Abstract P3-06-17: Unlocking the transcriptomic potential of formalin-fixed paraffin embedded breast cancer tissues for high-throughput genomic analysis

Abstract

Background: Transcriptomic analyses of clinical samples can help improve our understanding of disease aetiology, drug effectiveness, assign molecular subtypes and derive prognostic signatures for clinical decision-making. The success of early microarray studies relied heavily on sample quality and predominantly fresh frozen (FF) tissues to generate reliably robust data. The emergence of next-generation microarray and sequencing-based technologies from formalin-fixed paraffin-embedded (FFPE) tissues provides an opportunity to study archival clinical tissues with long-term follow-up. Here we assess 9 technologies, which vary in resolution, cost and RNA requirements, with matched FF and FFPE tissues from the same patient. Methods: Sequential tumour biopsies were taken pre-treatment and on-treatment (at 14-days and 3-months) from 11 postmenopausal patients with oestrogen receptor positive breast cancer treated with 3 months of neoadjuvant letrozole. Half of each sample was snap frozen in liquid nitrogen and half was FFPE, RNA was extracted from both. Transcriptomic analyses were performed using 9 technologies: Illumina Beadarray, Affymetrix U133A, Affymetrix Clariom S, NanoString nCounter, AmpliSeq Transcriptome, Lexogen QuantSeq and IonXpress RNAseq, Tempo-Seq BioSpyder and Qiagen UPX39. Results: Success rates for generating robust expression profiles from FFPE tissues were 100% all except the Illumina BeadChip (22%) and AmpliSeq Transcriptome (83%) , which varied by the age of tissue. With the total number and position of probes/primers/counts varying widely between approaches, in total 7305 genes were represented across all of the whole-genome technologies tested. Clear batch effects were evident when comparing data from FF and FFPE tissues and when comparing between different technologies. Standard batch correction approaches such as XPN and ComBat minimised technical bias effect and increased the correlations between matched samples (FF and FFPE) to R>0.9, irrespective of the technology used. When analysed by multi-dimensional scaling following batch correction, samples clustered by treatment time-point. When ranked by expression of 60 proliferation genes, reported by us to change with letrozole treatment, samples ordered again by time-point, consistent with our previous findings, and paired samples clustered together. Conclusions: · Robust gene expression profiles can be reliably generated from FFPE tissues and are comparable to those derived from FF tissue using established transcriptomic approaches. · A range of new technologies are available for the study of FFPE tissues; these vary in cost, resolution and RNA requirements to fit the user9s needs. · Gene expression data from biologically similar studies, generated using different technologies, can be reliably integrated for robust meta-analysis, subject to appropriate batch correction analysis. Citation Format: Turnbull AK, Selli C, Martinez-Perez C, Fernando A, Renshaw L, Keys J, Figueroa JD, He X, Tanioka M, Munro A, Murphy L, Fawkes A, Clark R, Coutts A, Perou CM, Carey LA, Dixon JM, Sims AH. Unlocking the transcriptomic potential of formalin-fixed paraffin embedded breast cancer tissues for high-throughput genomic analysis [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-17.