Abstract PD01-08: Decoding the Transcriptional Landscape of Triple-Negative Breast Cancer Using Next-Generation Whole Transcriptome Sequencing
Authors: M Radovich, SE Clare, GW Sledge, I Pardo, T Mathieson, N Kassem, BA Hancock, AMV Storniolo, C Rufenbarger, HA Lillemoe, J Sun, JE Henry, R Goulet, EE Hilligoss, AS Siddiqui, H Breu, O Sakarya, FC Hyland, MW Muller, L Popescu, J Zhu, M Hickenbotham, J Glasscock, M Ivan, Y Liu, BP. Schneider
Journal: Cancer Research (2010)

Abstract Background: Triple-negative breast cancer (TNBC) has been plagued by the absence of targeted therapies. Discovery of therapeutic targets in TNBC has in part, been hampered by an inadequate understanding of the transcriptional biology of the normal breast as an optimal comparator. Using next-generation sequencing, we embarked on a study to compare the transcriptomes of TNBC and normal breast to comprehensively identify novel targets by analyzing all full length transcripts expressed in these tissues. Methods: Normal breast tissues from healthy pre-menopausal volunteers with no history of disease were procured from the Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center. To eliminate bias from stromal tissue, normal tissues were laser capture microdissected for ductal epithelium. cDNA libraries from 10 TNBC tumors and 10 normal breast tissues were sequenced on an Applied Biosystems (AB) SOLiD3 sequencer using 50bp fragment runs. For gene expression, mapping of reads to the genome was performed using the AB BioScope 1.2 Pipeline and outputs imported into Partek Genomics Suite for analysis. In Partek, mapped reads were cross-referenced against known genes from the UCSC database followed by statistical comparison of RPKM values for each gene between TNBC and normal. Dimensionality reduction analyses (PCA &amp; Hierarchical clustering) and identification of Novel Transcribed Regions were also performed in Partek, whereas construction of gene networks was performed using Ingenuity Pathway Analysis. To identify gene fusions, partially mapped reads were interrogated utilizing a novel algorithm that searched for reads spanning exons from two different genes. Fusions that were supported by at least 3 reads (of which 2 had to be unique) were considered candidates and were subsequently validated. Results/Discussion: Sequencing produced 1.1 billion reads equaling 57.3GB of data of which 36.0GB (63%) mapped to the human genome. In comparing RPKM values between TNBC and Normal, we report 7140 RefSeq Genes, 22 pre-miRNAs, 109 lincRNA exons, and 15 ultraconserved regions that were differentially expressed between these tissues (FDR&amp;lt;0.01). Biological interpretation of these results reveals upregulation of genes and miRNAs involved in DNA repair, angiogenesis, and inhibitors of Estrogen Receptor-alpha. Some previous drug targets (e.g. EGFR and c-kit) were not found to be upregulated here which may explain lack of clinical success to date. Conversely, PARP was significantly upregulated and early trial results suggest a strong signal for efficacy with inhibition of PARP. We also surveyed the genome for Novel Transcribed Regions (NTRs), defined as areas of significant transcription where no annotated gene is present. When comparing between TNBC and Normal, we report 6408 NTRs to be differentially expressed (FDR&amp;lt;0.01). Lastly, when analyzing the dataset for gene fusions, we identified several gene fusions in the TNBC samples, though no individual fusion was present in more than one sample. Conclusion: We report an extensive comparison of the transcriptomes of TNBC and normal ductal epithelium. We identified numerous genes previously unknown to be dysregulated in TNBC that can be utilized for therapeutic discovery. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD01-08.