Abstract
How dysregulated liquid–liquid phase separation (LLPS) contributes to the oncogenesis of female triple-negative breast cancer (TNBC) remains unknown. Here we demonstrate that phosphorylated histone deacetylase 6 (phospho-HDAC6) forms LLPS condensates in the nuclei of TNBC cells that are essential for establishing aberrant chromatin architecture. The disordered N-terminal domain and phosphorylated residue of HDAC6 facilitate effective LLPS, whereas nuclear export regions exert a negative dominant effect. Through phase-separation-based screening, we identified Nexturastat A as a specific disruptor of phospho-HDAC6 condensates, which effectively suppresses tumor growth. Mechanistically, importin-β interacts with phospho-HDAC6, promoting its translocation to the nucleus, where 14-3-3θ mediates the condensate formation. Disruption of phospho-HDAC6 LLPS re-established chromatin compartments and topologically associating domain boundaries, leading to disturbed chromatin loops. The phospho-HDAC6-induced aberrant chromatin architecture affects chromatin accessibility, histone acetylation, RNA polymerase II elongation and transcriptional profiles in TNBC. This study demonstrates phospho-HDAC6 LLPS as an emerging mechanism underlying the dysregulation of chromatin architecture in TNBC.
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Data availability
Hi-C, ChIP-seq, ATAC-seq and RNA-seq data that support the findings of this study were deposited to the Gene Expression Omnibus under accession codes GSE254213, GSE253743 and GSE253744. The human breast cancer data were derived from TCGA Research Network (http://cancergenome.nih.gov/) and METABRIC dataset. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
Code availability
No unique code was developed for this study.
References
Shi, Y., Jin, J., Ji, W. & Guan, X. Therapeutic landscape in mutational triple negative breast cancer. Mol. Cancer 17, 99 (2018).
Garrido-Castro, A. C., Lin, N. U. & Polyak, K. Insights into molecular classifications of triple-negative breast cancer: improving patient selection for treatment. Cancer Discov. 9, 176–198 (2019).
Derakhshan, F. & Reis-Filho, J. S. Pathogenesis of triple-negative breast cancer. Annu. Rev. Pathol. 17, 181–204 (2022).
Kim, C. et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell 173, 879–893 (2018).
Shu, S. et al. Response and resistance to BET bromodomain inhibitors in triple-negative breast cancer. Nature 529, 413–417 (2016).
Mehta, S. & Zhang, J. Liquid–liquid phase separation drives cellular function and dysfunction in cancer. Nat. Rev. Cancer 22, 239–252 (2022).
Ahn, J. H. et al. Phase separation drives aberrant chromatin looping and cancer development. Nature 595, 591–595 (2021).
Lu, B. et al. Pharmacological inhibition of core regulatory circuitry liquid–liquid phase separation suppresses metastasis and chemoresistance in osteosarcoma. Adv. Sci. 8, e2101895 (2021).
Chiu, Y.-P. et al. Liquid–liquid phase separation and extracellular multivalent interactions in the tale of galectin-3. Nat. Commun. 11, 1229 (2020).
Shi, B. et al. Phase separation of Ddx3xb helicase regulates maternal-to-zygotic transition in zebrafish. Cell Res. 32, 715–728 (2022).
Sadar, M. D. Discovery of drugs that directly target the intrinsically disordered region of the androgen receptor. Expert Opin. Drug Discov. 15, 551–560 (2020).
Yasuda, S. et al. Stress- and ubiquitylation-dependent phase separation of the proteasome. Nature 578, 296–300 (2020).
Valenzuela-Fernández, A., Cabrero, J. R., Serrador, J. M. & Sánchez-Madrid, F. HDAC6: a key regulator of cytoskeleton, cell migration and cell–cell interactions. Trends Cell Biol. 18, 291–297 (2008).
Banik, D. et al. HDAC6 plays a noncanonical role in the regulation of antitumor immune responses, dissemination, and invasiveness of breast cancer. Cancer Res. 80, 3649–3662 (2020).
Zeleke, T. Z. et al. Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer. Nat. Cancer 4, 257–275 (2023).
Dowling, C. M. et al. Multiple screening approaches reveal HDAC6 as a novel regulator of glycolytic metabolism in triple-negative breast cancer. Sci. Adv. 7, eabc4897 (2021).
Pulya, S. et al. HDAC6 as privileged target in drug discovery: a perspective. Pharmacol. Res. 163, 105274 (2021).
Kawaguchi, Y. et al. The deacetylase HDAC6 regulates aggresome formation and cell viability in response to misfolded protein stress. Cell 115, 727–738 (2003).
Mazzetti, S. et al. Phospho-HDAC6 gathers into protein aggregates in Parkinson’s disease and atypical parkinsonisms. Front. Neurosci. 14, 624 (2020).
Tellier, M. et al. CDK12 globally stimulates RNA polymerase II transcription elongation and carboxyl-terminal domain phosphorylation. Nucleic Acids Res. 48, 7712–7727 (2020).
Nativio, R. et al. An integrated multi-omics approach identifies epigenetic alterations associated with Alzheimer’s disease. Nat. Genet. 52, 1024–1035 (2020).
Padeken, J., Methot, S. P. & Gasser, S. M. Establishment of H3K9-methylated heterochromatin and its functions in tissue differentiation and maintenance. Nat. Rev. Mol. Cell Biol. 23, 623–640 (2022).
Shen, M. et al. Tinagl1 suppresses triple-negative breast cancer progression and metastasis by simultaneously inhibiting integrin/FAK and EGFR signaling. Cancer Cell 35, 64–80 (2019).
Nogués, L. et al. G protein-coupled receptor kinase 2 (GRK2) promotes breast tumorigenesis through a HDAC6–Pin1 axis. EBioMedicine 13, 132–145 (2016).
Bhat-Nakshatri, P. et al. Breast cancer cell detection and characterization from breast milk-derived cells. Cancer Res. 80, 4828–4839 (2020).
Bergman, J. A. et al. Selective histone deacetylase 6 inhibitors bearing substituted urea linkers inhibit melanoma cell growth. J. Med. Chem. 55, 9891–9899 (2012).
Lee, J.-H. et al. Development of a histone deacetylase 6 inhibitor and its biological effects. Proc. Natl Acad. Sci. USA 110, 15704–15709 (2013).
Huang, X. et al. 14-3-3 proteins are potential regulators of liquid–liquid phase separation. Cell Biochem. Biophys. 80, 277–293 (2022).
Kuersten, S., Ohno, M. & Mattaj, I. W. Nucleocytoplasmic transport: Ran, beta and beyond. Trends Cell Biol. 11, 497–503 (2001).
Li, Y. et al. The structural basis for cohesin–CTCF-anchored loops. Nature 578, 472–476 (2020).
Nwosu, Z. C., Ebert, M. P., Dooley, S. & Meyer, C. Caveolin-1 in the regulation of cell metabolism: a cancer perspective. Mol. Cancer 15, 71 (2016).
Schlesinger, Y. et al. Single-cell transcriptomes of pancreatic preinvasive lesions and cancer reveal acinar metaplastic cells’ heterogeneity. Nat. Commun. 11, 4516 (2020).
Price, J. G. et al. CDKN1A regulates Langerhans cell survival and promotes Treg cell generation upon exposure to ionizing irradiation. Nat. Immunol. 16, 1060–1068 (2015).
Zhang, Y. et al. Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer. Cancer Cell 39, 1578–1593 (2021).
Croessmann, S. et al. NDRG1 links p53 with proliferation-mediated centrosome homeostasis and genome stability. Proc. Natl Acad. Sci. USA 112, 11583–11588 (2015).
Gibson, B. A. et al. Organization of chromatin by intrinsic and regulated phase separation. Cell 179, 470–484 (2019).
Liu, Y., Peng, L., Seto, E., Huang, S. & Qiu, Y. Modulation of histone deacetylase 6 (HDAC6) nuclear import and tubulin deacetylase activity through acetylation. J. Biol. Chem. 287, 29168–29174 (2012).
Folkmann, A. W., Putnam, A., Lee, C. F. & Seydoux, G. Regulation of biomolecular condensates by interfacial protein clusters. Science 373, 1218–1224 (2021).
Tessarz, P. & Kouzarides, T. Histone core modifications regulating nucleosome structure and dynamics. Nat. Rev. Mol. Cell Biol. 15, 703–708 (2014).
Bernier, M. et al. Linker histone H1 and H3K56 acetylation are antagonistic regulators of nucleosome dynamics. Nat. Commun. 6, 10152 (2015).
Peixoto, P. et al. HDAC5 is required for maintenance of pericentric heterochromatin, and controls cell-cycle progression and survival of human cancer cells. Cell Death Differ. 19, 1239–1252 (2012).
Yin, X. et al. ATF3, an adaptive-response gene, enhances TGFβ signaling and cancer-initiating cell features in breast cancer cells. J. Cell Sci. 123, 3558–3565 (2010).
Zheng, Y.-C. et al. Curriculum vitae of HDAC6 in solid tumors. Int. J. Biol. Macromol. 230, 123219 (2023).
Li, M. et al. Comprehensive 3D epigenomic maps define limbal stem/progenitor cell function and identity. Nat. Commun. 13, 1293 (2022).
Simon, M. D. et al. The site-specific installation of methyl-lysine analogs into recombinant histones. Cell 128, 1003–1012 (2007).
Parida, P. K. et al. Limiting mitochondrial plasticity by targeting DRP1 induces metabolic reprogramming and reduces breast cancer brain metastases. Nat. Cancer 4, 893–907 (2023).
Sun, X. et al. Loss of the receptors ER, PR and HER2 promotes USP15-dependent stabilization of PARP1 in triple-negative breast cancer. Nat. Cancer 4, 716–733 (2023).
Xie, J. et al. Targeting androgen receptor phase separation to overcome antiandrogen resistance. Nat. Chem. Biol. 18, 1341–1350 (2022).
Acknowledgements
This work was supported by the National Natural Science Foundation of China (82372857 to B.L.; 81972651 and 82172698 to W.Z.), Natural Science Foundation of Guangdong Province (2017A030312009 to W.Z.) and the High-Level Hospital Construction Project (DFJHBF202102 to W.Z.). We extend our gratitude to Guangzhou Raybio Medical Technology Co., Ltd. for generously providing the HALO image analysis platform.
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Authors and Affiliations
Contributions
B.L. performed the phase separation experiments and wrote the paper. R.Q. discovered the phospho-HDAC6 LLPS, conducted ATAC-seq, ChIP-seq and RNA-seq analyses and helped in revising the paper. L.W. and J.W. performed the animal experiments and in vitro assays. Q.Z. performed the ChIP-seq and DNaseI TUNEL assays. M.L. analyzed the Hi-C seq data and provided technical support. X.Z. and J.C. performed the metabolic assays. I.-Y.H. and C.Y. performed the drug screening assays. J.Z. and Z.S. generated the PDX model. Y.Z., T.J. and H.Z. prepared the plasmids and shRNA lentiviral vectors. J.L. designed the experiments, interpreted the data, revised the paper and provided supervision. W.Z. conceptualized and designed the experiments, interpreted the data, wrote and revised the paper and provided supervision.
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Extended data
Extended Data Fig. 1 Phosphorylated HDAC6 (phospho-HDAC6) in the nuclei of triple-negative breast cancer (TNBC).
Related to Fig. 1. a. HALO® image analysis platform was used to identify tumor cells and measure the staining intensity of HDAC6 in breast cancer samples (n = 13 for para-cancerous, n = 19 for non-TNBC, and n = 3 for TNBC). Solid lines represent the median, and dashed lines represent the upper and lower quartiles. P values were calculated by one-way ANOVA with multiple comparisons. Scale bar, 50 μm. b. MDA-MB231 cells were transduced with HA-tagged HDAC6 or empty vector control. Subsequently, nuclear cell lysates underwent a pulldown process utilizing the HA antibody, followed by immunoblotting with the phosphorylation antibody. c. Sanger sequencing results of HDAC6 mutant variants. d. Immunoblot analysis was conducted using the phospho-HDAC6 antibody on BT-549 cells transfected with either HDAC6 wild-type or mutant constructs. e. Representative immunofluorescence images of BT-549 cells transfected with HDAC6 wide-type (WT) or mutations. Scale bar, 5 μm. f. Quantification of phospho-HDAC6 staining intensity in breast cancer samples using the HALO® image analysis platform. The staining intensity was separated into nucleus and cytoplasm in breast cancer specimens (n = 6 for para-cancerous, n = 53 for non-TNBC, and n = 9 for TNBC). Solid lines represent the median, and dashed lines represent the upper and lower quartiles. P values were calculated by one-way ANOVA with multiple comparisons. Scale bars, 100 μm. g. Statistical analysis table showing the correlation between phospho-HDAC6 staining intensity and clinical data from 62 breast cancer patients (non-TNBC, n = 53; TNBC, n = 9). Significance was determined using a two-sided chi-squared test. h. Kaplan-Meier overall survival curve of 62 breast cancer patients based on their nuclear phospho-HDAC6 levels. N = 53 for non-TNBC, n = 9 for TNBC. Statistical significance was determined using log-rank test. Experiments were repeated three times independently with similar results; representative images are shown (a-b, d-f).
Extended Data Fig. 2 Liquid-liquid phase separation (LLPS) of phospho-HDAC6 in TNBCs.
Related to Fig. 1. a. Representative immunofluorescence images of HDAC6 in breast cancer specimens were obtained using a Super-resolution microscope (50 cells in each sample are used for statistical analysis). Nuclei were counterstained with DAPI. Scale bars, 25 μm. b. High-resolution images of HDAC6 immunofluorescence staining in mammary epithelial cell line (MCF-10A), luminal breast cancer cell line (MCF-7), and TNBC cell lines (BT-549 and MDA-MB231). N = 15 cells per group. Scale bar, 5 μm. c. Single-particle tracks for mean speed of simulated phosphorylation HDAC6 (HDAC6-S22E) single molecules within the temporally registered reference frame binned into 1 s intervals. HDAC6-S22E was fused with monomeric enhanced green fluorescent protein (mEGFP). d. BT-549 cells were subjected to staining using anti-phospho-HDAC6, anti-HP1α (heterochromatin marker), and anti-H3K9me3 antibodies. Subsequently, the correlation of fluorescence intensity between phospho-HDAC6 and HP1α or H3K9me3 was quantified. Scale bar, 5 μm. e. MCF-7 and MCF-10A cells were treated with EGF (200 ng/ml) for 30 mins, and the statistical results of the number of condensates in the control and EGF treatment group were shown, n = 15 cells per group. f. Immunoblot analysis of HDAC6 and phospho-HDAC6 proteins in BT-549 cells treated with or without EGF (200 ng/ml) for 30 mins. Scale bar, 5 μm. g. Immunofluorescence imaging of phospho-HDAC6 condensates in MCF-10A and MCF-7 cells upon GRK2 inhibitor GSK180736A (2 μM) treatment for 24 h, with statistical results of condensates number in control and GRK2 inhibitor treatment group shown. N = 15 cells per group, Scale bar, 5 μm. h. Immunoblot analysis of HDAC6 and phospho-HDAC6 proteins in BT-549 cells treated with or without GRK2 inhibitor GSK180736A (2 μM) for 48 h. i. Bar chart showing the relative expression levels of GRK2 in shCtrl and shGRK2 BT-549 cells, as determined by real-time polymerase chain reaction (qPCR) analysis. N = 3 per group. In a-b, e, g the boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. Data in c and i are shown as the mean ± s.d.; P values in a-b, i were calculated by one-way ANOVA with multiple comparisons. P values in e, g were calculated by two-way ANOVA with multiple comparisons. Experiments were repeated three times independently with similar results; representative images are shown in a-b and d-h.
Extended Data Fig. 3 Role of phosphorylation residue, catalytic domain, and nuclear export sequence (NES) regions in modulating HDAC6 phase separation.
Related to Fig. 2. a. Immunoblotting analysis of HDAC6 in WT and HDAC6 knockout (KO) MDA-MB231 and BT-549 cells. b. Immunofluorescence images of phosphorylated form of HDAC6 (or HDAC6 truncates) when overexpressing HDAC6 deletion segments(ΔIDR1/2) in the cell nuclei of HDAC6 KO MDA-MB231 cells. N = 15 cells per group. Scale bar, 5 μm. c. Analysis of droplet formation in the indicated protein mixture (160 μM each) before and after 5% 1,6-hexanediol treatment. WT refers to the wide-type HDAC6 IDR1 fused with mEGFP. S22F, HDAC6 IDR1 Ser 22 to Phe; S22E, HDAC6 IDR1 Ser 22 to Glu. N = 3 per group. Scale bar, 5 μm. Each point in the statistical chart represents the average diameter of all droplets in each experiment. d. Cell viability assays were performed using CellTiter-Glo in BT-549 and MDA-MB321 cells transduced with HDAC6 wild-type (WT) or mutations (S22E or S22F). N = 3 per group, statistical analysis is conducted after a 72-hour period. e. Sphere formation assay was conducted in BT-549 and MDA-MB321 cells transduced with HDAC6 WT or mutations, and the results were compared with the empty vector control. N = 3 per group, the number of spheres formed was counted on day 7. f. Invasion assays were performed in BT-549 and MDA-MB321 cells transduced with HDAC6 WT or mutations, respectively, n = 3 per group. g. Representative images of orthotopic tumor tissue (day 14) derived from MDA-MB231 cells transfected with HDAC6 WT, S22E, or S22F mutations (6 mice in each group). The tumor volume and weight data (day 14) are also presented. h. Immunofluorescence images of phosphorylated form of HDAC6 (or HDAC6 truncates) when overexpressing HDAC6 deletion segments (ΔBUZ, ΔDD1, ΔDD2, ΔDD) in the cell nuclei of HDAC6 KO MDA-MB231 cells. N = 15 cells per group. Scale bar, 5 μm. i. Immunofluorescence images of phosphorylated form of HDAC6 (or HDAC6 truncates) when overexpressing HDAC6 deletion segments (ΔNES1, ΔSE14, ΔNES2, ΔNES) in the cell nuclei of HDAC6 KO MDA-MB231 cells. N = 15 cells per group. Scale bar, 5 μm. j. Sphere formation assay of BT-549 cells overexpressing the empty vector (EV), full-length (FL), or NES-truncated HDAC6 variants. k. Extreme limiting dilution assay of BT-549 cells overexpressing the empty vector (EV), full-length (FL), or NES-truncated HDAC6 variants (ΔNES). (Left) An extreme limiting dilution algorithm was used to calculate the frequency of cancer stem cells, showing significant differences between EV and ΔNES (P = 0.0492). (Right) The table displays the estimated stem cell frequency and 95% confidence interval (CI). In b, h-i the boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. Data in c-g, j are shown as the mean ± s.d.; P values in b, e-j were calculated by one-way ANOVA with multiple comparisons. P values in c-d were calculated by two-way ANOVA with multiple comparisons. P values in k were calculated by chi-square test. Experiments were repeated three times independently with similar results; representative images are shown in a-c and g-j.
Extended Data Fig. 4 Inhibition of HDAC6 LLPS condensates by Nexturastat A suppresses TNBC growth in vitro and in vivo.
Related to Fig. 3. a. MDA-MB231 cells were transduced with HA tagged HDAC6 WT or S22F. Co-immunoprecipitation (Co-IP) analysis showing the interaction between HDAC6 and PPP1CA in MDA-MB231 cells. b. Immunoblotting analysis of HDAC6 and phosphorylated HDAC6 levels in MDA-MB231 cells transduced with shPPP1CA and control shRNA. c. Immunoblotting analysis of HDAC6 and phosphorylated HDAC6 in MDA-MB231 cells transduced with shPPP1CA or control shRNA, followed by treatment with 5 μM Nexturastat A or 5 mM HPOB (a reference compound) for 24 h. d. Immunoblotting analysis of HDAC6 and phosphorylated HDAC6 in MDA-MB231 cells treated with or without 5 mM Nexturastat A or 1.5% 1,6-hexanediol. e. Cell viability assays were performed in chondrocytes (as a normal control), MCF-7 cells treated with Nexturastat A for 48 h, n = 3 per group. f. Transwell assay was conducted in BT-549 cells treated with DMSO, HPOB, or Nexturastat A for 24 h, respectively. g. Flow cytometry analysis of apoptotic cells in BT-549 and MDA-MB231 cells treated with DMSO, HPOB, or Nexturastat A. h. Flow cytometry analysis of apoptotic cells in MDA-MB231, BT-549, and MCF-7 cells treated with Nexturastat A at the indicated concentrations. i. Flow cytometry analysis of apoptotic cells in MDA-MB231 cells stably transduced with HDAC6 WT or S22F mutation, with or without treatment of Nexturastat A (5 μM). j. Cell cycle analysis of BT-549 cells treated with Nexturastat A at the indicated concentrations for 48 h, n = 3 per group. k. Representative images of IHC staining and quantification of Ki67-positive cells in MDA-MB231-derived subcutaneous tumors treated with Nexturastat A at the indicated concentration, n = 3 per group. l. Representative immunohistochemistry (IHC) staining for ER, PR, and HER2 in TNBC patient-derived xenografts. m. Weight curve of mice bearing MDA-MB231-derived subcutaneous tumors after treatment with Nexturastat A at the indicated concentration, n = 5 per group. n. Cell viability assays were conducted in MDA-MB231 and BT-549 cells stably transduced with non-targeting scrambled control shRNA (shCtrl) or two HDAC6 shRNAs (shHDAC6-1 and shHDAC6-2), respectively. Related cell viability values are normalized to the control (day 0), n = 3 per group. o. Sphere formation assays were conducted in MDA-MB231 and BT-549 cells stably transduced with shCtrl, shHDAC6-1, or shHDAC6-2, respectively, with or without Nexturastat A (5 μM). N = 3 per group, the number of spheroids was counted on day 7. p. Invasion assays were conducted in MDA-MB231 cells stably transduced with shCtrl, shHDAC6-1, or shHDAC6-2, respectively, with treatment of DMSO or Nexturastat A (5 μM), n = 3 per group. q. Flow cytometry analysis of apoptotic cells in MDA-MB231 and BT-549 cells stably transduced with shCtrl, shHDAC6-1, or shHDAC6-2, respectively, with or without Nexturastat A (5 μM), n = 3 per group. Data in e-k and m-q are shown as the mean ± s.d.; P values in f-h, k were calculated by one-way ANOVA with multiple comparisons. P values in i, n-q were calculated by two-way ANOVA with multiple comparisons. Experiments were repeated three times independently with similar results; representative images are shown in a-d and k-l.
Extended Data Fig. 5 14-3-3θ promotes phospho-HDAC6 LLPS in TNBCs.
Related to Fig. 4. a. Schematic diagram depicting the immunoprecipitation-mass spectrometry (IP-MS) experiment performed to identify components in phospho-HDAC6 LLPS condensates. b. The HDAC6 up-regulated interacting proteins upon 8 μM Nexturastat A treatment. c. Co-IP analysis in MDA-MB231 cells transduced with HA-tagged HDAC6 and treated with or without 10 μM Nexturastat A, showing the interaction between HDAC6 and a-Tubulin. EV, empty vector. d. Mass spectrometry images showing the 14-3-3θ interacted with HDAC6. e. qPCR showing the knockdown efficiency of 14-3-3θ in BT-549 cells. f-g. In vitro droplet formation assays demonstrating that HDAC6-WT droplets but not HDAC6-S22F droplets incorporate 14-3-3θ protein. Scale bar = 50 μm. h. Statistical analysis of the diameter distribution of mixed protein droplets formed by HDAC6-WT, HDAC6-S22F, and HDAC6-S22E with 14-3-3θ protein in vitro. i. Quantitative PCR (qPCR) demonstrating the knockdown efficiency of Importin β in BT-549 cells j. Representative super-resolution microscope images showing total HDAC6 localization in BT-549 cells with or without Importin β KD (n = 15). Nuclei were counterstained with DAPI. Scale bars, 5 μm. k. qPCR demonstrating the knockdown efficiency of NUP153, NUP214, NUP88, and NUP98 in BT-549 cells. In j the boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. Data in e and h-k are shown as the mean ± s.d.; P values in e, i-k were calculated by one-way ANOVA with multiple comparisons. P values in h were calculated by two-way ANOVA with multiple comparisons. Experiments were repeated three times independently with similar results; representative images are shown in c, f-g and j.
Extended Data Fig. 6 Disruption of phospho-HDAC6 LLPS re-establish chromatin structure.
Related to Fig. 5. a. DNase I-treated TUNEL assay was performed to analyze chromatin accessibility in MDA-MB231 cells treated with either DMSO control (Ctrl) or Nexturastat A. Nuclei were counterstained with DAPI. b. Heatmaps showing chromatin interactions of chromosome 2 at different resolutions: 100-kb, 50-kb, and 10-kb. c. Chromatin compartments and Pearson correlation heatmap of cis-interactions on chromosome 1. Positive first principal component (PC1) values represent compartment A (blue), and negative PC1 values represent compartment B (red). d. Boxplots showing the GC content of compartments A and B in the Ctrl and Nexturastat A-treated cells. e. Comparison of chromatin compartments and Pearson correlation heatmap of Ctrl and Nexturastat A-treated cells on chromosome 6, chromosome 10, and chromosome 17. The shaded area indicates the switching region between compartments A and B. f. BODIPY 493/503 staining of BT-549 and MDA-MB231 cells treated with or without 10 mM Nexturastat A for 48 h. BODIPY 493/503 is used to visualize lipid droplets, indicating changes in lipid metabolism upon treatment. g. Representative images of immunohistochemistry (IHC) staining of CD4, CD8, PD-1, and CD86 in 4T1 xenografts. h. Venn diagram shows the overlap of TAD boundaries between control and Nexturastat A treatment groups. i. The number of differential TAD in four classification groups after Nexturastat A treatment. j. Representative images of merge, split and rearrangement in TAD. k. Top ten TF-binding motifs found in control and Nexturastat A treatment group TAD boundaries, separately. l. GO enrichment of genes in Nexturastat A specific loops. Gene Ontology (GO) enrichment analysis was performed using the hypergeometric test, a two-tailed non-parametric method. m. IGV Genome Browser visualization depicting histone pan-acetylation, HDAC, and RNA Polymerase II (Pol II) Chromatin Immunoprecipitation followed by DNA Sequencing (ChIP-seq) data, RNA-seq results, and interactions identified from Hi-C in MDA-MB231 cells treated with or without Nexturastat A for PCDHA1, UPB1, ATP1A2, and GALNT9 loci. In a, d the boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. Data in f is shown as the mean ± s.d.; P values in a, d, and f were calculated by two-tailed student’s t-test. Experiments were repeated three times independently with similar results; representative images are shown in a, f-g.
Extended Data Fig. 7 Phospho-HDAC6 LLPS condensates disruption induces transcriptional reprogramming in TNBCs.
Related to Fig. 6. a. Genomic binding patterns of Assay for Transposase-Accessible Chromatin using Sequencing (ATAC-seq) and Pol II ChIP-seq with or without Nexturastat A treatment, centered around peak regions and 1 kb upstream and downstream of lost, common and new peaks. b. Box plots displaying the consistency of ATAC-seq and Pol II ChIP-seq signal. X-axis is grade of log2 (fold change) of ATAC signal and Y-axis is log2 (fold change) of pol II occupancy. The boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. P values were calculated by one-way ANOVA with multiple comparisons. c. Heatmap showing binding pattern of ATAC-seq and Pol II ChIP-seq surrounding new peaks. d-e. Volcano plot displaying the changes in gene expression following Nexturastat A, HPOB, Tubastatin A treatment or knockdown of HDAC6 in MDA-MB231 cells. Gene expression differences were assessed using DESeq2, which models read counts with a negative binomial distribution and uses two-tailed Wald tests to identify differentially expressed genes between conditions. f. Heatmap displaying the expression levels of differentially expressed genes, including tumor suppressor genes, proto-oncogenes, and immunomodulators, in MDA-MB-231 cells with or without Nexturastat A treatment. g-h. Gene set enrichment analysis (GSEA) enrichment plot showing the pathway of Antigen Processing and Presentation (GO:0019882) and TNFα Signaling via NF-κB for Nexturastat A treatment versus control and shHDAC6 versus shCtrl. GSEA was performed using a two-tailed non-parametric permutation-based method. Genes were first ranked by their correlation with the phenotype. P values in d-e were calculated by two-tailed Wald tests and g-h was performed using a two-tailed non-parametric permutation-based method. N = 3 biologically independent experiments.
Extended Data Fig. 8 Identification of direct targets of phospho-HDAC6 LLPS condensates in TNBCs.
Related to Fig. 7. a. Genomic binding patterns of HDAC6 ChIP-seq and H3 Pan-acetylation (Pan-acetyl) ChIP-seq with and without Nexturastat A treatment, centered around the transcription start site (TSS) and 3 kb upstream and downstream of differentially expressed genes in HDAC6 ChIP-seq. HDAC6 ChIP-seq replicate 1 (Rep1) utilized HDAC6 antibody from Cell Signaling Technology, while replicate 2 (Rep2) employed HDAC6 antibody from Novusbio. b. Metagene plot showing HDAC6 ChIP-seq and H3 Pan-acetyl ChIP-seq occupancy profiles across the transcription start site (TSS) and transcription end site (TES) regions with and without Nexturastat A treatment. c. Pie chart illustrating the percentage of genomic occupancy for decreased binding regions in HDAC6 ChIP-seq and increased binding regions in H3 Pan-acetyl ChIP-seq. d. Genomic tracks of HDAC6 ChIP-seq and H3 Pan-acetyl ChIP-seq with and without Nexturastat A treatment at the tumor suppressor gene NDRG1 and immunomodulator PD-L1 loci. HDAC6 ChIP-seq Rep1 utilized HDAC6 antibody from Cell Signaling Technology, while Rep2 employed HDAC6 antibody from Novusbio. e. Boxplot showing the expression levels of ATF3 in TNBC and non-TNBC patients from TCGA. Statistical significance was determined using Student’s two-tailed t-test. f. Boxplot showing the expression levels of ATF3 in different stages (I-IV) of TNBC patients. Statistical significance was determined using one-way ANOVA followed by post-hoc tests with Bonferroni correction for multiple comparisons. g. Bar chart showing the relative expression levels of ATF3 in shCtrl and shATF3 MDA-MB231 cells as determined by qPCR analysis. P values were calculated by one-way ANOVA with multiple comparisons. h. Representative images showing the number of invasive cells in the control group (shCtrl) and ATF3 knockdown group (shATF3) with or without Nexturastat A treatment. i. Representative images showing the number of spheres in the control group (shCtrl) and ATF3 knockdown group (shATF3) with or without Nexturastat A treatment. j. Flow cytometry plots showing the percentage of apoptotic cells in the control group (shCtrl) and ATF3 knockdown group (shATF3) treated with or without Nexturastat A treatment. k. Schematic representation of the orthotopic tumor model. BT-549 cells with ATF3 knockdown or control were injected into nude mice, respectively. Nexturastat A or 0.9% NaCl was administered every 2 days for 11 days. In e-f the boxplots represent the median values and quartiles, and the whiskers represent the maximum and minimum values. Data in g are shown as the mean ± s.d.; P values in e, g were calculated by two-tailed student’s t-test, f was calculated by one-way ANOVA. Experiments were repeated three times independently with similar results; representative images are shown in h-j.
Supplementary information
Supplementary Information
Supplementary Fig. 1: gating strategies.
Supplementary Tables 1–6
Supplementary Table 1: HDAC inhibitors information in Fig. 3. Supplementary Table 2: shRNAs used in this study. Supplementary Table 3: qPCR primers used in this study. Supplementary Table 4: Antibodies used in this study. Supplementary Table 5: The list of abbreviations for lipid metabolites in Fig. 5g. Supplementary Table 6: Gene_exp_loop in Fig. 5q.
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Lu, B., Qiu, R., Wei, J. et al. Phase separation of phospho-HDAC6 drives aberrant chromatin architecture in triple-negative breast cancer. Nat Cancer 5, 1622–1640 (2024). https://doi.org/10.1038/s43018-024-00816-y
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DOI: https://doi.org/10.1038/s43018-024-00816-y
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