A novel REST-regulated lncRNA PCAT-NE1 induces neuroendocrine differentiation in castration-resistant prostate cancer

doi:10.21203/rs.3.rs-1761199/v1

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A novel REST-regulated lncRNA PCAT-NE1 induces neuroendocrine differentiation in castration-resistant prostate cancer

https://doi.org/10.21203/rs.3.rs-1761199/v1

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Background Lineage plasticity is recognized as a treatment-induced resistance mechanism in prostate cancer (PCa) and contributes to the development of neuroendocrine prostate cancer (NEPC), a lethal variant of castration-resistant prostate cancer (CRPC), that is increasing in the era of second-generation anti-hormonal therapy. At present, there are no effective treatments for NEPC.

Conclusions and perspectives Following our long-standing interest in studying RE1-silencing transcription factor (REST), a pivotal repressor of neuroendocrine differentiation (NED), we conducted a siRNA screening targeting 147 REST-repressing long non-coding RNAs (lncRNAs) and identified prostate cancer transcript-neuroendocrine 1 (PCAT-NE1) as a novel lncRNA that induces NED through activating autophagy signaling, crucial for NED of prostate adenocarcinoma cell. Analyses of clinical data and samples indicate that PCAT-NE1 is elevated in NEPC. Through gain- and loss-of-function experiments, we find that PCAT-NE1 promotes NED. Mechanistically, PCAT-NE1 acts as a competing endogenous RNA (ceRNA) that sponge hsa-miR-6889-3p, leading to the up-regulation of autophagy-related gene VPS13A and autophagy activation. These findings provide new insight into lncRNA-mediated mechanism for autophagy activation in NEPC and suggest PCAT-NE1 as a potential diagnostic biomarker and therapeutic target for NEPC.

Prostate Cancer (PCa)

Neuroendocrine Prostate Cancer (NEPC)

long non-protein coding RNA (lncRNA)

competing endogenous RNA (ceRNA)

microRNA (miRNA)

Prostate cancer (PCa) is the second most frequent malignancy diagnosed and the fifth leading cause of cancer death in men worldwide [1]. Though androgen deprivation therapy (ADT) remains the gold standard for treating patients with PCa since 1941 [2], the disease often develops into castration-resistant PCa (CRPC), associated with restoration of androgen receptor (AR) signaling [3, 4]. The prevalence of CRPC drove the development of second-generation AR pathway inhibitors, such as the androgen biosynthesis inhibitor abiraterone and the AR antagonist enzalutamide [5]. Unfortunately, the response to these new generation therapies is only transient. In spite of improving overall survival of CRPC patients [6, 7], approximately 20% of the patients eventually relapse with progression to a more aggressive form of PCa with neuroendocrine (NE) features [8, 9]. Thus, the incidence of neuroendocrine prostate cancer (NEPC) has escalated and is observed in around one-fifth of CRPC cases after the wide use of second-generation AR-targeting therapy [10]. This subset of treatment-induced NEPC not only associates with resistance to AR-targeted therapy [8], but also results in increased tumor growth [11] and chemoresistance [12]. In this regard, there are currently no effective treatments for this disease. Patients diagnosed with NEPC have a median overall survival of less than a year [10, 13]. Identifying novel targets for biomarkers and therapeutics for NEPC is urgently needed.

Emerging evidence indicates REST, also known as neuron restrictive silencing factor (NRSF), is a master repressor for NED of PCa [8, 14–16]. REST was initially identified as a transcription repressor that plays a critical role in silencing neuronal genes in non-neuronal cells and in maintaining the pluripotency of neural precursor cells. It contains a DNA binding domain that recognizes the repressor element-1 (RE-1) site, a 21 nucleotide consensus sequence, and two repressor domains (RD). The N-terminal RD interacts with Sin3 complex, which contains Sin3A or Sin3B, histone deacetylases 1 (HDAC1) and/or HDAC2, whilst its C-terminal RD interacts with CoREST complex that contains lysine-specific demethylase 1 (LSD1), HDAC1, and MeCP2 [17]. Therefore, REST complex is well recognized as a transcriptional repressor that forms epigenetic remodeling complexes to silence target genes [17]. The loss of REST expression resulted in NED of PCa suggesting epigenetic regulation as a potential mechanism for the transdifferentiation process of NEPC [18, 19].

Long non-coding RNAs (lncRNAs) have emerged as novel epigenetic regulators [20] and oncogenes or tumor suppressors in cancer progression [21]. However, their role in regulating PCa NED is just in its infancy. LncRNAs are RNA transcripts longer than 200 nt and do not encode proteins [22]. These RNAs share many common features with mRNAs, such as (1) 5’-methylguanosine capping, (2) polyadenylation, (3) RNA polymerase II transcription, and (4) splicing [22], but are generally expressed at a lower level and display a higher tissue specificity [23]. They regulate biological functions through either serving as scaffolds to recruit chromatin-remodeling complexes or transcription factors to specific genomic loci [22, 24] or by acting as decoys that sequester miRNAs or DNA binding proteins [25]. Dysregulation of lncRNAs could provide an additional mechanism for NE transdifferentiation of PCa [26, 27]. In line with this, in 2016, Cre et al provided the first evidence for a NEPC-associated lncRNA with the identification of MIAT [28]. Our previous work also highlighted HOTAIR as a novel REST-regulated lncRNA participating in NED of PCa cells [29]. More recently, a report showed that the AR antagonist enzalutamide could promote LncRNA-p21 expression, which consequently induced NED in PCa [30]. These data suggest that lncRNAs can be exploited as novel biomarkers and therapeutic targets for NEPC.

Using combined transcriptome analysis and small interfering RNA (siRNA) knockdown screening approaches, we comprehensively surveyed the NED potential of 147 REST-targeted lncRNAs. We discovered a previously unrecognized role of long intergenic non-protein coding RNA 01801 (LINC01801) as a potential driver of NED. Following the classification style of prostate cancer associated transcript (PCAT) initiated by Prensner et al. in 2011 [31], we named LINC01801 as prostate cancer associated transcript-neuroendocrine 1 (PCAT-NE1). PCAT-NE1 expression was significantly increased in CRPC patients with NE features and in PCa cells after NED induction, highlighting its possible role in the development of NEPC. Mechanistically, PCAT-NE1 up-regulates the autophagy-related gene VPS13A by competitively binding hsa-miR-6889-3p and consequently induces autophagy pathway. Since autophagy activation has been known to evoke NED of PCa cells, targeting PCAT-NE1-hsa-miR-6889-3p-VPS13A axis may impede unwanted treatment-induced NED and consequently prevent CRPC relapse.

2.1 Cell culture and treatment

LNCaP, LNCaP-TR and LNCaP-TR-shREST were cultured as described previously [14]. For the generation of PCAT-NE1-inducible LNCaP cell line, PCAT-NE1 cDNA was synthesized by GeneArt (Thermo Fisher Scientific), cloned into the pLenti4-CMV/TO vector, and then transduced into LNCaP-TR cells by lentivirus, followed by selection with 200µg/ml zeocin (InvivoGen, ant-zn-1) for 2 weeks. LNCaP-TR-PCAT-NE1 cells were maintained as described for LNCaP-TR-shREST.

2.2 Gene-knockdown experiment

For siRNA screening, LNCaP cells were seeded at 5 x 10³ cells/well in 96-well plates and transfected with siRNAs from Lincode Set of 4 siRNA Library-Human NR lncRNA RefSeq v54-SMARTpool (Dharmacon, GU-301000) at a final concentration of 20nM using Lipofectamine RNAiMAX (Invitrogen, 13778-150) following the manufacturer’s protocol. The siGLO Green Transfection Indicator (Dharmacon, D-001630-01-20) was used as a negative control and to ensure the transfection efficiency. For siRNA-mediated knockdown of PCAT-NE1, the PCAT-NE1 siRNA oligonucleotide was purchased from Lincode siRNA Library (Dharmacon, 400685); the sequence was 5′-UGAGAAGGGUACCCAAACA-3′. For shRNA-mediated knockdown experiment, the plenti4-H1/TO-shBECN1 that we generated in our previous study [14] and the commercially available pLK0.1-shVPS13A vectors (Academia Sinica, RNAi Core, TRCN0000118770) were used to generate lentiviral particles for knockdown beclin-1 and VPS13A expression, respectively.

2.3 High-throughput RNA and small RNA sequencing (RNA-seq and smRNA-seq) and gene ontology (GO) data analysis.

Total cellular RNA was extracted from control and PCAT-NE1 knockdown LNCaP cells treated with/without 100ng/ml IL-6 in phenol red-free RPMI 1640 (Gibco) supplemented with 10% charcoal/dextran-treated FBS (CDT; HyClone, SH30068.03) and LNCaP-TR-PCAT-NE1 cells treated with/without doxycycline (Dox) (0.1µg/ml). RNA-seq was performed by Illumina HiSeq 2000 platform (Illumina, Inc., San Diego, CA, USA). The raw reads were aligned to human reference genome GRCh37/hg19 using CLC Genomics Workbench 11. Partek Genomics Suite v.7.0 (Partek, St. Louis, Missouri) was used to calculate transcript abundances. Transcriptome information was obtained from RefSeq Transcripts, NONCODE v4.0, and miRBase v21. To identify the biological functions, the differentially expressed mRNAs were subjected to disease and function analysis by Ingenuity Pathway Analysis (IPA) software (http://www.ingenuity.com).

2.4 Real-time reverse transcription and quantitative PCR (real-time RT-qPCR)

Total RNA from cells and formalin-fixed paraffin-embedded (FFPE) specimens was isolated by TRIzol (Invitrogen, 15596-018) and truXTRAC FFPE RNA kit (Covaris, PN 520161), respectively. cDNA was generated by SuperScript™ III First-Strand Synthesis kit (Invitrogen, 18080-085) using Oligo-(dT). The qPCR primer pairs (Table S1) were designed by PerlPrimer (http://perlprimer.sourceforge.net/). Expression levels of mRNA and lncRNA were normalized against GAPDH.

Small RNA was isolated using miRNeasy Mini Kit (Qiagen, 217004) according to the manufacturer's instructions. For miRNA detection, 0.1 µg of RNA was reverse transcribed using miRCURY LNA miRNA PCR RT Kit (QIAGEN, 339340) and detected by miRCURY SYBR Green PCR Kit (QIAGEN, 339345). The sequence-specific LNA primers for hsa-miR-3620-3p (YP02109143), hsa-miR-6515-3p (YP02118952) and hsa-miR-6889-3p (YP02104407) were purchased from QIAGEN. The expression levels of miRNAs were normalized to UniSp6 (sp6), the spike-in control. Real-time qPCR analysis was carried out in CFX96 connect real-time PCR detection system (Bio-Rad, Hercules, CA, USA).

2.5 Chromatin immunoprecipitation-sequencing (ChIP-Seq) and real-time qPCR

ChIP was performed following the protocol from Farnham laboratory (http://genomics.ucdavis.edu/farnham) using anti-REST (Millipore, 17–641) and non-immune rabbit serum IgG (Alpha Diagnostic International). ChIP DNA prepared from 1 x 10⁷ LNCaP-TR-shREST cells were subjected to SYBR® Green based qPCR using primer pair (5′-GCCTTTCTCCCACAATTTCTG-3′ and 5′-GTCCCTCTCCATCTCTGTC-3′) targeting PCAT-NE1 promoter of potential REST binding region identified in ChIP-seq data [32].

2.6 Immunoblotting

Total protein was extracted using 0.5%NP-40 lysis buffer containing 1X protease inhibitor cocktail (Roche, 04693132001)). Protein concentration was measured by Bio-Rad protein assay dye reagent (Bio-Rad, 500-0006). Protein samples were resolved by SDS-polyacrylamide gels electrophoresis (SDS-PAGE), transferred onto 0.45µm pore size PVDF membranes (GE Healthcare, RPN303F), blocked with 5% BSA in 1X TBST, immunoblotted with primary antibodies against each of the indicated proteins followed by horseradish peroxidase (HRP) conjugated-secondary antibodies, visualized by Pierce ECL Western Blotting Substrate (Thermo Scientific, 34080) and imaged using a Luminescence/Fluorescence Imaging System (FUJIFILM, LAS-4000). Primary antibodies used were anti-REST (Millipore, 07-579), anti-AR (Millipore, 06-680), anti-CgA (Thermo Fisher Scientific, MA5-13096), anti-SYP (GeneTex, GTX100865), anti-TUBIII (Sigma Aldrich, 2200), anti-LC3 (Cell Signaling, 2775), anti-p62 (Cell Signaling, 5114), anti-VPS13A (Sigma, HPA021662) and anti-GAPDH (GTX 100118).

2.7 Immunohistochemistry (IHC) staining

FFPE tissues of hormone sensitive prostate cancer (HSPC) and CRPC were collected at Taipei Veterans General Hospital (TPEVGH). Ethics was approved by the Institutional Review Board (IRB) of TPEVGH. Tissue sections were stained for CgA (Thermo Fisher Scientific) and visualized as described previously [29]. Expression of CgA was evaluated using H-score (multiplying the staining intensity (0–3) by the percentage of epithelial cells with positive staining) by board-certified pathologists, Dr. Yu-Ching Peng and Dr. Chin-Chen Pan, in a blind fashion.

2.8 RNAscope in situ hybridization

The RNA in situ hybridization (RNA-ISH) was conducted following the manufacturer's instructions of RNAscope Multiplex Fluorescent Detection Kit v2 (Advanced Cell Diagnostics (ACD), 323110). LNCaP cells were fixed with 4% paraformaldehyde (PFA) in PBS (PFA/PBS), treated with H₂O₂ for 10 minutes to block endogenous peroxidase activity followed by Protease III treatment at room temperature (RT) for 10 minutes. RNAscope probes targeting 715–1616 nucleotide of LINC01801 (accession number NR_033982.1) (ACD, 1032341-C1) and the positive/negative controls PPIB/Bacillus subtilis DapB (ACD, 313911/310043) were hybridized at 40^oC in HybEZ II oven (ACD, 241000ACD) for 2 hours followed by 3 signal amplification steps and probe visualization. Slides were counterstained with DAPI and analyzed by Vectra Polaris (Akoya Biosciences, Vectra Polaris) using the excitation/emission wavelengths of 494/525nm for RNA probe and 358/461nm for DAPI. For the quantification, dots co-localized with and without DAPI signal were counted.

2.9 Cell proliferation assay

LNCaP-TR-PCAT-NE1 cells were seeded into 96-well plates (1 × 10⁴ cells/well), treated the next day with 0.1µg/ml Dox, and performed 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The absorbance (570 and 660nm) was measured spectrophotometrically using Multimode microplate readers TECAN 200Pro (Tecan, Germany). The same volume of medium was used as blank control.

2.10 Neurite outgrowth assay

LNCaP and LNCaP-TR-PCAT-NE1 cells were seeded on poly-L-lysine-coated coverslips in 6-well plates at a density of 1x10⁵ cell/well. Following treatments as indicated, cells were fixed, stained, mounted, visualized/photographed and analyzed as described previously [29].

2.11 Measurement of autophagy activity

LNCaP-TR-PCAT-NE1 cells were plated and fixed as described for the neurite outgrowth assay. Following fixation, cells were permeabilized with 0.5% Triton X-100/PBS for 15 minutes at RT, blocked with 1% BSA/PBS for 1 hour at RT, stained overnight at 4^oC with anti-LC3 (Cell Signaling, 2775) antibody and incubated at RT for 1 hour with Alexa Flour 488 anti-rabbit IgG (Jackson ImmunoResearch, ab181448). PBS washes were performed between each step. After the final wash, cell nuclei were counterstained, mounted and photographed as described in the neurite outgrowth assay. The LC3 images were visualized, analyzed and calculated as described previously [15].

2.12 Luciferase assay

293T cells were co-transfected with siGLO or hsa-miR-6889-3p mimics (5'-UCUGUGCCCCUACUUCCCAGGGGAAGUAGGGGCACAGAUU-3', Biotools), luciferase construct containing potential hsa-miR-6889-3p binding site on PCAT-NE1 or vector control and TK-Renilla plasmid, and harvested to determine the luciferase activities by using a dual-luciferase reporter assay system (Promega, E1960). The activity of the firefly luciferase was normalized to that of the Renilla luciferase in the same assayed sample.

2.13 miRNA target prediction

DIANA-LncBase v2.0 (http://carolina.imis.athena-innovation.gr) was used to predict the miRNAs that interact with PCAT-NE1. Target scan (http://www.targetscan.org/vert_72/), miRTarBase (https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2019/php/index.php), and TarBase (https://carolina.imis.athena-innovation.gr/diana_tools/web/index.php?r=tarbasev8%2Findex) were used to predict the mRNAs that may targeted by hsa-miR-6889-3p.

2.14 The Cancer Genome Atlas (TCGA) database

RNA-seq profiles of clinical data from 499 patients with prostate adenocarcinoma (AdPC) and 52 normal prostate tissues were download from TCGA (https://www.cancer.gov/tcga.). The expression of PCAT-NE1 was analyzed using Two-tailed Student’s t-test.

3.1 Identification of novel REST-repressed NE-associated lncRNA

To identify novel REST-repressed lncRNAs that are associated with NED, we first re-annotated the RNA-sequencing (RNA-seq) data [15] from control and doxycycline (Dox) treated LNCaP-TR-shREST cells using NONCODE v4.0 database [33]. Consistent with the repressive role for REST, of the 27,661 expressed lncRNAs (defined by FPKM > 1.0), more were up-regulated (7,913; 28%) than down-regulated (4,774; 17%) upon knockdown of REST (Fig. 1A). Among the up-regulated lncRNAs, 2,196 (27.8%) were sense exonic, 545 (6.9%) were sense intronic, 1,521 (19.2%) were antisense, and 3,651 (46.1%) were intergenic (long intergenic non-coding RNAs, lincRNAs). In this study, we focus on studying lincRNAs, the subclass of lncRNAs that do not overlap with mRNA coding regions.

Since our laboratory focuses on NED, we used an image-based assay model relying on observations of neurite-like morphology of LNCaP to monitor NED of PCa cells. We screened for lincRNA whose knockdown inhibits IL-6-induced NED. Human Lincode siRNA Library-NR lncRNA RefSeq v54-SMARTpool (Dharmacon) that contains 4 different siRNAs targeting each lncRNA transcript was employed to target the 147 lincRNAs whose expressions was up-regulated in REST knockdown LNCaP cells (Fig. 1A). Among this set, 17 lincRNAs were identified (Fig. 1B), and 14 of them whose knockdown significantly inhibited IL-6-induced NED in two independent experiments (Fig. 1B, bold). Following the screening, we further confirmed the up-regulation of the identified lncRNAs in REST knockdown LNCaP cells (Fig. 1C). RT-qPCR was able to detect 10 of the 14 lincRNAs and confirmed a consistent up-regulation of 8 lincRNAs (Fig. 1D).

3.2 PCAT-NE1 increases in NEPC

To begin understanding the association of the 8 lncRNAs with NEPC, we examined their expression in The Cancer Genome Atlas (TCGA) database. To study NE phenotype, we first ranked the 499 PCa samples by the expression levels of neuronal marker β-tubulin III (TUBIII). Expression levels scored as the top 20% indicates high expression (TUBIII^High), while the bottom 20% indicates low expression (TUBIII^Low).

Since only FAM225A, LINC01801, SNHG8 and TPT1-AS1 were identified in TCGA PCa dataset, the expression levels of the 4 lncRNAs were compared. FAM225A and LINC01801 were significantly higher in TUBIII^High group (Fig. 2A), suggesting their association with NED. In this study, we focus on LINC01801, the most significantly up-regulated lncRNA in TUBIII^High group.

To further evaluate the clinical value of LINC01801 in NEPC, we measured the levels of NE marker chromogranin A (CgA) and LINC01801 in 8 hormone sensitive prostate cancer (HSPC) and 26 CRPC tissues by immunohistochemistry (IHC) staining and RT-qPCR. respectively. The CgA^High sections showed a typical NEPC feature of focal staining pattern (H-score > 10) in 12 cases of CRPC but not in HSPC (Fig. 2B). RT-qPCR analysis revealed that LINC01801 expression was significantly higher in CgA^High CRPC when compared with CgA^Low CRPC and with HSPC (Fig. 2C). Together, these data support the idea that LINC01801 is a novel NEPC associated lncRNA. Based on the classification style of PCAT [31], we named it as prostate cancer associated transcript-neuroendocrine 1 (PCAT-NE1).

3.3 PCAT-NE1 is a direct target of REST

To confirm the up-regulation of PCAT-NE1 in NE transdifferentiated PCa cells, we examined the levels of PCAT-NE1 in two prostate adenocarcinoma cell lines, LNCaP and C4-2B, following IL-6 treatment. Immunoblotting confirmed the decrease in AR and the increase in NE markers (Fig. 3A). RT-qPCR revealed that PCAT-NE1 was stimulated by IL-6 in both cell lines (Fig. 3B). Since enzalutamide treatment associated with NED [34], we treated LNCaP and C4-2B cells with enzalutamide and found NE markers and PCAT-NE1 were similarly up-regulated by enzalutamide in both cell lines (Fig. 3C and 3D), indicating that PCAT-NE1 expression is induced by different NED stimuli.

To investigate whether PCAT-NE1 is a direct target of REST, we first searched for REST binding sites (RE-1) in the PCAT-NE1 promoter region (TSS ± 2000) by JASPAR (http://jaspar.genereg.net/). Surprisingly, no RE-1 site is identified within this region. However, the chromosome view of REST chromatin immunoprecipitation-sequencing (ChIP-seq) data from ENCODE showed potential REST binding sites on PCAT-NE1 promoter in neuroectodermal, neuroblastoma, hepatocellular carcinoma, and chronic myelogenous leukemia cell lines (Fig. 3E). Thus, we further looked into our ChIP-seq data [32] for potential REST binding sites in LNCaP cells. The result revealed several potential REST binding regions on PCAT-NE1 promoter (Fig. 3F, upper panel). We verified the binding of REST to the PCAT-NE1 promoter by ChIP-qPCR and showed that recruitment was significantly reduced by REST knockdown (Fig. 3F, lower panel). To further validate the REST-mediated regulation of PCAT-NE1, we treated LNCaP-TR-REST cells prior to IL-6 stimulation with Dox to induce expression of REST. We found that REST overexpression blocked the induction of PCAT-NE1 by IL-6 (Fig. 3G). Together, our results indicated that PCAT-NE1 is a direct REST-regulated lncRNA and is up-regulated in NE cells after down-regulation of REST.

3.4 PCAT-NE1 induces NED in PCa cells

Since the above observations indicate that PCAT-NE1 may play an important role in NED of PCa, we decided to further study this using knockdown and overexpression approaches. To test whether PCAT-NE1 induces NE transdifferentiation, we established an inducible PCAT-NE1-overexpressing LNCaP cell line, LNCaP-TR-PCAT-NE1. Successful induction of PCAT-NE1 RNA and neuronal marker TUBIII was first confirmed at various concentrations of Dox treatment (Fig. 4A and 4B). Therefore, 0.1µg/ml of Dox was used for subsequent in vitro experiments. Overexpression of PCAT-NE1 led to an induction of neuronal cell morphology changes in LNCaP cells (Fig. 4C) and an increase in NE markers (Fig. 4D).

In LNCaP-TR-shREST cells that were treated with Dox, silencing PCAT-NE1 significantly suppressed the expression of neuronal marker TUBIII (Fig. 5A and 5B) and changes in NE-like cellular morphology in LNCaP cells (Fig. 5C and 5D). These results support that PCAT-NE1 is essential for REST knockdown-induced NED. We also knocked down PCAT-NE1 in IL-6 treated LNCaP cells (Fig. 5E). Consistently, the result showed that IL-6 failed to induce NED after PCAT-NE1 knockdown (Fig. 5F to 5H). Interestingly, PCAT-NE1 also affects the basal NE-like cellular morphology that might be induced by siRNA transfection (Fig. 5H), indicating the general role of PCAT-NE1 in NED.

3.5 PCAT-NE1 activates the autophagy pathway by increasing autophagy-related gene expression.

To investigate the underlying mechanism on how PCAT-NE1 could control NED, we performed transcriptome analyses in LNCaP-TR-PCAT-NE1 cells with/without overexpression of PCAT-NE1 and in siGLO or siPCAT-NE1-treated LNCaP cells before and after IL-6 stimulation. For PCAT-NE1 overexpression, we detected 1279 PCAT-NE1-regulated genes, with 985 (12%) up- and 294 (4%) down-regulated genes. For knockdown of PCAT-NE1 in IL-6-induced NE differentiated cells, the successful induction of PCAT-NE1 under IL-6 treatment and effective knockdown of PCAT-NE1 RNA was first verified by RT-qPCR (Fig. 6A). Overall, we detected 710 IL-6 responsive genes with 428 up- and 282 down-regulated genes. After knockdown of PCAT-NE1, 297 and 968 genes were up- and down-regulated by IL-6, respectively. Gene set enrichment analysis (GSEA) (http://www.broad.mit.edu/gsea/) on the top 500 PCAT-NE1 overexpression up-regulated (Fig. 6B) and PCAT-NE1 knockdown down-regulated genes (Fig. 6C) showed a positive correlation between PCAT-NE1 and castration, supporting the castration resistant feature in NEPC.

Next, we perform gene ontology (GO) data analysis using Ingenuity Pathway Analysis (IPA) software on the IL-6-regulated genes with/without PCAT-NE1 knockdown (Fig. 6D). We found that genes regulated byPCAT-NE1 were associated with cell viability, autophagy and gene expression (Fig. 6E). More importantly, knockdown of PCAT-NE1 abolished the autophagy and gene expression pathways, but not the cell viability pathway, enriched in PCAT-NE1 overexpression and IL-6 stimulation (Fig. 6E). Previously, our laboratory and others have demonstrated that autophagy is required for NED of PCa cells [14, 15, 35, 36]. Thus, we investigated whether autophagy is activated by PCAT-NE1 overexpression. As shown in Fig. 7A and 7B, autophagic cells, as well as LC3-II levels, were increased in LNCaP cells overexpressing PCAT-NE1. More importantly, knockdown of the autophagy-related gene beclin-1, which inhibits autophagy, in LNCaP-TR-PCAT-NE1 cells blocked PCAT-NE1-induced NED (Fig. 7C), indicating that PCAT-NE1 likely induces NED by activation of autophagy.

Given that PCAT-NE1 was associated with gene expression (Fig. 6E), the levels of the 19 autophagy-related genes defined in the autophagy pathway were measured by RT-qPCR. The results revealed that overexpression of PCAT-NE1 increased the expression of ATM, HIF1A, PTEN, TBK1, VPS13A and XPO1 in three independent experiments (Fig. 7D). TCGA dataset analysis showed that the expression levels of ATM, HIF1A, PTEN, TBK1, VPS13A and XPO1 were significantly higher in PCAT-NE1^High group of PCa tissues (Fig. 7E). Taken together, our results indicated that PCAT-NE1 may induce NED in part by modulating the expression of autophagy-related genes with consequent activation of autophagy.

3.6 PCAT-NE1 activates the autophagy pathway through sponging miR-6889-3p and up-regulating VPS13A

Given the concept of lncRNAs in modulating gene transcription through sponging miRNAs showed co-up- and co-down regulation of their target genes and most of the PCAT-NE1-regulated mRNAs were co-up- and down-regulated with PCAT-NE1, we hypothesized that PCAT-NE1 may function as a ceRNA to modulate gene expression. Hence, we first determined the subcellular distribution of PCAT-NE1 using RNA scope assay. Consistent with the cytoplasmic localization of ceRNA, though PCAT-NE1 was distributed in both nuclear and cytoplasmic compartments, it was more enriched in the cytoplasm (Fig. 8A). To identify miRNAs that can be sequestered by PCAT-NE1, we performed smRNA-seq to profile miRNA expression in IL-6-treated LNCaP cells with/without knockdown of PCAT-NE1. Among the 725 expressed miRNAs (RPM > 1), 47 (6%) were up- and 179 (25%) were down-regulated after IL-6 treatment. Notably, knockdown of PCAT-NE1 under IL-6 treatment condition significantly increased the numbers of up-regulated miRNAs (157 miRNAs; 22%) when compared with IL-6 treatment alone (47 miRNAs; 6%), supporting the notion of PCAT-NE1 as a ceRNA. Next, we predicted the potential miRNAs that can be sponged by PCAT-NE1. DIANA-LncBase v2.0 was used. Of the 179 miRNAs that are down-regulated by IL-6 treatment, 9 miRNAs were predicted to be potential targets of PCAT-NE1 (Fig. 8B). For the 157 miRNAs that were up-regulated after knockdown of PCAT-NE1 under IL-6 treatment conditions, 10 miRNAs were predicted as potential targets of PCAT-NE1 (Fig. 8B). Among these two groups, hsa-miR-3620-3p, hsa-miR-6515-3p and hsa-miR-6889-3p were common potential targets of PCAT-NE1 (Fig. 8B, bold).

To examine whether these miRNAs are targets of PCAT-NE1, we performed RT-qPCR to detect miRNA levels in PCAT-NE1 overexpressed LNCaP cells and identified hsa-miR-6889-3p as a potential target (Fig. 8C). Supporting the notion of ceRNA possess multiple binding sites for its targeted miRNA, PCAT-NE1 contains 5 potential binding sites for hsa-miR-6889-3p (Fig. 8D). To investigate whether hsa-miR-6889-3p participates in PCAT-NE1-induced NED and autophagy activation, we transfected hsa-miR-6889-3p mimic into LNCaP-TR-PCAT-NE1 cells. Indeed, hsa-miR-6889-3p mimic inhibited NED and autophagy induced by PCAT-NE1 overexpression (Fig. 8E). Next, we analyzed the expression of autophagy-related genes and the result showed that hsa-miR-6889-3p mimic inhibited VPS13A expression (> 1.5-fold) (Fig. 8F). Moreover, overexpression of PCAT-NE1 partially restored the suppression effect of hsa-miR-6889-3p mimic (Fig. 8G). Unfortunately, we were unable to identify any potential hsa-miR-6889-3p target site on the transcript of VPS13A by using various bioinformatic tools, including TargetScan, miRTar base and TarBase. This indicates that hsa-miR-6889-3p may inhibit VPS13A expression through an indirect mechanism requiring future elucidation. Collectively, our results suggest that REST and PCAT-NE1 control NED and autophagy activation by direct targeting hsa-miR-6889-3p.

NEPC was initially considered to be rare, however with the emergence of new types of anti-AR therapies, NEPC is now becoming more and more common. Importantly, our preliminary data also demonstrates that chemotherapeutic drugs, such as cabazitaxel and docetaxel, are also able to induce/enhance the NED in PCa cells (data not shown). Considering that NEPC is lethal with no effective treatment options currently, identification of the molecular mechanisms underlying the emergence of NEPC is urgently needed for the prevention and control of this subtype of PCa.

Although master regulators that modulate NEPC lineage plasticity have been identified, the underlying mechanisms have yet to be established. The development of NEPC may evolve via multiple mechanisms. One of the most striking observations was that NEPC minimizes AR dependency coinciding with the acquisition of a NE phenotype. In addition to gene mutations and amplifications [37–42], epigenetic regulation of chromatin accessibility for transcription was also found to play a key role in NEPC [18, 43–45]. More importantly, the epigenetic/non-coding interactome is emerging as a novel mechanism that orchestrates the initiation and progression of NEPC [26, 28]. Since lncRNAs possess higher tissue specificity, discovering NEPC-associated lncRNAs may help identify specific biomarkers for disease diagnosis/prognosis and therapeutic targets for NEPC. One promising example is prostate cancer gene 3 (PCA3), an FDA-approved lncRNA biomarker, that is now routinely used in the clinic for PCa diagnosis [46, 47]. More importantly, lncRNAs have been found to regulate transcription through either serving as scaffolds to recruit transcription regulators to specific genomic loci or acting as ceRNA that function as sponges to decoy miRNAs [24, 25]. Although transcriptome studies identified the expression profiles of lncRNAs associated with NEPC progression, few lncRNAs have been established as drivers for NEPC transdifferentiation.

Since REST serves as a master epigenetic repressor governing NED driver genes in PCa [14, 15, 48] and down-regulation of REST was observed in up to 50% of clinical NEPC specimens [49], we therefore hypothesized that REST may also negatively regulate lncRNAs with NED driving potential. Down modulation of REST during NED may concomitantly up-regulate the expression of those lncRNAs and consequently induce NED. To identify potential NED driving lncRNAs, we used an inducible REST-knockdown LNCaP cell model to identify lncRNAs that are up-regulated upon REST down-regulation. Following a comprehensive siRNA knockdown screening, we identified PCAT-NE1 as a novel REST targeting lncRNA with NED driving potential. LINC01801/PCAT-NE1 (Gene ID: 400685; Location (hg38): chr19:34788534–34832869), originally named as LOC400685, is classified as a subtype of lncRNA, known as lincRNA. It is a novel lncRNA with limited published information available. The only clue to its function comes from a 2012 study that showed deletion of the genomic locus containing LINC01801/PCAT-NE1 in relation to “19q13.11 deletion syndrome” [50], an autosomal dominant neurodevelopmental disorder [51], suggesting its potential role in mediating neuronal differentiation.

To elucidate the function of this novel lncRNA, transcriptome analysis was performed in LNCaP cells under PCAT-NE1 overexpression and knockdown conditions. GSEA analysis showed that PCAT-NE1 is positively correlated with castration resistance (Fig. 6B and 6C). To further confirm its role in NED, we performed IHC staining of CgA in 8 HSPC and 26 CRPC tissues and identified a NE feature in 12 CRPC (Fig. 2C). PCAT-NE1 was expressed at a significantly higher level in CRPC with a NE feature when compared with that without NE feature or with HSPC (Fig. 2C). Collectively, our results not only defined PCAT-NE1 as a NED driver of PCa, but also uncovered its potential clinical use as a biomarker of NEPC.

Bioinformatics analysis using IPA showed that cell viability, autophagy and RNA transcription pathways were significantly enriched in genes regulated by IL-6 treatment and PCAT-NE1 overexpression (1,279), while siRNA knockdown of PCAT-NE1 resulted in loss of autophagy and RNA transcription pathways (Fig. 6E). Consistent with previous reports showing that IL-6 treatment [14, 35] induces NED of PCa through activation of autophagy, results here indicate that PCAT-NE1 may participate in IL-6-induced NED through transcriptional regulation of autophagy genes. Following this hypothesis, the levels of PCAT-NE1-regulated autophagy genes were determined by real-time RT-qPCR. As shown in Fig. 7D, ATM, HIF1A, PTEN, TBK1, VPS13A and XPO1 were up-regulated after PCAT-NE1 overexpression, supporting the notion of PCAT-NE1 in mediating transcriptional regulation of autophagy genes.

Among the 6 autophagy genes up-regulated upon PCAT-NE1 overexpression, hsa-miR-6889-3p overexpression inhibits the expression of VPS13A (Fig. 8F). Moreover, PCAT-NE1 overexpression partially restores VPS13A expression (Fig. 8G). VPS13A, a phospholipid transporter participating in packaging organelle into autophagosomes, is a newly identified autophagy-related gene [52]. This suggests that PCAT-NE1-hsa-miR-6889-3p axis may modulate autophagy through VPS13A. However, we were unable to identify a hsa-miR-6889-3p target site on the VPS13A transcript. Whether hsa-miR-6889-3p reduces VPS13A expression through another mediator is worth further investigation. Nevertheless, autophagy activation helps explain the potential of PCAT-NE1 in driving NED.

In conclusion, in this study, we identified PCAT-NE1 as a novel REST targeted lncRNA and elucidated its role in inducing NED of PCa cells. Moreover, we showed that PCAT-NE1 induces NED of PCa cells via activation of autophagy pathway (Fig. 8). Our findings provide new insight into the potential use of PCAT-NE1 as a diagnosis biomarker for NEPC, as well as the target for new treatments against NEPC, a highly drug-resistant subtype of PCa.

Ethics approval Experimental analysis of the FFPE tissues was approved by the Ethics Review Board of Taipei Veterans General Hospital (TPEVGH).

Consent for publication Not applicable

Availability of data The datasets generated in the current study are available in public database at https://www.ncbi.nlm.nih.gov/geo/. Supplementary table is available as supporting data.

Competing interests The authors disclose no potential conflicts of interest.

Funding This work was supported by grants to T.P.L (MOST 106-2314-B-075-053-MY3, 109-2314-B-075-072-MY3, 107-2622-E-075-001-CC2, 108-2622-E-075-001-CC2 and 109-2622-E-075-001-CC2; NHRI NHRI-109BCCO-MF-202014-03; Taipei Veterans General Hospital (VGH107C-195, VGH108C-114, V109C-111, V110C-104, V111C-081) and YEN TJING LING MEDICAL FOUNDATION (CI-106-17 and CI-110-21)) and grants to P.C.C. (MOST 104-2320-B-010-038 and YEN TJING LING MEDICAL FOUNDATION (CI-107-18)). This work was financially supported by the “Cancer Progression Research Center, National Yang-Ming University” within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.

Authors’ contributions C.H.C. contributed to collect patient samples and database analysis. W.W.Y., T.Y.C. and Y.L.L. contributed to design and carried out the experiments. T.C.K. contributed to siRNA preparation and transfection condition test. T.W.S. and Y.C.H. contributed to repeat experiments. Y.C.P. and C.C.P. contributed to interpretation of IHC staining results. M.C. contributed to writing of the manuscript. M.H.Y., W.J.H., J.C.S. and H.J.K. contributed to study design and discussion. P.C.C. and T.P.L. were in charge of all experimental design, discussion of ideas and manuscript writing.

Acknowledgements The authors acknowledge the Genomics Center for Clinical and Biotechnological Applications of National Core Facility for Biopharmaceuticals, Taiwan (MOST 108-2319-B-010-001) for sequencing.

Authors’ information

Ching-Hsin Chang, Wayne W. Yeh contributed equally to this work

Authors and Affliations

Institute of Microbiology and Immunology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.

Ching-Hsin Chang, Wayne W. Yeh, Ting-Yu Cheng, Yun-Li Luo, Tsai-Wen Shen & Pei-Ching Chang

Institute of Microbiology and Immunology, National Yang-Ming University, Taipei, 11221, Taiwan

Ching-Hsin Chang, Wayne W. Yeh, Ting-Yu Cheng, Yun-Li Luo, Tsai-Wen Shen & Pei-Ching Chang

Department of Urology, Taipei Medical University Hospital, Taipei 11031, Taiwan

Ching-Hsin Chang

TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei 11031, Taiwan

Ching-Hsin Chang

Comprehensive Cancer Center, University of California at Davis, Sacramento, CA, 95817, USA

Mel Campbell

Institute of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan, Miaoli County, 35053, Taiwan

Tse-Chun Kuo & Hsing-Jien Kung

Faculty of medicine, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan

Yung-Chih Hong & Hsing-Jien Kung

Department of Urology, Taipei Veterans General Hospital, Taipei 11217, Taiwan

Cheng-Han Tsai, William J. Huang & Tzu-Ping Lin

Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan

Yu-Ching Peng& Chin-Chen Pan

Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan

Muh-Hwa Yang

Institute of Biotechnology in Medicine, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan

Muh-Hwa Yang

Cancer Progression Research Center, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan

Muh-Hwa Yang& Pei-Ching Chang

Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan

Muh-Hwa Yang

Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan

Muh-Hwa Yang

Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA 90089, USA

Jean-Chen Shih

USC-Taiwan Center for Translational Research, University of Southern California, Los Angeles, CA 90089, USA

Jean-Chen Shih

Department of Integrative Anatomical Sciences, Keck School of Medicine, University of Southern California, 1975 Zonal Ave., Los Angeles, CA 90033, USA

Jean-Chen Shih

Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan

Hsing-Jien Kung

Ph.D. Program for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan

Hsing-Jien Kung

TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, 11031, Taiwan

Hsing-Jien Kung

Department of Urology, School of Medicine, and Shu-Tien Urological Research Center, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan

William J. Huang & Tzu-Ping Lin

Corresponding authors

Corresponding toPei-Ching Changor Tzu-Ping Lin

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A novel REST-regulated lncRNA PCAT-NE1 induces neuroendocrine differentiation in castration-resistant prostate cancer

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Abstract

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1 Introduction

2 Materials And Methods

2.1 Cell culture and treatment

2.2 Gene-knockdown experiment

2.3 High-throughput RNA and small RNA sequencing (RNA-seq and smRNA-seq) and gene ontology (GO) data analysis.

2.4 Real-time reverse transcription and quantitative PCR (real-time RT-qPCR)

2.5 Chromatin immunoprecipitation-sequencing (ChIP-Seq) and real-time qPCR

2.6 Immunoblotting

2.7 Immunohistochemistry (IHC) staining

2.8 RNAscope in situ hybridization

2.9 Cell proliferation assay

2.10 Neurite outgrowth assay

2.11 Measurement of autophagy activity

2.12 Luciferase assay

2.13 miRNA target prediction

2.14 The Cancer Genome Atlas (TCGA) database

3 Result

3.1 Identification of novel REST-repressed NE-associated lncRNA

3.2 PCAT-NE1 increases in NEPC

3.3 PCAT-NE1 is a direct target of REST

3.4 PCAT-NE1 induces NED in PCa cells

3.5 PCAT-NE1 activates the autophagy pathway by increasing autophagy-related gene expression.

3.6 PCAT-NE1 activates the autophagy pathway through sponging miR-6889-3p and up-regulating VPS13A

4 Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1