Clinical samples
A total of 81 patients diagnosed with CRC at Shengjing Hospital of the China Medical University and 50 healthy volunteers were enrolled in present study. All the blood samples used in this research were collected with complete informed consent from the participants and ethics approval was obtained from the ethics review committee of the Shengjing Hospital of China Medical University before this study. Serum samples were extracted from blood samples after being centrifuged at 3000 rpm, 4 °C for 10 min and were stored at −80 °C until RNA isolation.
RNA isolation and RT-qPCR
Blood samples in containers without coagulant were preserved at 4°C for 4 h to ensure serum separation. Then, serum was stored at −80°C until for use after centrifuged for 10 min at 5,000 rpm and 3,000 rpm, respectively. Total RNA was isolated from serum with TRIzol reagent (Invitrogen, Carlsbad, CA, United States) according to the manufacturer’s protocol. The concentration and quality of total RNA in all samples were detected using NanoDrop ND-1000 spectrophotometer (NanoDrop, Wilmington, DE, United States). The synthesis of cDNA and RT-qPCR reactions were conducted using a reverse transcription kit and the SYBR Green kit (Takara Bio, Dalian, China). Relative gene expression was determined using the ABI 7500 System (Applied Biosystems, USA) with the following qPCR cycling program: 45 cycles including denaturation at 95°C for 5 sec, annealing at 60 for 30 sec and extension at 72°C for 30 sec. GAPDH was selected as the reference gene. The primers used for qRTPCR were shown in Table 1. All genes expression levels were quantified using the ΔΔct method.
Table 1. The Primers used for qRTPCR.
|
Name
|
Sequence
|
hsa_circ_0004831
|
Forward
|
5′- AAAGAAGAAAGAGCGTGCCG-3′
|
Reverse
|
5′- ATGATCATCAGAGGAGGGCG-3′
|
miR-4326
|
RT primer
|
5-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGTCTGG-3′
|
Forward
|
5′-GCCCGC TGTTCCTCTGTCTCCC-3′
|
Reverse
|
5′-GTGCAGGGTCCGAGGT-3′
|
ZBED1
|
Forward
|
5’-CCCGGACGAATTCTTCGAAATGGAGAATAAAAGCCTGGAGAG-3’
|
Reverse
|
5’-TGCGGATCACTAGTGCTAGCCTACAGGAAGCTGCTGTCCCTAATG-3’
|
GAPDH
|
Forward
|
5′-ATGGGGAAGGTGAAGGTCG
|
Reverse
|
5′- TTACTCCTTGGAGGCCATGTG -3′
|
U6
Forward
|
5′-CTCGCTTCGGCAGCACA-3′
|
Reverse
|
5′-AACGCTTCACGAATTTGCGT-3′
|
Identification of differentially expressed circRNAs, miRNAs and mRNAs
The circRNA and mRNA expression profiles in extracellular vesicles of CRC and normal samples were obtained from the exoRBase database [12]. The corresponding miRNA expression profile in extracellular vesicles was downloaded from the BBCancer database [13]. To ensure the reliability of data processing, the genes which have no expression value in more than half samples were excluded for analysis. The limma package[14] in R was used to identify differentially expressed circRNAs, miRNAs and mRNAs between CRC and normal samples. |Log2FC| > 1 and adj. P value < 0.05 were considered to be statistically significant difference.
Construction of circRNA-miRNA-mRNA network
The miRNAs which include miRNA binding sites on hsa_circ_0004831 genome sequence were predicted with Circbank [15] database (www.circbank.cn). The overlaps of predicted results and down-regulated miRNAs in CRC were regarded as miRNAs which could be regulated by hsa_circ_0004831 through competitive endogenous RNA mechanism. The target genes of miRNAs were predicted by TargetScan v7.1 tool [16]. Similarly, the overlaps of predicted genes and up-regulated mRNAs in CRC were regarded as target genes which involved in competitive endogenous RNA network. Finally, the circRNA-miRNA-mRNA regulatory network was constructed and visualized using Cytoscape v3.7.1 [17].
GSEA based on co-expressed mRNAs
The mRNAs co-expressed with hsa_circ_0004831 in CRC and normal samples were identified using pearson correlation analysis. Pearson |r| > 0.3 and p value < 0.05 were considered statistically significant. The expression matrix of co-expressed mRNAs was performed for GSEA to explore the biological differences between CRC and normal samples. The hallmark and KEGG [18] subsets in the Molecular Signatures Database (MSigDB) [19] were used as annotated gene sets during GSEA [20].
Statistical analysis
Statistical analysis used in present study was performed with GraphPad Prism v 7.00 for Windows (GraphPad Software, USA). The differences of genes expression levels between two groups were analyzed by two-tailed Student’s t-test. The overall survival analysis was performed using Kaplan–Meier curves and log-rank test. The optimal cut-off threshold of low or high hsa_circ_0004831 expression was calculated by X-tile [21]. A p value of < 0.05 was considered statistically significant.