Robust transcriptional tumor signatures applicable to both formalin-fixed paraffin-embedded and fresh-frozen samples

// Rou Chen 1, * , Qingzhou Guan 1, * , Jun Cheng 1 , Jun He 1 , Huaping Liu 1 , Hao Cai 1 , Guini Hong 1 , Jiahui Zhang 1 , Na Li 1 , Lu Ao 1 , Zheng Guo 1 1 Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou 350001, China * These authors contributed equally as first authors Correspondence to: Zheng Guo, email: guoz@ems.hrbmu.edu.cn Keywords: formalin-fixed paraffin-embedded samples, fresh-frozen samples, RNA degradation, gene expression measurements, relative expression orderings Received: October 27, 2016      Accepted: December 02, 2016      Published: December 27, 2016 ABSTRACT Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable resource for clinical researches. However, FFPE samples are usually considered an unreliable source for gene expression analysis due to the partial RNA degradation. In this study, through comparing gene expression profiles between FFPE samples and paired fresh-frozen (FF) samples for three cancer types, we firstly showed that expression measurements of thousands of genes had at least two-fold change in FFPE samples compared with paired FF samples. Therefore, for a transcriptional signature based on risk scores summarized from the expression levels of the signature genes, the risk score thresholds trained from FFPE (or FF) samples could not be applied to FF (or FFPE) samples. On the other hand, we found that more than 90% of the relative expression orderings (REOs) of gene pairs in the FF samples were maintained in their paired FFPE samples and largely unaffected by the storage time. The result suggested that the REOs of gene pairs were highly robust against partial RNA degradation in FFPE samples. Finally, as a case study, we developed a REOs-based signature to distinguish liver cirrhosis from hepatocellular carcinoma (HCC) using FFPE samples. The signature was validated in four datasets of FFPE samples and eight datasets of FF samples. In conclusion, the valuable FFPE samples can be fully exploited to identify REOs-based diagnostic and prognostic signatures which could be robustly applicable to both FF samples and FFPE samples with degraded RNA.