Novel Insights into Breast Cancer Genetic Variance through RNA Sequencing

Breast cancer is the third most frequent cancer in the world as it affects approximately one in ten women in the western world1. The initial knowledge that connected breast cancer to genetic susceptibility originated from the clinical observations that highlighted the clustering of breast cancer cases in families2,3. Approximately 5–10% of breast cancers are believed to result from the inheritance of rare genetic components that confer significantly elevated risk4,5. For example, mutations in the tumor suppressor genes BRCA1 and BRCA2 account for approximately 16% of the familial breast cancer6,7,8. The vast majority of breast cancer cases, however, are derived from a complex interaction between multiple environmental, lifestyle and genetic factors with relatively weak individual risk contribution9,10. While the effects of many environmental and lifestyle factors, such as diet, reproductive behavior and radiation are well appreciated, the knowledge on genetically contributing patterns is limited. Association studies have identified ATM, BRIP1, CASP8, CDH1, CHEK2, PALB2, PTEN, STK11, and TP53 as breast cancer susceptibility genes. Such mutations collectively account for 2.3% of familial risk of breast cancer, and together with BRCA1, BRCA2 and others have been implicated in high risk screening strategies5,8,11,12,13,14,15,16,17,18,19,20. Nonetheless, significant proportion of the familial and non-familial breast cancer susceptibility remains unknown, suggesting plethora of genetic elements that need to be understood. Transcriptome sequencing comprises a unique interplay between individual genetic background, reflected in the variation content, and the epigenetic and environmental regulation affecting gene expression levels and splice patterns. Recent transcriptome sequencing efforts have highlighted important somatic events in metastatic triple negative breast cancer (TNBC) and described important for the clinical outcome genotype-phenotype correlations21. Further, transcriptome sequencing data have been successfully explored to reveal disrupted pathways in TNBC through genome-wide loss of heterozygosity and mono-allelic expression estimation22. As a result of these and other studies, the feasibility of transcriptome sequencing to uncover molecular mechanisms of breast cancer drivers is increasingly appreciated23. Here we used whole transcriptome RNA-sequencing to reveal the variation signatures of 17 breast cancer patient tissues, and compared with human normal breast organoids (referred from here on as normal breast tissue, NBT). The 17 samples include six TNBC, lacking expression of therapeutically significant components - estrogen receptor (ER), progesterone-receptor (PR) and the Human Epidermal Growth Factor Receptor 2 (HER2); six Non-TNBC (ER, PR and HER2-positive); and five HER2-positive samples (ER and PR negative). Compared to the extensively performed searches for somatic breast cancer mutations, our RNA-sequencing based approach detects SNPs that are expressed at the mRNA level, and allows estimation of their allelic expression at nucleotide resolution. A set of novel variants were validated through Sanger sequencing. As a proof-of-principle, we have explored the effect of a rare SNP- p.R353Q - in the epithelial splicing regulatory protein ESRP2, on the binding and splicing of its target pre-mRNA. Our study reports a set of novel mutations in essential regulatory molecules in breast cancer and discusses their allelic preferential expression and potential involvement in breast cancer.