Abstract 2323: Deciphering RNA degradation: Insights from a comparative analysis of paired fresh frozen/FFPE total RNA-seq

Abstract

Abstract Background: Fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) samples are primary resources for archival tissues in cancer studies. Despite the advantages of easy storage and cost-effectiveness, FFPE samples have the disadvantage of inevitable chemical-induced RNA degradation. Although, in mRNA-seq data, the 3' bias due to the characteristics of the mRNA-seq platform allows the measure of RNA degradation levels, for total RNA-seq and FFPE samples, there is still no clear measure for RNA degradation. Methods: Our study, utilizing The Cancer Genome Atlas (TCGA) pilot data comprised of 26 paired samples of fresh frozen mRNA-seq [FFM], fresh frozen total RNA-seq [FFT], and FFPE total RNA-seq [PET], investigated RNA degradation patterns in FFPE samples. Upon investigating the read coverage of transcripts in FFPE data, we observed increased noise parameters in selected samples compared to others, suggesting a method for assessment of RNA degradation in FFPE. To measure these noise patterns, we developed a method called windowCV (wCV) utilizing coefficient of variance (CV) along the transcript length. Also, based on reports that membrane-surrounded RNA such as lncRNA and mitochondrial RNA (mtRNA) might be less affected by formalin fixation, we developed the simple measure dividing expression value of other proteins with certain lncRNA or mtRNA inferring the degree of RNA degradation. Results: We first compared the shape of transcript read coverage from 3 different RNA-seq data and observed 3’bias pattern in FFM which was not observed in FFT and PET. For FFT and PET, we applied wCV and executed hierarchical clustering. We observed that a subset of samples and genes were clustered by high wCV value suggesting notable RNA degradation. To support the hypothesis of RNA degradation, we utilized Trimmed Mean of M values (TMM) expression ratio of paired FFT and PET to determine which samples and genes were associated with underestimation of expression in PET. Interestingly, we observed that PET/FFT TMM ratio showed negative correlation with wCV. Additionally, when we investigated hierarchical clustering result of PET/FFT TMM ratio, we found that lncRNA and mtRNA were less affected by FFPE. We then calculated expression ratio between membrane-surrounded RNA and a set of protein coding genes largely affected by FFPE. As a result, we found that this ratio positively correlated with paired PET/FFT TMM ratio. We conclude that this simple measurement can provide information of FFPE induced underestimated expression with limited transcriptome data as well as RNA degradation. Conclusion: Our method can provide gene-level CV while avoiding false positive variance signal originating from transcript model and simple way to detect the degree of RNA degradation across FFPE samples. Citation Format: Wonyoung Choi, Miyeon Yeon, Hyo Young Choi, David Neil Hayes. Deciphering RNA degradation: Insights from a comparative analysis of paired fresh frozen/FFPE total RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2323.