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:

Nutrient-delivery and metabolism reactivation therapy for melanoma

Nature Nanotechnology (2024)Cite this article

Subjects

Abstract

To fulfil the demands of rapid proliferation, tumour cells undergo significant metabolic alterations. Suppression of hyperactivated metabolism has been proven to counteract tumour growth. However, whether the reactivation of downregulated metabolic pathways has therapeutic effects remains unexplored. Here we report a nutrient-based metabolic reactivation strategy for effective melanoma treatment. l-Tyrosine–oleylamine nanomicelles (MTyr–OANPs) were constructed for targeted supplementation of tyrosine to reactivate melanogenesis in melanoma cells. We found that reactivation of melanogenesis using MTyr–OANPs significantly impeded the proliferation of melanoma cells, primarily through the inhibition of glycolysis. Furthermore, leveraging melanin as a natural photothermal reagent for photothermal therapy, we demonstrated the complete eradication of tumours in B16F10 melanoma-bearing mice through treatment with MTyr–OANPs and photothermal therapy. Our strategy for metabolism activation-based tumour treatment suggests specific nutrients as potent activators of metabolic pathways.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Nutrient-based metabolism reactivation strategy for melanoma treatment.
Fig. 2: Stability, biocompatibility and delivery efficiency of MTyr–OANPs.
Fig. 3: Quantitative analysis of efficiency of MTyr–OANPs in promoting melanogenesis and inhibiting growth and migration of melanoma cells.
Fig. 4: MTyr–OANP-induced tyrosinase activation and glycolysis suppression.
Fig. 5: In vivo antitumour activity of MTyr–OANPs in melanoma-bearing mice.
Fig. 6: Pigmented cell phenotypes enhanced cell death in response to 808 nm laser irradiation.

Similar content being viewed by others

Data availability

All the data supporting the results are available within the paper and its Supplementary Information. The bulk RNA-seq data and clinical information of patients with SKCM were downloaded from The Cancer Genome Atlas (TCGA) database: https://portal.gdc.cancer.gov/. All raw sequencing data and associated processed data files that support the findings of this study have been deposited in the Gene Expression Omnibus under accession code GSE263497 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE263479). Source data are provided with this paper.

References

  1. Faubert, B., Solmonson, A. & DeBerardinis, R. J. Metabolic reprogramming and cancer progression. Science 368, 152–163 (2020).

    Article  Google Scholar 

  2. Martinez-Reyes, I. & Chandel, N. S. Cancer metabolism: looking forward. Nat. Rev. Cancer 21, 669–680 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Heiden, M. G. V., Cantley, L. C. & Thompson, C. B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009).

    Article  Google Scholar 

  4. Schiliro, C. & Firestein, B. L. Mechanisms of metabolic reprogramming in cancer cells supporting enhanced growth and proliferation. Cells 10, 1056–1097 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Koundouros, N. & Poulogiannis, G. Reprogramming of fatty acid metabolism in cancer. Br. J. Cancer 122, 4–22 (2020).

    Article  CAS  PubMed  Google Scholar 

  6. Eniafe, J. & Jiang, S. The functional roles of TCA cycle metabolites in cancer. Oncogene 40, 3351–3363 (2021).

    Article  CAS  PubMed  Google Scholar 

  7. Nakhle, J., Rodriguez, A. M. & Vignais, M. L. Multifaceted roles of mitochondrial components and metabolites in metabolic diseases and cancer. Int. J. Mol. Sci. 21, 4405–4436 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Abdel-Wahab, A. F., Mahmoud, W. & Al-Harizy, R. M. Targeting glucose metabolism to suppress cancer progression: prospective of anti-glycolytic cancer therapy. Pharmacol. Res. 150, 104511 (2019).

    Article  CAS  PubMed  Google Scholar 

  9. Di Cosimo, S. et al. Lonidamine: efficacy and safety in clinical trials for the treatment of solid tumors. Drugs Today 39, 157–174 (2003).

    Article  Google Scholar 

  10. Qi, H. et al. Shikonin induced apoptosis mediated by endoplasmic reticulum stress in colorectal cancer cells. J. Cancer 13, 243–252 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Dowsett, M. et al. Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet 386, 1341–1352 (2015).

    Article  Google Scholar 

  12. Ma, C. X., Reinert, T., Chmielewska, I. & Ellis, M. J. Mechanisms of aromatase inhibitor resistance. Nat. Rev. Cancer 15, 261–275 (2015).

    Article  CAS  PubMed  Google Scholar 

  13. Ruijtenberg, S. & van den Heuvel, S. Coordinating cell proliferation and differentiation: antagonism between cell cycle regulators and cell type-specific gene expression. Cell Cycle 15, 196–212 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Gaude, E. & Frezza, C. Tissue-specific and convergent metabolic transformation of cancer correlates with metastatic potential and patient survival. Nat. Commun. 7, 13041 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Garrett, M. et al. Metabolic characterization of isocitrate dehydrogenase (IDH) mutant and IDH wildtype gliomaspheres uncovers cell type-specific vulnerabilities. Cancer Metab. 6, 4 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Suzuki, H. et al. Metabolic alteration in hepatocellular carcinoma: mechanism of lipid accumulation in well-differentiated hepatocellular carcinoma. Can. J. Gastroenterol. Hepatol. 2021, 8813410 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Ma, R. et al. Switch of glycolysis to gluconeogenesis by dexamethasone for treatment of hepatocarcinoma. Nat. Commun. 4, 2508 (2013).

    Article  PubMed  Google Scholar 

  18. Soballe, P. W. & Herlyn, M. Cellular pathways leading to melanoma differentiation—therapeutic implications. Melanoma Res. 4, 213–223 (1994).

    Article  CAS  PubMed  Google Scholar 

  19. Lei, M. J., Dong, Y., Sun, C. X. & Zhang, X. H. Resveratrol inhibits proliferation, promotes differentiation and melanogenesis in HT-144 melanoma cells through inhibition of MEK/ERK kinase pathway. Microb. Pathog. 111, 410–413 (2017).

    Article  CAS  PubMed  Google Scholar 

  20. Chaabane, F., Pinon, A., Simon, A., Ghedira, K. & Chekir-Ghedira, L. Phytochemical potential of Daphne gnidium in inhibiting growth of melanoma cells and enhancing melanogenesis of B16-F0 melanoma. Cell Biochem. Funct. 31, 460–467 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Sung, J. Y. & Cheong, J. H. New immunometabolic strategy based on cell type-specific metabolic reprogramming in the tumor immune microenvironment. Cells 11, 768 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Elia, I., Schmieder, R., Christen, S. & Fendt, S. M. Organ-specific cancer metabolism and its potential for therapy. Handb. Exp. Pharmacol. 233, 321–353 (2016).

    Article  CAS  PubMed  Google Scholar 

  23. Costello, L. C. & Franklin, R. B. Novel role of zinc in the regulation of prostate citrate metabolism and its implications in prostate cancer. Prostate 35, 285–296 (1998).

    Article  CAS  PubMed  Google Scholar 

  24. Franklin, R. B. & Costello, L. C. Zinc as an anti-tumor agent in prostate cancer and in other cancers. Arch. Biochem. Biophys. 463, 211–217 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Goode, D. R., Totten, R. K., Heeres, J. T. & Hergenrothert, P. J. Identification of promiscuous small molecule activators in high-throughput enzyme activation screens. J. Med. Chem. 51, 2346–2349 (2008).

    Article  CAS  PubMed  Google Scholar 

  26. Williams, K. P. & Scott, J. E. Enzyme assay design for high-throughput screening. Methods Mol. Biol. 565, 107–126 (2009).

    Article  CAS  PubMed  Google Scholar 

  27. Werle, M. & Bernkop-Schnurch, A. Strategies to improve plasma half life time of peptide and protein drugs. Amino Acids 30, 351–367 (2006).

    Article  CAS  PubMed  Google Scholar 

  28. Casero, R. A., Stewart, T. M. & Pegg, A. E. Polyamine metabolism and cancer: treatments, challenges and opportunities. Nat. Rev. Cancer 18, 681–695 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Frezza, C. Histidine metabolism boosts cancer therapy. Nature 559, 484–485 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Pal, P., Hales, K., Petrik, J. & Hales, D. B. Pro-apoptotic and anti-angiogenic actions of 2-methoxyestradiol and docosahexaenoic acid, the biologically derived active compounds from flaxseed diet, in preventing ovarian cancer. J. Ovarian Res. 12, 49–65 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Tapsell, L. C., Neale, E. P., Satija, A. & Hu, F. B. Foods, nutrients, and dietary patterns: interconnections and implications for dietary guidelines. Adv. Nutr. 7, 445–454 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Fanzo, J. et al. Nutrients, foods, diets, people: promoting healthy eating. Curr. Dev. Nutr. 4, nzaa069 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zhuang, C. et al. Small molecule-drug conjugates: a novel strategy for cancer-targeted treatment. Eur. J. Med. Chem. 163, 883–895 (2019).

    Article  CAS  PubMed  Google Scholar 

  34. Donaldson, M. S. Nutrition and cancer: a review of the evidence for an anti-cancer diet. Nutr. J. 3, 19 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  35. De Cicco, P. et al. Nutrition and breast cancer: a literature review on prevention, treatment and recurrence. Nutrients 11, 1514 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kim, M. et al. Thermohydrogel containing melanin for photothermal cancer therapy. Macromol. Biosci. 17, 1600371 (2017).

    Article  Google Scholar 

  37. Zhao, X. et al. Melanin-inspired design: preparing sustainable photothermal materials from lignin for energy generation. ACS Appl. Mater. Interfaces 13, 7600–7607 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Wang, K. et al. Melanin-perovskite composites for photothermal conversion. Adv. Energy Mater. 9, 1901753 (2019).

    Article  CAS  Google Scholar 

  39. Lunt, S. Y. & Vander Heiden, M. G. Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu. Rev. Cell Dev. Biol. 27, 441–464 (2011).

    Article  CAS  PubMed  Google Scholar 

  40. Gatenby, R. A. & Gillies, R. J. Why do cancers have high aerobic glycolysis? Nat. Rev. Cancer 4, 891–899 (2004).

    Article  CAS  PubMed  Google Scholar 

  41. Saeedi, M., Khezri, K., Zakaryaei, A. S. & Mohammadamini, H. A comprehensive review of the therapeutic potential of alpha-arbutin. Phytother. Res. 35, 4136–4154 (2021).

    Article  CAS  PubMed  Google Scholar 

  42. Zolghadri, S. et al. A comprehensive review on tyrosinase inhibitors. J. Enzym. Inhib. Med. Chem. 34, 279–309 (2019).

    Article  CAS  Google Scholar 

  43. Liu, J. L. et al. Spectroscopy and molecular docking analysis reveal structural specificity of flavonoids in the inhibition of alpha-glucosidase activity. Int. J. Biol. Macromol. 152, 981–989 (2020).

    Article  PubMed  Google Scholar 

  44. Prakash, J. et al. Tumor-targeted intracellular delivery of anticancer drugs through the mannose-6-phosphate/insulin-like growth factor II receptor. Int. J. Cancer 126, 1966–1981 (2010).

    Article  CAS  PubMed  Google Scholar 

  45. Sarna, M., Krzykawska-Serda, M., Jakubowska, M., Zadlo, A. & Urbanska, K. Melanin presence inhibits melanoma cell spread in mice in a unique mechanical fashion. Sci. Rep. 9, 9280 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Halaban, R. et al. Aberrant retention of tyrosinase in the endoplasmic reticulum mediates accelerated degradation of the enzyme and contributes to the dedifferentiated phenotype of amelanotic melanoma cells. Proc. Natl Acad. Sci. USA 94, 6210–6215 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Wellbrock, C. & Arozarena, I. Microphthalmia-associated transcription factor in melanoma development and MAP-kinase pathway targeted therapy. Pigment Cell Melanoma Res. 28, 390–406 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhao, X., Fiske, B., Kawakami, A., Li, J. & Fisher, D. E. Regulation of MITF stability by the USP13 deubiquitinase. Nat. Commun. 2, 414 (2011).

    Article  PubMed  Google Scholar 

  49. Wu, M. et al. c-Kit triggers dual phosphorylations, which couple activation and degradation of the essential melanocyte factor Mi. Genes Dev. 14, 301–312 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Gabra, M. B. I. et al. Dietary glutamine supplementation suppresses epigenetically-activated oncogenic pathways to inhibit melanoma tumour growth. Nat. Commun. 11, 3326 (2020).

    Article  Google Scholar 

  51. Gonzalez, P. S. et al. Mannose impairs tumour growth and enhances chemotherapy. Nature 563, 719 (2018).

    Article  CAS  PubMed  Google Scholar 

  52. Allen, T. M. & Cullis, P. R. Liposomal drug delivery systems: from concept to clinical applications. Adv. Drug Deliv. Rev. 65, 36–48 (2013).

    Article  CAS  PubMed  Google Scholar 

  53. Wu, M. X. & Yang, Y. W. Metal–organic framework (MOF)-based drug/cargo delivery and cancer therapy. Adv. Mater. 29, 1606134 (2017).

    Article  Google Scholar 

  54. Zahorowska, B., Crowe, P. J. & Yang, J. L. Combined therapies for cancer: a review of EGFR-targeted monotherapy and combination treatment with other drugs. J. Cancer Res. Clin. Oncol. 135, 1137–1148 (2009).

    Article  CAS  PubMed  Google Scholar 

  55. Wang, C. et al. Inducing and exploiting vulnerabilities for the treatment of liver cancer. Nature 574, 268–272 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Marullo, R. et al. The metabolic adaptation evoked by arginine enhances the effect of radiation in brain metastases. Sci. Adv. 7, eabg1964 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work is supported by the Key Program of National Natural Science Foundation of China (22235004) and Innovation Program of Shanghai Municipal Education Commission (2023ZKZD01) to W.B.; National Natural Science Foundation of China (grant numbers 82172091 and 82372122) and Shanghai Science and Technology Innovation Action Plan (grant numbers 23XD1422800 and 23S31900200) to Y. Wu; and National Science Foundation for the Young Scientists of China (grant number 32000948) and State Key Laboratory of Molecular Engineering of Polymers Project (Fudan University, grant number K2023-24) to Y.C.

Author information

Author notes

  1. These authors contributed equally: Yang Chen, Chaochao Wang, Yelin Wu.

Authors and Affiliations

  1. Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, Tongji University Cancer Center, School of Life Sciences and Technology, Tongji University, Shanghai, P. R. China

    Yang Chen,��Chaochao Wang, Yelin Wu, Yun Meng, Jieyun Shi & Wenbo Bu

  2. Department of Materials Science and State Key Laboratory of Molecular Engineering of Polymers, Academy for Engineering and Technology, Fudan University, Shanghai, P. R. China

    Yang Chen, Chaochao Wang, Ya Wang, Fan Wu, Huilin Zhang, Xingwu Jiang, Huiyan Li, Peiran Zhao & Wenbo Bu

  3. Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, P. R. China

    Huilin Zhang, Jinfeng Wu & Wenbo Bu

  4. Institute for Biomedical Materials and Devices (IBMD), Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia

    Yuen Yee Cheng & Dayong Jin

  5. Cedars-Sinai Cancer Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Bin Zheng

  6. Eastern Institute for Advanced Study, Eastern Institute of Technology, Ningbo, P. R. China

    Dayong Jin

Authors
  1. Yang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chaochao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yelin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ya Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yun Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Huilin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yuen Yee Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xingwu Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jieyun Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Huiyan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Peiran Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jinfeng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Bin Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Dayong Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Wenbo Bu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

W.B., Y.C., J.W. and D.J. conceived the study. Y.C., C.W. and Y. Wu designed and performed the experiments. C.W., Y. Wang, P.Z. and H.Z. synthesized and characterized MTyr–OANPs. Y.C., Y.M. and F.W. performed cell- and tumour-bearing mice-related experiments. X.J. and J.S. assisted with cell biological and animal experiments. B.Z., H.L., C.W. and Y.C. analysed the data. W.B., Y.C., C.W., J.W., D.J. and Y.Y.C. wrote the paper. All authors interpreted data, discussed results and contributed to the review, revision and finalization of the paper.

Corresponding authors

Correspondence to Jinfeng Wu, Dayong Jin or Wenbo Bu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Nanotechnology thanks Yale Yue and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

Extended data

Extended Data Fig. 1 MTyr-OANPs downregulated the expression of MMP9 and MMP2,and inhibited cell migration.

a, Immunofluorescence images of MMP9 and MMP2 in control and MTyr-OANPs treated cells (n = 3 biological replicates), scale bars, 50 μm. b and c, wound-healing assay in control and MTyr-OANPs treated cells (n = 3 biological replicates), scale bars, 50 μm. Data were represented as mean ± s.d., and P values were performed with one-way ANOVA followed by post hoc Tukey’s test.

Source data

Extended Data Fig. 2 The metabolite analysis of B16F10 cells after MTyr-OANPs or MTyr-OANPs + α-Arbutin co-treatment.

a, Principal Component Analysis (PCA) of metabolites measured by LC-MS in MTyr-OANP (72h after co-incubation) versus control cells (n = 3 biological replicates). b, Intracellular melanin content of cell in control, MTyr-OANPs treated, MTyr-OANPs and α-Arbutin co-treated cells after 72 h (results were presented as percentage relative to control, n = 3 biological replicates, means ± s.d.). c, Heat map of glycolysis intermediate metabolites in MTyr-OANPs and α-Arbutin co-treated cells (72 h after co-incubation) (n = 3 biological replicates). Colour bar is Z-score. d, Pyruvate activities of B16F10 cells after incubation with melanin for 48 h (p > 0.05, n = 5 biological replicates, means ± s.d.). P values were performed with Student’s t test (unpaired, two-tailed) or one-way ANOVA followed by post hoc Tukey’s test.

Source data

Extended Data Fig. 3 LC-MS results of melanin intermediates including L-DOPA, 5,6-DHI and 5,6-DHICA after MTyr-OANPs treatment for 72 h.

a, Mass spectra of intracellular L-DOPA content by LC-MS (n = 3 independent experiments). b, Quantitative results based on peak intensity (n = 3 independent experiments, means ± s.d., P value was performed with Student’s t test (unpaired, two-tailed). c, The mass spectra of DHI and DHICA by LC-MS (n = 3 independent experiments).

Source data

Extended Data Fig. 4 MTyr-OANPs promote melanin synthesis and related gene expression in murine and human-derived melanoma.

Pictures of resected B16F10 tumors (a) and Fontana-Masson staining results for melanin of tumor tissue sections (b) with or without MTyr-OANPs treatment (n = 3 biological replicates, scale bars, 100 μm). Relative mRNA expression of Tyr, Tyrp1 and Tyrp2 (c), tyrosinase activity and total melanin content (d) in PBS and MTyr-OANPs treated mice tumor after three injections (n = 3 biological replicates). e, mRNA expression of Mitf in A375 and Mewo cells co-cultured with MTyr-OANPs for 24 h. f and g, Immunohistochemistry results of MITF in mice tumors (n = 3 biological replicates, scale bars, 200 μm). Data were represented as mean ± s.d., and P values were performed with Student’s t test (unpaired, two-tailed).

Source data

Extended Data Fig. 5 Enhanced anti-tumor efficiency under MTyr-OANPs and 808 nm laser irradiation co-treatment.

a, Fluorescent images of Calcein-AM/PI-stained B16F10 cells incubated with 1 mg/mL MTyr-OANPs for 72 h and/or treated with 808 nm laser for 5 min. (red represents dead cells, and green represents live cells) (n = 3 independent experiments, scale bars, 100 μm). b, Temperature increase curves vs. irradiation time of mice tumors (n = 3 biological replicates, means ± s.d. and P values were performed with Student’s t test (unpaired, two-tailed)). c) Representative images of tumor-bearing mice in different treated groups (n = 5 independent mice). d, Representative images of mice in ‘MTyr-OANPs + Laser group’ within 49 days of observation. e, H&E staining of tumors in each groups after 6 days of treatment (n = 5 independent experiments, scale bars, 100 μm).

Source data

Extended Data Fig. 6 The anti-tumor efficiency of photothermal effect after increasing melanin production.

Laser power intensity screening to achieve the same photothermal effect as that in ‘MTyr-OANPs + Laser’ group’. a, The tumor temperature increase curves versus irradiation time under different laser power intensity. b, Temperature increase curves versus irradiation time in tumors in ‘MTyr-OANPs + Laser (0.28 W/cm2)’ and ‘Laser (0.32 W/cm2)’ groups (n = 4 biological replicates, means ± s.d.). c, Relative infrared thermal images of mice (n = 4 biological replicates). Tumor Growth curves (V/V0) (d) and Kaplan–Meimer survival curves (e) of B16F10 tumor-bearing mice treated with PBS, MTyr-OANPs, Laser (0.32 W/cm2), and MTyr-OANPs + Laser (0.28 W/cm2), n = 6 biological replicates, means ± s.d. P values were performed with Student’s t test (unpaired, two-tailed) or one-way ANOVA followed by post hoc Tukey’s test. The differences of survival curves were determined by the two-side log-rank test.

Source data

Supplementary information

Supplementary Information

Additional methods and Supplementary Figs. 1–16.

Reporting Summary

Supplementary Video 1

Body distribution of MTyr–OANPs in mice with time.

Statistical source data for Supplementary figures

Statistical source data for Supplementary Figs. 1–8, 11, 12 and 14.

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Figs. 3 and 6

Unprocessed western blots.

Source Data Extended Data Figs. 1–6

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Wang, C., Wu, Y. et al. Nutrient-delivery and metabolism reactivation therapy for melanoma. Nat. Nanotechnol. (2024). https://doi.org/10.1038/s41565-024-01690-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41565-024-01690-6

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research