Meta-analysis of the differentially expressed colorectal cancer-related microRNA expression profiles

H.-G. Li, L.-H. Zhao, X.-B. Bao, P.-C. Sun, B.-P. Zhai

Department of General Surgery, Henan Provincial People’s Hospital, Zhengzhou, China. lihongguanglhg@hotmail.com

---

• Oncology

OBJECTIVES: Unique microRNAs (miRNAs) have been identified in colorectal cancer in recent studies which can be used to accurately diagnose the presence of colorectal cancer and help predict disease recurrence. Differential expression of specific miRNAs in tissues or blood offers the prospect of their use in early detection and screening for colorectal cancer. However, the experiments under different environments would produce different results. The purpose of this study was to get a reliable result on differentially expressed miRNAs related to colorectal cancer by integrating different studies.

MATERIALS AND METHODS: A meta-analysis was performed to review three miRNA microarray datasets from three published literatures that compared the microRNAs expression profiles in colorectal cancer tissues with those in normal colorectal tissues. The R VennDiagram package was applied to identify the overlapping miRNAs with differential expression among these three studies.

RESULTS: A total of 175 differentially expressed miRNAs were reported in the three miRNA expression profiling studies that compared colorectal cancer tissues with normal tissues, of which 25 miRNAs were reported at least by two studies including 15 up-regulated miRNAs and 10 down-regulated miRNAs. Among the 25 miRNAs, 15 ones were differentially expressed between early stage colorectal cancer and normal tissues including 11 up-regulated miRNAs and 4 down-regulated miRNAs, of which hsa-miR-195 (down-regulated) and hsa-miR-20a (up-regulated) were shared by these three studies.

CONCLUSIONS: The 15 differentially expressed miRNAs, especially hsa-miR-195 and hsa-miR-20a may be used as potential biomarkers for early detection and screening of colorectal cancer.

Free PDF Download