RANK is a poor prognosis marker and a therapeutic target in ER‐negative postmenopausal breast cancer

Abstract Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor‐negative, ER−) from four independent cohorts. RANK protein expression was more frequent in ER− tumors, where it associated with poor outcome and poor response to chemotherapy. In ER− breast cancer patient‐derived orthoxenografts (PDXs), RANKL inhibition reduced tumor cell proliferation and stemness, regulated tumor immunity and metabolism, and improved response to chemotherapy. Intriguingly, tumor RANK protein expression associated with poor prognosis in postmenopausal breast cancer patients, activation of NFKB signaling, and modulation of immune and metabolic pathways, suggesting that RANK signaling increases after menopause. Our results demonstrate that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and ER− breast cancer patients and support the therapeutic benefit of RANK pathway inhibitors, such as denosumab, in breast cancer patients with RANK+ ER− tumors after menopause.

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Lise Roth
Lise Roth, PhD Senior Editor EMBO Molecular Medicine ***** Reviewer's comments ***** Referee #1 (Remarks for Author): This is a potentially interesting results on the connection of RANK expression with response to chemotherapy in TNBC. The main thrust of the paper is shown in Figures 4-6: RANKL inhibitions cooperate with chemotherapy (docetaxel) to suppress ERnegative/RANK+ PDX growth (Fig 4); RANK tumor expression associates with poor survival in postmenopausal patients ( Fig 5); and RANKL inhibition attenuates tumor growth of a RANK+ ER-BC PDX in ovariectomized mice (postmenopausal conditions). Although interesting, the results are descriptive and seem like the beginning of a good story, which need further development. Most importantly, the mechanistic basis for the effect of RANKL inhibition on survival of postmenopausal ER-RANK+ BC patients and for the cooperation with or potentiation of chemotherapy is lacking? Specifically: -the mechanistic basis for the enhanced effect of RANKL-inhibition in ovariectomized mice should be explored/elucidated. -There is a known crosstalk between ER and NFkB. Does ER suppress RANK in ER+ breast cancer or does high RANK suppress ER expression in TNBC? i.e. can the authors immunoblot for ER in figure 2D? -Why ER-BC cells respond to ovariectomy? -Postmenopausal ER+ breast cancer is treated with aromatase inhibitors. Would such inhibitors further enhance the effect of ovariectomy? -Does RANK-shRNA have similar effect as RANKL-inhibitors - Fig. 6 should be expanded to include additional PDXs Other issues • The Abstract is a bit sloppy going back and forth about the correlation of RANK expression with poor prognosis in ER-negative BC (first) and then with poor prognosis in postmenopausal BC (Second). These two may be combined.
"Our results demonstrate that. RANK protein expression..." -a full stop in the middle of a sentence.
One sentence is interrupted and another line starts as a new paragraph.
Abstract ends with no full stop. • Fig. 1d shows distant metastasis-free survival (DMFS) of all patients is worse for RANK+ patients but not significantly. The Hazard ratio should be provided. As indicated by the authors, the worse OS of RANK+ patients (the only statistically significant cohort), and the poor DMFS may reflect the fact that RANK is a marker for TNBCs which have poor prognosis. If only TNBC patients are stratified based on RANK expression -is there any effect on clinical outcome? This analysis is shown later, in Fig. 3b bottom, where high RANK is associated with a moderate but not significant worse prognosis. Overall, the differences are not great, may be subtype-related, and are not entirely clear.
Notably, a KM-Plotter analysis (https://kmplot.com) shows no significant effect of RANK expression in TN -Basal-breast cancer, based on RNA expression. When protein levels are used -high RANK expression correlates with better prognosis. Can the authors confirm and discuss the discrepancy between this site vs their IHC data?
• "Tumors with the highest levels of RANK mRNA expression were found in the ER-subtype. Meanwhile". -A correlation analysis between RANK and ER should be provided.
• page 6 "In all cohorts, RANK expression (H > 0) was significantly associated with ER/PR negativity and TNBC subtype, but not HER2, age, tumor size or stage. In the NPS collection, RANK expression was also associated with a higher mitosis rate and grade (Fig. 1d, Table S1). RANK has been extensively studied in breast cancer. The conclusions are drawn from very few patient samples.
Referee #2 (Remarks for Author): In this manuscript, Ciscar et al. present evidence that RANK is a poor prognosis and a potential target in ER-negative breast cancer. Denosumab (DNS) a RANK ligand (RANKL) inhibitor has been used clinically in breast cancer (BC) for decades, in patients who have bone metastasis to prevent further loss of bone mass, most often associated with ER-positive breast cancers. DNS is also extensively used in patients with osteoporosis to prevent further bone density loss. Both RANK and the receptor of RANKL activity have been heavily published in BC, including by the authors. The authors present data from two independent TMA collections for all BC subtypes from the IDIBELL (IDB) and the Nottingham series (NPS) s and a subset of the NPS which were part of the METRABIC study. The IHC from these data was not impressive for RANK protein expression. The number of RANK-positive was highest in the NPS than IDB study with The result for TNBC in both IRB and NPS subtypes was correlating with the highest expression of RANK. RANK expression has been shown to be a prognostic and predictive marker in breast cancer subtypes Functional, validation for RANK was done by using several PDX models, the authors show that RANK is mostly restricted to ERnegative PDX tumors. Exposure to hRANKL activated the TNF/NFκB signaling pathway in three PDX models in vitro ERnegative. And In vivo PDX ER-negative tumor treated with RANK inhibitor (RANK-Fc) alone or in combination with docetaxel inhibition showed moderate effects on tumor growth. Nonetheless, combination with docetaxel decreases tumor growth. Comparisons using expression profiling with generated GSEA pathways utilizing: 1) METABRIC, PDX derived tumors inhibited for RANK activity and clinical trials for early breast cancer using denosumab concluded the RANK signature prevails in ERnegative BC above the ER-positive BC. The GSEA pathways /data sets/ survival outcome(s), along with premenopausal and postmenopausal status were integrated to further provide evidence that RANK is most prominently predictive in premeopsaul ER-negative BC. Suggesting that clinical work should target RANK as a precision target in premenopausal ER-negative breast cancer a very important aspect to meet clinic needs.
In general: This is an extensive study that provide evidence to convince us that RANK is important in ER-negative BC from a leader in the field. Yet several areas of concern as to the virtuosity of the study as to how widely to define ER-negative breast cancer subtypes, that is within such a category you also may harbor other subtypes, e.g., TNBC, HER2, BRCA etc... The nomenclature used to draw conclusion between ER-negative and ER-positive BC cause concerns due to having analysis on limited sample size, that de-arms datas statistically insignificant. In the present form the manuscript is not acceptable and or will require major revisions. Major/Minor issues: 1) The authors are well verse and know that BC subtypes is a heterogenous disease. ER+, PR+, ER+/PR+ HER2, Luminal A, Luminal B , Basal-like, BRCA, TNBC etc... 2) ER-negative can be reflective of several subtype for example, PR+ or HER2 or a TNBC they are all ER-negative so is RANK. As example of this in the Nottingham Series were histological grade is provide to be significant for RANK expression the data reflect only 61 patient samples out of 1,054. 3) Similarly with the "vascular invasion" significance is based on 4 positive patients to make ana argument for RANK expression to be important paler in vascular invasion. 4) Additionally BCSS and DMFS significance is driving by few sample number the ER-negative Nottingham Series 8 and 7. 5) The author never reflect the true number in the text they are significance but in very few samples. 6) The menopausal status for RANK expression the Nottingham Series for ER+ BC was significant with only 24 driving the postmenopausal significance. Yet the ER-negative cohort BC postmenopausal was not statistically significance. Is not the argument that RANK is important in ER-negative postmenopausal women? Please clarify. 7) On occasion this reviewer was not sure if the authors were speaking describing correct clinical data when this reviewer was looking at in supplemental tables. A possible suggestion a "red highlight" in the excel table sheet would facilitate finds the discussed results. 8) Figure 1: IHC for stroma vs tumor staining for RANK was not impressive as the staining looks like it is mostly stroma and no tumor. One sample of IHC does not represent the IDB and or NPS study to draw these conclusions. None of these results are in ER negative subtypes. SFS1A/B/C has no statistical significance shown. 9) Figure 2: The authors state that there is no "functionality of RANK in human BC..." there are at minimum 256 published articles on RANK in BC, and more than one has done functionality studies of RANK. Fig2a qPCR is of poor resolution. 10) Figure 2D why was no RANK western run of the PDX tumors? because IHC on the PDX not impressive and is the BCM3277 least impressive by IHC, yet is very responsive to hRANKL activation of TNF/NFKB signaling. SFS2B RANK in the STG139M is low vs that of BCM-3277 is high yet IHC is the reverse. 11) If BCM3277 was original an ER positive as stated then become a ER negative how do the authors know if PR or HER2 is not there as well? Or if it's truly TNBC? Same goes for the other PDX models used. 12) Rationale not provide as to why RNA seq was done on the PDX model with exposure to RANKL for one month. 13) Fig3E is followed by "Tumor stage independently associated with three survival parameters analyzed.." refer data to Table  S1. Which specific comparisons where done did the authors use the COX NPS vs CP NPS tabs? Please clarify. 14) Fig4. In Fig 1 IHC show that PDX AB521-X has more RANK that STG139-M, both responded to hRANKL yest these same PDX is never treated with DNS why? Same goes for BCM-3277 . 15) Similar concerns arise in the combinatorial DTX studies. No rationale is given. 16) If you block with RANK-Fc why did the tumor proliferate? This is never discussed. 17) Section on pathways the authors state "PDX GSEA demonstrates....200 pathways differentially expresses. TS3 has allot dozens of tabs was not easy to identify, which it is please clarify and identify. 18) FigS5A TS3 "Immunity" pathways? Which comparison again dozen of tabs multiple comparison which one are the authors referring to? S5B RANKL inhibition in three PDX models which three is not clear. 19) RANKL is regulated by progesterone in mammary gland homeostasis whereas estradiol/opg is the inhibitor of RANK/RANKL signaling (reference 30). Should state that is in bone please clarify inference make it sound like it does so in mammary gland . 20) Fig5a Table S1 it was not clear if RANK was predicting DMFS and BCSS not clear from the data if it was refereeing to ERor the ER+, please clarify. 21) Following Fig5B, data from Table S1 was sued to refence "survival of 15/20 years" yet on the data CNIO data was only for 12 years, please clarify, similarly please clarify which chemoresistance data is been represented, not clear which one if been used from the text or the Tables S1. 22) The rationale to compare PDX data (Fig5C Table S4) with that of the postmenopausal METABRIC data sets is not clear stated at all. How does a PDX in a NSG mice comparison work? 23) Fig6C data set not significant, why not use denosumab in the AB 521?
Referee #3 (Remarks for Author): The manuscript is rather interesting as it looks at the role of RANK in breast cancer and leverages the large datasets to do sobut importantly the authors have followed up with wet work to test the hypotheses that they generated. They should be commended for this. Only minor concerns are listed that may aid in the manuscript: 1) Figure 1D -can you split this to the PAM50 subtypes and show that this is not simply a function of basal vs all other subtypes. It would be good to show here that RANK status within a subtype can show altered outcomes.
2) Figure 2 -I would suggest bringing some of the supplemental data for a non-responsive line as a control into the main figure (2D).
3) RNAseq data -I was unable to review the data deposited to GeoDatasets. Please make a reviewer token available so that the data can be reviewed PRIOR to publication. An embargo until publication is fine, but please provide a reviewer link and token. 4) GSEA -again, I'd suggest bringing this into the main portion of the manuscript. Cut some of Figure 2C and bring some of the data from table S3 in as a GSEA based figure showing the random walk. FIgure 3B does not indicate in the legend or on the figure which is RANK +ve or -ve 6) Figure 5 -again, split out the subtypes and do the appropriate statistical tests.

Point by point response EMM-2022-16715
Referee #1 (Remarks for Author): This is a potentially interesting results on the connection of RANK expression with response to chemotherapy in TNBC. The main thrust of the paper is shown in Figures 4-6: RANKL inhibitions cooperate with chemotherapy (docetaxel) to suppress ERnegative/RANK+ PDX growth (Fig 4); RANK tumor expression associates with poor survival in postmenopausal patients ( Fig 5); and RANKL inhibition attenuates tumor growth of a RANK+ ER-BC PDX in ovariectomized mice (postmenopausal conditions). Although interesting, the results are descriptive and seem like the beginning of a good story, which need further development. Most importantly, the mechanistic basis for the effect of RANKL inhibition on survival of postmenopausal ER-RANK+ BC patients and for the cooperation with or potentiation of chemotherapy is lacking?
Specifically: -the mechanistic basis for the enhanced effect of RANKL-inhibition in ovariectomized mice should be explored/elucidated.
We agree with the referee that it is highly relevant to explore further the mechanism underlying the distinct biology of RANK signaling in postmenopausal conditions and the greater effect in ovariectomized mice. This is an ongoing line of research in the laboratory. We are using additional experimental models and clinical samples from our ongoing clinical trial, D-BIOMARK for this purpose. Our current hypothesis is that differences in tumor cell metabolism driven by RANK contribute to the greater effect observed in postmenopausal conditions. Preliminary results support that the drop in estradiol changes systemic metabolism but also tumor cell metabolism driven by RANK. Additional mechanisms may include: enhanced activation of RANK signaling in the tumors after menopause that would make them more responsive to RANKL inhibition, putative cooperation of RANKL inhibitors with soluble factors released from the bone. Additional work that extends beyond this revision is required to provide a solid mechanism. For this reason, as suggested by the editors, we have submitted the revised manuscript as a Report, where we discuss potential mechanisms contributing to these differences.
-There is a known crosstalk between ER and NFkB. Does ER suppress RANK in ER+ breast cancer or does high RANK suppress ER expression in TNBC? i.e. can the authors immunoblot for ER in figure 2D?

ER was not detectable by IHC in any of the PDX used in the manuscript for functional studies, despite some of them (such as BCM-3277) were derived from luminal tumors. Lack of ER expression in these PDXs has been reported previously by the donor laboratories (MT Lewis, C Caldas, A Bruna and ours). As requested by the referee, we confirmed the lack of ER expression by WB and IHC in the three PDXs used for in vivo experiments, BCM-3277, STG139-M and AB521-X. The ER + MCF7 cell line was used as a positive control in the WB. ER expression was detected by IHC in the mammary glands of NSG mice as the ER antibody we used recognizes both mouse and human ER. These results have not been included in the revised manuscript to keep it focused.
We agree that addressing the potential regulation of RANK by ER or vice versa would be interesting. To explore this possibility we have analyzed ER expression in different ER + breast cancer cell lines where we have overexpressed RANK. As shown below, we 1st Dec 2022 1st Authors' Response to Reviewers did not find any association between RANK and ER expression levels. These results are not included in the revised version of the manuscript to keep it focused. -Why ER-BC cells respond to ovariectomy?
The most plausible explanation is that the "response" is indirect. The drop in systemic estrogen levels has multiple effects, changes in systemic metabolism, inflammation, bone resorption and osteoporosis (due to increased RANK signaling in the bone) (Khosla et al.Trends Endocrinol. Metab. 2012, 23: 576); enhanced RANK signaling is also observed in the ERtumors after menopause ( Fig 3D). Moreover, in ERtumors the pathways associated with RANK expression are different between pre and postmenopausal conditions (Fig 3D).
-Postmenopausal ER+ breast cancer is treated with aromatase inhibitors. Would such inhibitors further enhance the effect of ovariectomy?

Indeed, aromatase inhibitors (AIs) block E1 (estrone), the main source of estrogens after menopause and are efficient in postmenopausal ER + BC. Previous studies have
demonstrated that the AIs letrozole and exemestane suppress tumor growth in ovariectomized mice transplanted with the ER + MCF7 breast cancer cell line (Jelovac et al. Clin Cancer Res 2004,10:7375;Nuñez et al. Clin Cancer Res 2004,10:5375).
As the PDX models used in this study are ER-, it is not expected that AIs will show therapeutic value. As the current manuscript is focused on the prognostic and therapeutic potential of RANK signaling in ER-BC, addressing the therapeutic benefit of AIs after ovariectomy is not in the scope of this study.
-Does RANK-shRNA have similar effect as RANKL-inhibitors

While shRANK will inhibit RANK signaling on the tumor cells, RANKL inhibitors will have a systemic effect, inhibiting RANK signaling not only on the tumor cells, but also in any other RANK+ cell; thus, the effects may not be similar. Ongoing research in the laboratory aims to dissect the contribution of each compartment to tumorigenesis using tissue-specific genetic cre/loxp approaches. We previously showed that RANK loss specifically in tumor cells changes the immune microenvironment (Gomez-Aleza, Nat
Comm 2020) and ongoing unpublished results evidence that myeloid RANK signaling also modulates tumor growth. In this manuscript, given its translational nature, we chose to work with RANK-Fc/denosumab, as it is the current therapeutic treatment, and PDX models, given its superior clinical relevance.

Figures for reviewers removed
Other issues: • The Abstract is a bit sloppy going back and forth about the correlation of RANK expression with poor prognosis in ER-negative BC (first) and then with poor prognosis in postmenopausal BC (Second). These two may be combined. We decided to keep both messages separated in the abstract. Our results support that RANK is a factor of poor prognosis and response to chemotherapy in ERbreast cancer. The chemotherapy experiments in the PDXs were performed in premenopausal conditions. On the other hand, RANK is associated with poor prognosis in postmenopausal patients from IDIBELL and NPS heterogeneous cohorts (Fig 3A and EV5A of the revised manuscript). As most of the samples in these cohorts are ER+ tumors, RANK is an independent factor of poor prognosis after menopause irrespectively of ER expression. Of course, when both conditions are met, ER-and postmenopause, the prognostic value of RANK is stronger.
"Our results demonstrate that. RANK protein expression..." -a full stop in the middle of a sentence. One sentence is interrupted and another line starts as a new paragraph. Thanks for noticing the mistake. It is now corrected.

Abstract ends with no full stop.
This is now corrected. The revised manuscript is now formatted as a Report with three main figures. We selected the most relevant findings from the previous Fig 1 to highlight the large number of samples analyzed (> 1500 from two independent collections) and the PDX models selected for functional studies.

• Fig 1d shows distant metastasis-free survival (DMFS) of all patients is worse for RANK+ patients but not significantly. The Hazard ratio should be provided.
A new panel including the hazard ratios is now provided for this (Fig 1E revised manuscript), but also for the other relevant findings (Fig 2D, Fig 3C). Complete information is included in Table EV1.
As indicated by the authors, the worse OS of RANK+ patients (the only statistically significant cohort), and the poor DMFS may reflect the fact that RANK is a marker for TNBCs which have poor prognosis. If only TNBC patients are stratified based on RANK expression -is there any effect on clinical outcome? This analysis is shown later, in Fig 3b bottom, where high RANK is associated with a moderate but not significant worse prognosis. Overall, the differences are not great, may be subtype-related, and are not entirely clear. Fig 1D support

This is solid evidence that RANK protein expression in the tumor is a biomarker of poor prognosis in ER -BC.
Notably, a KM-Plotter analysis (https://kmplot.com) shows no significant effect of RANK expression in TN -Basal-breast cancer, based on RNA expression. When protein levels are used -high RANK expression correlates with better prognosis. Can the authors confirm and discuss the discrepancy between this site vs their IHC data?
Several reasons may contribute to the discrepancies between this and other studies using RNA or protein data: 1. The levels of RANK mRNA and protein expression do not necessarily correlate, as supported by the PDX analyses. Moreover, RANK protein expression is frequently found in the stroma (Fig 1A-B), which misleads the results. Our study adds a differential analysis of RANK expression by IHC in either the tumor or the stroma using the most specific and sensitive antibody in the field. • "Tumors with the highest levels of RANK mRNA expression were found in the ER-subtype. Meanwhile".
-A correlation analysis between RANK and ER should be provided.
We have now rephrased the sentence: "RANK mRNA expression was detected in the 52 BC PDX models tested, mean levels being higher in PDX derived from ERtumors".
As requested by the referee, we have analyzed ESR1 mRNA expression levels in most PDXs shown in Fig EV2A,   • page 6 "In all cohorts, RANK expression (H > 0) was significantly associated with ER/PR negativity and TNBC subtype, but not HER2, age, tumor size or stage. In the NPS collection, RANK expression was also associated with a higher mitosis rate and grade (Fig 1d, Table S1). Shouldn't this be Fig 1C? The revised manuscript has been re-organized to meet the requirement of a Report.

The analyses from three independent cohorts (NPS -277 tumors-, ER-NEGATIVE ONLY -377 tumors-and TNBC (CNIO) -56 tumors-) strongly support that RANK is a marker of poor prognosis in ER -BC. Cox regression analyses in the ER-NEGATIVE ONLY cohort reinforce this conclusion.
The importance of RANK as a marker of poor survival in postmenopausal BC is proven using data from three independent collections .

Cox regression analyses supports that RANK is an independent poor survival marker in postmenopausal ER -BC.
Referee #2 (Remarks for Author): In this manuscript, Ciscar et al. present evidence that RANK is a poor prognosis and a potential target in ER-negative breast cancer. Denosumab (DNS) a RANK ligand (RANKL) inhibitor has been used clinically in breast cancer (BC) for decades, in patients who have bone metastasis to prevent further loss of bone mass, most often associated with ER-positive breast cancers. DNS is also extensively used in patients with osteoporosis to prevent further bone density loss. Both RANK and the receptor of RANKL activity have been heavily published in BC, including by the authors. The authors present data from two independent TMA collections for all BC subtypes from the IDIBELL (IDB) and the Nottingham series (NPS) s and a subset of the NPS which were part of the METRABIC study.
The IHC from these data was not impressive for RANK protein expression. The number of RANK-positive was highest in the NPS than IDB study with The result for TNBC in both IRB and NPS subtypes was correlating with the highest expression of RANK. RANK expression has been shown to be a prognostic and predictive marker in breast cancer subtypes. The GSEA pathways /data sets/ survival outcome(s), along with premenopausal and postmenopausal status were integrated to further provide evidence that RANK is most prominently predictive in premeopsaul ER-negative BC. Suggesting that clinical work should target RANK as a precision target in premenopausal ER-negative breast cancer a very important aspect to meet clinic needs.

Our data in 3 independent collections, IDB, NPS and ER-NEGATIVE ONLY, supports that RANK expression is a marker of poor prognosis in BC and ER -BC in postmenopausal women.
GSEA analyses in METABRIC also demonstrate that RANK protein expression strongly associates with NFKB activation in postmenopausal BC but not in premenopausal BC, which may be indicative of an enhanced RANK signaling and/or inflammation in postmenopausal tumors.
In general: This is an extensive study that provide evidence to convince us that RANK is important in ER-negative BC from a leader in the field. Yet several areas of concern as to the virtuosity of the study as to how widely to define ER-negative breast cancer subtypes, that is within such a category you also may harbor other subtypes, e.g., TNBC, HER2, BRCA etc... The nomenclature used to draw conclusion between ER-negative and ER-positive BC cause concerns due to having analysis on limited sample size, that de-arms datas statistically insignificant. In the present form the manuscript is not acceptable and or will require major revisions.
We agree that ER -BC is heterogeneous and can be further sub-classified according to HER2 expression, BRCA1 mutations, and many other parameters. The value of our study is that it provides an additional parameter, RANK expression, independently associated with prognosis in ER -BC. More importantly, we provide evidence that women, particularly postmenopausal women with RANK + ER -BC, may benefit from denosumab treatments.
To our knowledge this is the first study that concludes that RANK is a biomarker of poor prognosis, based on results from more than 700 ER -BC from three independent cohorts: - 2) ER-negative can be reflective of several subtype for example, PR+ or HER2 or a TNBC they are all ER-negative so is RANK. As example of this in the Nottingham Series were histological grade is provide to be significant for RANK expression the data reflect only 61 patient samples out of 1,054.
3) Similarly with the "vascular invasion" significance is based on 4 positive patients to make ana argument for RANK expression to be important paler in vascular invasion.
We do not draw solid conclusions about associations of RANK expression with histological grade or vascular invasion, as they are based on few cases and observed in only one of the cohorts. These results are reported but would need to be validated in additional cohorts. The conclusions of the manuscript are based on results derived from at least two/three independent collections.  Table EV1, Fig EV3A). Importantly, the conclusion that RANK expression associates with poor survival in the ER-negative BC, is confirmed in an independent collection: ER-NEGATIVE ONLY cohort (113 RANK + out of 337) (Fig 2C, green

ER-NEGATIVE ONLY (BRCA1-mutated all patients)
60 months 0.106 5) The author never reflect the true number in the text they are significance but in very few samples.
To facilitate the reading and to adjust to the journal guidelines we decided not to cite the numbers in the text, but they are shown in the figures and the Tables.
6) The menopausal status for RANK expression the Nottingham Series for ER+ BC was significant with only 24 driving the postmenopausal significance. Yet the ER-negative cohort BC postmenopausal was not statistically significance. Is not the argument that RANK is important in ER-negative postmenopausal women? Please clarify. RANK expression was not associated with survival in ER + BC (Fig EV3A), so we did not analyze associations with menopause in the ER + samples. However, additional studies on ER+ tumors will be required to draw conclusions, given the limitation of RANK detection in the NPS cohort. Data in Fig 3A (IDB) show that RANK expression associated with poor DMFS in postmenopausal patients (33 RANK + out of 117 (p=0.01)) (pink tabs in Table EV1). This was validated in the NPS (35 RANK + out of 618) (Fig EV5A and  8) Figure 1: IHC for stroma vs tumor staining for RANK was not impressive as the staining looks like it is mostly stroma and no tumor. One sample of IHC does not represent the IDB and or NPS study to draw these conclusions. None of these results are in ER negative subtypes. SFS1A/B/C has no statistical significance shown.
In the revised manuscript we have included new pictures of positive staining for RANK/RANKL (Fig 1B). These pictures show representative positive samples to prove the specificity of the staining. We have included pictures from ER-negative tumors in Fig  1B, as requested.

H-scores for tumor RANK and RANKL in the three collections are shown in Fig EV1B
(previous S1a-c). We do not intend to "compare" these variables, so no statistical analyses are performed. Figure 2: The authors state that there is no "functionality of RANK in human BC..." there are at minimum 256 published articles on RANK in BC, and more than one has done functionality studies of RANK. Fig2a qPCR is of poor resolution.

9)
Most functional studies rely on breast cancer cell lines or mouse models. To our knowledge, our study is the first to provide functional studies on RANK + BC samples derived from patients (PDXs). We have now rephrased to clarify: "Despite encouraging results in BC mouse models and cell lines (Yoldi et al. Cancer Res. 2016, 76:5857), the functional relevance of RANK signaling in clinical breast cancer remains poorly studied". Resolution of Fig EV2A (prior S2a) has been improved.
10) Figure 2D why was no RANK western run of the PDX tumors? because IHC on the PDX not impressive and is the BCM3277 least impressive by IHC, yet is very responsive to hRANKL activation of TNF/NFKB signaling. SFS2B RANK in the STG139M is low vs that of BCM-3277 is high yet IHC is the reverse. (Fig 1 and Fig EV2). As requested by the referee, we have now analyzed RANK protein expression by WB using the AF683 antibody from R&D. RANK protein expression is detected in the AB521-X PDX, which shows the highest RANK expression by IHC. This is in accordance with our experience indicating that IHC using the N1H8 is the most sensitive and specific manner to detect RANK. Fig R5. hRANK protein expression in the indicated PDX models using the AF683 antibody (R&D Systems), determined by western blot. 12) Rationale not provide as to why RNA seq was done on the PDX model with exposure to RANKL for one month.

We and others have shown that cells with low levels of RANK, detected by IHC, can be responsive to RANKL, while others with similar levels are not (see WB in Palafox et al Cancer Res 2012, Sanz-Moreno et al 2021). For this reason, selection the PDX models for the in vivo experiments was based on RANKL responsiveness (downstream RANK targets and NFKB activation) and not only on RANK expression
We have now explained in the text that the goal was to confirm the impact of constitutive activation of RANK signaling in tumor biology.
13) Fig3E is followed by "Tumor stage independently associated with three survival parameters analyzed.." refer data to Table S1. Which specific comparisons where done did the authors use the COX NPS vs CP NPS tabs? Please clarify.  (Fig EV4A).
16) If you block with RANK-Fc why did the tumor proliferate? This is never discussed. (Fig EV4C). These results suggest that the reduction of tumor cell proliferation is driven in part by the inhibition of tumor RANKL. This is in line with our previous findings (Gonzalez-Suarez,

Nature 2010), showing that RANKL inhibition decreased proliferation in mammary epithelial cells and preneoplasic lesions (where RANKL is expressed) but not in established tumors (where RANKL is not expressed). This is stated in the manuscript (page 10).
17) Section on pathways the authors state "PDX GSEA demonstrates....200 pathways differentially expresses. TS3 has allot dozens of tabs was not easy to identify, which it is please clarify and identify.
18) FigS5A TS3 "Immunity" pathways? Which comparison again dozen of tabs multiple comparison which one are the authors referring to? S5B RANKL inhibition in three PDX models which three is not clear. Fig  1H of Table  EV3. We have assigned a letter for each tab and included a color coding. The name in the tab indicates whether it includes differentially expressed genes or GSEA. The pathways that are differentially expressed are indicated in bold.

In vivo treatments with RANKL inhibitors and gene expression analyses have been done
in three independent PDX models, BCM-3277, STG139-M and AB521-X. Fig 1H. 19) RANKL is regulated by progesterone in mammary gland homeostasis whereas estradiol/opg is the inhibitor of RANK/RANKL signaling (reference 30). Should state that is in bone please clarify inference make it sound like it does so in mammary gland.
Thanks for pointing this out. OPG is a general physiological inhibitor of RANK signaling that binds to RANKL acting as a dominant negative, so it will inhibit RANKL in all the tissues. The sentence has been rewritten to clarify (page 14). Table S1 it was not clear if RANK was predicting DMFS and BCSS not clear from the data if it was refereeing to ER-or the ER+, please clarify.

20) Fig5a
Data have been reorganized to fit the guidelines of a Report. Fig 3A and Fig EV5A in Table S1 was sued to refence "survival of 15/20 years" yet on the data CNIO data was only for 12 years, please clarify, similarly please clarify which chemoresistance data is been represented, not clear which one if been used from the text or the Tables S1.
In prior Fig 5b (now Fig 3 and Fig EV5), there is not data of the TNBC (CNIO) collection,

5-year survival is represented for samples of the ERsubset of NPS, while in the ER-NEGATIVE ONLY collection 10-year survival is represented. In Table EV1 survival data for other time-points are shown. Time of follow-up varies between different collections but it is always indicated in the figures or table.
The chemotherapy regimens used in each collection are included in the manuscript text, Methods section, page 16, in the TNBC (CNIO) cohort are shown in Fig EV3D ( 22) The rationale to compare PDX data (Fig5C Table S4) with that of the postmenopausal METABRIC data sets is not clear stated at all. How does a PDX in a NSG mice comparison work?
We believe that the referee may be misinterpreting the data from Table EV4. In Table  EV4 we indicate the pathways associated with RANK expression in ER + and ERtumors (Fig 2A). In the PDXs, we identified pathways directly regulated by RANKL/RANK-Fc in each of the tumors. In The manuscript is rather interesting as it looks at the role of RANK in breast cancer and leverages the large datasets to do so -but importantly the authors have followed up with wet work to test the hypotheses that they generated. They should be commended for this. Only minor concerns are listed that may aid in the manuscript: 1) Figure 1D -  The manuscript has been reorganized to fit the format of a Report, as requested by the editors. Attending to the suggestion of the referee, the WB to test NFKB activation upon RANKL stimulation in all the models are shown together in Fig EV2C. As only three main figures are allowed they could not be included in the main figure.
3) RNAseq data -I was unable to review the data deposited to GeoDatasets. Please make a reviewer token available so that the data can be reviewed PRIOR to publication. An embargo until publication is fine, but please provide a reviewer link and token.
We apologize for the inconvenience, the token was provided in the cover letter but not in the manuscript. RNAseq results have been deposited in GEO: GSE185513 study (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185513). Token for reviewers is izcjgemgxrwrbkj.
4) GSEA -again, I'd suggest bringing this into the main portion of the manuscript. Cut some of Figure 2C and bring some of the data from table S3 in as a GSEA based figure showing the random walk.
Thanks for the suggestion. Fig 1H now FIgure 3B does not indicate in the legend or on the figure which is RANK +ve or -ve Thanks for noticing this; it has now been corrected (Fig EV3A). Figure 5 -again, split out the subtypes and do the appropriate statistical tests.

6)
Data has been reorganized to fit the guidelines of a Report. Menopausal findings are now shown in Fig 3 and  Thank you for the submission of your revised manuscript to EMBO Molecular Medicine, and please accept my apologies for the delay in getting back to you following this very busy time of the year. We have now received the enclosed reports from the three initial referees. As you will see below, while referees #2 and #3 are satisfied with the revision, referee #1 still raises a few concerns that should be addressed in a last round of revisions. In particular, the point raised by the referee regarding differences between post-menopausal vs. pre-menopausal conditions should be either addressed experimentally, convincingly discussed, or as suggested by the reviewer, panel 3E should be removed. Other concerns might be addressed in writing.
Moreover, please address the following editorial points: 1/ Main manuscript text: -Please address the queries (figure legends) from our data editors in the related Data Edited file in track changes mode. Please keep in track changes mode any new modification in the manuscript text.
-We can accommodate a maximum of 5 keywords. Am I correct to assume your keywords are: 1/ breast cancer patients-derived xenografts; 2/ER-Breast cancer; 3/menopause; 4/pharmacological RANKL inhibitors; 5/RANK-RANKL? -Material and methods: o Human samples: Please include a statement confirming that informed consent was obtained from all subjects and that the experiments conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report. o Animal experiments: please indicate the origin of the mice. o Please provide the antibody dilutions. o Statistics: please include a statement about blinding, randomization and exclusion criteria. -Data Availability Section: Thank you for depositing your datasets in a public repository. Please note that the data must be publicly available before acceptance of the manuscript.
-Please merge the Acknowledgements and Funding sections, and make sure that the information provided in the manuscript matches the information provided in the submission system. -Please update "Conflict of interest" by "Disclosure statement and competing interests". (We updated our journal's competing interests policy in January 2022 and request authors to consider both actual and perceived competing interests. Please review the policy https://www.embopress.org/competing-interests and update your competing interests if necessary.) 2/ Figures: You currently have 4 EV tables: please add the legends to the tables that should be renamed Datasets EV1-4 (please update the callouts in the manuscript text accordingly).
3/ At EMBO Press we encourage authors to provide source data for the main figures. Please see: https://www.embopress.org/page/journal/17574684/authorguide#sourcedata 4/ In the checklist, please indicate if relevant guidelines (i.e. ARRIVE) have been followed or provided. You also filled out the section about human clinical and genomic datasets deposited in public repositories, please confirm that this is correct. 5/ Thank you for providing The Paper Explained. I added minor modifications, please amend as you see fit: Problem The search for new prognostic factors and therapeutic targets has become an essential task for the individualization of breast cancer therapy. RANK signaling pathway has emerged a new target for breast cancer based on compelling preclinical evidence. RANKL inhibition prevents or attenuates mammary tumor initiation and induces tumor cell differentiation and an anti-tumorigenic immune response in established tumors. However, in clinical trials the therapeutic benefit of the RANKL inhibitor denosumab in breast cancer, beyond its bone related effects, is unclear. Given the heterogeneity of breast cancer, a better understanding of RANK biology is needed to identify the patients who may benefit from denosumab.

Results
Here, we report the expression patterns of RANK and RANKL proteins in more than 2000 breast tumor samples from independent collections, together with functional studies in breast cancer patient-derived xenografts (PDXs). Our results demonstrate that RANK in tumors cells constitutes a new independent biomarker of poor prognosis in patients with ER-tumors and in postmenopausal women. Accordingly, RANKL inhibition improves response to chemotherapy in ER-BC PDXs, reducing recurrence, and show a greater therapeutic effect in ER-BC tumors growing in postmenopausal conditions. The distinct biology of RANK signaling according to ER expression and menopause enlighten these paradoxical results: RANK activation increases in tumors after menopause and regulates tumor cell metabolism in ER-disease. Impact Our findings identify RANK as a new biomarker of poor prognosis in postmenopausal women with ER-breast tumors. These results will help to identify breast cancer patients who can benefit from denosumab in a personalized therapeutic strategy. 6/ As part of the EMBO Publications transparent editorial process initiative (see our Editorial at http://embomolmed.embopress.org/content/2/9/329), EMBO Molecular Medicine will publish online a Review Process File (RPF) to accompany accepted manuscripts. This file will be published in conjunction with your paper and will include the anonymous referee reports, your point-by-point response and all pertinent correspondence relating to the manuscript. Let us know whether you agree with the publication of the RPF and as here, if you want to remove or not any figures from it prior to publication. Please note that the Authors checklist will be published at the end of the RPF.
I look forward to receiving your revised manuscript.

Lise Roth
Lise Roth, PhD Senior Editor EMBO Molecular Medicine ***** Reviewer's comments ***** Referee #1 (Remarks for Author): In this revised manuscript, the authors changed format to a Report, so as to bypass the need for mechanistic insight required for a full paper.
The authors show that RANKL inhibitions cooperate with chemotherapy (docetaxel) to suppress ER-negative/RANK+ PDX growth and that RANK tumor expression associates with poor survival in postmenopausal patients.
They addressed some concerns but not others: First, and most importantly, the authors show that RANKL inhibition attenuates tumor growth of a RANK+ ER-BC PDX in ovariectomized mice (postmenopausal conditions - Fig. 3E in revised manuscript) -and that this inhibition is stronger than that seen in a similar experiment in pre-menopausal mice ( Fig. 2F ). However, these experiments were not done side-by-side and may therefore reflect experiment-to-experiment (batch-to-batch) variations rather than a qualitative difference. Notably, in AB521-X cells -treatment accelerated growth in Fig 2F. Is this reproducible in independent biological replicas? How do the authors explain this response in these cells as opposed to the other lines? Or are the two groups (red -blue) switched?
The Reviewer noted in the initial review: " Fig. 6 shows the results in ovariectomized NSG mice. To demonstrate specificity, the authors should show side-by-side the effect of RANKL inhibition alone in normal mice as shown in Fig. 4a." The authors response "We decided to maintain the results from premenopausal and postmenopausal conditions in separate figures to facilitate the comprehension of the manuscript." -is beside the point as the request was to show the post-menopausal experiment side-by-side with a (new/additional) premenopausal experiment. This is critical because while the difference for AB521-X cells is dramatic -but is it real (see above)?the difference for the other line -BCM-3277 -is moderate (P=0.003 vs P=0.011) and may be due to differences in other experimental conditions/variables (e.g. drug activity, number of cells injected etc).
These are tough experiments and I appreciate the difficulty in repeating them as this stage. However, can the authors justify why they are convinced the differences between post-menopausal vs pre-menopausal conditions are real without performing the experiments side-by-side? If not, they may remove Fig. 3E -and highlight the other results in this manuscript.
-The authors response to the question " Does RANK-shRNA have similar effect as RANKL-inhibitors?" -that "RANKL inhibitors will have a systemic effect", may be correct -but still the question whether denosumab or denosumab -DTX inhibits growth of cells in vitro -and whether such inhibition is seen with shRNA or RNAi (or CRISPR/CAS) are very informative. If RANKLinhibitors (plus/minus DTX) do not have any effects in vitro -that would strengthen the idea that they act on the microenvironment. If, on the other hand -these drugs do suppress growth in vitro -the question is whether shRNA/RNAidepletion (or crispr/cas9 KO) would have a similar effect -because otherwise, these inhibitors may have off target effects.
However -this analysis may be performed as part of future followup. The issue above regarding post-menopausal sensitivity is more critical to this manuscript.
Other issues - Fig 2G bottom right -what cells are these? How is it different than bottom left? -Abstract In the revised Abstract -the definition of denosumab has been deleted from the first sentence (which appeared in the original Abstract). It should be defined again as "Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients is unclear, ...". ***** Reviewer's comments ***** Referee #1 (Remarks for Author): In this revised manuscript, the authors changed format to a Report, so as to bypass the need for mechanistic insight required for a full paper.
The authors show that RANKL inhibitions cooperate with chemotherapy (docetaxel) to suppress ER-negative/RANK+ PDX growth and that RANK tumor expression associates with poor survival in postmenopausal patients.
They addressed some concerns but not others: First, and most importantly, the authors show that RANKL inhibition attenuates tumor growth of a RANK+ ER-BC PDX in ovariectomized mice (postmenopausal conditions - Fig. 3E in revised manuscript) -and that this inhibition is stronger than that seen in a similar experiment in premenopausal mice ( Fig. 2F ). However, these experiments were not done side-by-side and may therefore reflect experiment-to-experiment (batch-to-batch) variations rather than a qualitative difference. Notably, in AB521-X cells -treatment accelerated growth in Fig 2F. Is this reproducible in independent biological replicas? How do the authors explain this response in these cells as opposed to the other lines? Or are the two groups (red -blue) switched?
The Reviewer noted in the initial review: " Fig. 6 shows the results in ovariectomized NSG mice. To demonstrate specificity, the authors should show side-by-side the effect of RANKL inhibition alone in normal mice as shown in Fig.  4a." The authors response "We decided to maintain the results from premenopausal and postmenopausal conditions in separate figures to facilitate the comprehension of the manuscript." -is beside the point as the request was to show the post-menopausal experiment side-by-side with a (new/additional) pre-menopausal experiment. This is critical because while the difference for AB521-X cells is dramatic -but is it real (see above)? -the difference for the other line -BCM-3277 -is moderate (P=0.003 vs P=0.011) and may be due to differences in other experimental conditions/variables (e.g. drug activity, number of cells injected etc). growth in vitro -the question is whether shRNA/RNAi-depletion (or crispr/cas9 KO) would have a similar effect -because otherwise, these inhibitors may have off target effects. However -this analysis may be performed as part of future followup. The issue above regarding post-menopausal sensitivity is more critical to this manuscript.
We agree with the referee that it will be informative to compare inhibition of the receptor and the ligand. However, as explained in the previous point by point, denosumab is a monoclonal antibody against human RANKL. Therefore would only act in vitro in models where RANKL is expressed, such as STG139-M. The other models and most breast cancer cell lines express the receptor but not the ligand. It cannot be discarded that the culture media/serum may act as a source of RANKL (most probably not human RANKL).
Other issues - Fig 2G bottom right -what cells are these? How is it different than bottom left?
It is the same model, STG139, and the same experiment. Bottom left shows tumor growth/regression during DTX/RANKL-inhibitor treatment. Bottom right shows the tumor relapse in these same mice after interruption of the combined treatment. We have included a sentence in the methods explaining that treatment was interrupted when tumors regress below 3 mm of diameter. In the docetaxel-only arm, despite treatment could not be interrupted tumors continued growing.
-Abstract In the revised Abstract -the definition of denosumab has been deleted from the first sentence (which appeared in the original Abstract). It should be defined again as "Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients is unclear, ...". Second sentece should start with "Aiming to select patients who may benefit from denosumab, we hereby analyzed ...." Second/subsequent sentences -when referring to "RANK and RANKL expression" -the author should specify what they mean -e.g. "RANK and RANKL expression by immunostaining"; "RANK and RANKL protein expression"(as per last sentence) The Abstract starts with the therapeutic benefit of denosumab -but this drug is not mentioned in the rest of the Abstract. It should be used in the middle of the Abstract and surely in the end -or more specifically state "RANKL inhibitors RANK-Fc or denosumab....." 8th Feb 2023 2nd Revision -Editorial Decision 8th Feb 2023 Dear Dr. Gonzalez-Suarez, Thank you for the submission of your revised manuscript to EMBO Molecular Medicine. We have now received the report from the referee who assessed the final revisions. As you will see, this referee is now supportive of publication, and I am therefore pleased to inform you that your manuscript is accepted for publication and is now being sent to our publisher to be included in the next available issue of EMBO Molecular Medicine.
Please read below for additional IMPORTANT information regarding your article, its publication and the production process. The authors have revised the manuscript in response to critic adequately Referee #2 (Remarks for Author): The author have address all the concerns raised. *** *** *** IMPORTANT INFORMATION *** *** ***