Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas - PubMed (original) (raw)

Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas

Grazyna Fedorowicz et al. BMC Med Genomics. 2009.

Abstract

Background: Gene expression profiling of formalin-fixed, paraffin-embedded (FFPE) samples represents a valuable approach for advancing oncology diagnostics and enhancing retrospective clinical studies; however, at present, this methodology still requires optimization and thus has not been extensively used. Here, we utilized thorough quality control methods to assess RNA extracted from FFPE samples and then compared it to RNA extracted from matched fresh-frozen (FF) counterparts. We preformed genome-wide expression profiling of FF and FFPE ovarian serous adenocarcinoma sample pairs and compared their gene signatures to normal ovary samples.

Methods: RNA from FFPE samples was extracted using two different methods, Ambion and Agencourt, and its quality was determined by profiling starting total RNA on Bioanalyzer and by amplifying increasing size fragments of beta actin (ACTB) and claudin 3 (CLDN3) by reverse-transcriptase polymerase chain reaction. Five matched FF and FFPE ovarian serous adenocarcinoma samples, as well as a set of normal ovary samples, were profiled using whole genome Agilent microarrays. Reproducibility of the FF and FFPE replicates was measured using Pearson correlation, whereas comparison between the FF and FFPE samples was done using a Z-score analysis.

Results: Data analysis showed high reproducibility of expression within each FF and FFPE method, whereas matched FF and FFPE pairs demonstrated lower similarity, emphasizing an inherent difference between the two sample types. Z-score analysis of matched FF and FFPE samples revealed good concordance of top 100 differentially expressed genes with the highest correlation of 0.84. Genes characteristic of ovarian serous adenocarcinoma, including a well known marker CLDN3, as well as potentially some novel markers, were identified by comparing gene expression profiles of ovarian adenocarcinoma to those of normal ovary.

Conclusion: Conclusively, we showed that systematic assessment of FFPE samples at the RNA level is essential for obtaining good quality gene expression microarray data. We also demonstrated that profiling of not only FF but also of FFPE samples can be successfully used to identify differentially expressed genes characteristic of ovarian carcinoma.

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Figures

Figure 1

Figure 1

Bioanalyzer profiles of total RNA (A) and cRNA (B) of matched FF and FFPE ovarian serous adenocarcinoma samples 3136, 3138, 3194, 3207 and 390. The method used for RNA extraction (Qiagen, Agencourt, Ambion) is indicated for each sample type. The RNA Integrity Number (RIN) is shown next to each total RNA profile.

Figure 2

Figure 2

RT-PCR amplification of different fragment sizes (200, 400, 600 and 800 bp) of ACTB and CLDN3 genes in FF and matched FFPE ovarian adenocarcinoma samples 3136, 3138, 3194, and 3207. The method used for RNA extraction is indicated next to each sample type.

Figure 3

Figure 3

Reproducibility of gene expression profiling within FF and FFPE sample type. Pearson correlation value (r) and number of "passing" probes are listed for samples 3136, 3138, 3194, 3207 and 390. Scatter graphs of log2 ratios comparing two FF (top) and two FFPE replicates (bottom) are shown for sample 3194.

Figure 4

Figure 4

Z-score analyses comparing FFPE and FF samples. Pearson correlation and misclassification rate (A) as well as scatter plots of Z-score values (B) for samples 3136, 3138, 3194 and 3207 are shown for "All probes" (in grey), "1000 Cy5" (in red) and "100 DE" (in blue) probe selection criteria.

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