Strategy for Scanning Peptide-Coding Circular RNAs in Colorectal Cancer Based on Bioinformatics Analysis and Experimental Assays

基于生物信息学分析和实验检测的结直肠癌中肽编码环状RNA的扫描策略

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作者:Zhanghan Chen,Zhipeng Qi,Dongli He,Jingyi Liu,Enpan Xu,Bing Li,Shilun Cai,Di Sun,Yirong Cheng,Qiang Shi,Yunshi Zhong

Abstract

Background: Colorectal cancer (CRC) is the third most common cause of cancer deaths worldwide. Numerous studies have reported that circular RNAs (circRNAs) have important functions in CRC. It was first thought that circRNAs were non-coding RNA; however, more recently they were discovered to encode peptides and play a pivotal role in cancer development and progression. It was shown that most circRNAs possess coding potential; however, not all of them can truly encode peptides. Therefore, a practical strategy to scan for coding circRNAs is needed. Method: Sequence analyses included open reading frame (ORF) prediction, coding peptide prediction, and the identification of unique sequences. Then, experimental assays were used to verify the coded peptides, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was introduced to detect sequences of circRNAs with coding potential, and Western blot was used to identify the encoded peptides. Finally, the functions of the circRNAs were primarily explored. Result: An efficient strategy for searching circRNAs with coding potential was created. We verified this schedule using public databases and LC-MS/MS, then two of these circRNAs were selected for further verification. We used commercial antibodies that can also identify the predicted peptides to test the coded peptides. The functions of the circRNAs were explored primarily, and the results showed that they were mainly involved in the promotion of proliferation and invasion ability. Discussion: We have constructed an efficient strategy of scanning circRNAs with coding potential. Our strategy helped to provide a more convenient pathway for identifying circRNA-derived peptides, which can be a potential therapeutic target or a diagnostic biomarker.

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