Abstract PD05-05: RNA-seq identifies unique transcriptomic changes after brief exposure to preoperative nab-paclitaxel (N), bevacizumab (B) or trastuzumab (T) and reveals down-regulation of TGF-β signaling associated with response to bevacizumab

Abstract

Abstract Background: Identification of differentially expressed transcripts upon brief exposure to preoperative therapy can help determine likely response markers. We quantify and compare differential transcript expression using RNA-seq on patient samples before and after one dose of T or B or N. We also evaluate correlation of brief-exposure transcriptomic changes with response to B. Methods: We sequenced transcriptomes of core biopsy RNA from 50 pairs of breast tumors obtained from neoadjuvant clinical trials BrUOG 211A/211B. Patients were given a run-in dose of B or N or T, followed by combination biologic/chemotherapy (HER2− with B/carboplatin/N; HER2+ with T/carboplatin/N). We sequenced biopsy pairs obtained pre/post 10 day exposure to run-in monotherapy. Paired-end sequencing was done on Illumina GAII platform using amplified total RNA with 74bp read length, yielding expression data for 22,302 genes and 35,768 transcripts. We evaluated transcriptomic changes upon brief exposure to monotherapy assuming Poisson-distributed read-counts, followed by multiple testing correction and enrichment analysis of 185 KEGG pathways. We investigated association of transcriptomic changes upon brief exposure and pathologic complete response (pCR) in the B arm. Differential expression of previously published signatures of tumor vasculature, TGF-β, β-catenin, MYC, E2F3 and RAF-MEK pathway activities were evaluated to identify associations with pCR. Results: PAM50-based clustering showed individual samples cluster together, demonstrating that tumor subtypes do not change over the 10-day treatment. We identified unique transcripts that were significantly differentially expressed in each therapy arm (p < 0.05;FDR<0.1). Significant down-regulation of tumor vasculature-related genes was seen in B samples (p = 0.05). We found 1024 genes whose significant differential expression correlated with pCR in the B arm (Mann-Whitney p-val<0.05; abs log2-fold change≥0.5). Only 4 KEGG pathways, TGF-β signaling, Cell Cycle, DNA Replication and Steroid Biosynthesis were found to be enriched (p ≤ 0.05) in the pCR-associated gene list, and displayed significant down-regulation of member genes within the pCR group. To further evaluate the enrichment results, we used several published pathway activity gene signatures. Interestingly, clustering of the B-treated samples using a TGF-β response signature strongly clustered pCR cases due to down-regulation of TGF-β activity in that group (p = 0.004). We found that the TGF-β signature was most informative of pCR when compared to E2F3, RAF-MEK, β-catenin and MYC signatures in the B arm. Conclusions: This is the first study to compare differential gene expression upon brief exposure across therapies using RNA-seq technology. The association of TGF-β activity with pCR in B arm was identified using both a bottom-up statistical approach and with a previously published TGF-β activity signature. The unique aspects of transcriptional response to each treatment and the association of transcriptional changes with response underscore the value of the brief-exposure paradigm to identify markers of neo-adjuvant therapeutic response. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr PD05-05.