BMC Biotechnology

official impact factor 2.86

Open Access Highly Access Methodology article

Optimization and analysis of a quantitative real-time PCR-based technique to determine microRNA expression in formalin-fixed paraffin-embedded samples

Rashmi S Goswami1,2, Levi Waldron3,4, Jerry Machado1,2, Nilva K Cervigne1, Wei Xu5, Patricia P Reis1, Denis J Bailey2,6, Igor Jurisica3,7,8, Michael R Crump9 and Suzanne Kamel-Reid1,2,8,6*

Author Affiliations

1 Division of Applied Molecular Oncology, Ontario Cancer Institute, University Health Network, Toronto, ON, Canada

2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada

3 Division of Signaling Biology, Ontario Cancer Institute

4 Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON, Canada

5 Department of Biostatistics, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada

6 Department of Pathology, Toronto General Hospital, University Health Network, Toronto, ON, Canada

7 Department of Computer Science, University of Toronto, Toronto, ON, Canada

8 Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada

9 Division of Medical Oncology, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada

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BMC Biotechnology 2010, 10:47 doi:10.1186/1472-6750-10-47

Published: 23 June 2010

Abstract

Background

MicroRNAs (miRs) are non-coding RNA molecules involved in post-transcriptional regulation, with diverse functions in tissue development, differentiation, cell proliferation and apoptosis. miRs may be less prone to degradation during formalin fixation, facilitating miR expression studies in formalin-fixed paraffin-embedded (FFPE) tissue.

Results

Our study demonstrates that the TaqMan Human MicroRNA Array v1.0 (Early Access) platform is suitable for miR expression analysis in FFPE tissue with a high reproducibility (correlation coefficients of 0.95 between duplicates, p < 0.00001) and outlines the optimal performance conditions of this platform using clinical FFPE samples. We also outline a method of data analysis looking at differences in miR abundance between FFPE and fresh-frozen samples. By dividing the profiled miR into abundance strata of high (Ct<30), medium (30≤Ct≤35), and low (Ct>35), we show that reproducibility between technical replicates, equivalent dilutions, and FFPE vs. frozen samples is best in the high abundance stratum. We also demonstrate that the miR expression profiles of FFPE samples are comparable to those of fresh-frozen samples, with a correlation of up to 0.87 (p < 0.001), when examining all miRs, regardless of RNA extraction method used. Examining correlation coefficients between FFPE and fresh-frozen samples in terms of miR abundance reveals correlation coefficients of up to 0.32 (low abundance), 0.70 (medium abundance) and up to 0.97 (high abundance).

Conclusion

Our study thus demonstrates the utility, reproducibility, and optimization steps needed in miR expression studies using FFPE samples on a high-throughput quantitative PCR-based miR platform, opening up a realm of research possibilities for retrospective studies.