Adaptation of a RAS pathway activation signature from FF to FFPE tissues in colorectal cancer

Abstract

Background: The KRAS gene is mutated in about 40 % of colorectal cancer (CRC) cases, which has been clinically validated as a predictive mutational marker of intrinsic resistance to anti-EGFR inhibitor (EGFRi) therapy. Since nearly 60 % of patients with a wild type KRAS fail to respond to EGFRi combination therapies, there is a need to develop more reliable molecular signatures to better predict response. Here we address the challenge of adapting a gene expression signature predictive of RAS pathway activation, created using fresh frozen (FF) tissues, for use with more widely available formalin fixed paraffin-embedded (FFPE) tissues.

Methods: In this study, we evaluated the translation of an 18-gene RAS pathway signature score from FF to FFPE in 54 CRC cases, using a head-to-head comparison of five technology platforms. FFPE-based technologies included the Affymetrix GeneChip (Affy), NanoString nCounter™ (NanoS), Illumina whole genome RNASeq (RNA-Acc), Illumina targeted RNASeq (t-RNA), and Illumina stranded Total RNA-rRNA-depletion (rRNA).

Results: Using Affy_FF as the "gold" standard, initial analysis of the 18-gene RAS scores on all 54 samples shows varying pairwise Spearman correlations, with (1) Affy_FFPE (r = 0.233, p = 0.090); (2) NanoS_FFPE (r = 0.608, p < 0.0001); (3) RNA-Acc_FFPE (r = 0.175, p = 0.21); (4) t-RNA_FFPE (r = -0.237, p = 0.085); (5) and t-RNA (r = -0.012, p = 0.93). These results suggest that only NanoString has successful FF to FFPE translation. The subsequent removal of identified "problematic" samples (n = 15) and genes (n = 2) further improves the correlations of Affy_FF with three of the five technologies: Affy_FFPE (r = 0.672, p < 0.0001); NanoS_FFPE (r = 0.738, p < 0.0001); and RNA-Acc_FFPE (r = 0.483, p = 0.002).

Conclusions: Of the five technology platforms tested, NanoString technology provides a more faithful translation of the RAS pathway gene expression signature from FF to FFPE than the Affymetrix GeneChip and multiple RNASeq technologies. Moreover, NanoString was the most forgiving technology in the analysis of samples with presumably poor RNA quality. Using this approach, the RAS signature score may now be reasonably applied to FFPE clinical samples.

Keywords: Colorectal cancer; FF (fresh-frozen); FFPE (formalin-fixed; Microarray; NanoString; Paraffin embedded); RAS pathway signature; RNASeq.

Fig. 1

Flow-chart of the procedure followed in the pre-processing and analysis of the data. Six datasets (1 FF and 5 FFPE, each with 54 samples and 18 genes) underwent quality control procedures before analysis. Thirty-nine [39] “good” samples and 16 “good” genes were retained. Correlation analyses were performed using mean scores from the sample pairs. The predictive ability of the 16–gene set was validated using the Affymetrix FF, Affymetrix FFPE and NanoString gene expression data, by the PAM method

Fig. 2

Scatterplot of the second vs. first principal component (PC2 vs PC1) for the 54 Affymetrix FFPE samples. The 15 “bad” samples (with low PC1 scores) are colored red and were excluded from subsequent analyses. Each sample was labeled using the last 3 digits of its name (barcode)

Fig. 3

Scatterplots of the Affymetrix FF vs. Affymetrix FFPE (a) and NanoString FFPE (b) mean scores for the 54 samples. The red circles represent the 15 samples with “poor” RNA quality