{'fraction_non_alphanumeric': 0.02207727044656297, 'fraction_numerical': 0.004515805318615153, 'mean_word_length': 5.310126582278481, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Probing the Effects of Androgen and Glucocorticoid Receptor Sequences on DNA Binding Preferences

Prostate cancer is the second leading cause of cancer among men and although survival rates are high for regional tumors, it is estimated that almost 30,000 men will succumb to their diagnosis in 2018. Androgen hormones fuel prostate tumor growth by signaling through the androgen receptor (AR), a member of the nuclear receptor superfamily of transcription factors. Blocking androgen signaling through administration of antagonists (e.g bicalutamide, enzalutamide) or halting production of androgens through chemical or surgical castration arrests progression of the disease. Patients often relapse with castration resistant prostate cancer (CRPC) that continues to grow despite the lack of androgens. One mechanism of resistance is due to upregulation of a related nuclear receptor, the glucocorticoid receptor (GR). Because AR and GR have overlapping DNA binding specificities, GR is able to functionally substitute for AR at key disease genes. We have shown previously, using SELEX (Selective Evolution of Ligands by Exponential Enrichment) coupled with a novel computational algorithm (SelexGLM), that although AR and GR bind similar sequences, they recognize DNA differently. GR is less specific than AR, allowing it to accommodate predominantly AR sequences. To better understand the selectivity of AR and GR, and to identify the determinants of their specificity, we are measuring the sequence preference of AR and GR mutants using the No Read Left Behind (NRLB) method. As opposed to traditional SELEX, NRLB yields high resolution models of specificity with a single round of selection, which allows rapid screening of our mutants. We have over‐expressed and purified both the AR and GR DNA binding domains, and have designed hybrid mutants. Comparison of the DNA binding preferences of AR, GR and the hybrid molecules by NRLB should help uncover how GR might be playing a role in CRPC.