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. 2004 Nov;165(5):1799-807.
doi: 10.1016/S0002-9440(10)63435-9.

Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays

Marina Bibikova  1 , Dimitri Talantov, Eugene Chudin, Joanne M Yeakley, Jing Chen, Dennis Doucet, Eliza Wickham, David Atkins, David Barker, Mark Chee, Yixin Wang, Jian-Bing Fan
Affiliations

Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays

Marina Bibikova et al. Am J Pathol. 2004 Nov.

Abstract

We recently developed a sensitive and flexible gene expression profiling system that is not dependent on an intact poly-A tail and showed that it could be used to analyze degraded RNA samples. We hypothesized that the DASL (cDNA-mediated annealing, selection, extension and ligation) assay might be suitable for the analysis of formalin-fixed, paraffin-embedded tissues, an important source of archival tissue material. We now show that, using the DASL assay system, highly reproducible tissue- and cancer-specific gene expression profiles can be obtained with as little as 50 ng of total RNA isolated from formalin-fixed tissues that had been stored from 1 to over 10 years. Further, tissue- and cancer-specific markers derived from previous genome-wide expression profiling studies of fresh-frozen samples were validated in the formalin-fixed samples. The DASL assay system should prove useful for high-throughput expression profiling of archived clinical samples.

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Figures

Figure 1
Figure 1
Real-time PCR analysis of RNAs isolated from FFPE tissues with different duration of storage. The Ct values (y axis) for two amplicons of different sizes that monitor a highly expressed gene, RPL13A, were plotted for each sample group (x axis): FF, fresh-frozen; FS1, 1 year; FS2, 2 years; FS3, 9–11 years. The average difference in the Ct values (ΔCt) of the two amplicons was derived from each sample group as −0.3 ± 0.1, 2.7 ± 1.1, 4.2 ± 1.1, and 5.8 ± 1.0, respectively. The error bars represent the SD from the mean.
Figure 2
Figure 2
Reproducible expression profiling with various amounts of input RNA. The assay intensity for lower RNA input (50 ng, x axis) is plotted against the assay intensity for the same genes in the higher RNA input (500 ng, y axis) for six individual tissue samples.
Figure 3
Figure 3
Cluster analysis of FFPE samples. Agglomerative clustering was based on the differentially expressed genes identified from fresh-frozen samples. The distance between subclusters (y axis, Height) measures the divergence of their expression profiles.
Figure 4
Figure 4
Box plots of the array data for selected cancer-specific markers. Array intensities (y axis) were calculated for the four colon cancer markers (A) and the four breast cancer markers (B) from both fresh-frozen and FFPE sample analysis. For the colon cancer markers (A), 12 cancer and 12 normal tissues were used. For the breast cancer markers (B), 11 cancer and 11 normal tissues were used. 500 ng of total RNA isolated from the FFPE tissue blocks were used in each assay. The black bar represents the mean intensity value. The gray box defines quartiles (25% and 75%, respectively). The error bars are upper and lower adjacent limits (median ± 1.5*IQR). Dots represent the outliers. The P values for the colon cancer markers are 7.40E-07 (SIM2), 0.0005 (PLAB), 0.0014 (FGFR2), and 0.0015 (human skin collagenase). The P values for the breast cancer markers are 0.0002 (EGFR), 0.0010 (IGF-1a), 0.0035 (FGF2), and 0.0063 (calmegin).
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