Breast Cancer Patient Prognosis Is Determined By The Interplay Between Tp53 Mutation And Alternative Transcript Expression: Insights From Tp53 Long Amplicon Digital Pcr Assays

Simple SummaryThe TP53 gene, the most commonly mutated gene in human cancers, is capable of producing multiple RNAs (transcripts). The aim of our study was to measure the abundance of each TP53 transcript, combined with TP53 gene mutation information, to determine the interplay between these in a cohort of breast tumors from New Zealand patients. To do this, we devised a new assay which then enabled the measurement of all known TP53 transcripts. We showed how TP53 gene mutations influenced the levels of specific TP53 transcripts in breast tumors. We evaluated whether a combination of TP53 tumor information, including TP53 mutation status and the levels of certain TP53 transcripts, with standard clinical and pathological information, was associated with breast cancer patient outcome. We recommend that a truly comprehensive analysis of TP53 needs to incorporate data about both TP53 DNA mutations and the expression of the alternative TP53 transcripts.The TP53 gene locus is capable of producing multiple RNA transcripts encoding the different p53 protein isoforms. We recently described multiplex long amplicon droplet digital PCR (ddPCR) assays to quantify seven of eight TP53 reference transcripts in human tumors. Here, we describe a new long amplicon ddPCR assay to quantify expression of the eighth TP53 reference transcript encoding increment 40p53 alpha. We then applied these assays, alongside DNA sequencing of the TP53 gene locus, to tumors from a cohort of New Zealand (NZ) breast cancer patients. We found a high prevalence of mutations at TP53 splice sites in the NZ breast cancer cohort. Mutations at TP53 intron 4 splice sites were associated with overexpression of increment 133TP53 transcripts. Cox proportional hazards survival analysis showed that interplay between TP53 mutation status and expression of TP53 transcript variants was significantly associated with patient outcome, over and above standard clinical and pathological information. In particular, patients with no TP53 mutation and a low ratio of TP53 transcripts t2 to t1, which derive from alternative intron 1 acceptor splice sites, had a remarkably good outcome. We suggest that this type of analysis, integrating mutation and transcript expression, provides a step-change in our understanding of TP53 in cancer.