The expression of androgen receptor (AR) variants is a frequent, yet poorly-understood mechanism of clinical resistance to AR-targeted therapy for castration-resistant prostate cancer (CRPC). Among the multiple AR variants expressed in CRPC, AR-V7 is considered the most clinically-relevant AR variant due to broad expression in CRPC, correlations of AR-V7 expression with clinical resistance, and growth inhibition when AR-V7 is knocked down in CRPC models. Therefore, efforts are under way to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC). The aim of this study was to understand whether other AR variants are co-expressed with AR-V7 and promote resistance to AR-targeted therapies. To test this, we utilized RNA-seq to characterize AR expression in CRPC models. RNA-seq revealed the frequent coexpression of AR-V9 and AR-V7 in multiple CRPC models and metastases. Furthermore, long-read single-molecule real-time (SMRT) sequencing of AR isoforms revealed that AR-V7 and AR-V9 shared a common 3’terminal cryptic exon. To test this, we knocked down AR-V7 in prostate cancer cell lines and confirmed that AR-V9 mRNA and protein expression were also impacted. In reporter assays with AR-responsive promoters, AR-V9 functioned as a constitutive activator of androgen/AR signaling. Similarly, infection of AR-V9 lentiviral construct in LNCaP cells induced androgen-independent cell proliferation. In conclusion, these data implicate co-expression of AR-V9 with AR-V7 as an important component of constitutive AR signaling and therapeutic resistance in CRPC.
Activating mutations in PIK3CA are frequent in human breast cancer, and phosphoinositide 3-kinase alpha (PI3Ka) inhibitors have been approved for therapy. To characterize determinants of sensitivity to these agents, we analyzed PIK3CA-mutant cancer genomes and observed the presence of multiple PIK3CA mutations in 12 to 15% of breast cancers and other tumor types, most of which (95%) are double mutations. Double PIK3CA mutations are in cis on the same allele and result in increased PI3K activity, enhanced downstream signaling, increased cell proliferation, and tumor growth. The biochemical mechanisms of dual mutations include increased disruption of p110a binding to the inhibitory subunit p85a, which relieves its catalytic inhibition, and increased p110a membrane lipid binding. Double PIK3CA mutations predict increased sensitivity to PI3Ka inhibitors compared with single-hotspot mutations.Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Hybrid sequencing-based personal full-length transcriptomic analysis implicates proteostatic stress in metastatic ovarian cancer.
Comprehensive molecular characterization of myriad somatic alterations and aberrant gene expressions at personal level is key to precision cancer therapy, yet limited by current short-read sequencing technology, individualized catalog of complete genomic and transcriptomic features is thus far elusive. Here, we integrated second- and third-generation sequencing platforms to generate a multidimensional dataset on a patient affected by metastatic epithelial ovarian cancer. Whole-genome and hybrid transcriptome dissection captured global genetic and transcriptional variants at previously unparalleled resolution. Particularly, single-molecule mRNA sequencing identified a vast array of unannotated transcripts, novel long noncoding RNAs and gene chimeras, permitting accurate determination of transcription start, splice, polyadenylation and fusion sites. Phylogenetic and enrichment inference of isoform-level measurements implicated early functional divergence and cytosolic proteostatic stress in shaping ovarian tumorigenesis. A complementary imaging-based high-throughput drug screen was performed and subsequently validated, which consistently pinpointed proteasome inhibitors as an effective therapeutic regime by inducing protein aggregates in ovarian cancer cells. Therefore, our study suggests that clinical application of the emerging long-read full-length analysis for improving molecular diagnostics is feasible and informative. An in-depth understanding of the tumor transcriptome complexity allowed by leveraging the hybrid sequencing approach lays the basis to reveal novel and valid therapeutic vulnerabilities in advanced ovarian malignancies.