RNA quality in frozen breast cancer samples and the influence on gene expression analysis--a comparison of three evaluation methods using microcapillary electrophoresis traces

Abstract

Background: Assessing RNA quality is essential for gene expression analysis, as the inclusion of degraded samples may influence the interpretation of expression levels in relation to biological and/or clinical parameters. RNA quality can be analyzed by agarose gel electrophoresis, UV spectrophotometer, or microcapillary electrophoresis traces, and can furthermore be evaluated using different methods. No generally accepted recommendations exist for which technique or evaluation method is the best choice. The aim of the present study was to use microcapillary electrophoresis traces from the Bioanalyzer to compare three methods for evaluating RNA quality in 24 fresh frozen invasive breast cancer tissues: 1) Manual method = subjective evaluation of the electropherogram, 2) Ratio Method = the ratio between the 28S and 18S peaks, and 3) RNA integrity number (RIN) method = objective evaluation of the electropherogram. The results were also related to gene expression profiling analyses using 27K oligonucleotide microarrays, unsupervised hierarchical clustering analysis and ontological mapping.

Results: Comparing the methods pair-wise, Manual vs. Ratio showed concordance (good vs. degraded RNA) in 20/24, Manual vs. RIN in 23/24, and Ratio vs. RIN in 21/24 samples. All three methods were concordant in 20/24 samples. The comparison between RNA quality and gene expression analysis showed that pieces from the same tumor and with good RNA quality clustered together in most cases, whereas those with poor quality often clustered apart. The number of samples clustering in an unexpected manner was lower for the Manual (n = 1) and RIN methods (n = 2) as compared to the Ratio method (n = 5). Assigning the data into two groups, RIN > or = 6 or RIN < 6, all but one of the top ten differentially expressed genes showed decreased expression in the latter group; i.e. when the RNA became degraded. Ontological mapping using GoMiner (p < or = 0.05; > or = 3 genes changed) revealed deoxyribonuclease activity, collagen, regulation of cell adhesion, cytosolic ribosome, and NADH dehydrogenase activity, to be the five categories most affected by RNA quality.

Conclusion: The results indicate that the Manual and RIN methods are superior to the Ratio method for evaluating RNA quality in fresh frozen breast cancer tissues. The objective measurement when using the RIN method is an advantage. Furthermore, the inclusion of samples with degraded RNA may profoundly affect gene expression levels.

Figure 1

Bioanalyzer electropherograms. Bioanalyzer electropherograms of three samples, a) Sample 3, b) Sample 5, and c) Sample 6 after different lengths of time: 50 seconds, 2–3 minutes, 10 minutes, and 30 minutes, respectively. Three methods were used for evaluating the RNA quality, see Methods. Pearson correlation coefficients were obtained, when the gene expression levels of the sample for the different time periods at room temperature were related to the gene expression levels of the sample left at room temperature for 50 seconds.

Figure 2

Unsupervised hierarchical clustering. Unsupervised hierarchical clustering was used to assess which samples clustered together based on their gene expression profiles. A. Clustering according to the Manual evaluation method; green = good, blue = partly degraded, red = degraded. B. Clustering according to the Ratio method; green = ratio ≥ 0.65 (i.e. good), red = ratio < 0.65 (i.e. degraded), and black = N/A (i.e. not available). C. Clustering according to the RIN method; green = RIN ≥ 6 and red = RIN < 6. Arrows indicate samples clustering in an unexpected manner, according to the respective methods.

Figure 3

Top ten differentially expressed genes. The top ten most differentially expressed genes between RIN ≥ 6 and RIN < 6. LAMA4 = laminin 4, DCN = decorin, OR10C1 = olfactory receptor, LGALS1 = lectin galactoside-binding, PNMA1 = paraneoplastic antigen, neuron and testis specific protein, TCEA1 = transcription elongation factor A, MRLC2 = myosin regulatory light chain, KIFAP3 = kinesin-associated protein 3, GNG10 = guanine nucleotide binding protein, and C6orf89 = chromosome 6 open reading frame 89. Filled circles represent outliers.

Figure 4

Correlation between the RIN value and Pearson correlation. In order to evaluate the RIN cut-off value of 6, we compared it to Pearson correlation coefficients. Pearson correlation coefficients were obtained, when the gene expression levels of the samples for the different time periods at room temperature, were related to the gene expression levels of the samples left 50 seconds at room temperature. If the correlation coefficient of the gene expression level is the true value, two samples obtain unexpected RIN values, i.e. a low correlation coefficient and a RIN value above the cut-off or vice versa (arrows, RIN 5 = Sample 5, 10 min and RIN 6 = Sample 3, 30 min).