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Nanoparticles for inducing Gaucher disease-like damage in cancer cells

Nature Nanotechnology (2024)Cite this article

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Abstract

Nutrient avidity is one of the most distinctive features of tumours. However, nutrient deprivation has yielded limited clinical benefits. In Gaucher disease, an inherited metabolic disorder, cells produce cholesteryl-glucoside which accumulates in lysosomes and causes cell damage. Here we develop a nanoparticle (AbCholB) to emulate natural-lipoprotein-carried cholesterol and initiate Gaucher disease-like damage in cancer cells. AbCholB is composed of a phenylboronic-acid-modified cholesterol (CholB) and albumin. Cancer cells uptake the nanoparticles into lysosomes, where CholB reacts with glucose and generates a cholesteryl-glucoside-like structure that resists degradation and aggregates into microscale crystals, causing Gaucher disease-like damage in a glucose-dependent manner. In addition, the nutrient-sensing function of mTOR is suppressed. It is observed that normal cells escape severe damage due to their inferior ability to compete for nutrients compared with cancer cells. This work provides a bioinspired strategy to selectively impede the metabolic action of cancer cells by taking advantage of their nutrient avidity.

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Fig. 1: AbCholB enters cells via LDLR.
Fig. 2: AbCholB induces GlcCholB formation to inhibit the growth of cancer cells in a glucose-dependent manner.
Fig. 3: GlcCholB accumulation interferes with tumour metabolism.
Fig. 4: GlcCholB aggregates cause GD-like storage damage to cancer cells.
Fig. 5: GD-like disorder induced by AbCholB inhibits mTOR activation.
Fig. 6: AbCholB induces GD-like damage to suppress tumour growth and metastasis.

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Data availability

The data supporting the findings of this study are provided in the article or Supplementary Information. The unprocessed raw data of RNA-seq are available from the corresponding author on reasonable request. Source data are provided with this paper.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (82204293), the Collaborative Innovation Project of Yangtze River Delta Science and Technology Community (2023CSJZN0800) and the Logistics Research Program (BWS20J017). We thank P. Li for manuscript advice, Y. Qiu for grammar editing, H. Guo for help with TEM detection, and H. Wang, C. Wang, Y. Cheng and Y. Liu for advice on the introduction.

Author information

Author notes

  1. These authors contributed equally: Chunyan Yue, Wenjing Lu, Shuxin Fan.

Authors and Affiliations

  1. State Key Laboratory of Pharmaceutical Biotechnology, Medical School, Nanjing University, Nanjing, China

    Chunyan Yue, Wenjing Lu, Shuxin Fan, Zhusheng Huang, Jiaying Yang, Hong Dong, Xiaojun Zhang, Yuxin Shang, Dandan Li, Tiejun Dong, Ahu Yuan, Jinhui Wu & Yiqiao Hu

  2. Institute of Drug R&D, School of Life Science, Nanjing University, Nanjing, China

    Chunyan Yue, Wenjing Lu, Shuxin Fan, Zhusheng Huang, Jiaying Yang, Hong Dong, Xiaojun Zhang, Yuxin Shang, Dandan Li, Tiejun Dong, Ahu Yuan, Jinhui Wu & Yiqiao Hu

  3. Jiangsu Key Laboratory for Nano Technology, Nanjing University, Nanjing, China

    Chunyan Yue, Wenjing Lu, Shuxin Fan, Zhusheng Huang, Jiaying Yang, Hong Dong, Xiaojun Zhang, Yuxin Shang, Dandan Li, Tiejun Dong, Ahu Yuan, Jinhui Wu & Yiqiao Hu

  4. CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing, China

    Wenjia Lai

  5. School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia

    Lifeng Kang

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Contributions

Y.H. conceived the study. C.Y. and Y.H. designed the study. C.Y. conducted cell growth, GLUT1 and LDLR knockdown, movie making, immunocytochemistry assays, western blotting, all confocal imaging experiments, RNA-seq and metabonomics analyses and all statistical analyses. C.Y., W.L., S.F. and D.L. conducted the preparation and characterization of AbCholB and AbChol, and flow cytometry analysis. Z.H. synthesized CholB and conducted 1H NMR analysis. H.D., W.L., X.Z. and S.F. performed HPLC detection. W.L. and S.F. performed TLC analysis. T.D. and Y.S. downloaded and analysed TCGA data. W.L. conducted MALDI–TOF MS and LC–MS/MS scans. W.L., S.F., J.Y. and D.L. performed animal experiments. C.Y. and Y.H wrote the manuscript. A.Y., J.W. and L.K. revised the manuscript. All authors read and edited the manuscript.

Corresponding author

Correspondence to Yiqiao Hu.

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The authors declare no competing interests.

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Nature Nanotechnology thanks Dong-Bing Cheng, Chi (V) Dang and Ming Tan for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characteristic features of AbCholB.

a, 1H-NMR showing the molecular structure of CholB. 1H-NMR (500 MHz, CDCl3): δ 8.02 – 7.74 (m, 2H), 7.57 – 7.28 (m, 2H), 6.69 (d, J = 99.9 Hz, 1H), 5.52 – 5.36 (m, 1H), 4.67 (tt, J = 11.1, 4.5 Hz, 1H), 2.59 – 2.35 (m, 2H), 2.10 – 1.82 (m, 6H), 1.67 – 1.47 (m, 8H), 1.41 – 1.34 (m, 3H), 1.28 (dq, J = 7.0, 3.8 Hz, 4H), 1.16 (tt, J = 19.7, 7.2 Hz, 6H), 1.07 (d, J = 6.5 Hz, 3H), 1.01 (dd, J = 11.1, 5.1 Hz, 2H), 0.94 (dd, J = 6.7, 4.3 Hz, 3H), 0.90 – 0.88 (m, 3H), 0.71 (q, J = 4.7, 3.1 Hz, 3H). b, TLC analysis for Chol and CholB. TLC analysis was developed in petroleum ether/ethyl acetate (1/1, vol/vol) and visualized with iodine vapour. c, d, In situ MALDI–TOF–MS analysis showing the binding of CholB and glucose (Glu) based on a typical ion (m/z = 568.19, M + NH4) of CholB (c) and a typical ion (m/z = 716.48, M+Na) of GlcCholB complex (d). e, Morphologies of AbChol under TEM. n = 3 independent experiments. f, g, Dynamic light scattering (DLS) revealing the size of AbCholB (f) and AbChol (g). Right top was the aqueous solution of AbCholB (f) and AbChol (g) at 5 mM. h, Diameter changes of AbCholB dispersed in saline with a concentration of 50 μM.

Source data

Extended Data Fig. 2 Uptake of AbCholB could be inhibited by LDLR knockdown.

a, A higher magnification view of Fig. 1e with bright field. Scale bar, 10 μm. b, FCM analysis showing the uptake of Dil-AbChol (left) or Dil-AbChoB (middle) in DU145 cells treated with or without LDL blockade. The histogram (right) was quantitative MFI of FCM data. n = 3 replicates. Mean ± s.e.m. Paired two-tailed Student’s t-test as indicated (right). c, WB analysis for LDLR knockdown in MDA-MB-231 cells. n = 3 independent experiments. d, Representative fluorescence confocal images of Dil-AbCholB (upper) or Dil-AbChol (lower) uptake in MDA-MB-231 cells with or without LDLR knockdown as indicated. Scale bar, 20 μm. n = 3. Cells were incubated with Dil-AbCholB or Dil-AbChol for 4 h before collection. e, FCM analysis showing the uptake of Dil-AbChol (left) or Dil-AbCholB (middle) in MDA-MB-231 cells treated with or without LDLR knockdown. The histogram (right) was quantitative MFI of FCM data. n = 3 replicates. Mean ± s.e.m. Paired two-tailed Student’s t-test as indicated (right).

Source data

Extended Data Fig. 3 AbCholB inhibits the proliferation of multiple cancer cells.

a-e, Growth curves showing the effect of AbCholB on proliferation of breast cancer MDA-MB-231 cells (a), prostate cancer DU145 cells (b), pancreas cancer Hs766T cells (c), lung cancer A549 cells (d) and normal breast MCF10A cells (e). All cells were cultured for 48 h in the presence of AbChol (grey), Ph-B+AbChol (blue) and AbCholB (magenta) with a series of gradient concentrations. MTT analysis was performed on 6 replicates. Mean ± s.e.m. Two-way ANOVA with Dunnett’s multiple comparisons test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. From low concentration to high concentration, the exact P values in (a) were 0.2276, 0.9973, 0.0123, 0.0001, 4.637 x 10-9, 6.337 x 10-7, 2.364 x 10-10, 2.8 x 10-14 and 2.8 x 10-14. The exact P values in (b) were 0.0263, 0.9628, 0.7987, 0.962, 0.0007, 6.6 x 10-6, 7.791 x 10-11, 3.2 x 10-14 and 2.8 x 10-14. The exact P values in (c) were 0.9942, 0.9888, 0.4375, 0.0012, 7.634 x 10-5, 1.436 x 10-8, 3.4 x 10-14, 2.8 x 10-14 and 2.8 x 10-14. The exact P values in (d) were 0.967, 0.9371, 0.9532, 0.004, 0.0013, 8.342 x 10-5, 5.432 x 10-7, 1.01 x 10-13 and 2.8 x 10-14. The exact P values in (e) were 1, 0.9956, 1, 0.8813, 0.1854, 0.0209, 1.327 x 10-8, 2.8 x 10-14 and 2.8 x 10-14. f, Western blots showing GLUT1 levels in sh.Ctrl and sh.GLUT1 MDA-MB-231 cells. n = 3 independent experiments.

Source data

Extended Data Fig. 4 AbCholB affects cholesterol homeostasis in MDA-MB-231 cells.

a, PCA for untargeted metabolism analysis in AbCholB treated, Ph-B+AbChol treated and control MDA-MB-231 cells. Left for positive ion model and right for negative ion model. b, c, Relative levels of intermediates involved in cholesterol biosynthesis including farnesyl pyrophosphate (b) and squalene (c). n = 6 replicates. Minimum to maximum, 0–100. Centre line for the median (50th percentile). The box indicates the 25th-75th percentiles of dataset. Paired two-tailed Student’s t-test. d-l, Relative levels of representative metabolites involved in cholesterol metabolic progress including cholesteryl ester (d), steroid hormone biosynthetic intermediates (e to h), bile acid biosynthetic intermediates (i to l). n = 6 replicates. Minimum to maximum, 0–100. Centre line for the median (50th percentile). The box indicates the 25th-75th percentiles of dataset. Statistical analysis was conducted by paired two-tailed Student’s t-test. All cells were subjected to the indicated treatments for 48 h before metabolites extraction. LC-MS/MS analysis revealing the deficiency in cholesterol synthesis and accumulation of various cholesterol derivatives in the presence of AbCholB. Relative levels of metabolites expressed as normalized peak intensity. m, Model revealing the detailed position of differential intermediates in cholesterol metabolic progress.

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Extended Data Fig. 5 AbCholB disturbs mRNA levels of genes enriched in glucose and cholesterol metabolisms.

a, PCA for RNA-seq in AbCholB treated, Ph-B+AbChol treated and control MDA-MB-231 cells. b-d, Volcano plot showing the significantly changed mRNAs between groups as follow: AbCholB vs Ctrl (b), AbCholB vs Ph-B + AbChol (c), Ph-B + AbChol vs Ctrl (d). All RNA-seq samples were collected after treatment for 48 h. n = 3 replicates. e-g, GSEA analysis showing depletion of glucose metabolic gene signatures, including glycolysis/gluconeogenesis (e), pentose phosphate pathway (f) and glycosaminoglycan degradation (g) in AbCholB treated MDA-MB-231 cells compared to Ph-B + AbChol treatment. h, GSEA analysis showing depletion of sterol homeostasis gene signatures in the presence of AbCholB compared to Ph-B + AbChol. i, GSEA analysis showing enrichment of sterol homeostasis gene signatures in Ph-B + AbChol treated cells compared to control cells. GO, gene ontology. j-l, RNA levels of glucose metabolic enzymes G6PD (j), PFKL (k), UGDH (l). G6PD: glucose-6-phosphate dehydrogenase, participates in pentose phosphate pathway; PFKL: phosphofructokinase, key enzyme in glycolysis; UGDH: UDP-glucose-6-dehydrogenase, participates in the biosynthesis of glycosaminoglycans. n = 3 replicates. Floating bar, minimum–maximum; the centre line indicates the mean. Statistical analysis was conducted by paired two-tailed Student’s t-test. m-r, RNA levels of cholesterol homeostasis regulatory factors SREBF2 (m), FDFT1 (n), SREBF1 (o), ABCA1 (p), ABCG1 (q) and SCD (r). n = 3 replicates. Floating bar, minimum–maximum; the centre line indicates the mean. Statistical analysis was conducted by paired two-tailed Student’s t-test. SREBF1/SREBF2: sterol regulatory element binding transcription factor 1/2, necessary for cholesterol and lipid homeostasis. FDFT1: farnesyl-diphosphate farnesyltransferase 1, key enzyme catalysing the sterol biosynthesis. ABCA1: ATP Binding Cassette Subfamily A Member 1, ABCG1: ATP Binding Cassette Subfamily G Member 1, ABCA1 and ABCG1 mediate cholesterol and lipid efflux. SCD: stearoyl-CoA desaturase, key enzyme involved in fatty acid biosynthesis. mRNA levels in (j-r) are from RNA-seq data.

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Extended Data Fig. 6 GlcCholB formation and accumulation causes GD-like storage features in MDA-MB-231 cells.

a, FCM analysis for the uptake of Dil-AbChol (left) or Dil-AbCholB (middle) and the quantitative MFI histogram (right) in DU145 cells at 24 h, 48 h and 72 h. MFI was presented as mean ± s.e.m. n = 3 replicates. Statistical analysis was conducted by paired two-tailed Student’s t-test. b, GSEA showing depletion of lysosomal lumen gene signatures in AbCholB treated MDA-MB-231 cells compared to Ph-B+AbChol treated cells. c, Heatmap of lysosome lumen gene expressions based on GSEA analysis. n = 3 replicates. d, Representative TEM images of autolysosomes (black arrows) and MLB (orange arrows) in DU145 cells subjected to the indicated treatments for 48 h. e, Histogram of MLB counts from (d). MLBs were counted under at least 5 visual fields. Minimum to maximum, 0–100. Centre line for the median (50th percentile). 25th-75th percentiles of dataset in the box. Statistical analysis was conducted by one-way ANOVA. f, TLC analysis for the GlcCholB treated with GBA. GlcCholB was incubated with GBA for 16 h. TLC was developed with petroleum ether/ethyl acetate (1:1, vol/vol). g, GBA activity in shGLUT1 MDA-MB-231 cells subjected to the indicated treatments for 48 h. n = 3 replicates. Statistical analysis was conducted by paired Student’s two-tailed t-test. h, Western blots showing the protein level of caspase 3 (including cleaved-caspase3). n = 3 independent experiments. i, Representative TEM images with lower magnification for Fig. 4e. Autolysosomes (black arrows), MLB (orange arrows), mitochondria (yellow arrows).

Extended Data Fig. 7 AbCholB specifically accumulates in tumour tissues without significant systematic toxicity.

a, Tumour growth kinetics in 4T1-Luci-sh.GLUT1 implanted mice treated with saline and AbCholB. n = 9. Mean ± s.e.m. Statistical analysis was conducted by two-way ANOVA. b, Body weights during the treatment period. n = 9. Mean ± s.e.m. Statistical analysis was conducted by two-way ANOVA. ns: no significance. *P < 0.05. The exact P values were 0.0344 (AbChol vs Saline), 0.0748 (Ph-B+AbChol vs Saline) and 0.0603 (AbCholB vs Saline), respectively. c, Representative images of time-dependent in vivo fluorescence imaging in 4T1-Luci tumour bearing mice. Imaging was performed after tail-vein injection of DiD-AbCholB or DiD-AbChol for 2 h, 6 h, 12 h, 24 h and 48 h. d, Fluorescence images showing DiD-AbCholB distribution in tissues of heart, liver, spleen, lung, kidney, brain and tumour. n = 3. Scale bar, 200 μm. Tumour-bearing mice were sectioned and stained for DAPI after i.v. of DiD-AbCholB for 72 h. e, LC-MS analysis revealing the formation of GlcCholB in tumour treated with AbCholB. Specific peak of GlcCholB (m/z = 694.44, M + H) was only found in AbCholB treated tumour. f, PAS and H&E staining for liver tissues from mice subjected to indicated treatments. Black arrow in H&E images was for macrophages. Scale bar, 30 μm. g, h, Serum biochemical measurement for glucose (g) and glycated albumin (GA) (h). GA was presented as ratio of glycated albumin to total albumin. n = 9 for glucose and n = 8 for GA. Minimum to maximum, 0–100. The centre line indicates the median (50th percentile); the box indicates the 25th–75th percentiles of the dataset. One-way ANOVA. i-l, Serum biochemical measurement for triglyceride (TG) (i), total cholesterol (j), HDL-C (k), and LDL-C (l). n = 8. Minimum to maximum, 0–100. The centre line indicates the median (50th percentile); the box indicates the 25th–75th percentiles of the dataset. Statistical analysis was conducted by one-way ANOVA.

Extended Data Fig. 8 High GLUT1 or LDLR level is correlated to poor prognosis in multiple cancers.

a, Analysis of GLUT1 expression across multiple tumours and normal tissues from TCGA RNA-seq data. Minimum to maximum, 0–100. The centre line indicates the median (50th percentile); the box indicates the 25th–75th percentiles of the dataset. Paired two-tailed Student’s t-test. b-k, Kaplan–Meier curves revealing the overall survival of patients with bladder cancer (BLCA, n = 403), breast cancer (BRCA, n = 1096), brain cancer (n = 667), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC, n = 304), head and neck squamous carcinoma (HNSC, n = 518), kidney renal clear cell carcinoma (KIRC, n = 532), liver hepatocellular carcinoma (LIHC, n = 369), lung adenocarcinoma (LUAD, n = 476), pancreatic adenocarcinoma (PAAD, n = 178) and prostate adenocarcinoma (PRAD, n = 597) based on GLUT1 mRNA levels in TCGA online database. Log-rank (Mantel-Cox) test. Error bar: 95% CI. l, Analysis of LDLR expression across multiple tumours and normal tissues from TCGA RNA-seq data. Minimum to maximum, 0–100. The centre line indicates the median (50th percentile); the box indicates the 25th–75th percentiles of the dataset. Paired two-tailed Student’s t-test. m-s, Kaplan–Meier curves revealing the overall survival of patients with bladder cancer (BLCA, n = 407), brain cancer (n = 653), kidney renal clear cell carcinoma (KIRC, n = 532), liver hepatocellular carcinoma (LIHC, n = 369), lung adenocarcinoma (LUAD, n = 496), pancreatic adenocarcinoma (PAAD, n = 178) and prostate adenocarcinoma (PRAD, n = 497) based on LDLR mRNA levels in TCGA online database. Log-rank (Mantel-Cox) test. Error bar: 95% CI.

Supplementary information

Supplementary Information

Supplementary Figs. 1–4 and Discussion.

Reporting Summary

Supplementary Table 1

Differential metabolites in AbCholB treated MDA-MB-231 cells compared to Ctrl. Including statistical source data for Figs. 3c–m and 4g and Extended Data Fig. 4.

Supplementary Video 1

Uptake of Dil-AbCholB by MDA-MB-231 cells in 12 h. MDA-MB-231 cells were seeded into a confocal dish. 50 μM Dil-AbCholB was added and the uptake process was videoed for 12 h. Scale bar, 20 μm.

Supplementary Video 2

LDL inhibits the uptake of Dil-AbCholB. LDL was added into MDA-MB-231 cells to block LDLR. 1 h later, 50 μM Dil-AbCholB was added for 12 h video. Scale bar, 20 μm.

Supplementary Video 3

Uptake of Dil-AbChol by MDA-MB-231 cells in 12 h. MDA-MB-231 cells were seeded into a confocal dish. 50 μM Dil-AbChol was added and the uptake process was videoed for 12 h.

Supplementary Video 4

LDL inhibits the uptake of Dil-AbChol. LDL was added into MDA-MB-231 cells to block LDLR. 1 h later, 50 μM Dil-AbChol was added for 12 h video. Scale bar, 20 μm.

Supplementary Video 5

Access of Dil-AbCholB into lysosomes in 12 h. MDA-MB-231 cells were seeded into a confocal dish. LAMP1-GFP probe was added to trace lysosomes prior to Dil-AbCholB addition. The medium was replenished with fresh medium contained 50 μM Dil-AbCholB and cells were videoed for 12 h. Scale bar, 20 μm.

Supplementary Video 6

Changes of co-localized positions of Dil-AbCholB and lysosomes from (Supplementary Video 5). The co-localized progress of Dil-AbCholB and LAMP1-positive lysosomes was analysed using cellSens Dimension software.

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Yue, C., Lu, W., Fan, S. et al. Nanoparticles for inducing Gaucher disease-like damage in cancer cells. Nat. Nanotechnol. (2024). https://doi.org/10.1038/s41565-024-01668-4

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