Androgen receptor splice variant 7 (ARv7) detection from circulating tumor DNA

The levels of the Androgen receptor splice variant 7 (ARv7) are associated with prostate cancer progression and the transition to the incurable castrate-resistance state. Monitoring the levels of ARv7 in real-time for individual patients may guide therapeutic decisions for precision oncology and elucidate resistance mechanisms of castration-resistant prostate cancer. However, currently there is no direct way to measure the levels of ARv7 that is also considered as standard-of-care. Here, we suggest using the analysis of circulating tumor DNA (ctDNA) from blood biopsies to infer the levels of ARv7. We use publicly available gene expression data to identify differentially expressed genes between the AR full length (ARfl), and the ARv7, and their binding sites. We then use Griffin – a nucleosome profiling pipeline developed in our lab, to characterize the expression levels of the genes of interest and the ARfl an ARv7 activity as transcription factors. We then apply machine learning approach with the Griffin output to classify and quantify samples according to their ARv7 status. We will develop a similar classifier to predict the ARv7 status from ultra-low-pass genome sequencing of blood biopsies, which will pave the way for developing cost-effective tests for clinical use. This proposal encompasses the first attempt to directly measure ARv7 levels, in “real-time”, in individual patients, with immediate implications for informed therapeutic decision making. It can also serve as a proof of concept for additional assays to various types of cancer where differential splicing variant expression is correlated to patient’s outcomes.