Christine Henzler

Truncation and constitutive activation of the androgen receptor by diverse genomic rearrangements in prostate cancer

Molecularly targeted therapies for advanced prostate cancer include castration modalities that suppress ligand-dependent transcriptional activity of the androgen receptor (AR). However, persistent AR signalling undermines therapeutic efficacy and promotes progression to lethal castration-resistant prostate cancer (CRPC), even when patients are treated with potent second-generation AR-targeted therapies abiraterone and enzalutamide. Here we define diverse AR genomic structural rearrangements (AR-GSRs) as a class of molecular alterations occurring in one third of CRPC-stage tumours. AR-GSRs occur in the context of copy-neutral and amplified AR and display heterogeneity in breakpoint location, rearrangement class and sub-clonal enrichment in tumours within and between patients. Despite this heterogeneity, one common outcome in tumours with high sub-clonal enrichment of AR-GSRs is outlier expression of diverse AR variant species lacking the ligand-binding domain and possessing ligand-independent transcriptional activity. Collectively, these findings reveal AR-GSRs as important drivers of persistent AR signalling in CRPC.

Cerebellar Transcriptome Profiles of ATXN1 Transgenic Mice Reveal SCA1 Disease Progression and Protection Pathways

SCA1, a fatal neurodegenerative disorder, is caused by a CAG expansion encoding a polyglutamine stretch in the protein ATXN1. We used RNA sequencing to profile cerebellar gene expression in Pcp2-ATXN1[82Q] mice with ataxia and progressive pathology and Pcp2-ATXN1[30Q]D776 animals having ataxia in absence of Purkinje cell progressive pathology. Weighted Gene Coexpression Network Analysis of the cerebellar expression data revealed two gene networks that significantly correlated with disease and have an expression profile correlating with disease progression in ATXN1[82Q] Purkinje cells. The Magenta Module provides a signature of suppressed transcriptional programs reflecting disease progression in Purkinje cells, while the Lt Yellow Module reflects transcriptional programs activated in response to disease in Purkinje cells as well as other cerebellar cell types. Furthermore, we found that upregulation of cholecystokinin (Cck) and subsequent interaction with the Cck1 receptor likely underlies the lack of progressive Purkinje cell pathology in Pcp2-ATXN1[30Q]D776 mice.

Lineage-Specific Effector Signatures of Invariant NKT Cells Are Shared amongst γδ T, Innate Lymphoid, and Th Cells

Invariant NKT cells differentiate into three predominant effector lineages in the steady state. To understand these lineages, we sorted undifferentiated invariant NK T progenitor cells and each effector population and analyzed their transcriptional profiles by RNAseq. Bioinformatic comparisons were made to effector subsets among other lymphocytes, specifically Th cells, innate lymphoid cells (ILC), and γδ T cells. Myc-associated signature genes were enriched in NKT progenitors, like in other hematopoietic progenitors. Only NKT1 cells, but not NKT2 and NKT17 cells, had transcriptome similarity to NK cells and were also similar to other IFN-γ–producing lineages such as Th1, ILC1, and intraepithelial γδ T cells. NKT2 and NKT17 cells were similar to their analogous subsets of γδ T cells and ILCs, but surprisingly, not to Th2 and Th17 cells. We identified a set of genes common to each effector lineage regardless of Ag receptor specificity, suggesting the use of conserved regulatory cores for effector function.

Androgen Receptor Variant AR-V9 Is Coexpressed with AR-V7 in Prostate Cancer Metastases and Predicts Abiraterone Resistance

Purpose: Androgen receptor (AR) variant AR-V7 is a ligand-independent transcription factor that promotes prostate cancer resistance to AR-targeted therapies. Accordingly, efforts are under way to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC). The purpose of this study was to understand whether other AR variants may be coexpressed with AR-V7 and promote resistance to AR-targeted therapies. Experimental Design: We utilized complementary short- and long-read sequencing of intact AR mRNA isoforms to characterize AR expression in CRPC models. Coexpression of AR-V7 and AR-V9 mRNA in CRPC metastases and circulating tumor cells was assessed by RNA-seq and RT-PCR, respectively. Expression of AR-V9 protein in CRPC models was evaluated with polyclonal antisera. Multivariate analysis was performed to test whether AR variant mRNA expression in metastatic tissues was associated with a 12-week progression-free survival endpoint in a prospective clinical trial of 78 CRPC-stage patients initiating therapy with the androgen synthesis inhibitor, abiraterone acetate. Results: AR-V9 was frequently coexpressed with AR-V7. Both AR variant species were found to share a common 3′ terminal cryptic exon, which rendered AR-V9 susceptible to experimental manipulations that were previously thought to target AR-V7 uniquely. AR-V9 promoted ligand-independent growth of prostate cancer cells. High AR-V9 mRNA expression in CRPC metastases was predictive of primary resistance to abiraterone acetate (HR = 4.0; 95% confidence interval, 1.31–12.2; P = 0.02). Conclusions: AR-V9 may be an important component of therapeutic resistance in CRPC. Clin Cancer Res; 23(16); 4704–15. ©2017 AACR.

ScanIndel: a hybrid framework for indel detection via gapped alignment, split reads and de novo assembly

Comprehensive identification of insertions/deletions (indels) across the full size spectrum from second generation sequencing is challenging due to the relatively short read length inherent in the technology. Different indel calling methods exist but are limited in detection to specific sizes with varying accuracy and resolution. We present ScanIndel, an integrated framework for detecting indels with multiple heuristics including gapped alignment, split reads and de novo assembly. Using simulation data, we demonstrate ScanIndel’s superior sensitivity and specificity relative to several state-of-the-art indel callers across various coverage levels and indel sizes. ScanIndel yields higher predictive accuracy with lower computational cost compared with existing tools for both targeted resequencing data from tumor specimens and high coverage whole-genome sequencing data from the human NIST standard NA12878. Thus, we anticipate ScanIndel will improve indel analysis in both clinical and research settings. ScanIndel is implemented in Python, and is freely available for academic use at https://github.com/cauyrd/ScanIndel.

Preclinical evaluation of cyclin dependent kinase 11 and casein kinase 2 survival kinases as RNA interference targets for triple negative breast cancer therapy

IntroductionTargeted therapies for aggressive breast cancers like triple negative breast cancer (TNBC) are needed. The use of small interfering RNAs (siRNAs) to disable expression of survival genes provides a tool for killing these cancer cells. Cyclin dependent kinase 11 (CDK11) is a survival protein kinase that regulates RNA transcription, splicing and mitosis. Casein kinase 2 (CK2) is a survival protein kinase that suppresses cancer cell death. Eliminating the expression of these genes has potential therapeutic utility for breast cancer.MethodsExpression levels of CDK11 and CK2 mRNAs and associated proteins were examined in breast cancer cell lines and tissue arrays. RNA expression levels of CDC2L1, CDC2L2, CCNL1, CCNL2, CSNK2A1, CSNK2A2, and CSNK2B genes in breast cancer subtypes were analyzed. Effects following transfection of siRNAs against CDK11 and CK2 in cultured cells were examined by viability and clonal survival assays and by RNA and protein measures. Uptake of tenfibgen (TBG) nanocapsules by TNBC cells was analyzed by fluorescence-activated cell sorting. TBG nanocapsules delivered siRNAs targeting CDK11 or CK2 in mice carrying TNBC xenograft tumors. Transcript cleavage and response parameters were evaluated.ResultsWe found strong CDK11 and CK2 mRNA and protein expression in most human breast cancer cells. Immunohistochemical analysis of TNBC patient tissues showed 100% of tumors stained positive for CDK11 with high nuclear intensity compared to normal tissue. The Cancer Genome Atlas analysis comparing basal to other breast cancer subtypes and to normal breast revealed statistically significant differences. Down-regulation of CDK11 and/or CK2 in breast cancer cells caused significant loss of cell viability and clonal survival, reduced relevant mRNA and protein expression, and induced cell death changes. TBG nanocapsules were taken up by TNBC cells both in culture and in xenograft tumors. Treatment with TBG- siRNA to CDK11 or TBG- siRNA to CK2αα’ nanocapsules induced appropriate cleavage of CDK11 and CK2α transcripts in TNBC tumors, and caused MDA-MB-231 tumor reduction, loss of proliferation, and decreased expression of targeted genes.ConclusionsCDK11 and CK2 expression are individually essential for breast cancer cell survival, including TNBC. These genes serve as promising new targets for therapeutic development in breast cancer.

Staged miRNA re-regulation patterns during reprogramming

BackgroundMiRNAs often operate in feedback loops with transcription factors and represent a key mechanism for fine-tuning gene expression. In transcription factor-induced reprogramming, miRNAs play a critical role; however, detailed analyses of miRNA expression changes during reprogramming at the level of deep sequencing have not been previously reported.ResultsWe use four factor reprogramming to induce pluripotent stem cells from mouse fibroblasts and isolate FACS-sorted Thy1- and SSEA1+ intermediates and Oct4-GFP+ induced pluripotent stem cells (iPSCs). Small RNAs from these cells, and two partial-iPSC lines, another iPSC line, and mouse embryonic stem cells (mES cells) were deep sequenced. A comprehensive resetting of the miRNA profile occurs during reprogramming; however, analysis of miRNA co-expression patterns yields only a few patterns of change. Dlk1-Dio3 region miRNAs dominate the large pool of miRNAs experiencing small but significant fold changes early in reprogramming. Overexpression of Dlk1-Dio3 miRNAs early in reprogramming reduces reprogramming efficiency, suggesting the observed downregulation of these miRNAs may contribute to reprogramming. As reprogramming progresses, fewer miRNAs show changes in expression, but those changes are generally of greater magnitude.ConclusionsThe broad resetting of the miRNA profile during reprogramming that we observe is due to small changes in gene expression in many miRNAs early in the process, and large changes in only a few miRNAs late in reprogramming. This corresponds with a previously observed transition from a stochastic to a more deterministic signal.

Antagonism of B cell enhancer networks by STAT5 drives leukemia and poor patient survival

The transcription factor STAT5 has a critical role in B cell acute lymphoblastic leukemia (B-ALL). How STAT5 mediates this effect is unclear. Here we found that activation of STAT5 worked together with defects in signaling components of the precursor to the B cell antigen receptor (pre-BCR), including defects in BLNK, BTK, PKCβ, NF-κB1 and IKAROS, to initiate B-ALL. STAT5 antagonized the transcription factors NF-κB and IKAROS by opposing regulation of shared target genes. Super-enhancers showed enrichment for STAT5 binding and were associated with an opposing network of transcription factors, including PAX5, EBF1, PU.1, IRF4 and IKAROS. Patients with a high ratio of active STAT5 to NF-κB or IKAROS had more-aggressive disease. Our studies indicate that an imbalance of two opposing transcriptional programs drives B-ALL and suggest that restoring the balance of these pathways might inhibit B-ALL.

CNV-RF Is a Random Forest–Based Copy Number Variation Detection Method Using Next-Generation Sequencing

Simultaneous detection of small copy number variations (CNVs) (<0.5 kb) and single-nucleotide variants in clinically significant genes is of great interest for clinical laboratories. The analytical variability in next-generation sequencing (NGS) and artifacts in coverage data because of issues with mappability along with lack of robust bioinformatics tools for CNV detection have limited the utility of targeted NGS data to identify CNVs. We describe the development and implementation of a bioinformatics algorithm, copy number variation-random forest (CNV-RF), that incorporates a machine learning component to identify CNVs from targeted NGS data. Using CNV-RF, we identified 12 of 13 deletions in samples with known CNVs, two cases with duplications, and identified novel deletions in 22 additional cases. Furthermore, no CNVs were identified among 60 genes in 14 cases with normal copy number and no CNVs were identified in another 104 patients with clinical suspicion of CNVs. All positive deletions and duplications were confirmed using a quantitative PCR method. CNV-RF also detected heterozygous deletions and duplications with a specificity of 50% across 4813 genes. The ability of CNV-RF to detect clinically relevant CNVs with a high degree of sensitivity along with confirmation using a low-cost quantitative PCR method provides a framework for providing comprehensive NGS-based CNV/single-nucleotide variant detection in a clinical molecular diagnostics laboratory.

Targeting a single alternative polyadenylation site coordinately blocks expression of androgen receptor mRNA splice variants in prostate cancer

Prostate cancer is the second leading cause of male cancer deaths due to disease progression to castration-resistant prostate cancer (CRPC). Androgen receptor (AR) splice variants including AR-V7 function as constitutively active transcription factors in CRPC cells, thereby promoting resistance to AR-targeted therapies. To date, there are no AR variant-specific treatments for CRPC. Here we report that the splicing of AR variants AR-V7 as well as AR-V1 and AR-V9 is regulated coordinately by a single polyadenylation signal in AR intron 3. Blocking this signal with morpholino technology or silencing of the polyadenylation factor CPSF1 caused a splice switch that inhibited expression of AR variants and blocked androgen-independent growth of CRPC cells. Our findings support the development of new therapies targeting the polyadenylation signal in AR intron 3 as a strategy to prevent expression of a broad array of AR variants in CRPC. Cancer Res; 77(19); 5228-35. ©2017 AACR.