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

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 < or = Ct < or = 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.

Figure 1

Ct values according to different input RNA concentrations. A) Plot of the difference in Ct values vs. mean Ct between duplicate plates for varying input RNA concentrations. Red lines indicate divisions between high (Ct<30), medium (30≤Ct≤35) and low (Ct>35) abundance strata. The total number of miRs is shown within each stratum for each RNA concentration (e.g., 72 miRs have Ct values <30 at the 10 ng RNA dilution compared to 112 miRs at the 200 ng dilution). B) Boxplots depicting the median of the absolute difference in Cts between duplicate plates for each miR abundance stratum according to input RNA concentration.

Figure 2

Clustering heat-maps and pair-wise correlations for equivalent samples. The pair-wise correlations between equivalent samples are shown within A) low abundance stratum: The low abundance miRs have a low correlation coefficient (range: 0.16-0.31) regardless of the concentration and dilution factor used. B) medium abundance stratum, showing higher correlation coefficients (range: 0.75-0.86) compared to the low abundance stratum. C) high abundance stratum: In this stratum we detect the highest correlation coefficients (range: 0.98-0.99) between samples. Note that the scales are different for each abundance stratum, reflecting the respective correlation coefficients.

Figure 3

Ct values according to different extraction methods for paired fresh-frozen and FFPE tissues. Comparison of the summary statistics (mean Ct, standard deviation, and overall range of Ct values) using raw Ct scores obtained from the normal lymph nodes and mantle cell lymphoma samples extracted using three separate RNA extraction methods. On comparison of the FFPE summary statistics to those from the mirVana and TRIzol-Qiagen extraction protocols, we see that the mean Ct values obtained from the FFPE samples are significantly higher than those obtained from the mirVana and TRIzol-Qiagen extraction protocols (p < 0.0001 and p < 0.0001 respectively).

Figure 4

Correlation heatmaps and PCA mapping for paired fresh-frozen and FFPE tissues. Correlation heat-maps demonstrating hierarchical clustering among 3 normal lymph nodes (n1-n3) and 3 mantle cell lymphomas (t1-t3) extracted using different techniques using: A) Low abundance miRs B) Medium abundance miRs C) High abundance miRs. Panel D) shows principal component analysis (PCA) confirming the similarity of miR expression between tumours (red), and normal samples (blue), irrespective of tissue origin (FFPE vs. fresh-frozen).

Figure 5

Comparison of miR abundance in paired fresh-frozen and FFPE tissues, using different RNA extraction methods. Plots show the comparison of Ct values for three normal and three mantle cell lymphoma samples by the three different extraction methods: A) FFPE (RecoverAll) vs. mirVana; B) FFPE (RecoverAll) vs. TRIzol; C) TRIzol vs. mirVana. Red lines delineate the abundance strata for each extraction method, with numbers indicating the average number of miRs per sample in each zone. For example, in the FFPE vs. mirVana plot (Figure 5A), 44 miRs are high abundance by mirVana and medium abundance by FFPE (RecoverAll), but only 4 miRs are high abundance by FFPE (RecoverAll) and medium abundance by mirVana.