Abstract 4971: Transcriptome analysis and the identification of novel somatic mutations in breast cancer by the next-generation sequencing

Abstract

Abstract Background: Breast cancer is the most common cancer among women in the United States and the second most common cause of cancer mortality in this population. Despite extensive research, the complexity of this disease has caused it to elude simple approaches to prevention and treatment. Breast cancer is a collection of heterogeneous tumor types that exhibit distinct histopathological features. This has clinical implications since these breast cancer types often correlate with patient outcomes such as prognosis, response to treatment, and survival. In this study, we present a comprehensive characterization of transcriptomes for breast tumors and their adjacent normal tissues using the next-generation sequencing (NGS) technology. Material and Methods: We analyzed 8 samples: 4 primary breast tumors (2 triple negatives; 2 HER2 positive and ER/PR negative) and 4 matched normal tissues. Poly-A mRNA was isolated and sequenced using Illumina GAII. We obtained about 140 millions of 76 bp pair-end reads for each sample. The sequences were mapped to the hg18 reference sequences with BWA, and the mapping efficiency of our data was around 90%. Validation of mutations was performed using the traditional ABI sequencing. Results and Discussion: We compared gene expression difference between tumor and its matched adjacent normal tissue and found that a large number of genes showed significant changes in expression level (FDR=0.1), including more than 10,000 down-regulated genes and around 4,000 up-regulated genes. Examples of down-regulated genes include GNAS, TP73L, and KRT14 whereas up-regulated genes include TOP2A, MMP9, and FOXM1. Nucleotide-resolution of the NGS data made it possible to identify changes in specific isoforms for each gene. As an example, GNAS is a complex locus, containing 7 Refseq transcripts, 3 of which are subject to genomic imprinting regulation (one expressed from the maternal chromosome and two from the paternal chromosome) and the other 4 transcripts are normally expressed from both chromosomes; down-regulation of GNAS affected only the maternally expressed imprinted transcript whereas bi-allelic transcripts were expressed at high-level in both tumors and normal tissues. Furthermore, the NGS data also enabled us to identify somatic mutations. We uncovered 28 sequence variants that changed coding sequences and were mutated specifically in tumors. We were able to design PCR primers for 22 variants for analysis by the use of traditional ABI sequencing. We validated 14 out of 22 mutations, one of which is a known mutation, G1049R, in the PIK3CA gene and the other 13 are novel mutations, including mutations in ARID1B and VIM. In conclusion, our NGS analysis of breast cancer transcriptomes has generated new insights into both transcription regulation and genetic alterations, and these new insights may be explored for better diagnosis and treatment of breast cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4971. doi:10.1158/1538-7445.AM2011-4971