Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Small-molecule inhibitors that disrupt the MTDH–SND1 complex suppress breast cancer progression and metastasis

Abstract

Metastatic breast cancer is a leading health burden worldwide. Previous studies have shown that metadherin (MTDH) promotes breast cancer initiation, metastasis and therapy resistance; however, the therapeutic potential of targeting MTDH remains largely unexplored. Here, we used genetically modified mice and demonstrate that genetic ablation of Mtdh inhibits breast cancer development through disrupting the interaction with staphylococcal nuclease domain-containing 1 (SND1), which is required to sustain breast cancer progression in established tumors. We performed a small-molecule compound screening to identify a class of specific inhibitors that disrupts the protein–protein interaction (PPI) between MTDH and SND1 and show that our lead candidate compounds C26-A2 and C26-A6 suppressed tumor growth and metastasis and enhanced chemotherapy sensitivity in preclinical models of triple-negative breast cancer (TNBC). Our results demonstrate a significant therapeutic potential in targeting the MTDH–SND1 complex and identify a new class of therapeutic agents for metastatic breast cancer.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Induced Mtdh KO suppresses breast cancer progression and metastasis.
Fig. 2: MTDH–SND1 interaction is essential for breast cancer progression and metastasis.
Fig. 3: Identification of small chemical inhibitors that block MTDH–SND1 interaction.
Fig. 4: C26s block the MTDH binding pocket on SND1 to disrupt the MTDH–SND1 complex.
Fig. 5: C26-A2 and C26-A6 suppress tumor formation in vitro.
Fig. 6: MTDH–SND1 complex disruption suppresses breast cancer progression and metastasis.
Fig. 7: MTDH–SND1 targeting and chemotherapy synergistically suppress breast cancer progression and metastasis.
Fig. 8: C26-A6 enhances chemotherapy response in a metastatic breast cancer model without additional toxicity.

Similar content being viewed by others

Data availability

All RNA-sequencing data generated in this study have been deposited as a superseries at the NCBI Gene Expression Omnibus with the accession code GSE174630. The crystal structure data for SND1–C26-A2 (PDB ID: 7KNW) and SND1–C26-A6 (PDB ID: 7KNX) have been deposited at the Protein Data Bank. Further information and requests for resources and reagents should be directed to the corresponding author. All requests for raw and analyzed data and materials will be reviewed promptly by the corresponding author to verify whether the request is subject to any intellectual property or confidentiality obligations. Any data and materials that can be shared will be released via a material transfer agreement. Source data are provided with this paper.

References

  1. Nguyen, D. X., Bos, P. D. & Massague, J. Metastasis: from dissemination to organ-specific colonization. Nat. Rev. Cancer 9, 274–284 (2009).

    Article  CAS  PubMed  Google Scholar 

  2. Hu, G., Wei, Y. & Kang, Y. The multifaceted role of MTDH/AEG-1 in cancer progression. Clin. Cancer Res. 15, 5615–5620 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Wan, L. & Kang, Y. Pleiotropic roles of AEG-1/MTDH/LYRIC in breast cancer. Adv. Cancer Res. 120, 113–134 (2013).

    Article  CAS  PubMed  Google Scholar 

  4. Wan, L. et al. MTDH–SND1 interaction is crucial for expansion and activity of tumor-initiating cells in diverse oncogene- and carcinogen-induced mammary tumors. Cancer Cell 26, 92–105 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wan, L. et al. Genetic ablation of metadherin inhibits autochthonous prostate cancer progression and metastasis. Cancer Res. 74, 5336–5347 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Shen, M. et al. Therapeutic targeting of metadherin suppresses colorectal and lung cancer progression and metastasis. Cancer Res. 81, 1014–1025 (2021).

    Article  CAS  PubMed  Google Scholar 

  7. Blanco, M. A. et al. Identification of staphylococcal nuclease domain-containing 1 (SND1) as a metadherin-interacting protein with metastasis-promoting functions. J. Biol. Chem. 286, 19982–19992 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Yoo, B. K. et al. Increased RNA-induced silencing complex (RISC) activity contributes to hepatocellular carcinoma. Hepatology 53, 1538–1548 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Van Nostrand, E. L. et al. A large-scale binding and functional map of human RNA-binding proteins. Nature 583, 711–719 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Jariwala, N. et al. Role of the staphylococcal nuclease and tudor domain containing 1 in oncogenesis (review). Int. J. Oncol. 46, 465–473 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Guo, F. et al. Structural insights into the tumor-promoting function of the MTDH–SND1 complex. Cell Rep. 8, 1704–1713 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Du, J. et al. PDK1 promotes tumor growth and metastasis in a spontaneous breast cancer model. Oncogene 35, 3314–3323 (2016).

    Article  CAS  PubMed  Google Scholar 

  13. Canovas, B. et al. Targeting p38α increases DNA damage, chromosome instability, and the anti-tumoral response to taxanes in breast cancer cells. Cancer Cell 33, 1094–1110 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Klein, A. et al. Comparison of gene expression data from human and mouse breast cancers: identification of a conserved breast tumor gene set. Int. J. Cancer 121, 683–688 (2007).

    Article  CAS  PubMed  Google Scholar 

  15. Kretschmer, C. et al. Identification of early molecular markers for breast cancer. Mol. Cancer 10, 15 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Maroulakou, I. G., Anver, M., Garrett, L. & Green, J. E. Prostate and mammary adenocarcinoma in transgenic mice carrying a rat C3(1) simian virus 40 large tumor antigen fusion gene. Proc. Natl Acad. Sci. USA 91, 11236–11240 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Cho, R. W. et al. Isolation and molecular characterization of cancer stem cells in MMTV-Wnt-1 murine breast tumors. Stem Cells 26, 364–371 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Hollern, D. P. & Andrechek, E. R. A genomic analysis of mouse models of breast cancer reveals molecular features of mouse models and relationships to human breast cancer. Breast Cancer Res. 16, R59 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Pond, A. C. et al. Fibroblast growth factor receptor signaling dramatically accelerates tumorigenesis and enhances oncoprotein translation in the mouse mammary tumor virus-Wnt-1 mouse model of breast cancer. Cancer Res. 70, 4868–4879 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Luker, K. E. et al. Kinetics of regulated protein–protein interactions revealed with firefly luciferase complementation imaging in cells and living animals. Proc. Natl Acad. Sci. USA 101, 12288–12293 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Paulmurugan, R. & Gambhir, S. S. Combinatorial library screening for developing an improved split-firefly luciferase fragment-assisted complementation system for studying protein–protein interactions. Anal. Chem. 79, 2346–2353 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Porter, J. R., Stains, C. I., Jester, B. W. & Ghosh, I. A general and rapid cell-free approach for the interrogation of protein–protein, protein–DNA, and protein–RNA interactions and their antagonists utilizing split-protein reporters. J. Am. Chem. Soc. 130, 6488–6497 (2008).

    Article  CAS  PubMed  Google Scholar 

  23. Hoffmann, C. et al. A FlAsH-based FRET approach to determine G protein-coupled receptor activation in living cells. Nat. Methods 2, 171–176 (2005).

    Article  CAS  PubMed  Google Scholar 

  24. Kang, Y. et al. A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3, 537–549 (2003).

    Article  CAS  PubMed  Google Scholar 

  25. Groftehauge, M. K., Hajizadeh, N. R., Swann, M. J. & Pohl, E. Protein–ligand interactions investigated by thermal shift assays (TSA) and dual polarization interferometry (DPI). Acta Crystallogr. D Biol. Crystallogr. 71, 36–44 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Jerabek-Willemsen, M., Wienken, C. J., Braun, D., Baaske, P. & Duhr, S. Molecular interaction studies using microscale thermophoresis. Assay Drug Dev. Technol. 9, 342–353 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wienken, C. J., Baaske, P., Rothbauer, U., Braun, D. & Duhr, S. Protein-binding assays in biological liquids using microscale thermophoresis. Nat. Commun. 1, 100 (2010).

    Article  PubMed  Google Scholar 

  28. van Breemen, R. B. & Li, Y. Caco-2 cell permeability assays to measure drug absorption. Expert Opin. Drug Metab. Toxicol. 1, 175–185 (2005).

    Article  PubMed  Google Scholar 

  29. DeRose, Y. S. et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat. Med. 17, 1514–1520 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Esposito, M. et al. Bone vascular niche E-selectin induces mesenchymal-epithelial transition and Wnt activation in cancer cells to promote bone metastasis. Nat. Cell Biol. 21, 627–639 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. 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).

    Article  CAS  PubMed  Google Scholar 

  32. Kaur, P. et al. A mouse model for triple-negative breast cancer tumor-initiating cells (TNBC-TICs) exhibits similar aggressive phenotype to the human disease. BMC Cancer 12, 120 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Arkin, M. R., Tang, Y. & Wells, J. A. Small-molecule inhibitors of protein–protein interactions: progressing toward the reality. Chem. Biol. 21, 1102–1114 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lage, K. Protein–protein interactions and genetic diseases: the interactome. Biochim. Biophys. Acta 1842, 1971–1980 (2015).

    Article  Google Scholar 

  35. Scott, D. E., Bayly, A. R., Abell, C. & Skidmore, J. Small molecules, big targets: drug discovery faces the protein-protein interaction challenge. Nat. Rev. 15, 533–550 (2016).

    CAS  Google Scholar 

  36. Jubb, H., Higueruelo, A. P., Winter, A. & Blundell, T. L. Structural biology and drug discovery for protein–protein interactions. Trends Pharmacol. Sci. 33, 241–248 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Surade, S. & Blundell, T. L. Structural biology and drug discovery of difficult targets: the limits of ligandability. Chem. Biol. 19, 42–50 (2012).

    Article  CAS  PubMed  Google Scholar 

  38. Tari, L. W. The utility of structural biology in drug discovery. Methods Mol. Biol. 841, 1–27 (2012).

    Article  CAS  PubMed  Google Scholar 

  39. Jin, L., Wang, W. & Fang, G. Targeting protein–protein interaction by small molecules. Annu. Rev. Pharmacol. Toxicol. 54, 435–456 (2013).

    Article  PubMed  Google Scholar 

  40. Nero, T. L., Morton, C. J., Holien, J. K., Wielens, J. & Parker, M. W. Oncogenic protein interfaces: small molecules, big challenges. Nat. Rev. Cancer 14, 248–262 (2014).

    Article  CAS  PubMed  Google Scholar 

  41. Vassilev, L. T. et al. In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 303, 844–848 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Zhao, J. et al. Discovery and structural characterization of a small molecule 14-3-3 protein–protein interaction inhibitor. Proc. Natl Acad. Sci. USA 108, 16212–16216 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Zimmermann, G. et al. Small molecule inhibition of the KRAS–PDEδ interaction impairs oncogenic KRAS signalling. Nature 497, 638–642 (2013).

    Article  CAS  PubMed  Google Scholar 

  44. Jiang, Y. Z. et al. Preoperative measurement of breast cancer overestimates tumor size compared to pathological measurement. PLoS ONE 9, e86676 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Jiang, Y. Z. et al. Transcriptome analysis of triple-negative breast cancer reveals an integrated mRNA–lncRNA signature with predictive and prognostic value. Cancer Res. 76, 2105–2114 (2016).

    Article  CAS  PubMed  Google Scholar 

  46. Liu, Y. R. et al. Comprehensive transcriptome analysis identifies novel molecular subtypes and subtype-specific RNAs of triple-negative breast cancer. Breast Cancer Res. 18, 33 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Mootha, V. K. et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).

    Article  CAS  Google Scholar 

  49. Kozlov, A. G., Galletto, R. & Lohman, T. M. SSB–DNA binding monitored by fluorescence intensity and anisotropy. Methods Mol. Biol. 922, 55–83 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Okoye-Okafor, U. C. et al. New IDH1 mutant inhibitors for treatment of acute myeloid leukemia. Nat. Chem. Biol. 11, 878–886 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank G. Ren, W. Li, Z. Li, W. Lu and other lab members for technical support and helpful discussions. We thank M. Alpern and V. Buynevich of the University Medical Center of Princeton at Plainsboro for assistance in blood sample analysis and W. Wang at the Genomics Core Facility of Princeton University for RNA sequencing. We thank H. Lin at Pharmacokinetics and Pharmacodynamics (PK/PD) Shared Resource, Rutgers Cancer Institute of New Jersey Rutgers for C26-A6 in vivo tolerability and pharmacokinetics and pharmacodynamics studies. We thank A.V. Korennykh and A. Chitrakar for advice in establishing the split-luciferase assay. This research was supported by the Ludwig Cancer Research, the Brewster Foundation and grants from the Breast Cancer Research Foundation, the NIH (R01CA134519), the Department of Defense Breast Cancer Research Program (BC151403), the American Cancer Society, and the Susan G. Komen Foundation to Y.K. and postdoctoral fellowships from Susan G. Komen (PDF17332118) and NJCCR (DFHS15PPCO21) to M.S. This research was also supported by the Pre-clinical Imaging and Flow Cytometry Shared Resources of the Rutgers Cancer Institute of New Jersey (P30CA072720).

Author information

Authors and Affiliations

Authors

Contributions

M.S. designed and performed the experiments, analyzed data and wrote the manuscript. Y.W., H.K., L.W. and H.A.S. established and helped with the small-molecule screenings. Y.-Z.J., Z.-M.S. and S.W. provided human samples and performed human sample-related experiments. H.K. performed structural analyses and prioritization of the screening hits, selected the candidates for the focused collection of C26s and C32s and provided advice in interpreting the compound–SND1 cocrystal results. J.F.J., M. Raba, S.R. and C.-G.W. coordinated and performed the thermal melt and MST assays and cocrystal structural analysis of the compound–SND1 complex. L.Z. provided essential reagents and advice for toxicity tests. A.Z. and Y.X. established the FRET assay. J.B. performed pharmacokinetic/pharmacodynamic study of the compound. M. Rowicki helped with cell culture. X.L. established the Mtdhfl/fl strain. X.H. and M.Y. maintained the mouse strains and assisted with the animal experiments. Y.K. supervised the overall study, designed experiments, analyzed data and wrote the manuscript.

Corresponding author

Correspondence to Yibin Kang.

Ethics declarations

Competing interests

Princeton has filed a disclosure on the findings based on this study. Y.K., M.S. and H.K. are named as co-inventors on the disclosure. J.F.J. is a cofounder, and Y.K. is a cofounder and chair of the scientific advisory board of Firebrand Therapeutics Inc., which has licensed relevant technologies from Princeton University to develop MTDH–SND1-targeting therapeutics. Y.K. is also a cofounder of Kayothera, Inc. and a member of the scientific advisory board for Cytocare, Inc. and Vibrant Pharma Limited. M. Raba is an employee of Crelux GmgH. S.R. is the owner of SWR Pharma Consulting LLC. The remaining authors declare no competing interests.

Additional information

Peer review information Nature Cancer thanks Daniel Ajona, Taosheng Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Mtdh acute knockout inhibits breast cancer progression and metastasis.

a, Treatment response of each individual mouse in Fig. 1e. b, More representative lungs for Fig. 1g. Size bars, 5 mm. c,i, Tumor burdens of FVB.C3;UBC-CreERT+/-;Mtdhfl/fl (c) or FVB.WNT;UBC-CreERT+/-;Mtdhfl/fl (i) mice before treatment. d,e and j, k, Tumor burdens were showed as in groups or individuals in C3 (d,e) or WNT (j,k) tumor models after treatment. f,l, Tumor burden-based survival was plotted. 500 mm3 was used as cutoff based on the moribund criteria set in our IACUC protocol. p value by Log-rank test. C3 model: Vehicle, n = 9; Tmx, n = 9 (c-f). WNT model: Vehicle, n = 9; Tmx, n = 12 (i-l). g,m MTDH expression in tumors from C3 mice (g) or WNT mice (m) that were treated with vehicle or Tmx was evaluated with western blot. h,n, Lungs from C3 mice (h) or WNT mice (n) were fixed. H&E staining was performed and metastatic incidence (h) or nodules were quantified (n). The metastatic nodules of the representative lungs were highlighted with red and blue respectively (n). C3: Vehicle, n = 9 lungs; Tmx, n = 9 lung; WNT: Vehicle, n = 9 lungs; Tmx, n = 12 lung. Size bar, 5 mm (h,n). Data represent mean ± SEM. Significance determined by two tailed Student’s t-test (c,h,I,n), two-sided Log-rank test (f,l), Two-Way Repeated Measures ANOVA test (d,j). Numerical source data for a, c-f, h-l, n, and uncropped blots for g and m are provided.

Source data

Extended Data Fig. 2 Tamoxifen by itself does not affect tumorsphere formation.

a,b, Primary tumors from PyMT, C3, or WNT mice with vehicle or Tmx treatment were stained with Ki67 or cleaved caspase 3 (Casp-3) (a). Images were acquired at non-necrotic/apoptotic areas that were close to tumor border. Positive cells were quantified (b). Size bar, 50 μm (a). Data represent mean ± SEM. Significance determined by two tailed Student’s t-test. c, PyMT;UBC-CreERT+/-;Mtdhfl/fl cells that were pretreated with 0.02 μg/ml of 4-OHT for 5 days were recovered for another 2 weeks. 25k cells were then seed in each well of the 24-well low attachment plate. One day after seeding, cells were treated with vehicle or 0.02 μg/ml of 4-OHT. 10 days after treatment, sphere number and size were measured and normalized to vehicle control group. Data represent mean ± SEM. n = 3 independent experiments. Significance determined by two tailed Student’s t-test. d, Representative images for tumorspheres in Fig. 2b and Extended Data Fig. 2c are shown. Size bar, 200 μm. e,f, Tumors from Fig. 2d were dissected (e) and tumor mass was measured (f). Size bar, 2 cm. Data represent mean ± SEM. Significance determined by two tailed Student’s t-test. g, H&E-stained sections of Fig. 2e are complemented by high-magnification images. Size bar, 5 mm. h, Cell lines in Fig. 2f were pretreated with 0.02 μg/ml of 4-OHT for 5 days and then recovered for another 2 weeks. The cells were employed for tumorsphere assay with 25k cells per well. Similar treatment as in (c) was performed and number and size of the spheres in 4-OHT treatment groups were measured and normalized to vehicle controls of the same cell line. Data represent mean ± SEM. n = 3 independent experiments. Significance determined by two tailed Student’s t-test. Numerical source data for b, c, f, and h are provided.

Source data

Extended Data Fig. 3 Screening of small chemical compounds that disrupt MTDH/SND1 interaction.

a, 293 T cells that expressed wild type luciferase or indicated split-luciferase components were lysed and subjected to luciferase assay. Data represent mean ± SEM. n = 3 independent experiments. b, 293 T cells that were transfected with CLuc-MTDH-HA and Myc-SND1-NLuc plasmids were lysed for Co-IP assay 3 days later. c, 293 T cells that express split or linked luciferase components were lysed for luciferase assay. 50 μM of wild type (WT) or SND1 interaction-deficient (MT) MTDH peptides were added into the luciferase assay system. Luciferase activity was measured and normalized to control sample. Data represent mean ± SEM. n = 3 independent experiments. Significance determined by one-way ANOVA analysis with Dunnett’s test for multiple comparisons. d, 0.5 μM of CFP-MTDH and 2 μM of TC-SND1 that labeled with 2.4 μM of FIAsH-EDT2 labeling reagent was used to performed FRET assay in 50 μL system. Indicated concentration of wild type (WT) or mutant (MT) MTDH peptides were added and FRET efficiency was calculated. Data represent mean ± SEM. n = 3 independent experiments. Significance determined by one-way ANOVA analysis with Sidak’s test for multiple comparisons. e, Schematic diagram of Co-IP based confirmation of MTDH-SND1 inhibitory compounds (left). SCP28 cells were lysed for IP assay.2 μg of MTDH antibody together with 500 μM of MTDH wild type (Pep-WT) or mutant (Pep-MT) peptides were added into each 1 ml of samples. Red star indicates wild type MTDH peptide competing off SND1 that binds to MTDH. f, 0.1 mg/ml of SND1 purified protein together with the indicated concentration of compounds were applied for thermal melt assay. Melting temperature changes were determined. AU: arbitrary units. g, 200 nM of SND1, 50 nM RED-tris-NTA dye and MTDH peptides (24.4 nM-50 μM) were used to perform Microsacle Thermophoresis (MST) assay. Numerical source data for a, c, d, f, g and uncropped blots for b and e are provided.

Source data

Extended Data Fig. 4 C26-A2 and A6 compete with MTDH to bind the SND1 pocket in the same manner.

a, Overall structures of MTDH-SND1 complex (top). A close-up view is shown at SND1 pocket 2 (bottom). SND1 is shown in red ribbon and cylinder (side chain). MTDH is shown in worm (backbone) and cylinder (side chain) and colored green. b,c, Overall structures of SND1-C26-A2 and SND1-MTDH complexes (b) or SND1-C26-A6 and SND1-MTDH complexes (c). Two perpendicular views are shown. In SND1-C26-A2 and SND1-C26-A6, SND1 is shown in dark blue ribbon, C26-A2 and A6 are shown in orange backbone and surface; In SND1-MTDH complex, SND1 is shown in light blue ribbon, and MTDH is shown in worm (backbone) and cylinder (side chain) and colored red. d, Overall structures of SND1-C26-A2 and SND1-C26-A6 complexes (left). Two perpendicular views are shown. A close-up view of C26-A2 and A6 is shown at SND1 pocket (Right). In SND1-C26-A2, SND1 is shown in red ribbon, C26-A2 is shown in orange backbone; In SND1-C26-A6, SND1 is shown in dark green ribbon, C26-A6 is shown in green backbone.

Extended Data Fig. 5 C26-A2 and A6 inhibits tumorsphere formation in vitro.

a, Caco-2 cells were employed to test cell permeability of C26-A2 and A6. 5 μM of compounds were dosed on both apical side (A-to-B) and basolateral side (B-to-A). Samples were taken from the donor and receiver chambers at 120 min after treatment. All samples were assayed by LC-MS/MS using electrospray ionization. The apparent permeability (Papp) and percent recovery were calculated. b-e, C3;UBC-CreERT+/-;Mtdhfl/fl (b,c) and Wnt;UBC-CreERT+/-;Mtdhfl/fl tumor cells (d,e) that with (c,e) or without (b,d) 5 days of 0.02 μg/ml 4-OHT pre-treatment were subjected to the tumorsphere assay. 50k per well of cells were seed and treated with indicated compounds the next day. 5 days after treatment, sphere number and size were assessed and normalized to vehicle control group. Data represent mean ± SEM. n = 3 independent experiments. Significance determined by one-way ANOVA analysis with Dunnett’s test for multiple comparisons. Numerical source data for b-e are provided.

Source data

Extended Data Fig. 6 C26-A6 treatment blocks MTDH/SND1 interaction in vivo with limited toxicity.

a,b, NSG female mice were inoculated with 10k of SCP28 cells that express split-luciferase components by MFP injection. Two weeks after injection, the mice were treated with 0.25 mg/mouse or 0.5 mg/mouse of C26-A6 via tail-vein injection. 30 min after the treatment, luciferase activity at primary tumors was measured. Data represent mean ± SEM. n = 3 mice. Significance determined by one-way ANOVA analysis with Dunnett’s test for multiple comparisons. c, H&E-stained sections of Fig. 6d are complemented by high-magnification images. Size bar, 5 mm. d, Body weight of the mice in experiment Fig. 6b was measured. Vehicle, n = 10 mice; C26-A6, n = 12 mice. e, Serum from mice in experiment in Fig. 6b were collected for ALT and AST activity measurement following the standard protocol (Sigma). Three FVB females treated with 200 μl of 8% CCl4 in corn oil for 2 days served as positive control. Data represent mean ± SEM. n = 5 mice per group. Significance determined by one-way ANOVA analysis with Dunnett’s test for multiple comparisons. f, Blood samples were drawn from the heart of mice in experiment Fig. 6b, and blood cell counts were performed with the Sysemx XN-3000 Hematology System (Sysmex America, Inc.) Data represent mean ± SEM. Vehicle, n = 6 mice; C26-A6, n = 5 mice. Significance determined by two tailed Student’s t-test. g, Small intestine samples were obtained from mice in experiment Fig. 6b. H&E and Alcian blue staining was performed on processed, sliced samples. Scale bar: 200 μm. h, Quantification of Alcian blue staining results from (g). Data represent mean ± SEM. n = 12 fields from 5 mice in each group. Significance determined by two tailed Student’s t-test. Numerical source data for b, d-f, and h are provided.

Source data

Extended Data Fig. 7 C26-A6 inhibits breast cancer progression and metastasis.

a-c, NGS female mice injected with 2k SCP28 cells orthotopically were subjected to vehicle or C26-A6 treatment after two weeks. Primary tumor volumes were measured(a). 8 weeks after treatment, tumor mass (b) and lung metastasis (c) were assessed. Vehicle, n = 10 mice; C26-A6, n = 10 mice. Size bars, 2 cm for (b) and 5 mm for (c). d,e, Primary tumors from experiment in Fig. 6b were stained with Ki67 and Cleaved-Caspase 3 (Casp-3) antibodies (d). Positive cells were quantified (e). Size bar, 100 μm. Data represent mean ± SEM. n = 6 mice. f, Fresh HCI-001 PDX tumors were implanted into the mammary glands of female NSG mice. One day after implantation, the mice were treated with vehicle or C26-A6. Primary tumors were monitored. g, Primary tumors from (f) were weighted. Representative tumors are shown. Size bar, 2 cm. n = 12 tumors per group. h,i, Primary tumors from (f) were stained with Ki67 and cleaved-Caspase 3 (Casp-3) antibodies (h). Positive cells were quantified (i). Size bar, 200 μm. n = 5 tumors per group. j, Heatmap representation of Next-generation sequencing data displaying the expression of genes in tumors that treated with vehicle (Ctrl), 60 mg/kg of Tmx for 5 consecutive days, or 15 mg/kg of C26-A6 5 days per week. Color key indicates log2 values. n = 4 mice per group. k,l, Ingenuity pathway analysis shows the top five molecular and cellular functions of C26-A6 treatment-downregulated genes (n = 620, fold change >2, p < 0.05) (k). Effects of C26-A6 treatment-downregulated genes in cell death and survival functions (l). p values were automatically determined by QIAGEN Ingenuity Pathway Analysis (QIAGEN IPA). Data represent mean ± SEM. Significance determined by Two-Way Repeated Measures ANOVA test (a,f) and two tailed Student’s t-test (b,c,e,g,i). Numerical source data for a-c, e, f, g, and i are provided.

Source data

Extended Data Fig. 8 C26-A6 induces cell cycle arrest and reduces cell viability.

a, Spheres were treated with vehicle or indicated concentrations of C26-A6 for 1 week. The viability of the spheres was then quantified by MTT assay. b-i, Similar sphere assay as in (a) was performed. The apoptosis (b,f) and cell cycle status (d,h) were determined. The live cells (c,g) and percentage of the cells in each cell cycle phase (e,i) were quantified. n ≥ 3 independent experiments. Data represent mean ± SEM and significance determined by two tailed Student’s t-test for all panels. Numerical source data for a, c, e, g, and i are provided.

Source data

Extended Data Fig. 9 Pathways that are altered upon C26-A6 treatment.

a, Gene set enrichment analysis plot showing the top 4 gene signatures in ranked list of genes. b, Leading edge analysis was performed with the 4 gene signature and the heatmap of top candidate genes was shown. Color key indicates log2 values. c, Sphere assay was performed and treated with vehicle and C26-A6 as in Extended Data Fig. 8a. The spheres were collected for western blot to analyze the expression of the candidates. d,e, Primary tumors from experiment in Extended Data Fig. 7a were stained with indicated antibodies (d). Positive cells were quantified (e). Size bars, 50 μm. n = 5 tumors per group. Data represent mean ± SEM and significance determined by two tailed Student’s t-test (e). f-h, Mammary epithelial cell (MEC) spheres were treated with vehicle or C26-A6 for 1 week. The spheres were then harvested for RNA-sequencing and followed by gene set enrichment analysis(f). The normalized enrichment scores of the indicated signatures in C26-A6 treated MECs and tumors are shown (g). MEC spheres in (f) were collected for western blot analysis with indicated antibodies. Numerical source data for e and uncropped blots for c and h are provided.

Source data

Extended Data Fig. 10 C26-A6 inhibits metastatic breast cancer progression.

a, Indicated cells were injected into NSG females orthotopically and followed by vehicle or C26-A6 treatment after 2 weeks. Tumor volumes were measured 8 weeks after injection. Vehicle, n = 6 mice; C26-A6, n = 6 mice. b, Spontaneous lung metastasis of the mice in (a) were assessed by BLI (right). Size bar, 5 mm. Vehicle, n = 5 lungs; C26-A6, n = 6 lungs. c, The SND1 and MTDH expression of the cells used in (a) was evaluated. d,e,Tail-vein injection lung metastasis was determined by BLI right before (Week 0) or after (5 weeks) vehicle or C26-A6 treatment (f).. Lung metastatic nodules were quantified. The metastatic nodules of the representative lungs were highlighted with red and blue respectively. Size bar, 5 mm (e). Vehicle, n = 11 lungs; C26-A6, n = 12 lungs. f,g, SUM159-M1a cells were injected into NSG females orthotopically. 2 weeks after injection, the mice were treated with vehicle or C26-A6. 5 weeks later, primary tumors (f) and spontaneous lung metastasis (g) were measured. n = 10 mice per group. h,i, Tail-vein injection lung metastasis was determined by BLI right before (Week 0) or after (5 weeks) vehicle or C26-A6 treatment (h).The metastatic nodules of the representative lungs were highlighted with red and blue respectively (i). n = 12 mice per group. Size bar, 5 mm. j,k, 4T1 cells were injected into Balb/C females orthotopically. 1 week after injection, the mice were treated with vehicle or C26-A6. 5 weeks after the treatment, primary tumors (j) and spontaneous lung metastasis (k) were measured. n = 10 mice per group. l, 4T1 cells were injected into Balb/C females intravenously. 5 weeks after vehicle or C26-A6 treatment, lung metastatic nodules were counted. The metastatic nodules of the representative lungs were highlighted with red and blue respectively. Vehicle, n = 5 mice; C26-A6, n = 6 mice. Size bar, 5 mm. Data represent mean ± SEM andsignificance determined by two tailed Student’s t-test for all panels. Numerical source data for a, b, d-l and uncropped blots for c are provided.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2.

Reporting Summary

Supplementary Table

Supplementary Tables 1–10.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 1

Unprocessed western blots.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 2

Unprocessed western blots.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 3

Unprocessed western blots.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 5

Unprocessed western blots.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 6

Unprocessed western blots.

Source Data Fig. 7

Statistical source data.

Source Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 1

Unprocessed western blots.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 3

Unprocessed western blots.

Source Data Extended Data Fig. 5

Statistical source d.ata

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 9

Statistical source data.

Source Data Extended Data Fig. 9

Unprocessed western blots.

Source Data Extended Data Fig. 10

Statistical source data.

Source Data Extended Data Fig. 10

Unprocessed western blots.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, M., Wei, Y., Kim, H. et al. Small-molecule inhibitors that disrupt the MTDH–SND1 complex suppress breast cancer progression and metastasis. Nat Cancer 3, 43–59 (2022). https://doi.org/10.1038/s43018-021-00279-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43018-021-00279-5

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer