Abstract

For many patients with breast cancer, symptomatic bone metastases appear after years of latency. How micrometastatic lesions remain dormant and undetectable before initiating colonization is unclear. Here, we describe a mechanism involved in bone metastatic latency of oestrogen receptor-positive (ER+) breast cancer. Using an in vivo genome-wide short hairpin RNA screening, we identified the kinase MSK1 as an important regulator of metastatic dormancy in breast cancer. In patients with ER+ breast cancer, low MSK1 expression associates with early metastasis. We show that MSK1 downregulation impairs the differentiation of breast cancer cells, increasing their bone homing and growth capacities. MSK1 controls the expression of genes required for luminal cell differentiation, including the GATA3 and FOXA1 transcription factors, by modulating their promoter chromatin status. Our results indicate that MSK1 prevents metastatic progression of ER+ breast cancer, suggesting that stratifying patients with breast cancer as high or low risk for early relapse based on MSK1 expression could improve prognosis.

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Acknowledgements

We thank V. Raker for manuscript editing and IRB Barcelona Functional Genomics (J.I. Pons and D. Fernández), Histopathology (N. Prats), Advanced Digital Microscopy (J. Colombelli) and Flow Cytometry (J. Comas) Core Facilities for assistance. S.Gawrzak, L.R., E.J.A. and K.S. were supported by La Caixa PhD fellowships. J.M.C. received a fellowship from ‘PhD4MD’, a Collaborative Research Training Programme for Medical Doctors (IDIBAPS, August Pi i Sunyer Institute for Biomedical Research and IRB Barcelona), and partial funding by the ISCIII (project: II14/00019). S.Gregorio, C.F.-P. and A.B. were funded by the Spanish Government (MINECO-Formación de personal Investigador). J.U. is an AECC (Asociación Española Contra el Cáncer) Fellow. D.K. was co-funded by FP7 Marie Curie Actions (COFUND program; grant agreement no. IRBPostPro2.0 600404); A.P. was supported by Susan Komen Foundation, SEOM, BBVA Foundation and the ISCIII–PI13/01718. J. Albanell. was supported by ISCIIi/FEDER under projects CIBERONC, PIE15/00008, PI15/00146 and Generalitat de Catalunya (2014 SGR 740). R.R.G., S.A.-B, J. Arribas. and A.R.N. are supported by the Institució Catalana de Recerca i Estudis Avançats. Support and structural funds were provided by the Generalitat de Catalunya (2014 SGR 535) to R.R.G. and A.R.N., and by the BBVA Foundation, the ISCIII/FEDER-CIBERONC, Worldwide Cancer Research (grant 15–1316), the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds (CIBEREONC and SAF2016-76008-R) to R.R.G.

Author information

Author notes

    • Anna Arnal-Estapé

    Present address: Department of Pathology, Yale University School of Medicine, Yale, CT, USA

Affiliations

  1. Oncology Program, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain

    • Sylwia Gawrzak
    • , Lorenzo Rinaldi
    • , Sara Gregorio
    • , Enrique J. Arenas
    • , Fernando Salvador
    • , Jelena Urosevic
    • , Cristina Figueras-Puig
    • , Ivan del Barco Barrantes
    • , Juan Miguel Cejalvo
    • , Marc Guiu
    • , Aikaterini Symeonidi
    • , Anna Bellmunt
    • , Daniela Kalafatovic
    • , Anna Arnal-Estapé
    • , Esther Fernández
    • , Barbara Müllauer
    • , Rianne Groeneveld
    • , Konstantin Slobodnyuk
    • , Angel R. Nebreda
    • , Salvador Aznar Benitah
    •  & Roger R. Gomis
  2. CIBERONC, Madrid, Spain

    • Jelena Urosevic
    • , Federico Rojo
    • , Marc Guiu
    • , Joaquín Arribas
    • , Ana Lluch
    • , Violeta Serra
    • , Joan Albanell
    •  & Roger R. Gomis
  3. Cancer Research Program, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain

    • Federico Rojo
    • , Ana Rovira
    •  & Joan Albanell
  4. Pathology Department, IIS-Fundación Jimenez Diaz, Madrid, Spain

    • Federico Rojo
  5. Translational Genomics and Targeted Therapeutics, Institut d’Investigacions Biomèdiques Pi i Sunyer-IDIBAPS, Barcelona, Spain

    • Juan Miguel Cejalvo
    • , Montse Muñoz
    •  & Aleix Prat
  6. Experimental Therapeutics, Vall d’Hebron Insitute of Oncology, Barcelona, Spain

    • Marta Palafox
    •  & Violeta Serra
  7. Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain

    • Antonio Berenguer-Llergo
    •  & Camille Stephan-Otto Attolini
  8. Department of Oncology, Vall d’Hebrón University Hospital, Barcelona, Spain

    • Cristina Saura
  9. Vall d’Hebron Institute of Oncology, Barcelona, Spain

    • Cristina Saura
    • , Joaquín Arribas
    •  & Javier Cortes
  10. Universitat Autònoma de Barcelona, Bellaterra, Spain

    • Joaquín Arribas
  11. ICREA, Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

    • Joaquín Arribas
    • , Angel R. Nebreda
    • , Salvador Aznar Benitah
    •  & Roger R. Gomis
  12. Ramon y Cajal University Hospital, Madrid, Spain

    • Javier Cortes
  13. Medical Oncology Service, Hospital del Mar, Barcelona, Spain

    • Ana Rovira
    •  & Joan Albanell
  14. Department of Oncology, Hospital Clinic de Barcelona, Barcelona, Spain

    • Montse Muñoz
    •  & Aleix Prat
  15. Department of Oncology and Hematology, Hospital Clínico Universitario, Valencia, Spain

    • Ana Lluch
  16. University of Valencia, Valencia, Spain

    • Ana Lluch
  17. INCLIVA, Instituto de Investigación Sanitaria, Valencia, Spain

    • Ana Lluch
  18. Universitat Pompeu Fabra, Barcelona, Spain

    • Joan Albanell
  19. Universitat de Barcelona, Barcelona, Spain

    • Roger R. Gomis

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Contributions

S.Gawrzak designed and performed the experiments and analysed the data. L.R. performed the ChIP–seq experiments and analysed the data. E.J.A. F.S., J.U., C.F.-P., I.d.B.B., B.M., D.K., R.G., S.Gregorio, K.S., A.B., E.F. and M.G. contributed to the experiments. A.A.-E. isolated DBM cell line. F.R., A.L., A.R., M.M., J.M.C., A.P. and J. Albanell. contributed to building and analysing the tissue micro-array. M.P., C.S., J. Arribas., J.C. and V.S. contributed the PDX generation and analyses. A.B.-L. and C.S.-O.A. analysed the public transcriptomic data sets of the breast cancer human samples and statistics. S.A.-B. and A.R.N. participated in data analyses. R.R.G. conceived the project, designed and analysed the data, and supervised the overall project. S.Gawrzak and R.R.G. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Roger R. Gomis.

Integrated supplementary information

  1. Figure Supplementary 1 Characterization of ER+ breast cancer tumour mass dormancy model suitable for shRNA screen.

    (a) Kaplan-Meier analysis of bone metastasis-free survival in a DBM cells xenograft (n = 12 mice). (b) Representative bioluminescence images showing bone metastasis progression in DBM xenograft (top), and quantification of BLI signal in bone metastatic lesion (n = 5 limbs with metastatic lesions) (bottom). (c) Kaplan–Meier analysis of bone metastasis-free survival in a BoM2 cell xenograft (n = 17 mice). (d) Representative bioluminescence images showing bone metastasis progression in BoM2 xenograft (top), and quantification of bone metastatic lesion BLI signal (bottom) (n = 10 limbs with metastatic lesions). (e) CGH analysis of DBM and parental cells. Genetic gains and losses in DBM cells, for each chromosome, are depicted with red and green color bars respectively. (f) Quantification of ex vivo BLI signal in bones isolated during homing (n = 8 limbs), latency (n = 7 limbs), metastasis (n = 8 limbs). Two-tailed Mann Whitney test. (g) Quantification of osteolythic area from X-ray scans in bones isolated during homing (n = 3 limbs) and metastasis (n = 5 limbs). Two-tailed Mann–Whitney test. Experiment was performed once. (h) Analysis of bone samples with detected micrometastatic lesions or single DTC by means of human ER_ IHC during homing (i) Quantification of phospho-P38-positive cells in latent lesions (n = 20 ROIs from 4 limbs) and metastatic lesions (n = 25 ROIs from 3 limbs). Two-tailed Mann-Whitney test (left). Representative image of phospho P38 staining in lesions during latency or metastatic phase (right). Scale bar, 50 µm. (j) Quantification of phospho-SMAD2-positive cells in latent lesions (n = 21 ROIs from 4 limbs) and metastatic lesions (n = 42 ROIs from 3 limbs). Two-tailed Mann-Whitney test. Experiment was performed once. Panels (b) and (d) show data as mean ± SEM, and panels (f), (g) and (i-j), as whisker plots: mid-line, median; box, 25 – 75 percentile; whisker, min-max. ns (nonsignificant) P > 0.05, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001. Statistics source data and P values are provided in Supplementary Table 9.

  2. Supplementary Figure 2 Clinical and in vivo validation of MSK1 as regulator of homing, tumor mass dormancy and metastasis in ER+ breast cancer.

    (a) In vitro cell growth curve of shControl and shMSK1 DBM cells. Mixed-effect linear model in which the response was square-root transformed, n = 3 independent experiments were modeled as random effect and group, time point and their interaction were included as explanatory variables. (b) MSK1 KO generation by CRISPR/Cas9 genome editing. Five target sequences were located in exons 5, 6, 8, 9 or 13 (green), which overlap with residues critical for MSK1 catalytic and kinase activity (violet circles). The 20-nt target sequence in exon 5 (blue);the 3-nt PAM sequence(red); guide RNA is composed of complementary target sequence. The cleavage site is located between the 3rd and 4th nucleotides upstream from PAM (arrows). (c) Representative bioluminescence images showing bone metastasis progression of shControl and shMSK1 DBM cells. Experiment was repeated two times independently with similar results. (d) Bone metastasis incidence of ZR-75.1 cells infected with shControl (n=14 limbs) and shMSK1#1 (n=14 limbs) (left). Western blot analysis of MSK1, MSK2 and tubulin in ZR-75.1 cells (right). Western blot was repeated two times independently with similar results (e) Time-matched quantification of in vivo BLI signal in hind limbs during homing, latency and metastasis after injection of DBM shControl (n=4 limbs), shMSK1#1 (n=12 limbs) or shMSK1#2 (n=24 limbs). Two-tailed Wald tests from a linear model in which the response was log-transformed and group, status and their interaction were included as explanatory variables. (f) Time-matched quantification of apoptotic signal (Z-DEVD) normalized to lesion size (LUC) in hind limbs during homing, latency, metastasis after injection of DBM shControl (nh=6 limbs, nl=4 limbs, nm=3 limbs), shMSK1#1 (nh=6 limbs, nl=4 limbs, nm=4 limbs) or shMSK1#2 (nh=7 limbs, nl=4 limbs, nm=4 limbs). Two-tailed Wald test from a linear model in which the response was log-transformed and group, status and their interaction were included as explanatory variables. (g) Analysis of bone samples with detected metastatic lesions or single DTC by means of human ERα IHC (n=25 ROIs from 5 limbs). Panel (a) show data as mean ± SEM from three independent experiments (d,f) show data as whisker plots: mid-line, median; box, 25 – 75 percentile; whisker, min-max. ns (nonsignificant) P>0.05, * P≤0.05, ** P≤0.01, *** P≤0.001. Schaffer method was used for P-value correction when three or more groups are compared. Statistics source data P values are provided in Supplementary Table 9. Unprocessed original scans of blots are shown in Supplementary Fig. 8.

  3. Supplementary Figure 3 Angiogenesis in vitro and in vivo is unaffected by MSK1 levels in breast cancer cells.

    (a) mRNA levels fold change of angiogenesis-associated genes ANGPT1, ANGPT2, ANGPTL4 and VEGF in DBM, cells upon MSK1 downregulation, n = 4. Two-tailed Wald test from a linear model in which group was included as explanatory variable. (b) mRNA levels fold change of angiogenesis-associated genes ANGPT1, ANGPT2, ANGPTL4 and VEGF in DBM, cells upon MSK1 knockout, n = 4. Two-tailed Student’s t-test. (c) Quantification of in vitro endothelial HUVEC cell tube formation assay upon treatment with conditioned medium derived from shControl, shMSK1#1 and shMSK1#2 DBM cells, n = 3. Multiple t-test across points comparing each condition to control (d) Quantification of in vitro endothelial HUVEC cell tube formation assay upon treatment with conditioned medium derived from wild-type (WT) and MSK1 knockout (KO) DBM cells, n = 3. Multiple t-test across points comparing each condition to control (e) Quantification of number of CD31 positive vessels in metastatic lesions formed by shControl (n = 12), shMSK1#1 (n = 13) and shMSK1#2 (n = 18) DBM cells (left). Representative images of CD31 staining (right). Scale bar, 50 µm. Two-tailed Wald test from a linear model in which group was included as explanatory variable. Experiment was performed once (f) Quantification of EdU-positive cells in latent lesions formed by DBM shControl (n = 19 ROIs from 3 limbs) and shMSK1#2 cells (n = 19 ROI from 3 limbs) and metastatic lesions formed by DBM shControl (n = 22 ROIs from 2 limbs) and shMSK1#2 (n = 11 ROI from 2 limbs). Two-tailed Mann–Whitney test. (g) Representative image of EdU staining in lesions during latency or metastatic phase. Experiment was performed once. Panels (a-d) show data as mean ± SEM from three biologically independent samples each of which is an average from three technical replicates and panel (e-g) shows data as whisker plots: mid-line, median; box, 25 – 75 percentile; whisker, min-max. ns (nonsignificant) P > 0.05, * P ≤ 0.05, ** P ≤ 0.01. Schaffer method was used for P-value correction when three or more groups are compared. Statistics source data and P values are provided in Supplementary Table 9.

  4. Supplementary Figure 4 MSK1 is dispensable for in vitro survival in hypoxia, adhesion and migration, but inhibits tumor initiation.

    (a) Flow-cytometry quantification of apoptosis and cell death after 72 h of hypoxic conditions, n = 4. Representative plots of flow cytometric analysis of annexin V and PI staining in cells infected with shControl or shMSK1 are shown. Apoptotic cells, top-right quadrants; dead cells, top-left quadrants. Two-tailed Wald test from a linear model in which the response was log-transformed and group, status and their interaction were included as explanatory variables. (b) Cell adhesion to collagen, fibronectin and matrigel in DBM cells infected with shControl or shMSK1, n = 3. Two-tailed Wald test from a linear model in which the response was log-transformed and group was included as explanatory variable. (c) Cell migration of shControl or shMSK1 DBM cells, n = 3. Two-tailed Wald test from a linear model in which the response was log-transformed and group was included as explanatory variable. (d) Cell invasion of shControl or shMSK1 infected DBM cells, n = 3. Two-tailed Wald test from a linear model in which the response was log-transformed and group was included as explanatory variable. (e) mRNA levels fold change of CXCL12 upon MSK1 downregulation (n = 5) or knockout (n = 4). Wald test from a linear model in which group was included as explanatory variable. (f) Quantification of CXCR4 positive cells upon downregulation and knockout of MSK1, n = 8. Two-tailed Wald tests from a linear model in which the response was transformed (power 4) and group was included as explanatory variable. (g) Representative images of CXCR4 and MSK1 staining of shControl, shMSK1#1, shMSK1#2, WT and KO DBM cells. Scale bar, 50 µm. Experiment was performed once. (h) Fold-change of oncospheres in 3D in DBM cells upon 72-h treatment with MSK inhibitor (10 µM) (left), n = 5. Representative image of 3D oncospheres treated with DMSO (control) or MSK1 inhibitor (right). Scale bar, 500 µm. Two-tailed Wald test from a linear model in which the response was log-transformed and group was included as explanatory variable. (i) Fold-change of second-generation oncosphere formation in DBM cells with (n = 4) or without (n = 6) p38 inhibitor PH-797804 (2 µM). Two-tailed Student’s t-test test. (j) mRNA levels fold change of p38 and MSK1 genes, upon p38 depletion, n = 3. Two-tailed Student’s t-test. Panels (a-f) and (h-j) show data as mean ± SEM from minimum three biologically independent samples. ns (nonsignificant), * P ≤ 0.05, ** P ≤ 0.01. Schaffer method was used for P-value correction when three or more groups are compared. Statistics source data and P values are provided in Supplementary Table 9.

  5. Supplementary Figure 5 MSK1 loss decreases the expression of luminal genes in ER+ breast cancer, but maintains the luminal subtype.

    (a) Gene set enrichment analysis (GSEA) plots of a subset of the luminal (top) and basal (bottom) gene sets adapted from (Neve et al Cancer Cell 2006 and Charafe-Jauffret et al Oncogene 2006) and their correlation with MSK1 expression in ER+ breast cancer patients (n = 370 patient samples). NES, normalized enrichment score; NOMp, nominal P value (b) Representative images of oestrogen receptor (ERα) and MSK1 immunohistochemistry in metastatic lesions upon MSK1 knockdown and knockout. Percentage of positive cells for each lesion was quantified from shControl (n = 6), shMSK1#1 (n = 4), shMSK1#2 (n = 4), MSK1 WT (n = 3) and MSK1 KO (n = 3) biologically independent samples (lesions), and at least 8 × 102 cells were assessed. Scale bar, 50 µm. (c) Heatmap of the log2 transformed gene expression for PAM50 signatures in T47D, DBM, DBM WT and DBM MSK1 KO cells. Green and red colors represent higher and lower expression levels, respectively. The samples are further categorized into molecular subtype. (d) Proliferation assay of DBM WT and DBM MSK1 KO cells treated with increasing doses of tamoxifen, n = 3. Panels (b and d) and show data as mean ± SEM from three biologically independent samples. Statistics source data are provided in Supplementary Table 9.

  6. Supplementary Figure 6 MSK1 loss impairs luminal gene expression and increases metastatic traits.

    (a) Fold-change of mRNA levels of luminal genes in DBM MSK1 WT or MSK1 KO cells, n = 3. Two-tailed Student’s t-test. (b) Images of MSK1 and FOXA1 immunohistochemistry in overt-metastasis–bearing DBM shControl hind limbs (n = 3 limbs per group) or DBM shMSK1 hind limbs (n = 2 limbs per group). Scale bar, 50 μm. Experiment was performed once. (c) Representative images of ERα immunohistochemistry in PDX tumours. Percentage of positive cells for each PDX was quantified from two biologically independent samples (passages), and at least 4 × 103 cells were assessed. Scale bar, 50 μm. (d) Fold-change of mRNA levels of luminal genes in DBM MSK1-downregulated cells upon ectopic expression of (OE) of FOXA1 (top), GATA3 (middle) or combination of both (bottom), n = 3. Two-tailed Wald test from a linear model in which group, OE and their interaction were included as explanatory variables. Comparisons where made across each gene response comparing control versus the indicated overexpression condition. (e) Survival analysis representing the proportion of bone metastasis recurrence-free patients stratified according to MSK2 mRNA levels in ER+ breast cancer patient samples (low, n = 65; medium, n = 64; high, n = 35). Two-tailed Wald test. HR(<3y)=1.34; CI[0.47, 3.79], p=0.58 (f) Western blot analysis of MSK1, MSK2 and tubulin in MSK1 WT and KO cells upon downregulation of MSK2. Experiment was performed two times with similar results. (g) Fold-change of mRNA levels of luminal genes in DBM MSK1 KO upon MSK1 downregulation, n = 3. Statistical significance was tested by Wald test from a linear model in which group was included as explanatory variable. Panels (a), (d) and (g) show data as mean ± SEM from 3 biologically independent samples, each of which is an average from three technical replicates. ns, non-significant; P > 0.05, *P ≤ 0.05 and ****P ≤ 0.0001. Schaffer method was used for p-value correction when three or more groups are compared. Statistics source data and P values are provided in Supplementary Table 9. Unprocessed original scans of blots are shown in Supplementary Fig. 8.

  7. Supplementary Figure 7 MSK1 acts at promoters of luminal transcription factors by modulating histone H3 phosphorylation of S10 and S28 residues and histone H3 acetylation of K9 and K27 residues.

    (a) Correlation of MSK1 in ER+ patient cohort (n = 370). Dashed line indicates cut-off of 5% FDR, and positively- or negatively-correlated genes are marked in red. (b) ChIP-seq coverage-depth of H3K9ac, H3K27ac, H3K9me3 and H3K27me3 peaks in DBM shControl or shMSK1 cells. (c) ChIP-seq coverage depth of HK9me3 and H3K27me3 around TSS of luminal (n = 601) and basal genes (n = 873) in DBM shControl and shMSK1 cells. Two-tailed paired Student´s t-test. (d) ChIP-seq coverage depth of H3S10p, H3S28p at promoters of luminal transcription factors FOXA1 and GATA3. Zoom in from (7e) (e) ChIP-seq coverage depth of H3K9ac, H3K27ac at promoters of luminal transcription factors FOXA1 and GATA3. Zoom in from (7a). (f) Violin plots showing normalized peak count of input, H3K9me3 and H3K27me3 in promoters of genes bound by MSK1, n = 834. Two-tailed Paired Student´s t-test. ChIP-seq experiments were performed once. Panels (c and e) show data as violin plots that indicate the distribution of data points: mid-point, median; vertical lines 95% confidence interval ns (non-significant) P > 0.05, * P ≤ 0.05, *** P ≤ 0.001. P values are provided in the Supplementary data Supplementary Table 9.

  8. Supplementary Figure 8 Unprocessed Western Blots.

    Unprocessed Western blots from key blots in Fig: 4a, 4b, 5c and 5g, and, Supplementaty Fig: 2e, 6f. Dashed line boxes indicate the cropped areas shown in the figures.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–8 and Supplementary Table titles and legends.

  2. Life Sciences Reporting Summary

  3. Supplementary Table 1

    List of differentially expressed genes between T47D (parental) and DBM (derivative) cell lines.

  4. Supplementary Table 2

    Deconvolution results of shRNA screen.

  5. Supplementary Table 3

    List of genes with >1.5-fold enrichment.

  6. Supplementary Table 4

    CRISPR–Cas9 genome editing efficiency.

  7. Supplementary Table 5

    Luminal and basal gene lists used for GSEA.

  8. Supplementary Table 6

    PDX tumor details.

  9. Supplementary Table 7

    GSEA of genes significantly correlated with MSK1 in BC primary tumours.

  10. Supplementary Table 8

    Materials and reagents.

  11. Supplementary Table 9

    Statistics source data.