A Comparison of RNA-Seq Results from Paired Formalin-Fixed Paraffin-Embedded and Fresh-Frozen Glioblastoma Tissue Samples

Abstract

The molecular classification of glioblastoma (GBM) based on gene expression might better explain outcome and response to treatment than clinical factors. Whole transcriptome sequencing using next-generation sequencing platforms is rapidly becoming accepted as a tool for measuring gene expression for both research and clinical use. Fresh frozen (FF) tissue specimens of GBM are difficult to obtain since tumor tissue obtained at surgery is often scarce and necrotic and diagnosis is prioritized over freezing. After diagnosis, leftover tissue is usually stored as formalin-fixed paraffin-embedded (FFPE) tissue. However, RNA from FFPE tissues is usually degraded, which could hamper gene expression analysis. We compared RNA-Seq data obtained from matched pairs of FF and FFPE GBM specimens. Only three FFPE out of eleven FFPE-FF matched samples yielded informative results. Several quality-control measurements showed that RNA from FFPE samples was highly degraded but maintained transcriptomic similarities to RNA from FF samples. Certain issues regarding mutation analysis and subtype prediction were detected. Nevertheless, our results suggest that RNA-Seq of FFPE GBM specimens provides reliable gene expression data that can be used in molecular studies of GBM if the RNA is sufficiently preserved.

Fig 1. Degradation quality metrics in FF and FFPE tumour samples.

(A) Paired-end distance distributions. Negative values correspond to overlapping paired-end reads. Blue lines represent FF samples and red lines represent FFPE samples. (B) Read GC content distributions. The more degraded the sample, the sharper the distribution. Regions with 40% of GC content are more conserved. A small peak at 80% of GC content can be clearly observed for the most degraded FFPE sample (AA6365). Blue lines represent FF samples and red lines represent FFPE samples.

Fig 2. Degradation quality metrics.

(A) Gene coverage heatmap. More degraded regions are depicted blue. All samples were affected at the 5’ end of the gene body but this effect was more prominent for FFPE samples. The most degraded FFPE sample (AA6365) also showed degradation at the 3’ end and across the gene body. (B) Line graphs (FF, blue; FFPE, red) showing the mean per-base coverage of RNA transcripts for all paired samples. Strong coverage unevenness was observed for the most degraded sample (FFPE_AA6365).

Fig 3. Mapped reads in FF and FFPE tissue samples.

Percentages of uniquely mapped paired-reads, ambiguously mapped paired-end reads, paired-end reads mapping into a single gene, and paired-end reads mapping into multiple genes. Note that the most degraded FFPE sample (AA_6365) had very high percentages of ambiguous reads (>90%) and reads mapping to multiple genes (>80%), whereas the second most degraded FFPE sample (AA_6364) had intermediate percentages (25% and ~30% respectively). The remaining samples had low percentages of ambiguities (~10%).

Fig 4. Mapping results in FFPE and matched FF tissue samples.

(A) Percentages of unmapped reads and split-mapped reads in FFPE and FF samples. (B) Percentages of paired-end reads mapping to exonic, intronic or intergenic regions.

Fig 5. Boxplots of PSI values for intron retention events.

Results for FF samples are shown in blue and those for FFPE samples in red. The PSI value was defined as the number of reads supporting the inclusion divided by the number of reads supporting the inclusion or the exclusion. The median PSI value for intron retention events was higher in FFPE samples, suggesting a greater abundance of transcripts with unspliced introns, such as pre-mRNAs or linc-RNAs.

Fig 6. Annotated paired-end reads mapping to different gene biotypes.

The majority of annotated reads mapped to protein-coding genes for all samples except FFPE_AA6365, which showed extremely high amounts of ribosomal MT RNA. The percentage of reads mapping to non-coding RNA was higher for FFPE than FF samples.

Fig 7. Comparison of gene expression between FF and FFPE samples.

(A) Correlation plots of gene expression in FF-FFPE pairs. In general, the correlation was high (R²~0.9), with the exception of the FF_AA6361-FFPE_AA6365 pair, where the FFPE sample was highly degraded. Higher variability was observed for more degraded samples. (B) Results of the principal component analysis. FF-FFPE pairs clustered together. The most degraded sample (FFPE_AA6365) was not included in the plot.

Fig 8. Number of mismatches across the read length.

Mismatch profiles changed dramatically mainly due to G>A and C>T changes, which were substantially more frequent in FFPE samples (top pink and blue lines). Sample FFPE_AA6365, which was highly degraded, showed a totally different pattern, not matching with any other sample.