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Targeting metastasis with nanomedicine

Abstract

Metastatic cancer remains difficult to treat. Nanomedicine formulations can accumulate in primary tumours and metastases and can be designed to target key components of the metastatic cascade, including cancer cell invasion, intravasation, circulation, extravasation and colonization. Eight antimetastatic nanomedicines are approved for clinical use, more than twenty antimetastatic nanomedicines are currently explored in clinical trials and various designs are preclinically explored. In this Review, we outline key in vitro and in vivo models to study metastatic cancer and discuss how the different steps of the metastatic cascade can be targeted by nanomedicines. Furthermore, we highlight the design of antimetastatic nanomedicines for tumour microenvironment modulation, active targeting, stimuli-responsive drug release, multidrug combination therapy, RNA delivery and immunotherapy. Finally, we explore key future milestones in this field, emphasizing the importance of patient stratification in the clinical testing and translation of antimetastatic nanomedicines.

Key points

  • Metastases cause most cancer deaths; yet, their onset and spread remain poorly understood, and preclinical studies mainly focus on primary tumors, creating a gap towards developing effective treatments against metastasis.

  • Preclinical models, ranging from in vitro platforms to animal systems, and offering trade-offs between experimental throughput and biological relevance, are essential to study the metastatic cascade and identify therapeutic targets.

  • Cancer nanomedicines, like most standard anticancer therapies, are not designed to target metastases and antimetastatic pathways, leaving ample room for better understanding drug targeting to and treatment of metastatic cancers.

  • Several nanomedicines are being developed to use strategies that extend beyond traditional EPR-based passive drug targeting, including stimuli-responsive and actively targeted systems, nucleic acid delivery, multidrug combinations, and nano-immunotherapy.

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Fig. 1: Primary tumour and metastasis incidence.
Fig. 2: The metastatic cascade and potential targets for therapeutic intervention.
Fig. 3: Preclinical models to study metastasis.
Fig. 4: Next-generation antimetastatic nanomedicines.

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References

  1. Talmadge, J. E. & Fidler, I. J. AACR centennial series: the biology of cancer metastasis: historical perspective. Cancer Res. 70, 5649–5669 (2010).

    Article  Google Scholar 

  2. Hoshino, A. et al. Tumour exosome integrins determine organotropic metastasis. Nature 527, 329–335 (2015).

    Article  Google Scholar 

  3. Welch, D. R. & Hurst, D. R. Defining the hallmarks of metastasis. Cancer Res. 79, 3011–3027 (2019).

    Article  Google Scholar 

  4. Paget, S. The distribution of secondary growths in cancer of the breast. Lancet 133, 571–573 (1889).

    Article  Google Scholar 

  5. Fares, J., Fares, M. Y., Khachfe, H. H., Salhab, H. A. & Fares, Y. Molecular principles of metastasis: a hallmark of cancer revisited. Signal Transduct. Target. Ther. 5, 28 (2020).

    Article  Google Scholar 

  6. Pantel, K. & Brakenhoff, R. H. Dissecting the metastatic cascade. Nat. Rev. Cancer 4, 448–456 (2004).

    Article  Google Scholar 

  7. Hunter, K. W., Amin, R., Deasy, S., Ha, N.-H. & Wakefield, L. Genetic insights into the morass of metastatic heterogeneity. Nat. Rev. Cancer 18, 211–223 (2018).

    Article  Google Scholar 

  8. Martínez-Jiménez, F. et al. Pan-cancer whole-genome comparison of primary and metastatic solid tumours. Nature 618, 333–341 (2023).

    Article  Google Scholar 

  9. Haffner, M. C. et al. Genomic and phenotypic heterogeneity in prostate cancer. Nat. Rev. Urol. 18, 79–92 (2021).

    Article  Google Scholar 

  10. Suh, J. H. et al. Current approaches to the management of brain metastases. Nat. Rev. Clin. Oncol. 17, 279–299 (2020).

    Article  Google Scholar 

  11. Abufaraj, M. et al. The role of surgery in metastatic bladder cancer: a systematic review. Eur. Urol. 73, 543–557 (2018).

    Article  Google Scholar 

  12. Mayer, E. L. & Burstein, H. J. Chemotherapy for metastatic breast cancer. Hematol. Oncol. Clin. North Am. 21, 257–272 (2007).

    Article  Google Scholar 

  13. Gerlinde, P. et al. A systematic review of the clinical effectiveness of first-line chemotherapy for adult patients with locally advanced or metastatic non-small cell lung cancer. Thorax 70, 359 (2015).

    Article  Google Scholar 

  14. Kirstein, M. M. et al. Targeted therapies in metastatic colorectal cancer: a systematic review and assessment of currently available data. Oncologist 19, 1156–1168 (2014).

    Article  Google Scholar 

  15. Lito, P., Rosen, N. & Solit, D. B. Tumor adaptation and resistance to RAF inhibitors. Nat. Med. 19, 1401–1409 (2013).

    Article  Google Scholar 

  16. Sabnis, A. J. & Bivona, T. G. Principles of resistance to targeted cancer therapy: lessons from basic and translational cancer biology. Trends Mol. Med. 25, 185–197 (2019).

    Article  Google Scholar 

  17. Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2020. CA Cancer J. Clin. 70, 7–30 (2020).

    Google Scholar 

  18. Hudock, N. L. et al. Future trends in incidence and long-term survival of metastatic cancer in the United States. Commun. Med. 3, 76 (2023).

    Article  Google Scholar 

  19. Gallicchio, L., Devasia, T. P., Tonorezos, E., Mollica, M. A. & Mariotto, A. Estimation of the number of individuals living with metastatic cancer in the United States. J. Natl Cancer Inst. 114, 1476–1483 (2022).

    Article  Google Scholar 

  20. Zhang, C. et al. Differences in stage of cancer at diagnosis, treatment, and survival by race and ethnicity among leading cancer types. JAMA Netw. Open3, e202950–e202950 (2020).

    Article  Google Scholar 

  21. Pallares, R. M., Mottaghy, F. M., Schulz, V., Kiessling, F. & Lammers, T. Nanoparticle diagnostics and theranostics in the clinic. J. Nucl. Med. 63, 1802 (2022).

    Article  Google Scholar 

  22. Maeda, H., Sawa, T. & Konno, T. Mechanism of tumor-targeted delivery of macromolecular drugs, including the EPR effect in solid tumor and clinical overview of the prototype polymeric drug SMANCS. J. Control. Release 74, 47–61 (2001).

    Article  Google Scholar 

  23. Nguyen, L. N. M. et al. The mechanisms of nanoparticle delivery to solid tumours. Nat. Rev. Bioeng. 2, 201–213  (2024).

    Article  Google Scholar 

  24. Harrington, K. J. et al. Effective targeting of solid tumors in patients with locally advanced cancers by radiolabeled pegylated liposomes. Clin. Cancer Res. 7, 243–254 (2001).

    Google Scholar 

  25. Miedema, I. H. C. et al. PET–CT imaging of polymeric nanoparticle tumor accumulation in patients. Adv. Mater. 34, 2201043 (2022).

    Article  Google Scholar 

  26. Lammers, T. Nanomedicine tumor targeting. Adv. Mater. 36, 2312169 (2024).

    Article  Google Scholar 

  27. van der Meel, R. et al. Smart cancer nanomedicine. Nat. Nanotechnol. 14, 1007–1017 (2019).

    Article  Google Scholar 

  28. Schroeder, A. et al. Treating metastatic cancer with nanotechnology. Nat. Rev. Cancer 12, 39–50 (2012).

    Article  Google Scholar 

  29. Kingston Benjamin, R., Syed Abdullah, M., Ngai, J., Sindhwani, S. & Chan Warren, C. W. Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning. Proc. Natl Acad. Sci. USA 116, 14937–14946 (2019).

    Article  Google Scholar 

  30. Miao, L., Lin, C. M. & Huang, L. Stromal barriers and strategies for the delivery of nanomedicine to desmoplastic tumors. J. Control. Release 219, 192–204 (2015).

    Article  Google Scholar 

  31. Gao, D. et al. Endothelial progenitor cells control the angiogenic switch in mouse lung metastasis. Science 319, 195–198 (2008).

    Article  Google Scholar 

  32. Pein, M. & Oskarsson, T. Microenvironment in metastasis: roadblocks and supportive niches. Am. J. Physiol. Cell Physiol. 309, C627–C638 (2015).

    Article  Google Scholar 

  33. Goel, S. et al. Sequential deconstruction of composite drug transport in metastatic breast cancer. Sci. Adv. 6, eaba4498 (2020).

    Article  Google Scholar 

  34. Goldman, E. et al. Nanoparticles target early-stage breast cancer metastasis in vivo. Nanotechnology 28, 43LT01 (2017).

    Article  Google Scholar 

  35. Psaila, B. & Lyden, D. The metastatic niche: adapting the foreign soil. Nat. Rev. Cancer 9, 285–293 (2009).

    Article  Google Scholar 

  36. De Lorenzi, F. et al. Analysis of nanomedicine primary tumor vs. metastasis targeting using clinical-stage core-crosslinked polymeric micelles. Cell Rep. 44, 8116086 (2025).

    Google Scholar 

  37. Benderski, K. et al. Analysis of multi-drug cancer nanomedicine. Nat. Nanotechnol. 20, 1163–1172 (2025).

    Article  Google Scholar 

  38. Lamouille, S., Xu, J. & Derynck, R. Molecular mechanisms of epithelial–mesenchymal transition. Nat. Rev. Mol. Cell Biol. 15, 178–196 (2014).

    Article  Google Scholar 

  39. Pastushenko, I. & Blanpain, C. EMT transition states during tumor progression and metastasis. Trends Cell Biol. 29, 212–226 (2019).

    Article  Google Scholar 

  40. Guarino, M. Epithelial–mesenchymal transition and tumour invasion. Int. J. Biochem. Cell Biol. 39, 2153–2160 (2007).

    Article  Google Scholar 

  41. Ni, T. et al. Snail1-dependent p53 repression regulates expansion and activity of tumour-initiating cells in breast cancer. Nat. Cell Biol. 18, 1221–1232 (2016).

    Article  Google Scholar 

  42. Krebs, A. M. et al. The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat. Cell Biol. 19, 518–529 (2017).

    Article  Google Scholar 

  43. Yang, J. et al. Twist, a master regulator of morphogenesis, plays an essential role in tumor metastasis. Cell 117, 927–939 (2004).

    Article  Google Scholar 

  44. Chen, A. & Koehler, A. N. Transcription factor inhibition: lessons learned and emerging targets. Trends Mol. Med. 26, 508–518 (2020).

    Article  Google Scholar 

  45. Pandelakis, M., Delgado, E. & Ebrahimkhani, M. R. CRISPR-based synthetic transcription factors in vivo: the future of therapeutic cellular programming. Cell Syst. 10, 1–14 (2020).

    Article  Google Scholar 

  46. Peng, D. H. et al. ZEB1 induces LOXL2-mediated collagen stabilization and deposition in the extracellular matrix to drive lung cancer invasion and metastasis. Oncogene 36, 1925–1938 (2017).

    Article  Google Scholar 

  47. Chen, L. et al. Metastasis is regulated via microRNA-200/ZEB1 axis control of tumour cell PD-L1 expression and intratumoral immunosuppression. Nat. Commun. 5, 5241 (2014).

    Article  Google Scholar 

  48. Pecot, C. V. et al. Tumour angiogenesis regulation by the miR-200 family. Nat. Commun. 4, 2427 (2013).

    Article  Google Scholar 

  49. Bordeleau, F. et al. Matrix stiffening promotes a tumor vasculature phenotype. Proc. Natl Acad. Sci. USA 114, 492–497 (2017).

    Article  Google Scholar 

  50. Kessenbrock, K., Plaks, V. & Werb, Z. Matrix metalloproteinases: regulators of the tumor microenvironment. Cell 141, 52–67 (2010).

    Article  Google Scholar 

  51. Winer, A., Adams, S. & Mignatti, P. Matrix metalloproteinase inhibitors in cancer therapy: turning past failures into future successes. Mol. Cancer Ther. 17, 1147–1155 (2018).

    Article  Google Scholar 

  52. Ling, B. et al. A novel immunotherapy targeting MMP-14 limits hypoxia, immune suppression and metastasis in triple-negative breast cancer models. Oncotarget 8, 58372–58385 (2017).

    Article  Google Scholar 

  53. Yao, Q., Kou, L., Tu, Y. & Zhu, L. MMP-responsive ‘Smart’ drug delivery and tumor targeting. Trends Pharmacol. Sci. 39, 766–781 (2018).

    Article  Google Scholar 

  54. Isaacson, K. J., Martin Jensen, M., Subrahmanyam, N. B. & Ghandehari, H. Matrix-metalloproteinases as targets for controlled delivery in cancer: an analysis of upregulation and expression. J. Control. Release 259, 62–75 (2017).

    Article  Google Scholar 

  55. Reymond, N., d’Água, B. B. & Ridley, A. J. Crossing the endothelial barrier during metastasis. Nat. Rev. Cancer 13, 858–870 (2013).

    Article  Google Scholar 

  56. Roh-Johnson, M. et al. Macrophage contact induces RhoA GTPase signaling to trigger tumor cell intravasation. Oncogene 33, 4203–4212 (2014).

    Article  Google Scholar 

  57. Ahirwar, D. K. et al. Fibroblast-derived CXCL12 promotes breast cancer metastasis by facilitating tumor cell intravasation. Oncogene 37, 4428–4442 (2018).

    Article  Google Scholar 

  58. Harney, A. S. et al. Real-time imaging reveals local, transient vascular permeability, and tumor cell intravasation stimulated by TIE2hi macrophage-derived VEGFA. Cancer Discov. 5, 932–943 (2015).

    Article  Google Scholar 

  59. Goel, H. L. & Mercurio, A. M. VEGF targets the tumour cell. Nat. Rev. Cancer 13, 871–882 (2013).

    Article  Google Scholar 

  60. Bottsford-Miller, J. N., Coleman, R. L. & Sood, A. K. Resistance and escape from antiangiogenesis therapy: clinical implications and future strategies. J. Clin. Oncol. 30, 4026–4034 (2012).

    Article  Google Scholar 

  61. Donato, C. et al. Hypoxia triggers the intravasation of clustered circulating tumor cells. Cell Rep. 32, 108105 (2020).

    Article  Google Scholar 

  62. Jain, R. K. Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy. Science 307, 58–62 (2005).

    Article  Google Scholar 

  63. Magnussen, A. L. & Mills, I. G. Vascular normalisation as the stepping stone into tumour microenvironment transformation. Br. J. Cancer 125, 324–336 (2021).

    Article  Google Scholar 

  64. Martin, J. D., Seano, G. & Jain, R. K. Normalizing function of tumor vessels: progress, opportunities, and challenges. Annu. Rev. Physiol. 81, 505–534 (2019).

    Article  Google Scholar 

  65. Mpekris, F. et al. Normalizing tumor microenvironment with nanomedicine and metronomic therapy to improve immunotherapy. J. Control. Release 345, 190–199 (2022).

    Article  Google Scholar 

  66. Dong, X. et al. Anti-VEGF therapy improves EGFR-vIII-CAR-T cell delivery and efficacy in syngeneic glioblastoma models in mice. J. Immunother. Cancer 11, e005583 (2023).

    Article  Google Scholar 

  67. Jain, R. K. & Stylianopoulos, T. Delivering nanomedicine to solid tumors. Nat. Rev. Clin. Oncol. 7, 653–664 (2010).

    Article  Google Scholar 

  68. Chauhan, V. P. et al. Normalization of tumour blood vessels improves the delivery of nanomedicines in a size-dependent manner. Nat. Nanotechnol. 7, 383–388 (2012).

    Article  Google Scholar 

  69. Chauhan, V. P. et al. Angiotensin inhibition enhances drug delivery and potentiates chemotherapy by decompressing tumour blood vessels. Nat. Commun. 4, 2516 (2013).

    Article  Google Scholar 

  70. Panagi, M. et al. Polymeric micelles effectively reprogram the tumor microenvironment to potentiate nano-immunotherapy in mouse breast cancer models. Nat. Commun. 13, 7165 (2022).

    Article  Google Scholar 

  71. Schuster, E. et al. Better together: circulating tumor cell clustering in metastatic cancer. Trends Cancer 7, 1020–1032 (2021).

    Article  Google Scholar 

  72. Aceto, N. et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 158, 1110–1122 (2014).

    Article  Google Scholar 

  73. Ming, Y. et al. Circulating tumor cells: from theory to nanotechnology-based detection. Front. Pharmacol. 8, 35 (2017).

    Article  Google Scholar 

  74. Bhana, S., Wang, Y. & Huang, X. Nanotechnology for enrichment and detection of circulating tumor cells. Nanomedicine 10, 1973–1990 (2015).

    Article  Google Scholar 

  75. Liu, X. et al. Homophilic CD44 interactions mediate tumor cell aggregation and polyclonal metastasis in patient-derived breast cancer models. Cancer Discov. 9, 96–113 (2019).

    Article  Google Scholar 

  76. Yao, J. et al. Neovasculature and circulating tumor cells dual-targeting nanoparticles for the treatment of the highly-invasive breast cancer. Biomaterials 113, 1–17 (2017).

    Article  Google Scholar 

  77. Kesharwani, P., Chadar, R., Sheikh, A., Rizg, W. Y. & Safhi, A. Y. CD44-targeted nanocarrier for cancer therapy. Front. Pharmacol. 12, 800481 (2021).

    Article  Google Scholar 

  78. Perea Paizal, J., Au, S. H. & Bakal, C. Squeezing through the microcirculation: survival adaptations of circulating tumour cells to seed metastasis. Br. J. Cancer 124, 58–65 (2021).

    Article  Google Scholar 

  79. Au, S. H. et al. Clusters of circulating tumor cells traverse capillary-sized vessels. Proc. Natl Acad. Sci. USA 113, 4947–4952 (2016).

    Article  Google Scholar 

  80. Hamidi, H. & Ivaska, J. Every step of the way: integrins in cancer progression and metastasis. Nat. Rev. Cancer 18, 533–548 (2018).

    Article  Google Scholar 

  81. Chen, M. B. et al. Inflamed neutrophils sequestered at entrapped tumor cells via chemotactic confinement promote tumor cell extravasation. Proc. Natl Acad. Sci. USA 115, 7022–7027 (2018).

    Article  Google Scholar 

  82. Chambers, A. F., Groom, A. C. & MacDonald, I. C. Dissemination and growth of cancer cells in metastatic sites. Nat. Rev. Cancer 2, 563–572 (2002).

    Article  Google Scholar 

  83. Ganesh, K. & Massague, J. Targeting metastatic cancer. Nat. Med. 27, 34–44 (2021).

    Article  Google Scholar 

  84. Steeg, P. S. Targeting metastasis. Nat. Rev. Cancer 16, 201–218 (2016).

    Article  Google Scholar 

  85. Liu, Y. & Cao, X. Characteristics and significance of the pre-metastatic niche. Cancer Cell 30, 668–681 (2016).

    Article  Google Scholar 

  86. Miller, B. W. et al. Targeting the LOX/hypoxia axis reverses many of the features that make pancreatic cancer deadly: inhibition of LOX abrogates metastasis and enhances drug efficacy. EMBO Mol. Med. 7, 1063–1076 (2015).

    Article  Google Scholar 

  87. Saatci, O. et al. Targeting lysyl oxidase (LOX) overcomes chemotherapy resistance in triple negative breast cancer. Nat. Commun. 11, 2416 (2020).

    Article  Google Scholar 

  88. Cox, T. R. et al. The hypoxic cancer secretome induces pre-metastatic bone lesions through lysyl oxidase. Nature 522, 106–110 (2015).

    Article  Google Scholar 

  89. Erler, J. T. et al. Hypoxia-induced lysyl oxidase is a critical mediator of bone marrow cell recruitment to form the premetastatic niche. Cancer Cell 15, 35–44 (2009).

    Article  Google Scholar 

  90. Natarajan, S. et al. Collagen remodeling in the hypoxic tumor-mesothelial niche promotes ovarian cancer metastasis. Cancer Res. 79, 2271–2284 (2019).

    Article  Google Scholar 

  91. Kanapathipillai, M. et al. Inhibition of mammary tumor growth using lysyl oxidase-targeting nanoparticles to modify extracellular matrix. Nano Lett. 12, 3213–3217 (2012).

    Article  Google Scholar 

  92. Wei, D. et al. Stroma-targeted nanoparticles that remodel stromal alignment to enhance drug delivery and improve the antitumor efficacy of Nab-paclitaxel in pancreatic ductal adenocarcinoma models. Nano Today 45, 101533 (2022).

    Article  Google Scholar 

  93. Lee, E. et al. Breast cancer cells condition lymphatic endothelial cells within pre-metastatic niches to promote metastasis. Nat. Commun. 5, 4715 (2014).

    Article  Google Scholar 

  94. Pein, M. et al. Metastasis-initiating cells induce and exploit a fibroblast niche to fuel malignant colonization of the lungs. Nat. Commun. 11, 1494 (2020).

    Article  Google Scholar 

  95. Lu, Z. et al. Epigenetic therapy inhibits metastases by disrupting premetastatic niches. Nature 579, 284–290 (2020).

    Article  Google Scholar 

  96. Zhen, Z. et al. Protein nanocage mediated fibroblast-activation protein targeted photoimmunotherapy to enhance cytotoxic T cell infiltration and tumor control. Nano Lett. 17, 862–869 (2017).

    Article  Google Scholar 

  97. Lang, J. et al. Reshaping prostate tumor microenvironment to suppress metastasis via cancer-associated fibroblast inactivation with peptide-assembly-based nanosystem. ACS Nano 13, 12357–12371 (2019).

    Article  Google Scholar 

  98. Phan, T. G. & Croucher, P. I. The dormant cancer cell life cycle. Nat. Rev. Cancer 20, 398–411 (2020).

    Article  Google Scholar 

  99. Price, T. T. et al. Dormant breast cancer micrometastases reside in specific bone marrow niches that regulate their transit to and from bone. Sci. Transl. Med. 8, 340ra373 (2016).

    Article  Google Scholar 

  100. Khalil, B. D. et al. An NR2F1-specific agonist suppresses metastasis by inducing cancer cell dormancy. J. Exp. Med. 219, e20210836 (2022).

    Article  Google Scholar 

  101. Tiram, G. et al. Identification of dormancy-associated MicroRNAs for the design of osteosarcoma-targeted dendritic polyglycerol nanopolyplexes. ACS Nano 10, 2028–2045 (2016).

    Article  Google Scholar 

  102. Angus, L. et al. The genomic landscape of metastatic breast cancer highlights changes in mutation and signature frequencies. Nat. Genet. 51, 1450–1458 (2019).

    Article  Google Scholar 

  103. Bertucci, F. et al. Genomic characterization of metastatic breast cancers. Nature 569, 560–564 (2019).

    Article  Google Scholar 

  104. McDonald, O. G. et al. Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis. Nat. Genet. 49, 367–376 (2017).

    Article  Google Scholar 

  105. Chen, Q. & Massagué, J. Molecular pathways: VCAM-1 as a potential therapeutic target in metastasis. Clin. Cancer Res. 18, 5520–5525 (2012).

    Article  Google Scholar 

  106. Cheng, V. W. T. et al. VCAM-1-targeted MRI enables detection of brain micrometastases from different primary tumors. Clin. Cancer Res. 25, 533–543 (2019).

    Article  Google Scholar 

  107. Schneider, J. G., Amend, S. R. & Weilbaecher, K. N. Integrins and bone metastasis: Integrating tumor cell and stromal cell interactions. Bone 48, 54–65 (2011).

    Article  Google Scholar 

  108. Ross, M. H. et al. Bone-induced expression of integrin β3 enables targeted nanotherapy of breast cancer metastases. Cancer Res. 77, 6299–6312 (2017).

    Article  Google Scholar 

  109. Khawar, I. A., Kim, J. H. & Kuh, H.-J. Improving drug delivery to solid tumors: priming the tumor microenvironment. J. Control. Release 201, 78–89 (2015).

    Article  Google Scholar 

  110. Jiang, W., Chan, C. K., Weissman, I. L., Kim, B. Y. S. & Hahn, S. M. Immune priming of the tumor microenvironment by radiation. Trends Cancer 2, 638–645 (2016).

    Article  Google Scholar 

  111. Zinger, A. et al. Collagenase nanoparticles enhance the penetration of drugs into pancreatic tumors. ACS Nano 13, 11008–11021 (2019).

    Article  Google Scholar 

  112. Kooshkaki, O. et al. Combination of ipilimumab and nivolumab in cancers: from clinical practice to ongoing clinical trials. Int. J. Mol. Sci. 21, 4427 (2020).

    Article  Google Scholar 

  113. Hellmann, M. D. et al. Nivolumab plus ipilimumab in advanced non-small-cell lung cancer. N. Engl. J. Med. 381, 2020–2031 (2019).

    Article  Google Scholar 

  114. Yang, L., Pang, Y. & Moses, H. L. TGF-β and immune cells: an important regulatory axis in the tumor microenvironment and progression. Trends Immunol. 31, 220–227 (2010).

    Article  Google Scholar 

  115. Dai, L. et al. TGF-β blockade-improved chemo-immunotherapy with pH/ROS cascade-responsive micelle via tumor microenvironment remodeling. Biomaterials 276, 121010 (2021).

    Article  Google Scholar 

  116. Zhou, F., Wang, M., Luo, T., Qu, J. & Chen, W. R. Photo-activated chemo-immunotherapy for metastatic cancer using a synergistic graphene nanosystem. Biomaterials 265, 120421 (2021).

    Article  Google Scholar 

  117. Park, J. et al. Combination delivery of TGF-β inhibitor and IL-2 by nanoscale liposomal polymeric gels enhances tumour immunotherapy. Nat. Mater. 11, 895–905 (2012).

    Article  Google Scholar 

  118. Wang, B. et al. Genetically engineered hematopoietic stem cells deliver TGF-beta inhibitor to enhance bone metastases immunotherapy. Adv. Sci. 9, e2201451 (2022).

    Article  Google Scholar 

  119. Borcoman, E. et al. Novel patterns of response under immunotherapy. Ann. Oncol. 30, 385–396 (2019).

    Article  Google Scholar 

  120. Gajic, Z. Z., Deshpande, A., Legut, M., Imieliński, M. & Sanjana, N. E. Recurrent somatic mutations as predictors of immunotherapy response. Nat. Commun. 13, 3938 (2022).

    Article  Google Scholar 

  121. Murciano-Goroff, Y. R., Warner, A. B. & Wolchok, J. D. The future of cancer immunotherapy: microenvironment-targeting combinations. Cell Res. 30, 507–519 (2020).

    Article  Google Scholar 

  122. Wakefield, L., Agarwal, S. & Tanner, K. Preclinical models for drug discovery for metastatic disease. Cell 186, 1792–1813 (2023).

    Article  Google Scholar 

  123. Zhu, G. et al. Intertwining DNA–RNA nanocapsules loaded with tumor neoantigens as synergistic nanovaccines for cancer immunotherapy. Nat. Commun. 8, 1482 (2017).

    Article  Google Scholar 

  124. Hebert, J. D., Neal, J. W. & Winslow, M. M. Dissecting metastasis using preclinical models and methods. Nat. Rev. Cancer 23, 391–407 (2023).

    Article  Google Scholar 

  125. Vargo-Gogola, T. & Rosen, J. M. Modelling breast cancer: one size does not fit all. Nat. Rev. Cancer 7, 659–672 (2007).

    Article  Google Scholar 

  126. Francia, G., Cruz-Munoz, W., Man, S., Xu, P. & Kerbel, R. S. Mouse models of advanced spontaneous metastasis for experimental therapeutics. Nat. Rev. Cancer 11, 135–141 (2011).

    Article  Google Scholar 

  127. Zhang, W. et al. Comparative study of subcutaneous and orthotopic mouse models of prostate cancer: vascular perfusion, vasculature density, hypoxic burden and BB2r-targeting efficacy. Sci. Rep. 9, 11117 (2019).

    Article  Google Scholar 

  128. Fernandez, J. L. et al. A comparative analysis of orthotopic and subcutaneous pancreatic tumour models: tumour microenvironment and drug delivery. Cancers 15, 5415 (2023).

    Article  Google Scholar 

  129. Gómez-Cuadrado, L., Tracey, N., Ma, R., Qian, B. & Brunton, V. G. Mouse models of metastasis: progress and prospects. Dis. Model. Mech. 10, 1061–1074 (2017).

    Article  Google Scholar 

  130. Johansen, P. L., Fenaroli, F., Evensen, L., Griffiths, G. & Koster, G. Optical micromanipulation of nanoparticles and cells inside living zebrafish. Nat. Commun. 7, 10974 (2016).

    Article  Google Scholar 

  131. Sieber, S. et al. Zebrafish as a predictive screening model to assess macrophage clearance of liposomes in vivo. Nanomedicine 17, 82–93 (2019).

    Article  Google Scholar 

  132. Papadopoulou, P. et al. Phase-separated lipid-based nanoparticles: selective behavior at the nano-bio interface. Adv. Mater. 36, 2310872 (2024).

    Article  Google Scholar 

  133. Merrifield, G. D. et al. Rapid and recoverable in vivo magnetic resonance imaging of the adult zebrafish at 7T. Magnetic Reson. Imaging 37, 9–15 (2017).

    Article  Google Scholar 

  134. De Lorenzi, F. et al. Engineering mesoscopic 3D tumor models with a self-organizing vascularized matrix. Adv. Mater. 36, 2303196 (2024).

    Article  Google Scholar 

  135. Park, W., Lee, J.-S., Gao, G., Kim, B. S. & Cho, D.-W. 3D bioprinted multilayered cerebrovascular conduits to study cancer extravasation mechanism related with vascular geometry. Nat. Commun. 14, 7696 (2023).

    Article  Google Scholar 

  136. Chen, Y. et al. 3D bioprinted tumor model with extracellular matrix enhanced bioinks for nanoparticle evaluation. Biofabrication 14, 025002 (2022).

    Article  Google Scholar 

  137. Sharifi, M. et al. 3D bioprinting of engineered breast cancer constructs for personalized and targeted cancer therapy. J. Control. Release 333, 91–106 (2021).

    Article  Google Scholar 

  138. Chen, M. B. et al. On-chip human microvasculature assay for visualization and quantification of tumor cell extravasation dynamics. Nat. Protoc. 12, 865–880 (2017).

    Article  Google Scholar 

  139. Guy, J.-B. et al. Evaluation of the cell invasion and migration process: a comparison of the video microscope-based scratch wound assay and the boyden chamber assay. J. Vis. Exp. 129, e56337 (2017).

    Google Scholar 

  140. Li, Y., Vulpe, C., Lammers, T. & Pallares, R. M. Assessing inorganic nanoparticle toxicity through omics approaches. Nanoscale 16, 15928–15945 (2024).

    Article  Google Scholar 

  141. Kenny, P. A. et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol. Oncol. 1, 84–96 (2007).

    Article  Google Scholar 

  142. Priwitaningrum, D. L. et al. Tumor stroma-containing 3D spheroid arrays: a tool to study nanoparticle penetration. J. Control. Release 244, 257–268 (2016).

    Article  Google Scholar 

  143. Priwitaningrum, D. L. et al. Evaluation of paclitaxel-loaded polymeric nanoparticles in 3D tumor model: impact of tumor stroma on penetration and efficacy. Drug Deliv. Transl. Res. 13, 1470–1483 (2023).

    Article  Google Scholar 

  144. Viegas, J., Costa, S., Dias, S., Pereira, C. L. & Sarmento, B. Patient-derived melanoma immune-tumoroids as a platform for precise high throughput drug screening. Adv. Sci. 11, 2408707 (2024).

    Article  Google Scholar 

  145. Hsieh, P.-H. et al. Dual-responsive polypeptide nanoparticles attenuate tumor-associated stromal desmoplasia and anticancer through programmable dissociation. Biomaterials 284, 121469 (2022).

    Article  Google Scholar 

  146. Rice, A. J. et al. Matrix stiffness induces epithelial–mesenchymal transition and promotes chemoresistance in pancreatic cancer cells. Oncogenesis 6, e352–e352 (2017).

    Article  Google Scholar 

  147. Hapach, L. A., Mosier, J. A., Wang, W. & Reinhart-King, C. A. Engineered models to parse apart the metastatic cascade. npj Precis. Oncol. 3, 20 (2019).

    Article  Google Scholar 

  148. Ingber, D. E. Human organs-on-chips for disease modelling, drug development and personalized medicine. Nat. Rev. Genet. 23, 467–491 (2022).

    Article  Google Scholar 

  149. Jeon, J. S. et al. Generation of 3D functional microvascular networks with human mesenchymal stem cells in microfluidic systems. Integr. Biol. 6, 555–563 (2014).

    Article  Google Scholar 

  150. Leung, C. M. et al. A guide to the organ-on-a-chip. Nat. Rev. Methods Primers 2, 33 (2022).

    Article  Google Scholar 

  151. Rodrigues, J., Heinrich, M. A., Teixeira, L. M. & Prakash, J. 3D in vitro model (R)evolution: unveiling tumor–stroma interactions. Trends Cancer 7, 249–264 (2021).

    Article  Google Scholar 

  152. Barbato, M. G. et al. A permeable on-chip microvasculature for assessing the transport of macromolecules and polymeric nanoconstructs. J. Colloid Interface Sci. 594, 409–423 (2021).

    Article  Google Scholar 

  153. Straehla, J. P. et al. A predictive microfluidic model of human glioblastoma to assess trafficking of blood–brain barrier-penetrant nanoparticles. Proc. Natl Acad. Sci. USA 119, e2118697119 (2022).

    Article  Google Scholar 

  154. Jin, X. et al. A metastasis map of human cancer cell lines. Nature 588, 331–336 (2020).

    Article  Google Scholar 

  155. Kather, J. N. et al. High-throughput screening of combinatorial immunotherapies with patient-specific in silico models of metastatic colorectal cancer. Cancer Res. 78, 5155–5163 (2018).

    Article  Google Scholar 

  156. Lyass, O. et al. Correlation of toxicity with pharmacokinetics of pegylated liposomal doxorubicin (Doxil) in metastatic breast carcinoma. Cancer 89, 1037–1047 (2000).

    Article  Google Scholar 

  157. Fukuda, A. et al. Comparison of the adverse event profiles of conventional and liposomal formulations of doxorubicin using the FDA adverse event reporting system. PLoS ONE 12, e0185654 (2017).

    Article  Google Scholar 

  158. Ibrahim, N. K. et al. Phase I and pharmacokinetic study of ABI-007, a cremophor-free, protein-stabilized, nanoparticle formulation of paclitaxel1. Clin. Cancer Res. 8, 1038–1044 (2002).

    Google Scholar 

  159. Ranade, A. A. et al. Clinical and economic implications of the use of nanoparticle paclitaxel (Nanoxel) in India. Ann. Oncol. 24, v6–v12 (2013).

    Article  Google Scholar 

  160. Verry, C. et al. Targeting brain metastases with ultrasmall theranostic nanoparticles, a first-in-human trial from an MRI perspective. Sci. Adv. 6, eaay5279 (2020).

    Article  Google Scholar 

  161. Bonvalot, S. et al. NBTXR3, a first-in-class radioenhancer hafnium oxide nanoparticle, plus radiotherapy versus radiotherapy alone in patients with locally advanced soft-tissue sarcoma (Act.In.Sarc): a multicentre, phase 2–3, randomised, controlled trial. Lancet Oncol. 20, 1148–1159 (2019).

    Article  Google Scholar 

  162. Krauss, A. C. et al. FDA approval summary: (Daunorubicin and Cytarabine) liposome for injection for the treatment of adults with high-risk acute myeloid leukemia. Clin. Cancer Res. 25, 2685–2690 (2019).

    Article  Google Scholar 

  163. Irvine, D. J. & Dane, E. L. Enhancing cancer immunotherapy with nanomedicine. Nat. Rev. Immunol. 20, 321–334 (2020).

    Article  Google Scholar 

  164. Maeda, H. Toward a full understanding of the EPR effect in primary and metastatic tumors as well as issues related to its heterogeneity. Adv. Drug Deliv. Rev. 91, 3–6 (2015).

    Article  Google Scholar 

  165. Miller, M. A. et al. Tumour-associated macrophages act as a slow-release reservoir of nano-therapeutic Pt(IV) pro-drug. Nat. Commun. 6, 8692 (2015).

    Article  Google Scholar 

  166. Karimi, M. et al. Smart micro/nanoparticles in stimulus-responsive drug/gene delivery systems. Chem. Soc. Rev. 45, 1457–1501 (2016).

    Article  Google Scholar 

  167. Zagar, T. M. et al. Two phase I dose-escalation/pharmacokinetics studies of low temperature liposomal doxorubicin (LTLD) and mild local hyperthermia in heavily pretreated patients with local regionally recurrent breast cancer. Int. J. Hyperthermia 30, 285–294 (2014).

    Article  Google Scholar 

  168. Lyon, P. C. et al. Safety and feasibility of ultrasound-triggered targeted drug delivery of doxorubicin from thermosensitive liposomes in liver tumours (TARDOX): a single-centre, open-label, phase 1 trial. Lancet Oncol. 19, 1027–1039 (2018).

    Article  Google Scholar 

  169. Hossann, M. et al. Proteins and cholesterol lipid vesicles are mediators of drug release from thermosensitive liposomes. J. Control. Release 162, 400–406 (2012).

    Article  Google Scholar 

  170. Xu, R. et al. An injectable nanoparticle generator enhances delivery of cancer therapeutics. Nat. Biotechnol. 34, 414–418 (2016).

    Article  Google Scholar 

  171. Donahue, N. D., Acar, H. & Wilhelm, S. Concepts of nanoparticle cellular uptake, intracellular trafficking, and kinetics in nanomedicine. Adv. Drug Deliv. Rev. 143, 68–96 (2019).

    Article  Google Scholar 

  172. Su, J. et al. Bioinspired nanoparticles with NIR-controlled drug release for synergetic chemophotothermal therapy of metastatic breast cancer. Adv. Funct. Mater. 26, 7495–7506 (2016).

    Article  Google Scholar 

  173. Sun, W. et al. Bone-targeted nanoplatform combining zoledronate and photothermal therapy to treat breast cancer bone metastasis. ACS Nano 13, 7556–7567 (2019).

    Article  Google Scholar 

  174. Xie, Z. et al. Emerging combination strategies with phototherapy in cancer nanomedicine. Chem. Soc. Rev. 49, 8065–8087 (2020).

    Article  Google Scholar 

  175. Ngwa, W. et al. Using immunotherapy to boost the abscopal effect. Nat. Rev. Cancer 18, 313–322 (2018).

    Article  Google Scholar 

  176. Rosenblum, D., Joshi, N., Tao, W., Karp, J. M. & Peer, D. Progress and challenges towards targeted delivery of cancer therapeutics. Nat. Commun. 9, 1410 (2018).

    Article  Google Scholar 

  177. Vázquez-Ríos, A. J. et al. Exosome-mimetic nanoplatforms for targeted cancer drug delivery. J. Nanobiotechnol. 17, 85 (2019).

    Article  Google Scholar 

  178. Kirpotin, D. B. et al. Antibody targeting of long-circulating lipidic nanoparticles does not increase tumor localization but does increase internalization in animal models. Cancer Res. 66, 6732–6740 (2006).

    Article  Google Scholar 

  179. Zhu, G. & Chen, X. Aptamer-based targeted therapy. Adv. Drug Deliv. Rev. 134, 65–78 (2018).

    Article  Google Scholar 

  180. Zhao, Z. et al. Dual-active targeting liposomes drug delivery system for bone metastatic breast cancer: synthesis and biological evaluation. Chem. Phys. Lipids 223, 104785 (2019).

    Article  Google Scholar 

  181. Kunjachan, S. et al. Passive versus active tumor targeting using RGD- and NGR-modified polymeric nanomedicines. Nano Lett. 14, 972–981 (2014).

    Article  Google Scholar 

  182. Wilhelm, S. et al. Analysis of nanoparticle delivery to tumours. Nat. Rev. Mater. 1, 1–12 (2016).

    Article  Google Scholar 

  183. van der Meel, R., Vehmeijer, L. J. C., Kok, R. J., Storm, G. & van Gaal, E. V. B. Ligand-targeted particulate nanomedicines undergoing clinical evaluation: current status. Adv. Drug Deliv. Rev. 65, 1284–1298 (2013).

    Article  Google Scholar 

  184. O’Brien Laramy, M. N., Luthra, S., Brown, M. F. & Bartlett, D. W. Delivering on the promise of protein degraders. Nat. Rev. Drug Discov. 22, 410–427 (2023).

    Article  Google Scholar 

  185. Regenold, M. et al. Turning down the heat: the case for mild hyperthermia and thermosensitive liposomes. Nanomedicine 40, 102484 (2022).

    Article  Google Scholar 

  186. Mura, S., Nicolas, J. & Couvreur, P. Stimuli-responsive nanocarriers for drug delivery. Nat. Mater. 12, 991–1003 (2013).

    Article  Google Scholar 

  187. Ma, L., Kohli, M. & Smith, A. Nanoparticles for combination drug therapy. ACS Nano 7, 9518–9525 (2013).

    Article  Google Scholar 

  188. Lu, J. et al. Nano-enabled pancreas cancer immunotherapy using immunogenic cell death and reversing immunosuppression. Nat. Commun. 8, 1811 (2017).

    Article  Google Scholar 

  189. Yin, J. et al. pH-Sensitive nano-complexes overcome drug resistance and inhibit metastasis of breast cancer by silencing Akt expression. Theranostics 7, 4204 (2017).

    Article  Google Scholar 

  190. Detappe, A. et al. Molecular bottlebrush prodrugs as mono- and triplex combination therapies for multiple myeloma. Nat. Nanotechnol. 18, 184–192 (2023).

    Article  Google Scholar 

  191. Pitt, J. M. et al. Resistance mechanisms to immune-checkpoint blockade in cancer: tumor-intrinsic and -extrinsic factors. Immunity 44, 1255–1269 (2016).

    Article  Google Scholar 

  192. Zhang, Y. et al. Cargo-free immunomodulatory nanoparticles combined with anti-PD-1 antibody for treating metastatic breast cancer. Biomaterials 269, 120666 (2021).

    Article  Google Scholar 

  193. Reda, M. et al. Development of a nanoparticle-based immunotherapy targeting PD-L1 and PLK1 for lung cancer treatment. Nat. Commun. 13, 4261 (2022).

    Article  Google Scholar 

  194. Duan, X., Chan, C. & Lin, W. Nanoparticle-mediated immunogenic cell death enables and potentiates cancer immunotherapy. Angew. Chem. Int. Ed. 58, 670–680 (2019).

    Article  Google Scholar 

  195. Feng, B. et al. Binary cooperative prodrug nanoparticles improve immunotherapy by synergistically modulating immune tumor microenvironment. Adv. Mater. 30, 1803001 (2018).

    Article  Google Scholar 

  196. McLaughlin, M. et al. Inflammatory microenvironment remodelling by tumour cells after radiotherapy. Nat. Rev. Cancer 20, 203–217 (2020).

    Article  Google Scholar 

  197. Luo, M. et al. Synergistic STING activation by PC7A nanovaccine and ionizing radiation improves cancer immunotherapy. J. Control. Release 300, 154–160 (2019).

    Article  Google Scholar 

  198. Locati, M., Curtale, G. & Mantovani, A. Diversity, mechanisms, and significance of macrophage plasticity. Annu. Rev. Pathol. Mech. Dis. 15, 123–147 (2020).

    Article  Google Scholar 

  199. Lv, Q. et al. Thermosensitive exosome–liposome hybrid nanoparticle-mediated chemoimmunotherapy for improved treatment of metastatic peritoneal cancer. Adv. Sci. 7, 2000515 (2020).

    Article  Google Scholar 

  200. Spaas, M. et al. Checkpoint inhibitors in combination with stereotactic body radiotherapy in patients with advanced solid tumors: the CHEERS phase 2 randomized clinical trial. JAMA Oncol. 9, 1205–1213 (2023).

    Article  Google Scholar 

  201. Hwang, W. L., Pike, L. R. G., Royce, T. J., Mahal, B. A. & Loeffler, J. S. Safety of combining radiotherapy with immune-checkpoint inhibition. Nat. Rev. Clin. Oncol. 15, 477–494 (2018).

    Article  Google Scholar 

  202. Djureinovic, D. et al. A bedside to bench study of anti-PD-1, anti-CD40, and anti-CSF1R indicates that more is not necessarily better. Mol. Cancer 22, 182 (2023).

    Article  Google Scholar 

  203. Yin, H. et al. Non-viral vectors for gene-based therapy. Nat. Rev. Genet. 15, 541–555 (2014).

    Article  Google Scholar 

  204. Winkle, M., El-Daly, S. M., Fabbri, M. & Calin, G. A. Noncoding RNA therapeutics — challenges and potential solutions. Nat. Rev. Drug Discov. 20, 629–651 (2021).

    Article  Google Scholar 

  205. Paunovska, K., Loughrey, D. & Dahlman, J. E. Drug delivery systems for RNA therapeutics. Nat. Rev. Genet. 23, 265–280 (2022).

    Article  Google Scholar 

  206. Xie, Y. et al. Stromal modulation and treatment of metastatic pancreatic cancer with local intraperitoneal triple miRNA/siRNA nanotherapy. ACS Nano 14, 255–271 (2020).

    Article  Google Scholar 

  207. Yu, H. et al. Triple-layered pH-responsive micelleplexes loaded with siRNA and cisplatin prodrug for NF-kappa B targeted treatment of metastatic breast cancer. Theranostics 6, 14–27 (2016).

    Article  Google Scholar 

  208. Hou, X., Zaks, T., Langer, R. & Dong, Y. Lipid nanoparticles for mRNA delivery. Nat. Rev. Mater. 6, 1078–1094 (2021).

    Article  Google Scholar 

  209. Weber, J. S. et al. Individualized neoantigen therapy mRNA-4157 (V940) plus pembrolizumab in resected melanoma: 3-year update from the mRNA-4157-P201 (KEYNOTE-942) trial. J. Clin. Oncol. 42, LBA9512–LBA9512 (2024).

    Article  Google Scholar 

  210. Fan, T. et al. Therapeutic cancer vaccines: advancements, challenges and prospects. Signal Transduct. Target. Ther. 8, 450 (2023).

    Article  Google Scholar 

  211. Lin, M. J. et al. Cancer vaccines: the next immunotherapy frontier. Nat. Cancer 3, 911–926 (2022).

    Article  Google Scholar 

  212. Oberli, M. A. et al. Lipid nanoparticle assisted mRNA delivery for potent cancer immunotherapy. Nano Lett. 17, 1326–1335 (2017).

    Article  Google Scholar 

  213. Lizotte, P. H. et al. In situ vaccination with cowpea mosaic virus nanoparticles suppresses metastatic cancer. Nat. Nanotechnol. 11, 295–303 (2016).

    Article  Google Scholar 

  214. Liu, C. et al. A nanovaccine for antigen self-presentation and immunosuppression reversal as a personalized cancer immunotherapy strategy. Nat. Nanotechnol. 17, 531–540 (2022).

    Article  Google Scholar 

  215. Hald Albertsen, C. et al. The role of lipid components in lipid nanoparticles for vaccines and gene therapy. Adv. Drug Deliv. Rev. 188, 114416 (2022).

    Article  Google Scholar 

  216. Shetty, K. & Ott, P. A. Personal neoantigen vaccines for the treatment of cancer. Annu. Rev. Cancer Biol. 5, 259–276 (2021).

    Article  Google Scholar 

  217. Blass, E. & Ott, P. A. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nat. Rev. Clin. Oncol. 18, 215–229 (2021).

    Article  Google Scholar 

  218. Mulroney, T. E. et al. N1-Methylpseudouridylation of mRNA causes +1 ribosomal frameshifting. Nature 625, 189–194 (2024).

    Article  Google Scholar 

  219. Sterner, R. C. & Sterner, R. M. CAR-T cell therapy: current limitations and potential strategies. Blood Cancer J. 11, 69 (2021).

    Article  MathSciNet  Google Scholar 

  220. Cappell, K. M. & Kochenderfer, J. N. Long-term outcomes following CAR T cell therapy: what we know so far. Nat. Rev. Clin. Oncol. 20, 359–371 (2023).

    Article  Google Scholar 

  221. Lemech, C. et al. 676TiP MYE symphony: a first-in-human study to investigate the safety, pharmacokinetics, pharmacodynamics and preliminary efficacy of the in vivo mRNA CAR therapy, MT-302, targeting TROP2 in adults with advanced epithelial tumors. Ann. Oncol. 35, S528 (2024).

    Google Scholar 

  222. Bui, T. A., Mei, H., Sang, R., Ortega, D. G. & Deng, W. Advancements and challenges in developing in vivo CAR T cell therapies for cancer treatment. eBioMedicine 106, 105266 (2024).

    Article  Google Scholar 

  223. Pfeiffer, A. et al. In vivo generation of human CD19-CAR T cells results in B-cell depletion and signs of cytokine release syndrome. EMBO Mol. Med. 10, e9158 (2018).

    Article  Google Scholar 

  224. Parayath, N. N., Stephan, S. B., Koehne, A. L., Nelson, P. S. & Stephan, M. T. In vitro-transcribed antigen receptor mRNA nanocarriers for transient expression in circulating T cells in vivo. Nat. Commun. 11, 6080 (2020).

    Article  Google Scholar 

  225. Hunter, T. L. et al. In vivo CAR T cell generation to treat cancer and autoimmune disease. Science 388, 1311–1317 (2025).

    Article  Google Scholar 

  226. Zhou, J. -e et al. Lipid nanoparticles produce chimeric antigen receptor T cells with interleukin-6 knockdown in vivo. J. Control. Release 350, 298–307 (2022).

    Article  Google Scholar 

  227. Wei, T., Cheng, Q., Min, Y.-L., Olson, E. N. & Siegwart, D. J. Systemic nanoparticle delivery of CRISPR–Cas9 ribonucleoproteins for effective tissue specific genome editing. Nat. Commun. 11, 3232 (2020).

    Article  Google Scholar 

  228. Tao, J., Bauer, D. E. & Chiarle, R. Assessing and advancing the safety of CRISPR–Cas tools: from DNA to RNA editing. Nat. Commun. 14, 212 (2023).

    Article  Google Scholar 

  229. Meister, H. et al. Multifunctional mRNA-based CAR T cells display promising antitumor activity against glioblastoma. Clin. Cancer Res. 28, 4747–4756 (2022).

    Article  Google Scholar 

  230. Hirabayashi, K. et al. Dual-targeting CAR-T cells with optimal co-stimulation and metabolic fitness enhance antitumor activity and prevent escape in solid tumors. Nat. Cancer 2, 904–918 (2021).

    Article  Google Scholar 

  231. Nguyen, N. T. et al. Nano-optogenetic engineering of CAR T cells for precision immunotherapy with enhanced safety. Nat. Nanotechnol. 16, 1424–1434 (2021).

    Article  Google Scholar 

  232. Tang, L. et al. Enhancing T cell therapy through TCR-signaling-responsive nanoparticle drug delivery. Nat. Biotechnol. 36, 707–716 (2018).

    Article  Google Scholar 

  233. Bocca, P. et al. Bevacizumab-mediated tumor vasculature remodelling improves tumor infiltration and antitumor efficacy of GD2-CAR T cells in a human neuroblastoma preclinical model. Oncoimmunology 7, e1378843 (2018).

    Article  Google Scholar 

  234. Zhang, F. et al. Nanoparticles that reshape the tumor milieu create a therapeutic window for effective T-cell therapy in solid malignancies. Cancer Res. 78, 3718–3730 (2018).

    Article  Google Scholar 

  235. Siriwon, N. et al. CAR-T cells surface-engineered with drug-encapsulated nanoparticles can ameliorate intratumoral T-cell hypofunction. Cancer Immunol. Res. 6, 812–824 (2018).

    Article  Google Scholar 

  236. Kang, M. et al. Nanocomplex-mediated in vivo programming to chimeric antigen receptor-M1 macrophages for cancer therapy. Adv. Mater. 33, 2103258 (2021).

    Article  Google Scholar 

  237. May, J.-N. et al. Histopathological biomarkers for predicting the tumour accumulation of nanomedicines. Nat. Biomed. Eng. 8, 1366–1378 (2024).

    Article  Google Scholar 

  238. Sung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 71, 209–249 (2021).

    Google Scholar 

  239. Mehlen, P. & Puisieux, A. Metastasis: a question of life or death. Nat. Rev. Cancer 6, 449–458 (2006).

    Article  Google Scholar 

  240. Riihimaki, M., Thomsen, H., Sundquist, K., Sundquist, J. & Hemminki, K. Clinical landscape of cancer metastases. Cancer Med. 7, 5534–5542 (2018).

    Article  Google Scholar 

  241. Chiang, A. C. & Massagué, J. Molecular basis of metastasis. N. Engl. J. Med. 359, 2814–2823 (2008).

    Article  Google Scholar 

  242. Xiao, Q. & Ge, G. Lysyl oxidase, extracellular matrix remodeling and cancer metastasis. Cancer Microenviron. 5, 261–273 (2012).

    Article  Google Scholar 

  243. Cronin, P. A., Wang, J. H. & Redmond, H. P. Hypoxia increases the metastatic ability of breast cancer cells via upregulation of CXCR4. BMC Cancer 10, 225 (2010).

    Article  Google Scholar 

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Acknowledgements

This work was funded by the Federal Ministry of Education and Research (BMBF) and the Ministry of Culture and Science of the German State of North Rhine-Westphalia (MKW) under the Excellence Strategy of the Federal Government and the Länder through the Junior Principal Investigator (JPI) Fellowship, by the European Research Council (ERC CoG 864121, Meta-Targeting), by the European Commission (EuroNanoMed-III: NSC4DIPG), and by the German Research Foundation (DFG: GRK 2375 (grant no. 331065168), KFO 5011 and SFB 1066).

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R.M.P., L.C. and T.L conceived the project and were involved in all the phases of the preparation of the manuscript. R.M.P., L.C., A.W. and F.D. wrote the manuscript. L.C, A.W. and F.D designed the figures. R.M.P. designed the tables. All authors edited the manuscript.

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Correspondence to Roger M. Pallares or Twan Lammers.

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Pallares, R.M., Consolino, L., Wang, A. et al. Targeting metastasis with nanomedicine. Nat Rev Bioeng 4, 47–66 (2026). https://doi.org/10.1038/s44222-025-00358-7

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