Machine-learning-assisted single-vessel analysis of nanoparticle permeability in tumour vasculatures
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Abstract
The central dogma that nanoparticle delivery to tumours requires enhanced leakiness of vasculatures is a topic of debate. To address this, we propose a single-vessel quantitative analysis method by taking advantage of protein-based nanoprobes and image-segmentation-based machine learning (nano-ISML). Using nano-ISML, >67,000 individual blood vessels from 32 tumour models were quantified, revealing highly heterogenous vascular permeability of protein-based nanoparticles. There was a >13-fold difference in the percentage of high-permeability vessels in different tumours and >100-fold penetration ability in vessels with the highest permeability compared with vessels with the lowest permeability. Our data suggest passive extravasation and transendothelial transport were the dominant mechanisms for high- and low-permeability tumour vessels, respectively. To exemplify the nano-ISML-assisted rational design of nanomedicines, genetically tailored protein nanoparticles with improved transendothelial transport in low-permeability tumours were developed. Our study delineates the heterogeneity of tumour vascular permeability and defines a direction for the rational design of next-generation anticancer nanomedicines.
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Data analysis of >67,000 individual blood vessels by image-segmentation-based machine learning (nano-ISML) techniques can predict nanoparticle permeability in tumor vasculatures.
“Subsequently, data analysis of >67,000 individual blood vessels was performed by image-segmentation-based machine learning (nano-ISML) techniques to predict nanoparticle permeability in the tumor vasculatures.”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [343]
Genetically tailored protein nanoparticles developed based on rational design of nano-ISML-assisted nanomedicines improve transendothelial transport in low-permeability tumors and assist nanoparticles to enter solid tumors.
“And based on the rational design of nano-ISML-assisted nanomedicines, genetically tailored protein nanoparticles were developed to improve transendothelial transport in low-permeability tumors and assists nanoparticles to enter solid tumors.343”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [343]
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Cites
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404 · see citing works
A survey on deep learning in medical image analysis
Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332 · see citing works
Principles of nanoparticle design for overcoming biological barriers to drug delivery
Blanco, E., Shen, H., & Ferrari, M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3330 · Cited by 7,002 · see citing works
Cancer nanomedicine: progress, challenges and opportunities
Shi, J., Kantoff, P. W., Wooster, R., & Farokhzad, O. C. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2016.108 · Cited by 5,873 · see citing works
Machine learning for molecular and materials science
Butler, K. T., Davies, D. W., Cartwright, H., Isayev, O., & Walsh, A. (2018) · Nature · doi:10.1038/s41586-018-0337-2 · Cited by 4,968 · see citing works
Delivering nanomedicine to solid tumors
Jain, R. K., & Stylianopoulos, T. (2010) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2010.139 · Cited by 3,196 · see citing works
Drug penetration in solid tumours
Minchinton, A. I., & Tannock, I. F. (2006) · Nature reviews. Cancer · doi:10.1038/nrc1893 · Cited by 2,805 · see citing works
A guide to machine learning for biologists
Greener, J. G., Kandathil, S. M., Moffat, L., & Jones, D. T. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00407-0 · Cited by 2,127 · see citing works
U-Net: deep learning for cell counting, detection, and morphometry
Falk, T., Mai, D., Bensch, R., Çiçek, Ö., Abdulkadir, A., Marrakchi, Y., Böhm, A., Deubner, J., Jäckel, Z., Seiwald, K., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0261-2 · Cited by 1,912 · see citing works
The entry of nanoparticles into solid tumours
Sindhwani, S., Syed, A. M., Ngai, J., Kingston, B. R., Maiorino, L., Rothschild, J., MacMillan, P., Zhang, Y., Rajesh, N. U., Hoang, T., et al. (2020) · Nature Materials · doi:10.1038/s41563-019-0566-2 · Cited by 1,732 · see citing works
Mechanisms of clathrin-mediated endocytosis
Kaksonen, M., & Roux, A. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.132 · Cited by 1,698 · see citing works
Key principles and methods for studying the endocytosis of biological and nanoparticle therapeutics
Rennick, J. J., Johnston, A. P. R., & Parton, R. G. (2021) · Nature Nanotechnology · doi:10.1038/s41565-021-00858-8 · Cited by 1,494 · see citing works
Deep learning for cellular image analysis
Moen, E., Bannon, D., Kudo, T., Graf, W., Covert, M., & Van Valen, D. (2019) · Nature Methods · doi:10.1038/s41592-019-0403-1 · Cited by 1,225 · see citing works
Chauhan, V. P., Stylianopoulos, T., Martin, J. D., Popović, Z., Chen, O., Kamoun, W. S., Bawendi, M. G., Fukumura, D., & Jain, R. K. (2012) · Nature Nanotechnology · doi:10.1038/nnano.2012.45 · Cited by 1,101 · see citing works
Greenwald, N. F., Miller, G., Moen, E., Kong, A., Kagel, A., Dougherty, T., Fullaway, C. C., McIntosh, B. J., Leow, K. X., Schwartz, M. S., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01094-0 · Cited by 953 · see citing works
Enzyme-activatable polymer–drug conjugate augments tumour penetration and treatment efficacy
Zhou, Q., Shao, S., Wang, J., Xu, C., Xiang, J., Piao, Y., Zhou, Z., Yu, Q., Tang, J., Liu, X., et al. (2019) · Nature Nanotechnology · doi:10.1038/s41565-019-0485-z · Cited by 822 · see citing works
Lysosomes as a therapeutic target
Bonam, S. R., Wang, F., & Muller, S. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0036-1 · Cited by 764 · see citing works
Magnetoferritin nanoparticles for targeting and visualizing tumour tissues
Fan, K., Cao, C., Pan, Y., Lü, D., Yang, D., Feng, J., Song, L., Liang, M., & Yan, X. (2012) · Nature Nanotechnology · doi:10.1038/nnano.2012.90 · Cited by 756 · see citing works
Self-citationTransport of drugs from blood vessels to tumour tissue
Dewhirst, M. W., & Secomb, T. W. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2017.93 · Cited by 749 · see citing works
Data-analysis strategies for image-based cell profiling
Caicedo, J. C., Cooper, S., Heigwer, F., Warchal, S., Qiu, P., Molnar, C., Vasilevich, A. S., Barry, J. D., Bansal, H. S., Kraus, O., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4397 · Cited by 739 · see citing works
Quantifying the Ligand-Coated Nanoparticle Delivery to Cancer Cells in Solid Tumors
Dai, Q., Wilhelm, S., Ding, D., Syed, A. M., Sindhwani, S., Zhang, Y., Chen, Y. Y., MacMillan, P., & Chan, W. C. W. (2018) · ACS Nano · doi:10.1021/acsnano.8b03900 · Cited by 663 · see citing works
Functional inference integrated in the FROGS suite
Samb, M., Bernard, M., & Pascal, G. (2020) · HAL (Le Centre pour la Communication Scientifique Directe) · doi:10.1038/s41587 · Cited by 631 · see citing works
The Endosomal Escape of Nanoparticles: Toward More Efficient Cellular Delivery
Smith, S. A., FitzGerald, L. I., Johnston, A. P. R., & Such, G. K. (2018) · Bioconjugate Chemistry · doi:10.1021/acs.bioconjchem.8b00732 · Cited by 616 · see citing works
Matteis, M. A. D., & Luini, A. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2378 · Cited by 483 · see citing works
Obstacles and opportunities in a forward vision for cancer nanomedicine
de Lázaro, I., & Mooney, D. J. (2021) · Nature Materials · doi:10.1038/s41563-021-01047-7 · Cited by 442 · see citing works
Heterogeneity of the Tumor Vasculature
Nagy, J. A., Chang, S.-H., Shih, S., Dvořàk, A. M., & Dvorak, H. F. (2010) · Seminars in Thrombosis and Hemostasis · doi:10.1055/s-0030-1253454 · Cited by 422 · see citing works
Vascular bursts enhance permeability of tumour blood vessels and improve nanoparticle delivery
Matsumoto, Y., Nichols, J. W., Toh, K., Nomoto, T., Cabral, H., Miura, Y., Christie, R. J., Yamada, N., Ogura, T., Kano, M. R., et al. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2015.342 · Cited by 412 · see citing works
Machine learning analysis of whole mouse brain vasculature
Todorov, M. I., Paetzold, J. C., Schoppe, O., Tetteh, G., Shit, S., Efremov, V., Todorov-Völgyi, K., Düring, M., Dichgans, M., Piraud, M., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0792-1 · Cited by 338 · see citing works
Vascular permeability—the essentials
Claesson, L. (2015) · Upsala Journal of Medical Sciences · doi:10.3109/03009734.2015.1064501 · Cited by 304 · see citing works
The Vesiculo–Vacuolar Organelle (VVO): A New Endothelial Cell Permeability Organelle
Dvořàk, A. M., & Feng, D. (2001) · Journal of Histochemistry & Cytochemistry · doi:10.1177/002215540104900401 · Cited by 280 · see citing works
Chen, S., Zhong, Y., Fan, W.-F., Xiang, J.-J., Wang, G., Zhou, Q., Wang, J.-Q., Geng, Y., Sun, R., Zhang, Z., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00701-4 · Cited by 273 · see citing works
Self-citationDvořàk, A. M., Kohn, S., Morgan, E. S., Fox, P., Nagy, J. A., & Dvorak, H. F. (1996) · Journal of Leukocyte Biology · doi:10.1002/jlb.59.1.100 · Cited by 271 · see citing works
Chimeric Ferritin Nanocages for Multiple Function Loading and Multimodal Imaging
Lin, X., Xie, J., Niu, G., Zhang, F., Gao, H., Yang, M., Quan, Q., Aronova, M. A., Zhang, G., Lee, S., et al. (2011) · Nano Letters · doi:10.1021/nl104141g · Cited by 263 · see citing works
Biomimetic Design of Mitochondria‐Targeted Hybrid Nanozymes as Superoxide Scavengers
Zhang, Y., Khalique, A., Du, X., Gao, Z., Wu, J., Zhang, X., Zhang, R., Sun, Z., Liu, Q., Xu, Z., et al. (2021) · Advanced Materials · doi:10.1002/adma.202006570 · Cited by 233 · see citing works
Self-citationPrediction and Design of Nanozymes using Explainable Machine Learning
Wei, Y., Wu, J., Wu, Y., Liu, H., Meng, F., Liu, Q., Midgley, A. C., Zhang, X., Qi, T., Kang, H., et al. (2022) · Advanced Materials · doi:10.1002/adma.202201736 · Cited by 191 · see citing works
Self-citationGreenwald, N. F., Miller, G., Moen, E., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.01.431313 · Cited by 140 · see citing works
Specific Endothelial Cells Govern Nanoparticle Entry into Solid Tumors
Kingston, B. R., Lin, Z. P., Ouyang, B., MacMillan, P., Ngai, J., Syed, A. M., Sindhwani, S., & Chan, W. C. W. (2021) · ACS Nano · doi:10.1021/acsnano.1c04510 · Cited by 140 · see citing works
Protein nanocages that penetrate airway mucus and tumor tissue
Huang, X., Chisholm, J., Zhuang, J., Xiao, Y., Duncan, G., Chen, X., Suk, J. S., & Hanes, J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705407114 · Cited by 131 · see citing works
Self-citationEndothelial Cell Receptors in Tissue Lipid Uptake and Metabolism
Abumrad, N. A., Cabodevilla, A. G., Samovski, D., Pietka, T., Basu, D., & Goldberg, I. J. (2021) · Circulation Research · doi:10.1161/circresaha.120.318003 · Cited by 125 · see citing works
A natural drug entry channel in the ferritin nanocage
Jiang, B., Chen, X., Sun, G., Chen, X., Yin, Y., Jin, Y., Mi, Q., Ma, L., Yang, Y., Yan, X., et al. (2020) · Nano Today · doi:10.1016/j.nantod.2020.100948 · Cited by 108 · see citing works
Self-citationDifferent Pathways of Macromolecule Extravasation from Hyperpermeable Tumor Vessels
Feng, D., Nagy, J. A., Dvořàk, A. M., & Dvorak, H. F. (2000) · Microvascular Research · doi:10.1006/mvre.1999.2207 · Cited by 94 · see citing works
Yokota, S., & Fahimi, H. D. (1981) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.78.8.4970 · Cited by 85 · see citing works
Hypoxia-tropic Protein Nanocages for Modulation of Tumor- and Chemotherapy-Associated Hypoxia
Huang, X., Zhuang, J., Chung, S. W., Huang, B., Halpert, G., Negrón, K., Sun, X., Yang, J., Oh, Y., Hwang, P. M., et al. (2018) · ACS Nano · doi:10.1021/acsnano.8b05399 · Cited by 82 · see citing works
Self-citationA ribonucleoprotein octamer for targeted siRNA delivery
Tai, W., Li, J., Corey, E., & Gao, X. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0214-1 · Cited by 79 · see citing works
Bern, M., Nilsen, J., Ferrarese, M., Sand, K. M. K., Gjølberg, T. T., Lode, H. E., Davidson, R. J., Camire, R. M., Bækkevold, E. S., Foss, S., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.abb0580 · Cited by 71 · see citing works
The effect of Golgi depletion on exocytic transport
Pelletier, L., Jokitalo, E., & Warren, G. W. (2000) · Nature Cell Biology · doi:10.1038/35041089 · Cited by 70 · see citing works
Liu, Q., Tian, J., Liu, J., Zhu, M., Gao, Z., Hu, X., Midgley, A. C., Wu, J., Wang, X., Kong, D., et al. (2021) · Advanced Materials · doi:10.1002/adma.202103128 · Cited by 69 · see citing works
Self-citationImmunohistochemical localization of albumin and in situ hybridization of albumin mRNA
Shroyer, K. R., & Nakane, P. K. (1987) · Cell Biochemistry and Function · doi:10.1002/cbf.290050307 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Chen, S. Q. et al. Enhanced tumour penetration and prolonged circulation in blood of polyzwitterion- drug conjugates with cell-membrane a nity. Nat Biomed Eng 5, 1019-+, doi:10.1038/s41551-021- 00701-4 (2021). · DOI
Cited by
Sorted by citations
Smart nanoparticles for cancer therapy
Sun, L., Liu, H., Ye, Y., Lei, Y., Islam, R., Tan, S., Tong, R., Miao, Y.-B., & Cai, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01642-x · Cited by 1,073 · see citing works
Huang, Y., Guo, X., Wu, Y., Chen, X., Feng, L., Xie, N., & Shen, G. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01745-z · Cited by 528 · see citing works
Designing nanotheranostics with machine learning
Rao, L., Yuan, Y., Shen, X., Yu, G., & Chen, X. S. (2024) · Nature Nanotechnology · doi:10.1038/s41565-024-01753-8 · Cited by 219 · see citing works
AI-enabled organoids: Construction, analysis, and application
Bai, L., Wu, Y., Li, G., Zhang, W., Zhang, H., & Su, J. (2023) · Bioactive Materials · doi:10.1016/j.bioactmat.2023.09.005 · Cited by 216 · see citing works
Liu, M., Wang, Y., Zhang, Y.-B., Hu, D., Tang, L., Zhou, B., & Yang, L. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02112-8 · Cited by 174 · see citing works
Applications of liposomes and lipid nanoparticles in cancer therapy: current advances and prospects
Cheng, Z., Huang, H., Yin, M., & Liu, H. (2025) · Experimental Hematology and Oncology · doi:10.1186/s40164-025-00602-1 · Cited by 155 · see citing works
Transvascular transport of nanocarriers for tumor delivery
Li, X., Hu, Y. M., Zhang, X., Shi, X., Parak, W. J., & Pich, A. (2024) · Nature Communications · doi:10.1038/s41467-024-52416-0 · Cited by 131 · see citing works
Nanoparticle delivery to tumours: from EPR and ATR mechanisms to clinical impact
Dasgupta, A., Sofias, A. M., Kiessling, F. M., & Lammers, T. (2024) · Nature Reviews Bioengineering · doi:10.1038/s44222-024-00203-3 · Cited by 114 · see citing works
Developments in nanotechnology approaches for the treatment of solid tumors
Venturini, J., Chakraborty, A., Baysal, M. A., & Tsimberidou, A. M. (2025) · Experimental Hematology and Oncology · doi:10.1186/s40164-025-00656-1 · Cited by 107 · see citing works
‘Passive’ nanoparticles for organ-selective systemic delivery: design, mechanism and perspective
Fu, L., Zhang, Y., Farokhzad, R. A., Mendes, B. B., Conde, J., & Shi, J. (2023) · Chemical Society Reviews · doi:10.1039/d2cs00998f · Cited by 99 · see citing works
The pathways for nanoparticle transport across tumour endothelium
Wu, J. L. Y., Ji, Q., Blackadar, C., Nguyen, L. N. M., Lin, Z. P., Sepahi, Z., Stordy, B. P., Farias, A. G., Sindhwani, S., Ngo, W., et al. (2025) · Nature Nanotechnology · doi:10.1038/s41565-025-01877-5 · Cited by 94 · see citing works
Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation
Yan, X., Yue, T., Winkler, D. A., Yin, Y., Zhu, H., Jiang, G., & Yan, B. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00070 · Cited by 88 · see citing works
Self-citationApplying artificial intelligence and computational modeling to nanomedicine
Hamilton, S., & Kingston, B. R. (2023) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.103043 · Cited by 90 · see citing works
Noury, H., Rahdar, A., Ferreira, L. F. R., & Jamalpoor, Z. (2025) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2025.104701 · Cited by 86 · see citing works
Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures
Kuznetsova, V. A., Coogan, Á., Botov, D., Gromova, Y. A., Ushakova, E. V., & Gun’ko, Y. K. (2024) · Advanced Materials · doi:10.1002/adma.202308912 · Cited by 76 · see citing works
Rational strategies for improving the efficiency of design and discovery of nanomedicines
Shan, X., Cai, Y., Zhu, B., Zhou, L., Sun, X., Xu, X., Yin, Q., Wang, D., & Li, Y. (2024) · Nature Communications · doi:10.1038/s41467-024-54265-3 · Cited by 74 · see citing works
Multi-omics approaches to decipher the interactions of nanoparticles and biological systems
Wang, Y., Xiao, Z., Wang, Z., Lee, D., Ma, Y., Wilhelm, S., Wang, H., Kim, B. Y. S., & Jiang, W. (2024) · Nature Reviews Bioengineering · doi:10.1038/s44222-024-00264-4 · Cited by 74 · see citing works
Machine Learning‐Enhanced Nanoparticle Design for Precision Cancer Drug Delivery
Wang, Q., Liu, Y., Li, C., Xu, S., Xu, S., & Liu, B. (2025) · Advanced Science · doi:10.1002/advs.202503138 · Cited by 75 · see citing works
Does the surface charge of the nanoparticles drive nanoparticle–cell membrane interactions?
Balog, S., de Almeida, M. S., Taladriz‐Blanco, P., Rothen‐Rutishauser, B., & Petri‐Fink, A. (2024) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2024.103128 · Cited by 68 · see citing works
Yuan, S., Hu, D., Gao, D., Butch, C. J., Wang, Y., Zheng, H., & Sheng, Z. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03572-y · Cited by 63 · see citing works
Zhou, L., Yi, W., Zhang, Z., Shan, X., Zhao, Z., Sun, X., Wang, J., Wang, H., Jiang, H., Zheng, M., et al. (2023) · National Science Review · doi:10.1093/nsr/nwad214 · Cited by 56 · see citing works
Self-citationAgrahari, V., Choonara, Y. E., Mosharraf, M., Patel, S. K., & Zhang, F. (2024) · Pharmaceutical Research · doi:10.1007/s11095-024-03798-9 · Cited by 54 · see citing works
Ma, X., Tang, Y., Wang, C., Li, Y., Zhang, J., Luo, Y., Xu, Z., Wu, F., & Wang, S. (2023) · ACS Applied Bio Materials · doi:10.1021/acsabm.3c00527 · Cited by 45 · see citing works
Design Considerations for Organ-Selective Nanoparticles
Baek, M., Hur, W., Kashiwagi, S., & Choi, H. S. (2025) · ACS Nano · doi:10.1021/acsnano.5c00484 · Cited by 45 · see citing works
The evolution of nanomedicine: The rise of next-generation nanomaterials in cancer nanomedicine
Forgham, H., Chang, Y.-X., Wang, Y., Zhu, J., Liu, L., Biggs, H., Käkinen, A., Jiang, Y., You, X., Thurecht, K. J., et al. (2025) · Science Advances · doi:10.1126/sciadv.adx1576 · Cited by 45 · see citing works
Fan, S., Wang, W., Che, W., Xu, Y., Jin, C., Dong, L., & Xia, Q. (2025) · Metabolites · doi:10.3390/metabo15030201 · Cited by 43 · see citing works
Paun, R. A., Jurchuk, S., & Tabrizian, M. (2023) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10601 · Cited by 45 · see citing works
Machine learning reshapes the paradigm of nanomedicine research
Wei, Z., Zhuo, S., Zhang, Y., Wu, L., Gao, X., He, S., Bo, X., & Zhou, W. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.05.014 · Cited by 42 · see citing works
From synthesis to properties: expanding the horizons of machine learning in nanomaterials research
Diao, S., Wu, Q., Li, S., Xu, G., Ren, X., Tan, L., Jiang, G., Song, P., & Meng, X. (2025) · Materials Horizons · doi:10.1039/d4mh01909a · Cited by 39 · see citing works
Bio-nanomaterials: Promising anticancer properties and treatment strategies
Elemike, E. E., Onunkwo, I. C., Ughumiakpor, O., Alawuru, F., Mukoro, A., Ishom, P., Obarakpor, F., Hossain, I., & Aziza, A. E. (2025) · Nano TransMed · doi:10.1016/j.ntm.2025.100076 · Cited by 41 · see citing works
Younas, A., Wang, S., Asad, M., Mamun, A. A., Majeed, S., Sharif, A., Zhou, Q., Liu, Y., Geng, P., Shao, C., et al. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.102660 · Cited by 38 · see citing works
SynBioNanoDesign: pioneering targeted drug delivery with engineered nanomaterials
Cai, Q., Guo, R. F., Chen, D., Deng, Z., & Gao, J. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03254-9 · Cited by 35 · see citing works
Artificial intelligence-powered nanomedicine
Luo, G., 蒋显超, Hu, C., Li, L., Yan, L., Xiao, G., Duo, Y., & Zhang, X. (2026) · Chemical Society Reviews · doi:10.1039/d5cs01406a · Cited by 33 · see citing works
Strategies to enhance the penetration of nanomedicine in solid tumors
Liu, S., Ren, Z., Yan, M., Ye, W., & Hu, Y. (2025) · Biomaterials · doi:10.1016/j.biomaterials.2025.123315 · Cited by 30 · see citing works
Optical trapping of optical nanoparticles: Fundamentals and applications
Zhang, F., Camarero, P., Haro‐González, P., Labrador‐Páez, L., & Jaque, D. (2023) · Opto-Electronic Science · doi:10.29026/oes.2023.230019 · Cited by 29 · see citing works
Learning lessons from nano-medicine to improve the design and performances of nano-agrochemicals
Cong, V. T., Gooding, J. J., & Kah, M. (2025) · Nature Communications · doi:10.1038/s41467-025-57650-8 · Cited by 29 · see citing works
Nanodelivery Systems as a Novel Strategy to Overcome Treatment Failure of Cancer
Shi, H., Gou, X., Zhang, S., Zhang, X., Huang, H., Wang, W., Yi, L., Zhang, R., Duan, Z., Zhou, P., et al. (2023) · Small Methods · doi:10.1002/smtd.202301127 · Cited by 28 · see citing works
The spatiotemporal journey of nanomedicines in solid tumors on their therapeutic efficacy
Qin, M., Xia, H., Xu, W., Chen, B., & Wang, Y. (2023) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2023.115137 · Cited by 28 · see citing works
Omics‐Enhanced Nanomedicine for Cancer Therapy
Qi, L., Li, Z., Liu, J., & Chen, X. S. (2024) · Advanced Materials · doi:10.1002/adma.202409102 · Cited by 30 · see citing works
Self-citationCooley, M. B., Wegierak, D., Perera, R., Abenojar, E., Nittayacharn, P., Berg, F. M., Kim, Y., Kolios, M. C., & Exner, A. A. (2024) · ACS Nano · doi:10.1021/acsnano.4c11805 · Cited by 28 · see citing works
Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery
Su, K., Qiu, J., Xu, T., & Liu, S. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.11.029 · Cited by 35 · see citing works
Wang, Z., Su, Q., Deng, W., Wang, X., Zhou, H., Zhang, M., Lin, W., Xiao, J., & Duan, X. (2024) · ACS Nano · doi:10.1021/acsnano.4c07085 · Cited by 26 · see citing works
Nanomedicine Reimagined: Translational Strategies for Precision Tumor Theranostics
Wu, Q., Yao, X., Duan, X., Chen, X. S., & Zhang, J. (2025) · Advanced Materials · doi:10.1002/adma.202510293 · Cited by 26 · see citing works
Einen, C., Snipstad, S., Wesche, H. F., Nordlund, V., Devold, E. J., Amini, N., Hansen, R., Sulheim, E., & Davies, C. D. L. (2024) · Journal of Controlled Release · doi:10.1016/j.jconrel.2024.12.037 · Cited by 24 · see citing works
Zhang, Y., Watson, S. L., Ramaswamy, Y., & Singh, G. (2024) · Advances in Colloid and Interface Science · doi:10.1016/j.cis.2024.103200 · Cited by 23 · see citing works
Artificial intelligence (AI) meets biomaterials and biomedicine
Han, S., & Wu, J. (2024) · Smart Materials in Medicine · doi:10.1016/j.smaim.2024.03.001 · Cited by 22 · see citing works
Nanoparticle-based strategy in CAR-T cell immunotherapy: challenges, implications, and perspectives
Shang, D., Zhou, Z., Shi, R., Wang, Z., Zhang, P., Fu, P., Li, H., Cheng, G., Qin, H., Xie, Z., et al. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02476-7 · Cited by 22 · see citing works
Liu, Q., Gao, Z., Zhang, X., Duan, Q., Zhang, Y., Midgley, A. C., Li, J., Liu, R., Zhu, M., Kong, D., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56414-8 · Cited by 22 · see citing works
Self-citationAddressing the in vivo delivery of nucleic-acid nanostructure therapeutics
Alexander, S., Moghadam, M. G., Rothenbroker, M., & Chou, L. Y. T. (2023) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2023.114898 · Cited by 21 · see citing works
Self‐Assembly of Heterogeneous Ferritin Nanocages for Tumor Uptake and Penetration
Liu, Q., Wang, C., Zhu, M., Liu, J., Duan, Q., Midgley, A. C., Liu, R., Jiang, B., Kong, D., Chen, Q., et al. (2024) · Advanced Science · doi:10.1002/advs.202309271 · Cited by 20 · see citing works
Self-citationMim, J. J., Mamun, A. A., Nayem, M. H., Mahmud, S., Nath, A., Rahman, S., Fidal, S. A., & Hossain, N. (2025) · Materials Today Communications · doi:10.1016/j.mtcomm.2025.114485 · Cited by 20 · see citing works
Kockelmann, J., Zentel, R., & Nuhn, L. (2023) · Macromolecular Chemistry and Physics · doi:10.1002/macp.202300199 · Cited by 19 · see citing works
A Generative Artificial Intelligence Copilot for Biomedical Nanoengineering
Wang, Y., Song, H., Teng, Y., Huang, G., Qian, J., Wang, H., Dong, S., Ha, J., Ma, Y., Chang, M., et al. (2025) · ACS Nano · doi:10.1021/acsnano.5c03454 · Cited by 18 · see citing works
Accelerating discoveries in cancer nanomedicine using AI
Guan, C., Mendes, B. B., Conniot, J., Dias, A. L., Hammad, L., Thambi, T., Langer, R., Rodrigues, T., Conde, J., & de la Fuente‐Núñez, C. (2025) · Cell Biomaterials · doi:10.1016/j.celbio.2025.100279 · Cited by 18 · see citing works
Elastic Polymer Coated Nanoparticles with Fast Clearance for 19F MR Imaging
Konishi, Y., Minoshima, M., Fujihara, K., Uchihashi, T., & Kikuchi, K. (2023) · Angewandte Chemie International Edition · doi:10.1002/anie.202308565 · Cited by 18 · see citing works
Liu, Z., Lu, T., Qian, R., Wang, Z., Qi, R., & Zhang, Z. (2024) · International Journal of Nanomedicine · doi:10.2147/ijn.s455407 · Cited by 18 · see citing works
Self-citationZhu, M., Liu, Q.-Q., Chen, Z., Liu, J.-M., Zhang, Z., Tian, J., Wang, X., Yang, X., Chen, Q., Huang, X.-L., et al. (2025) · ACS Nano · doi:10.1021/acsnano.4c12808 · Cited by 17 · see citing works
Self-citationDelivery of Chemotherapy Agents and Nucleic Acids with pH-Dependent Nanoparticles
Leng, Q., Imtiyaz, Z., Woodle, M. C., & Mixson, A. J. (2023) · Pharmaceutics · doi:10.3390/pharmaceutics15051482 · Cited by 17 · see citing works
Artificial intelligence for nanomedicine
Song, X., Gao, X., Wang, H., Yu, F., Qin, M., Li, Y., Liu, Y., Feng, W., Zhou, C., Chukavin, N. N., et al. (2025) · Science China Chemistry · doi:10.1007/s11426-025-2942-5 · Cited by 16 · see citing works
DNA Framework-Templated Synthesis of Copper Cluster Nanozyme with Enhanced Activity and Specificity
Li, L., Ding, Y., Lei, M., Xue, Y., He, X., Xue, J., Bu, H., Su, Y. L., Ouyang, X., & Wan, Y. (2024) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.4c09208 · Cited by 15 · see citing works
Intersection of ferroptosis and nanomaterials brings benefits to breast cancer
Gao, J., Ma, N., Ni, S., & Han, X. F. (2025) · Cell Biology and Toxicology · doi:10.1007/s10565-025-10067-x · Cited by 15 · see citing works
Regulating tumor cells to awaken T cell antitumor function and enhance melanoma immunotherapy
Zhang, W., Yuan, S., Zhang, Z., Fu, S., Liu, S., Liu, J., Ma, Q., Xia, Z., Gu, P., Gao, S., et al. (2024) · Biomaterials · doi:10.1016/j.biomaterials.2024.123034 · Cited by 14 · see citing works
Self-citationTanaka, M., Araujo, A. C., Valenti, V. E., Guiguer, E. L., Catharin, V. C. S., Gualhardi, C. M., de Souza Bastos Mazuqueli Pereira, E., de Alvares Goulart, R., de Argolo Haber, R. S., de Carvalho, A. C. A., et al. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27052370 · Cited by 13 · see citing works
Li, M., Li, T., Wu, F., Ren, F. Z., Xue, S., & Li, C. (2024) · Chemosensors · doi:10.3390/chemosensors12060113 · Cited by 13 · see citing works
Zhang, X., Liu, Q., Zhao, R., Pang, Z., Zhang, W., Qi, T., Zhu, M., Kang, H., Qian, M., Wan, Y., et al. (2024) · Nano Letters · doi:10.1021/acs.nanolett.4c04462 · Cited by 14 · see citing works
Self-citationYin, J., Sun, W., Xiong, H., Yao, W., Liu, X., Jiang, H., & Wang, X. (2025) · Biomaterials · doi:10.1016/j.biomaterials.2025.123388 · Cited by 13 · see citing works
Nano-oncology revisited: Insights on precise therapeutic advances and challenges in tumor
Teng, L., Bi, Y., Xing, X., & Yao, G. (2025) · Fundamental Research · doi:10.1016/j.fmre.2025.03.024 · Cited by 13 · see citing works
Zhang, P., Pan, J., Lin, S., Peng, B., Zhang, J., Zhang, J., Xu, L., Lai, Y. L., Yu, H., & Xu, Z. (2025) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2025.115620 · Cited by 13 · see citing works
Javan, M., Zareian, D. A., & Mojarad-Jabali, S. (2026) · International Journal of Nanomedicine · doi:10.2147/ijn.s563233 · Cited by 12 · see citing works
Ramesan, S. P., Poonacha, J. B., Pathirana, D., Merkt, S. J., Maaß, C., Hasenauer, J., & Reckzeh, E. S. (2026) · Trends in biotechnology · doi:10.1016/j.tibtech.2026.01.009 · Cited by 11 · see citing works
Self-assembly of peptides in living cells for disease theranostics
Mo, X., Zhang, Z., Song, J., Wang, Y., & Yu, Z. (2024) · Journal of Materials Chemistry B · doi:10.1039/d4tb00365a · Cited by 11 · see citing works
Self-citationKulkarni, S., Lin, B., & Radhakrishnan, R. (2025) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2025.109081 · Cited by 10 · see citing works
Challenges and opportunities of poly(amino acid) nanomedicines in cancer therapy
Li, Y., He, J., Liu, J., Um, W., & Ding, J. (2024) · Nanomedicine · doi:10.1080/17435889.2024.2402677 · Cited by 9 · see citing works
Tiwary, P., Oswal, K., Varghese, R., Anchan, H., & Gupta, P. K. (2025) · Chemistry and Physics of Lipids · doi:10.1016/j.chemphyslip.2025.105510 · Cited by 11 · see citing works
Nanoparticle-enabled molecular imaging diagnosis of osteoarthritis
Zhang, T., Zhang, Q. T., Wei, J., Dai, Q., Muratovic, D., Zhang, W., Diwan, A. D., & Gu, Z. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.101952 · Cited by 9 · see citing works
Zhao, L., Liu, X., & Deng, X. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03947-1 · Cited by 11 · see citing works
Xu, K., Li, S., Zhou, Y., Gao, X., Mei, J., & Liu, Y. (2023) · Pharmaceutics · doi:10.3390/pharmaceutics15041064 · Cited by 9 · see citing works
Deep learning technology in vascular image segmentation and disease diagnosis
Du, C., Zhuang, J., & Huang, X. (2024) · Journal of intelligent medicine. · doi:10.1002/jim4.15 · Cited by 8 · see citing works
Self-citationJi, M., Liu, H., Liang, X., Wei, M., Shi, D., Gou, J., Yin, T., He, H., Tang, X., & Zhang, Y. X. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.102535 · Cited by 8 · see citing works
AI-Enhanced Patient-Derived Cancer Organoids: Integrating Machine Learning for Precision Oncology
Heinzelmann, E., & Piraino, F. (2025) · Organoids · doi:10.3390/organoids4040030 · Cited by 7 · see citing works
Zhou, H., Guo, Y., Fu, T., Peng, Y., Chen, Z., Cui, Y., Guo, M., Zhang, K., Chen, C., & Wang, Y. (2024) · ACS Nano · doi:10.1021/acsnano.4c06095 · Cited by 7 · see citing works
Yang, C., Cao, X., He, L., Wu, C., Zhao, M., Duan, F., Qiu, Z., Zhu, X., Yan, Y., Li, S., et al. (2023) · International Journal of Nanomedicine · doi:10.2147/ijn.s434645 · Cited by 7 · see citing works
Peng, S., Yuan, X., Li, H., Huang, H., Li, C., Wei, C., Ren, J., Zhang, Q., Ding, G., & Bai, J. (2024) · Materials & Design · doi:10.1016/j.matdes.2024.112893 · Cited by 6 · see citing works
Liu, Y., Lv, C., Zhang, X., Liu, Y., Yang, L., Li, D., & Xi, Q. (2025) · Industrial Crops and Products · doi:10.1016/j.indcrop.2025.121718 · Cited by 6 · see citing works
Nanodrug delivery systems in tumor immunotherapy: From immune activation to tumor reprogramming
Mao, D., Li, B., Li, J., Pan, J., Wu, Z., & Feng, N. (2026) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2026.115838 · Cited by 6 · see citing works
Cai, Y., Zhang, Z., Lu, Y., Shen, S., Lu, H., He, H., & Wu, W. (2026) · Journal of Controlled Release · doi:10.1016/j.jconrel.2026.114759 · Cited by 6 · see citing works
Self-citationHuang, W., Zhang, L., Sun, J., Sun, Y., Gong, L., Ge, S., Wei, X., & Gao, W. (2023) · Advanced Healthcare Materials · doi:10.1002/adhm.202301890 · Cited by 6 · see citing works
Mmereke, K. M., Oladipo, A. O., Masebe, T. M., Nemavhola, F. J., & Pandelani, T. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.11.013 · Cited by 4 · see citing works
Hao, H., Yi, Y., Fu, Y., Sun, S., Peng, Z., Tang, J., Fang, Y., Zhuang, S., Ouyang, Y., Wang, T., et al. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.11.040 · Cited by 4 · see citing works
Machine learning for nanoparticle-based imaging: From rational design to precision diagnosis
Kang, N., Li, Z., Tan, F., Liu, Z., Yang, Y., Qian, X., & Zhang, Q. (2025) · Advances in Colloid and Interface Science · doi:10.1016/j.cis.2025.103773 · Cited by 4 · see citing works
Self-citationPurcell, C., Ryspayeva, D., Gopal, J., Schmidt, A., Vaughn-Beaucaire, P. C., Su, A. Y., Lawler, S. E., MacDonald, W., Pinho-Schwerrman, M., El‐Deiry, W. S., et al. (2026) · Cancer Letters · doi:10.1016/j.canlet.2026.218610 · Cited by 4 · see citing works
Li, Z., Xu, J., Lin, H., Sheng, Y., Sun, J., Zhang, C., Zhang, S., Li, T., Yang, A., & Lü, W. (2025) · Pharmaceutics · doi:10.3390/pharmaceutics17050615 · Cited by 4 · see citing works
Self-citation朱金薇, Lin, H., Wang, K., Zhang, S., He, H., & Hao, K. (2026) · Journal of Controlled Release · doi:10.1016/j.jconrel.2026.114684 · Cited by 4 · see citing works
Elastic Polymer Coated Nanoparticles with Fast Clearance for 19F MR Imaging
Konishi, Y., Minoshima, M., Fujihara, K., Uchihashi, T., & Kikuchi, K. (2023) · Angewandte Chemie · doi:10.1002/ange.202308565 · Cited by 4 · see citing works
Learning what keeps nanomedicines in tumours
Wang, Y., Schrank, B. R., Jiang, W., & Kim, B. Y. S. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01251-1 · Cited by 4 · see citing works
Fixation alters the physical properties of tumor tissue that regulate nanomedicine transport
Martin, J. D., Mpekris, F., Chauhan, V. P., Martin, M. R., Walsh, M. E., Stuber, M. D., McDonald, D. M., Yuan, F., Stylianopoulos, T., & Jain, R. K. (2024) · Drug Delivery · doi:10.1080/10717544.2024.2430528 · Cited by 3 · see citing works
Ma, L., Zhang, B., Liu, X., Gao, S., Kong, S., Li, Y., Wang, R., Li, M., Mao, X., Li, Y., et al. (2025) · Frontiers in Pharmacology · doi:10.3389/fphar.2025.1641618 · Cited by 3 · see citing works
Bao, X., Zheng, Z., Li, M., Wang, X., Zhao, Q., Wang, H., Xin, Y., & Jiang, X. M. (2025) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2025.217234 · Cited by 3 · see citing works
The landscape of genitourinary cancer vaccines: clinical advances and future opportunities
Zheng, R., Cai, Y., Ding, W., Yang, F., Xu, K., & Gao, Y. (2025) · Journal of Advanced Research · doi:10.1016/j.jare.2025.11.049 · Cited by 3 · see citing works
Light‐Harvesting Photothermal Hotspots Enabled by NIR Scattering‐Absorption Coupling
Wu, Z., Bao, C., Zhang, P., Ding, T., Lin, W., Li, H., Luo, W., Deng, X., Wang, H., Li, G., et al. (2026) · Advanced Science · doi:10.1002/advs.202523721 · Cited by 3 · see citing works
- Authors
- Zhu, M., Zhuang, J., Li, Z., Liu, Q., Zhao, R., Gao, Z., Midgley, A. C., Qi, T., Tian, J., Zhang, Z., Kong, D., Tian, J., Yan, X., & Huang, X.
- Affiliations
- Nankai University (CN)
- University of Science and Technology of China (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Tian, Jingwei
- Tian, Jie
- Yan, Xiyun
- Huang, Xinglu
- ORCID
- Venue
- Nature Nanotechnology
- Published
- 2023-02-13
- Volume
- 18
- Issue
- 6
- Pages
- 657-666
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W4320486498
- Cited by
- 140
- References
- 46
- Citations by year
- 2026: 32 · 2025: 55 · 2024: 31 · 2023: 22
- FWCI
- 8.96
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Nanotechnology (publishedVersion)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (91959129, 31870999, 82072054)
- Topics
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Life Sciences › Neuroscience › Neurology › Barrier Structure and Function Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Angiogenesis and VEGF in Cancer
- Keywords
- protein nanoparticles, nanoprobes, tumor heterogeneity, transendothelial transport, tumor vasculature
- MeSH terms
- Capillary Permeability, Humans, Neoplasms, Permeability, Nanomedicine, Nanoparticles
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