COMMENTARY Tissue Barriers 3:3, e1037418; July/August/September 2015; © 2015 Taylor & Francis Group, LLC
Capillary collagen as the physical transport barrier in drug delivery to tumor microenvironment Arturas Ziemys1,*, Kenji Yokoi1, and Milos Kojic1,2,3 1
Houston Methodist Research Institute; Houston, TX USA; 2Belgrade Metropolitan University; Research and Development Center for Bioengineering;
Kragujevac, Serbia; 3Serbian Academy of Sciences and Arts; Belgrad, Serbia
T
Keywords: biophysical marker, collagen, drug delivery, pharmacokinetics, tumor microenvironment, vascular barrier *Correspondence to: Arturas [email protected]
Ziemys;
he capillary wall is among the most important barriers that controls mass exchange between tumor microenvironment and systemic circulation. There are numerous studies on endothelial cells role in this mass exchange, but the role of capillary collagen of Type-IV in transport of small molecules and nanotherapeutics is less known. Our recent study revealed that the capillary wall collagen modulates the drug transport across the wall, and that it can be taken as a biophysical marker for drug transport. In our in vivo investigations with the 3LL and 4T1 tumors we noticed the differences in the collagen content in capillary walls. The imaging analysis and transport computational model of the capillary microenvironment showed that the penetration of doxorubicin (DOX) and pegylated liposomal doxorubicin (PLD) is substantially reduced by larger collagen content in the capillaries of the 3LL tumors. The results pointed to the importance of transport oncophysics, which opens a new avenue with respect to classical biology in understanding and improving drug delivery by nanotherapeutics, and aims to better explain the therapeutic resistance.
Email:
Submitted: 03/10/2015
Introduction
Revised: 03/26/2015 Accepted: 03/27/2015 http://dx.doi.org/10.1080/21688370.2015.1037418 Commentary on: Yokoi K, M Kojic, M Milosevic, T Tanei, M Ferrari, and A Ziemys, Capillary-wall collagen as a biophysical marker of nanotherapeutic permeability into the tumor microenvironment. Cancer Res. 2014; 74: 4239–4246
www.tandfonline.com
The advent of nanotherapeutics started changing the landscape of drug delivery, especially in the treatment of cancer.1,2 There are many nanotherapeutic formulations developed with different nano- and microstructures which rely on numerous materials, like lipid particles, liposomes, micelles, serum albumin particles, fullerTissue Barriers
enes, carbon nanotubes, silica and silicon, metallic particles, polymeric particles, or hydrogels. Nanotherapeutics loaded with therapeutic or imaging payload for the enhanced delivery with benefits in lower systemic toxicity, increased therapeutic dose, advantages over classical drugs in pharmacokinetics (PKs), and improved therapy.3,4 Nanotherapeutics, or drug vectors (DVs), is most frequently delivered by the systemic circulation after intravenous injections, which distributes DVs across vascular network and body. That is the same route as for classical systemic drug delivery; however the difference emerges as soon as DVs start to interact with the body, especially within the vascular tree. The benefits and shortfalls of nanotherapeutics can be attributed to the altered biodistribution in organs or tissues, where the delivery of the therapeutic payload depends on tissue barriers.5,6 Specifically, it is assumed that the Enhanced Permeability and Retention (EPR) effect is related to the fact that particles of a certain size preferentially accumulate in the tumor environment.7 The preferentially increased number of nanotherapeutics particles in tumor tissues enables enhanced therapeutic payload delivery compared to classical systemic drug delivery. At the same time, the Mononuclear Phagocyte System (MPS), consisting of phagocytic cells in the lymph nodes, spleen, or the Kupffer cells in the liver, sequester circulating nanotherapeutic particles.8 This effect usually is not desired and chemical modifications by using PEG9 are employed to make the circulating particles less visible to MPS, leading to the reduction of the lost nanotherapeutic particles from the circulation. Because of the e1037418-1
EPR and MPS, the PKs of vectors are very different from those of small molecule drugs, and therapeutic payload that is associated with a nanotherapeutic particle will adopt the carrier’s PK profile.10 The nanotherapeutics distribution in systemic circulation tree eventually leads to the interactions between drug delivering particles and vessel walls. In the drug delivery process, a drug molecule has to pass through biological barriers on the way from systemic circulation down to tumor cells in tumor microenvironment. If systemic circulation relies on convective (flow) transport, diffusion becomes fundamental transport mode for payload extravasation into tumor microenvironment. Therefore, concentration gradients drive passively the payload diffusion into tumor microenvironment.11 Our study of the 3LL and 4T1 tumors revealed that the differences in the vascular barrier (Fig. 1) lead to different levels of payload extravasation from the Pegylated Liposomal Doxorubicin (PLD) formulation.12 More specifically, the differences in the capillary collagen become a specific marker of doxorubicin (DOX) extravasation delivered by PLD. Therefore, the actual PK inside tumors of different types or phenotypes may become different, and emphasize the importance of the tumor
microenvironment PK (mPK), suggesting that the mPK is more adequate in judging therapeutic efficacies.13
Vascular barrier in drug delivery The vascular barrier might be one of the most important biological barriers in human body, responsible for modulating the exchange of mass between blood and tissues, including nutrients, gasses, metabolites, and eventually – therapeutics. The vascular barrier is composed of endothelial cells and basal membrane, forming a structure which separates fluid of systemic circulation from tissue. The gap between endothelial cells is very small (on the order of tens or hundreds of nanometers), offering the passage for paracellular transport. The gap is the domain where passive diffusion controls the mass exchange between blood and microenvironment. Endothelial cells provide more complex transport modalities: active transport of xenobiotics out of cell, active internalization of particulates, and also passive concentration gradient-driven diffusion. The aspects above are very important in analyzing drug transport as it manifests the interplay of transports: bringing drug-loaded nanotherapeutics into endothelial and transporting small molecules (payload) out of
Figure 1. The differences of the 3LL and 4T1 tumors in the content of capillary collagen (green). Endothelia (red) and thick collagen bands colocalize leading to yellow zones in the 3Ll tumors, while the 4T1 lack capillary collagen. The insets illustrate processed view into collagen and capillary overlap (capillaries – red, collagen – green, colocalization – yellow).
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endothelial cells. Apart from endothelial and immune cells, not many other cells have very pronounced role in active transport of particulates, like endocytosis. Finally, endothelial cells rest on the basal membrane, which serves as a substrate for endothelial cells to tile capillaries and other vessels. One of the most important constituents of the basal membrane is collagen of type-IV, which like a sleeve surrounds capillaries. Structurally, this capillary collagen has a mesh-like structure with an average mesh size of 400–800 nm and thickness of approximately 50– 60 nm. The structure of capillary collagen is well reviewed in,14,15 showing that several morphologies do exist. Moreover, capillary collagen was found to be associated with the tissue ability to regenerate vessels on an old collagen scaffold.16 In view of capillary collagen, our results offer additional insight into the vascular barrier and the role of collagen, where the capillary collagen directly or indirectly modulates the transport of liposomes and small molecules. Even more interesting, our analysis showed that capillary collagen can function as a semi-permeable barrier for the size-based exclusion of particles or molecules. We have shown that the effective size of collagen mesh opening is critical to large particles, like PLD of~80 nm: the diffusion transport of liposomes becomes substantially reduced when the collagen mesh gets smaller than 200 nm. As anticipated, the collagen sleeve does not represent any substantial barrier to smaller molecules like DOX. Regarding the transport properties of collagen sleeve, the in vivo data of the 3LL and 4T1 tumors clearly illustrated that the DOX extravasation from PLD formulation is impeded by larger collagen content in the 3LL tumors. Although the 4T1 tumors are known to be more aggressive compared to the 3LL, the 3LL tumors did not respond to PLD; but the 4T1 – which lacks of capillary collagen – did respond.17 Therefore, the phenotypical differences among the 3LL and 4T1 tumors exceed just biology, but extend into the structure of tumor microenvironment, and particularly – to transport barriers. This aspect of tumor classification as a rule has been neglected, because the majority of the cancer community is traditionally focused on
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very biological determinants of cancer, like mutations, genes, or protein expression. Although current results indicated the correlation of collagen content in the vascular barrier and the mPK, more studies are needed to reveal better the true role of capillary collagen in modulation of transport.
Transport oncophysics The physics of transport of therapeutics historically was not considered very important, but lately there is more awareness about its importance in oncology, nanomedicine, and drug delivery.6 The study of PLD (DOX) delivery to the 3LL and 4T1 tumors has shown the actual manifestation of the transport barrier providing phenotypically-specific control over DOX extravasation. One of the most innovative approaches about the analysis of DOX and PLD transport was incorporation of specific DOX and PLD interactions with collagen scaffold. The inclusion of molecular interactions and microstructure of surrounding into transport is relatively new approach we have developed over the last 5 years.18 We demonstrated that particle and molecular size and their interactions with the collagen matrix modulate transport and the extravasation. This formulation of diffusion transport is a deviation from the classical Fickian diffusion, which in certain cases may result to non-Fickian transport.19 For the same
reason, although sometimes the drug delivery can phenomenologically look as the classical Fickian transport, in reality it is much more complex phenomena being governed by physical and chemical properties of drug vectors and tissues. However, the dominant approach to quantify and rationalize diffusion transport in tissues exclusively relies on the classical Fick’s law and converges to the fitting of diffusion coefficient D. Once D is fit, it usually integrates all transport effects, but at the same time it also hides better understanding of transport phenomena and limits the opportunities to improve drug delivery. Therefore, the rational design of drug delivery strategies should have deeper insight how physical and chemical properties of tissues, drugs and drug vectors control mass exchange. This topic became one of the important programs in NIH which are focused on how physical processes at different scales could help to understand cancer disease.20 Here, a tight integration of many disciplines is needed, like the study about capillary collagen which relies on cancer biology and transport physics.
Transport models in drug delivery The computational models of cancer can be very sophisticated, where the complexity transcends multiple scales (from the molecular to the organ level) and biological processes involved. Tumor models
Figure 2. Drug Vector (DV) localization in tumor microenvironment can be different, like illustrated in (A). DV are depicted as large green circles carrying inside therapeutic payload (small dark green circles). The systemic delivery example is depicted for the comparison with DV marginated on the vessel wall and internalized into perivascular space. The differences in DV localization can lead to very different concentration profiles (B), as predicted in Ref.29 Therefore, differences in collagen microstructure of the 3LL and 4T1 tumors may control the DV localization and, consequently, different mPK in tumor microenvironment.
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Tissue Barriers
reveal valuable mechanisms which bring major insights into complex oncology problems, like tumor growth, metastasis and circulating cancer cells, progression, invasion, mutations, heterogeneity, invasion, or resistance. Most of these models employ reaction–diffusion–advection equations for mass transports, but some can be hybrid with involving discrete and continuous,21 or statistical variables.22-24 Drug delivery and distribution models make another group focusing on transport problems, which is well reviewed in Ref..25 Most frequently, a sophisticated mathematics seeks to decipher vascularization and fluid mechanics, vascular geometry and extravasation, drug tumor uptake, cellular fate and pharmacodynamics, transport in stroma, advection, or drug vector uptake. Despite the recognized significance of mass transport in cancer,26 there are still missing links to connect therapeutic efficacy, pharmacology, and mass transport of therapeutics in phenotypically-specific fashion. While different tumor phenotypes can have very different structure of microenvironment (e.g. vascularization, cell density, etc.), the appropriate computational model and theory should be applied, which are capable to use that information in the prediction and understanding of mPK. Our recently developed computational multiscale transport theory and methodology enabled us to couple molecular and micro-scales for better prediction of drug transport.18,27,28 We have used the systemic PK and characteristic pathology information to feed the transport models for the 3LL and 4T1 tumors. The kinetics of DOX accumulation showed that the DOX retention overcomes limitations of poorer diffusing DOX-loaded liposomes (PLD). In the light of the above discussed collagen role in capillary barrier and oncophysics, the multiscale transport model succeeded to show transport differentials based on physics which controls the transport properties through biopolymers. Our latest computational analysis of mPK focused more on the role of diffusion and convective transport in microenvironment (Fig. 2), and showed that the localization of nanotherapeutics can have dramatic effects on local concentration in
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microenvironment: concentration and the area under the curve (AUC) of internalized drug vectors can be larger by up to 2 orders of magnitude than in case of circulating or adhered at the capillary walls.29 Non-biological markers The use of biomarkers in oncology and clinics is widely spread, which is also well reflected in numerous publications; although some debate about the usefulness of biomarkers is alive.30 Biomarkers are classified to prognostic, predictive and pharmacodynamic, where each can aid in the rational development of better therapies.31 The prognostic biomarkers provide a guess about the natural evolution of individual cancer, the pharmacodynamics biomarkers give clues to short-term therapeutic effects, and the predictive biomarkers enable us to predict the probability of therapeutic efficacy for a specific patient. In general, all biomarkers rely on the expression of biomolecules. On the other hand, physical or biophysical markers are less frequently in use, probably not because these markers do not exist, but because the oncology is led by biologists and clinicians who have less bias for physical sciences. For example, the online search at the date of preparing this commentary gives references to approximately 500,000 cancer biomarkers, 400 physical markers, and only 70 biophysical markers. The growth in modern diagnostic techniques brings new technologies that rely on physical aspects of nature and enables to expand markers according to physical or biophysical properties. The capillary collagen as a biophysical marker appeared not in the context of growing diagnostic modality, but rather due to the increasing attention to physical aspects of cancer - oncophysics. The differences in vascular barrier between the 3LL and 4T1 tumors correlate well drug extravasation (DOX in our case) with the microstructure and the collagen content in capillary walls. Our study has shown that the collagen content and DOX extravasation is positively correlated with the therapeutic efficacy of the in vivo investigation. Therefore, the collagen content could be used as a predictive marker of the physical origin, which enables evaluation of whether a specific tumor
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phenotype would be responding to therapy or not. Furthermore, a set of proteins circulating in plasma was found to serve as surrogate markers for the collagen content in tumor microenvironment.17 A combination of both markers would ideally allow to correlate patient biopsies with blood samples, with making prediction even more reliable. Our study offered an insight into cancer mPK and suggested new biophysical markers; however, the usefulness of biophysical markers has to be investigated deeper. Further, the most important questions would be whether the content of capillary collagen can be used in case of other anti-cancer drugs and nanotherapeutics (other than DOX and PLD), and what about other tumor phenotypes – how far our results can be extrapolated (?). Additionally, we have to learn if capillary collagen – as a biophysical marker – predicts mass extravasation (transport) alone, or it also reveals the health of endothelial cells and the whole vascular barrier. Perspectives The results of the 3LL and 4T1 tumors in PLD delivery to tumor microenvironment have touched the topic well known in cancer biology – the heterogeneity.32 The heterogeneity can be discussed in view of a particular tumor and its microenvironment, among phenotypes, or even wider. Although in most cases the primary tumors can be resected, the leading problem is metastasis.33,34 While the primary tumor can be a single formation, metastasis may lead to multiple or even hundreds of secondary tumor sites. Certain heterogeneity can be expected among those sites, which will be affected in part by the local tissue microenvironment. In the case of metastasis, as well as among different patients, the differences in the vascular barrier may bring differences in the extravasation of therapeutic molecules which is the key for the therapeutic outcomes. This consideration of the vascular barrier is beyond the classical determinants of the biological origin. The coupling between oncophysics, mass transport, and multiscale transport model, used here in studying the differences of 2 tumors, emphasized the importance of tumor microenvironment PK and the key role of
Tissue Barriers
physical transport in it. We expect that further efforts in investigating the role of the microstructure of tumor microenvironment, its transport properties, and local heterogeneities, could ultimately help to improve drug delivery, nanotherapeutics, and to overcome therapeutic resistance of metastasis.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed. Acknowledgments
The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that contributed to the results reported in this paper. Funding
This project was partially supported by the Houston Methodist Research Institute, and also by grant OI 174028 of the Serbian Ministry of Education and Science. The authors also acknowledge partial support from the National Institute of Health (U54CA143837). References 1. Ferrari M. Cancer nanotechnology: opportunities and challenges. Nat Rev Cancer 2005; 5:161–71; PMID:15738981; http://dx.doi.org/10.1038/nrc1566 2. Wang AZ, Langer R, Farokhzad OC. Nanoparticle delivery of cancer drugs. Annu Rev Med 2012; 63:185– 98; PMID:21888516; http://dx.doi.org/10.1146/ annurev-med-040210-162544 3. Shi J, Votruba AR, Farokhzad OC, Langer R. Nanotechnology in drug delivery and tissue engineering: from discovery to applications. Nano Lett 2010; 10:3223–30; PMID:20726522; http://dx.doi.org/ 10.1021/nl102184c 4. Caruthers SD, Wickline SA, Lanza GM. Nanotechnological applications in medicine. Curr Opin Biotechnol 2007; 18:26–30; PMID:17254762; http://dx.doi.org/ 10.1016/j.copbio.2007.01.006 5. Sriraman SK, Aryasomayajula B, Torchilin VP. Barriers to drug delivery in solid tumors. Tissue Barriers 2014; 2:e29528; PMID:25068098; http://dx.doi.org/ 10.4161/tisb.29528 6. Ferrari M. Frontiers in cancer nanomedicine: directing mass transport through biological barriers. Trends Biotechnol 2010; 28:181–8; PMID:20079548; http://dx. doi.org/10.1016/j.tibtech.2009.12.007 7. Matsumura Y, Maeda H. A new concept for macromolecular therapeutics in cancer chemotherapy: mechanism of tumoritropic accumulation of proteins and the antitumor agent smancs. Cancer Res 1986; 46:6387– 92; PMID:2946403 8. Geissmann F, Gordon S, Hume DA, Mowat AM, Randolph GJ. Unravelling mononuclear phagocyte
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heterogeneity. Nat Rev Immunol 2010; 10:453–460; PMID:20467425; http://dx.doi.org/10.1038/nri2784 Li SD, Huang L. Stealth nanoparticles: high density but sheddable PEG is a key for tumor targeting. J Control Release 2010; 145:178–81; PMID:20338200; http:// dx.doi.org/10.1016/j.jconrel.2010.03.016 Simovic S, Prestidge CA. Nanoparticle layers controlling drug release from emulsions. Eur J Pharm Biopharm 2007; 67:6739–47; PMID:17329085 Yuan F. Transvascular drug delivery in solid tumors. in Semin Radiat Oncol. Elsevier; 1998; 8(3):164–75; http://dx.doi.org/10.1016/S1053-4296(98)80042-8 Yokoi K, Kojic M, Milosevic M, Tanei T, Ferrari M, Ziemys A. Capillary-wall collagen as a biophysical marker of nanotherapeutic permeability into the tumor microenvironment. Cancer Res 2014; 74:4239–46; PMID:24853545; http://dx.doi.org/10.1158/00085472.CAN-13-3494 Presant C, Wolf W, Waluch V, Wiseman C, Kennedy P, Blayney D, Brechner R, Kennedy D. Association of intratumoral pharmacokinetics of fluorouracil with clinical response. Lancet 1994; 343:1184–7; PMID:7909867; http://dx.doi.org/10.1016/S01406736(94)92399-X Van der Rest M, Garrone R. Collagen family of proteins. FASEB J 1991; 5:2814–23; PMID:1916105 Laurie G, Leblond C, Martin G. Localization of type IV collagen, laminin, heparan sulfate proteoglycan, and fibronectin to the basal lamina of basement membranes. J Cell Biol 1982; 95:340–44; PMID:6216257; http:// dx.doi.org/10.1083/jcb.95.1.340 Inai T, Mancuso M, Hashizume H, Baffert F, Haskell A, Baluk P, Hu-Lowe DD, Shalinsky DR, Thurston G, Yancopoulos GD. Inhibition of vascular endothelial growth factor (VEGF) signaling in cancer causes loss of endothelial fenestrations, regression of tumor vessels, and appearance of basement membrane ghosts. Am J Pathol 2004; 165:35–52; PMID:15215160; http://dx. doi.org/10.1016/S0002-9440(10)63273-7 Yokoi K, Tanei T, Godin B, van de Ven AL, Hanibuchi M, Matsunoki A, Alexander J, Ferrari M. Serum
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biomarkers for personalization of nanotherapeutics-based therapy in different tumor and organ microenvironments. Cancer Lett 2014; 345:48–55; PMID:24370567; http:// dx.doi.org/10.1016/j.canlet.2013.11.015 Kojic M, Milosevic M, Kojic N, Kim K, Ferrari M, Ziemys A. A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure. Computer Methods Appl Mech Eng 2014; 269:123–138; PMID:24578582; http://dx.doi.org/10.1016/j. cma.2013.11.010 Ziemys A, Kojic M, Milosevic M, Ferrari M. Interfacial effects on nanoconfined diffusive mass transport regimes. Phys Rev Lett 2012; 108:5; PMID:23003974; http://dx.doi.org/10.1103/PhysRevLett.108.236102 Moore NM, Calcagno AM, Hanlon S, Nagahara LA, Kuhn NZ. Editorial. Cell Mol Bioeng 2010; 3:334–6; http://dx.doi.org/10.1007/s12195-010-0144-9 Rejniak KA, Anderson AR. Hybrid models of tumor growth. Wiley Interdiscip Rev Syst Biol Med 2011; 3:115–125; PMID:21064037 McFarland CD, Mirny LA, Korolev KS. Tug-of-war between driver and passenger mutations in cancer and other adaptive processes. Proc Natl Acad Sci 2014; 111:15138–43; PMID:25277973; http://dx.doi.org/ 10.1073/pnas.1404341111 Newton PK, Mason J, Bethel K, Bazhenova L, Nieva J, Norton L, Kuhn P. Spreaders and sponges define metastasis in lung cancer: a Markov chain Monte Carlo mathematical model. Cancer Res 2013; 73:2760–9; PMID:23447576; http://dx.doi.org/10.1158/00085472.CAN-12-4488 Newton PK, Mason J, Bethel K, Bazhenova LA, Nieva J, Kuhn P. A stochastic Markov chain model to describe lung cancer growth and metastasis. PLoS One 2012; 7: e34637; PMID:22558094; http://dx.doi.org/10.1371/ journal.pone.0034637 Kim M, Gillies RJ, Rejniak KA. Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues. Front Oncol 2013; 3:278;
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PMID:24303366; http://dx.doi.org/10.3389/ fonc.2013.00278 Michor F, Liphardt J, Ferrari M, Widom J. What does physics have to do with cancer? Nat Rev Cancer 2011; 11:657–70; PMID:21850037 Ziemys A, Kojic M, Milosevic M, Kojic N, Hussain F, Ferrari M, Grattoni A. Hierarchical modeling of diffusive transport through nanochannels by coupling molecular dynamics with finite element method. J Comput Phys 2011; 230:5722–31; http://dx.doi.org/ 10.1016/j.jcp.2011.03.054 Ruiz Esparza GU, Wu S, Segura Ibarra V, Cara FE, Evans KW, Milosevic M, Ziemys A, Kojic M, Meric Bernstam F, Ferrari M. Polymer nanoparticles encased in a cyclodextrin complex shell for potential site and sequence specific drug release. Adv Funct Mater 2014; 24:4753–61; http://dx.doi.org/10.1002/ adfm.201400011 Ziemys A, Klemm S, Milosevic M, Yokoi K, Ferrari M, Kojic M. Computational analysis of drug transport in tumor microenvironment as a critical compartment for nanotherapeutic pharmacokinetics. Drug Deliv 2015; (accepted); PMID:25835222 Carroll KJ. Biomarkers in drug development: friend or foe? A personal reflection gained working within oncology. Pharm Stat 2007; 6:253–60; PMID:17351904; http://dx.doi.org/10.1002/pst.269 Sawyers CL. The cancer biomarker problem. Nature 2008; 452:548–52; PMID:18385728; http://dx.doi. org/10.1038/nature06913 Fidler IJ. Tumor heterogeneity and the biology of cancer invasion and metastasis. Cancer Res 1978; 38:2651–60; PMID:354778 SEER Cancer Statistics Review, 1975–2008. SEER Cancer Statistics Review, 1975–2008 2011; Available from: http://seer.cancer.gov/csr/1975_2008/. Freyer G, Ligneau B, Tranchand B, Ardiet C, SerreDebeauvais F, Trillet-Lenoir V. Pharmacokinetic studies in cancer chemotherapy: usefulness in clinical practice. Cancer Treat Rev 1997; 23:153; PMID:9251720; http://dx.doi.org/10.1016/S0305-7372(97)90036-0
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Capillary collagen as the physical transport barrier in drug delivery to tumor microenvironment Arturas Ziemys1,*, Kenji Yokoi1, and Milos Kojic1,2,3 1
Houston Methodist Research Institute; Houston, TX USA; 2Belgrade Metropolitan University; Research and Development Center for Bioengineering;
Kragujevac, Serbia; 3Serbian Academy of Sciences and Arts; Belgrad, Serbia
T
Keywords: biophysical marker, collagen, drug delivery, pharmacokinetics, tumor microenvironment, vascular barrier *Correspondence to: Arturas [email protected]
Ziemys;
he capillary wall is among the most important barriers that controls mass exchange between tumor microenvironment and systemic circulation. There are numerous studies on endothelial cells role in this mass exchange, but the role of capillary collagen of Type-IV in transport of small molecules and nanotherapeutics is less known. Our recent study revealed that the capillary wall collagen modulates the drug transport across the wall, and that it can be taken as a biophysical marker for drug transport. In our in vivo investigations with the 3LL and 4T1 tumors we noticed the differences in the collagen content in capillary walls. The imaging analysis and transport computational model of the capillary microenvironment showed that the penetration of doxorubicin (DOX) and pegylated liposomal doxorubicin (PLD) is substantially reduced by larger collagen content in the capillaries of the 3LL tumors. The results pointed to the importance of transport oncophysics, which opens a new avenue with respect to classical biology in understanding and improving drug delivery by nanotherapeutics, and aims to better explain the therapeutic resistance.
Email:
Submitted: 03/10/2015
Introduction
Revised: 03/26/2015 Accepted: 03/27/2015 http://dx.doi.org/10.1080/21688370.2015.1037418 Commentary on: Yokoi K, M Kojic, M Milosevic, T Tanei, M Ferrari, and A Ziemys, Capillary-wall collagen as a biophysical marker of nanotherapeutic permeability into the tumor microenvironment. Cancer Res. 2014; 74: 4239–4246
www.tandfonline.com
The advent of nanotherapeutics started changing the landscape of drug delivery, especially in the treatment of cancer.1,2 There are many nanotherapeutic formulations developed with different nano- and microstructures which rely on numerous materials, like lipid particles, liposomes, micelles, serum albumin particles, fullerTissue Barriers
enes, carbon nanotubes, silica and silicon, metallic particles, polymeric particles, or hydrogels. Nanotherapeutics loaded with therapeutic or imaging payload for the enhanced delivery with benefits in lower systemic toxicity, increased therapeutic dose, advantages over classical drugs in pharmacokinetics (PKs), and improved therapy.3,4 Nanotherapeutics, or drug vectors (DVs), is most frequently delivered by the systemic circulation after intravenous injections, which distributes DVs across vascular network and body. That is the same route as for classical systemic drug delivery; however the difference emerges as soon as DVs start to interact with the body, especially within the vascular tree. The benefits and shortfalls of nanotherapeutics can be attributed to the altered biodistribution in organs or tissues, where the delivery of the therapeutic payload depends on tissue barriers.5,6 Specifically, it is assumed that the Enhanced Permeability and Retention (EPR) effect is related to the fact that particles of a certain size preferentially accumulate in the tumor environment.7 The preferentially increased number of nanotherapeutics particles in tumor tissues enables enhanced therapeutic payload delivery compared to classical systemic drug delivery. At the same time, the Mononuclear Phagocyte System (MPS), consisting of phagocytic cells in the lymph nodes, spleen, or the Kupffer cells in the liver, sequester circulating nanotherapeutic particles.8 This effect usually is not desired and chemical modifications by using PEG9 are employed to make the circulating particles less visible to MPS, leading to the reduction of the lost nanotherapeutic particles from the circulation. Because of the e1037418-1
EPR and MPS, the PKs of vectors are very different from those of small molecule drugs, and therapeutic payload that is associated with a nanotherapeutic particle will adopt the carrier’s PK profile.10 The nanotherapeutics distribution in systemic circulation tree eventually leads to the interactions between drug delivering particles and vessel walls. In the drug delivery process, a drug molecule has to pass through biological barriers on the way from systemic circulation down to tumor cells in tumor microenvironment. If systemic circulation relies on convective (flow) transport, diffusion becomes fundamental transport mode for payload extravasation into tumor microenvironment. Therefore, concentration gradients drive passively the payload diffusion into tumor microenvironment.11 Our study of the 3LL and 4T1 tumors revealed that the differences in the vascular barrier (Fig. 1) lead to different levels of payload extravasation from the Pegylated Liposomal Doxorubicin (PLD) formulation.12 More specifically, the differences in the capillary collagen become a specific marker of doxorubicin (DOX) extravasation delivered by PLD. Therefore, the actual PK inside tumors of different types or phenotypes may become different, and emphasize the importance of the tumor
microenvironment PK (mPK), suggesting that the mPK is more adequate in judging therapeutic efficacies.13
Vascular barrier in drug delivery The vascular barrier might be one of the most important biological barriers in human body, responsible for modulating the exchange of mass between blood and tissues, including nutrients, gasses, metabolites, and eventually – therapeutics. The vascular barrier is composed of endothelial cells and basal membrane, forming a structure which separates fluid of systemic circulation from tissue. The gap between endothelial cells is very small (on the order of tens or hundreds of nanometers), offering the passage for paracellular transport. The gap is the domain where passive diffusion controls the mass exchange between blood and microenvironment. Endothelial cells provide more complex transport modalities: active transport of xenobiotics out of cell, active internalization of particulates, and also passive concentration gradient-driven diffusion. The aspects above are very important in analyzing drug transport as it manifests the interplay of transports: bringing drug-loaded nanotherapeutics into endothelial and transporting small molecules (payload) out of
Figure 1. The differences of the 3LL and 4T1 tumors in the content of capillary collagen (green). Endothelia (red) and thick collagen bands colocalize leading to yellow zones in the 3Ll tumors, while the 4T1 lack capillary collagen. The insets illustrate processed view into collagen and capillary overlap (capillaries – red, collagen – green, colocalization – yellow).
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endothelial cells. Apart from endothelial and immune cells, not many other cells have very pronounced role in active transport of particulates, like endocytosis. Finally, endothelial cells rest on the basal membrane, which serves as a substrate for endothelial cells to tile capillaries and other vessels. One of the most important constituents of the basal membrane is collagen of type-IV, which like a sleeve surrounds capillaries. Structurally, this capillary collagen has a mesh-like structure with an average mesh size of 400–800 nm and thickness of approximately 50– 60 nm. The structure of capillary collagen is well reviewed in,14,15 showing that several morphologies do exist. Moreover, capillary collagen was found to be associated with the tissue ability to regenerate vessels on an old collagen scaffold.16 In view of capillary collagen, our results offer additional insight into the vascular barrier and the role of collagen, where the capillary collagen directly or indirectly modulates the transport of liposomes and small molecules. Even more interesting, our analysis showed that capillary collagen can function as a semi-permeable barrier for the size-based exclusion of particles or molecules. We have shown that the effective size of collagen mesh opening is critical to large particles, like PLD of~80 nm: the diffusion transport of liposomes becomes substantially reduced when the collagen mesh gets smaller than 200 nm. As anticipated, the collagen sleeve does not represent any substantial barrier to smaller molecules like DOX. Regarding the transport properties of collagen sleeve, the in vivo data of the 3LL and 4T1 tumors clearly illustrated that the DOX extravasation from PLD formulation is impeded by larger collagen content in the 3LL tumors. Although the 4T1 tumors are known to be more aggressive compared to the 3LL, the 3LL tumors did not respond to PLD; but the 4T1 – which lacks of capillary collagen – did respond.17 Therefore, the phenotypical differences among the 3LL and 4T1 tumors exceed just biology, but extend into the structure of tumor microenvironment, and particularly – to transport barriers. This aspect of tumor classification as a rule has been neglected, because the majority of the cancer community is traditionally focused on
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very biological determinants of cancer, like mutations, genes, or protein expression. Although current results indicated the correlation of collagen content in the vascular barrier and the mPK, more studies are needed to reveal better the true role of capillary collagen in modulation of transport.
Transport oncophysics The physics of transport of therapeutics historically was not considered very important, but lately there is more awareness about its importance in oncology, nanomedicine, and drug delivery.6 The study of PLD (DOX) delivery to the 3LL and 4T1 tumors has shown the actual manifestation of the transport barrier providing phenotypically-specific control over DOX extravasation. One of the most innovative approaches about the analysis of DOX and PLD transport was incorporation of specific DOX and PLD interactions with collagen scaffold. The inclusion of molecular interactions and microstructure of surrounding into transport is relatively new approach we have developed over the last 5 years.18 We demonstrated that particle and molecular size and their interactions with the collagen matrix modulate transport and the extravasation. This formulation of diffusion transport is a deviation from the classical Fickian diffusion, which in certain cases may result to non-Fickian transport.19 For the same
reason, although sometimes the drug delivery can phenomenologically look as the classical Fickian transport, in reality it is much more complex phenomena being governed by physical and chemical properties of drug vectors and tissues. However, the dominant approach to quantify and rationalize diffusion transport in tissues exclusively relies on the classical Fick’s law and converges to the fitting of diffusion coefficient D. Once D is fit, it usually integrates all transport effects, but at the same time it also hides better understanding of transport phenomena and limits the opportunities to improve drug delivery. Therefore, the rational design of drug delivery strategies should have deeper insight how physical and chemical properties of tissues, drugs and drug vectors control mass exchange. This topic became one of the important programs in NIH which are focused on how physical processes at different scales could help to understand cancer disease.20 Here, a tight integration of many disciplines is needed, like the study about capillary collagen which relies on cancer biology and transport physics.
Transport models in drug delivery The computational models of cancer can be very sophisticated, where the complexity transcends multiple scales (from the molecular to the organ level) and biological processes involved. Tumor models
Figure 2. Drug Vector (DV) localization in tumor microenvironment can be different, like illustrated in (A). DV are depicted as large green circles carrying inside therapeutic payload (small dark green circles). The systemic delivery example is depicted for the comparison with DV marginated on the vessel wall and internalized into perivascular space. The differences in DV localization can lead to very different concentration profiles (B), as predicted in Ref.29 Therefore, differences in collagen microstructure of the 3LL and 4T1 tumors may control the DV localization and, consequently, different mPK in tumor microenvironment.
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reveal valuable mechanisms which bring major insights into complex oncology problems, like tumor growth, metastasis and circulating cancer cells, progression, invasion, mutations, heterogeneity, invasion, or resistance. Most of these models employ reaction–diffusion–advection equations for mass transports, but some can be hybrid with involving discrete and continuous,21 or statistical variables.22-24 Drug delivery and distribution models make another group focusing on transport problems, which is well reviewed in Ref..25 Most frequently, a sophisticated mathematics seeks to decipher vascularization and fluid mechanics, vascular geometry and extravasation, drug tumor uptake, cellular fate and pharmacodynamics, transport in stroma, advection, or drug vector uptake. Despite the recognized significance of mass transport in cancer,26 there are still missing links to connect therapeutic efficacy, pharmacology, and mass transport of therapeutics in phenotypically-specific fashion. While different tumor phenotypes can have very different structure of microenvironment (e.g. vascularization, cell density, etc.), the appropriate computational model and theory should be applied, which are capable to use that information in the prediction and understanding of mPK. Our recently developed computational multiscale transport theory and methodology enabled us to couple molecular and micro-scales for better prediction of drug transport.18,27,28 We have used the systemic PK and characteristic pathology information to feed the transport models for the 3LL and 4T1 tumors. The kinetics of DOX accumulation showed that the DOX retention overcomes limitations of poorer diffusing DOX-loaded liposomes (PLD). In the light of the above discussed collagen role in capillary barrier and oncophysics, the multiscale transport model succeeded to show transport differentials based on physics which controls the transport properties through biopolymers. Our latest computational analysis of mPK focused more on the role of diffusion and convective transport in microenvironment (Fig. 2), and showed that the localization of nanotherapeutics can have dramatic effects on local concentration in
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microenvironment: concentration and the area under the curve (AUC) of internalized drug vectors can be larger by up to 2 orders of magnitude than in case of circulating or adhered at the capillary walls.29 Non-biological markers The use of biomarkers in oncology and clinics is widely spread, which is also well reflected in numerous publications; although some debate about the usefulness of biomarkers is alive.30 Biomarkers are classified to prognostic, predictive and pharmacodynamic, where each can aid in the rational development of better therapies.31 The prognostic biomarkers provide a guess about the natural evolution of individual cancer, the pharmacodynamics biomarkers give clues to short-term therapeutic effects, and the predictive biomarkers enable us to predict the probability of therapeutic efficacy for a specific patient. In general, all biomarkers rely on the expression of biomolecules. On the other hand, physical or biophysical markers are less frequently in use, probably not because these markers do not exist, but because the oncology is led by biologists and clinicians who have less bias for physical sciences. For example, the online search at the date of preparing this commentary gives references to approximately 500,000 cancer biomarkers, 400 physical markers, and only 70 biophysical markers. The growth in modern diagnostic techniques brings new technologies that rely on physical aspects of nature and enables to expand markers according to physical or biophysical properties. The capillary collagen as a biophysical marker appeared not in the context of growing diagnostic modality, but rather due to the increasing attention to physical aspects of cancer - oncophysics. The differences in vascular barrier between the 3LL and 4T1 tumors correlate well drug extravasation (DOX in our case) with the microstructure and the collagen content in capillary walls. Our study has shown that the collagen content and DOX extravasation is positively correlated with the therapeutic efficacy of the in vivo investigation. Therefore, the collagen content could be used as a predictive marker of the physical origin, which enables evaluation of whether a specific tumor
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phenotype would be responding to therapy or not. Furthermore, a set of proteins circulating in plasma was found to serve as surrogate markers for the collagen content in tumor microenvironment.17 A combination of both markers would ideally allow to correlate patient biopsies with blood samples, with making prediction even more reliable. Our study offered an insight into cancer mPK and suggested new biophysical markers; however, the usefulness of biophysical markers has to be investigated deeper. Further, the most important questions would be whether the content of capillary collagen can be used in case of other anti-cancer drugs and nanotherapeutics (other than DOX and PLD), and what about other tumor phenotypes – how far our results can be extrapolated (?). Additionally, we have to learn if capillary collagen – as a biophysical marker – predicts mass extravasation (transport) alone, or it also reveals the health of endothelial cells and the whole vascular barrier. Perspectives The results of the 3LL and 4T1 tumors in PLD delivery to tumor microenvironment have touched the topic well known in cancer biology – the heterogeneity.32 The heterogeneity can be discussed in view of a particular tumor and its microenvironment, among phenotypes, or even wider. Although in most cases the primary tumors can be resected, the leading problem is metastasis.33,34 While the primary tumor can be a single formation, metastasis may lead to multiple or even hundreds of secondary tumor sites. Certain heterogeneity can be expected among those sites, which will be affected in part by the local tissue microenvironment. In the case of metastasis, as well as among different patients, the differences in the vascular barrier may bring differences in the extravasation of therapeutic molecules which is the key for the therapeutic outcomes. This consideration of the vascular barrier is beyond the classical determinants of the biological origin. The coupling between oncophysics, mass transport, and multiscale transport model, used here in studying the differences of 2 tumors, emphasized the importance of tumor microenvironment PK and the key role of
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physical transport in it. We expect that further efforts in investigating the role of the microstructure of tumor microenvironment, its transport properties, and local heterogeneities, could ultimately help to improve drug delivery, nanotherapeutics, and to overcome therapeutic resistance of metastasis.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed. Acknowledgments
The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that contributed to the results reported in this paper. Funding
This project was partially supported by the Houston Methodist Research Institute, and also by grant OI 174028 of the Serbian Ministry of Education and Science. The authors also acknowledge partial support from the National Institute of Health (U54CA143837). References 1. Ferrari M. Cancer nanotechnology: opportunities and challenges. Nat Rev Cancer 2005; 5:161–71; PMID:15738981; http://dx.doi.org/10.1038/nrc1566 2. Wang AZ, Langer R, Farokhzad OC. Nanoparticle delivery of cancer drugs. Annu Rev Med 2012; 63:185– 98; PMID:21888516; http://dx.doi.org/10.1146/ annurev-med-040210-162544 3. Shi J, Votruba AR, Farokhzad OC, Langer R. Nanotechnology in drug delivery and tissue engineering: from discovery to applications. Nano Lett 2010; 10:3223–30; PMID:20726522; http://dx.doi.org/ 10.1021/nl102184c 4. Caruthers SD, Wickline SA, Lanza GM. Nanotechnological applications in medicine. Curr Opin Biotechnol 2007; 18:26–30; PMID:17254762; http://dx.doi.org/ 10.1016/j.copbio.2007.01.006 5. Sriraman SK, Aryasomayajula B, Torchilin VP. Barriers to drug delivery in solid tumors. Tissue Barriers 2014; 2:e29528; PMID:25068098; http://dx.doi.org/ 10.4161/tisb.29528 6. Ferrari M. Frontiers in cancer nanomedicine: directing mass transport through biological barriers. Trends Biotechnol 2010; 28:181–8; PMID:20079548; http://dx. doi.org/10.1016/j.tibtech.2009.12.007 7. Matsumura Y, Maeda H. A new concept for macromolecular therapeutics in cancer chemotherapy: mechanism of tumoritropic accumulation of proteins and the antitumor agent smancs. Cancer Res 1986; 46:6387– 92; PMID:2946403 8. Geissmann F, Gordon S, Hume DA, Mowat AM, Randolph GJ. Unravelling mononuclear phagocyte
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