Hsa_circ_0066351 acts as a prognostic and immunotherapeutic biomarker in colorectal cancer. Hsa_circ_0066351 acts as a prognostic and immunotherapeutic biomarker in colorectal cancer

Circular RNA (circRNA), a novel class of non-coding RNA, has been reported in various diseases, especially in tumors. However, the key signatures of circRNA-competitive endogenous RNA (ceRNA) network are largely unclear in colorectal cancer (CRC). We first characterized circRNAs profile by using circRNA-seq analysis from real-word dataset. The expression level of hsa_circ_0066351 in CRC tissues and cell lines was detected by quantitative real-time PCR. Then, cell proliferation assay was used to confirm the proliferation function of hsa_circ_0066351. Next, Cytoscape was used to construct circRNA–miRNA–mRNA networks. Last but not least, the landscape of hsa_circ_0066351–miRNA–mRNA in CRC had been investigated in the bulk tissue RNA-Seq level and single-cell Seq level. We proved that hsa_circ_0066351 was significantly downregulated in CRC cell lines and tissues (P < 0.001), and was negatively associated with distant metastasis (P < 0.01). Significantly, the expression of hsa_circ_0066351 was associated with better survival in patients with CRC. Function assays showed that hsa_circ_0066351 could inhibit CRC cells proliferation. In addition, a ceRNA network, including hsa_circ_0066351, two miRNAs, and ten mRNAs, was constructed. Our analyses showed that these ten mRNAs were consistently downregulated in pan-cancer and enriched in tumor suppressive function. A risk score model constructed by these ten downstream genes also indicated that they were related to the prognosis and immune response in CRC. In conclusion, we demonstrated that a novel circRNA (hsa_circ_0066351) inhibited CRC prol Overall design: Total RNA from each sample was quantified using the NanoDrop ND-1000. The sample preparation and microarray hybridization were performed based on the Arraystar’s standard protocols. Briefly, total RNAs were digested with Rnase R (Epicentre, Inc.) to remove linear RNAs and enrich circular RNAs. Then, the enriched circular RNAs were amplified and transcribed into fluorescent cRNA utilizing a random priming method (Arraystar Super RNA Labeling Kit; Arraystar). The labeled cRNAs were hybridized onto the Arraystar Human circRNA Array V2 (8x15K, Arraystar). After having washed the slides, the arrays were scanned by the Agilent Scanner G2505C. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed using the R software limma package. Differentially expressed circRNAs with statistical significance between two groups were identified through Volcano Plot filtering. Differentially expressed circRNAs between two samples were identified through Fold Change filtering. Hierarchical Clustering was performed to show the distinguishable circRNAs expression pattern among samples.