Androgen Receptor Regulates CD44 Expression in Bladder Cancer

Abstract

The androgen receptor (AR) is important in the development of both experimental and human bladder cancer. However, the role of AR in bladder cancer growth and progression is less clear, with literature indicating that more advanced stage and grade disease are associated with reduced AR expression. To determine the mechanisms underlying these relationships, we profiled AR-expressing human bladder cancer cells by AR chromatin immunoprecipitation sequencing and complementary transcriptomic approaches in response to in vitro stimulation by the synthetic androgen R1881. In vivo functional genomics consisting of pooled shRNA or pooled open reading frame libraries was employed to evaluate 97 genes that recapitulate the direction of expression associated with androgen stimulation. Interestingly, we identified CD44, the receptor for hyaluronic acid, a potent biomarker and driver of progressive disease in multiple tumor types, as significantly associated with androgen stimulation. CRISPR-based mutagenesis of androgen response elements associated with CD44 identified a novel silencer element leading to the direct transcriptional repression of CD44 expression. In human patients with bladder cancer, tumor AR and CD44 mRNA and protein expression were inversely correlated, suggesting a clinically relevant AR-CD44 axis. Collectively, our work describes a novel mechanism partly explaining the inverse relationship between AR and bladder cancer tumor progression and suggests that AR and CD44 expression may be useful for prognostication and therapeutic selection in primary bladder cancer. SIGNIFICANCE: This study describes novel AREs that suppress CD44 and an expected inverse correlation of AR-CD44 expression observed in human bladder tumors.

Figure 1:. Characterization of the AR regulon in bladder cancer.

UMUC3-c31 cells were stimulated with 10nM R1881 (n = 5) or vehicle control (n = 4) for 24 hours prior to analysis by ChIP-seq. Control peaks were background subtracted from five independent biological replicates performed. A) ChIP peaks from a representative biological replicate, minus background peaks, depicted across the human genome. B) Representation of ChIP peaks in association to the transcription start site of all genes. C) Graphical summary of ChIP-peak association with common promoter and genomic elements. D) Distribution of ChIP peaks in association with genes identified to be regulated by AR upon R1881 stimulation. E) Motif analysis showing bladder cancer specific AR binding motifs with the total number of sites shown. F) Gene Ontology (GO) pathway analysis of genes regulated by AR when stimulated by R1881 (FDR < 0.1). G) Representative description of ChIP peaks associated with the canonical AR target gene FKBP5 (NM_004117.4) accompanied by H3K4Me1, H3K4Me3, H3K27Ac, and DNaseI Signal.

Figure 2:. Characterization of the AR transcriptome in response to AR stimulation by R1881 in UMUC3-c31 cells.

Cells were stimulated with 10nM R1881 (n = 5), or ethanol vehicle control (n = 5), for 24 hours followed by RNA isolation and microarray analysis. A) Volcano plot depicting fold change (log₂) and statistical significance with red dots representing a significant difference (FDR < 0.05) between vehicle control and R1881 stimulated samples (n = 3/group). B) Unsupervised hierarchical clustering of the 250 genes found to be significantly (FDR < 0.05) differentially expressed. C) Gene Ontology (GO) analysis (FDR < 0.01) of the 250 genes identified.

Figure 3:. Description of 97 genes putatively regulated directly by AR in bladder cancer.

A) Genes identified in ChIP-seq and microarray were compared to define 97 genes putatively regulated directly by AR. B) Gene Ontology (GO) pathways were determined for the 97 gene overlap from the Venn diagram (FDR < 0.1). The GO pathways, in identical order, were analyzed across all the 3599 ChIP-seq specific genes and 250 microarray specific genes for comparison across modalities.

Figure 4:. Functional screening of 12 AR down-regulated gene candidates.

The 97 genes identified via ChIP-seq and transcriptomic approaches were screened using pooled ORF and shRNA libraries. A) Schematic showing experimental design of the ORF and shRNA screens. UMUC3-c31 cells were transduced with pooled libraries, selected, and injected into castrated or intact mice. B) Final tumor volume of mice (intact n = 6; castrated n = 4) challenged with the pooled AR-shRNA library show a significant inhibition in tumor volume associated with castration (p<0.05; two-tailed unpaired t-test). Tumors were resected and prepared for NGS using library specific methods. C) Volcano plot depicting shRNA constructs significantly varying between sham and castrated tumors. D) Filtering schema of shRNA constructs. Genes with multiple significant shRNA constructs with contradictory accumulation were removed from analysis. Genes not recapitulating the R1881 induced expression as measured by microarray were removed from analysis. E) Heatmap of filtered significant (FDR < 0.1) genes identified from the pooled screen. Genes with more than one shRNA construct were averaged for graph.

Figure 5:. CRISPR based functional evaluation of putative CD44 regulatory AREs.

A pooled CRISPR library targeting AREs associated with CD44 was developed to saturate all potential AREs. A) A schematic of the experimental methodology of targeting potential CD44-AREs with CRISPR. UMUC3-c31 cells were transduced with the library before being treated with vehicle control (ethanol) or 10nM of R1881 in CSS media. B) UMUC3-c31 cells were sorted by FACS 1, 3, and 5 days post treatment into CD44^low, CD44^int, and CD44^high groups and gDNA prepared for NGS of the gRNA. Volcano plots of CD44 population comparisons on Day 5 sorted samples shows a significant number of differential gRNAs present between the CD44^low (C) and CD44^high (D) populations. E) Three gRNAs found to have the most significant read count changes at Day 5 between populations with different CD44 expression.

Figure 6:. Validation of CD44 based AREs using single gRNA.

To verify that mutation of the putative ARE was effective, single gRNAs identified from the pooled screened were further validated. A) Schematic of the CD44 gene, ChIP-peaks, H3K4Me1, H3K4Me3, H3K27Ac, and DNAseI Signal (DNAse I Hypersensitivity) (e.g. active/open chromatin), and associated gRNAs used for further validation highlighted (red = CD44-006; blue = CD44-008; and purple = CD44-009). B) Alignment of CD44-006 and (C) alignment of CD44-008 UMUC3-clones showing mutated ARE located within introns. Black boxes show the CRISPR mediated insertion. The magenta box (B) shows the ‘AGAAC’ AR partial-motif broken by the CRISPR mediated insertion. The light blue box (C) shows the ‘ATTTC’ STAT3 motif broken by the CRISPR mediated insertion. D) qPCR validation of ARE disruption was validated by measuring EDN2 (positive control) and CD44 RNA expression (n = 4 per group). ChIP-PCR of the CD44-006 (E), CD44-008 (F), or a control ARE (G; FKBP5, control) are shown (n = 3–4 per group; 3 replicate experiments). ARE targeting significantly altered AR binding, but CRISPR based ARE modification did not alter a distant control site (G; FKBP5). H) Western blot of stable gRNA expressing UMUC3-c31 cells with densitometry of the resulting blot depicted as relative fold change in respect to vehicle control. Two-tailed unpaired t-test with p< 0.05 were used to assess D, E, F, and G. A one-sample t-test comparing each group to ‘1’ (no change in expression) with a p < 0.05 was used for (H).

Figure 7:. RNA and protein assessment of AR-CD44 associations in patients with bladder cancer.

A) RNA expression correlation between AR and CD44 from bladder cancer TCGA dataset via www.cBioPortal.org (n = 408 samples). B) Regression of pre and post-neoadjuvant chemotherapy of patients with invasive bladder cancer for AR and CD44 RNA expression (n = 115). C) Representative sections of AR and CD44 IHC stained from contiguous sections are presented. D) CD44 stain intensity was not statistically different (p > 0.05) between patients based on AR expression. E) Patient primary and metastatic tumors were evaluated for AR and CD44 staining. A significant (bar; p < 0.05) decrease in CD44 staining was observed in those patients with AR positive primary disease compared to those with AR negative disease. In contrast, no difference in CD44 intensity was observed in metastatic sections. F) CD44 staining intensity in patients with matched primary-metastatic tumors was evaluated based on AR status. Overall, CD44 increased (p > 0.05) in metastatic tumors independent of AR status in the primary or metastatic tumor.