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Cholesterol-targeting Wnt–β-catenin signaling inhibitors for colorectal cancer

Nature Chemical Biology volume 21, pages 1376–1386 (2025)Cite this article

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Abstract

Most persons with colorectal cancer (CRC) carry adenomatous polyposis coli (APC) truncation leading to aberrant Wnt–β-catenin signaling; however, effective targeted therapy for them is lacking as the mechanism by which APC truncation drives CRC remains elusive. Here, we report that the cholesterol level in the inner leaflet of the plasma membrane (IPM) is elevated in all tested APC-truncated CRC cells, driving Wnt-independent formation of Wnt signalosomes through Dishevelled (Dvl)–cholesterol interaction. Cholesterol–Dvl interaction inhibitors potently blocked β-catenin signaling in APC-truncated CRC cells and suppressed their viability. Because of low IPM cholesterol level and low Dvl expression and dependence, normal cells including primary colon epithelial cells were not sensitive to these inhibitors. In vivo testing with a xenograft mouse model showed that our inhibitors effectively suppressed truncated APC-driven tumors without causing intestinal toxicity. Collectively, these results suggest that the most common type of CRC could be effectively and safely treated by blocking the cholesterol–Dvl–β-catenin signaling axis.

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Fig. 1: Cholesterol quantification in colon cells.
Fig. 2: Differential Wnt–β-catenin signaling activity of various colon cells.
Fig. 3: IPM cholesterol and β-catenin levels in unstimulated isogenic HCT15 cells.
Fig. 4: Cholesterol-mediated formation of Wnt signalosomes.
Fig. 5: Inhibition of Dvl-PDZ–cholesterol interaction by small molecules.
Fig. 6: In vivo antitumor activity of WC522 and WC593.

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All described data, all the databases/datasets used in the study and accessible links and accession codes are contained within the paper and Supplementary Information. Source data are provided with this paper.

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Acknowledgements

This work was supported by grants from the National Institutes of Health (R35 GM122530 to W.C.; R01 CA234025 to E.R.N., GM 120281 to V.G.; P41 GM104601 and R01 GM123455 to E.T.; R01 NS114413 to S.M.C.; DK114373 and DK128167 to B.W.) and Department of Defense Breast Cancer Research Program (Era of Hope Scholar Award BC200206 to E.R.N.). E.T. acknowledges computing resources provided by Blue Waters at National Center for Supercomputing Applications and Extreme Science and Engineering Discovery Environment (grant MCA06N060 to E.T.). E.T. is also grateful to the School of Chemical Sciences Scientific Software Program for access to the Schrödinger Suite. W.C. thanks F. Cong of Novartis for a generous gift of Dvl triple-KO MEF cells.

Author information

Authors and Affiliations

  1. Department of Chemistry, University of Illinois Chicago, Chicago, IL, USA

    Ashutosh Sharma, Julian Zalejski, Simona Kavrokova, Jiachen Sun, Koralege C. Pathmasiri, Ahmed Aloulou, Kyli Berkley, Charles F. Delisle, Young Wang, Pawanthi Buweneka, Dominick Pierre-Jacques, Sayandeb Mukherjee, Daesung Lee, Stephanie M. Cologna & Wonhwa Cho

  2. Department of Molecular and Integrative Physiology, Cancer Center at Illinois, Beckman Institute for Advanced Science and Technology, Carl R. Woese Institute for Genomic Biology- Anticancer Discovery from Pets to People, Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, USA

    Shruti Vijay Bendre, Erin Weisser & Erik R. Nelson

  3. NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA

    Hale Siir Hasdemir, Defne Gorgun Ozgulbas & Emad Tajkhorshid

  4. Department of Comparative Biosciences, Division of Nutritional Sciences, Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, IL, USA

    Ruicheng Shi & Bo Wang

  5. Department of Neurogenetics and Translational Neuroscience, Rush University, Chicago, IL, USA

    Diana A. Abbasi

  6. Department of Chemistry, University of Texas at Dallas, Dallas, TX, USA

    Vladimir Gevorgyan

Authors
  1. Ashutosh Sharma
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Contributions

A.S. performed the inhibitor synthesis, screening and optimization and the cellular assays. J.Z., S.K. and J.S. performed the quantitative imaging analyses. D.G.O., H.S.M. and E.T. performed the computational analysis. A.A. and C.F.D contributed to the inhibitor screening. K.B. and P.B. assisted in the cell studies. K.P., D.A.A., D.P.J., S.M. and S.M.C. performed the MS analyses. Y.W. and V.G. constructed the small-molecule library and participated in the early lead optimization. D.L. assisted in the lead optimization. S.V.B., E.W., R.S., B.W. and E.R.N. performed the in vivo inhibitor testing. W.C. conceptualized and supervised the work and wrote the paper.

Corresponding author

Correspondence to Wonhwa Cho.

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Nature Chemical Biology thanks Gunnar Schulte and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Effects of APC and IPM cholesterol on β-catenin stability.

a. Western blot analysis of active β-catenin before and after APC knockdown and site-specific IPM cholesterol depletion, respectively, in APC-truncated CRC (HCT15 and Caco-2) cells. b. Quantification of active β-catenin/GAPDH is shown in a. Error bars are SD’s. n = 3 for all western blots. Statistical analysis was performed with one-way ANOVA. ns, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001. p = 0.0009 (HCT15; column1-2), 0.0008 (HCT15; column1-3), 0.41 (HCT15; column3-4), 0.00012 (Caco2; column1-2), 0.0037 (Caco2; column1-3), 0.43 (Caco2; column3-4). Displayed gel images are representative of similar images from three independent measurements.

Source data

Extended Data Fig. 2 Dvl2 specificity of WC522.

a. The structure of WC522B. b. Western blot analysis of WC522B-binding proteins captured by streptavidin beads pull-down. Biotin was used as a negative control. 1 μM WC522B (12 h) was used for pulldown experiments and GAPDH was used as a gel loading control for all immunoblotting. Displayed data are representative of similar images from three independent measurements.

Source data

Extended Data Fig. 3 Inhibition of β-catenin signaling by WC522 and WC593.

a. Inhibition of the active β-catenin level by WC522 and WC593 was measured in unstimulated APC-truncated CRC cells. GAPDH was employed as a gel loading control for all immunoblotting. Displayed gel images are representative of similar images from three independent measurements. b. Quantification of active β-catenin/GAPDH data shown in a. c. Inhibition of β-catenin transcriptional activity by WC522 and WC593 in unstimulated APC-truncated CRC cells measured by the TopFlash luciferase assay. Error bars are SD’s from three independent measurements (n = 3). Statistical analysis was performed with one-way ANOVA. ns, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001. For b, p = 0.021 (HCT15; column1-2), <0.0001 (HCT15; column1-3), <0.0001 (HCT15; column1-4), 0.014 (Caco2; column1-2), <0.0001 (Caco2; column1-3), <0.0001 (Caco2; column1-4), 0.021 (DLD1; column1-2), <0.0001 (DLD1; column1-3), <0.0001 (DLD1; column1-4)., 0.68 (LOVO; column1-2), <0.0001 (LOVO; column1-3), <0.0001 (LOVO; column1-4)., 0.073 (HT29; column1-2), <0.0001 (HT29; column1-3), <0.0001 (HT29; column1-4). For c, p = 0.47 (HCT15; column1-2), <0.0001 (HCT15; column1-3), <0.0001 (HCT15; column1-4), 0.27 (Caco2; column1-2), <0.0001 (Caco2; column1-3), <0.0001 (Caco2; column1-4), 0.26 (DLD1; column1-2), <0.0001 (DLD1; column1-3), <0.0001 (DLD1; column1-4)., 0468 (LOVO; column1-2), <0.0001 (LOVO; column1-3), <0.0001 (LOVO; column1-4)., 0.28 (HT29; column1-2), <0.0001 (HT29; column1-3), <0.0001 (HT29; column1-4).

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Extended Data Fig. 4 Cellular inhibitory activity of WC522 and WC593.

a. Inhibition of the active β-catenin level by WC522 and WC593 in Wnt3a-stimulated colon cells. b. Quantification of the data shown in a. c. Inhibition of β-catenin transcriptional activity by WC522 and WC593 in Wnt3a-stimulated colon cells. Wnt3a was 50 ng/ml for HCT15, Caco-2 and DLD1 cells and 200 ng/ml for HCT116, RKO, NCI-H508, and CCD-18Co cells. d. Inhibition of the active β-catenin level by WC522 and WC593 in isogenic HCT15 cells. Western blot analysis of active β-catenin in unstimulated HCT15 cells harboring various APC truncations and FL APC was performed as described in Fig. 3a. e. Quantification of the data shown in d. 1 μM WC522 and WC593 (12 h) were used for all inhibition experiments. GAPDH was employed as a gel loading control for all immunoblotting. Error bars are SD’s. n = 3 for all measurements. Statistical analysis was performed with one-way ANOVA. ns, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001. For b, p = 0.00025 (HCT15; column1-2), 0.45 (HCT15; column2-3), <0.0001 (HCT15; column2-4), <0.0001 (HCT15; column2-5), 0.0096 (Caco2; column1-2), 0.34 (Caco2; column2-3), <0.0001 (Caco2; column2-4), <0.0001 (Caco2; column2-5), <0.0001 (DLD1; column1-2), 0.048 (DLD1; column2-3), <0.0001 (DLD1; column2-4), <0.0001 (DLD1; column2-5), 0.0009 (HCT116; column1-2), 0.86 (HCT116; column2-3), 0.039 (HCT116; column2-4), 0.0045 (HCT116; column2-5), 0.004 (RKO; column1-2), 0.79 (RKO; column2-3), 0.51 (RKO; column2-4), 0.086 (RKO; column2-5), 0.002 (NCI-H508; column1-2), 0.57 (NCI-H508; column2-3), 0.33 (NCI-H508; column2-4), 0.14 (NCI-H508; column2-5), <0.0001 (CCD-18Co; column1-2), 0.075 (CCD-18Co; column2-3), 0.037 (CCD-18Co; column2-4), 0.012 (CCD-18Co; column2-5). For c, p = <0.0001 (HCT15; column1-2), 0.43 (HCT15; column2-3), <0.0001 (HCT15; column2-4), <0.0001 (HCT15; column2-5), <0.0001 (Caco2; column1-2), 0.56 (Caco2; column2-3), <0.0001 (Caco2; column2-4), <0.0001 (Caco2; column2-5), <0.0001 (DLD1; column1-2), 0.23 (DLD1; column2-3), <0.0001 (DLD1; column2-4), <0.0001 (DLD1; column2-5), 0.0002 (CCD-18Co; column1-2), 0.27(CCD-18Co; column2-3), 0.066 (CCD-18Co; column2-4), 0.019 (CCD-18Co; column2-5). For e, p = <0.0001 (APC1-1941; column1-2), <0.0001 (APC1-1941; column1-3), <0.0001 (APC1-1941; column1-4), 0.11 (APC1-1309; column1-2), <0.0001 (APC1-1309; column1-3), <0.0001 (APC1-1309; column1-4), 0.68 (APC1-331; column1-2), <0.0001 (APC1-331; column1-3), <0.0001 (APC1-331; column1-4), 0.55 (APC1-2843; column1-2), 0.31 (APC1-2843; column1-3), 0.16 (APC1-2843; column1-4).

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Extended Data Fig. 5 In vivo safety of WC522 and WC593.

a. The length of intestines in xenografted mice treated with placebo, WC593, and WC522 for 21 days. b. Representative histology and quantification of jejunum from mice as in a (~40 villi and 40 crypts per mouse, 6–9 mice/group). c. Representative images of EdU staining and quantification of EdU+ proliferating cells in mice (~25 crypts per mouse, 6–9 mice/group). Scale bars indicate 200 µm for b and 50 µm for c, respectively. For all data, values are means ± SEM with n = 10 for each group. Statistical analysis was performed with one-way ANOVA. ns, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001. For a, p = 0.79 (column1-2), 0.79 (column1-3). For b, p = 0.46 (villi; column1-2), 0.43 (villi; column1-3), 0.60 (crypt height; column1-2), 0.13 (crypt height; column1-3), 0.11 (crypt number; column1-2), 0.22 (crypt number; column1-3). For c, p = 0.29 (column1-2), 0.07 (column1-3).

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Supplementary information

Supplementary Information

Supplementary Figs. 1–16, Tables 1–3, Notes 1 and 2 and Data 1–6.

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Sharma, A., Zalejski, J., Bendre, S.V. et al. Cholesterol-targeting Wnt–β-catenin signaling inhibitors for colorectal cancer. Nat Chem Biol 21, 1376–1386 (2025). https://doi.org/10.1038/s41589-025-01870-y

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