Co-targeting RANK pathway treats and prevents acquired resistance to CDK4/6 inhibitors in luminal breast cancer

Inês Gomes; Lina M Gallego-Paez; Maria Jiménez; Patricia G Santamaria; André Mansinho; Rita Sousa; Catarina Abreu; Eva González Suárez; Luis Costa; Sandra Casimiro

doi:10.1016/j.xcrm.2023.101120

. 2023 Jul 13;4(8):101120. doi: 10.1016/j.xcrm.2023.101120

Co-targeting RANK pathway treats and prevents acquired resistance to CDK4/6 inhibitors in luminal breast cancer

Inês Gomes ¹, Lina M Gallego-Paez ¹, Maria Jiménez ², Patricia G Santamaria ², André Mansinho ^3,⁵, Rita Sousa ³, Catarina Abreu ³, Eva González Suárez ^2,⁴, Luis Costa ^1,^3,^6,^∗, Sandra Casimiro ^1,^5,^6,^7,^∗∗

PMCID: PMC10439176 PMID: 37451269

Summary

The combination of endocrine therapy (ET) and cyclin-dependent kinase 4/6 (CDK4/6) inhibitors (CDK4/6i) was a hallmark in metastatic luminal breast cancer (BC). However, intrinsic and acquired resistance affects long-term efficacy. Here, we study the role of the receptor activator of nuclear factor-κB (RANK) pathway in CDK4/6i resistance. We find that RANK overexpression in luminal BC is associated with intrinsic resistance to CDK4/6i, both in vitro and in mouse xenografts, and decreased proliferation rate and chronic interferon (IFN) γ response are highlighted as resistance drivers. Gene expression data from the NeoPalAna CDK4/6i clinical trial, and studies with palbociclib-resistant cell lines, show that RANK is upregulated after treatment with CDK4/6i, supporting a role in acquired resistance. Our study shows that RANK ligand (RANKL) inhibitors can restore sensitivity to CDK4/6i and prevent acquired resistance. On the basis of these findings, we conclude that pharmacological inhibition of the RANK pathway through RANKL blocking could represent an add-on to ET + CDK4/6i, warranting further clinical studies.

Keywords: breast cancer, CDK4/6 inhibitors, RANKL, RANK, acquired resistance

Graphical abstract

Highlights

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RANK signaling contributes to resistance to CDK4/6 inhibitors in ER⁺ breast cancer
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RANK overexpression predicts resistance to CDK4/6 inhibitors in ER⁺ breast cancer
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RANK pathway activates an interferon (IFN) response program
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RANKL inhibitors treat and prevent/delay resistance to CDK4/6 inhibitors

CDK4/6i and endocrine therapy are the first-line treatment for advanced luminal breast cancer. Gomes et al. show that the RANK pathway is involved in resistance to CDK4/6i, via interferon response and alternative cell cycle mediators. Moreover, RANKL inhibitors concomitant with CDK4/6i can increase therapy efficacy and delay acquired resistance.

Introduction

Breast cancer (BC) is a heterogeneous disease with multiple histological and molecular presentations, in which about 70% of all cases belong to the luminal sub-type, characterized by the expression of estrogen receptor (ER) and/or progesterone receptor (PR). Although these patients have the better prognosis at early stages, the prognosis is dismal in advanced disease (4-year survival rate 35.9%), accounting for 10% of all deaths of cancer among women in the United States.¹

Currently, the first-line standard-of-care treatment for advanced ER⁺HER2⁻ BC is the combination of endocrine therapy (ET) with cyclin-dependent kinase 4/6 inhibitors (CDK4/6i), which remarkably improved outcomes in this setting.² Unfortunately, up to 20% of patients are unresponsive to therapy, and the majority develop clinical resistance within two years of starting treatment. So far, there are no validated biomarkers to predict response to CDK4/6i, although there are evidences of mechanisms of resistance, such as amplification or deletion of cell cycle proteins, stabilizing cyclin D1 mutations, increased transcription of cyclin genes via mTORC1 or androgen receptor (AR), or increased upstream signaling, such as PI3K-AKT pathway activation.³ Therefore, strategies to predict and overcome intrinsic resistance to CDK4/6i, or to extend benefit by delaying acquired resistance, are a clear unmet need.

The receptor activator of nuclear factor-κB (RANK) is a transmembrane receptor of the tumor necrosis factor receptor (TNFR) family, activated by RANK ligand (RANKL), a homotrimeric transmembrane or soluble protein.⁴ Activated RANK recruits TNFR-associated cytoplasmic factors (TRAFs), and subsequently activates the NF-κB, c-Jun N-terminal kinase (JNK), p38, extracellular signal-regulated kinase (ERK), and Src pathways, modulating cellular responses. In the clinical setting, pharmacological inhibition of RANKL with denosumab, a fully human anti-RANKL monoclonal antibody, is approved for prevention of skeletal-related events in patients with multiple myeloma and in patients with cancer-induced bone metastases, as well as for the treatment of osteoporosis.⁵

Over the past decade, RANK pathway has emerged as an important mediator of breast morphogenesis and carcinogenesis,⁶^,⁷^,⁸^,⁹^,¹⁰^,¹¹ mostly associated with triple-negative BC aggressiveness.¹²^,¹³^,¹⁴^,¹⁵^,¹⁶^,¹⁷^,¹⁸^,¹⁹ However, the relevance of RANK pathway in luminal BC has been recently acknowledged. We have found that RANK overexpression (OE) mediates an aggressive luminal BC phenotype, with decreased proliferation rate and susceptibility to chemotherapy and ET.²⁰ Moreover, it was demonstrated that ectopic RANK expression in non-transformed mammary epithelia induces senescence, leading to delayed onset of subsequent aggressive luminal-like tumors.²¹

Stemming from these findings, we decided to investigate whether RANK pathway could be involved in luminal BC resistance to CDK4/6i. Here, we report that RANK OE drives intrinsic resistance to CDK4/6i, associated with decreased proliferation rate and aberrant interferon (IFN) response in tumor cells. Moreover, we have found not only that elevated RANK metagene expression in the tumor prior to CDK4/6i therapy could predict resistance to treatment in patients enrolled in the NeoPalAna neoadjuvant clinical trial (NCT01723774) but also that it increases after treatment in therapy-responding patients, a feature we also observed in cells with acquired resistance to CDK4/6i. Focusing on the therapeutic potential of RANK pathway inhibition via RANKL targeting, we demonstrate that it not only sensitized RANK OE luminal BC cells to CDK4/6i in vitro and in vivo but also effectively restored sensitivity of cells that have acquired resistance as well as prevented its onset when used in combination with CDK4/6i. Therefore, we propose that RANK pathway status might represent a predictive biomarker for CDK4/6i therapy, and our results unveil the clinical relevance of the combination of CDK4/6i + ET with RANKL inhibition.

Results

RANK OE in luminal BC cells induces intrinsic resistance to CDK4/6i reversible by RANK pathway inhibition

Standard-of-care first-line therapy for patients with metastatic luminal BC is the combination of ET and CDK4/6i. Our previous studies demonstrate that RANK expression has effects in the phenotype of luminal BC, both in vitro and in vivo.²⁰ To investigate if RANK expression would influence the response to CDK4/6i we assessed the sensitivity of two luminal BC cell lines, MCF-7 and T47D, to the three currently approved CDK4/6i, palbociclib (Palbo), ribociclib (Ribo), and abemaciclib (Abema), in comparison with their RANK OE derivatives (MCF-7^OE and T47D^OE).²⁰ These RANK OE cell lines express high levels of RANK as confirmed by qRT-PCR (Figure S1A) and western blot (Figure S1B) and, without exception, were more resistant to CDK4/6i compared with their parental (PAR) counterparts (Figure 1A).

RANK overexpression in luminal BC cells induces intrinsic resistance to CDK4/6i reversible by RANK pathway inhibition

(A, B, and D) Viability of PAR and RANK OE cells (RANK OE confirmed in Figures S1A and S1B) cultured (A) for 7 days in the presence of indicated concentrations of CDK4/6i, (B) in the presence of CDK4/6i ± 100 ng/mL OPG-Fc for 7 days and in drug-free media for additional 7 days, or (D) for 7 days in the presence of indicated concentrations of CDK4/6i + Fulv ± 100 ng/mL OPG-Fc. Viability was measured by Alamar blue (A and D) or clonogenic (B) assay. Data are mean percentages from control ± SEM. Experiments were repeated independently three times (indicated by dots), with a minimum of three technical replicates per experiment. ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, and ∗∗∗∗p < 0.0001 (two-way ANOVA).

(C and E) Cell cycle analysis performed by propidium iodide (PI) incorporation in MCF-7 PAR and RANK OE cells cultured for 7 days with (C) 100 nM Palbo ± 100 ng/mL OPG-Fc or (E) 100 nM Palbo + 10 nM Fulv ± 100 ng/mL OPG-Fc. Data are mean percentages ± SEM. Experiments were repeated independently three times (indicated by dots), with a minimum of three technical replicates per experiment. ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001 (two-way ANOVA).

See also Figures S1 and S2.

As resistance to CDK4/6i has been linked mostly to alterations in Rb pathway members, we assessed CDK4-dependent proliferation and the expression of Rb pathway proteins, at baseline (BL) or after Palbo treatment. We observed that RANK OE cells retain features of CDK4/6-dependent proliferation, such as CDK4 phosphorylation at Thr172 (Figure S1C). Moreover, RANK OE cells showed higher expression of CDK7 and p21 at BL and after Palbo treatment, and sustained p-CDK4(Thr172) under CDK4/6i (Figure S1D). Although p21 is a cyclin-CDK inhibitor, it was recently shown that catalytic inhibition of CDK4/6 is p21 independent.²² On the other hand, CDK7 complexes with cyclin H and MAT1 can lead to the phosphorylation of several CDKs, including CDK4 and CDK6.²³ Interestingly, CDK7 was also increased in PAR cells after treatment with Palbo, reinforcing a possible role in resistance to CDK4/6i.

Cyclin-CDK complexes are often redundant and the inhibition of specific cyclins or CDKs can be compensated by an increase in the activity of others. Therefore, we assessed the effect of specific CDK loss in cell proliferation. RANK OE cells were resistant not only to specific CDK4 inhibition (3-ATA: CDK4i) (Figure S1E) but also to pan-CDK inhibition (seliciclib: CDK2,7,9i) (Figure S1F). CDK6 knockdown (KD) (Figure S1G) per se had a negligible impact on PAR and RANK OE cell proliferation (Figure S1H). Moreover, neither CDK4i nor CDK6 KD alone could sensitize RANK OE cells to Palbo (Figure S1I), and seliciclib had a modest effect (Figure S1J). Therefore, and although RANK OE cells have some alterations in cell cycle-related proteins that can contribute to resistance to CDK4/6i, we hypothesized that other mechanism(s) would also be involved in RANK-mediated resistance to CDK4/6i.

To demonstrate a causal role of RANK signaling in resistance to CDK4/6i, we inhibited the RANK pathway with OPG-Fc, a RANKL inhibitor that impairs RANK pathway activation. In the cell lines used in this study, endogenous RANKL expression is low, as expected from Cancer Cell Line Encyclopedia (CCLE) dataset analysis (not shown) and the literature and confirmed by qRT-PCR (Figure S2A). Therefore, although some autocrine RANKL may exist, the major source of RANKL in vitro will be the fetal bovine serum (FBS) added to the culture medium. To estimate the concentration of RANKL present in the in vitro studies, we measured RANKL concentration in three independent batches of FBS used in the present study, with [RANKL] = 3.5 ± 0.6 pg/mL. To show the inhibitory effect of OPG-Fc over RANK signaling, cells were first depleted from exogenous RANKL (and other growth factors present in FBS) by serum starvation for 24 h (medium with 0.1% FBS) and then treated with exogenous RANKL, neutralized or not with OPG-Fc. The analysis of phosphorylated RANK downstream mediators showed that OPG-Fc prevents RANKL-induced pathway activation (Figure S2B).

Regarding RANK OE cells’ resistance to CDK4/6i, it was abrogated by OPG-Fc (Figure 1B), which increased G0/G1 cell-cycle arrest in comparison with untreated cells or cells treated only with Palbo (Figure 1C). Although OPG-Fc did not affect the cell cycle when used alone for the same time (7 days) (Figure S2C), it effectively sensitized RANK OE cells to specific CDK4i (Figure S2D) and to Palbo in association with CDK6 KD (Figure S2E). Therefore, our data support a mechanism of RANK-mediated intrinsic resistance to CDK4/6i, which can be bypassed by RANK pathway inhibition. Interestingly, OPG-Fc also improved to some extent the sensitivity to CDK4/6i of the MCF-7 and T47D cell lines with physiological levels of RANK (Figure 1B).

In the clinic, CDK4/6i are used in combination with ET, namely, letrozole or fulvestrant (Fulv), to which we have previously shown that RANK OE cells are resistant.²⁰ Importantly, RANK pathway inhibition with OPG-Fc abrogated RANK OE cells’ resistance to CDK4/6i + ET (Figures 1D and S2F), increasing G0/G1 cell-cycle arrest in comparison with untreated cells or cells treated with Palbo + Fulv (Figure 1E). RANK-Fc, another RANKL inhibitor, had the same effect in restoring the sensitivity of MCF-7^OE cells to Palbo + Fulv (Figure S2G).

RANK pathway inhibition overcomes RANK OE-induced intrinsic resistance to Palbo + Fulv in vivo

As a next step, we aimed to assess the therapeutic potential of CDK4/6i + ET + OPG-Fc in vivo. To address this question we used an ectopic xenograft mouse model (Figure 2A). In accordance with the in vitro results, RANK OE tumors were resistant to Palbo + Fulv (standard therapy [STD]), whereas Palbo + Fulv + OPG-Fc (combination therapy [COMB]) could induce tumor regression (Figure 2B). We quantified Ki67 and p-Rb proliferation markers (Figures 2C and 2D, respectively) and apoptosis (Figure S3A) on tumors collected at sacrifice, observing an association between decreased proliferation and treatment efficacy, without significant differences in apoptosis. Decreased serum TRAcP 5b was used to infer OPG-Fc inhibition of RANK pathway (Figure S3B).

The major source of circulating RANKL in vivo remains unclear; however, as immune cells contribute to the pool of systemic RANKL, and we used an immunodeficient model, we quantified RANKL in the serum of tumor-naive animals from three distinct mouse strains: NSG, Balb/c, and CD-1 (Figure S3C). We observed that RANKL concentration varies across the different strains; however, it was not significantly lower in NSG animals in comparison with immune competent ones (Balb/c or CD-1). Additionally, the measured RANKL levels were in accordance with a previous study using NODSCID mice.²⁴

In agreement with what we previously reported,²⁰ RANK OE tumors had a lower growth rate than PAR counterparts (Figure 2E), which resulted into lower proliferation markers measured in the RANK OE vehicle (VEH) group at day 22, compared with PAR VEH (Figures 2C and 2D) (p-Rb, p < 0.05). It is important to note that decreased proliferation on its own can contribute to CDK4/6i resistance, which may confound data interpretation in our model. To further characterize RANK OE xenografts, we performed hallmark gene set enrichment analysis (GSEA-H; normalized enrichment score [NES] > 1 or <−1; nominal [NOM] p < 0.05; false discovery rate [FDR] q < 0.25) of untreated tumors (VEH) (Figure 2F; Table S1), which confirmed that proliferation-related hallmarks such as E2F targets and G2M checkpoint were negatively enriched in RANK OE compared with PAR tumors. However, the 82 genes found to be differentially expressed between RANK OE and PAR VEH tumors (differentially expressed genes [DEGs]; log₂ > 1 or <−1; FDR q < 0.1) (Figure S3D; Table S2) did not include Rb pathway genes, in accordance with the in vitro data. Moreover, RANK OE tumors were enriched in hallmarks such as epithelial-to-mesenchymal transition (EMT), angiogenesis, KRAS signaling, TNF-α signaling via NF-κB, inflammatory response, IL2/STAT5 signaling, IFNγ response, apical junction, and early response to estradiol, reflecting the previously characterized RANK OE phenotype.²⁰ Among these hallmarks, an enrichment in IFNγ response was previously reported in cell lines and breast tumors resistant to CDK4/6i.²⁵ Overall, this suggests that RANK OE tumors harbor several characteristics that may affect the response to CDK4/6i.

RANK OE and CDK4/6i are associated with an increase in IFN response hallmark

Next, we questioned which were the most significant hallmarks of residual tumors treated for 21 days with Palbo + Fulv, as they could be associated with response to treatment and/or selection of resistant clones. By analyzing the transcriptomic profiles of xenografts collected at day 22 (Figure 3A), treatment effect was demonstrated by a decrease in E2F targets and other cell cycle and proliferation-related hallmarks compared with the untreated conditions (VEH) (Figure 3B; Table S1). On the other hand, IFNα/γ responses were the two most enriched hallmarks in PAR STD tumors and the only signature differentially expressed between the sensitive and resistant tumors (PAR STD vs. RANK OE STD).

RANK overexpression and CDK4/6i are associated with an increase in IFN response hallmarks

(A) Diagram representing the characteristics (sensitivity or resistance to Palbo + Fulv or Palbo + Fulv + OPG-Fc) of the analyzed tumors. Samples were collected after 21 days of treatment. See also Figure 2A.

(B) Gene set enrichment analyses were performed using indicated MSigDB Hallmark gene sets. IFN response hallmarks are highlighted (blue dashed outline rectangle). See also Table S1.

(C) Venn diagram depicting the overlap between the lead genes retrieved from the IFNα/γ hallmarks (GSEA curves in Figure S4A) of PAR tumors treated with Palbo + Fulv (STD [standard therapy]) or RANK OE treated with Palbo + Fulv + OPG-Fc (COMB [combination therapy]) and the IRPS genes.²⁵

(D) Hallmark enrichment analysis was performed with the top 2,000 differentially expressed genes (DEGs) between RANK-high (*RANK* > median) and RANK-low (*RANK* < median) ER⁺HER2⁻ breast tumors from the TCGA database. See also Table S3.

See also Figure S4.

As mentioned above, IFN response was previously associated with response to ET + CDK4/6i, as an enrichment in “IFN-related Palbo resistance signature” (IRPS) at BL was shown to predict patients’ intrinsic resistance to CDK4/6i in two neoadjuvant clinical trials (NeoPalAna and NeoMONARCH).²⁵ The NeoMONARCH analysis also shown that IFN response increased in patients sensitive to CDK4/6i with 16 weeks of treatment, which we hypothesized could reflect the selection of CDK4/6i-resistant clones. Importantly, we observed that, although COMB did not completely abrogate IFN response enrichment, it decreased it in comparison with STD (Figures 3B and S4A).

To assess the commonality between IFN response in mouse tumors from our model and the previously reported IRPS,²⁵ we selected the IFNα/γ response lead genes from the GSEA-H analysis of RANK OE COMB and PAR STD responsive tumors (Figure S4A). The overlap between PAR STD IFN response lead genes and IRPS genes was remarkable (32 of 35 genes); however, only 7 of 35 genes overlapped between RANK OE COMB and IRPS, namely, B2M, CCL5, CSF1, IRF1, JAK2, LGALS3BP, and MX1 (Figure 3C). Moreover, the expression of the 32 IRPS genes overlapping with PAR STD-treated tumors was significantly decreased in the COMB groups (Figure S4B).

Regarding the RANK OE tumors, which were intrinsically resistant to STD (Figure 2B) and showed high IFNγ response at BL (Figure 2F), we observed that IFN response decreased following STD treatment (Figure 3B; Table S1), similar to what was seen in resistant patients who underwent treatment with ET + CDK4/6i.²⁵ On the contrary, other hallmarks that were previously associated with resistance to CDK4/6i, namely, PI3K/AKT/mTOR signaling and androgen response,²⁶^,²⁷^,²⁸ were enriched in RANK OE STD tumors.

Interestingly, in the case of tumors derived from PAR cells, although there was no significant difference in tumor volume between the PAR STD and PAR COMB groups at the end of the treatment (Figure 2B), there was a slight delay in the regression of tumors in the COMB group. Moreover, PAR COMB-treated tumors were characterized by higher Ki67 and p-Rb immunoscores in comparison with PAR STD ones (Figures 2C and 2D). Therefore, we specifically compared the transcriptomic profile of these two groups. GSEA-H (Figure S4C) and DEG analyses (Figures S4D and S4E) confirmed an enrichment in genes related with cell cycle in PAR COMB-treated tumors, whereas IFN response was found to be downregulated. This suggests that although there was a trend toward a delayed response to therapy in PAR COMB tumors, the mechanism underlying this effect remains unclear, and may be related to the RANK-mediated IFN response. It will be important to elucidate in the future how this mechanism contributes to the long-term response to CDK4/6i in luminal tumors with physiological levels of RANK.

Overall, these findings suggest that during treatment with ET + CDK4/6i, intrinsically resistant RANK OE tumors accumulate other characteristics contributing to resistance. Moreover, the upregulation of IFN response after treatment may have a role in acquired resistance to CDK4/6i or reflect its onset, and, of note, RANK pathway inhibition may decrease this effect. Therefore, we decided to further investigate a possible association between RANK signaling and IFN response.

The RANK pathway is associated with increased IFN signaling

To obtain evidence that RANK and IFN response are associated in a human cohort of luminal BC, we conducted GSEA-H analysis of the top 2,000 RANK-correlated genes in ER⁺HER2⁻ RANK-high breast tumors from The Cancer Genome Atlas (TCGA) database (RANK > median expression) (Figure 3D; Table S3). This analysis disclosed an enrichment (p < 0.05, FDR q < 0.05) in immune and inflammatory response hallmarks, including IFNγ response, further supporting our hypothesis. Of note, 22 of 35 genes from the IRPS signature were found to be upregulated (log fold change [FC] > 0, p < 0.05, adjusted p < 0.05) in RANK-high ER⁺HER2⁻ tumors from the TCGA BC cohort (Table S4).

Next, we quantified in vitro the expression of a panel of IFN-stimulated genes (ISGs; APOL6, IFI44, IFI44L, IFIT3, IRF9, ISG15, LGALS3BP, and OASL), selected from the IFN response lead genes overlapping with IRPS (Figure 3C), plus JAK-STAT members known to be upstream of ISGs (IFNG, STAT1, STAT2, STAT3, JAK1, and JAK2). All genes, except JAK1 and JAK2, were upregulated in RANK OE cells (intrinsic resistance) and in PAR cells after treatment with Palbo + Fulv (sensitive/residual disease) (Figure 4A). Importantly, we found RANK to be significantly upregulated in PAR cells treated with CDK4/6i, suggesting an upregulation of RANK in residual cells surviving therapy, or a selection of cells with higher expression of RANK. In both cases, these cells show an IFN signature, supporting its association with RANK OE.

The RANK pathway is associated with increased IFN signaling

(A) qRT-PCR analysis of ISGs and JAK-STAT members (normalized to *18S*) plus *RANK* expression (normalized to *GAPDH*) in MCF-7^OE cells relative to MCF-7 (red) and MCF-7 cells treated with Palbo + Fulv (STD) relative to untreated cells (blue). Data are log₁₀ of mean fold change ± SEM. Experiment was repeated independently with n = 3–9 biological replicates (indicated by dots), with three technical replicates per PCR. ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001 (two-sided unpaired t test).

(B) Western blot analysis of RANK and IFNγ pathway downstream mediators. MCF-7 or MCF-7^OE cells were serum starved for 24 h for depletion of exogenous growth factors including RANKL, and stimulated for 15 min treatment with 1 μg/mL RANKL and/or 5 ng/mL IFNγ, with β-actin as loading control.

(C) Viability of PAR and RANK OE cells cultured for 7 days in the presence of 100 nM CDK4/6i ± 100 ng/mL OPG-Fc or 100 nM STAT1i (fludarabine, STAT1i; see also Figure S5A), measured by Alamar blue assay. Data are mean percentages from control ± SEM. Experiments were repeated independently three times (indicated by dots), with a minimum of three technical replicates per experiment. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, and ∗∗∗∗p < 0.0001 (one-way ANOVA).

So far, our data suggest that RANK OE cells feature chronic IFN response. It was previously shown that RANK pathway could directly phosphorylate STAT1 at Ser727.²⁹ IFNγ-JAK1/2-induced phosphorylation of STAT1 at Tyr701 is essential for transcription regulation; however, the phosphorylation of STAT1 at S727 was reported to increase canonical and non-canonical transcriptional activity of STATs.³⁰ Therefore, we measured p-STAT1(Ser727) and p-STAT1(Tyr701) in serum-starved cells, stimulated with exogenous IFNγ or RANKL (Figure 4B). In accordance with the described evidence, whereas p-STAT1(Tyr701) was exclusively activated by IFNγ, p-STAT1(Ser727) was detected at BL and increased in RANK OE cells, being further upregulated by RANKL or IFNγ, supporting the intrinsic activation of IFN response in RANK OE cells. Even in cells with physiological levels of RANK, RANKL was able to induce p-STAT1(Ser727). As our results implicated chronic IFNγ-JAK-STAT pathway activation in intrinsic resistance to CDK4/6i, we used a STAT1 inhibitor (fludarabine; STAT1i), which causes a specific depletion of STAT1 protein and mRNA, in combination with Palbo, and compared the effect with OPG-Fc treatment. We observed that STAT1i restored RANK OE sensitivity to CDK4/6i was more effective than OPG-Fc, and increased the efficacy of CDK4/6i in cells with physiological levels of RANK (Figure 4C). The combination of CDK4/6i with both OPG-Fc and STAT1i was not better than CDK4/6i plus OPG-Fc or STAT1i, suggesting that both compounds target the same resistance-associated pathway. Moreover, the analysis of the inhibitory effect of STAT1i and OPG-Fc over p-STAT1(Ser727) confirmed p-STAT1(Ser727) down-regulation in both cases, with a superior effect of STAT1i (Figure S5A). This likely contributes to STAT1i being more effective than OPG-Fc in restoring RANK OE sensitivity to CDK4/6i.

Overall, our data show that RANK pathway is associated with IFN response. CDK4/6i therapy leads to an upregulation of RANK or selection of clones with higher expression of RANK, which may contribute to IFN response activation during treatment. Since RANK OE cells and tumors are intrinsically resistant to ET + CDK4/6i, we hypothesized that RANK upregulation could be associated with the onset of acquired resistance and that this resistance could be prevented or delayed by RANK pathway inhibition.

RANK is upregulated in luminal BC patients treated with CDK4/6i

To obtain clinical evidence of an association between RANK upregulation and IFN response in CDK4/6i-treated patients, we analyzed the publicly available dataset of human tumors treated with CDK4/6i in the neoadjuvant setting, from the NeoPalAna trial (NCT01723774; GEO: GSE93204).³¹ Tumor tissue samples were collected at BL, C1D1 (first day of first cycle of Palbo plus anastrozole, after 28 days on single anastrozole), C1D15, and surgery (after four 28 day cycles, only responders). Non-responders were defined as Ki67 > 10% at C1D15.

As RANK OE was associated with intrinsic resistance to ET + CDK4/6i, we analyzed the predictive value of RANK metagene expression at the beginning of CDK4/6i treatment. This RANK metagene, comprising the top RANK-correlated genes, was significantly increased at BL and C1D15 in patients classified as non-responders (Figure 5A). Moreover, in accordance to the in vitro observations in the cell lines, RANK metagene was upregulated in samples collected after treatment with CDK4/6i from patients classified as responsive to therapy (Figure 5B). This suggests that RANK upregulation can be involved in the development of acquired resistance. Additionally, and supporting the previous observations suggesting an association between RANK and IFN response, GSEA of the RANK-correlated genes disclosed an enrichment in IFN response hallmarks (Figure 5C).

*RANK* is upregulated in luminal BC patients treated with CDK4/6i

(A) Log-transformed normalized expression of *RANK* metagene at baseline (BL) and C1D15 (day 15 of first cycle) in patients classified as responders (n = 27) or non-responders (n = 5) to CDK4/6i treatment in the NeoPalAna clinical trial (NCT01723774). The *RANK* metagene comprises the top 100 genes correlated with *RANK* at baseline (BL). p value is obtained using two-sided Wilcoxon rank-sum test.

(B) Difference between score of *RANK*-correlated genes. Each score value is defined as the Spearman’s correlation coefficient obtained between *RANK* expression and the corresponding gene at day 15 of first cycle (C1D15) and surgery (Surg) in samples from the NeoPalAna clinical trial. Correlations are filtered by those having coefficients >0.4 and then ranked in descending order. The p value is obtained using Wilcoxon signed-rank test.

(C) Gene set enrichment analysis for Reactome pathways was performed with all analyzed genes ranked by their correlation with *RANK* (Spearman’s rank test) in the baseline samples. Significantly enriched gene sets include several ones associated with interferon signaling (dot size represents the number of genes in each Reactome pathway, color gradient indicates significance level of adjusted p values).

RANK pathway inhibition treats and prevents acquired resistance to CDK4/6i

To investigate further the upregulation of RANK in cells with acquired resistance to CDK4/6i, we generated two Palbo-resistant cell lines, MCF-7_PalbR and T47D_PalbR, by prolonged exposure of PAR cell lines to increasing concentrations of Palbo (Figure 6A). In this experiment, MCF-7 and T47D cell lines were cultured under standard conditions alongside Palbo-treated cells for the same period. We found that RANK (Figure 6B) and most of the previously analyzed ISGs (except ISG15) (Figure 6C), were upregulated in PalbR cells, further supporting that the axis RANK-IFN response seems to have an impact on acquired resistance to CDK4/6i. Remarkably, OPG-Fc and RANK-Fc were able to re-sensitize PalbR cells to Palbo + Fulv (Figure 6D). The same effect was observed with STAT1i, which, as observed in RANK OE cells, was able to increase PalbR cells’ sensitivity to Palbo (Figure 6E).

Additionally, and because there are multiple mechanisms associated with resistance to CDK4/6i, we analyzed the expression of major cell cycle-related proteins in PalbR cells (Figure 6F). The results show that PalbR cells exhibit higher p-Rb levels at BL compared with MCF-7, which was sustained after treatment with Palbo despite a decrease in p-CDK4(Thr172). PalbR cells show higher expression of CDK6, cyclin E, CDK2, and CDK7, which contribute to bypass CDK4 inhibition, as well as decreased expression of p21.

Finally, we questioned if RANK pathway inhibition during CDK4/6i treatment could prevent the onset of acquired resistance. To address this question, we exposed MCF-7 cells to increasing concentrations of Palbo for three months, in the constant presence of OPG-Fc or RANK-Fc (MCF-7_Prev cell lines). Once more, MCF-7 cell line was cultured under standard conditions or with Palbo alone alongside MCF-7_Prev cell lines. Remarkably, concomitant RANK pathway inhibition and CDK4/6i prevented the onset of acquired resistance to CDK4/6i (Figure 6G), as well as RANK (Figure 6H) and ISGs upregulation (Figure 6I) in comparison with PalbR cells.

Overall, the present study implicates RANK, and its association with IFN response, in intrinsic and acquired resistance to CDK4/6i and suggests that inhibition of RANK pathway may represent an important add-on to ET + CDK4/6i therapy (Figure 6J).

Discussion

CDK4/6 activity bridges numerous extracellular signaling pathways to the cell cycle, including the ER pathway.³ CDK4/6i, by blocking cell cycle progression, have proved highly efficient in combination with ET, substantially improving survival of luminal BC patients.² However, about 15% of patients are intrinsically resistant to this therapy, and acquired resistance is nearly inevitable in most patients after a period of controlled disease.

RANK pathway has been related with resistance to therapy in BC. For example, increased RANK signaling was associated with the development of lapatinib resistance through NF-κB activation in HER2⁺ BC,³² whereas we found that RANK OE Luminal BC cells were resistant to ET (Fulv) and chemotherapy (paclitaxel and doxorubicin).²⁰ In the present study, we describe a link between RANK pathway and intrinsic/acquired resistance to CDK4/6i, with or without ET in the form of Fulv (Figure 6J). Remarkably, we showed that RANK pathway inhibition via RANKL blocking, restores the sensitivity of RANK OE cells (Figures 1B, 1D, and 2B) and PalbR cell lines (with acquired resistance) (Figure 6D) to CDK4/6i and prevents the onset of acquired resistance (Figure 6G). These findings suggest a window of opportunity for the combination of RANKL inhibitors with ET + CDK4/6i.

Luminal BC cell lines used in this study were more sensitive to Palbo than to Ribo or Abema, and the effect of RANK pathway inhibition was more pronounced in Palbo-treated cells and identical in MCF-7 and T47D cell lines and RANK OE derivatives (Figure 1B). Although T47D harbors a mutation in TP53, several highly CDK4/6i sensitive cell lines also have TP53 or PIK3CA mutations.³³

Our previous observations regarding the phenotype of RANK OE luminal BC cell lines,²⁰ and the data presented here, reveal that decreased proliferation is a characteristic of RANK OE luminal BC cells and RANK-high human luminal tumors. By itself, this may imply decreased sensitivity to cell cycle-targeting drugs, such as CDK4/6i, and affect data interpretation. In virtually all human cancer cells, Rb signaling is dysregulated, and alterations in cell cycle-related proteins, such as Rb, cyclin D1, cyclin E, and CDKs, affect sensitivity to CDK4/6i.²⁷ However, despite intrinsic lower proliferation of RANK OE cells (Figure 2E), we did not observe major differences in Rb pathway members between RANK-low or RANK-high cells, neither in vitro (Figure S1D) nor in vivo (Table S2). The exception was an increase in CDK7 and p21 observed in cultured RANK OE cell lines. CDK7 OE has been previously reported in PalbR ER⁺ BC cells.³⁴

The mechanism by which RANK OE decreases proliferation in luminal BC cell is not fully understood. Current evidence suggests that RANK OE in ER⁺HER2⁻ BC cells leads to the expression of stemness and mesenchymal-related genes, and decreased proliferation rate both in vitro and in vivo²⁰ and senescence.²¹ Moreover, data from an oncogene-driven murine BC models has shown that Rank OE in non-transformed mammary epithelium leads to oncogene-induced senescence, with phenotypic characteristics like reduced proliferation, increased senescence-associated β-galactosidase (SA-β-gal) activity, dependency on p16/p19 tumor suppressors, DNA damage, SASP induction, and sensitivity to senolytics.²¹ Importantly, it was shown that although Rank-driven senescence initially delayed tumor onset, it could promote stemness, tumor growth, and metastasis at later stages. In both studies, findings were supported by the analysis of transcriptomic data from the TCGA ER⁺ BC cohort, in which elevated RANK expression was associated with decreased predicted proliferative index,²⁰ stemness,²⁰^,²¹ and senescence²¹ in luminal BC.

Current RANKL inhibitors include denosumab, RANK-Fc, and OPG-Fc. Denosumab is a fully human antibody that cannot be used in the mouse models in our study, while RANK-Fc and OPG-Fc bind to human and mouse RANK. In the present study, most of the experiments were performed with OPG-Fc, for availability reasons. We acknowledge that although OPG-Fc has relatively low affinity for TRAIL, and this may be offset by OPG-Fc abundance; currently, the biological significance of TRAIL binding by OPG-Fc remains unclear. However, we conducted parallel in vitro experiments with RANK-Fc, which does not bind to TRAIL, with identical results in terms of restoring sensitivity to CDK4/6i (Figures S2G and 6D) and preventing the onset of acquired resistance (Figure 6G).

An enrichment of IFN response in MCF-7 cells with acquired resistance to Palbo was first observed when studying the efficacy of oncolytic virotherapy³⁵ and later in Palbo-resistant cells.³⁶ Moreover, CDK4/6i were described to increase tumor immunogenicity by enhancing IFN-driven gene expression programs in tumor cells³⁷^,³⁸ and found to induce remodeling of cancer cell chromatin, characterized by activator protein-1 (AP-1)-mediated enhancer activation, facilitating the regulation of ISGs.³⁹ Recently, in another study, the IRPS was derived from MCF-7 and T47D cells with acquired resistance to Palbo, being able to discriminate, at BL, therapy-resistant patients in the NeoPalAna and NeoMONARCH trials.²⁵ In this study, sensitive patients in the NeoMONARCH trial had an increase in IFN response after treatment, identical to our findings in cell lines (Figure 4A) and mouse tumors (Figure 3B). It was suggested a dual role for IFN-mediated response in resistance and response, remaining to be clarified the molecular basis for hyperactive IFN signaling in treatment-naive BC. According to our findings, we suggest that an increase in IFN response after treatment actually reflects the selection of CDK4/6i-resistant RANK-high clones, instead of having a role in response.

Here, we show that IFNγ response is a top hallmark of human ER⁺HER2⁻ breast tumors with elevated RANK expression (Figure 3D), which also overexpress most of the IRPS genes (Table S4). To our knowledge, there is no reported evidence of a direct link between RANK signaling and regulation of IFN-driven gene expression; however, AP-1, regulator of ISGs expression, is a major transcription factor downstream of RANK.⁴⁰ We observed an upregulation of both JUN and JUNB in RANK OE xenografts (data not shown). Moreover, NF-κB was also described to regulate the expression of IFNs and ISGs,⁴¹ with multiple ISGs having NF-κB binding sites within their promoters. Although BC cells may produce IFNγ, autocrine IFNγ was reported to be below 1 ng/mL in MCF-7.⁴² Here, we observed an upregulation of IFNG in RANK OE cells and CDK4/6i-treated cells, which may contribute to the activation of IFN response. Moreover, in accordance with a previous report that RANK activation by RANKL phosphorylates the serine but not the tyrosine residues of STAT-1 in a p38-dependent manner in osteoclast precursors,²⁹ we observed p-STAT1(Ser727) upregulation in cells stimulated with RANKL (Figure 4B). Although compelling evidence that activated STAT1 has a tumor suppressor role in cancer cells, aberrant STAT1 activation has been detected in several types of human cancer, including BC, with different studies reporting both positive and negative association with prognosis.⁴³

In our study, RANK upregulation accompanied the enrichment in IFNγ response after in vitro treatment with CDK4/6i (Figure 4A). As IFNγ response was a BL hallmark of RANK OE-resistant tumors, this suggested a link between RANK and IFN-mediated response in cells treated with CDK4/6i and the onset of acquired resistance. Remarkably, RANK metagene upregulation after CDK4/6i was observed in patient samples from the NeoPalAna (NCT01723774) neoadjuvant phase II trial (Figure 5B).

We acknowledge that our study has some limitations and leaves questions to be addressed in the future. Fortunately, only 15%–20% of patients are intrinsically resistant to CDK4/6i, and sample-driven datasets from large clinical trials are an unmet need. Therefore, our clinical inferences are based on the analysis of a relatively small number of samples from therapy-resistant patients from a neoadjuvant trial. Moreover, we could not assess the link between RANK upregulation and acquired resistance in clinical samples.

Overall, our data suggest that impairing or preventing RANK-induced chronic IFN response may sensitize BC to CDK4/6i, and prevent the onset of acquired resistance. This can be achieved with RANKL or JAK-STAT inhibition. However, PD-1 and PD-L1 expression seem to be regulated mainly by IFNγ-associated JAK/STAT signaling, involving STAT1 and STAT3, which deserves to be taken into account in future studies considering JAK-STAT inhibition plus CDK4/6i. Moreover, despite the cytotoxic effects of IFNγ on tumor cells, pro-tumor effects of IFNγ have emerged. In this sense, RANKL inhibition could represent an interesting option, as the RANK pathway plays a key role in the tumor-immune crosstalk, and the use of RANKL inhibitors, such as denosumab, enhances the immune response in poorly immunogenic luminal BC.⁴⁴ Therefore, it will be extremely important to reconcile data from in vitro experiments and NSG mouse models, which lack immune response, with data from immunocompetent patient samples. A recent analysis of the PALOMA-2 and PALOMA-3 trials showed that resistance genes unique to samples from patients treated with first-line CDK4/6i (PALOMA-2) are enriched in IFNγ response genes.⁴⁵ Moreover, a low ratio of ISGs in immune cells to ISGs in tumor cells was associated with resistance to therapy, as IFN signaling in the tumor cells opposed the effects of IFN signaling in adaptive and innate immune cells to limit immune response.⁴⁶ This low ratio is caused by chronic IFNγ signaling and upregulation of ISGs in the cancer cells. For that reason, the consequences of RANK-induced IFN response in immune response must be addressed in the future.

Limitations of the study

We are aware that the fact that RANK OE decreases proliferation may confound data interpretation. In our models, we focused on the RANKL-RANK-ISG axis, and we did not investigate the epigenetic modifications and concomitant gene expression changes that may occur upon RANK OE or upon RANK pathway inhibition and its relationship to cell-cycle arrest but also its propensity for senescence and MHC class I processing. Consequently, in our models, we did not address if and how the impact of RANK OE on the cell cycle and eventually in MHC class I antigen expression and cell senescence were related with resistance to CDK4/6i. Additionally, in our study, Palbo-resistant cells were generated by adaptive exposure to increasing concentrations of Palbo, not clonal selection, which did not allow the study of these cell lines in the absence of therapy.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies

Rabbit monoclonal anti phospho-Rb (Ser807/811) (D20B12)	Cell Signaling	Cat#8516; RRID:AB_11178658
Rabbit monoclonal anti phospho-NF-kB p65 (Ser536) (93H1)	Cell Signaling	Cat#3033; RRID:AB_331284
Rabbit monoclonal anti NF-kB p65 (D14E12)	Cell Signaling	Cat#8242; RRID:AB_10859369
Rabbit monoclonal anti p44/42 MAPK (Erk1/2) (137F5)	Cell Signaling	Cat#4695; RRID:AB_390779
Rabbit monoclonal anti CDK4 (D9G3E)	Cell Signaling	Cat#12790; RRID:AB_2631166
Rabbit monoclonal anti Cyclin D1 (92G2)	Cell Signaling	Cat#2978; RRID:AB_2259616
Rabbit monoclonal anti CDK2 (78B2)	Cell Signaling	Cat#2546; RRID:AB_2276129
Rabbit monoclonal anti p27 Kip1 (D69C12)	Cell Signaling	Cat#3686; RRID:AB_2077850
Rabbit monoclonal anti p21 Waf1/Cip1 (12D1)	Cell Signaling	Cat#2947; RRID:AB_823586
Rabbit monoclonal anti phospho-STAT1 (Tyr701) (D4A7)	Cell Signaling	Cat#7649; RRID:AB_10950970
Rabbit monoclonal anti phospho-STAT1 (Ser727) (D3B7)	Cell Signaling	Cat#8826; RRID:AB_2773718
Rabbit monoclonal anti STAT1 (D1K97)	Cell Signaling	Cat#14994; RRID:AB_2737027
Rabbit polyclonal anti phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204)	Cell Signaling	Cat#9101; RRID:AB_331646
Rabbit polyclonal anti phospho-CDK4 (Thr172)	St John’s Laboratory	Cat#STJ29359; RRID:AB_2928079
Rabbit polyclonal anti RANK	Cell Signaling	Cat#4845; RRID:AB_2205336
Rabbit polyclonal anti CDK7	Cell Signaling	Cat#2090; RRID:AB_2077140
Mouse monoclonal anti CDK6 (DCS83)	Cell Signaling	Cat#3136; RRID:AB_2229289
Mouse monoclonal anti Cyclin E (HE12)	Sigma-Aldrich	Cat#05–363; RRID:AB_2071085
Mouse monoclonal anti β-Actin	Abcam	Cat#ab6276; RRID:AB_2223210
Horseradish peroxidase-conjugated (HRP) specific secondary antibody anti-mouse-HRP IgG	Cell Signaling	Cat#7076; RRID:AB_330924
Horseradish peroxidase-conjugated (HRP) specific secondary antibody anti-rabbit-HRP IgG	Cell Signaling	Cat#7074; RRID:AB_2099233
Rabbit monoclonal anti human Ki67 (MIB-1)	Dako	Cat#IR626; RRID:AB_2890068

Chemicals, peptides, and recombinant proteins

DMEM	Gibco^TM	41966–029
Fetal Bovine Serum	Gibco^TM	10270106
Pen/Strep	Gibco^TM	15140122
Insulin	Gibco^TM	12585014
TrypLE™ Express Enzyme (1X), phenol red	Gibco^TM	12605028
Dimethyl sulfoxide (DMSO)	Merck Life Science	D4540
Palbociclib	Sigma-Aldrich	PZ0199
Ribociclib	Santa Cruz Biotechnology	LEE011
Abemaciclib	Selleck Chemicals	Ly2835219
Fulvestrant	Selleckchem	S1191
Seliciclib	Focus Biomolecules	10–1332
3-ATA	Santa Cruz Biotechnology	SC-202414
OPG-Fc	Amgen Inc.	461130
RANK-Fc	R&D Systems	683-RK-100
17β-estradiol pellets	Innovative Research of America	SE-121
Phenol-free matrigel solution	Corning®	356237
Na Lactate	Sigma-Aldrich	L7900
Corn oil	Sigma-Aldrich	C8267
DMSO	Sigma-Aldrich	D8418-50ML
Sodium Pentobarbital	CEVA SANTE ANIMALE	N/A
Control shRNA	Santa Cruz Biotechnology	sc-108060
CDK6 specific shRNA	Santa Cruz Biotechnology	sc-29264-SH
Lipofectamin-3000	invitrogen	L-3000-015
Puromycin dihydrochloride	Santa Cruz Biotechnology	sc-108071
Fludarabine	Santa Cruz Biotechnology	SC-204755
Paclitaxel	Sigma-Aldrich	Y0000698
Doxorubicin hydrochloride	Sigma-Aldrich	D2975000
Paraformaldehyde	Merck Life Science	818715
Crystal violet	Sigma-Aldrich	HT90132-1L
SDS	Merck Life Science	11667289001
Ethanol	VWR^TM	20821.330
Human RANKL	Amgen Inc.	11000457
Human IFNγ	Peprotech®	300–02
RIPA buffer	Sigma-Aldrich	R0278
Protease inhibitors cocktail	Cell Signaling	5871
Phosphatase inhibitors cocktail	Sigma-Aldrich	P5726
Albumin Bovine Fraction V (BSA) MB Grade	Nzytech	MB04602
Molico Skimmed dry milk powder	Nestlé	N/A
Antigen Retrieval Solution pH9.0	Dako	S2368
Peroxidase Blocking Solution	Dako	411126
Protein Block Solution	Dako	411161
Antibody Diluent	Dako	411115
DAB	Dako	411066
RNA later	Thermo Fisher Scientific	AM7021
Acrylamide/bis-Acrylamide	Nzytech	MB04501
TEMED	Nzytech	MB03501
Ammonium persulfate (APS)	Sigma-Aldrich	A3678-100G

Critical commercial assays

Alamar blue assay	Invitrogen	DAL1100
Propidium iodide (PI) flow cytometry kit	Abcam	ab139418
NZY Total RNA Isolation kit	Nzytech	MB13402
NZY M-MuLV First-Strand cDNA Synthesis kit	Nzytech	MB17301
Pierce BCA Protein Assay Kit	Thermo Scientific	23225
Novex® ECL HRP chemiluminescent substrate reagent kit	Invitrogen	WP20005
EnVisionTM Detection System, rabbit/mouse	Dako	411083
TUNEL Assay Kit - HRP-DAB	Abcam	ab206386
MouseTRAP (TRAcP 5b) ELISA kit	IDS®	SB-TR103
RANKL (TNFS11) mouse ELISA kit	Abcam	ab100749
NZYSupreme qPCR Green Master Mix (2x), ROX plus	Nzytech	MB44101
RQ1 RNase-free DNase	Promega	M6101
TaqMan Gene Expression Master Mix	Applied Biosystems	4369016

Deposited data

Raw and analyzed transcriptomic data	This paper	GEO: GSE224435
Raw Western blot images	This paper	Mendeley: https://doi.org/10.17632/9zn7pyxmdp.2
Publically available dataset	Ma et al.³¹	GEO: GSE93204

Experimental models: Cell lines

Human: MCF-7^GFP+Luc+	Laboratory of Luis Costa, iMM	N/A
Human: T47D	Laboratory of Luis Costa, iMM	N/A
Human: MCF-7^OE	Laboratory of Luis Costa, iMM	N/A
Human: T47D^OE	Laboratory of Luis Costa, iMM	N/A

Experimental models: Organisms/strains

NOD.Cg-Prkdcscid Il2rgtm1Wjl/Szj	Charles River Laboratories	RRID: IMSR_JAX:005557

Oligonucleotides

Primers for qRT-PCR, see Table S5	N/A	N/A

Software and algorithms

FlowJo version 10.8.1 software	BD Biosciences	https://www.flowjo.com/; RRID:SCR_008520
ImageJ software	Schindelin et al.⁴⁷	https://imagej.nih.gov/ij/download.html; RRID:SCR_003070
GraphPad Prism version 8.4.3 software	GraphPad Software	https://www.graphpad.com; RRID:SCR_002798
R project version 4.1.2 software	CRAN	https://www.R-project.org/; RRID:SCR_001905
HISAT	Kim et al.⁴⁸	http://www.ccb.jhu.edu/software/hisat/index.shtml; RRID:SCR_015530
Bowtie2	Langmead et al.⁴⁹	https://bowtie-bio.sourceforge.net/bowtie2/index.shtml; RRID:SCR_016368
RSEM	Li et al.⁵⁰	https://deweylab.github.io/RSEM/; RRID:SCR_013027
PossionDis	Audic et al.⁵¹	N/A
Dr. Tom	BGI	https://biosys.bgi.com/
GSEA software	Subramanian et al.⁵²	http://www.gsea-msigdb.org/gsea/index.jsp
GEO2R package	Davis et al.⁵³	N/A
ReactomePA Bioconductor package	Yu et al.⁵⁴	https://bioconductor.org/packages/release/bioc/html/ReactomePA.html; RRID:SCR_019316

Other

Mycoplasma contamination test barcodes	Eurofins Genomics	MPC service
Silica beads	Biospec Products	110791102
iBlot®2 NC Mini Stacks	Invitrogen	IB23002
iBlot®2 NC Regular Stacks	Invitrogen	IB23001

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Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Sandra Casimiro (scasimiro@medicina.ulisboa.pt).

Materials availability

All unique/stable cell lines generated in this study are available from the lead contact with a completed materials transfer agreement.

Experimental model and subject details

Mouse studies

For this study, only female NSG mice (Mus musculus, NOD.Cg-Prkdcscid Il2rgtm1Wjl/Szj) were used to establish in vivo models of luminal BC (ectopic xenografts). Four-weeks-old animals were purchased from Charles River Laboratories (Massachusetts, USA). All animals were kept in specific pathogen-free (SPF) conditions, randomly housed per groups under standard laboratory conditions (at 20–22°C under 10-h light/14-h dark), and given free access to food (RM3, SDS Diets, Witham, UK) and water (Ultrapure). General or model-specific humane endpoints included 10% body weight loss, head-tilt, neurological disorders (such as paralysis and stereotypic behavior), abdominal distension, subcutaneous tumor >1000mm³ tumor volume. Animals were monitored at least once a week. Once they reached the humane or experimental endpoint, animals were euthanized by intraperitoneal injection of 0.25 mg/kg Sodium Pentobarbital (Eutasil). Experiments involving the use of mice were carried out in accordance with Directive 2010/63/EU (transposed to Portuguese legislation through Decreto-Lei No. 113/2013, of August 7th), to ensure that the use of animals complies with all applicable legislation and following the 3R’s principle. All animal procedures were approved by the institutional animal welfare body (ORBEA-iMM) and licensed by the Portuguese competent authority (Direcção Geral Animal e Veterinária - DGAV; license number: #005132-2020).

Cell lines

All cell lines used in this study were previously isolated from female BC patients, and include: MCF-7GFP+Luc+, herein designated by MCF-7, and T47D (provided by Dr. Phyllippe Clézardin, INSERM, Lyon, France). Their derivatives MCF-7 RANK OE (MCF-7^OE) and T47D RANK OE (T47D^OE) were previously generated by our group.²⁰ MCF-7 and T47D parental or derived cell lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco) supplemented with 10% (v/v) fetal bovine serum (FBS, Gibco), 1% (v/v) Penicillin/Streptomycin (Pen/Strep, 10,000 U/mL Penicillin, 10,000 μg/mL Streptomycin, Gibco), and 0.01 mg/mL insulin (Gibco). PalbR cells were derived from MCF-7 or T47D cells by continuous exposure to increasing concentrations of palbociclib (10 nM - 2.5 μM), with or without 100 ng/mL OPG-Fc (Amgen, Inc.) or 100 ng/mL RANK-Fc (R&D Systems) for 3 months. Cells were maintained at 37°C with 5% CO₂, used at low passage number, and regularly tested for Mycoplasma contamination by qPCR (Eurofins Genomics). In all studies related to acquired resistance, parental cells were cultured in parallel, for the same period of time under the indicated experimental conditions (untreated, Palbo-treated or Palbo+RANKLi-treated).

Human data

The publically available dataset GSE93204, which comprises transcriptomic data from the neoadjuvant clinical trial NeoPalAna (NCT01723774)³¹ was used.

Method details

Animal studies

Four-week old female NSG animals were supplemented with subcutaneous 0.36mg, 60-day release 17β-estradiol pellets (Innovative Research of America), inserted with a trochar in the mid-scapular region of the mouse under mild isoflurane anesthesia, four days prior to BC cell injection. MCF-7 PAR or MCF-7 RANK OE cells were harvested at the exponential phase of growth and resuspended at 10⁶ cells/mL in 50% phenol-free matrigel solution (Corning). Mice were injected subcutaneously with 100 μL of cell suspension, directly into the flanks. Tumor growth was monitored every three days with a caliper and tumor volume calculated using the formula Tvol = 1/2(lengthxwidth²). When tumors reached approximately 100mm³, mice were randomized based on tumor size and treated with: palbociclib (Palbo) 30 mg/kg/day p.o. (Sigma-Aldrich) plus fulvestrant (Fulv) 1mg/day s.c. (Selleckchem); Palbo+Fulv+OPG-Fc 10 mg/kg i.p. 3x/week (Amgen, Inc.); or vehicle (0.05 M Na Lactate (Sigma-Aldrich) plus 95% corn oil (Sigma-Aldrich) in 5% DMSO (Sigma-Aldrich)). At the experimental endpoint, mice were sacrificed by administration of 0.25 mg/kg Sodium Pentobarbital (Eutasil 200 mg/mL, CEVA SANTE ANIMALE). At necropsy, blood was collected by cardiac puncture into centrifuge tubes, centrifuged for 10 min at 1200g and serum was stored at −20°C until further use. Tumors were harvested and sectioned into two fragments for paraffin embedding or snapshot freezing. Organs were harvested and paraffin embedded. Results depict pooled data obtained from two independent experiments.

CDK6 knockdown

For CDK6 knockdown (KD), MCF-7 parental and RANK OE cells were seeded in 6-well plates, at a density of 2 × 10⁵ cells/well. 24 h after seeding, cells were transfected with control shRNA (Santa Cruz Biotechnology) or CDK6 specific shRNA (Santa Cruz Biotechnology) using Lipofectamin-3000 (Invitrogen) according to the manufacturer’s protocol. After 48h, cells were selected with 0.5 μg/mL puromycin dihydrochloride (Santa Cruz Biotechnology), and KD confirmed by Western Blot.

Cellular assays

To measure cell proliferation, cells were seeded in 96-well plates at a density of 1 × 10⁴ cells/well and 1:10 (v/v) Alamar blue (Invitrogen) was added to each well. Fluorescence (excitation 560nm; emission 590nm) was measured 2h after adding Alamar blue and at indicated time points in an Infinite M200 microplate reader (Tecan). To quantify cell viability, cells were seeded in 96-well plates at a density of 1 × 10⁴ cells/well, with or without fulvestrant (Selleck Chemicals), palbociclib (Sigma-Aldrich), ribociclib (Santa Cruz Biotechnology), abemaciclib (Selleck Chemicals), OPG-Fc (Amgen Inc), RANK-Fc (R&D Systems), 3-ATA (Santa Cruz Biotechnology), seliciclib (Focus Biomolecules), and/or fludarabine (Santa Cruz Biotechnology). Complete medium with drugs was replaced every 2 days. After 8 days, viability was measured by Alamar blue assay as described above. For clonogenic assays, cells were seeded in 6-well plates at a density of 2 × 10⁴ - 4 × 10⁴ cells/well for 7 days and allowed to recover for additional 7 days in drug-free medium. Cells were washed and fixed with 4% PFA (Merck) for 10min and stained with 2% crystal violet (Sigma-Aldrich) for 10 min. Crystal violet was solubilized with 1% SDS (Merck) for 15–30 min and absorbance at 570 nM was measured in an Infinite M200 microplate reader (Tecan).

Flow cytometry

For cell cycle analysis, 2 × 10⁵ - 4 × 10⁵ cells were seeded in 60mm dishes and cultured for 7 days, fixed in ice-cold 66% ethanol (VWR) and kept at 4°C until analysis. Cell cycle analysis was performed using the Propidium iodide (PI) flow cytometry kit (Abcam), following the manufacturer’s protocol. Data acquisition was performed in a BD LSRFortessa flow cytometer (BD Biosciences) and analysis was performed with the FlowJo V10 software. All flow cytometry experiments were performed at the Cytometry Facility of Instituto de Medicina Molecular João Lobo Antunes, Lisbon, Portugal.

qRT-PCR

Total RNA was extracted with the NZY Total RNA Isolation kit (Nzytech), according to manufacturer’s instructions, quantified in a NanoDrop spectrophotometer (Thermo Fischer Scientific), and treated with RQ1 RNase-free DNase (Promega) for 30 min at 37°C, in accordance with manufacturer instructions. All primers, except TaqMan probes, were synthesized by Thermo Fisher. DNase I-treated RNA was reverse transcribed using the NZY M-MuLV First-Strand cDNA Synthesis kit (Nzytech) and Oligo(dT)20 primers. cDNA was amplified by real-time PCR using TaqMan Gene Expression Master Mix (Applied Biosystems) or NZYSupreme qPCR Green Master Mix (2x), ROX plus (Nzytech), according to manufacturer’s instructions. For primer details, see Table S5. PrimerBank sequences were obtained from https://pga.mgh.harvard.edu/primeRbank/.

Western Blot

For the analysis of RANK pathway activation, 4 × 10⁵ cells were seeded in 6-well plates for 24h, serum-starved in low-serum medium (0.1% FBS, 1% Pen/Strep) for 24h, to ensure depletion from exogenous growth factors present in FBS including RANKL, and stimulated with 1 μg/mL human RANKL (Amgen Inc.) and/or 5 ng/mL human IFNγ (Peprotech) for 15 min. RANKL was neutralized by incubation at 37°C with 2.5 μg/mL of OPG-Fc (Amgen Inc.) or RANK-Fc (R&D Systems) for 60 min, before being used to stimulate cells. To assess the effect of specific compounds, cells were seeded in 6-well plates at a density of 1 × 10⁵-4x10⁵ cells/well. Total cell lysates were prepared with RIPA buffer (Sigma-Aldrich) containing 1:100 (v/v) protease (Cell Signaling) and phosphatase (Sigma-Aldrich) inhibitors’ cocktails, according to manufacturer’s instructions. Total protein was quantified using Pierce BCA Protein Assay Kit (Thermo Scientific), following the manufacturer’s protocol. Specific primary antibodies were used overnight at the following dilution conditions: rabbit monoclonal anti phospho-Rb (Ser807/811) (D20B12), anti phospho-NF-kB p65 (Ser536) (93H1), anti NF-kB p65 (D14E12), anti phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204), anti p44/42 MAPK (Erk1/2) (137F5), anti CDK4 (D9G3E), anti cyclin D1 (92G2), anti CDK2 (78B2), anti CDK6 (DCS83), anti CDK7, anti p27 Kip1 (D69C12), anti p21 Waf1/Cip1 (12D1), anti phospho-STAT1 (Tyr701) (D4A7), anti phospho-STAT1 (Ser727) (D3B7), anti STAT1 (D1K97), all from Cell Signaling, and anti phospho CDK4 (Thr172) (St John’s Laboratory), all 1:1000 in 5% BSA; anti cyclin E (HE12) (Sigma-Aldrich), 1:1000 in 5% Milk; anti RANK (Cell Signaling), 1:750 in 2.5% BSA; and anti β-Actin antibody (#ab6276; Abcam), 1:24000 in 5% Milk. Horseradish peroxidase-conjugated (HRP) specific secondary antibodies anti-mouse-HRP IgG and anti-rabbit-HRP IgG (both from Cell Signaling) were used. Proteins were detected using the Novex ECL HRP chemiluminescent substrate reagent kit (Invitrogen) according to the manufacturer’s instructions, and membranes were visualized in Amersham Imager 680 (GE Healthcare Life Sciences). Proteins were detected by chemiluminescence and ImageJ software⁴⁷ was used to obtain the best contrast for Western Blot band visualization and background removal.

Immunohistochemistry

All animal samples were processed at the Comparative Pathology Facility of Instituto de Medicina Molecular João Lobo Antunes, Lisbon, Portugal. 5μm tissue sections from Formalin-Fixed Paraffin-Embedded (FFPE) samples were stained by immunohistochemistry (IHC) for the detection of Ki67 and p-Rb, using Dako reagents and PT Link Pre-Treatment Module for Tissue Specimens for deparaffinization and antigen retrieval with Antigen Retrieval Solution pH9.0, at 94°C for 20 min. Endogenous peroxidase was blocked with Peroxidase Blocking Solution for 10 min at RT, and total protein was blocked by incubation with Protein Block Solution, for 20 min at RT. Slides were incubated for 30 min with rabbit anti human Ki67 primary antibody (1:100, MIB-1, Dako) or rabbit monoclonal anti phospho-Rb (Ser807/811) (D20B12) (1:400, Cell Signaling) in Antibody Diluent. Slides were incubated with EnVisionTM Detection System, rabbit/mouse for Ki67 and rabbit for p-Rb, according to manufacturer’s instructions, followed by 5 min of incubation with DAB. Slides were counterstained with hematoxylin, and visualized in a bright field microscope (LeicaDM750) with a Leica ICC50 HD camera.

TUNEL assay

Terminal deoxynucleotidyl transferase dUTP nick end labeling for the detection of apoptotic cells was performed using the TUNEL Assay Kit - HRP-DAB (Abcam), according to the manufacturer’s instructions, on 5μm FFPE tissue sections.

ELISA

TRAcP 5b was quantified in mouse serum using the MouseTRAP (TRAcP 5b) ELISA kit (SB-TR103, IDS), according to the manufacturer’s instructions.

RANKL was quantified in mouse serum and in FBS using RANKL (TNFS11) mouse ELISA kit (Abcam), following manufacturer’s instructions. Serum was isolated from the peripheral blood of tumor naive animals (NSG, Balb/c or CD-1), collected by cardiac puncture at euthanasia.

Transcriptomic analysis of mouse tumors

Total RNA was extracted using the NZY Total RNA Isolation kit (Nzytech), according to manufacturer’s instructions. Tumor tissues collected at necropsy were preserved in RNA later (Thermo Fisher Scientific), transferred to lysis buffer with silica beads (Biospec Products), and disrupted in a Minibeadbeater (Biospec Products) for 1–2 min. RNA quality control (QC) was performed by BGI, using the Agilent 2100 Bio analyzer (Agilent RNA 6000 Nano Kit).

Quantification and statistical analysis

Gene expression by qRT-PCR

Gene expression was normalized to GAPDH (TaqMan) or 18S (other) expression, and relative mRNA expression was calculated using the 2^−ΔCt method.

Band densitometry analysis

Membranes were visualized in Amersham Imager 680 (GE Healthcare Life Sciences). Proteins were detected by chemiluminescence and ImageJ software⁴⁷ was used to obtain the best contrast for Western Blot band visualization and background removal. Band intensity was calculated using ImageJ software and normalized for β-Actin.

Immunoscores

Ki67 and p-RB positive cells (ImmunoRatio) were quantified as the percentage of DAB-stained nuclear area over total nuclear area, from four fields at 400x magnification, using the ImageJ software.⁴⁷ For TUNEL slides, visualized as described above, it were quantified the total number of positive cells on four fields of tumor area at 400x magnification.

RNA-sequencing and microarray data analysis

RNA-seq of mouse tumors was performed in the BGISEQ-500 platform; mapping to reference genome (GCF_000001405.38_GRCh38.p12) was performed with HISAT⁴⁸ and to the reference genes with Bowtie2.⁴⁹ Expression levels in fragments per kilobase million (FPKM) for each sample were calculated with RSEM.⁵⁰ For tumor tissues (2–3 tumors per treatment group), the average bases per sample was 6.85G, average mapping ratio with reference genome 76.76%, and average mapping ratio with gene 55.49%. Were identified 19.313 genes. Differential expressed genes (DEGs) were detected with PossionDis.⁵¹ For The Cancer Genome Atlas (TCGA) BC cohort, in silico analysis was performed as previously described.²⁰ The web-based solution Dr. Tom (BGI, https://biosys.bgi.com/) and GSEA software (Broad Institute, Massachusetts, USA)⁵² using MSigDB v6.2 Hallmarks gene sets collection, were used for calculating enrichment scores (assuming all expressed genes) in tumor tissue and TCGA datasets, respectively. p value was set at 0.05 and false discovery rate (FDR) for each p value was set as 0.25 for tumor analyses and 0.05 for TCGA dataset. GEO query, log-transformation and normalization of the NeoPalAna microarray dataset was performed by using the loading and normalization modules in the GEO2R package.⁵³ Gene set enrichment analysis of NeoPalAna RANK correlated genes was performed using the ReactomePA Bioconductor package.⁵⁴

Statistical analysis

Data was analyzed using GraphPad Prism version 8.4.3 software and the R environment (https://www.R-project.org/). The unpaired t-test, one sample t-test, one-way ANOVA, two-way ANOVA or Wilcoxon rank test were used as appropriate. Results are presented as mean ± SEM and p value <0.05 was considered statistically significant. ns, not significant, ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Acknowledgments

The authors acknowledge Drs. Nuno Barbosa-Morais, Angelica Santiago, and Pedro Luis Echevarria for critical discussion of experimental results and for reviewing the manuscript and the Histology and Comparative Pathology Laboratory and Rodent and Flow Cytometry Facilities of Instituto de Medicina Molecular for technical support. This project was funded by the research project PTDC/MED-ONC/28636/2017 from Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES) through Fundos do Orçamento de Estado. I.G. was supported by FCT PhD grant SFRH/BD/139178/2018. The laboratory of E.G.S. is supported by FUNDACION MARATO TV3 43/C/2019, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-CoG grant agreement 682935), and the Spanish Ministry of Science and Innovation, Agencia Estatal de Investigación (AEI) (PID2020-116441GB-I00), co-funded by FEDER funds/European Regional Development Fund (ERDF) (a way to build Europe). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author contributions

Conceptualization, S.C. and L.C.; methodology, I.G., L.M.G.-P., M.J., P.G.S., A.M., R.S., C.A., E.G.S., and S.C.; investigation, I.G., L.M.G.-P., and S.C.; writing—original draft, I.G. and S.C.; writing—review & editing, all authors; funding acquisition, L.C. and S.C.; supervision, L.C. and S.C.

Declaration of interests

S.C., L.C., and E.G.S. received research support from Amgen Inc. in the form of supplies. E.G.S. has received funding from Amgen Inc. A.M., C.A., and R.S. have received honoraria as consultants/speakers and/or travel/logistics support from Amgen, Novartis, and Pfizer. L.C. and S.C. are inventors on a patent application directed to combination treatment with RANK pathway inhibitors and CDK inhibitors.

Inclusion and diversity

We support inclusive, diverse, and equitable conduct of research.

Published: July 13, 2023

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.xcrm.2023.101120.

Contributor Information

Luis Costa, Email: luiscosta.oncology@gmail.com.

Sandra Casimiro, Email: scasimiro@medicina.ulisboa.pt.

Supplemental information

Document S1. Figures S1–S5 and Tables S1–S5

mmc1.pdf^{(1.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(7.3MB, pdf)}

Data and code availability

RNA-Seq data have been deposited at Gene Expression Omnibus (GEO: GSE224435) and is publicly available as of the date of publication. This paper analyzes existing, publicly available data (GEO: GSE93204). Raw data from Figures 4B, 6F, S1B, S1C, S1D, S1G, S2B, and S5A, was deposited on Mendeley at https://doi.org/10.17632/9zn7pyxmdp.2 and is publicly available as of the date of publication. Microscopy data reported in this paper will be shared by the lead contact upon request. This paper does not report original code. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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Associated Data

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

Supplementary Materials

Document S1. Figures S1–S5 and Tables S1–S5

mmc1.pdf^{(1.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(7.3MB, pdf)}

Data Availability Statement

[bib1] 1.Howlader N., Cronin K.A., Kurian A.W., Andridge R. Differences in breast cancer survival by molecular subtypes in the United States. Cancer Epidemiol. Biomarkers Prev. 2018;27:619–626. doi: 10.1158/1055-9965.EPI-17-0627. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Co-targeting RANK pathway treats and prevents acquired resistance to CDK4/6 inhibitors in luminal breast cancer

Inês Gomes

Lina M Gallego-Paez

Maria Jiménez

Patricia G Santamaria

André Mansinho

Rita Sousa

Catarina Abreu

Eva González Suárez

Luis Costa

Sandra Casimiro

Summary

Graphical abstract

Highlights

Introduction

Results

RANK OE in luminal BC cells induces intrinsic resistance to CDK4/6i reversible by RANK pathway inhibition

Figure 1.

RANK pathway inhibition overcomes RANK OE-induced intrinsic resistance to Palbo + Fulv in vivo

Figure 2.

RANK OE and CDK4/6i are associated with an increase in IFN response hallmark

Figure 3.

The RANK pathway is associated with increased IFN signaling

Figure 4.

RANK is upregulated in luminal BC patients treated with CDK4/6i

Figure 5.

RANK pathway inhibition treats and prevents acquired resistance to CDK4/6i

Figure 6.

Discussion

Limitations of the study

STAR★Methods

Key resources table

Resource availability

Lead contact

Materials availability

Experimental model and subject details

Mouse studies

Cell lines

Human data

Method details

Animal studies

CDK6 knockdown

Cellular assays

Flow cytometry

qRT-PCR

Western Blot

Immunohistochemistry

TUNEL assay

ELISA

Transcriptomic analysis of mouse tumors

Quantification and statistical analysis

Gene expression by qRT-PCR

Band densitometry analysis

Immunoscores

RNA-sequencing and microarray data analysis

Statistical analysis

Acknowledgments

Author contributions

Declaration of interests

Inclusion and diversity

Footnotes

Contributor Information

Supplemental information

Data and code availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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