Crosstalk between EZH2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticity

Domain: chemistry
Published: 2026-02-21
Editorial outcome: major_revision

Abstract
Prostate cancer lineage plasticity is associated with changes in DNA methylation and enhancer of zeste homolog 2 (EZH2) activity. How these epigenetic programs functionally interact to modulate transcriptional reprogramming in neuroendocrine prostate cancer (NEPC) is not well understood. In this study, we demonstrate that hypomethylated regions of DNA preferentially accumulate the repressive mark, H3K27me3. We established an NEPC mouse model with deletion of Ezh2 in the background of Pten and Rb1 loss plus human MYCN overexpression. Deletion or pharmacological inhibition of EZH2 in NEPC murine or patient-derived models leads to a genome-wide rewiring of DNA methylation, characterized by hypomethylation and upregulation of neuroendocrine-lineage genes along with hypermethylation and repression of polycomb repressive complex 2 (PRC2) targets. On the other hand, deletion of DNA methyltransferase 1 (DNMT1) results in significant changes in H3K27me3 distribution, particularly affecting bivalent promoters bearing both H3K27me3 and active H3K4me3 marks. In NEPC models, neuroendocrine-lineage genes are repressed upon DNMT1 deletion associated with increased H3K27me3. Conversely, in prostate adenocarcinoma models, DNMT1 deletion leads to de-repression of neuroendocrine lineage genes with a loss of H3K27me3 marks. Our findings reveal a functional interplay between two repressive epigenetic machineries that mediates lineage plasticity in prostate cancer.

Introduction
Acquired change in DNA methylation has been proposed as a mechanism underlying epigenetic plasticity in several cancer types1. In prostate cancer, the DNA methylome is altered during the transition from benign prostate to localized prostate cancer2, and later during disease progression and castration resistance3,4; this is especially apparent in the subset of prostate adenocarcinomas that transform histologically to neuroendocrine prostate cancer (NEPC)2,5. Methylation changes are dynamic, with preclinical studies pointing to a tumor suppressor role of the DNA methyltransferase DNMT1 in early-stage prostate cancer, in contrast to an oncogenic function of DNMT1 in later stage prostate cancer, corresponding with distinct changes in the global methylome and transcriptome6. The importance of DNA methylation dynamics during normal development and cell lineage fate decisions points to DNA methylation having a critical function in lineage plasticity7–9, yet the mechanisms by which DNA methylation changes drive lineage transitions in prostate cancer are not well understood.

DNA methylation can directly repress gene expression but can also cooperate with other epigenetic pathways to modulate downstream transcriptional activity10–12. The enhancer of zeste homolog 2 (EZH2) protein is a catalytic subunit of the polycomb repressive complex 2 (PRC2) and catalyzer of the repressive histone 3 lysine 27 tri-methylation (H3K27me3) mark that also acts to suppress downstream transcriptional activity and has been implicated in prostate cancer lineage plasticity13–16. EZH2 is overexpressed in castration-resistant prostate cancer (CRPC) including NEPC and is an emerging therapeutic target13,16–20. We have previously shown how differential activity of PRC2 can result in modulation of neuroendocrine (NE)-associated lineage transcription factors facilitating NEPC genome-wide reprogramming13,16. Evidence from embryonic stem cell (ESC) studies suggests that DNA hypomethylation at CpG islands during the transition to a ground-state pluripotency state redirects PRC2 occupancy leading to increased H3K27me3 levels similar to what is observed in DNMT knockout cell lines21–23. Conversely, H3K27me3 depletion can lead to an increase in DNA methylation in ESCs24. The compensatory relationship between DNA methylation and EZH2 has been shown in some cancer types during acquired treatment resistance25,26 or immune evasion27–29, where continued transcriptional repression upon DNA methylation inhibition is alleviated by an EZH2 inhibitor. How DNA methylation and EZH2/PRC2 activity interact to modulate prostate cancer lineage plasticity has not been well characterized.

Here, we sought to address the potential crosstalk between DNA methylation and EZH2 in advanced prostate cancer. We demonstrate an overlap in DNA methylation and H3K27me3 profiles that is dynamic following genetic and pharmacological perturbations of either. Using mouse and patient-derived models, we highlight the compensatory roles of these two repressive mechanisms during progression of CRPC towards a NE-lineage state.

Results
Overlap of hypo-methylated DMRs and H3K27me3 marked genes in NEPC
Consistent with the distinct methylation patterns observed in NEPC patient tumors compared with castration-resistant prostate adenocarcinoma (PRAD)17, the PRAD-to-NEPC transitioning murine model that lacks Pten and Rb1 and harbors human MYCN overexpression (PRN mice) also acquires DNA methylation changes during progression to NEPC30. NEPC tumors from patients and PRN mice, as well patient-derived NEPC organoids and androgen-deprived PRAD cells with similar genomic alterations (MYCN (gene encoding N-Myc) overexpression and RB1 loss), all exhibit overexpression of DNA methylation regulators including DNMT1 compared to their PRAD counterparts (Fig. S1A–F). Analysis of differentially methylated regions (DMRs) that distinguish NEPC and PRAD tumors in PRN mice revealed 548 hypo-methylated (hypo-DMR) and 589 hyper-methylated (hyper-DMR) regions in NEPC as compared to PRAD foci; 67% of these DMR-associated genes had similar methylation changes in NEPC versus castration-resistant PRAD patient-derived organoids (PDOs, Fig. 1A). Of these, 41% of hyper- and 54% of hypo-DMRs were also common with patient tumor derived DMRs from Zhao et al. (Fig. 1B)4. While differences are expected due to inter-tumoral heterogeneity, overall, these data support substantial consistency of DNA methylation patterns in NEPC versus castration-resistant PRAD across patients and models.

The distribution of hypo- and hyper-DMRs was similar across different genomic locations and chromosomes (Fig. S2A, B). The murine-defined gene-sets associated with DMRs when applied to patient datasets31,32 also distinguished samples according to histological subtype, further highlighting the clinical relevance of the defined DMRs (Fig. S2C). Notably, gene set enrichment analysis (GSEA) of PRN-defined DMRs revealed an enrichment for hypo-DMRs associated with bivalent promoters, neurogenesis, and PRC2-related pathway genes as compared to hyper-DMRs (Fig. 1C). We observed similar enriched pathways at the common patient-defined and PDO-defined 274 hypo- and 116 hyper-DMRs that were at promoters (Fig. 1D). Gene body and intergenic DMRs from PRN and PDOs had a similar pathway enrichment (Fig. S2D–G). Bivalent promoters contain both repressive H3K27me3 and activating histone 3 lysine 4 tri-methylation (H3K4me3) marks rendering genes in a poised state which is critical for lineage specification during normal tissue development33. Significant enrichment of PRC2 target genes across NEPC patients and models pointed to a potential interplay between DNA methylation and PRC2 activity.

To further characterize this potential interplay, we profiled genome-wide H3K27me3 marks in PRN mice and observed a distinct H3K27me3 profile in NEPC tumor foci compared to PRAD (Fig. 2A). Overall, 38% of the H3K27me3 marks in PRAD were lost following the transition to NEPC, and NEPC foci acquired 51% of new H3K27me3 marks. There was increased deposition of H3K27me3 at hypo-DMRs compared with hyper-DMRs, which was not specific for any genomic location (e.g., promoter, gene body or intergenic regions, Fig. 2B and S3A, B). Similarly, we identified increased occupancy of H3K27me3 at the patient tumor hypo-DMRs described in Zhao et al.4 in patient-derived models of NEPC compared with PRAD (Fig. 2C, D, and S3C). This relationship was further validated using EPIC-array-based DMR data of NEPC patient-derived xenografts (Fig. S3D)32,34. Extending this analysis to an additional 9 NEPC and 9 CRPC PRAD patient tumors that we characterized by H3K27me3 CUT&RUN16,17, we observed negative correlation between H3K27me3 levels and DNA methylation at promoter regions (Fig. 2E)4. Of note, NE-lineage associated genes (e.g., PROX1, INSM1, ASCL1) were enriched for both repressive marks in PRAD and luminal-lineage genes (e.g., AR, REST) were enriched for both marks in NEPC associated with their lower expression levels in PRAD and NEPC, respectively (Fig. 2E, Fig. S3E).

Overall, our findings in different models and patient tumors demonstrate an increased deposition of H3K27me3 at DNA hypo-DMRs regions in NEPC as compared to PRAD supporting an interaction of DNA methylation and PRC2-mediated epigenetic programs.

DNA methylation changes upon EZH2 deletion
To functionally characterize this interaction, we deleted Ezh2 in PRN mice. For this, we crossed mice harboring Ezh2 floxed alleles (Ezh2f/f) with PRN mice and generated PRNE mice (Pb-Cre4+/-;Ptenf/f;Rb1f/f;LSL-MYCN+/+;Ezh2f/f) with prostate epithelial cells having triple homozygous knockout of Pten, Rb1 and Ezh2 and an induction of human MYCN upon Cre recombinase activation (Fig. 3A, B). Upon Ezh2 deletion, PRNE mice still developed NEPC and had a similar survival as PRN mice, but had a shorter survival compared with heterozygous mice (PRNEhet (Pb-Cre4+/-;Ptenf/f;Rb1f/f;LSL-MYCN+/+;Ezh2f/+)) with one wild-type EZH2 allele (Fig. S4A, B). Histological evaluation of PRNEhet mice (n=2) demonstrated only 30% of the tumor foci to be NEPC at 12 weeks compared to the 95% of NEPC foci in PRNE mice at a similar age (Fig. S4B, C). These data suggest that deleting both EZH2 alleles does not prevent aggressive NEPC progression.

Evaluation of DNA methylation changes at the clinically relevant PRN-defined DMRs (Fig. 1A) in the PRNE model revealed that 52% hypo-DMRs from the PRN model were hyper-methylated in the absence of Ezh2 while 25% of PRN hyper-DMRs were hypo-methylated in PRNE (Fig. 3C). Deletion of Ezh2 resulted in a substantial change in the global DNA methylation profile (3635 hypo- and 1754 hyper-DMRs; FDR < 0.05) in NEPC tumors from PRNE mice compared to PRN mice (Fig. 3D). Of the DMRs, 20% of hypo-DMRs and 60% of hyper-DMRs were marked by H3K27me3 in NEPC tumors in PRN. This data suggests that the majority of EZH2 deletion-induced DNA methylation changes occur at regions that were differentially methylated during disease progression and were marked by H3K27me3 in the EZH2-intact NEPC model.

To examine whether pharmacological inhibition of EZH2 influences the DNA methylome, we treated the NEPC PDO MSKPCa10, which was used to define DMRs (Fig. 1B), with the EZH2 inhibitor (EZH2i) tazemetostat or vehicle control for 14 days (Fig. 3E) and evaluated for genome-wide DNA methylation changes after treatment. We observed 185 hyper- and 681 hypo-DMRs after tazemetostat as compared to vehicle-treated organoids (Fig. 3E). When evaluating the genomic distribution of DMRs upon EZH2 silencing or inhibition, we found that, for both models, hyper-methylated regions were enriched at promoters as compared to hypo-methylated regions (Fig. S4D). We further observed similar hypo-methylation at neuron-related genes (e.g., Onecut2, Ntng2, and Slitrk2) and hyper-methylation at H3K27me3 targets (e.g., Gata5, Kcnt1, Hoxb3, and Uncx) in tazemetostat-treated NEPC PDO as observed in PRNE NEPC tumors compared to PRN NEPC (Figure S4E). Interestingly, 76% of the hyper-methylated promoters in PRNE mice were marked by H3K27me3 in NEPC tumors of PRN mice, supporting the compensatory role of the DNA methylation machinery upon EZH2 loss.

Hypo-methylation after EZH2 inhibition is associated with neuroendocrine differentiation
Next, we sought to understand which genes and pathways were specifically impacted by differential DNA methylation upon EZH2 silencing or inhibition. We performed integrative analyses using differentially expressed genes and DMRs in PRNE NEPC tumors compared to PRN NEPC tumors and identified 648 downregulated genes that were hyper-methylated and 676 upregulated genes that were hypo-methylated (Fig. 4A). Gene-set enrichment analyses with DMRs at promoters and intergenic regions overlapping with known enhancers, revealed that upregulated genes with hypo-DMRs in PRNE NEPC tumors were enriched at genes associated with neural differentiation and nervous system development, while downregulated genes with hyper-DMRs were enriched at genes associated with canonical PRC2 targets and bivalent promoters (Fig. 4B). Additionally, gene-sets related to NEPC from Beltran et al.17 and Tsai et al.35 were strongly enriched in PRNE as compared to PRN suggesting that deletion of Ezh2 may induce NE-lineage genes further owing to changes in DNA methylation patterns (Fig. 4C). Genes such as Foxa1, Onecut2 and Gata5 showed a compensatory phenomenon where deletion of Ezh2 led to hyper-methylation at the regions covered by H3K27me3 in PRN mice with wildtype Ezh2, leading to further downregulated expression in PRNE NEPC (Fig. 4D, E). In contrast, upon Ezh2 deletion, Foxa2 was upregulated and hypo-methylated at its distal enhancer-like region following Ezh2 deletion. This region is covered by H3K27me3 in PRN NEPC tumors (Fig. 4D, E).

We performed similar analyses of the acquired DMRs in MSKPCA10 NEPC PDO cells following tazemetostat treatment. Consistent with genetic perturbation, gene set enrichment analysis with hypo DMRs at the promoters and intergenic regions overlapping with enhancers showed enrichment at neurogenesis related pathways following EZH2 inhibition. However, PRC2 target genes as well as bivalently marked promoters and intergenic regions were enriched with both hypo- and hyper-DMRs upon EZH2 inhibition. (Fig. 4F).

Taken together, these data suggest that changes in DNA methylation upon EZH2 silencing or inhibition leads to a further induction of NE-related genes, pointing to a potential compensatory mechanism for DNA methylation to occupy regions that were PRC2 targets.

DNMT silencing or inhibition lead to redistribution of H3K27me3
Given that EZH2 impacts DNA methylation, we posited that DNA methylation changes could also impact EZH2/PRC2 activity. Silencing of DNMT has been associated with redistribution of H3K27me3 repressive marks during normal development, and an intact methylome is required for PRC2-mediated gene repression10. Using CRISPR-Cas9, we knocked out DNMT1 in NEPC PDO (WCM154) and the CRPC cell line 22Rv136 (Fig. S5). Analysis of H3K27me3 signal in 10-kb genome-wide regions revealed 27,390 regions to be enriched and 38,741 regions to be depleted for H3K27me3 upon DNMT knockout (KO) in WCM154 as compared to control (Fig. S6A); this differential distribution of H3K27me3 was not specific for any genomic location (e.g., promoter, intron, or exon) (Fig. S6B, C). In 22Rv1, silencing of DNMT1 led to enrichment in 19,724 and depletion in 23,386 10-kb regions of H3K27me3 levels (Fig. S6D) with a significant level of depletion of H3K27me3 at gene promoters (sgGFP, 15.1%; sgDNMT1, 4.7%) (Fig. S6E).

Next, we sought to understand how re-distribution of H3K27me3 upon DNMT1 KO impacts gene expression. Focusing only on promoter regions, we identified 303 upregulated genes and 242 downregulated genes that were associated with depletion or enrichment of H3K27me3, respectively, after DNMT1 silencing in NEPC organoids (Fig. 5A). Gene ontology analyses revealed that downregulated genes were related to neurogenesis processes as compared to upregulated genes impacted by changes in H3K27me3 (Fig. 5B, and S7A). Curated gene-set (C2) enrichment analyses identified H3K27me3-enriched downregulated genes with high-CpG-density promoters that are bivalent in the brain37 (Fig. 5C). Investigating the epigenetic profile of H3K27me3 and H3K4me3 at the downregulated genes confirmed the marked impact on bivalent promoters upon DNMT1 silencing, particularly with a notable loss of H3K4me3 accompanying the enrichment of H3K27me3 (Fig. 5D). NEPC-related transcription factors such as POU3F2 (encoding BRN2) and LHX2 were among the genes with prominent bivalent promoters that were dysregulated upon DNMT1 silencing and associated with transcriptional repression (Fig. 5E). Homer motif analyses of differentially regulated bivalent-genes did not reveal motifs of classical transcription factors implicated in lineage plasticity (Figure S7B, C).

We explored whether DNMT inhibition has a similar effect on H3K27me3 re-distribution by performing a short-term in vivo treatment study with the pan-DNMT inhibitor decitabine in NEPC patient-derived xenografts. A significant shift in H3K27me3 deposition was observed with 57,333 H3K27me3-enriched and 23,980 H3K27me3-depleted peaks in decitabine-treated tumors compared to vehicle (Fig. 5F; and Fig. S8A). Consistent with DNMT1 deletion, decitabine-treated tumors showed a decrease in promoter bivalency (increase in H3K27me3 deposition, decrease in H3K4me3), (Fig. 5G). This included promoters associated with neuronal development/signaling (e.g. CDX2, NTRK2, PTPN7 and STON2). The regions that had a decrease in bivalency following DNMT1 deletion or decitabine treatment overlap with DMRs observed in patient tumors (Fig. S8B).

In the CRPC cell line 22Rv1, DNMT1 silencing led to 307 upregulated and 49 downregulated genes impacted by the re-distribution of H3K27me3 (Fig. 6A). There was a negative correlation between baseline DNA methylation and H3K27me3 levels genome-wide, though no correlation between baseline DNA methylation status and H3K27me3 levels at promoters of differentially expressed genes (Fig. S9A, B). In contrast to the downregulated genes in NEPC, upregulated genes in 22Rv1 were related to neurogenesis and neuron development pathways (Fig. 6B, and S10A). Among the upregulated genes, Curated GSEA (C2) also revealed an enrichment of genes with bivalent promoters in the brain (Fig. 6C). H3K4me3 deposition was increased upon loss of DNMT1 at promoters with a marked loss of H3K27me3 associated with their induction (Fig. 6D). In this case, NEPC-related genes POU3F2 and LHX2 had inverse effects on their epigenetic profile; in other words, their bivalent promoters were depleted of H3K27me3 which may have contributed to their de-repression upon DNMT1 silencing (Fig. 6E). Homer analyses of the promoters of differentially regulated genes impacted by changes in H3K27me3 identified potential transcriptional regulators influencing gene expression including ASCL2 binding sites in genes upregulated upon DNMT1 silencing in 22Rv1 (Figure S10B, and C).

To investigate the potential therapeutic relevance of the PRC2-DNMT interaction, we conducted pilot studies co-targeting DNMT and EZH2, both in combination and sequentially. Unfortunately, all in vivo studies had to be discontinued due to toxicity associated with dosing and administration (Figure S11). Further research is needed to optimize dosing strategies, evaluate safety, and assess the efficacy of combination therapy in prostate cancer preclinical models.

Overall, these data support a crosstalk between DNMT1 and PRC2-mediated H3K27me3 distribution patterns. DNMT1 silencing leads to downregulation of NE-related genes and pathways in NEPC and an upregulation of similar pathways in PRAD.

Methods
Our research adhered to all relevant ethical regulations, with the study protocol approved by the institutional IACUC. All mouse experiments were conducted in accordance with protocols approved by the WCM-IACUC (protocol no. 2008-0019).

Human cell lines
The prostate cancer cell line, LNCaP and 22Rv1 was obtained from ATCC and authenticated using short tandem repeat (STR) analysis. The cells were grown in RPMI 1640 medium (Gibco, 11875-093) supplemented with 10% fetal bovine serum (Gemini, 900–108) and 1% penicillin/streptomycin (Gibco, 15140-122). For acute and chronic androgen deprived experiments, cells were cultured in phenol red–free RPMI medium (Gibco, 11835-030) supplemented with 5% charcoal-stripped serum (Gibco, A33821-01) and 1% penicillin/streptomycin, for 4 and 14 days respectively.

Patient-derived organoids
Established patient-derived organoids, WCM154, WCM1078, WCM1262 and WCM1358 were maintained as previously described18. The NEPC patient-derived organoid line (MSKPCa10) was a generous gift from Dr. Yu Chen’s lab (Memorial Sloan Kettering Cancer Center, New York) and grown in human organoid media as previously described56. CRPC lines were supplemented with 10 nM DHT (5α-dihydrotestosterone, Sigma-Aldrich, D-073).

Genetically engineered mouse models
Mouse experiments were performed as per protocols approved by the WCM-IACUC (protocol no. 2008-0019). All mice were bred on the same mixed genetic background (C57BL6/129×1/SvJ). Previously published PRN (Pb-Cre4+/-;Ptenf/f;Rb1f/f;LSL-MYCN+/+)30 were crossed with transgenic mice harboring Ezh2 floxed alleles (a kind gift from Dr. David Goodrich at Roswell Park Comprehensive Cancer Center) to generate a new transgenic PRNE (Pb-Cre4+/-;Ptenf/f;Rb1f/f;LSL-MYCN+/+;Ezh2f/f) model. The mice carried a CAG-LSL-MYCN human transgene at the Rosa26 locus and a Cre recombinase under prostate-specific probasin promoter. Expression of Cre results in removal of lox-stop-lox (LSL) cassette and expresses MYCN under chicken actin promoter, simultaneously knocking out Pten, Rb1 and Ezh2 floxed alleles. For analysis of differentially methylated regions, NEPC vs. PRAD tumors (n=2 pairs) of PRN mice and PRNE vs. PRN NEPC tumors (n=2 pairs) were used. All mice were housed in specific pathogen-free facility maintained at 21.5 ± 1°C temperature and 30-70% humidity in 12h dark-light cycle with access to food and water.

Knockout cell lines
Previously published LNCaP cells engineered with N-Myc induction57 were transduced with lentiviral particles to knockout RB1. The cells were infected with 500 MOI of viral particles and antibiotic selection was carried out with 1 μg/mL of puromycin for two weeks. Two guide RNAs for RB1 and two non-targeting controls were used (Table S2). Efficiency of RB1 knockout was assessed by analyzing DNA sequence around the CRISPR edit sites and comparing it with Western blots for RB1. The guide with most efficient knockout was used for further downstream experiments. WCM154 and 22Rv1 cells with DNMT1 knockout have been described previously36. For stable DNMT1 knockout in PRN organoids, 500 MOI of viral particles were used followed by spinoculation and antibiotic selection with 1 μg/mL of puromycin for two weeks. Three guide RNAs for DNMT1 and three non-targeting controls were used (Table S2). Adenovirus based Cre transduction was performed for both PRN and PRNE 3D-orgnoids in matrigel as per our previously published protocol30. Efficiency of Cre-induction was validated by western blots.

In vivo inhibitor studies in patient-derived xenografts
NEPC patient-derived organoid cells (1×106 cells diluted in 100 μl of 1:1 PBS and Matrigel) were injected subcutaneously in the flanks of nude (NU/J) mice (Jackson Laboratories, #002019, RRID: IMSR_JAX:002019). Tumor growth was measured by calipers every day for 1 week. Mice were randomly placed in treated or vehicle groups (n=5 each). Once the tumors measured 150 mm3, 0.8 mg/kg of decitabine was administered to mice in treated group by intraperitoneal injection once daily for 7 days. Equal volume of PBS was injected to mice in vehicle groups. Tumors were harvested at the end of treatment. Immunohistochemistry for DNMT1 and H3K27me3 ChIP-Seq was performed on the harvested tumors (n=3 pairs).
Sub-cutaneously implanted NEPC xenografts (PDXs) were castrated when tumor size reached 75 mm3 and treated with decitabine mice (0.8 mg/kg) and EPZ011989 (250 mg/kg), an EZH2 inhibitor when tumor size reached 150 mm3. Decitabine was administered once daily for a month by intraperitoneal injection while EPZ011989 was administered twice daily starting at day 8 for 21 days by oral gavage. Control mice were treated with equal volume of vehicle. Tumor volume was assessed every other day using caliper measurements for both vehicle (n=4) and decitabine+EPZ011989 (n=2) treated mice. All other mice in the treatment group were sick and had to be euthanized following our animal protocol before the end of treatment timepoint.

In vitro inhibitor studies in cell lines and patient-derived organoids
MSKPCa10 (NEPC) were treated with 5 μM tazemetostat, an EZH2 inhibitor for 14 days. Treatment efficacy was confirmed by H3K27me3 Western blotting at the end of treatment before performing RRBS. For cell viability assay using Celltiter Glo, MSKPCa10 and MSKPCa2 (CRPC) organoids were treated with tazemetostat (5 μM) and/or decitabine (5 μM) for 14 days while LNCaP cells with RB1 deletion and MYCN overexpression was treated similarly for 6 days. For growth response assay using incucyte, 3D organoids of PRN, PRNE and PRN with DNMT1 KO were treated with varying doses of decitabine or tazemetostat for 10 days. Media was replenished every 48h for all experiments.

Western blotting
Protein lysates were prepared in RIPA buffer (Thermo Scientific, 89901) supplemented with a cocktail of protease and phosphatase inhibitor (Thermo Scientific, 78428/78430). DC assay was used for protein quantification and 30 μg of protein was resolved in 4-15% of midi-Protean TGX gel (BioRad, 4561084) and transferred onto a PVDF membrane (Thermo Scientific, IB24002). Membranes were blocked in 5% non-fat milk (Bio-Rad, 1706404) or bovine serum albumin (BSA) (Sigma-Aldrich, A7906) in Tris-Buffered Saline Tween-20 (TBST) (Thermo Scientific, AAJ77500K8) for 1h at room temperature, followed by incubation with primary antibodies overnight at 4°C (Table S1). Membranes were then incubated with horseradish peroxidase-conjugated secondary antibody for 1h at room temperature and visualized by chemiluminescence detection method (Millipore, WBLUF0500). For blotting H3K27me3, proteins lysates were prepared in analysis buffer with 110 mM SDS, 100 mM DTT, 80 mM Tris-HCl pH 6.9 and 10% glycerol. RCDC assay was used for quantification of the H3K27me3-specific protein lysate.

ChIP-Seq
PRAD and NEPC foci were identified from hematoxylin-eosin stained slides of OCT blocks of primary tumors, reviewed by pathologist. The corresponding foci in OCT blocks were cored using 2 mm biopsy punch and tissues were dissociated using pestle and motor homogenizer, followed by syringes in cold PBS. Dissociated cells were crosslinked in 1% methanol-free formaldehyde (Thermo Scientific, 28908) for 15 min at 37°C. Crosslinking was quenched with 2.5 M glycine for 5 min at room temperature. Washed cell pellets were resuspended in 1 mL of lysis buffer (50 mM Tris HCl pH 8, 0.5% SDS, 10 mM EDTA with protease and phosphatase inhibitors; Thermo Fisher Scientific, 78428/78430) and lysed for 20 min at 4°C. Collected nuclei were resuspended in a second lysis buffer (10 mM Tris HCl pH 7.5, 150 mM NaCl, 0.1% SDS, 1 mM EDTA, 1% NP-40, 1% sodium deoxycholate, with protease and phosphatase inhibitors; Thermo Fisher Scientific, 78428/78430) and sonicated in Bioruptor Pico, Diagenode for 12 mins (30 sec on/30 sec off). To the sheared chromatin, equal volumes of specific antibody and respective IgG control antibody was added and incubated overnight at 4°C. The immunoprecipitated chromatin was washed with several buffers and eluted in 300 μL of fresh elution buffer (100 mM NaHCO3 and 1% SDS). Reverse crosslinking was performed with 45 mM Tris pH 7, 170 mM NaCl at 65°C overnight, followed by RNase and proteinase K treatment and DNA was purified using the NucleoSpin Gel and PCR Clean-up Kit (Macherey-Nagel, 740609) as per manufacturer’s recommendation. Libraries with purified immunoprecipitated DNA fragments were generated using the Hyper Prep Kit (Kapa Biosystems, KK8502). Library quality and fragment size distribution was checked in DNA High Sensitivity Bioanalyzer (Agilent, 5067-4626). Equimolar concentration of immunoprecipitated and input DNA fragments were pooled and sequenced for paired-end 50bp in Illumina NovaSeq 6000 instrument at Weill Cornell Medicine Genomics core facility.

ChIP-Seq data analysis
Quality of raw sequencing reads was assessed by FastQC (Babraham Bioinformatics). Adapters and low-quality reads (Phred score <20) were removed using TrimGalore. High quality reads were aligned to mm10 or hg38 genome using Bowtie2. Reads with mapping quality score <20 were removed from downstream analysis. PCR duplicates were removed using Picard MarkDuplicates. Peak calling was performed using the sonicated input DNA as control by MACS2 algorithm with a q value of <0.05. For H3K27me3, broad peak module of MACS2 was used. Enriched ChIP-seq peak regions were annotated to mm10/hg38 genomic features using HOMER annotatePeak.pl. Known or de novo transcription factor motifs were identified using HOMER findMotifs.pl +/- 100 bp from each peak. Unique and overlapping peaks between conditions were defined using BEDTools, keeping at least 1 bp overlap for overlapping peaks. For each condition, two replicates were used and normalized to their input control before merging. The combined signal from both replicates were used to generate enrichment profile plots and heatmap using deepTools.

CUT&RUN
CUT&RUN studies were performed with 100,000 cells in duplicates using a kit from Epicypher adhering to manufacturer’s protocol using antibodies against IgG or H3K4me3 (Epicypher, cat. no. 13-0041, 0.5 μg per reaction) or H3K27me3 (Invitrogen, cat. no. MA511198, 0.5 μg per reaction). Automated library-preparation and sequencing was performed by Molecular Biology Core Facilities in Dana-Farber Cancer Institute. Sequencing reads were mapped to hg38 human genome reference using bwa and visualized using deepTools as profile plots and heatmaps. Calculation of H3K27me3 signals in genome-wide 10 kb bins has been described previously16.

Reduced representation bisulfite sequencing (RRBS)
DNA methylation profiling was performed on biopsy punched tumor tissues of histopathologically confirmed foci of PRAD and NEPC from mouse primary tumor. DNA was extracted using Nucleospin Tissue kit (Macherey Nagel, 740952). For DNA methylation profiling in acute and chronic androgen deprived LNCaP NMYC induced and RB1 knockdown cells or scrambled shRNA control cells (n = 2 replicates), DNA was extracted after 4 and 42 days of androgen deprivation. For baseline DNA methylation profile from patient-derived organoids, DNA was extracted from cell pellets of each. For EZH2 knockout lines, DNA was extracted from cell pellets after 14 days of nucleofection and validating the knockout. Library preparation for RRBS libraries, sequencing, and post-processing of the raw data was performed at Epigenomics Core at Weill Cornell Medicine. The resulting libraries were normalized, pooled, multiplexed, and clustered on flow cells and sequenced for 100 cycles of single-end reads on an Illumina NovaSeq 6000 instrument.

Differential methylation analysis
Single-end bisulfite-converted reads were aligned using Bismark following trimming and adapter removal by TrimGalore. Methylkit was used for identifying differentially methylated sites (DMSs). Sites covered by at least 10 reads, at least 25% difference in methylation between conditions and 5% False Discovery Rate (FDR) were considered as significantly differentially methylated.
DMRcate was used to analyze differentially methylated regions (DMRs). CpG files generated by methylkit were normalized for coverage and sites covered by at least 10 reads were used for differential analysis. The comparison was made between two pairs of PRN NEPC Vs. PRN PRAD tumors and between NEPC PDOs (n=3) Vs. CRPC PDOs (n=2). A minimum of 5 consecutive CpGs were used to define a DMR and 5% FDR was used to identify significant DMRs. Homer was used to annotating the significant DMRs to promoters/TSS (±2000 bp from TSS and TSS), gene body (exons, introns, 5’-UTR and 3’-UTR), intergenic regions and CpG islands. Only the intergenic regions that overlapped with known enhancers were considered in downstream gene set enrichment analysis. Known enhancers or enhancer-like signatures were adopted from Vista Enhancers, ENCODE3 ENC+EPD enhancer gene map and ENCODE cis-regulatory elements in UCSC genome browser. Pathway analysis of the annotated genes was performed using MSigDB (HALLMARK, C2, C6 and GO gene sets) in Gene Set Enrichment Analysis.

Immunohistochemistry
All immunohistochemistry and hematoxylin and eosin (H&E)-stained slides were prepared at Center for Translational Pathology at Weill Cornell Medicine. Formalin fixed tissue was embedded in paraffin blocks and sectioned. Sections were de-paraffinized and endogenous peroxidase was inactivated. Antigen retrieval was accomplished by the Bond Epitope Retrieval Solution 1 (Leica Biosystems, AR9961) at 99–100°C for 30 min. The sections were incubated with primary antibody for 25 min, post-primary for 15 min, and polymer for 25 min ending with colorimetric development with diaminobenzidine (DAB) for 10 min using the Bond Polymer Refine Detection Kit (Leica Biosystems, DS9800). Hematoxylin and eosin (H&E)-stained slides were also prepared from frozen OCT-embedded tumor tissue blocks, used for identifying NEPC and PRAD foci in tumor tissues for ChIP and methylome experiments. All histological evaluations and quantifications (including hematoxylin and eosin (H&E)-stained and IHC images) were performed by a board-certified, genitourinary pathologist (B. Robinson) who was blinded to animal genotypes and follow criteria that have previously been described30.

Statistical analysis
All statistical analysis was done in GraphPad Prism. Replicates were included and a 5% false discovery rate was considered for identifying significant results. All graphs and plots were prepared in Prism, R studio or deeptools. For heatmap, Euclidean method was used for distance calculation while Ward 2 was used for clustering.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors have used cell lines, organoids and in vivo experiments to investigate a crosstalk between DNA methylation and EZH2 regulating NEPC progression. Their results showed DNA hypermethylation at H3K27me3 targets in the absence of Ezh2. Interestingly, DNMT1 deletion affected bivalent promoters with increased H3K27me3 and downregulation. The manuscript is well-written with significant findings. I have only a few comments:\n1. What is the EZH2 expression level during PRAD to NEPC transition in PRN mice, as 38% of the H3K27me3 marks were lost and 51% acquired?\n2. What mechanism might underlie regulation of bivalent promoters by DNMT1? Are there any other co-factors involved in directing DNMT1 to target the promoter of NE genes?\n3. In the Methods, please add the number of GE mice that were used in the study.\n4. Please add scale bar to S1A and S6C.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "In this manuscript, Singh and colleagues undertake integrative analyses of prostate cancer models (murine and human) to profile differences in gene expression and H3K4me3/H3K27me3 deposition. This is important as prostate cancer lineage plasticity is associated with changes in DNA methylation and PRC2 activities. EZH2 is highly unregulated in neuroendocrine prostate cancers, which result from the clinical use of high-affinity androgen receptor pathway inhibitors. The data presented here are of high quality, indicative of good technical expertise, and the interpretations are of interest. They focus on aspects of ‘bivalency’ in different model contexts, the presence of H3K4me3/H3K27me3 marks at CpG-rich promoters in mouse/human, and how they respond when Ezh2 (H3K27me3 methyltransferase) and Dnmt1 (maintenance CpG methylase) activities are inhibited.\nOverall, their data support a mutual crosstalk between Dnmt1 and PRC2-mediated H3K27me3 distribution patterns in castration-resistant prostate adenocarcinoma (PRAD). Dnmt1 silencing leads to downregulation of neuroendocrine (NE) related genes and pathways in neuroendocrine prostate cancer (NEPC) and an upregulation of similar pathways in PRAD. This is a very useful contribution to understanding epigenetic cross-talk, clinical understanding of the efficacy of epigenetic inhibitors against NEPC/PRAD, and the fact that the impact of epigenetic inhibition is context-dependent.\nI have a few comments.\nThe authors need to show formal evidence that Dnmt1 KO and decitabine treatment result in changes in DNA methylation through reliable methods (HPLC or WGBS, but not using 5mC antibody-based assays that are notoriously unreliable). Additionally, they should demonstrate the impact of Dnmt1 KO and decitabine treatment on the expression of known (general) genes and repeats whose silencing is maintained by DNA methylation in somatic cells.\nThe authors should also consider the model in which active histone modifications serve a supportive, rather than an essential regulatory, role in transcription, and silencing leads to a default (passive) accumulation of repressive marks (DNA methylation and H3K27me3). How would this impact the emergence of altered epigenetic profiles in prostate cancer undergoing cellular transitions?\nAdelman K. Nascent transcription as a predictor and driver of histone modifications. Nat Genet. 2022 Mar;54(3):223-224. doi: 10.1038/s41588-021-01004-9. PMID: 35273400.", "reviewer_4": "The manuscript entitled “Crosstalk between EZH2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticity” by Singh et al. addresses the functional interplay between two major repressive epigenetic mechanisms including EZH2/PRC2-mediated H3K27me3 deposition and DNA methylation during prostate cancer lineage plasticity and the emergence of neuroendocrine prostate cancer (NEPC). The team uses a comprehensive approach that integrates genetically engineered mouse models (GEMMs), patient-derived organoids (PDOs), patient tumor samples, and pharmacologic/genetic perturbations, the authors demonstrate that EZH2 inhibition or deletion results in substantial rewiring of DNA methylation, while DNMT1 deletion leads to redistribution of H3K27me3 marks, particularly at bivalent promoters. These reciprocal interactions are shown to regulate lineage-specific transcriptional programs critical for NEPC progression. While cross talk between PCR2 and DNMTs is well known in cancer and developmental biology, this current study provides important mechanistic insight into the compensatory relationship between DNA methylation and histone modifications in cancer lineage plasticity, with clear implications for therapeutic targeting strategies combining EZH2 and DNMT inhibitors.\nStrengths:\nNovel Mouse Model: Development of a new PRNE model (Pten/Rb1/Ezh2 loss with MYCN induction) represents a valuable resource for studying NEPC biology and epigenetic mechanisms.\nComprehensive Multi-Model Validation: Use of GEMMs, PDOs, CRPC and NEPC xenografts, and human clinical tumor data strengthens the translational relevance.\nMechanistic Depth: The demonstration of reciprocal, compensatory regulation between DNA methylation and EZH2/PRC2 is a major mechanistic advance.\nClinical Implications: Findings strongly support rational design of combinatorial epigenetic therapies to overcome resistance mechanisms.\nPotential for providing insight to similar disease sites involved with neuroendocrine/small cell features associated with RB1/TP53 LOF (eg: SCLC, Merkel cell).\nMajor Concerns:\nThe PRNE model develops NEPC with similar survival compared to PRN, despite significant methylome rewiring. More detail is needed on whether EZH2 loss alters tumor latency, heterogeneity, or therapeutic responses. The authors should clarify how these methylation changes impact NEPC biology beyond gene expression signatures. The authors should take note of a recent manuscript placed of Biorxiv demonstrating that Ezh2 genetic manipulation (het vs hom loss of Ezh2) implicates overall survival in GEM models of phenotypic plasticity. If the PRNE model carried heterozygous loss of Ezh2, would the biology of the model change?\nWhile the molecular interplay between EZH2 and DNMT1 is well established, the manuscript does not convincingly demonstrate phenotypic outcomes (tumor growth, progression, therapeutic response) when perturbing both pathways together. Would combined pharmacological inhibition of EZH2 and DNMT1 in vivo yield synergistic or antagonistic effects? Should SOC of be implicated in combination with these epigenetic approaches? Such functional validation is critical to strengthen the therapeutic implications.\nOverall Recommendation\nThis is a strong and timely manuscript with clear mechanistic and translational relevance to the field of prostate cancer and epigenetic therapy. However, I recommend revisions addressing the major concerns before acceptance in Nature Communications. Specifically, the authors should strengthen in vivo functional validation of dual inhibition strategies and clarify the biological consequences of methylome rewiring (based on Ezh2 genetic inhibition verse chemical inhibition). Addressing these points will significantly enhance the impact of the study."}, "author_response": "Response to Reviewers\nWe are grateful to the Reviewers for the time and effort they invested in carefully evaluating our manuscript and for their constructive feedback, which has significantly strengthened our study. Overall, the Reviewers provided positive feedback on our work. Below, we provide a point-by-point response to their comments, and all suggested changes have been incorporated into the revised manuscript.\nReviewer #1 (Remarks to the Author):\nThe authors have used cell lines, organoids and in vivo experiments to investigate a crosstalk between DNA methylation and EZH2 regulating NEPC progression. Their results showed DNA hypermethylation at H3K27me3 targets in the absence of Ezh2. Interestingly, DNMT1 deletion affected bivalent promoters with increased H3K27me3 and downregulation. The manuscript is well-written with significant findings.\nWe appreciate the positive feedback.\nI have only a few comments:\n1. What is the EZH2 expression level during PRAD to NEPC transition in PRN mice, as 38% of the H3K27me3 marks were lost and 51% acquired?\nThis is an important point. To verify expression levels of EZH2 in PRAD-to-NEPC transitioning PRN mice, we evaluated both protein and mRNA (log 2FPKM) levels of EZH2 in NEPC vs PRAD foci (Response Figure 1A- B). Overall, EZH2 expression was higher in AR-negative NEPC compared with AR-positive PRAD PRN tumor foci. We also show EZH2 mRNA and protein (western blot) levels of EZH2 in CRPC and NEPC patient-derived organoid lines, also demonstrating higher expression in NEPC models (Response Figure 1C-D). These data suggest that although EZH2 expression increases during the PRAD-to-NEPC transition, both gain and loss of H3K27me3 marks can occur. These data have been incorporated in the revised manuscript as Supplementary Figure S1A-D.\nChanges to the manuscript: Line 149; Supplementary Figure S1A-D.\nResponse Figure 1: Expression of DNA methylation regulators in advanced prostate cancer.\nA. H&E and immunohistochemistry-staining for AR, DNMT1, DNMT3B, EZH2 and TET1 in AR-positive and AR-negative histologically confirmed NEPC primary prostate tumors from PRN murine model. Scale 20µM.\nB. Expression (log2 FPKM) of EZH2 in PRAD and NEPC tumors of PRN mice (n=3 each)\nC. Western blot of DNMT1 across patient-derived organoids- PRAD (WCM1358 and MSKPCa2) and NEPC (WCM1262, WCM1078, MSKPCa10, MSKPCa4 and WCM154).\nD. Expression (row Z-score normalized TPMs) of DNMTs, and TETs in NEPC (MSKPCa10, MSKPCa4, MSKPCa24 and MSKPCa14) and PRAD (MSKPCa22, MSKPCa2 and MSKPCa19) patient-derived organoid lines.\n2. What mechanism might underlie regulation of bivalent promoters by DNMT1? Are there any other co-factors involved in directing DNMT1 to target the promoter of NE genes?\nWe appreciate the Reviewer’s insightful question regarding the regulation of bivalent promoters by DNMT1 and the potential involvement of co-factors in directing DNMT1 to the promoters of NE genes. To address this, we performed HOMER motif enrichment analyses on the bivalent promoters identified to be differentially regulated in our study after DNMT1 knockout in 22Rv1 and WCM154 (Response Figure 2A-D). These analyses revealed the presence of binding motifs for several transcription factors including ASCL2, ZEB1, OCT in 22Rv1 and PRDM1, PRDM15, SIX4 in WCM154. In 22Rv1, bivalent genes that were upregulated were found to be associated with neuronal pathways and HOMER analyses isolating ASCL2 suggest that it may recruit DNMT1 to these regions and potentially mediate its role in regulating bivalency. While these findings suggest possible mechanisms of recruitment, confirming physical interactions between DNMT1 and these factors is beyond the scope of the current study. Future work will focus on experimentally validating these interactions and further elucidating the molecular mechanisms underlying DNMT1’s regulation of bivalent promoters. This point was added to the main text and these figures have also been added to the manuscript (Supplementary Figures S7, and S10).\nChanges to the manuscript: Lines 312-313, 343-346; Supplementary Figures S7 and S10.\n3. In the Methods, please add the number of GE mice that were used in the study.\nWe added the number of genetically engineered mice used for analysis of differentially methylated regions in NEPC vs. PRAD tumors (n=2 pairs) of PRN mice and in PRNE vs. PRN NEPC tumors (n=2 pairs) in the Methods section. We also included the number of GEMs used for Kaplan-Meier survival (Figure S4A) and histology distribution (Figure S4B-C) in the respective plots.\n4. Please add scale bar to S1A and S6C.\nWe have added scale bars to all immunohistochemistry images in Figure S1A and Figure S8A and refer to them in their respective figure legends.\nChanges to the manuscript: Lines 438-440 and 483.\nReviewer #2 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nWe appreciate your time and effort in carefully reviewing this manuscript.\nReviewer #3 (Remarks to the Author):\nIn this manuscript, Singh and colleagues undertake integrative analyses of prostate cancer models (murine and human) to profile differences in gene expression and H3K4me3/H3K27me3 deposition. This is important as prostate cancer lineage plasticity is associated with changes in DNA methylation and PRC2 activities. EZH2 is highly unregulated in neuroendocrine prostate cancers, which result from the clinical use of high-affinity androgen receptor pathway inhibitors.\nThe data presented here are of high quality, indicative of good technical expertise, and the interpretations are of interest. They focus on aspects of ‘bivalency’ in different model contexts, the presence of H3K4me3/H3K27me3 marks at CpG-rich promoters in mouse/human, and how they respond when Ezh2 (H3K27me3 methyltransferase) and Dnmt1 (maintenance CpG methylase) activities are inhibited.\nOverall, their data support a mutual crosstalk between Dnmt1 and PRC2-mediated H3K27me3 distribution patterns in castration-resistant prostate adenocarcinoma (PRAD). Dnmt1 silencing leads to downregulation of neuroendocrine (NE) related genes and pathways in neuroendocrine prostate cancer (NEPC) and an upregulation of similar pathways in PRAD.\nThis is a very useful contribution to understanding epigenetic cross-talk, clinical understanding of the efficacy of epigenetic inhibitors against NEPC/PRAD, and the fact that the impact of epigenetic inhibition is context-dependent.\nWe appreciate the positive feedback.\nI have a few comments.\nThe authors need to show formal evidence that Dnmt1 KO and decitabine treatment result in changes in DNA methylation through reliable methods (HPLC or WGBS, but not using 5mC antibody-based assays that are notoriously unreliable). Additionally, they should demonstrate the impact of Dnmt1 KO and decitabine treatment on the expression of known (general) genes and repeats whose silencing is maintained by DNA methylation in somatic cells.\nWe thank the Reviewer for raising this important point. To address the impact of decitabine treatment on DNA methylation, we analyzed reduced representation bisulfite sequencing (RRBS) data from decitabine-treated WCM154 samples1. We had previously shown a global reduction in DNA methylation levels upon decitabine treatment in WCM1541. A representative panel of genes (RXFP4, HES7, HS3ST6, CHRNA4) that exhibit DNA methylation near transcriptional start sites were upregulated following decitabine treatment, as shown below (Response Figure 3A-B), with their mRNA levels significantly higher after decitabine. The same genes (RXFP4, HES7, HS3ST6, CHRNA4) were also upregulated upon DNMT1 silencing (Response Figure 3C). This supports the efficacy of decitabine treatment on reducing DNA methylation, associated with de-repression of specific target genes. Furthermore, we found a significant positive correlation between differentially expressed genes following decitabine treatment and those regulated after DNMT1 silencing, reinforcing the functional overlap between these two perturbations (Response Figure 3D). These data have been incorporated into the revised manuscript (Supplementary Figure S5).\nChanges to the manuscript: Line 280; Supplementary Figure S5.\nThe authors should also consider the model in which active histone modifications serve a supportive, rather than an essential regulatory, role in transcription, and silencing leads to a default (passive) accumulation of repressive marks (DNA methylation and H3K27me3). How would this impact the emergence of altered epigenetic profiles in prostate cancer undergoing cellular transitions?\nAdelman K. Nascent transcription as a predictor and driver of histone modifications. Nat Genet. 2022 Mar;54(3):223-224. doi: 10.1038/s41588-021-01004-9. PMID: 35273400.\nThis is an interesting point. Our epigenetic profiling of clinical samples and integrative analyses using DNA methylation and H3K27me3 CUT&Tag demonstrated that H3K27me3 may have a more pronounced impact on gene expression compared to DNA methylation in NEPC vs PRAD prostate cancers , which has been included as Supplementary Figure S3E and shown below.\nWhile there are prior studies that have supported active histone marks playing a supportive role in transcription2,3, other studies have demonstrated how active histones can critically regulate transcriptional machinery4. The mechanisms of heterochromatin mediators regulating gene expression remain complex, and resolving active and passive roles of repressive marks in prostate cancer lineage plasticity will require further investigation. We have included these points in the Discussion and acknowledge the broader implications of this complexity on altering epigenetic profiles during prostate cancer lineage transitions.\nChanges to the manuscript: Lines 366.\nReviewer #4 (Remarks to the Author):\nThe manuscript entitled “Crosstalk between EZH2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticity” by Singh et al. addresses the functional interplay between two major repressive epigenetic mechanisms including EZH2/PRC2-mediated H3K27me3 deposition and DNA methylation during prostate cancer lineage plasticity and the emergence of neuroendocrine prostate cancer (NEPC). The team uses a comprehensive approach that integrates genetically engineered mouse models (GEMMs), patient-derived organoids (PDOs), patient tumor samples, and pharmacologic/genetic perturbations, the authors demonstrate that EZH2 inhibition or deletion results in substantial rewiring of DNA methylation, while DNMT1 deletion leads to redistribution of H3K27me3 marks, particularly at bivalent promoters. These reciprocal interactions are shown to regulate lineage-specific transcriptional programs critical for NEPC progression.\nWhile cross talk between PCR2 and DNMTs is well known in cancer and developmental biology, this current study provides important mechanistic insight into the compensatory relationship between DNA methylation and histone modifications in cancer lineage plasticity, with clear implications for therapeutic targeting strategies combining EZH2 and DNMT inhibitors.\nStrengths:\nNovel Mouse Model: Development of a new PRNE model (Pten/Rb1/Ezh2 loss with MYCN induction) represents a valuable resource for studying NEPC biology and epigenetic mechanisms.\nComprehensive Multi-Model Validation: Use of GEMMs, PDOs, CRPC and NEPC xenografts, and human clinical tumor data strengthens the translational relevance.\nMechanistic Depth: The demonstration of reciprocal, compensatory regulation between DNA methylation and EZH2/PRC2 is a major mechanistic advance.\nClinical Implications: Findings strongly support rational design of combinatorial epigenetic therapies to overcome resistance mechanisms.\nPotential for providing insight to similar disease sites involved with neuroendocrine/small cell features associated with RB1/TP53 LOF (eg: SCLC, Merkel cell).\nWe appreciate the positive feedback.\nMajor Concerns:\nThe PRNE model develops NEPC with similar survival compared to PRN, despite significant methylome rewiring. More detail is needed on whether EZH2 loss alters tumor latency, heterogeneity, or therapeutic responses. The authors should clarify how these methylation changes impact NEPC biology beyond gene expression signatures. The authors should take note of a recent manuscript placed of Biorxiv demonstrating that Ezh2 genetic manipulation (het vs hom loss of Ezh2) implicates overall survival in GEM models of phenotypic plasticity. If the PRNE model carried heterozygous loss of Ezh2, would the biology of the model change?\nTo address this comment, we have now included survival data of PRNE mice (n=5) (Response Figure 4A). Similar to data shown in Jacobi et al. study5, we observed improved survival in EZH2-heterozygous mice compared to EZH2-homozygous and EZH2-wildtype mice. Unfortunately, we do not have enough PRNE mice to fully dissect its molecular phenotype. However, histological evaluation of n=2 PRNE mice showed only 30% of the tumor to be NEPC at 12 weeks (Response Figure 4C) compared to PRNE mice where 95% tumor was NEPC at similar age (Response Figure 4B). Overall, these data suggest that deleting both EZH2 alleles does not prevent aggressive NEPC progression. This was added to the revised manuscript and Supplementary Figure S4.\nChanges to the manuscript: Lines 204-209; Supplementary Figure S4.\nWhile the molecular interplay between EZH2 and DNMT1 is well established, the manuscript does not convincingly demonstrate phenotypic outcomes (tumor growth, progression, therapeutic response) when perturbing both pathways together. Would combined pharmacological inhibition of EZH2 and DNMT1 in vivo yield synergistic or antagonistic effects? Should SOC of be implicated in combination with these epigenetic approaches? Such functional validation is critical to strengthen the therapeutic implications.\nOur study demonstrates increased sensitivity of the DNMT inhibitor decitabine in EZH2-deleted PRN mouse organoids and increased sensitivity of the EZH2 inhibitor tazemetostat in DNMT1-deleted PRN organoids in vitro (Response Figure 5A-C). This suggests a potential cross-pathway priming effect which may have therapeutic relevance. However, we found that the combination of DNMT+EZH2 inhibition showed varying effects on cell viability across models (Response Figure 5D-E) with the NEPC model MSKPCa10 having the highest response to decitabine with EPZ011989 (EZH2 inhibitor). We followed this up with an in vivo combination study, which was unfortunately limited due to toxicity. Treatment of WCM154 PDX models with decitabine for a week resulted in a reduction in tumor volume (Response Figure 5F). We extended the treatment time to a month, performing castration surgery after tumor reached 75mm3 and started treatment once the tumor reached 150 mm3. For the initial 7 days only decitabine was administered, while for next 21 days both decitabine and EPZ011989 were administered. Unfortunately, the mice in this experiment were sick and we had to euthanize following our animal protocol before the end of treatment timepoint. Although we observed on-target effects of DNMT and EZH2 inhibitors in the tumors of euthanized mice (Response Figure 5G-H), the dosing and administering schedules were toxic. Further investigation is required to determine the efficacy, dosing, and safety of combination therapy. Our study also supports future evaluation of how changes in DNA methylation could contributed to acquired resistance to EZH2 inhibition and vice versa. These data and points have been added to the manuscript.\nChanges to the manuscript: Lines 348-352. Experimental details of the in vitro and in vivo inhibitor study have been added in the method section in lines 450-455, 484-492 and 495-502; Supplementary Figure S11."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have fully addressed my previous concerns. I have no further questions.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "The authors have addressed my comments in full.\nMany thanks.", "reviewer_4": "The authors have made satisfactory changes to my concerns. I support its publication."}, "author_response": ""}]

Decision letter