Next-Generation Whole Transcriptome Sequencing of Triple-Negative Breast Tumors and Normal Tissues.
Authors: Radovich M. , Clare S. , Clare S. , Pardo I. , Hancock B. , Sledge G. , Rufenbarger C. , Rufenbarger C. , Storniolo A. , Storniolo A. , Mathieson T. , Mathieson T. , Sun J. , Sun J. , Henry J. , Henry J. , Hilligoss E. , Elliott J. , Richt R. , Hickenbotham M. , Glasscock J. , Liu Y. , Schneider B. 
Published: December 2010

Background: Triple-negative breast cancer predominately affects pre-menopausal women and women of African-American descent and has been plagued by the absence of targeted therapies leading to poor survival. Using a new cutting edge technology, next-generation sequencing, we embarked on a study to analyze the whole transcriptomes of triple-negative tumors and normal tissues from pre-menopausal women in order to comprehensively identify new targets by analyzing all full length transcripts expressed in these tissues. This approach is independent of pre-determined gene selection as is common with microarrays, and allows for the analysis of RNA species that have not been previously profiled in breast cancer.Methods: cDNA libraries were created from RNA isolated from 8 triple-negative tumors and 2 normal breast tissues. Triple negative tumors were procured from Origene Technologies and normal breast tissues were procured from the Susan G. Komen for the Cure tissue bank at Indiana University. Normal samples were from healthy pre-menopausal volunteers with no history of disease. In order to eliminate bias from stromal tissue, normal samples were laser capture microdissected for ductal cells and RNA extracted from the excised tissue. cDNA libraries were prepared and subsequently sequenced on an Applied Biosystems (ABI) SOLiD3 sequencer using a 50bp fragment run. Mapping of whole reads to the human genome was performed using the SOLiD Analysis Pipeline Tool software (ABI) followed by a split-read alignment in order to map reads crossing exon-exon junctions. Gene expression profiles for each sample were then created and statistically compared to identify the most differentially expressed genes. In order to analyze for fusion genes, a split-read alignment of non-mapping reads to a composite transcriptome formed from previously mapped reads (clusters) was performed.Results: Sequencing of the 10 samples produced 513 million filtered reads equaling 25.66GB of data. Mapping of the reads to the genome revealed 1.14 million transcribed regions (exons). A preliminary analysis of gene expression shows 55.2% of the transcribed loci to have significant differential expression between tumor and normal. In a further analysis for gene fusions, several candidate fusions were bioinformatically detected. These are currently being reviewed and validated.Discussion: Herein we present a preliminary analysis of the transcriptomes of triple-negative breast cancers in comparison to normal tissues. A multitude of analyses are ongoing, including but not limited to: gene fusions, differentially expressed novel genes, novel transcripts, alternative splicing, intrinsic subtyping, and presence of viral genes. In addition 2 more triple-negative tumors and 8 normal samples will also be sequenced. In the current analysis, differentially expressed non-coding RNAs was highly pervasive among the samples indicating a major role of this RNA species in tumorigenesis. In addition, triple-negative breast cancers may contain fusion genes that could be “drivers” of this malignancy. Further validation of these differentially expressed RNAs and fusion genes in a larger set of samples with subsequent functional studies is planned.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6134.