AKT1E17K mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Rudolph, Marion; Anzeneder, Tobias; Schulz, Anke; Beckmann, Georg; Byrne, Annette; Jeffers, Michael; Pena, Carol; Politz, Oliver; Köchert, Karl; Vonk, Richardus; Reischl, Joachim
• Is Part Of: BMC cancer. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: Breast cancer -- AKT1E17K mutation -- Blood-based mutation detection; Cancer -- Periodicals; 616.994005
• DOI: 10.1186/s12885-016-2626-1
• Languages: English
• ISSNs: 1471-2407

Abstract

Abstract Background The single hotspot mutationAKT1 [G49A:E17K] has been described in several cancers, with the highest incidence observed in breast cancer. However, its precise role in disease etiology remains unknown. Methods We analyzed more than 600 breast cancer tumor samples and circulating tumor DNA forAKT1 E17K and alterations in other cancer-associated genes using Beads, Emulsions, Amplification, and Magnetics digital polymerase chain reaction technology and targeted exome sequencing. Results OverallAKT1 E17K mutation prevalence was 6.3 % and not correlated with age or menopausal stage.AKT1 E17K mutation frequency tended to be lower in patients with grade 3 disease (1.9 %) compared with those with grade 1 (11.1 %) or grade 2 (6 %) disease. In two cohorts of patients with advanced metastatic disease, 98.0 % (n = 50) and 97.1 % (n = 35) concordance was obtained between tissue and blood samples for theAKT1 E17K mutation, and mutation capture rates of 66.7 % (2/3) and 85.7 % (6/7) in blood versus tissue samples were observed. AlthoughAKT1 -mutant tumor specimens were often found to harbor concurrent alterations in other driver genes, a subset of specimens harboringAKT1 E17K as the only known driver alteration was also identified. Initial follow-up survival data suggest thatAKT1 E17K could be associated with increased mortality. These findings warrant additional long-term follow-up. Conclusions The data suggest thatAKT1 E17K is the most likely disease driver in certain breast cancer patients. Blood-based mutation detection is achievable in advanced-stage disease. These findings underpin the need for a further enhanced-precision medicine paradigm in the treatment of breast cancer.