Identifying microRNA-mRNA regulatory network in colorectal cancer by a combination of expression profile and bioinformatics analysis

Abstract

Background: MicroRNAs (miRNAs) are involved in carcinogenesis and tumor progression by regulating post-transcriptional gene expression. However, the miRNA-mRNA regulatory network is far from being fully understood. The objective of this study is to identify the colorectal cancer (CRC) specific miRNAs and their target mRNAs using a multi-step approach.

Results: A multi-step approach combining microarray miRNA and mRNA expression profile and bioinformatics analysis was adopted to identify the CRC specific miRNA-mRNA regulatory network. First, 32 differentially expressed miRNAs and 2916 mRNAs from CRC samples and their corresponding normal epithelial tissues were identified by miRNA and mRNA microarray, respectively. Secondly, 22 dysregulated miRNAs and their 58 target mRNAs (72 miRNA-mRNA pairs) were identified by a combination of Pearson's correlation analysis and prediction by databases TargetScan and miRanda. Bioinformatics analysis revealed that these miRNA-mRNAs pairs were involved in Wnt signaling pathway. Additionally, 6 up-regulated miRNAs (mir-21, mir-223, mir-224, mir-29a, mir-29b, and mir-27a) and 4 down-regulated predicted target mRNAs (SFRP1, SFRP2, RNF138, and KLF4) were selected to validate the expression level and their anti-correlationship in an extended cohort of CRC patients by qRT-PCR. Except for mir-27a, the differential expression and their anti-correlationship were proven. Finally, a transfection assay was performed to validate a regulatory relationship between mir-29a and KLF4 at both RNA and protein levels.

Conclusions: Seventy-two miRNA-mRNA pairs combined by 22 dysregulated miRNAs and their 58 target mRNAs identified by the multi-step approach appear to be involved in CRC tumorigenesis. The results in our study were worthwhile to further investigation via a functional study to fully understand the underlying regulatory mechanisms of miRNA in CRC.

Figure 1

Step 1, both miRNA and mRNA microarray tests for identifying significantly dysregulated miRNAs and mRNAs in colorectal cancer. Step 2, Pearson correlation analysis for anti-correlationship of dysregulated miRNAs and mRNAs. Step 3, TargetScan and Mirnada predicting the target-relationship miRNA-mRNA pairs.

Figure 2

FDR < 0.05 for students t-test and q-value < 0.05 for SAM were considered as significantly differentially expressed. The data were z-score transformed and were indicated by the color bar below the heatmap.

Figure 3

A. The expression levels of 5 miRNAs were significantly up-regulated. B. The expression levels of 4 mRNA targets in CRC samples and adjacent normal tissues. The expression levels were expressed as –ΔΔCT after normalized with beta-actin. P-value was calculated by paired t-test.

Figure 4

A. The transfection of mir-29a mimics into HCT-116 cells down-regulates KLF4 mRNA expression (Left, QRT-PCR) and protein expression (Right, Western blot). B. The transfection of mir-29a inhibitor into HCT-116 cells up-regulates KLF4 mRNA expression (Left, QRT-PCR) and protein expression (Right, Western blot). The experiments were independently repeated three times and GADPH served as control. ***, P < 0.001.