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Open Access Highly Accessed Open Badges Methodology article

Improvement of tissue preparation for laser capture microdissection: application for cell type-specific miRNA expression profiling in colorectal tumors

Shuyang Wang1, Lei Wang1, Tengfang Zhu1, Xue Gao4, Jian Li2, Ying Wu12* and Hongguang Zhu134*

Author Affiliations

1 Department of Pathology, Shanghai Medical College, Fudan University, 138 Yi Xue Yuan Road, Shanghai 200032, PR China

2 Department of Healthcare, Philips Research Asia - Shanghai, No 10, Lane 888, Tian Lin Road, Shanghai 200233, PR China

3 Division of Surgical Pathology, Huashan Hospital, Fudan University, 12 middle-Wulumuqi Road, Shanghai 200040, PR China

4 Research Center for Pathology, Institute of Biomedical Sciences, Fudan University, 138 Yi Xue Yuan Road, Shanghai 200032, PR China

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BMC Genomics 2010, 11:163  doi:10.1186/1471-2164-11-163

Published: 10 March 2010



Laser capture microdissection (LCM) has successfully isolated pure cell populations from tissue sections and the combination of LCM with standard genomic and proteomic methods has revolutionized molecular analysis of complex tissue. However, the quantity and quality of material recovered after LCM is often still limited for analysis by using whole genomic and proteomic approaches. To procure high quality and quantity of RNA after LCM, we optimized the procedures on tissue preparations and applied the approach for cell type-specific miRNA expression profiling in colorectal tumors.


We found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p = 0.0014) and quantity (1.5 fold, p = 0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2 ± 1.5 (average ± SD) for normal (n = 43), 5.7 ± 1.1 for adenomas (n = 14) and 7.2 ± 1.2 for carcinomas (n = 44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal, 6 adenomas and 6 carcinomas) between LCM selected epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p <= 0.001) between these two cell types. We found that the miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues. Finally, we applied quantitative RT-PCR to cross-verify the expression patterns of 7 different miRNAs using 8 LCM-selected epithelial cells and found the excellent correlation of the fold changes between the two platforms (R = 0.996).


Our study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.