Although ribosomal protein S6 kinase A3 (RSK2) activation status positively correlates with patient responses to antiestrogen hormonal therapies, the mechanistic basis for these observations is unknown. Using multiple in vitro and in vivo models of estrogen receptor–positive (ER+) breast cancer, we report that ERα sequesters active RSK2 into the nucleus to promote neoplastic transformation and facilitate metastatic tumor growth. RSK2 physically interacted with ERα through its N terminus to activate a proneoplastic transcriptional network critical to the ER+ lineage in the mammary gland, thereby providing a gene signature that effectively stratified patient tumors according to ERα status. ER+ tumor growth was strongly dependent on nuclear RSK2, and transgenic mice engineered to stably express nuclear RSK2 in the mammary gland developed high-grade ductal carcinoma in situ. Mammary cells isolated from the transgenic model and introduced systemically successfully disseminated and established metastatic lesions. Antiestrogens disrupted the interaction between RSK2 and ERα, driving RSK2 into the cytoplasm and impairing tumor formation. These findings establish RSK2 as an obligate participant of ERα-mediated transcriptional programs, tumorigenesis, and divergent patient responses to antiestrogen therapies.
Significance: Nuclear accumulation of active RSK drives a protumorigenic transcriptional program and renders ER+ breast cancer susceptible to endocrine-based therapies. Cancer Res; 78(8); 2014–25. ©2018 AACR.
Intrinsic or therapy-induced resistance to endocrine-targeted therapy for estrogen receptor–positive (ER+) breast cancer is a major obstacle to improving patient outcomes (1). Therefore, there is an ongoing effort to identify predictive biomarkers that will indicate responsiveness to therapy. ERK1/2 in response to growth factor and cytokine signaling initiates a phosphorylation cascade that results in the activation of the Ser/Thr protein kinase, p90RSK (RSK; refs. 2, 3). Interestingly, active RSK correlates with disease-free survival and response to chemotherapy in ER+ breast cancer (4, 5). The kinase domains of the four members that comprise the RSK family are very similar but family members appear to have both redundant and separate contributions to development, homeostasis, and disease etiologies (6, 7). RSK controls several oncogenic processes, including proliferation, viability, and motility and, therefore, has accordingly been implicated in the etiology of numerous cancers including breast (8–16). However, despite detailed knowledge on RSK oncogenic functions, the mechanistic rationale that underpins the correlation of active RSK with endocrine-based responsiveness in ER+ breast cancer remains an enigma.
Here, we report that ERα physically interacts with RSK2, resulting in accumulation of RSK2 in the nucleus. This interaction activates a transcriptional network that is critical for ER+ tumor growth and provides a gene signature that stratifies patient tumors according to ERα status. Antiestrogens disrupt the association of ERα and RSK2 and drive RSK2 into the cytoplasm, which results in severely impaired tumorigenic capacity. Furthermore, forced nuclear RSK2 in a novel transgenic mouse model triggers neoplastic transformation of ER+ epithelial cells within the native mammary gland. Taken together, our results reveal that the nuclear sequestration of RSK2 by ERα activates a proneoplastic transcription program that is susceptible to disruption by antiestrogen therapy. These data provide a mechanistic explanation for the clinical observations that RSK2 correlates with responsiveness to endocrine-based therapies.
Materials and Methods
Additional experimental procedures, antibodies, and reagents are listed in the Supplementary Data.
All procedures involving animals were done in accordance with current federal (NIH Guide for Care and Use of Laboratory Animals) and university guidelines and were approved by the University of Virginia and Vanderbilt University Institutional Animal Care and Use Committee.
C57BL/6J mice carrying a transgene composed of the mouse mammary tumor virus-long terminal repeat (MMTV-LTR) linked to sequences encoding the hemagglutin (HA) tag, the NLS from SV40 (PKKKRKV) and murine RSK2 (MMTV-HA-NLS-RSK2) were generated by the University of Virginia Gene Targeting and Transgenic Facility (C57BL/6JMMTV-HA-NLS-RSK2). Ten backcrosses were performed to wild-type (WT) C57BL/6J. At 12 weeks, 6-month, or 16-month virgin female MMTV-NLS-RSK2 or WT mice were euthanized and the mammary glands analyzed.
Cell culture and treatment
Mycoplasma-free MCF-7, BT-474, and ZR-75-1 cells were obtained, cultured, and authenticated as directed by ATCC. Cells were serum starved and treated as described in the Supplementary Data.
Single epithelial cells were isolated from the mammary glands of 16-month-old mice and spheres cultured as described (17). For two passages (every 9 days) spheres were dissociated with 1× trypsin and equal number of cells from WT and NLS-RSK2 spheres were replated. Alternatively, p0 spheres (day 9) were transduced with GFP-luciferase and after 3 days the linearity of the bioluminescence signal was tested (15).
The Cooperative Human Tissue Network (CHTN) provided the human breast cancer tissue and clinical data. Every CHTN institution has obtained human subjects assurance from the Office of Human Research Protections, DHHS. The assurance document provides agreement that the institution will comply with federal human subjects regulations (The “Common Rule”; 45 CFR part 46). Each division of the CHTN is approved by its local Institutional Review Board (IRB) to collect and distribute biospecimens. The IRBs review the procedures in place to ensure adequate protection of human subjects and protection of patient privacy and confidentiality. The approvals are reviewed by the IRB yearly. Samples are described in (Supplementary Table S1) and assessment for ERα and progesterone receptor (PR) and HER2 amplification is described in the Supplementary Data. In some cases, organoids were prepared from the tissue (18).
Immunostaining and immunodetection
Indirect and direct fluorescence samples were stained as described (15, 18) and an overview is provided in the Supplementary Data.
MCF-7 cells treated with the dimethyl-3,3′-dithiobispropionimidate [5 mmol/L in PBS (30 minutes)] were quenched in 50 mmol/L Tris pH 8.0, 150 mmol/L NaCl (10 minutes). The insoluble fraction was obtained (19). Lysates were incubated with 2 μg rabbit anti-ERα, rabbit IgG (1 hour, 4°C) followed by MagnaBind goat antirabbit IgG-magnetic beads (50 μL, 1 hour, 4°C) or anti-GFP mAb-magnetic beads (50 μL, 1 hour, 4°C). Alternatively, lysates were incubated with GFP-Trap_M (ChromoTek GmbH; 18 μL, 1 hour, 4°C) prebound with GFP-GST protein (150 ng, 1 hour, 4°C). The immunoprecipitate was washed 2× with buffer (50 mmol/L Tris pH 8.0, 150 mmol/L NaCl, 5 mmol/L EDTA, 1% Triton X-100, 0.1% deoxycholate) and 3× with the same buffer without detergents. The beads were boiled (19). GST-fusion proteins were purified using glutathione sepharose 4B (300 μL) and stored (−20°C) in storage buffer (20 mmol/L HEPES pH 7.4, 300 mmol/L NaCl, 1 mmol/L EGTA, 1 mmol/L DTT, and 50% glycerol).
Total RNA extraction (RNeasy Kit) was performed on serum starved cells treated with EGF (10 nmol/L)/E2 (1 nmol/L) for 8 hours) and quality controlled using Agilent 2100 Bioanalyzer (RIN 8). Libraries were constructed (TruSeq RNA Library Prep Kit), and sequenced (Illumina HiSeq 2500 at the Vanderbilt VANTAGE Core). Raw reads were aligned to the human reference genome hg38 (Genome Reference Consortium GRCh38) and differential gene expression analyzed using CLC Workbench 10.0. Genes with absolute fold change >2.5 and false discovery rate (FDR) <0.05 were considered to be significantly differentially expressed (DE). RNA sequencing (RNA-seq) data are available at Gene Expression Omnibus under accession: GSE99707.
Gene expression data from patients with invasive breast carcinoma [The Cancer Genome Atlas (TCGA) version 1/11/2015] were analyzed using Morpheus. Samples were filtered to include primary tumors from patients with infiltrating ductal carcinoma. z scores were calculated for each ER+ patient by adding z scores of genes downregulated in RSK2-KO cells and subtracting z scores of genes upregulated in RSK2-KO cells. RSK2-low tumors have RSK2 z score < 0, and RSK2-high tumors RSK2 z score > 0. Hierarchical clustering of patient samples using one minus the Spearman's rank correlation and total linkage was performed using the RSK2_529 set. iRegulon1.3 (Cytoscape 3.5.0) was used for transcription factor prediction. STRING10.5 (confidence 0.7) was used to predict and identify functional nodes of protein networks. Gene set enrichment analysis (GSEA) was performed with javaGSEA software (Broad Institute) using expression of all detected genes (16,394) in RSK2-KO versus WT cells against gene signatures from the Molecular Signature Database v6.0 (20).
Statistical analyses were performed using GraphPad Prism 6.0a.
Nuclear active RSK2 in invasive ER+ breast cancer
We first addressed activation and localization of RSK by immunofluorescence (IF) across a panel of 25 invasive ER+ breast cancer patient samples. Active nuclear RSK was observed in ∼70% of these samples (Fig. 1A; Supplementary Fig. S1A and Supplementary Table S1) and, within these samples, the intensity of nuclear RSK was strongly correlated with the intensity of ERα (Fig. 1B). Cyclin D1 levels and ERα were also correlated (Fig. 1A and B; Supplementary Fig. S1A), consistent with observations that cyclin D1 is frequently overexpressed in ER+ cancers (21). Because IF provides a quantitative readout, we conclude that there is a positive linear relationship between the levels of active nuclear RSK and ERα in ER+ breast cancer.
Antibodies against active RSK cannot distinguish between different RSK isoforms, because the phosphorylation sites responsible for activation are identical (6). An anti-RSK2 antibody identified that RSK2 was localized to the nucleus in those ER+ tumor samples containing active nuclear RSK (Fig. 1C). A specific anti-RSK1 antibody suitable for IF was not available and therefore, we used human ER+ cell lines to examine RSK1 and RSK2 nuclear translocation. In response to growth factors and cytokines, endogenous-activated RSK2 accumulated in the nucleus (Fig. 1D; Supplementary Fig. S1B–S1D), as did C-terminally fluorescently tagged RSK2 (Supplementary Fig. S1E). In contrast, nuclear accumulation was not observed for RSK1 (Supplementary Fig. S1E) despite both isoforms being active (Supplementary Fig. S1F) and reports of RSK1 nuclear translocation (22). Taken together, we conclude that RSK2 is the active isoform present in the nucleus in invasive ER+ breast cancer tumor samples.
RSK2-regulated gene signature correlates with invasive ER+ breast cancer
RNAi knockdown experiments revealed that RSK2 was essential for ER+ tumor growth and expression of cyclin D1 in an MCF-7 orthotopic model (Fig. 1E and F; Supplementary Fig. S1G). To identify the mechanistic basis of these findings, we used CRISPR/Cas9 gRNA targeting to genetically delete RSK2 in MCF-7 cells (RSK2-KO; Supplementary Fig. S2A). RSK2-KO MCF-7 cells showed reduced proliferation relative to WT controls, which could be rescued by ectopic expression of RSK2 (Supplementary Fig. S2B). Addition of the ERα degrader, fulvestrant reduced proliferation to the same extent in WT and RSK2-KO MCF-7 cells (Fig. 2A). These results indicated that ERα-dependent proliferation is partly controlled by RSK2, because knockout of RSK2 did not result in a further reduction of proliferation at high concentrations of fulvestrant. Next, we performed RNA-seq on RSK2-KO and WT MCF-7 cells that were treated with a cocktail containing estradiol (E2) and EGF, in order to explore transcriptomic changes under conditions where both ERα and RSK2 are active. This analysis identified 529 DE genes in the RSK2-KO cells relative to WT (RSK2_529; Supplementary Table S2 and Supplementary Fig. S2C). We confirmed the specificity of the DE by quantitative RT-PCR of selected genes, which was further validated with rescue by overexpression of RSK2 in the RSK2-KO cells (Supplementary Fig. S2D). GSEA demonstrated that genes upregulated in invasive ductal breast cancer versus ductal carcinoma in situ (DCIS) were significantly enriched in WT versus RSK-KO (FDR q value < 0.05; Fig. 2B; refs. 23–25). To test whether the directionality of changes of the RSK2_529 set were reflected in ER+ breast cancer patients, we calculated z scores in ER+ patients with high and low RSK2 mRNA expression. Patient z scores were higher in RSK2-high compared with RSK2-low patients demonstrating that in ER+ breast cancer patients expression of the RSK2_529 set is correlated with RSK2 mRNA levels and that the direction of the effect of expression is concordant with that of the RSK2_529 set (Fig. 2C). Unsupervised hierarchical clustering of the RSK2_529 set across 782 breast cancer gene expression sets in the TCGA dataset revealed that patients were stratified into two major clusters, based on their positivity for ERα (Fig. 2D). Hypergeometric enrichment probability analyses further showed that the RSK2_529 set separated the ER+ patients with a probability of 5.8 × 10−69 and the ER− patients with a probability of 1.0 × 10−75 (two-tailed Fisher exact test P < 0.0001; Supplementary Table S3; ref. 26). These hypergeometric probabilities are in a similar range to those obtained with PAM50, a 50-gene intrinsic subtype classifier (27), and the luminal versus basal signature (28; Supplementary Table S3). There is <1% overlap between the RSK2_529 set and PAM50 (P > 0.05 two-tailed Fisher exact test), indicating that the RSK2_529 set is distinct from PAM50. The RSK2_529 set shares ∼10% of the genes with those found in the luminal versus basal signatures, which indicates the importance of RSK2 to the luminal lineage (Supplementary Fig. S2E). In contrast to results obtained with the RSK2_529 set, the signatures obtained from tissue homeostasis (29, 30), ductal versus lobular invasive carcinoma (31), or ER-related 1-gene set (32) failed to distinguish between ER+ and ER− patients (Supplementary Table S3). Proliferation and cell cycle genes (29, 30) did not significantly contribute to the RSK2_529 set as shown by GSEA (FDR q value > 0.05; Supplementary Fig. S2F) and their removal did not substantially reduce the high enrichment probabilities for separating ER+ from ER− patients (Supplementary Fig. S2G and Supplementary Table S3).
The RSK2 signature was further reduced to 212 DE genes (RSK2_212) by taking into account transcript level abundance. Analysis of the RSK2_212 set by iRegulon (33) and the STRING 10.0 database identified a network of genes consisting of 127 DE genes (RSK2_127) that were regulated by GATA3, FOXA1, EP300, and ESR1 (ERα gene). These results are in agreement with GSEA analysis, which identified that E2-responsive genes are enriched in WT versus RSK2-KO (FDR q value < 0.05; Fig. 2E; ref. 34). GATA3, FOX1, and EP300 are regulators of ERα function (35–41) and high mRNA and protein expression of GATA3 and FOXA1 are associated with ER+ breast cancer (42). The RSK2_127 set separated patients based on their ERα status with a greater probability that the RSK2_529 set (Fig. 2F; Supplementary Table S3). Removal of the 23 genes related to cell cycle and proliferation that were present in the RSK2_127 set improved the hypergeometric probability of distinguishing between ER+ and ER− breast cancer samples (Supplementary Fig. S2H and S2I). We conclude that RSK2 contributes to ER+ breast cancer through regulation of a subset of the ERα transcriptome.
ERK1/2 and ERα cooperatively control RSK2 nuclear sequestration
RSK2 activates ERα-mediated transcription through physical association and by phosphorylating ERα at Ser-167 (pSer-167; ref. 43). To distinguish whether physical association or pSer-167 was responsible for our transcriptomic findings, we treated MCF-7 cells with the antiestrogen, 4-hydroxytamoxifen (4-OHT). 4-OHT disrupted the association of RSK2 and ERα without altering pSer-167 (Supplementary Fig. S3A and S3B), strongly suggesting that the interaction of RSK2 with ERα (rather than pSer-167) is critical to the regulation of the ERα transcriptome. This conclusion was further supported in vivo, as inducible overexpression of ERα with doxycycline in the mammary gland, resulted in increased levels of active nuclear RSK, as predicted based on previous observations that proteins in a complex frequently regulate each other's protein levels (Supplementary Fig. S3C). Based on these observations, we tested whether association of ERα with RSK2 regulated RSK2 nuclear accumulation. Indeed 4-OHT inhibited RSK2 nuclear accumulation by ∼50% to 80% across multiple different ER+ breast cancer cell lines, which were sensitive to 4-OHT (Fig. 1D; Supplementary Figs. S1D, S3D–S3F). Fulvestrant also reduced RSK2 nuclear accumulation (Supplementary Fig. S3D). In addition to preventing RSK2 nuclear accumulation, antiestrogen treatment was able to drive RSK2 into the cytoplasm after it had accumulated (Supplementary Fig. S3G). Changes in RSK2 localization did not appear to arise secondary to altered expression levels or activity of RSK2 or ERK1/2 (Supplementary Fig. S3H). Consistent with the antiestrogen treatments, silencing ERα also reduced RSK2 nuclear accumulation in response to growth factors (Fig. 3A). Silencing RSK2 did not affect ERα nuclear localization (Supplementary Fig. S3I), indicating that ERα nuclear accumulation occurs independently of RSK2. To more rigorously test whether ERα controls RSK2 nuclear accumulation we developed a 3D organoid culture system and generated organoids from primary human ER+ breast cancer tissue. Importantly, the levels of ERα, cyclin D1, and activated nuclear RSK were similar to those observed in the patient tissues from which they were derived. Similar to 2D cultures, 4-OHT treatments in 3D resulted in loss of nuclear RSK2 coupled to cytoplasmic accumulation of RSK2 and reduced cyclin D1 levels (Fig. 3B and C; Supplementary Fig. S3J and S3K). We conclude that endocrine-based therapies result in dissociation of a complex consisting of RSK2 and ERα and that loss of this interaction reduces RSK2 nuclear accumulation.
Although our data clearly demonstrated that ERα is required for RSK2 nuclear accumulation, E2 stimulation alone was insufficient (Supplementary Fig. S3L) and required additional growth factor and cytokine signaling (Fig. 1D; Supplementary Fig. S1B–S1D). A panel of 80 kinase inhibitors was therefore screened to identify signaling inputs that contribute to RSK2 nuclear localization. Of these, only compounds that inhibited ERK1/2 decreased the levels of nuclear RSK2, which is consistent with the known role of RSK2 in ERK1/2 signaling (Supplementary Fig. S3M and Supplementary Table S4). We conclude that ERK1/2 activation allows RSK2 to translocate into the nucleus while ERα interacts and sequesters RSK2 in the nucleus.
The extreme N terminus of RSK2 is required for interaction with ERα
Because physical association with ERα was required for RSK2 nuclear accumulation, we next wished to identify the region of RSK2 responsible for nuclear accumulation and ERα binding. To this end we took advantage of the observations that the RSK1 isoform does not accumulate in the nucleus, and created chimeras of RSK1 and RSK2, which were fluorescently tagged at their C terminus (Supplementary Fig. S4A). A chimera in which the RSK2 C-terminal kinase domain (CTKD) was swapped with that of RSK1 [RSK2(1–407) RSK1(404–735)] retained its ability to accumulate, while a chimera with the reverse swap [RSK1(1–401) RSK2(406–740)] did not accumulate (Fig. 4A; Supplementary Fig. S4B), despite the fact that both chimeras were active (Supplementary Fig. S4C). Thus, the RSK2 residues from 1 to 407 were necessary for RSK2 accumulation. Within this region, the RSK2 residues at the extreme N terminus (1–67) and in the linker (329–424) diverge the most from those of RSK1 (54% and 68% identity, respectively, compared with 80% overall identity). We therefore hypothesized that either the linker domain or the N terminus were most likely responsible for nuclear translocation. Replacing the RSK2 linker with that of RSK1 [RSK2(1–375) RSK1(370–401) RSK2(406–740)] did not alter activity or nuclear accumulation (Fig. 4A; Supplementary Fig. S4B and S4D), suggesting that the linker region did not play a role. Because a deletion mutant of residues from 1 to 67 of RSK2 was highly unstable, we replaced the extreme N-terminal region of RSK1 with that of RSK2 [RSK2(1–67) RSK1(62–735)]. This chimera was both active (Supplementary Fig. S4C) and accumulated in the nucleus (Fig. 4A and B). In contrast, replacing the extreme N-terminal region of RSK2 with that of RSK1 to create RSK1(1–61) RSK2(68–740) resulted in a chimera that was active (Supplementary Fig. S4C) yet lost its ability to accumulate in the nucleus (Fig. 4C). We conclude that residues from 1 to 67 are required for RSK2 nuclear accumulation. The RSK2 residues from 1 to 67 on their own could not facilitate accumulation of a heterologous protein in comparison with the nuclear localization signal (NLS) of SV40 (PKKKRKV; Supplementary Fig. S4E). Thus, the extreme N terminus is necessary but not sufficient for RSK2 accumulation.
We hypothesized that the RSK2 residues from 1 to 67 are important for RSK2 nuclear accumulation because they are responsible for interaction with ERα. Consistent with this, both RSK2 and the chimera, RSK2(1–67) RSK1(62–735), but not RSK1, coimmunoprecipitated with ERα (Fig. 4D). Additionally, silencing ERα-reduced nuclear accumulation of the chimera, similar to the WT (Fig. 4E). The RSK2 region from 1 to 67 is highly conserved within the class Mammalia, as is the analogous region in RSK1 (Supplementary Fig. S4F). There are two notable differences in the extreme N terminus between RSK1 and RSK2, which include a Ser-Pro-Ser motif and a five amino acid insert that are present only in RSK2. A Ser-Pro-Ser motif regulates ERK2 nuclear translocation (44) but mutation of residues within this motif did not alter RSK2 nuclear accumulation (Supplementary Fig. S4G and S4H). However, deletion of the five amino acid insert (RSK2Δ27–32) prevented nuclear accumulation (Fig. 4F), without affecting RSK2 activation (Supplementary Fig. S4I). Moreover, ERα specifically coassociated with a purified, recombinant protein containing the RSK2 residues from 1 to 67 (Fig. 4G). We conclude that the extreme N terminus interacts with ERα to sequester RSK2 in the nucleus.
Nuclear accumulation of RSK2 promotes ER+ breast cancer growth
Silencing endogenous RSK2 with coexpression of a shRNA-resistant mutant that does not accumulate in the nucleus [rRSK1(1–61) RSK2(68–740)] failed to increase cyclin D1 levels compared with a mutant that localizes to the nucleus [rRSK2(1–67) RSK1(62–735); Fig. 5A; Supplementary Fig. S5A]. To further verify that RSK2 nuclear accumulation is required to support ER+ breast cancer growth we used the RSK2 chimeras that did or did not accumulate in the nucleus, which reflects their ability to interact with ERα. As expected, silencing RSK2 in MCF-7 cells strongly impaired tumor growth, and this inhibition was rescued with ectopic expression of WT shRNA-resistant RSK2 (Fig. 5B; Supplementary Fig. S5B). Importantly, restoration of tumor growth was also observed by ectopic expression of the nuclear accumulating chimera but not with the nonaccumulating chimera (Fig. 5B; Supplementary Fig. S5B). Nuclear accumulation of the various ectopically expressed fusion proteins (Fig. 5C) was consistent with our in vitro data (Fig. 4B and C) and their levels were similar (Supplementary Fig. S5C). As expected, cyclin D1 levels mirrored the ability of the constructs to accumulate in the nucleus, while levels of pSer-167 ERα did not (Fig. 5D). These data are consistent with a RSK2-dependent activation of a gene program that facilitates ER+ breast cancer by physical association rather than ERα phosphorylation at Ser-167. Collectively, these observations clearly demonstrate that RSK2 nuclear accumulation is required for tumor growth in ER+ breast cancer.
Nuclear accumulation of RSK2 triggers neoplastic transformation
Because nuclear RSK2 was required for ER+ tumor growth, we next asked whether forced expression of RSK2 in the nucleus of nontransformed ER+ mammary epithelia could facilitate neoplastic transformation in vivo. To this end a novel transgenic mouse with mammary gland-restricted, nuclear RSK2 expression (MMTV-NLS-RSK2) was generated. The transgene was expressed specifically in the mammary gland and localized to the nucleus (Supplementary Fig. S6A and S6B). Because mouse models of ER+ breast cancer have a long latency (45), we examined mammary glands at early (6 months) and later (16 months) time points. At 6 months, ductal hyperplasia was observed (Supplementary Fig. S6C and S6D) with expansion of the ER+ mammary population (Supplementary Fig. S6E). By 16 months, ducts and lobules were markedly expanded in NLS-RSK2 mice compared with controls (Fig. 6A). Microscopic examination of expanded ducts revealed clear evidence of neoplastic transformation, which was manifested as DCIS. DCIS can be histologically evaluated into a three-tiered grading system that is largely based on increasing severity in nuclear morphology. NLS-RSK2 mice showed clear evidence of high-grade DCIS, including solid growth within ducts that obliterated the lumen (Fig. 6B), prominent apoptosis and mitosis including atypical mitotic forms (Fig. 6C and D), severe nuclear atypia including nuclear enlargement (Fig. 6E and F), pleomorphism, loss of polarity, and stratification (Fig. 6E). Consistent with these observations IF experiments detected elevated levels of the S-phase marker, PCNA (Fig. 6G), and the DNA damage marker, γH2AX (Fig. 6H). Approximately, 50% of the mice developed high-grade ER+ DCIS (Fig. 6I; Supplementary Fig. S6G). To functionally confirm neoplastic transformation, we isolated the mammary cells from the 16-month-old NLS-RSK2 and assayed their in vitro and in vivo tumorigenic capacity. Sphere cultures generated from the NLS-RSK2 mice were more efficient at forming spheres over multiple passages than those obtained from WT mice (Fig. 6J). For the in vivo assays spheres generated from WT and NLS-RSK2 mammary glands from passage 0 were transduced with luciferase (Supplementary Fig. S6H). Intracardiac injection of equal numbers of the transduced spheres into NCG mice resulted in 100% of the mice injected with NLS-RSK2 spheres developing metastatic tumors; whereas, WT spheres failed to form tumors (Fig. 6K; Supplementary Fig. S6I). We conclude that forced nuclear expression of RSK2 triggers in situ transformation of ER+ mammary epithelial cells, and that these cells are capable of tumorigenic growth if removed from the mammary gland.
Our studies provide a mechanistic basis for the clinical observations that active RSK correlates with endocrine-therapy responsiveness and increased overall survival in patients with ER+ breast cancer. ERα interacts with residues from 27 to 32 located in the N terminus of RSK2 to sequester RSK2 in the nucleus. This motif is highly conserved from Mammalia to Aves, which is a hallmark of residues that are important as functional domains. The interaction of RSK2 with ERα, which is disrupted by mutagenesis of RSK2, antiestrogens, or silencing ERα, allows ERK1/2-activated RSK2 to accumulate to high levels in the nucleus. Loss of RSK2 from the nucleus results in reduced ER+ tumor formation, which is due to the inactivation of the proneoplastic transcriptional network comprised of ESR1, EP300, GATA3, and FOXA1 that is critical to maintain ER+ breast cancer (42, 46). This conclusion is further supported by the ability of the RSK2 gene signature to stratify breast cancer patients according to their ERα status.
RSK2 influences ERα-mediated transcriptional activity via phosphorylation or physical association (43, 47). The residue, Ser-167, within ERα is a RSK phosphorylation site (43) but a correlation between the phosphorylation of Ser-167 and tumor formation was not observed. However, tumor formation was absolutely dependent on RSK2 nuclear accumulation. Similar to the observations with active RSK, the phosphorylation of Ser-167 is correlated with responsiveness to endocrine-based therapies and overall survival (4, 48, 49) but we propose that this phosphorylation is an indirect biomarker for active RSK2 and therefore, is correlated but not causally related to ER+ breast cancer.
Remarkably, forced expression of RSK2 in normal mammary glands triggered the development of high-grade DCIS. In this model, transformation occurs with a long latency, which is similar to both human breast cancer and many other transgenic mouse models (45, 50). We note that although mice developed high-grade DCIS, no invasive tumors were identified, perhaps due to a need for additional time or because further genetic or epigenetic events beyond RSK2 are needed for initial invasion of neoplastic cells through the basement membrane into the surrounding stroma. Interestingly, bypassing the intravasation step, demonstrated that nuclear RSK2 supported metastatic tumor growth, indicating that RSK2 dependence is likely selected as an early in situ event that helps promote neoplastic transformation and remains essential thereafter to support tumorigenesis once invasive tumor growth has been established.
Disclosure of Potential Conflicts of Interest
D.A. Lannigan is CSO at Rx Targeting and has ownership interest (including patents) in University of Virginia and Rx Targeting. No potential conflicts of interest were disclosed by the other authors.
Conception and design: K.A. Ludwik, D.R. Brenin, D.A. Lannigan
Development of methodology: D.A. Lannigan
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): K.A. Ludwik, D.R. Brenin, D.A. Lannigan
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): K.A. Ludwik, O.G. McDonald, D.A. Lannigan
Writing, review, and/or revision of the manuscript: K.A. Ludwik, O.G. McDonald, D.R. Brenin, D.A. Lannigan
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.A. Lannigan
Study supervision: D.A. Lannigan
We thank Pricilla Furth, M.D. (Georgetown) for providing the CERM mice. We also thank the University of Virginia Research Histology Core and the Biorepository and Tissue Procurement Facility. Tissue samples were provided by the CHTN, which is funded by the National Cancer Institute. Other investigators may have received specimens from the same subjects. Data generated by the TCGA Research Network: http://cancergenome.nih.gov/ was used. This work was supported by NIH grant GM084386 (D.A. Lannigan) and Susan G. Komen Breast Cancer Foundation #IIR12223770 (D.A. Lannigan).
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.