With the exception of skin cancers, breast cancer is the most common cancer affecting women. While progress has been made in the detection of primary breast tumours, determining how likely a tumour will be to metastasise is still very difficult. Understanding this “metastatic potential” is most important in the so called “triple negative breast cancers” (TNBCs) which lack the classical markers that are commonly targeted by hormonal therapies. Adjuvant chemotherapy is almost always given for triple negative tumours, often unnecessarily. Better markers of tumour metastatic potential are clearly required for both TNBC diagnosis and treatment.
Alternative polyadenylation (APA) is the process whereby the poly(A) tail is added to the 3’ untranslated region (3' UTR) of a messenger RNA (mRNA) at one of multiple possible sites, changing 3' UTR length and potentially the regulatory elements that bind to it. APA has been shown to be indicative of tumour state, but is often overlooked when conducting RNA-seq analysis, which focuses on gene expression. We are developing a method to cheaply and effectively quantify the expression state of a primary breast tumour based off Poly (A) Test sequencing (PAT-seq) data, which sequences 3' UTRs in a genome wide fashion. Using PAT-Seq and custom bioinformatic methods we have uncovered novel APA events that are associated with tumour induction and outcome in both our model and real human TNBCs. Our findings provide novel insight into tumour associated RNA metabolism and provide new methods for the prediction of TNBC outcome.