Neurofibromin is an Estrogen Receptor-α Transcriptional Co-repressor in Breast Cancer

Ze-Yi Zheng; Meenakshi Anurag; Jonathan T Lei; Jin Cao; Purba Singh; Jianheng Peng; Hilda Kennedy; Nhu-Chau Nguyen; Yue Chen; Philip Lavere; Jing Li; Xin-Hui Du; Burcu Cakar; Wei Song; Beom-Jun Kim; Jiejun Shi; Sinem Seker; Doug W Chan; Guo-Qiang Zhao; Xi Chen; Kimberly C Banks; Richard B Lanman; Maryam Nemati Shafaee; Xiang H-F Zhang; Suhas Vasaikar; Bing Zhang; Susan G Hilsenbeck; Wei Li; Charles E Foulds; Matthew J Ellis; Eric C Chang

doi:10.1016/j.ccell.2020.02.003

. Author manuscript; available in PMC: 2021 Mar 16.

Published in final edited form as: Cancer Cell. 2020 Mar 5;37(3):387–402.e7. doi: 10.1016/j.ccell.2020.02.003

Neurofibromin is an Estrogen Receptor-α Transcriptional Co-repressor in Breast Cancer

Ze-Yi Zheng ¹, Meenakshi Anurag ¹, Jonathan T Lei ^1,², Jin Cao ³, Purba Singh ¹, Jianheng Peng ^1,⁴, Hilda Kennedy ¹, Nhu-Chau Nguyen ¹, Yue Chen ⁵, Philip Lavere ³, Jing Li ¹, Xin-Hui Du ^1,⁶, Burcu Cakar ¹, Wei Song ¹, Beom-Jun Kim ¹, Jiejun Shi ¹, Sinem Seker ¹, Doug W Chan ^1,³, Guo-Qiang Zhao ⁶, Xi Chen ³, Kimberly C Banks ⁷, Richard B Lanman ⁷, Maryam Nemati Shafaee ¹, Xiang H-F Zhang ^1,³, Suhas Vasaikar ¹, Bing Zhang ¹, Susan G Hilsenbeck ¹, Wei Li ¹, Charles E Foulds ^3,⁸, Matthew J Ellis ^1,^3,^9,^*, Eric C Chang ^1,^3,^*

PMCID: PMC7286719 NIHMSID: NIHMS1568796 PMID: 32142667

Summary

We report that neurofibromin, a tumor suppressor and Ras-GAP (GTPase Activating Protein), is also an estrogen receptor-α (ER) transcriptional co-repressor through leucine/isoleucine-rich motifs that are functionally independent of GAP activity. GAP activity, in turn, does not impact ER binding. Consequently, neurofibromin-depletion causes estradiol hypersensitivity and tamoxifen agonism, explaining the poor prognosis associated with neurofibromin-loss in endocrine therapy-treated ER⁺ breast cancer. Neurofibromin-deficient ER⁺ breast cancer cells initially retain sensitivity to selective estrogen receptor degraders (SERDs). However, Ras activation does play a role in acquired SERD resistance, which can be reversed upon MEK inhibitor addition, and SERD/MEK inhibitor combinations induce tumor regression. Thus, neurofibromin is a dual repressor for both Ras and ER signaling, and co-targeting may treat neurofibromin-deficient ER⁺ breast tumors.

Graphical Abstract

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In Brief (eTOC blurb)

Zheng et al. find that the Ras-GAP NF1 is also a transcriptional co-repressor of estrogen receptor α (ER). NF1 loss leads to estradiol hypersensitivity and tamoxifen agonism. A selective ER degrader and MEK inhibitor combination induces tumor regression in mouse models of NF1-deficient ER⁺ breast cancer.

Introduction

Germline mutations in the NF1 (Neurofibromatosis type 1) gene are responsible for neurofibromatosis type 1, the most common inherited disorder that predisposes individuals to both benign and malignant tumors of the nervous system (Ratner and Miller, 2015), as well as an increased risk for breast cancer (Madanikia et al., 2012; Salemis et al., 2010; Sharif et al., 2007). Analysis of TCGA data has shown that NF1 is mutated in a wide range of common cancers (e.g., melanoma, lymphoma, and cancers of the lung, breast, and colon) (Yap et al., 2014). Thus, NF1-deficiency underlies the formation and/or progression of a large number of cancers.

NF1 encodes neurofibromin, an established GTPase-Activating-Protein (GAP), that attenuates Ras signaling (Maertens and Cichowski, 2014). The human genome contains up to 14 Ras GAPs that share no significant sequence homology beyond the GAP domain. However, across species there is extensive evolutionary sequence conservation outside of the relatively small GAP domain (e.g., 83% overall identity in amino acid sequence between human and salmon neurofibromins), suggesting that neurofibromin has other yet undisclosed functional domains.

Approximately 80% of breast cancers are positive for estrogen receptor-α (ER⁺), a ligand-dependent transcription factor that is activated by estradiol (E2) (Feng and O’Malley, 2014). The E2-liganded ER recruits co-activators (such as steroid receptor co-activators, SRC-1–3) to estrogen-responsive elements (EREs) in ER-regulated genes. Tamoxifen, a selective estrogen receptor modulator (SERM), is predominantly antagonistic in breast cancer cells, hence its therapeutic effect. When tamoxifen binds to ER, co-activators are displaced by co-repressors in the ER-ERE complex (Shang et al., 2000). Established ER co-repressors bind ER via their leucine/isoleucine-rich motifs, and substitutions of L or I with an A can disrupt binding (Hu and Lazar, 1999). Interactions are also mediated by electrostatic interactions (Heldring et al., 2007; Shiau et al., 1998).

Besides tamoxifen, ER⁺ breast cancer can be treated with estrogen deprivation through ovarian suppression and aromatase inhibition (AI), and ER can be directly targeted by selective estrogen receptor degraders (SERDs), such as fulvestrant, which induce ER protein turnover. However, relapse is common, and the majority of breast cancer deaths occur after a diagnosis of an ER⁺ primary cancer.

Results

NF1 loss correlates with poor patient outcome in ER⁺ breast cancer.

While NF1 mutation frequencies are low in primary ER⁺ breast cancer (2% in TCGA (TCGA, 2012) as shown in Figure 1A, and 4% in our patient cohort (Griffith et al., 2018)), NF1 mutation frequency is higher in metastatic ER⁺ breast cancer patients (n=535) (Lanman et al., 2015; Zill et al., 2018) when circulating cell-free tumor DNA (ctDNA) was sequenced (18%, Figure 1A and Table S1). Similar enrichment of NF1 mutations in metastatic ER⁺ breast cancer has been reported by others (Bertucci et al., 2019; Meric-Bernstam et al., 2014; Pearson et al., 2019; Razavi et al., 2018; Sokol et al., 2019; Yates et al., 2017). These observations suggest that somatic NF1 events are an important class of mutations driving breast cancer progression.

We have previously analyzed somatic mutations in primary tumors accrued from ER⁺ breast cancer patients treated with adjuvant tamoxifen monotherapy and found that NF1 nonsense and frameshift mutations were associated with a markedly higher risk of breast cancer recurrence and death (Griffith et al., 2018). No GAP-inactivating missense mutations were found. When examining the COSMIC database, a C to T nonsense mutation at R2450 (R2450*) is the most frequent non-silent NF1 mutation, found 28 times (Figure S1A). Nonsense/frameshift mutations can trigger mRNA degradation through nonsense-mediated decay. Consistent with this mechanism, greatly reduced full-length NF1 mRNA levels were observed in both TCGA (Figure 1B) and METABRIC (Curtis et al., 2012) (Figure S1B) samples when nonsense/frameshift mutations were present. Similar reduction of NF1 mRNA in tumors carrying NF1 mutations have also been reported in another patient cohort (Pearson et al., 2019). ER⁺ breast cancer is also treated with aromatase inhibition (AI); therefore, we examined gene expression data from the ACOSOG Z1031 clinical trial, where patients were treated with an AI before surgery (Ellis et al., 2011). These data demonstrated that while a multi-gene proliferation score (MGPS) (Ellis et al., 2017) decreased after AI treatment in tumors with higher NF1 mRNA levels, reduced suppression of proliferation (high MGPS) was observed in tumors with low NF1 mRNA levels, indicating AI resistance (Figure 1C and Table S2). Finally, we found that NF1 proteins missing a small portion of the C-terminus caused by the NF1-R2450* mutation or by two other recurrent nonsense/frameshift mutations, NF1-R2258* and NF1-Y2285* (Figure S1A), could not be efficiently expressed unless a proteasome inhibitor was added (Figure S1C), supporting the possibility that some C-terminally truncated NF1 proteins may be unstable.

Collectively, these findings raise the possibility that depletion of neurofibromin is a common consequence of nonsense/frameshift mutations and most associated with poor outcomes. Importantly sequencing studies have found few recurrent inactivating mutations in the NF1 GAP domain, leading us to speculate that NF1 protein may harbor additional negative regulatory functions relevant to breast cancer pathogenesis.

NF1-depletion promotes tamoxifen agonism and E2 hypersensitivity in ER⁺ breast cancer cells.

To investigate the consequences of NF1-depletion on ER⁺ breast cancer, MCF-7 ER⁺ breast cancer cells were engineered to harbor lentiviruses expressing one of two doxycycline (DOX)-inducible shRNA clones (C5 and C6). Upon DOX addition (+DOX), NF1 protein levels were reduced by ~70% as detected by a monoclonal antibody (mAb) we raised (Figure S1 D and E). Increased ERK activating phosphorylation (pERK1/2) in DOX-treated cells vs. vehicle treated or scrambled shRNA controls indicated the anticipated reduction in GAP activity (Figure S1E). An NF1 shRNA-resistant expression construct reversed these effects (Figure S1E).

Remarkably, when NF1 expression was suppressed (+DOX) in MCF-7 cells as well as in two more ER⁺ breast cancer cell lines ZR-75B and T47D (Figure S1F), in vitro growth was consistently stimulated by 4-hydroxy-tamoxifen (4-OHT) under E2-deprived conditions (charcoal-stripped serum) (Figure 1D and Figure S1G), in comparison to the non-silenced control (−DOX) or the scrambled shRNA +DOX control, indicating an NF1 loss mediated transition from 4-OHT antagonism to agonism. Furthermore, NF1-silenced cells proliferated at lower concentrations of E2 than controls, and higher E2 concentrations paradoxically inhibited cell growth indicating E2 hypersensitivity (Figure 1E and Figure S1H). Two pools of NF1 “knock-out” (KO) MCF-7 cells were independently created by CRISPR-Cas9 (Figure S1D) with results similar to the shRNA data (Figure 1 D and E). MDA-MB-231 cells are ER⁻, and NF1 expression is barely detectable (Ogata et al., 2001) due to a frameshift mutation (NF1-T467^fs) (Neve et al., 2006). These ER⁻ “NF1^low” cells were unresponsive to 4-OHT or E2, indicating a requirement for ER for the endocrine effects of NF1 perturbation (Figure S1 G and H). E2 hypersensitivity and 4-OHT agonism were reproduced in vivo using an MCF-7-based xenograft mouse model — tamoxifen stimulated the growth of NF1-silenced tumors (Figure 1F left), and these tumors grew better than control tumors at a lower dose of E2 (0.05 mg dose) (Figure 1F, right).

NF1-depletion globally enhances ER transcriptional activity.

Since the abnormal E2 and tamoxifen responses observed in NF1-depleted cells are ER-dependent, we investigated whether NF1-depletion affects ER-dependent transcription. First, the mRNA levels of established ER-target genes were examined by qPCR in MCF-7 cells, and the expression levels of GREB1 and pS2/TFF1 in the presence of E2 were elevated when NF1 was depleted by DOX-inducible shRNA (Figure S2A) or CRISPR-mediated KO (Figure S2B). This increase was not due to an increase in ER protein levels and could be reversed by the shRNA-refractory NF1 construct (“NF1-rescue”, Figure S2A), indicating the specificity of the shRNA targeting. Gene expression was also stimulated by 4-OHT in MCF-7 cells depleted for NF1 by shRNA (Figure S2C) or by CRISPR (Figure S2B), consistent with conversion to agonism. E2 and 4-OHT-stimulated gene expression were similarly observed in NF1-silenced ZR-75B cells (Figure S2C). ER-dependent transcription is promoted by co-activators SRC1–3, and these factors can be selectively degraded by bufalin (Wang et al., 2014). Our data showed that bufalin inhibited 4-OHT-induced enhanced gene expression in NF1^KD MCF-7 cells (Figure S2D), indicating SRC1–3 is required for this activity. Finally, we examined tumor tissues from the MCF-7 xenograft model (Figure 1E) by qPCR and found that expression of two ER target genes GREB1 and TFF1 was greatly enhanced when NF1 was silenced (Figure S2E).

To examine the effects of NF1 on gene expression in a genome-wide fashion, RNA-seq experiments were performed in control (−DOX) and NF1 knock-down (+DOX, KD) MCF-7 cells with and without E2 stimulation. Overall, E2 altered expression from 540 genes in the control NF1⁺ cells and 955 genes in NF1^KD cells (Figure 2A and Table S3). There was an overlap of 388 genes between the two gene sets (Table S3), indicating that expression changes of 72% (=388/540) of the observed E2-altered genes seen in NF1⁺ cells were also altered in NF1^KD cells. These overlapping genes, referred to as the “common E2-regulon,” were analyzed by GSEA Hallmark Pathway analysis and found to be highly enriched with well-established E2-responsive genes (Figure 2A and Table S3). Furthermore, nearly all genes upregulated after E2-stimulation in NF1⁺ cells were more strongly induced in NF1^KD cells, and the great majority of E2-repressed genes were also more strongly repressed, consistent with bidirectional ER-hyperactivity upon NF1-depletion (Zubairy and Oesterreich, 2005). The 415 (=955−540) E2-altered genes that were selectively observed in the NF1-depleted state (referred to as the “NF1^KD-unique E2-regulon”) were also assessed by GSEA Hallmark pathway analysis (Table S3). Aside from a predominance of additional E2-regulated genes, a K-Ras-dependent gene expression signature was also observed (Figure 2A). Gene expression changes induced by 4-OHT were also examined by RNA-seq. While 4-OHT overall displays weak agonist activity as expected (Figure S2F, Table S3), the overlap of 4-OHT-altered gene expression between NF1⁺ and NF1^KD cells was 65% and enriched with well-established E2-responsive genes (Figure S2G). Furthermore, genes that were induced by 4-OHT in NF1⁺ cells were more highly induced, while 4-OHT-repressed genes were more strongly repressed in NF1^KD cells (Figure S2G).

To determine whether the E2-induced gene expression patterns shown in Figure 2A could be replicated in patient samples, differentially expressed genes according to NF1 status (with or without NF1 nonsense/frameshift mutation) in the METABRIC and TCGA ER⁺ data sets were identified, and pathway enrichments were similarly assessed (Table S4). The results were compared to the two MCF-7 E2-regulons described above. Supporting the conclusion that NF1-depletion dramatically affects the expression of E2-responsive genes in clinical ER⁺ specimens, E2-responsive pathway terms were most significantly modulated by NF1 mutation status, followed by the K-Ras signature (Figure 2B). A similar conclusion has been obtained by others after examining ER⁺ breast tumors with NF1 shallow deletion in METABRIC (Dischinger et al., 2018) and NF1 “truncating” mutations in TCGA (Pearson et al., 2019).

NF1-depletion increases ER recruitment to EREs.

In the presence of E2, NF1-depletion mostly affects expression of known E2-responsive genes. To assess whether this is due to direct ER binding to the EREs, we performed ChIP-qPCR to analyze ER recruitment to ten well-documented ERE sites in six genes, TFF1, GREB1, PGR, MYC, XBP1, and CCDN1. The data show that NF1-depletion enhances ER recruitment to all of these sites (Figure 2 C and D).

In the presence of 4-OHT, expression of 542 genes was mostly detected in NF1^KD cells (Figure S2G). We examined one 4-OHT-dependent ER ChIP-seq data set (He et al., 2018) and found that 68% of these 542 genes (371/542) were also found in this ER ChIP-seq study (Table S3). All together, these data suggest that NF1-depletion mostly quantitatively enhances ER-dependent transcription, whether it is stimulated by E2 or 4-OHT, but NF1 loss does not substantially qualitatively alter the profile of genes that get transcribed under the experimental conditions tested.

Neurofibromin contains two leucine/isoleucine rich co-repressor motifs.

Tamoxifen agonism and E2 hypersensitivity, together with the RNA-seq and ER ChIP-seq data, suggested that neurofibromin may function as a ligand-dependent co-repressor for ER transcriptional activity. Consistent with this postulate, there are two consensus co-repressor motifs in neurofibromin, designated here as M1 and M2 (Figure 3A). Notably the ER binding motifs in neurofibromin family members appear to have co-evolved with emergence of estrogen-dependent reproduction. M1/2 are highly conserved in salmon, the most human-distant species examined to have an ER homolog (Rogers et al., 2000), but not in fly or yeast (Figure 3A), which do not. Furthermore, mutations affecting key residues in M1 and M2 can be found in cancer (COSMIC and METABRIC) and some of these mutations are recurrent. In particular, a somatic M1 I417M mutation was found in our patient cohort (Griffith et al., 2018), which coexisted with an NF1 nonsense mutation suggesting a biallelic event.

Figure 3. — A. Protein alignment was created by ClustalW (MUSCLE). NF1 has two potential co-repressor motifs, M1 and M2 (potential consensus sequences shown at the bottom). Mutations found in cancers (COSMIC) or neurofibromatosis are colored blue, and the numbers in parentheses are the number of times found in the COSMIC database. B. Parental MCF-7 or the NF1-KO (clone #1) MCF-7 cells were grown in E2-deprived medium to which E2, 4-OHT, or vehicle was added. Whole cell or nuclear extracts were immunoprecipitated with NF1 or ER antibody, and the resulting samples were analyzed by immunoblotting. The number below the blot shows the percentage of co-immunoprecipitated protein. C. Recombinant purified ER-α preincubated with E2, 4-OHT, or vehicle was pulled-down by amylose beads containing His-MBP-tagged NF1-M2/GAP domain, or His-MBP-GST control, and the results were analyzed by immunoblotting. D. Left, whole cell lysates from parental MCF-7 cells (WT) or from a CRISPR “knock-in” mutant carrying either a I417M (colored red) or a R1362Q (colored blue) mutation grown in full-serum medium were examined by immunoblotting to measure the pERK/total ERK ratios (below). Right, reciprocal co-immunoprecipitation experiments in the presence of 4-OHT similar to those in (B) assessed ER binding to various NF1 proteins. E. Parental or NF1 mutant cells were seeded in E2-deprived medium and were examined for cell growth in response to E2 or 4-OHT (6 days later) n=3 experiments. F. *GREB1* and *TFF1* mRNA levels from parental or NF1 mutant cells treated with vehicle or E2 were measured by qPCR (n = 3 independent experiments). Expression levels were normalized to those of vehicle-treated wild-type cells. Data are reported as mean±SEM. *p<0.05, **p<0.01 by pair-wise two-tailed Student’s t-test. NS, not significant. G. mRNAs from cells seeded in charcoal-stripped serum were analyzed by RNA-seq. “E2-responsive genes” as defined in Figure 2A is shown on the left to which expression levels of genes (row Z-scores from “Log₂ Transcripts per Million” values) in various strains were aligned.

See also Figure S3 and Table S5.

The binding of ER to neurofibromin is selective, ligand-dependent, and direct.

Established ER co-repressors preferentially bind to the ER ligand-binding domain (LBD) in an interaction that is enhanced by 4-OHT but not by E2 (while the reverse is the case for co-activators) (Huang et al., 2002; Shiau et al., 1998). Ligand-dependent binding of neurofibromin to the ER LBD was detected in cells using a mammalian two-hybrid assay (Chang et al., 1999), mimicking a known co-repressor NCoR1 and opposite to the behavior of the coactivator SRC-1 (Figure S3 A and B). Reciprocal co-immunoprecipitation experiments in MCF-7 and ZR-75B cells were also performed to demonstrate that neurofibromin can co-immunoprecipitate ER using our mAb and vice versa (Figure S3C). NF1⁺ MCF-7 cells were used to illustrate the point that these interactions were enhanced by 4-OHT, but reduced by E2; in contrast, ER could not be pulled down in the NF1-KO line, indicating that our neurofibromin mAb is specific (Figure 3B). Finally, M2 is located in the GAP domain, which can be readily purified from Escherichia coli (Bollag et al., 1993). We thus determined that 4-OHT increased the efficiency of the interaction between purified NF1-M2/GAP domain and purified ER in a pull-down, confirming that the interaction between NF1 and ER is very likely direct (Figure 3C).

The human genome contains 14 potential Ras GAPs, but they do not share sequence homology beyond the GAP domain. For example, in p120GAP/RASA1, there is no identifiable M1; nor was there an M2 in a published GAP domain alignment study (Ballester et al., 1990) (Figure S3D). While ER co-immunoprecipitated NF1, ER did not co-immunoprecipitate p120/RASA1 (Figure S3C). Protein co-expression is a strong predictor for co-functionality (Wang et al., 2017a). Therefore, we assessed Gene Ontology molecular function terms of proteins whose levels positively correlated with those of neurofibromin from proteomics analysis of >100 breast cancer patient-derived samples (CPTAC) (Mertins et al., 2016). Whereas NF1 protein levels highly correlated with a number of transcription factor functionalities, and the “ligand-dependent nuclear receptor binding” term in particular, p120GAP, mostly negatively correlated with these factors (Figure S3E).

ER binding and GAP activity are two independent functions of neurofibromin.

To determine whether neurofibromin can directly interact with ER via M1/2 without a requirement for GAP activity or Ras pathway activation, we first took a pharmacological approach using Raf and MEK inhibitors, dabrafenib and trametinib (Robert et al., 2015). Here we found that Raf/MEK inhibition did not affect E2-dependent transcription measured by qPCR in either NF1⁺ or NF1-silenced MCF-7 cells (Figure S3F). Immunoblotting detected substantial loss of pERK levels by dabrafenib and trametinib, suggesting the Ras-Raf pathway was efficiently inhibited in these experiments (Figure S3F). Bufalin, which promotes degradation of SRC1–3 co-activators, was the positive control for this study. One of the best-known examples of a Ras-ER interaction is phosphorylation at serine 118 (pS118) in ER by ERK after growth factor stimulation (Kato et al., 1995). However, this event seems to be context (e.g., cell type and/or culture conditions)-dependent and can be catalyzed by other kinases (Anbalagan and Rowan, 2015). We could not detect a significant increase in ER-pS118 in NF1 KO MCF-7 cells, despite strong increase in activating phosphorylation in ERK1/2 (Figure S3G). Finally, we note that the average IC50 of trametinib in commonly used ER⁺ breast cancer cell lines under normal culture condition is 300 μM vs. 0.05 μM in melanoma cells (https://www.cancerrxgene.org). Thus, under standard culture conditions, Ras-Raf signaling is not critical for either ER-dependent gene expression or growth of E2-sensitive ER⁺ breast cancer cells.

To directly ascertain whether M1 and M2 are authentic ER-binding sites, residues I and V were substituted with A to create NF1-I417A-I418A and NF1-V1308A-V1309A. The I417M NF1 somatic M1 mutant found in an ER⁺ breast cancer was also generated. Conversely, two mutations found in metastatic breast cancer, NF1-R1362Q (Lanman et al., 2015) and NF1-K1444R (Li et al., 2013), were predicted (Wilkins et al., 2012) to inactivate GAP activity (Figure S3H). They were thus tested further to assess whether ER repression requires intact GAP activity. We confirmed that R1362Q and K1444R mutations greatly reduce the GAP activity of NF1, while the M1/2 mutations do not, by measuring pERK levels (Figure S3H).

Binding to ER (two-hybrid assay, Figure S3I) and repression of ER transcriptional activity (ERE-luciferase reporter assay (Hall and McDonnell, 1999), Figure S3J) were both greatly reduced by M1 and M2 mutations; in contrast, the two GAP mutants bound and suppressed ER activity as efficiently as wild-type NF1. One GAP and one M1 mutant were chosen for further study by expressing them in NF1-depleted cells to levels comparable to endogenous neurofibromin in control cells (Figure S3K). The enhanced GREB1 and TFF1 expression in NF1-silenced cells was completely repressed by wild-type NF1 and the GAP mutant, but only partially by the M1 mutant.

To ascertain whether ER-repression and GAP activity are two independent functions of NF1 without using ectopic overexpression, CRISPR-Cas9 mediated knock-in was used to create MCF-7 cells carrying homozygous NF1-I417M (M1) mutation or NF1-R1362Q (GAP) mutation (Figure S3L). The former cells had normal GAP activity, but their NF1-I417M cannot co-immunoprecipiate ER (Figure 3D). Similar to cells in which NF1 is depleted by shRNA or CRISPR, the NF1-I417M (ER binding) mutant cells showed abnormal endocrine responses because cell growth was stimulated by 4-OHT and low levels of E2; in contrast, the NF1-R1362Q (GAP) mutant behaved like wild-type cells (Figure 3E). We examined expression of two well-established ERE genes (TFF1 and GREB1) by qPCR (Figure 3F) and found that their expression after E2 stimulation was greatly enhanced by the I417M mutantion, which again behaved like full NF1-depletion. In contrast, the NF1-R1362Q mutatant behaved like wild-type cells showing only a modest increase in gene expression.

While conducting the ER ChIP experiments, we noted a trend that when NF1 was depleted, more ER was recruited to the chromatin even when the cells were seeded in the presence of vehicle alone (Figure 2D). Consistent with this, expression of GREB1 and TFF1 was significantly stronger in vehicle-treated NF1-I417M mutant cells than in wild-type and the NF1-R1362Q mutant cells (Figure 3F). To further examine these findings in a transcriptome-wide manner, cells were seeded in charcoal-stripped serum supplemented medium without adding ligand, and RNA-seq experiments were performed (Table S5 and Figure 3G). When expression levels of genes (row Z-scores from “Log2 Transcripts per Million” values) in various cell lines were aligned to the list of E2-responsive genes as identified previously (Figure 2A), it was evident that the majority of the E2-induced genes were more highly expressed and many E2-repressed genes were more strongly repressed in the NF1-I417M mutant (right panel, first column, Figure 3G). Essentially, the NF1-I417M mutation mimicked E2-stimulation. In contrast, the NF1-R1362Q mutant behaved like wild-type, showing no detectable transcriptional phenotype (middle and right columns in the right panel, Figure 3G). These results clearly illustrate that ER-repression and Ras-repression are two independent activites of NF1 that are mediated by distinct structural motifs.

Ligand-stimulated nuclear accumulation of neurofibromin.

For transcriptional regulation, neurofibromin must enter the nucleus. While neurofibromin is mainly cytoplasmic, nuclear neurofibromin has been previously reported in a variety of cell types including ER⁺ breast cancer cells (Beausoleil et al., 2004; Daston et al., 1992; Koliou et al., 2016; Kweh et al., 2009; Li et al., 2001; Nousiainen et al., 2006; Vandenbroucke et al., 2004). In one study, neurofibromin nuclear localization in neuronal cells was shown to be dependent on the Ran GTPase (Koliou et al., 2016). This mechanism may also operate in ER⁺ breast cancer, because neurofibromin co-immunoprecipitated with Ran in MCF-7 cells (Figure S3C). Leptomycin-B (LMB) blocks CRM1-dependent nuclear export. MCF-7, ZR-75B, and T47D cells were treated with LMB, and cell fractionation was then used to demonstrate that nuclear neurofibromin is increased after nuclear export blockade (Figure 4A). We further investigated whether NF1 nuclear levels are also affected by E2. Nuclear neurofibromin was decreased by E2 but increased by 4-OHT, indicating that ligand-regulated modulation of nuclear levels is an aspect of the co-repressor function of neurofibromin (Figure 4B). 4-OHT-enhanced ER and neurofibromin co-immunoprecipitation can be readily detected in nuclear extracts, and the percentages of co-immunoprecipitated proteins were higher in the nuclear extracts than in whole cell extracts (Figure 3B). To investigate neurofibromin subcellular localization by microscopy, an immunostaining protocol (Figure 4C) was developed using a set of cell lines with varying degrees of NF1 expression as controls (Figure S4), which included NF1-KO cells. Two cell lines were then chosen to confirm by microscopy the impact of LMB and ER ligands on nuclear neurofibromin levels (Figure 4 D and E). Overall these results suggest that while neurofibromin is mostly cytoplasmic at steady state, it is shuttled in and out of the nucleus, possibly by Ran and CRM-1, in a manner controlled by ER ligand exposure.

Figure 4. — A. Left, whole cell lysates from indicated cell lines treated with LMB were separated into nuclear (Nu.) and cytoplasmic (Cyt.) fractions. NF1, histone-3 (His. 3, nuclear marker), and GAPDH (cytoplasmic marker) were examined by immunoblotting. Right, NF1 levels in the cytoplasmic fraction (light blue) and the nuclear fraction (red) were normalized to GAPDH and His.−3, respectively, and the sum of these two fractions is defined as total NF1 (100%). The numbers in the graph represent the percentages of NF1 determined to be nuclear. The pair-wise comparisons were between NF1 nuclear fractions. n = 2 experiments. B. Left, Cells after ligand stimulation were similarly analyzed as in (A) and an immunoblot of treated MCF-7 cells is shown as an example. n = 3 experiments. C. Immuno-fluorescence deconvolution microscopy was performed using our monoclonal NF1 antibody on cells with varying levels of NF1 protein. A single focal plane across the middle of the nucleus (marked by DAPI) is shown. D. Cells treated with LMB were examined by microscopy. NF1 nuclear fractions were quantified in the indicated number of cells. E. Cells after treatment with ER-ligands were similarly examined by microscopy and quantified. Scale bars = 20 μm. Data are reported as mean±SEM. *p<0.05, **p<0.01, ***p<0.001 by pair-wise two-tailed Student’s t-test.

See also Figure S4.

Ligand-dependent association of neurofibromin with the ER-ERE complex.

When E2 is present, E2-liganded ER recruits co-activators to the ERE; 4-OHT, in turn, displaces co-activators with co-repressors in the complex. These ligand-mediated actions can be recapitulated by a cell-free assay using HeLa cell nuclear extract (Foulds et al., 2013), which does not have endogenous ER. When purified recombinant ER, biotinylated ERE, and HeLa nuclear extract were combined, the E2-liganded ER-ERE complex could more efficiently pull down the co-activator SRC-1 by streptavidin beads, while NF1, like the co-repressor HDAC1, was more strongly recruited to the ER-ERE complex in the presence of 4-OHT (Figure 5A). To assess whether neurofibromin is recruited to endogenous EREs in a ligand-dependent manner, we performed ChIP-qPCR using two separate polyclonal neurofibromin antibodies, one of which, Ab-2, was generated by us (Figure S5A), and found that neurofibromin was more efficiently recruited to the EREs of GREB1 and TFF1 when 4-OHT, but not E2, was added (Figure S5B). NF1-KO cells were examined as the control to show antibody specificity and neurofibromin-dependency (Figure 5B). We then selected ten well-documented ERE sites in six genes, TFF1, GREB1, PGR, MYC, XBP1, and CCDN1, and performed three separate neurofibromin ChIP-qPCR experiments to show that neurofibromin recruitment to these sites was enhanced by 4-OHT; in contrast, no neurofibromin recruitment was detected in other regions (Carroll et al., 2005; Carroll et al., 2006) that do not contain an ERE (Figure 5C). Together, these results demonstrate that neurofibromin is an authentic ER co-repressor that localizes with ER on an ERE. These findings may explain the recent observation that NF1 loss (e.g., by loss of heterozygosity) and ESR1 activating LBD mutations are mutually exclusive (Sokol et al., 2019), because they both lead to enhanced ER transcriptional activity (Gates et al., 2018; Jeselsohn et al., 2018).

Figure 5. — A. Ligands were added to the HeLa nuclear extract together with purified ER and biotinylated EREs immobilized onto streptavidin beads. After washing, the proteins bound to EREs with ER were analyzed by immunoblotting (left) and quantified (right). n = 4 experiments. B. ChIP-qPCR experiment was performed using NF1 antibody Ab-2 to assess NF1 occupancy at the EREs in *GREB1* (Region 2, Figure 2C) or *TFF1* (Region 1, Figure 2C) in parental or NF1-KO (clone 1) MCF-7 cells treated with 4-OHT. An ERE-negative region (site 2) (Carroll et al., 2006) was also analyzed as negative control. n = 2 experiments. C. NF1 occupancy in MCF-7 cells at ten ERE sites in six genes and two negative control regions was assessed by qPCR (n=3 separate ChIP experiments). Data are reported as mean±SEM. *p<0.05, **p<0.01, ***p<0.001 by pair-wise two-tailed Student’s t-test. NS, not significant.

See also Figure S5.

Co-targeting Ras and ER to treat NF1-deficient ER⁺ breast tumors.

The clinical and functional data presented thus far suggests that NF1-deficient ER⁺ breast tumors will not be effectively treated with tamoxifen or AI. However, when NF1 was depleted by either shRNA or CRISPR, the resulting MCF-7 cells were still sensitive to the SERD fulvestrant (Figure S6A). Similar observations were made in NF1^KD ZR-75B and T47D cells (Figure S6B). However, in NF1-silenced MCF-7 cells fulvestrant produced an enhanced compensatory activation of the Ras-Raf-MEK-ERK pathway that may promote cell survival and/or drug resistance in spite of effective ER inhibition (Figure 6A). Thus, combinatorial targeting of both ER with fulvestant and the Ras-Raf pathways was assessed to determine if NF1-deficient ER⁺ breast cancer can be effectively treated with this strategy. In vitro, the combination of Raf and MEK inhibitors, dabrafenib and trametinib enhanced fulvestrant activity to inhibit cell growth by mostly increasing apoptosis in NF1^KD MCF-7 and ZR-75B cells (Figure S6C). Immunoblots showed that all drugs inhibited the intended targets (Figure 6A). To develop a clinical protocol, we next investigated whether the dabrafenib and trametinib combination could be replaced by a single MEK inhibitor (MEKi). Selumetinib is a new generation MEKi that is less toxic than trametinib due to a shorter half-life is under consideration by the FDA for the treatment of plexiform neurofibromas in pediatric patients with neurofibromatosis (Dombi et al., 2016; Gross et al., 2018). Our data demonstrate that in vitro. fulvestrant plus selumetinib also strongly inhibited cell growth and induced apoptosis in NF1-silenced MCF-7, ZR-75B, and T47D cells whereas single agent exposure did not (Figure 6B). Immunoblotting was performed to confirm that the drugs effectively target ER and ERK activation (Figure 6A and Figure S6D).

Figure 6. — A. MCF-7 cells were seeded in 10⁻¹¹ M E2 to which fulvestrant (F), dabrafenib (D), trametinib (T) or selumetinib (S) were subsequently added at 10⁻⁹, 10⁻⁶, 10⁻⁷ or 10⁻⁶ M, respectively. After 6 days, proteins were measured by immunoblotting, and phosphorylation levels (as defined by the levels of the phosphorylated form over total protein) relative to the vehicle-treated cells were set to 1. ND, not detectable. B. Top: cells were grown for 6 days in the presence of 10⁻¹¹ M E2 and 10⁻⁹ M fulvestrant, to which increasing concentration of selumetinib was added. Cell numbers relative to the vehicle control are plotted. n = 3 experiments. Bottom: the cells were treated similarly except 10⁻⁶ M selumetinib was used, and apoptosis was measured 6 days post-treatment. n = 2 experiments. C. WHIM16 tumors were transplanted into cleared mammary fat pad of mice and later randomized to receive treatment (n=15 per treatment arm) when tumor volumes reached 200 mm³. Tumor volume comparison was performed at 52 days post-treatment by t-test between indicated treatment groups, and at the same time, binimetinib (B) was added to the fulvestrant-only arm (marked by the black arrow). After 84 days (grey arrow), treatments were withdrawn from all treatment groups expect the group receiving late binimetinib after initial fulvestrant monotherapy. D. WHIM16 tumors from each treatment arm at week-4 post-treatment in (C) were analyzed by immunoblot (one representative tumor shown on the left), and the results relative to those treated by the vehicle control were quantified on the right (n = 3 tumors). E. qPCR was performed to analyze expression levels of indicated genes from the same tumor samples as in (D). mRNA levels in vehicle-treated samples were set to 1. Data are reported as mean±SEM. *p<0.05, **p<0.01 by t-test. NS, not significant.

In vivo, while tumors from the MCF-7 NF1^KD xenograft model (+DOX) initially responded to fulvestrant, at later time points these tumors acquired resistance (Figure S6E). Acquired fulvestrant resistance in NF1-depleted ER⁺ breast cancer cells has recently also been reported by others (Pearson et al., 2019). We further demonstrated that the fulvestrant-resistant tumor outgrowth in ER⁺ NF1^low cells in vivo can be blocked by dabrafenib and trametinib (Figure S6E). In addition, RNA-seq (Li et al., 2013) and mass spectrometry data (Huang et al., 2017) suggested that a patient-derived xenograft (PDX), WHIM16 (Li et al., 2013), is NF1-deficient. Immunoblotting confirmed NF1 protein levels were barely detectable in WHIM16 (Figure S6F). This PDX line was derived from a patient who died after the development of resistance to multiple lines of endocrine therapies, including fulvestrant and AI.

An initial in vivo assessment of dabrafenib-trametinib in WHIM16 suggested activity for Ras-dependent kinase inhibition with fulvestrant over that observed for fulvestrant alone (Figure S6F), but longer term exposure was limited by weight loss and diarrhea. We therefore replaced the dabrafenib-trametinib combination with selumetinib-laced chow and conducted a four-arm study to compare single agent efficacy versus the combination. These data demonstrate that when selumetinib was combined with fulvestrant, efficient and long-term inhibition/regression of tumor was achieved (Figure 6C) without weight loss (Figure S6G) despite only 50% inhibition of ERK activity. In contrast, selumetinib alone slowed growth but did not induce tumor regression. Western blot confirmed ER degradation by fulvestrant and pERK inhibition by selumetinib (Figure 6D). Selumetinib did not reduce ER phosphorylation at S118 (Figure S6H), suggesting the MEKi efficacy cannot be easily explained on this basis. Binimetinib, another shorter half-life and better tolerated MEKi (Trojaniello et al., 2019), also efficiently inhibited tumor growth when combined with fulvestrant (Figure 6 C and D). Expression of several ERE-containing genes in treated tumors was examined by qPCR. Overall the lowest level of expression correlated with combination fulvestrant and MEKi exposure (Figure 6E). While fulvestrant was ineffective as a single agent, fulvestrant-treated tumors regressed with later addition of binimetinib (Black arrow, Figure 6C), mimicking the treatment of ER⁺ NF1^low tumors progressing on fulvestrant monotherapy. Furthermore, while selumetinib alone can modestly inhibit tumor growth, growth soon resumed after the treatment was withdrawn; in contrast, no relapse was detected in the fulvestrant + MEKi groups after both agents were withdrawn (grey arrow, Figure 6C).

Discussion

This study presents comprehensive evidence that neurofibromin is a transcriptional co-repressor of ER in ER⁺ breast cancer, independent of its GAP activity. Consequently, when NF1 is depleted through somatic mutation, ER function is enhanced, leading to tamoxifen agonism, estradiol hypersensitivity, AI resistance, and poor outcome. These data suggest that the NF1-depleted ER⁺ breast cancers represent a distinct molecular subset of the disease that will require the development a new standard of care since tamoxifen is likely contraindicated and aromatase inhibition ineffective.

Our data suggest that in most cases, complete loss of the NF1 protein is responsible for enhanced ER transcriptional activity and endocrine therapy resistance. Such an NF1-null or NF1^low state can be caused by nonsense and frame shift mutations due to nonsense mRNA decay and/or protein instability. Although nonsense and frame shift mutations are detectable by ctDNA sequencing on metastatic patients, NF1-depletion can also be caused by mechanisms not detectable by targeted sequencing. In a study of breast cancer by whole genome sequencing (Nik-Zainal et al., 2016), Nik-Zainal et al have described a wide range of structural variations affecting NF1 (tandem duplications, deletions, translocations, and inversions). Furthermore, in METABRIC database NF1 nonsense and frame shift mutations are also usually associated with shallow deletion (Griffith et al., 2018), suggesting biallelic loss of function events.

Human and salmon NF1 protein sequences share over 80% identity, which extends well beyond the GAP domain. However, defining a GAP-independent activity in neurofibromin has been difficult because of the broad range of cellular functions influenced by Ras. In hindsight, the commonly used ER⁺ breast cancer cells are ideal for investigating GAP-independent activities of neurofibromin because under standard culture conditions (e.g., in the absence of fulvestrant) growth and ER-dependent transcription operate independently of Ras. This is consistent with the observation that oncogenic mutations in RAS, RAF, MEK, and ERK almost never occur in primary ER⁺ breast cancer. However, Ras dependent cell survival becomes evident when the ER-dependent growth is inhibited by fulvestrant. Activation of Ras is made more efficient by NF1 loss, and NF1^low cells appear to most addicted to this pathway for survival when ER activity is efficiently inhibited. In vivo acquired fulvestrant resistance modeled in the NF1-depleted MCF-7 tumors, was efficiently inhibited by dabrafenib + trametinib. WHIM16 represents metastatic ER⁺ breast cancer that already had acquired fulvestrant resistance when the tumor was accrued from the patient. Fulvestrant has little effect on tumor growth unless the MEK was co-inhibited.

As ER⁺ NF1^low breast cancer acquires fulvestrant resistance, ER and MEK/ERK crosstalk likely occurs, but the finer details of this mechanism are beyond the scope of this paper. We investigated ER phosphorylation at S118 because this can be directly catalyzed by ERK. However, we could not detect a clear increase in pS118 levels in NF1-KO MCF-7 cells; conversely, in the presence of a MEKi, no decrease in pS118 can be seen in the WHIM16 tumors. Interpretation of WHIM16 experiments is complicated by the presence of fulvestrant, which greatly lowers total ER levels. There is a potential for selective stabilization of the S118-phosphorylated form of ER by other protein kinases, such as GSK3 (Grisouard et al., 2007).

In our experiments, estrogen deprivation therapy is mimicked by incubating cells in charcoal-stripped serum-containing media, as is customary in the field (Martin et al., 2017). We demonstrate that growth-simulation can be observed in NF1-depleted cells in vitro with as little as 10⁻¹² M E2, which parallels E2 levels seen in AI-treated patients. We also present evidence from a neoadjuvant trial that AI-resistance can be seen in NF1^low tumors defined at the mRNA level.

Our data suggest that the majority of the 569 NF1^KD-unique genes are well-established E2-responsive genes. We speculate that the reason the expression of these genes was not readily detected unless NF1 is depleted is due to the low E2 concentration (10⁻¹¹ M, see Methods) used to stimulate gene expression in this experiment. This E2 concentration was chosen because it best differentiates the growth of NF1⁺ from NF1^KD cells, making it possible to more easily detect the differences in gene expression pattern we display. However, 10⁻¹¹ M E2 is typical for the postmenopausal state and therefore may be too low to affect expression of some E2-responsive genes, until a co-repressor (NF1) is depleted. Of interest, the 569 genes also include genes responsible for EMT, a phenomenon that has also been seen in other resistance settings, i.e. the presence of ER-mutants (Jeselsohn et al., 2018) and ER-fusions (Lei et al., 2018).

The expression of the rest of the “NF1 knock-down only” genes that do not harbor an ERE is harder to decipher, and many of these genes appear in more than one functional category. Ras does not directly regulate gene expression, so gene expression influenced by Ras activity is likely to be context-dependent. Of the twelve “K-RAS signaling up genes”, three (ID2, SERPINA3, and PCP4) are also defined as “Estrogen response late,” so only the remaining 9 genes may be controlled by Ras activation.

In experimental systems, fulvestrant-resistance can be efficiently inhibited by further targeting MEK in both the MCF-7 and WHIM16 mouse models. These results strongly suggest that activation of the Ras-Raf pathway is the major driver for fulvestrant-resistance in NF1-deficient ER⁺ breast cancer. On this basis there is adequate clinical rationale to activate a clinical trial of a MEKi and a SERD specifically in patients with evidence for a loss of NF1 due to somatic mutation. Of note, WHIM16 regression was achieved with a well-tolerated dose of short half-life MEKi that inhibited ERK signaling by only 50%. This suggests that long term exposures to lower dose MEKi necessary for management of advanced breast cancer will be feasible, and the pediatric experience of neurofibromatosis-related plexiform neurofibroma treatment is relevant here (Gross et al., 2018). We note that a fulvestrant and selumetinib combination failed in a randomized Phase 2 trial (23 patients per arm) in unselected postmenopausal patients (Zaman et al., 2015). This study does not exclude a benefit in ER⁺ NF1^low tumors, however, as it is likely that less than 5 patients harbored NF1^low tumors in this study. Since the prevalence of ER⁺ advanced breast cancer in the USA exceeds 100,000 patients, the ctDNA based evidence suggest at least 7,000 to 10,000 of these individuals will have an NF1^low tumor where a SERD/MEKi combination could be beneficial.

Further research may connect the ER hyperactivity induced by NF1 depletion to other paradoxical or unexplained observations in ER⁺ breast cancer, for example, regression of endocrine therapy-resistant ER⁺ breast cancer with estradiol treatment (Ellis et al., 2009). Additionally, the role of neurofibromin as an ER co-repressor may underlie the sexually dimorphic features of neurofibromatosis, including tumor growth and the preponderance of optic chiasm gliomas during female puberty (Diggs-Andrews et al., 2014).

STAR★METHODS

LEAD CONTACT AND MATERIALS AVAILABILITY

Further information and requests for resources or reagents should be directed to and will be fulfilled by the lead contact Dr. Eric C. Chang at echang1@bcm.edu. All materials generated by this study are available upon request.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Cell lines

The human cell lines, growth media, and general methods of cell culture have been previously reported (Zheng et al., 2015), unless otherwise indicated. All lines were routinely tested for mycoplasma contamination. Estrogen deprivation was achieved by seeding cells in phenol red-free media (DMEM for ZR-75B, MDA-MB-231, and RPMI1640 for MCF-7 and T47D cells) containing 10% charcoal-stripped fetal bovine serum (Sigma-Aldrich) for two days prior to the experiment. Note that MDA-MB-175VII is an NF1-null cell line, apparently carrying biallelic frameshift mutation p.Y2285FS*5 (Neve et al., 2006).

The procedures for producing lentivirus, infecting breast cancer cells, and selecting for stable integrants were also conducted as previously described (Zheng et al., 2015). The cells stably expressing inducible shRNA were collected using FACS (Aria II, Becton Dickinson) two days after DOX treatment (2 μg/ml) by examining the presence of turboRFP, which is expressed together with the shRNA from the same bicistronic transcript. Typically, >85% of transduced cells were RFP⁺. For NF1 overexpression and CRISPR-mediated knock-out by two gRNA sequences, cells were transduced and selected in puromycin (1 μg/ml) and pooled.

Animals

All animal work was approved by the Baylor College of Medicine Institutional Animal Care and Use Committee. For MCF-7 xenografts, prior to transplantation, 5–6 week old female nude mice (Envigo International) were ovariectomized and left to recover for two weeks before an estrogen “capsule” (Robinson and Jordan, 1989) (0.7 cm silicone tubing, Dow Corning) was inserted. These capsules contain 0.5 mg E2 mixed with silicone gel (Factor II) to keep the final weight of the filler at 2 mg. Three days later, one million human cancer cells were suspended in Growth Factor-Reduced Matrigel (BD Biosciences) and PBS and injected into the No. 9 mammary glands. When average tumor volume reached ≈200 mm³, the mice were randomized into different treatment groups, and the E2 capsule in the tumor-bearing mice was replaced with a fresh one, or with a tamoxifen pellet (5 mg/pellet, Innovative Research of America). DOX was added in the drinking water at 0.2 mg/ml to silence NF1 expression. For PDX studies, WHIM16 tumors were engrafted into cleared mammary fat pads of SCID/bg female mice (Envigo International) and allowed to grow without exogenous E2 supplementation until tumors reached ≈200 mm³. Mice were then randomized into different treatment groups. Fulvestrant was injected subcutaneously at 250 mg/kg weekly. Trametinib (1 mg/kg), dabrafenib (30 mg/kg), binimetinib (20 mg/kg), and selumetinib (20 mg/kg) were given daily as chow (Research Diets Inc.). Mouse body weight was measured twice weekly to monitor treatment toxicity.

METHOD DETAILS

Chemicals

Chemicals used are listed in Key Resource Table. Note that with the exception of the animal experiments, in all other experiments involving E2, the water-soluble version was used. Ethanol was used to dissolve 4-OHT, while DMSO was used to dissolve trametinib, dabrafenib, fulvestrant, and selumetinib. We note that drug concentrations were selected such that fulvestrant plus the selumetinib combination can more easily produce an effect on the cells that is greater than either group alone.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Mouse monoclonal NF1 (against aa2471-2839, 1:200)	This study	N/A
Rabbit polyclonal NF1 (against aa2471-2839)	This study	N/A
NF1 (against aa2760–2839)	Bethyl Laboratories	Cat#A300-140A; RRID:AB_2149790
NF1 (against N-terminus, 1:500)	Cell Signaling Technology	Cat#14623; RRID:AB_2798543
ER-α (1:500)	Cell Signaling Technology	Cat#8644; RRID:AB_2617128
ER-α (HC-20)	Santa Cruz Biotechnology	Cat#sc-8002X; RRID:AB_627558
ER-α (F-10, ChIP grade, 1:5000 for Western blots)	Santa Cruz Biotechnology	Cat# sc-8002X; RRID:AB_627558
phospho-ER-α (Ser118, 1:500)	Millipore-Sigma	Cat#05–793; RRID:AB_310004
ERK1/2 (1:500)	Cell Signaling Technology	Cat#9102; RRID:AB_330744
Phospho-ERK1/2 (Thr202/Tyr204, 1:500)	Cell Signaling Technology	Cat#9101; RRID:AB_331646
AKT (1:500)	Cell Signaling Technology	Cat#4691; RRID:AB_915783
Phospho-AKT (Ser473, 1:500)	Cell Signaling Technology	Cat#4060; RRID:AB_2315049
His-tag (1:1000)	Cell Signaling Technology	Cat#2365; RRID:AB_2115720
Ran (1:1000)	Cell Signaling Technology	Cat#4462; RRID:AB_2284873
Histone-3 (1:1000)	Cell Signaling Technology	Cat#4499; RRID:AB_10544537
DNA-PKcs (1:1000)	Cell Signaling Technology	Cat#4602; RRID:AB_10692482
K48-linkage specific polyubiquitin (1:1000)	Cell Signaling Technology	Cat#8081; RRID:AB_10859893
α/β-tubulin (1:2000)	Cell Signaling Technology	Cat#2148; RRID:AB_2288042
α-tubulin (1:10,000)	Santa Cruz Biotechnology	Cat#sc-5286; RRID:AB_628411
p120/RasGAP (1:1000)	Santa Cruz Biotechnology	Cat#sc-63; RRID:AB_628206
SRC-1 (1:1,000)	Santa Cruz Biotechnology	Cat#sc-6096; RRID:AB_661355
HDAC1 (1:1,000)	Santa Cruz Biotechnology	Cat#sc-81598; RRID:AB_2118083
GAPDH (1:10,000)	Santa Cruz Biotechnology	Cat#sc-32233; RRID:AB_627679
Normal Mouse IgG	Santa Cruz Biotechnology	Cat# sc-2025; RRID:AB_628411
Normal Rabbit IgG	Millipore-Sigma	Cat# 12-370; RRID:AB_145841
Bacterial and Virus Strains
BL21 (DE3)	Agilent	Cat#200131
Biological Samples
Patient-derived xenografts (PDX) WHIM16	(Li et al., 2013)	N/A
Chemicals, Peptides, and Recombinant Proteins
17β-estradiol (E2)	Sigma-Aldrich	Cat#E8875
Cyclodextran-encapsulated “water-soluble” E2	Sigma-Aldrich	Cat#E4389
(Z)-4-hydroxytamoxifen (4-OHT)	Sigma-Aldrich	Cat#H7904
Doxycycline (DOX)	Sigma-Aldrich	Cat#D9891
Human epidermal growth factor (EGF)	Sigma-Aldrich	Cat#E4127
Leptomycin B (LMB)	Sigma-Aldrich	Cat#L2913
Bufalin	Sigma-Aldrich	Cat#B0261
Phenylmethanesulfonylfluoride (PMSF)	Sigma-Aldrich	Cat#78830
DMSO	Sigma-Aldrich	Cat#D8418
Ethanol	Sigma-Aldrich	Cat#E7023
MG132	Millipore-Sigma	Cat#474790
Polybrene	Millipore-Sigma	Cat#TR-1003-G
Trametinib	Selleck Chemicals, MedChem Express, or Novartis	Cat#S2673 or Cat#HY-10999A
Dabrafenib	Selleck Chemicals or MedChem Express	Cat#S2807 or Cat#HY-14660A
Fulvestrant	MedChem Express	Cat#HY-13636
Binimetinib	MedChem Express	Cat#HY-15202
Selumetinib	Selleck Chemicals or MedChem Express	Cat#S1008 or Cat#HY-50706
Recombinant ERα protein	ThermoFisher Scientific	Cat#A15674
Critical Commercial Assays
TruSeq RNA Library Prep Kit	Illumina	Cat# RS-122-2001
KAPA Library Quantification Kit	Kapa Biosystems	Cat# KR0405
Deposited Data
RNA-Seq	GEO	GSE142479
Experimental Models: Cell Lines
MCF-7	ATCC	Cat#HTB-22; RRID:CVCL_0031
ZR-75B	A gift from Marc E. Lippman (Georgetown Univ., Med. Cntr.)	RRID:CVCL_5614
T47D	ATCC	Cat#HTB-133; RRID:CVCL_0553
Experimental Models: Organisms/Strains
Athymic nude mice	Envigo	N/A
SCID/bg	Envigo	N/A
Oligonucleotides
See Table S6.	This study	N/A
Recombinant DNA
pMD2.G	Addgene	Cat#12259
pSPAX2	Addgene	Cat#12260
pINDUCER11-scrambled shRNA	This study	N/A
pINDUCER11-NF1 shRNA clone 5	This study	N/A
pINDUCER11-NF1 shRNA clone 6	This study	N/A
pLentiCRISPR v2-scramble	This study	N/A
pLentiCRISPR v2-NF1 clone 1	GenScript	N/A
pLentiCRISPR v2-NF1 clone 2	GenScript	N/A
pDONR225-NF1	A gift from the RAS Initiative at the Frederick National Laboratory for Cancer Research at NCI	N/A
pCL-FLAG	Zheng et al., 2012	N/A
pCL-FLAG-NF1	This study	N/A
pCL-FLAG-NF1-R2258*	This study	N/A
pCL-FLAG-NF1-Y2285*	This study	N/A
pCL-FLAG-NF1-R2450*	This study	N/A
pCL-FLAG-NF1-R1362Q	This study	N/A
pCL-FLAG-NF1-K1444R	This study	N/A
pCL-FLAG-NF1-I417M	This study	N/A
pCL-FLAG-NF1-V1308A/I1309A	This study	N/A
pM-NF1	This study	N/A
pM-NF1-R1362Q	This study	N/A
pM-NF1-K1444R	This study	N/A
pM-NF1-I417M	This study	N/A
pM-NF1-I417A/I418A	This study	N/A
pM-NF1-V1308A/I1309A	This study	N/A
pDEST566-GST	This study	N/A
pDEST566-NF1-M2/GAP	A gift from the RAS Initiative at the Frederick National Laboratory for Cancer Research at NCI	N/A
SpCas9(BB)-2A-GFP(PX458)	Addgene	Cat# 48138; RRID: Addgene_48138
pGL4.70-RLuc	Promega	Cat#E688A
pGL2-ERE-Luc	A gift from Donald P. McDonnell (Duke Univ.)	Hall and McDonnell, 1999
5×Gal4-Luc	Promega	Cat#E2440
pVP16-ERα	A gift from Donald P. McDonnell	Chang et al., 1999
pVP16-SRC1	A gift from Donald P. McDonnell	Chang et al., 1999
pVP16-NCoR1	A gift from Donald P. McDonnell	Chang et al., 1999
Software and Algorithms
ImageJ	Schneider et al., 2012	https://imagej.nih.gov/ij/
SoftWorx v7.0	GE Healthcare	N/A
FlowJo	FlowJo	N/A
Bowtie2	Langmead and Salzberg, 2012	http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
RSEM v1.2.31	Li and Dewey, 2011	https://deweylab.github.io/RSEM/
R 3.3.4	R Core Team	N/A

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Plasmids

Scrambled and NF1-targeting shRNAs (clone C5 and C6) in pGIPZ were obtained from Dharmacon. All nucleotide sequences used in this study are described in Key Resource Table and Table S6. The shRNA clones were subcloned into pINDUCER11, with which cell lines stably expressing DOX-inducible scrambled or NF1 shRNA were later created as described (Zheng et al., 2015). Unless otherwise mentioned, data obtained from cell lines expressing NF1 shRNA C5 are shown in the figures, while the cells expressing C6 were also tested in most experiments. NF1 CRISPR-Cas9 knock-out (KO) constructs (clone #1 and #2 in pLentiCRISPR v2) were purchased from GenScript, and scrambled gRNA sequences were synthesized and then cloned into pLentiCRISPR v2. pDONR225-NF1 was a kind gift from the RAS Initiative at the Frederick National Laboratory for Cancer Research at NCI. The full-length NF1 coding sequence in this vector has been extensively modified to facilitate expression studies without changing the amino acid sequence. To analyze its expression, an “NF1 (NCI)” primer set was used for RT-PCR. This NF1 coding sequence is also refractory to both the C5 and C6 shRNA clones. NF1 mutants were created by site-directed mutagenesis (QuickChange II XL Site-Directed Mutagenesis Kit, Agilent Technologies) using pDONR225-NF1 as the template. These cDNAs were finally transferred into destination vectors pCL-FLAG and pM (Chang et al., 1999) to create pCL-FLAG-NF1, pM-NF1, pCL-FLAG-NF1-R2258*, pCL-FLAG-NF1-Y2285*, pCL-FLAG-NF1-R2450*, pCL-FLAG-NF1-R1362Q, pM-NF1-R1362Q, pCL-FLAG-NF1-K1444R, pM-NF1-K1444R, pCL-FLAG-NF1-I417M, pM-NF1-I417M, pM-NF1-I417A/I418A, pCL-FLAG-NF1-V1308A/I1309A, and pM-NF1-V1308A/I1309A. pDEST566-NF1-M2/GAP (Bollag et al., 1993), which expresses recombinant 6×His-MBP tag at the N-terminus of NF1-M2/GAP in E. coli, was also a gift from the NCI RAS Initiative. pDEST566-GST was built by transferring GST cDNA from pENTR-GST to pDEST566.

Generation of NF1 point mutation knock-in (KI) cells using CRISPR-Cas9

MCF-7 cells carrying homozygous mutations were generated by the Cell-Based Assay Screening Service core at Baylor College of Medicine (BCM). The general procedure is as described previously (Ran et al., 2013) and depicted in the right figure. Briefly, gRNA sequences were cloned into SpCas9(BB)-2A-GFP (PX458, a gift from Feng Zhang, Addgene plasmid #48138; http://n2t.net/addgene:48138; RRID: Addgene_48138). In addition to silent mutations that prevent Cas9 cleavage, each single-stranded oligodeoxynucleotide (ssODN) repair template also contains an engineered restriction site to facilitate identification of the KI allele. Cells were co-transfected with the CRISPR/gRNA plasmid and its corresponding ssODN template using the Neon transfection system (Thermo Fisher Scientific). The resulting GFP⁺ cells were plated by limiting dilution for single clone isolation. The genomic region surrounding each target site was PCR-amplified for validation by sequencing.

Assays for cell growth and apoptosis

To compare cell growth between NF1⁺ and NF1^KD cells, cells stably expressing NF1 shRNA were first seeded in estrogen-deprived medium, typically in triplicate, with DOX added at the same time. Two days later (Day-0), the medium was replaced with a fresh medium containing either vehicle control or compound(s) under investigation, with medium change every three days thereafter. The number of viable cells was measured using the CellTiter 96 Aqueous One Solution Cell Proliferation Assay kit (Promega) six days later (Day-6). Cell growth between parental and NF1 knock-out cells was similarly examined except no DOX was added. Apoptosis was measured by FITC-Annexin (Becton Dickinson) staining followed by FACS.

Generation of NF1 antibodies

A cDNA encoding amino acid residues 2471–2839 in NF1 was subcloned into pRP259 (Chang et al., 1994) to express this C-terminal fragment of NF1 (NF1C) as a GST-tagged protein in E. coli (BL21 DE3). Purified GST-NF1C was injected into rabbits (Thermo Fisher Scientific) or mice (Protein and Monoclonal Antibody Production Shared Resource at BCM) to generate polyclonal and monoclonal antibodies, respectively. The polyclonal antibody from one rabbit (NF1 Ab-2, Figure S5A) was later affinity-purified against the same immunizing antigen. One hybridoma clone (mAb-376) was expanded in vitro and IgG was purified from culture medium by protein-G Sepharose column chromatography.

Immunoprecipitation (IP)

Cells grown in E2-deprived medium were treated with E2 (10⁻¹¹ M), 4-OHT (10⁻⁷ M), or the vehicle (ethanol) for 4 hrs before being isolated for whole cell or nuclear extracts. To conduct IP using whole cell extracts, cells were lysed in RIPA buffer supplemented with 1 mM PMSF and protease and phosphatase inhibitors (Roche Applied Science). The cell lysates were precleared with mouse IgG beads (Sigma, 3 hours at 4°C) before NF1 (mAb-376) or ER (F-10 monoclonal, Santa Cruz) antibody or the mouse IgG control (Santa Cruz) was added. Samples were incubated at 4°C overnight, followed by incubation with protein A/G agarose beads (Santa Cruz) for another 4 hours. All beads were finally washed three times with TBS (20 mM Tris-HCl (pH 7.5) and 150 mM NaCl). The bound proteins were eluted with 2× SDS sample buffer by boiling for 5 minutes and then examined by immunoblotting. To conduct IP using nuclear extracts, the same antibodies were pre-incubated with the protein-G Dynabeads™ (Thermo Fisher Scientific) overnight at 4°C before mixing with nuclear extracts which were prepared as described previously (Lanz et al., 2010). All beads were washed twice with NETN buffer (20 mM Tris-HCl (pH 7.5), 1 mM EDTA, 150 mM NaCl, and 0.5% NP-40), and once with PBS before elution and immunoblotting.

Immunoblotting

Cell lysates were generally prepared in RIPA buffer supplemented with protease and phosphatase inhibitors, and proteins were separated by SDS-PAGE before being transferred to nitrocellulose membranes. The primary antibodies used are listed in Key Resource Table. The fluorescein-conjugated secondary antibodies were from Li-COR Biosciences, and the protein levels were quantified by an Odyssey infrared imaging system (Li-COR Biosciences).

RNA-seq

Estrogen-deprived MCF-7 cells were treated with E2 (10⁻¹¹ M), 4-OHT (10⁻⁷ M), or ethanol (vehicle) before RNA was extracted after 24 hrs using RNeasy Mini Kit (Qiagen) according to manufacturer’s directions. The E2 concentration used in this and the ChIP experiment was chosen because it can efficiently differentiate the growth between NF1⁺ and NF1-depleted cells (Figure 1E). Because the E2 concentration used was low, pilot qPCR experiments were conducted to determine that it takes 24 hrs after E2 stimulation to observe substantial difference in gene expression between these cells. MCF-7 CRISPR KI cells were simply grown in estrogen deprivation medium for 72 hrs before RNA extraction. The Genomic and RNA Profiling Core (GARP) at BCM constructed libraries with 250 ng of total RNA using the TruSeq RNA Library Prep Kit (Illumina). cDNA was generated from poly(A)-selected RNA. Libraries were quantified with the KAPA Library Quantification Kit (Kapa Biosystems) and were sequenced on the NextSeq 500 (Illumina) with paired-end 75bp reads and aligned to the hg19 (GRCh37) reference genome using RSEM v1.2.31 (Li and Dewey, 2011) and Bowtie 2 (Langmead and Salzberg, 2012).

Differential gene expression and fold change analysis was performed using EBseq (Leng et al., 2013) with FDR < 0.2 as a cutoff. Differentially expressed genes were subsequently used in Gene Set Enrichment Analysis (GSEA) for “Hallmark Pathways” in the Molecular Signatures Database (MSigDB) (Subramanian et al., 2005) and the top 10 enriched pathways were reported. For validation in clinical datasets, mRNA levels of the 1,107 genes identified from the MCF-7 cell line study were analyzed in TCGA and METABRIC ER⁺ breast cancer cohorts using cBioportal (Cerami et al., 2012; Gao et al., 2013). Genes in these cohorts that are differentially expressed between NF1-FS/NS and NF1-WT tumors were identified by t-test with p values cutoff at < 0.05. The differentially expressed genes in these clinical validation datasets were each similarly analyzed for “Hallmark” pathways enrichment as above (FDR<0.05). Clustering was performed using Hierarchical Clustering in R.

ChIP

The cells were seeded in E2-deprived medium. After 48 hrs, the cells were treated with E2 (10⁻¹¹ M), 4-OHT (10⁻⁷ M), or the vehicle control (ethanol) for 45 min before ChIP, which was performed as described (Chen et al., 2008). Specifically, crosslinking was performed using 1% formaldehyde for 10 min at room temperature and quenched by glycine (final concentration of 125 mM). Cells were then scraped off the plate with ice-cold TBSE buffer (20 mM Tris-HCl, pH 7.5, 1.0 mM EDTA, 150 mM NaCl) and pelleted by centrifugation. Next, pelleted cells were resuspended in lysis buffer (10 mM Tris-HCl, pH 8.0, 0.25% Triton X-100, 10 mM EDTA, 100 mM NaCl) to release nuclei. The nuclei were further lysed in 1% SDS buffer (50 mM HEPESKOH, pH 7.5, 1% Triton X-100, 0.1% sodium deoxycholate, 1% SDS, 2 mM EDTA, 150 mM NaCl) and sonicated using a Branson Sonicator to shear genomic DNA to an average fragment size of 200 to 500 bp. ChIP was performed with a commercially available antibody against ER-α (HC-20 and F10 for ChIP-qPCR, and F10 for ChIP-seq, Santa Cruz), a rabbit polyclonal NF1 antibody (A300–140A from Bethyl Laboratories; Ab-1), a polyclonal NF1 antibody made by us (above; Ab-2), a rabbit IgG control (Millipore) or a mouse IgG control (Santa Cruz) added to the same amount of chromatin after SDS was diluted to 0.1%. The precipitated DNA was isolated by phenol-chloroform extraction. To assess ERE occupancy by qPCR, fold-enrichment of amplified ERE levels in the ChIPed samples vs. those in inputs were calculated.

qPCR

RNA was isolated using the RNeasy kit (Qiagen), and cDNAs were synthesized from 5 μg of total RNA using the SuperScript IV First-Strand Synthesis System (Thermo Fisher Scientific). Real-time PCR was performed with Fast SYBR Green Master Mix on a Light Cycle 96 (Roche Life Science) or CFX (Bio-Rad) Real-Time PCR system. The PCR primers used are described in Table S6. The relative amounts of PCR products generated from each primer set were determined on the basis of threshold cycle (Ct) using GAPDH as the loading control.

ERE-luciferase reporter assay

MCF-7 cells were seeded in E2-deprived medium for one day before being transfected with pGL2-ERE-Luc (Hall and McDonnell, 1999), which contains 3× vitellogenin EREs, for another day. The cells were then treated with 10⁻¹¹ M E2 for 24 hrs. Cells were also co-transfected with pGL4.70-RLuc (Promega, Madison, WI, USA) to express Renilla luciferase as an internal transfection efficiency control. The firefly and Renilla luciferase levels were measured using the Dual-Luciferase Reporter Assay kit (Promega).

The mammalian two-hybrid assay

The mammalian two-hybrid assays measuring the binding between ER and its coregulators have been described (Chang et al., 1999). Briefly, HEK293 cells were co-transfected by pM vectors expressing various versions of NF1 fused to the Gal4 DNA binding domain (DBD), as well as pVP16 vectors expressing various ER fragments fused to the VP16 transcriptional activation domain. These cells were also co-transfected to carry the firefly luciferase reporter 5×Gal4-Luc3 and the pGL4.70-RLuc, whose Renilla luciferase activity was measured to control transfection efficiency. Fusion protein expression levels were also assessed by Western blot. Luciferase activities were measured two days later. To determine whether the NF1-ER interaction can be modulated by E2 and 4-OHT, cells were estrogen-starved before transfection. E2 (10⁻¹¹ M), 4-OHT (10⁻⁷ M), or the vehicle control was added one day post-transfection. The luciferase activity was measured after another day.

ER and NF1-M2/GAP in vitro binding assay

E. coli BL21 (DE3) cells carrying either pDEST566-GST or pDEST566-NF1-M2/GAP were induced by 1 mM IPTG at 30°C for 4 hrs. The cell pellets were then resuspended in ice-cold MBP binding buffer (20 mM Tris-HCl (pH 7.4), 200 mM NaCl, 1 mM EDTA, 1 mM DTT, 1 mM PMSF, and protease inhibitors) and sonicated. The cell lysates were incubated with amylose magnetic beads (New England Biolabs) for 4 hrs at 4°C and washed by the MBP binding buffer. After elution (2× SDS sample buffer), the concentrations of bound proteins on the beads were quantified using BSA as the standard. Purified recombinant ER-α (10 ng, Thermo Fisher Scientific) was pre-incubated with 100 nM E2, 5 μM 4-OHT, or ethanol for 1 hr at 4°C, and then mixed with 200 ng bead-bound NF1-M2/GAP or the GST control, which was pre-incubated with 1 mg/ml BSA in MBP binding buffer for 1 hr at 4°C to reduce non-specific binding. After 1 hr at 4°C, the bound proteins were eluted with 2× SDS sample buffer and examined by immunoblotting.

Cell fractionation

The experiments were conducted as previously described (Suzuki et al., 2010). Leptomycin B (LMB) at 40 nM or ethanol (vehicle) was given to the cells grown in regular growth medium for 6 hours. To assess the influence of ER ligands, cells were first starved in E2-deprived medium and then treated with E2 (10⁻¹¹ M), 4-OHT (10⁻⁷ M), or the vehicle control for 16 hours.

Immunofluorescene deconvolution microscopy

Cells were seeded and treated by LMB or ER-ligands (above) in 12-well plates with an 18-mm No. 1.5 coverslip. The fixation (4% formaldehyde), permeabilization (200 mM glycine/1X PBS, 0.1% Triton X-100), and blocking (5% goat serum) were performed as previously described (Cheng et al., 2011). The sample was incubated with NF1 antibody mAb-376 at room temperature for 2.5 hrs. We found that it is important to optimize the dilution factor for the secondary antibody to reduce background. Alexa-Fluor™ 488 conjugated goat anti-mouse IgG secondary Ab (Thermo Fisher Scientific) was added after a 1:1,000 dilution in the blocking solution and incubation was performed in the dark for 1 hr. The samples were then mounted to slides with a DAPI-containing mounting medium (Vector Laboratories). Imaging was performed at the Integrated Microscopy Core at BCM on a DVLive epifluorescence image restoration microscope (GE Healthcare). The system is equipped with an Olympus PlanApo 60×/1.42 N.A. objective and a pco.EDGE sCMOS_5.5 camera with a resolution up to 2,560 ×2,160 pixels. The filter sets used were: DAPI and FITC. Z stacks (0.2 μm) covering the whole cell (~12 μm) were acquired before applying a conservative restorative algorithm for quantitative image deconvolution using SoftWorx v7.0. Image J was used to quantify NF1 levels. For each cell a single focal plane dissecting the middle of the nucleus was chosen, from which two ROIs were created: ROI-1 encircles the whole cell while ROI-2 encircles just the nucleus. The reported relative NF1 nuclear levels were defined as: ROI-2/ROI-1.

ERE pull-down using HeLa cell nuclear extract

These assays were conducted similarly to those previously described (Foulds et al., 2013). Briefly, 1 mg of HeLa S3 nuclear extract and 0.5 μg of purified recombinant ER were added to 4 μg of a 921 bp biotinylated 4× ERE DNA fragment immobilized onto 60 μl Dynabeads™ M280 (Thermo Fisher Scientific). Different ligands were included in these recruitment assays. After washing twice in NETN and once in DPBS, the retained proteins were detected by immunoblotting.

QUANTIFICATION AND STATISTICAL ANALYSIS

All reported data were typically presented as mean ± s.e.m. and pair-wise comparisons were analyzed by two-sided Student’s t-test unless otherwise mentioned. The n values are either separate biological replicates or numbers of cells or mice, as indicated. Human tumor databases were analyzed using the R statistical packages. We note that throughout this paper *, p<0.05; **, p<0.01; ***, p<0.001; NS, Not Significant (p≥0.05).

NF1 mutation frequency in patients

The extraction and general sequencing pipeline of cell-free DNA has been described previously (Lanman et al., 2015). Specifically, for NF1, most of its exons (except exons 1, 7, 15, 19, 22, 23, 29, 31, 51, and 56–61) were completely sequenced, and single nucleotide variants as well as small indel events were analyzed. M1 and M2 are encoded by exons 11 (25 amino acids) and 29 (35 amino acids). cBio (Cerami et al., 2012) was used for somatic mutation and clinical data mining. Mutations were visualized using the GeneVisR (Skidmore et al., 2016) Bioconductor package. The cohort of primary breast cancers was from TCGA (TCGA, 2012), while the metastatic cohort was described (Lanman et al., 2015).

Patient proliferation status after aromatase inhibitor (AI) treatments

Patients in the ACOSOG Z1031 trial (Ellis et al., 2011) were treated by AIs in a neoadjuvant setting, and their mRNAs before and after treatment were analyzed by Agilent microarray. A multigene proliferation score (MGPS) derived from mRNA expression of 772 genes was used to analyze proliferation status in the patient to assess treatment response (Ellis et al., 2017).

NF1 expression level analysis in patients

NF1 mutation types in TCGA (Ciriello et al., 2015) and METABRIC (Pereira et al., 2016) were mined from cBio (Cerami et al., 2012; Gao et al., 2013). NF1 mRNA levels in ER⁺ breast tumors from the METABRIC cohort (Curtis et al., 2012) together with survival information were obtained from Oncomine (Rhodes et al., 2007). High and low NF1 mRNA levels were as defined above. Univariate Cox regression was analyzed using the Survival package for R.

Protein levels correlation analysis

We have previously shown that protein co-expression is a strong predictor for co-functionality (Wang et al., 2017a). To identify proteins co-expressed with NF1, we used the LinkedOmics tool (http://www.linkedomics.org) (Vasaikar et al., 2018) to calculate the Pearson’s correlation coefficient between NF1 and all other proteins in the CPTAC (Clinical Proteomic Tumor Analysis Consortium) breast cancer mass spectrometry dataset, which contains 105 breast tumor samples (Mertins et al., 2016). We ranked the proteins based on correlation coefficient scores and then analyzed them using Gene Set Enrichment Analysis (GSEA) in WebGestalt (Wang et al., 2017b) to identify enriched Gene Ontology (GO) molecular functions. As a control, we similarly analyzed p120GAP/RASA1.

DATA AND SOFTWARE AVAILABILITY

RNA-seq data are deposited in Gene Expression Omnious (GEO) database, accession number GSE142479.

Supplementary Material

NIHMS1568796-supplement-2.pdf^{(2.6MB, pdf)}

Table S1, related to Figure 1. Non-silent NF1 mutations identified by sequencing circulating tumor DNA in a metastatic ER+ breast cancer cohort.

NIHMS1568796-supplement-3.xlsx^{(24.2KB, xlsx)}

Table S2, related to Figure 1. Multi Gene Proliferation Scores (MGPS) of samples in the Z1031 trial.

NIHMS1568796-supplement-4.xlsx^{(16.3KB, xlsx)}

Table S3, related to Figure 2. E2 and 4-OHT modulated gene expression changes in the MCF-7 cell model.

NIHMS1568796-supplement-5.xlsx^{(223.6KB, xlsx)}

Table S4, related to Figure 2. Hallmark Pathway enrichment validation in patient data in TCGA and METABRIC.

NIHMS1568796-supplement-6.xlsx^{(72.5KB, xlsx)}

Table S5, related to Figure 3. Gene expression as analyzed by RNA-seq in MCF-7 cells carrying wild-type NF1 or an NF1 Knock-in mutation.

NIHMS1568796-supplement-7.xlsx^{(44.8KB, xlsx)}

Table S6, related to STAR Methods. Oligonucleotides sequences used for this study.

NIHMS1568796-supplement-8.xlsx^{(12.4KB, xlsx)}

Highlights.

NF1 is a GAP-independent estrogen receptor transcription co-repressor.
Somatic NF1 loss causes tamoxifen/aromatase inhibitor resistance in ER⁺ breast cancer.
A MEK inhibitor plus a SERD is effective in NF1⁻ ER⁺ PDX and cell line models.

Significance.

Neurofibromin is a co-repressor of estrogen receptor (ER), therefore loss enhances ER transcriptional activity. Loss-of-function mutations in the NF1 gene promote tamoxifen agonism and estrogen-deprivation resistance. While ER⁺ NF1-depleted cells are initially responsive to fulvestrant, a selective ER degrader, enhanced Ras activity promotes acquired resistance. When Ras pathway activation is inhibited with a well-tolerated MEK inhibitor, fulvestrant resistance is reversed and full tumor regression ensues. Thus, neurofibromin-depletion represents a distinct breast cancer subset where the choice of endocrine treatment may be critical, and MEK inhibitor combinations require clinical investigation. A role as a dual repressor for both Ras and ER may also explain the sexually dimorphic characteristics of neurofibromatosis where tumorigenesis is promoted by female puberty.

Acknowledgements

We thank our colleagues for providing valuable resources and advice: Bert O’Malley, Anna Malovannaya, Jun Qin, Daniel Yan, Khushboo Shah, Jianhui Yao, Svasti Haricharan, Angela D. Wilkins, Dominic Esposito, Gary Chamness, Laura Smithson, David Gutmann, Ching-Yi Chang, and Donald McDonnell. This project was assisted by the following core facilities in the Dan L. Duncan Comprehensive Cancer Center: Cell-Based Assay Screening Service, Cytometry and Cell Sorting, Biostatistics and Informatics Shared Resource, Integrated Microscopy Core, Genomic and RNA Profiling Core, and the Protein and Monoclonal Antibody Production Shared Resource, which are all supported by a P30 Cancer Center Support Grant from NCI (CA125123). The Integrated Microscopy Core is also supported by grants from NIH (DK56338), CPRIT (RP150578 and RP170719) and the John S. Dunn Gulf Coast Consortium for Chemical Genomics. The Cell Sorting Core was also supported by P30AI036211 and S10RR024547. BC was supported by an ASCO Gianni Bonadonna Research Fellowship, and JTL was supported by T32GM008129 and T32CA203690 from NIH. CEF and YC were supported by the Adrienne Helis Malvin Medical Research Foundation through its direct engagement in the continuous active conduct of medical research in conjunction with BCM. ECC was supported by The Susan G. Komen Foundation (SAC150059), DOD (W81XWH-16-1-0538 and W81XWH-19-1-0527), Nancy Owen Memorial Foundation, NIH (R21CA185516 and P50CA186784), William and Ella Owens Foundation, and CPRIT (RP180844). M.J.E. is a CPRIT Scholar in cancer research supported by a CPRIT Established Investigator Recruitment Award RR140033 and is a McNair Scholar supported by the McNair Foundation. This research was also supported by NIH/NCI grants R01 CA095614 and U54CA233223 awarded to M.J.E. and by Susan G. Komen for the Cure Promise Grant PG12220321.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Declaration of Interests: Most authors declare no competing financial interests except: KCB and RBL are stockholders and employees of Guardant Health, Inc., CEF discloses an equity position in Coactigon, Inc., and MJE received consulting fees from Abbvie, Sermonix, Pfizer, AstraZeneca, Celgene, NanoString, Puma, and Novartis, and is an equity stockholder, consultant, and Board Director member of BioClassifier, and inventor on a patent for the Breast PAM50 assay.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

NIHMS1568796-supplement-2.pdf^{(2.6MB, pdf)}

Table S1, related to Figure 1. Non-silent NF1 mutations identified by sequencing circulating tumor DNA in a metastatic ER+ breast cancer cohort.

NIHMS1568796-supplement-3.xlsx^{(24.2KB, xlsx)}

Table S2, related to Figure 1. Multi Gene Proliferation Scores (MGPS) of samples in the Z1031 trial.

NIHMS1568796-supplement-4.xlsx^{(16.3KB, xlsx)}

Table S3, related to Figure 2. E2 and 4-OHT modulated gene expression changes in the MCF-7 cell model.

NIHMS1568796-supplement-5.xlsx^{(223.6KB, xlsx)}

Table S4, related to Figure 2. Hallmark Pathway enrichment validation in patient data in TCGA and METABRIC.

NIHMS1568796-supplement-6.xlsx^{(72.5KB, xlsx)}

Table S5, related to Figure 3. Gene expression as analyzed by RNA-seq in MCF-7 cells carrying wild-type NF1 or an NF1 Knock-in mutation.

NIHMS1568796-supplement-7.xlsx^{(44.8KB, xlsx)}

Table S6, related to STAR Methods. Oligonucleotides sequences used for this study.

NIHMS1568796-supplement-8.xlsx^{(12.4KB, xlsx)}

Data Availability Statement

RNA-seq data are deposited in Gene Expression Omnious (GEO) database, accession number GSE142479.

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PERMALINK

Neurofibromin is an Estrogen Receptor-α Transcriptional Co-repressor in Breast Cancer

Ze-Yi Zheng

Meenakshi Anurag

Jonathan T Lei

Jin Cao

Purba Singh

Jianheng Peng

Hilda Kennedy

Nhu-Chau Nguyen

Yue Chen

Philip Lavere

Jing Li

Xin-Hui Du

Burcu Cakar

Wei Song

Beom-Jun Kim

Jiejun Shi

Sinem Seker

Doug W Chan

Guo-Qiang Zhao

Xi Chen

Kimberly C Banks

Richard B Lanman

Maryam Nemati Shafaee

Xiang H-F Zhang

Suhas Vasaikar

Bing Zhang

Susan G Hilsenbeck

Wei Li

Charles E Foulds

Matthew J Ellis

Eric C Chang

Summary

Graphical Abstract

In Brief (eTOC blurb)

Introduction

Results

NF1 loss correlates with poor patient outcome in ER+ breast cancer.

Figure 1. NF1 loss promotes tamoxifen agonism and E2 hypersensitivity leading to poor patient outcome in ER+ breast cancer.

NF1-depletion promotes tamoxifen agonism and E2 hypersensitivity in ER+ breast cancer cells.

NF1-depletion globally enhances ER transcriptional activity.

Figure 2. NF1-depletion globally enhances ER transcriptional activity.

NF1-depletion increases ER recruitment to EREs.

Neurofibromin contains two leucine/isoleucine rich co-repressor motifs.

Figure 3. Neurofibromin binding to ER is selectively mediated by co-repressor motifs.

The binding of ER to neurofibromin is selective, ligand-dependent, and direct.

ER binding and GAP activity are two independent functions of neurofibromin.

Ligand-stimulated nuclear accumulation of neurofibromin.

Figure 4. ER ligand-mediated nuclear accumulation of neurofibromin.

Ligand-dependent association of neurofibromin with the ER-ERE complex.

Figure 5. Ligand-dependent association of neurofibromin with the ER-ERE complex.

Co-targeting Ras and ER to treat NF1-deficient ER+ breast tumors.

Figure 6. Co-targeting Ras and ER to treat NF1-deficient ER+ breast cancer.

Discussion

STAR★METHODS

LEAD CONTACT AND MATERIALS AVAILABILITY

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Cell lines

Animals

METHOD DETAILS

Chemicals

Plasmids

Generation of NF1 point mutation knock-in (KI) cells using CRISPR-Cas9

Assays for cell growth and apoptosis

Generation of NF1 antibodies

Immunoprecipitation (IP)

Immunoblotting

RNA-seq

ChIP

qPCR

ERE-luciferase reporter assay

The mammalian two-hybrid assay

ER and NF1-M2/GAP in vitro binding assay

Cell fractionation

Immunofluorescene deconvolution microscopy

ERE pull-down using HeLa cell nuclear extract

QUANTIFICATION AND STATISTICAL ANALYSIS

NF1 mutation frequency in patients

Patient proliferation status after aromatase inhibitor (AI) treatments

NF1 loss correlates with poor patient outcome in ER⁺ breast cancer.

Figure 1. NF1 loss promotes tamoxifen agonism and E2 hypersensitivity leading to poor patient outcome in ER⁺ breast cancer.

NF1-depletion promotes tamoxifen agonism and E2 hypersensitivity in ER⁺ breast cancer cells.

Co-targeting Ras and ER to treat NF1-deficient ER⁺ breast tumors.

Figure 6. Co-targeting Ras and ER to treat NF1-deficient ER⁺ breast cancer.