Abstract 1647: Radiation response genome-wide analysis using paired pre and post-radiation FFPE human breast tumor samples
Authors: Siamakpour-Reihani Sharareh , Chen Wei , Corcoran David , Lee Chen-Ting , Zhou Ying , Dewhirst Mark W. , Chi Jen-Tsan A. , Horton Janet K. 
Published: July 2016

Background: Breast cancer is the most common female malignancy in the US, and radiotherapy is a routine part of multi-disciplinary breast cancer care. Radiation treatment (RT) tailored to target radiation response pathways could maximize treatment benefit in radiation resistant tumors, while minimizing unnecessary toxicity and cost in more radiation responsive breast tumor subtypes. Here we report on genome-wide analysis, gene expression profiles and biological pathways associated with RT response in breast cancer patients. Methods: Between 2010-2013, a total of 32 breast cancer patients were enrolled at Duke University Medical Center on an IRB approved Phase I clinical trial testing preoperative radiotherapy. Paired pre and post-RT FFPE biopsy samples were available for N = 26. Genome wide-analysis was performed using two distinct techniques: i) Microarray analysis using the Affymetrix GeneChip ® Human Transcriptome Array 2.0 (HTA 2.0); ii) RNA-Seq using TruSeq ®RNA Access Library kit (Illumina). All libraries were sequenced on the Illumina HiSeq 2000 generating 50 bp single reads at a sequencing depth of 40 million reads. The RNA-Seq data was processed using the TrimGalore toolkit. For the paired pre and post-RT differential gene expression analysis we used the linear model. Genes that had an FDR ≤ 5% in the RNA-Seq experiment were compared with all microarray probesets that had an FDR ≤ 5%. If at least one probeset that belonged to a gene in the RNA-Seq list was significant and showed the same direction of change between pre and post-RT samples, they were identified as consistent. Gene Set Enrichment Analysis (GSEA) and Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to identify significant pathways and gene ontologies that were differentially regulated between the conditions. Results: 2648 genes showed the same significant results in response to RT in microarray and RNA-Seq including: i) a total of 1401 genes that had significantly higher expression levels, and ii) a total of 1247 genes that had significantly lower expression levels following RT. Principal Components Analysis (PCA) demonstrated distinct separation of pre and post-RT gene expression signatures. Differentially expressed genes were involved in major biological pathways such as cell cycle checkpoint, DNA replication and DNA repair pathways. A subset of these genes also demonstrated differential expression in radiation responsive vs. non-responsive breast cancer cell lines. Conclusion: New laboratory techniques have become available which provide the opportunity to use FFPE samples for microarray and RNA-seq analysis. Using these new techniques and our rare pre and post-RT FFPE breast tumor samples, we have been able to demonstrate distinct differences in gene expression profiles and modulation of biological pathways in response to RT in human breast tumors.

Citation Format: Sharareh Siamakpour-Reihani, Wei Chen, David Corcoran, Chen-Ting Lee, Ying Zhou, Mark W. Dewhirst, Jen-Tsan A. Chi, Janet K. Horton. Radiation response genome-wide analysis using paired pre and post-radiation FFPE human breast tumor samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1647.