC cell lines, one colorectal human tumour, one normal colon healthy control, vs. Peripheral Human Blood Leukocytes (2 pools) and Human Bone Marrow. Differentially expressed circRNAs were identified using fold change (FC) cut-off or through Volcano Plot filtering respectively. CircRNAs having FC ▪2 and P-values ▪ 0.05 were selected. CircRNA/microRNA interaction was predicted with target prediction software. Results: Hierarchical clustering showed distinguishable circRNA expression profiling among 10 samples. These data indicated that circRNAs have a different expression pattern in colorectal tissues compared with that in blood and bone marrow tissues. The microarray data showed 2329 circRNAs differentially expressed (FC > 2.0, P < 0.05). Among them, 964 circRNAs were upregulated and 1365 were downregulated in colon tissues compared with blood and bone marrow. Using a stringent criterion (FC > 10, P≤ 0.01 and false discovery rate [FDR] < 0.05) we have identified 30 circRNA upregulated in colorectal cancer versus non tumour samples. CircRNA/microRNA interaction prediction analysis showed that most upregulated circRNAs contain miRNA Binding Sites (MREs) for cancer-related miRNA, including among others, miR-17, miR-103, miR-let-7g. Conclusions: Microarray analysis was used to comprehensively identify dysregulated circRNAs in CRC. We identify novel circRNAs could be valuable as blood-based CRC biomarkers.