TSPYL Family Regulates CYP17A1 and CYP3A4 Expression: Potential Mechanism Contributing to Abiraterone Response in Metastatic Castration‐Resistant Prostate Cancer
The testis‐specific Y‐encoded‐like protein (TSPYL) gene family includes TSPYL1 to TSPYL6. We previously reported that TSPYL5 regulates cytochrome P450 (CYP) 19A1 expression. Here we show that TSPYLs, especially TSPYL 1, 2, and 4, can regulate the expression of many CYP genes, including CYP17A1, a key enzyme in androgen biosynthesis, and CYP3A4, an enzyme that catalyzes the metabolism of abiraterone, a CYP17 inhibitor. Furthermore, a common TSPYL1 single nucleotide polymorphism (SNP), rs3828743 (G/A) (Pro62Ser), abolishes TSPYL1's ability to suppress CYP3A4 expression, resulting in reduced abiraterone concentrations and increased cell proliferation. Data from a prospective clinical trial of 87 metastatic castration‐resistant prostate cancer patients treated with abiraterone acetate/prednisone showed that the variant SNP genotype (A) was significantly associated with worse response and progression‐free survival. In summary, TSPYL genes are novel CYP gene transcription regulators, and genetic alteration within these genes significantly influences response to drug therapy through transcriptional regulation of CYP450 genes.
Fructose-1,6-bisphosphatase Inhibits ERK Activation and Bypasses Gemcitabine Resistance in Pancreatic Cancer by Blocking IQGAP1–MAPK Interaction
Abstract Motivation: RNA-seq has been widely used to study the transcriptome. Comparing to microarray, sequencing-based RNA-seq is able to identify splicing variants and single nucleotide variants in one experiment simultaneously. This provides unique opportunity to detect variants that associated with aberrant splicing. Despite the popularity of RNA-seq, no bioinformatics tool has been developed to leverage this advantage to identify variants associated with aberrant splicing. Results: We have developed PVAAS, a tool to identify single nucleotide variants that associated with aberrant alternative splicing from RNA-seq data. PVAAS works in three steps: (i) identify aberrant splicings; (ii) use user-provided variants or perform variant calling; (iii) assess the significance of association between variants and aberrant splicing events. Availability and implementation: PVAAS is written in Python and C. Source code and a comprehensive user’s manual are freely available at: http://pvaas.sourceforge.net/. Contact: wang.liguo@mayo.edu or kocher.jeanpierre@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.
The Cistrome and Gene Signature of Androgen Receptor Splice Variants in Castration Resistant Prostate Cancer Cells