SETDB1 interactions with PELP1 contributes to breast cancer endocrine therapy resistance

MCF7, ZR75, and HEK293T cell lines were purchased from the American-Type Culture Collection (ATCC) and maintained in ATCC recommended medium. All model cells utilized were free of mycoplasma contamination and STR DNA profiling of the cells was used to confirm identity. MCF7-TamR cells were cultured in medium supplemented with 1 µmol/L of tamoxifen (H7904, Sigma, St. Louis, MO). MCF7-FR cells were cultured in medium supplemented with 1 µmol/L of fulvestrant (MedChem Express, Monmouth Junction, NJ) for 6 months to develop resistance. The SETDB1 antibody (11231-1-AP) was obtained from Proteintech (Rosemont, IL). The PELP1 antibody (A300-180A) was purchased from Bethyl Laboratories (Montgomery, TX). The ERα (04-820) and β-Actin antibodies (A-2066) were purchased from Millipore Sigma (Burlington, MA). The phospho-ER (Ser167) antibody (PA5-37570) was purchased from Invitrogen (Waltham, MA). The mCherry antibody (632543) was obtained from Takara Bio (San Jose, CA). The GFP antibody (632460) was obtained from Clontech. Antibodies for GST (2624), p-Akt (4060), Akt (9272), tri-methyl lysine motif (K-me3,14680) and GAPDH (8884) were purchased from Cell Signaling Technology (Beverly, MA). For IHC analysis, Ki67 antibody (ab16667) was purchased from Abcam (Cambridge, MA) and p-Akt (05-1003) antibody was purchased from Millipore Sigma.

MCF7 and ZR75 cells stably expressing SETDB1-shRNA were generated using lentivirus expressing SETDB1 shRNA (TRCN0000276169, TRCN0000276105, Sigma). MCF7 and ZR75 cells stably expressing PELP1-shRNA were created using validated human specific lentiviral PELP1-shRNA particles (TRCN0000159883, Sigma). MCF7 cells expressing T7-cyto-PELP1 were earlier described [22]. MCF7 and ZR75 cells stably expressing SETDB1 were generated using pLV-Bsd-EF1A-SETDB1 vector. HEK293T cells expressing GFP-SETDB1 were generated using pLV-Bsd-EF1A-EGFP-SETDB1 vector. MCF7, ZR75 and HEK293T cells expressing mCherry-cyto-PELP1 were generated using pLV-Hygro-EF1A-Cherry-PELP1-Cyto-NLSmt (KKK to EEE) vector. HEK293T cells stably expressing GST-Akt were created using the lentiviral vector pLV-Hygro-EF1A-GST-AKT. Lentiviral particles expressing non-targeted shRNA (SHC016-1EA, Sigma), GST-vector (pLV-Puro-EF1A-GST vector), mCherry-vector (pLV-mCherry-Puro-EF1A vector) were used to generate control cells. All the vectors are custom made by Vector Builder (https://​en.​vectorbuilder.​com). Stable clones were generated using puromycin (1 μg/mL) or hygromycin (100 μg/mL) selection and pooled clones were used for all studies.

HEK293T cells stably expressing ERE firefly luciferase reporter and ERα were transfected with SETDB1 expressing vector or control vector using Turbofect transfection reagent (Thermo Fisher Scientific, Waltham, MA). MCF7 cells stably expressing SETDB1-shRNA or non-targeted shRNA were transduced with ERE luciferase reporter. The Renilla reporter plasmid was co-transfected and used for data normalization. After 48 h, cells were treated with E2 (10^–8 M) for 24 h and luciferase activity was measured using the Dual luciferase assay system (Promega, Madison, WI) using a luminometer.

Mapping of the PELP1-SETDB1 interaction region using yeast-two hybrid assay was done as described [23]. Yeast cells were co-transfected with a gal4 activation domain (GAD) fusion GAD-SETDB1, along with gal4 binding domain (GBD) vector or GBD fusions of various domains of PELP1. Growth was recorded after 72 h on selection plates lacking leucine and tryptophan (− LT) or adenine, histidine, leucine, and tryptophan (− AHLT). BC cells were stimulated either with E2 or 10% fetal bovine serum (FBS). For E2 stimulation, MCF7 and ZR75 cells were cultured in Dextran Coated Charcoal stripped serum (DCC) supplemented medium for 48 h and then stimulated with E2 (10^–8 M). To simulate the growth factor driven signaling, MCF7 and ZR75 model cells were serum-starved for 24 h and stimulated with medium containing 10% serum. Cell lysates were prepared by RIPA buffer (Thermo Fisher Scientific) containing protease and phosphatase inhibitors and Western blot analysis was performed. For co-immunoprecipitation analysis, the lysates were incubated with indicated antibody or IgG control overnight at 4 °C, and then incubated with Protein A/G beads (Thermo Fisher Scientific) for 2 h, overnight incubation with GST beads (17-0756-01, GE Healthcare, Chicago, IL) or T7 Tag Antibody Agarose (69026, Novagen) or GFP-TRAP and RFP-TRAP Agarose (ChromoTek) at 4 °C. Interactions were analyzed by Western blotting using indicated antibodies. For GST pull-down assays, GST-tagged Akt1 protein was purified from HEK293T cells.

Purification of PELP1 protein was done using baculovirus system as earlier described [24]. GST-tagged Akt1 protein was purified from HEK293T cells using GST-pull down assay. Recombinant SETDB1 protein was purchased from Active Motif (cat#31452, Carlsbad CA) and manufacturer’s protocol was followed for the methylation assay. Briefly, SETDB1, Akt and PELP1 proteins were incubated in 50 mM Tris–HCl (pH 8.6), 0.02% Triton X-100, 2 mM MgCl₂, 1 mM TCEP, 50 µM S-adenosyl-methionine (SAM) buffer for 4 h at 37 °C. The reaction was stopped by the addition of Laemmli reducing sample buffer and run on 8% electrophoresis gel.

Cell viability was determined using MTT assay as described [25]. For the clonogenic assays, model cells (500 cells/well) were seeded in 6 well plates and survival was analyzed after 14 days. To test the drug effect on colony formation, the model cells were treated with E2 (10^–8 M) in the presence or absence of tamoxifen or Mithramycin A (Millpore Sigma) for 5 days and allowed to grow for another 7 days. The cells were fixed in ice-cold methanol and stained with 0.5% crystal violet solution. For 3D cell culture, model cells suspended in matrigel (6 × 10³/40 μL) were plated onto a culture plate, incubated at 37 °C for 10 min to solidify and subsequently cultured for 10 days in DMEM/F12 growth medium. The relative size of the colonies was analyzed by ImageJ software.

Total RNA from MCF7 cells stably expressing control non-targeted shRNA or SETDB1 shRNA was isolated using RNeasy mini kit (Qiagen). The RNA-Seq library was prepared using Illumina TruSeq stranded mRNA Sample preparation kit (Illumina) and sequencing was performed at Greehey Children’s Cancer Research Institute Genome Sequencing Facility (UT Health, SA) using 50 bp single read sequencing module with Illumina HiSeq 3000 sequencing platform. Sequence reads were mapped to UCSC hg19 genome using TopHat2 aligner and quantified to NCBI RefSeq genes using HTSeq [26]. Differential expression analysis was conducted using DEseq2 [27] and significant genes with fold change > 2 and adjusted p value < 0.05 were used for interpreting functional enrichment pathways. Gene set enrichment analysis (GSEA) (http://​www.​broadinstitute.​org/​gsea/​index.​jsp) [28] was used to perform gene set enrichment analysis. The Pheatmap package (1.0.12) was used to create heatmaps of differential genes. PELP1 RNA-seq analysis results used in this study was previously published [29]. RNA-seq data has been deposited in the GEO database under GEO accession number GSE187398. Biological network integration for prediction of gene interaction was done by GeneMANIA prediction server [30]. Biomolecular interaction networks were visualized using Cytoscape (V.3.8.2) [31]. Tumor subgroup SETDB1 gene expression analyses was done using UALCAN [32]. Comparison of SETDB1 gene expression in normal and breast tumor tissues was done by TNMplot [33]. Gene-expression correlation analyses of TCGA breast cancer dataset was done using bc-GenExMiner 3.0[34]. For Real-time quantitative PCR (RT-qPCR) analyses total RNA was isolated using Trizol Reagent (Invitrogen). Reverse transcription was performed using SuperScript III First Strand kit (Invitrogen). RT-qPCR was done using SYBR Green (Thermo Fisher Scientific) with the primers included in the Additional file 1.

All animal studies were conducted after obtaining UT Health San Antonio IACUC approval, and in accordance with IACUC guidelines. SCID mice (n = 5, per group) were implanted with E2 pellet (cat# SE-121, Innovative Research of America, Sarasota, FL) as described previously [35]. Model cells MCF7-Control, MCF7-SETDB1, MCF7-PELP1-KD, MCF7-PELP1-KD + SETDB1 (2 × 10⁶ cells) were mixed with equal volume of matrigel and injected orthotopically into the mammary fat pads of 8-week-old SCID mice. Tumor growth was measured using calipers at weekly intervals, and tumor volume was calculated using a modified ellipsoidal formula: tumor volume = 1/2(L × W²), where W is the transverse diameter and L represents longitudinal diameter. At the end of the experiment, mice were euthanized, and tumors were processed for histological studies.

Immunohistochemical analysis was conducted using an established protocol [25]. Briefly, sections were blocked with normal horse serum (Vector Labs, Burlingame, CA) followed by overnight incubation with primary antibody [Ki-67 (1:100); p-Akt(S473) (1:100)] and subsequent secondary antibody incubation for 30 min at room temperature. Percentage of Ki-67 positive cells and the staining intensity of p-Akt (S473) was calculated in five randomly selected microscopic fields. Quantification of D-HSCORE value was done by ImageJ software as described previously [36].

The student’s t-test and one-way ANOVA were used to analyze the statistical differences with GraphPad Prism 7 software (GraphPad Prism Software, San Diego, CA). All the data represented in bar graphs are shown as mean ± SEM. A value of p < 0.05 was considered as statistically significant.

To study the status of SETDB1 expression in BC, we examined the degree of SETDB1 alterations using TNM-plot that enables comparison of gene expression between tumor and normal tissues [37]. Results showed that SETDB1 is highly expressed in BC compared to normal tissues (Fig. 1A). Further, analyses using TCGA data bases showed that SETDB1 is highly expressed in ER⁺ and triple negative breast cancer (TNBC) compared to normal breast (Fig. 1B). To understand the role of SETDB1 in ER⁺ BC, we have established ER + BC models with stable knockdown (KD) of SETDB1 by using two distinct validated SETDB1 shRNAs. Western blot analyses confirmed knockdown of SETDB1 in both MCF7 and ZR75 cells (Fig. 1C). When cultured in E2 supplemented medium, SETDB1 KD cells showed decreased growth rates compared to control cells (Fig. 1D).

To determine the mechanisms by which SETDB1 regulate the cell viability of ER⁺ BC cells, we performed RNA-Seq of MCF7 control and SETDB1-KD cells cultured in E2 supplemented medium. These studies identified 245 down-regulated genes and 409 upregulated genes upon SETDB1 KD (Fig. 1E). Gene set enrichment analysis (GSEA) revealed the positive correlation between SETDB1-regulated genes with signatures of early and late estrogen response targets (Fig. 1F). Further analysis using the KEGG pathway database confirmed that down-regulated genes upon SETDB1-KD were involved in ER-signaling, breast cancer, and PI3K-Akt signaling. (Fig. 1G). We then examined whether SETDB1 regulates ER transcription using ERE reporter assays. In HEK293T cells, expression of SETDB1 enhanced ER-driven ERE-Luc reporter activity in a dose dependent manner (Fig. 1H). Further, SETDB1-KD significantly reduced the ERE reporter activity in MCF7 cells (Fig. 1I). Moreover, analyses of the RNA-seq data confirmed down regulation of several known ER target genes (Fig. 1J). We also independently validated that SETDB1-KD reduces ER target genes (Fig. 1K). Collectively, these results suggest that SETDB1 regulates the expression of subsets of genes involved in ER⁺ BC progression.

We next analyzed the SETDB1 regulated genes identified from RNA-seq analysis and found that these genes are positively correlated with the signatures of AKT pathway and tamoxifen resistance (Fig. 2A). Several genes known to be associated with tamoxifen therapy resistance were down regulated in SETDB1-KD cells (Fig. 2B). Further, we independently confirmed SETDB1 regulation of tamoxifen resistance genes by RT-qPCR (Fig. 2C). We then examined whether SETDB1 plays a role in tamoxifen response using cell viability and survival assays. Knock down of SETDB1 significantly enhanced the ability of tamoxifen to reduce cell viability (Fig. 2D) and cell survival compared to control cells (Fig. 2E). We next confirmed whether SETDB1 regulates activation of Akt1 in ER⁺ BC cells. Knockdown of SETDB1 in MCF7 and ZR75 cells reduced the levels of phospho-Akt compared to controls (Fig. 2F). Accordingly, overexpression of SETDB1 increased activation of Akt and phosphorylation of its substrate ER at Ser167 (Fig. 2G). Collectively, these results suggest that SETDB1 may participate in tamoxifen resistance by regulating Akt-mediated ER signaling.

Since Akt1 activation is implicated in endocrine therapy resistance [38] and our RNA-seq data suggested that SETDB1 regulates Akt-mediated ER signaling; we examined the status of SETDB1 in endocrine therapy resistant model cell lines. Western blot analysis confirmed tamoxifen-resistant and fulvestrant-resistant MCF7 models have higher levels of SETDB1 compared to parental MCF7 cells (Fig. 3A). Cell viability assays showed that knockdown of SETDB1 in MCF7-TamR and MCF7-FR cells sensitized them to tamoxifen and fulvestrant treatment respectively (Fig. 3B, C). Further analyses using Western blotting showed decreased Akt1 activation in SETDB1-KD cells compared to controls (Fig. 3D). Further, previous studies have shown cytoplasmic localization of PELP1 occurs in breast tumors and contributes to endocrine resistance via Akt1 activation [22]. Therefore, we next examined if SETDB1 plays a role in the activation of Akt1 using PELP1 cytoplasmic localization (PELP1cyto) model cells. We observed that SETDB1-KD substantially decreased the colony formation ability of MCF7-PELP1cyto cells (Fig. 3E, F) and sensitized them to tamoxifen treatment compared to control cells (Fig. 3G). Further, knockdown of SETDB1 substantially reduced Akt phosphorylation mediated by PELP1 cytoplasmic localization (Fig. 3H). We confirmed the role of SETDB1 in endocrine therapy resistance using Mithramycin A, a small molecular inhibitor previously shown to reduce SETDB1 expression via transcriptional down regulation [39]. In ER⁺ BC MCF7 and ZR75 cell lines, treatment with Mithramycin A significantly reduced SETDB1 expression (Fig. 3I). Further, Mithramycin A treatment significantly reduced the colony formation of BC cells in a dose dependent manner (Fig. 3J) and enhanced the efficacy of tamoxifen (Fig. 3K). Mithramycin A treatment reduced cell viability of MCF7-TamR and MCF7-FR cells when compared to tamoxifen or fulvestrant treatment respectively (Fig. 3L, M). Collectively, these data suggest that SETDB1 mediated activation of Akt1 may contributes to endocrine therapy resistance.

Our ongoing yeast two-hybrid library screening studies identified SETDB1 as a potential PELP1‐binding protein. To further confirm the specificity and domains of PELP1 interactions with SETDB1, we repeated the yeast-two-hybrid screen assay with co-transformation of a GAD-SETDB1 plasmid along with vectors expressing various domains of PELP1 as GBD fusions. We monitored the interactions via survival assays in selection medium using yeast cells which stably express adenine and  histidine, nutrient reporter genes under the control of GAL response elements. The GBD-PELP1-601-880 or GBD-PELP1-960-1130 and GAD-SETDB1 transformed colonies grew in medium lacking AHLT, whereas the cells co-transformed with the control GBD vector or GBD-PELP1-400 or GBD-PELP1-401-600 did not grow (Fig. 4A), suggesting a potential interaction of SETDB1 with the C-terminal region of PELP1. To verify that the observed interaction between PELP1 and SETDB1 in the yeast screen also occurs in BC cells, we performed immunoprecipitation assays using two widely used ER⁺ BC cells MCF7 and ZR75. In both models, immunoprecipitation of PELP1 followed by Western blotting confirmed that PELP1 interacts with SETDB1 (Fig. 4B). We next confirmed these interactions using SETDB1 immunoprecipitation followed by PELP1 Western blotting (Fig. 4C). Further, we validated the potential interaction between PELP1 and SETDB1 proteins using GFP-tagged PELP1 expressing MCF7 and ZR75 cell lines. In both models, GFP pull-down assays confirmed the interaction of SETDB1 with GFP-PELP1 (Fig. 4D). Since, SETDB1 knockdown decreased Akt phosphorylation in PELP1cyto cells, we examined whether cytoplasmic PELP1 interact with SETDB1 using epitope tag PELP1cyto expressing MCF7 and ZR75 cells. Immunoprecipitation with T7 tag (MCF7-PELP1cyto) and mCherry tag (ZR75-PELP1cyto) antibodies revealed that PELP1cyto interacts with endogenous SETDB1 (Fig. 4E, F). We also utilized full length GST tagged PELP1 protein to confirm PELP1 interaction with SETDB1. We incubated ZR75 whole cell lysates with GST-PELP1 and confirmed GST-PELP1 full length interacts with SETDB1 (Fig. 4G). Collectively, these results from multiple assays confirm that PELP1 is novel interacting protein of SETDB1.

To further explore the functional relationship between PELP1 and SETDB1 interactions in ER⁺ BC, we established ER⁺ BC models (MCF7 and ZR75) that stably overexpress SETDB1 with and without PELP1 KD (Fig. 5A). As expected from previous studies, overexpression of SETDB1 significantly enhanced the colony formation ability, while PELP1-KD significantly attenuated the SETDB1 mediated increase in the clonogenicity of both MCF7 and ZR75 models (Fig. 5B). Further, SETDB1 overexpression models exhibited resistance to tamoxifen treatment which was decreased significantly by PELP1-KD (Fig. 5C, D). To examine whether PELP1-SETDB1 interactions in the cytoplasm contribute to the resistance phenotype, we attempted to rescue the resistance phenotype in PELP1-KD + SETDB1 clones by expressing shRNA resistant PELP1cyto plasmid. The results showed overexpression of the PELP1cyto plasmid in PELP1-KD + SETDB1 clones rescued the resistance phonotype (Fig. 5E). These results suggest that SETDB1 and PELP1 interactions in the cytoplasm are essential in promoting resistance to endocrine therapy. We then validated the effect of PELP1-KD on SETDB1 mediated oncogenic function under 3D culture conditions. Results showed that SETDB1 promoted cell growth and PELP1-KD attenuated SETDB1 driven 3D growth of BC cells (Fig. 5F). Collectively, these results support that PELP1 is needed for SETDB1 mediated growth and therapy resistance of BC cells.

Previous studies have shown that SETDB1 regulates Akt activation via methylation [13, 40]. Further, cytoplasmic PELP1 is also implicated in the activation of Akt leading to endocrine therapy resistance [22]. Since PELP1 interacted with SETDB1, we examined whether PELP1 plays a role in SETDB1 mediated Akt activation. Protein interaction network analyses with the GeneMANIA database predicted that SETDB1 might have physical or functional relation with PELP1 and Akt1, which are involved in ER non-genomic pathway (Fig. 6A). By comparing with previous PELP1-KD RNA-Seq enrichment data using an ER⁺ BC model, we found that both SETDB1 and PELP1 mediated genes were positively correlated with ESR1 signatures regulated via Akt (Fig. 6B). We then examined whether PELP1, SETDB1 and Akt form a trimeric complex by GST pull- down assays. MCF7 cell lysates were incubated with GST-Akt and GST pull-down assays confirmed the presence of PELP1 and SETDB1 in the eluates (Fig. 6C). We independently confirmed trimeric interaction using HEK293T cells that express GFP-tagged SETDB1. GFP pull down assays using GFP-TRAP beads confirmed trimeric interaction of Akt, SETDB1 and PELP1 proteins (Fig. 6D).

Since cytoplasmic PELP1 is implicated in the activation of Akt leading to endocrine resistance, we examined whether PELP1cyto also forms the trimeric complex using co-transfection of mCherry-PELP1cyto, or GFP-SETDB1 plasmids alone or together in GST-Akt expressing HEK293T cells. GST pull-down assays confirmed formation of the Akt trimeric complex (Fig. 6E). PELP1 is shown to modulate enzymatic activities of several methylase or demethylase enzymes by direct interactions [24, 41]. Therefore, we examined whether PELP1 affects methyltransferase activity of SETDB1 We used total lysates from model cells expressing GST-Akt, SETDB1 or PELP1 alone or together and conducted immunoprecipitation using a tri-methyl lysine (K-me3) antibody followed by Western blotting. Results showed that overexpression of PELP1cyto increased both methylation and phosphorylation of Akt mediated by SETDB1 (Fig. 6F). We then examined if PELP1 affects the methyltransferase activity of SETDB1 using an in vitro methylation assay. The results showed that addition of purified PELP1 protein enhanced SETDB1 methyltransferase activity shown by an increase in methylation of Akt (Fig. 6G).

Methylation of Akt is critical for its membrane translocation and activation. Since we confirmed that PELP1 interacts with SETDB1 and promotes its methyltransferase activity, we tested whether PELP1 is needed for SETDB1 mediated Akt activation. We generated MCF7 and ZR75 model cells stably expressing SETDB1 with or without PELP1-KD. We confirmed SETDB1 regulation of estrogen (E2) mediated Akt activation by stimulating hormone-deprived cells with E2 for 15 min. Results showed a substantial activation of Akt in SETDB1 overexpressing cells which was abolished with PELP1 KD (Fig. 6H). To confirm PELP1 function in serum-induced Akt activation, model cells were serum starved for 24 h and then stimulated with serum for 15 min. Further analyses showed increased Akt activation and ER phosphorylation at the known Akt phosphorylation site Ser167 in SETDB1 overexpressing cells which was attenuated with PELP1 KD (Fig. 6I). Finally, overexpression of shRNA resistant PELP1cyto resulted in rescuing the Akt activation in PELP1-KD + SETDB1 cells (Fig. 6J). Collectively, these results suggest that PELP1 can enhance SETDB1 mediated Akt methylation and therefore PELP1 is required for optimal activation of Akt by SETDB1.

We examined whether PELP1 is required for SETDB1 mediated ER⁺ BC progression in vivo using xenografts of MCF7 model cells that express SETDB1 with or without PELP1 KD. MCF7-SETDB1 xenografts showed increased tumor volume compared to the control vector transfected group (Fig. 7A). Interestingly, knockdown of PELP1 in SETDB1 overexpression (MCF7-PELP1KD + SETDB1) xenografts resulted in significantly reduced tumor growth compared to MCF7-SETDB1 xenografts, suggesting that PELP1 KD effectively reduces SETDB1 mediated tumor progression (Fig. 7A). Ki67 staining of the tumor sections revealed greater proliferation in the MCF7-SETDB1 xenografts compared to the MCF7-control and MCF7-PELP1 KD + SETDB1 tumors (Fig. 7B, D). Importantly, MCF7-PELP1 KD + SETDB1 tumors showed decreased expression of phospho-Akt compared to MCF7-SETDB1 tumors (Fig. 7C, E). These results suggest that PELP1 is essential for SETDB1 driven tumor growth in vivo. We also examined the human TCGA database to determine if there is a correlation between PELP1 and SETDB1 expression in ER + BC. The results showed positive correlation of PELP1 and SETDB1 in ER + BC (Fig. 7F). Collectively, these results suggest the interactions between PELP1 and SETDB1 and conclude that they play an important role in ER + BC progression by enhancing Akt signaling (Fig. 7G).