The distribution of the anticancer drug Doxorubicin in relation to blood vessels in solid tumors
Abstract
Purpose Anticancer drugs gain access to solid tumors via the circulatory system and must penetrate the tissue to kill cancer cells. Here, we study the distribution of doxorubicin in relation to blood vessels and regions of hypoxia in solid tumors of mice. Experimental design The distribution of doxorubicin was quantified by immunofluorescence in relation to blood vessels (recognized by CD31) of murine 16C and EMT6 tumors and human prostate cancer PC-3 xenografts. Hypoxic regions were identified by injection of EF5. Results The concentration of doxorubicin decreases exponentially with distance from tumor blood vessels, decreasing to half its perivascular concentration at a distance of about 40 to 50 mum, The mean distance from blood vessels to regions of hypoxia is 90 to 140 microm in these tumors. Many viable tumor cells are not exposed to detectable concentrations of drug following a single injection. Conclusions Limited distribution of doxorubicin in solid tumors is an important and neglected cause of clinical resistance that is amenable to modification. The technique described here can be adapted to studying the distribution of other drugs within solid tumors and the effect of strategies to modify their distribution.
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The three-dimensional architecture of solid tumors presents significant challenges to the effective penetration and distribution of therapeutic agents.
“The three-dimensional (3D) architecture of solid tumors presents significant challenges to the effective penetration and distribution of therapeutic agents [99,100].”
From Modeling Tumor Microenvironment Complexity In Vitro: Spheroids as Physiologically Relevant Tumor Models and Strategies for Their Analysis (2025) · cites this paper as [100]
Cites
Normalization of Tumor Vasculature: An Emerging Concept in Antiangiogenic Therapy
Jain, R. K. (2005) · Science · doi:10.1126/science.1104819 · Cited by 5,527 · see citing works
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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
Self-citationDrug Resistance and the Solid Tumor Microenvironment
Tredan, O., Galmarini, C. M., Patel, K., & Tannock, I. F. (2007) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djm135 · Cited by 2,116 · 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
Improving drug delivery to solid tumors: Priming the tumor microenvironment
Khawar, I. A., Kim, J. H., & Kuh, H.-J. (2015) · Journal of Controlled Release · doi:10.1016/j.jconrel.2014.12.018 · Cited by 533 · see citing works
Lee, H., Fonge, H., Hoang, B., Reilly, R. M., & Allen, C. (2010) · Molecular Pharmaceutics · doi:10.1021/mp100038h · Cited by 349 · see citing works
Mikhail, A. S., & Allen, C. (2009) · Journal of Controlled Release · doi:10.1016/j.jconrel.2009.04.010 · Cited by 328 · see citing works
Chawla, S. P., Cranmer, L. D., Van Tine, B. A., Reed, D. R., Okuno, S. H., Butrynski, J. E., Adkins, D. R., Hendifar, A. E., Kroll, S., & Ganjoo, K. N. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.54.3660 · Cited by 155 · see citing works
Hyperthermia can alter tumor physiology and improve chemo- and radio-therapy efficacy
Dunne, M., Regenold, M., & Allen, C. (2020) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2020.07.007 · Cited by 150 · see citing works
Rodenhizer, D., Gaude, E., Cojocari, D., Mahadevan, R., Frezza, C., Wouters, B. G., & McGuigan, A. P. (2016) · Nature Materials · doi:10.1038/nmat4482 · Cited by 132 · see citing works
The role of kinin receptors in cancer and therapeutic opportunities
da Costa, P. L. N., Sirois, P., Tannock, I. F., & Chammas, R. (2014) · Cancer Letters · doi:10.1016/j.canlet.2013.12.009 · Cited by 133 · see citing works
Self-citationLiu, Q., Sun, J. D., Wang, J., Ahluwalia, D., Baker, A. F., Cranmer, L. D., Ferraro, D., Wang, Y., Duan, J.-X., Ammons, W. S., et al. (2012) · Cancer Chemotherapy and Pharmacology · doi:10.1007/s00280-012-1852-8 · Cited by 113 · see citing works
Vilgelm, A. E., Pawlikowski, J. S., Liu, Y., Hawkins, O. E., Davis, T. A., Smith, J., Weller, K. P., Horton, L. W., McClain, C. M., Ayers, G. D., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-14-2405 · Cited by 115 · see citing works
Tumor Cells Upregulate Normoxic HIF-1α in Response to Doxorubicin
Cao, Y., Eble, J. M., Moon, E., Yuan, H., Weitzel, D. H., Landon, C. D., Yu-Chih Nien, C., Hanna, G., Rich, J. N., Provenzale, J. M., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-1345 · Cited by 111 · see citing works
Application of nanoparticles on diagnosis and therapy in gliomas.
Hernández-Pedro, N. Y., Rangel-López, E., Magaña-Maldonado, R., de la Cruz, V. P., Santamaría del Angel, A., Pineda, B., & Sotelo, J. (2013) · BioMed Research International · doi:10.1155/2013/351031 · Cited by 84 · see citing works
Rodenhizer, D., Dean, T., D'Arcangelo, E., & McGuigan, A. P. (2018) · Advanced Healthcare Materials · doi:10.1002/adhm.201701174 · Cited by 80 · see citing works
Assessing the <i>in Vivo</i> Efficacy of Doxorubicin Loaded Hyaluronan Nanoparticles
El-Dakdouki, M. H., Xia, J., Zhu, D. C., Kavunja, H., Grieshaber, J., O’Reilly, S., McCormick, J. J., & Huang, X. (2014) · ACS Applied Materials & Interfaces · doi:10.1021/am404946v · Cited by 69 · see citing works
Shah, S., & D’Souza, G. G. M. (2025) · Cells · doi:10.3390/cells14100732 · Cited by 66 · see citing works
“The three-dimensional (3D) architecture of solid tumors presents significant challenges to the effective penetration and distribution of therapeutic agents [99,100].”
Yokoi, K., Chan, D., Kojic, M., Milosevic, M., Engler, D., Matsunami, R., Tanei, T., Saito, Y., Ferrari, M., & Ziemys, A. (2015) · Journal of Controlled Release · doi:10.1016/j.jconrel.2015.09.044 · Cited by 36 · see citing works
Dou, Y. N., Chaudary, N., Chang, M. C., Dunne, M., Huang, H., Jaffray, D. A., Milosevic, M., & Allen, C. (2017) · Journal of Controlled Release · doi:10.1016/j.jconrel.2017.07.039 · Cited by 21 · see citing works
- Authors
- Primeau, A. J., Rendon, A., Hedley, D., Lilge, L., & Tannock, I. F.
- Affiliations
- University of Toronto (CA)
- 2Biophysics and Bioimaging, and
- Venue
- Clinical Cancer Research
- Published
- 2005-12-15
- Volume
- 11
- Issue
- 24
- Pages
- 8782-8788
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- OpenAlex
- W2093916414
- Cited by
- 499
- References
- 1
- Citations by year
- 2026: 14 · 2025: 11 · 2024: 19 · 2023: 25 · 2022: 27 · 2021: 20 · 2020: 24 · 2019: 30 · 2018: 32 · 2017: 38 · 2016: 40 · 2015: 27 · 2014: 27 · 2013: 45 · 2012: 31
- FWCI
- 3.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Angiogenesis and VEGF in Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Keywords
- doxorubicin, tumor vasculature, tumor hypoxia, drug penetration, chemoresistance, CD31, EF5, EMT6 tumor, mouse tumors
- MeSH terms
- Animals, Antibiotics, Antineoplastic, Blood Vessels, Doxorubicin, Humans, Microscopy, Neoplasm Transplantation, Neoplasms, Drug Resistance, Neoplasm, Xenograft Model Antitumor Assays, Mice
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