The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation
Open accessAbstract
Significance: The cancer biology seed-and-soil paradigm recognizes the existence of organ-specific patterns of metastasization that drive the spread of selected primary tumors toward specific secondary loci. However, despite efforts to model the organotypic microenvironment, the organ specificity of cancer metastases needs to be elucidated. The relevance of this study lies in the generation of a human vascularized organ-specific microenvironment, which can be used to investigate and tune the extravasation process of metastatic tumor cells. Furthermore, beyond mimicking the pro- or antimetastatic signatures of different microenvironments, our microfluidic model provides insights into different properties of organ-specific endothelia. This study paves the way toward advanced in vitro models to screen for highly tailored organ-specific therapeutics and investigate key molecular pathways involved in organ-specific metastases.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“Through this, it was shown that adenosine played an important role in promoting tumor cells extravasation.”
From Microfluidic modelling of the tumor microenvironment for anti-cancer drug development (2019) · cites this paper as [98]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe cited source doesn’t support the claim as written.
In the citing paper
“By blocking A3 adenosine receptors, cancer cells were observed to have a reduced extravasation rate.”
From Microfluidic modelling of the tumor microenvironment for anti-cancer drug development (2019) · cites this paper as [98]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Endothelial cells displayed morphological features similar to in vivo conditions, contrasting to poorly aligned cells grown in 2D cultures or deprived of fl ow.”
From 3D In Vitro Model (R)evolution: Unveiling Tumor–Stroma Interactions (2021) · cites this paper as [78]
The cited source says what the claim attributes to it.
In the citing paper
“This micro fl uidic device not only promoted the perfusable culture of four different cells types but also proved to be an appropriate platform for monitoring cancer cell extravasation in real time.”
From 3D In Vitro Model (R)evolution: Unveiling Tumor–Stroma Interactions (2021) · cites this paper as [78]
The cited source says what the claim attributes to it.
In the citing paper
“The results indicated inhibitory role of adenosine on extravasation as blocking A3 adenosine receptors increased extravasation rates of breast cancer cells into the myoblast, mimicking microenvironments compared with untreated cells [57].”
From Tumor microenvironment complexity and therapeutic implications at a glance (2020) · cites this paper as [57]
The cited source says what the claim attributes to it.
In the citing paper
“Fortunately, with the development of biofabrication techniques, microfluidic and 3D bioprinting technologies have been employed to create more in vivo‐like perfusable 3D tumor models in the biomimetic matrix.[ 72 , 161 ]”
From 3D Biomimetic Models to Reconstitute Tumor Microenvironment In Vitro: Spheroids, Organoids, and Tumor‐on‐a‐Chip (2023) · cites this paper as [161]
In the citing paper
“CoC models can be applied to elucidate these effects, and researchers have developed vascularized CoC models to study extravasation to bone [74][75][76], brain [77,78], and other organs [79]”
From Cancer-on-chip models for metastasis: importance of the tumor microenvironment (2024) · cites this paper as [75]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited
Fidler, I. J. (2003) · Nature Reviews Cancer · doi:10.1038/nrc1098 · Cited by 4,686
Dissemination and growth of cancer cells in metastatic sites
Chambers, A. F., Groom, A. C., & MacDonald, I. C. (2002) · Nature reviews. Cancer · doi:10.1038/nrc865 · Cited by 4,018
Tumor Metastasis: Molecular Insights and Evolving Paradigms
Valastyan, S., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.09.024 · Cited by 4,011
Cell Migration: A Physically Integrated Molecular Process
Lauffenburger, D. A., & Horwitz, A. F. (1996) · Cell · doi:10.1016/s0092-8674(00)81280-5 · Cited by 3,915
Metastasis: from dissemination to organ-specific colonization
Nguyen, D. X., Bos, P. D., & Massagué, J. (2009) · Nature reviews. Cancer · doi:10.1038/nrc2622 · Cited by 2,716
Molecular regulation of vessel maturation
Jain, R. K. (2003) · Nature Medicine · doi:10.1038/nm0603-685 · Cited by 2,594
Tumor Self-Seeding by Circulating Cancer Cells
Kim, M.-Y., Oskarsson, T., Acharyya, S., Nguyen, D. X., Zhang, X. H.-F., Norton, L., & Massagué, J. (2009) · Cell · doi:10.1016/j.cell.2009.11.025 · Cited by 1,335
Crossing the endothelial barrier during metastasis
Reymond, N., d'Água, B. B., & Ridley, A. J. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3628 · Cited by 922
Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function
Zervantonakis, I. K., Hughes-Alford, S. K., Charest, J. L., Condeelis, J. S., Gertler, F. B., & Kamm, R. D. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1210182109 · Cited by 872
Self-citation
Cited by
Sorted by citations
Items 501–600 of 722
Danoy, M., Shinohara, M., Rizki-Safitri, A., Collard, D., Senez, V., & Sakai, Y. (2017) · Integrative Biology · doi:10.1039/c6ib00237d · Cited by 11
Future perspectives from lung cancer pre-clinical models: new treatments are coming?
Bersani, F., Morena, D., Picca, F., Morotti, A., Tabbò, F., Bironzo, P., Righi, L., & Taulli, R. (2020) · Translational Lung Cancer Research · doi:10.21037/tlcr-20-189 · Cited by 10
Cancer Cell Direct Bioprinting: A Focused Review
Lobo, D. A., Ginestra, P. S., Ceretti, E., Puig, T., & Ciurana, J. (2021) · Micromachines · doi:10.3390/mi12070764 · Cited by 11
Rimal, R., Desai, P. B., Márquez, A. B., Sieg, K., Marquardt, Y., & Singh, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-01513-x · Cited by 11
Natesh, N. R., Mogha, P., Chen, A., Antonia, S. J., & Varghese, S. (2024) · APL Bioengineering · doi:10.1063/5.0188238 · Cited by 11
Moon, B., Li, K., Malic, L., Morton, K. J., Shao, H., Banh, L., Viswanathan, S., Young, E. W. K., & Veres, T. (2024) · Lab on a Chip · doi:10.1039/d4lc00530a · Cited by 11
Advances in the Construction and Application of Bone‐on‐a‐Chip Based on Microfluidic Technologies
Zhong, C., Tang, Z., Yu, X., Wang, L., Ren, C., Qin, L., & Zhou, P. (2024) · Journal of Biomedical Materials Research Part B Applied Biomaterials · doi:10.1002/jbm.b.35502 · Cited by 11
Innovative in vitro models for breast cancer drug discovery
Kaemmerer, E., Garzon, T. E. R., Lock, A. M., Lovitt, C. J., & Avery, V. M. (2016) · Drug Discovery Today Disease Models · doi:10.1016/j.ddmod.2017.02.002 · Cited by 10
Modeling Tumor: Lymphatic Interactions in Lymphatic Metastasis of Triple Negative Breast Cancer
Ji, K., Zhao, Z., Sameni, M., Moin, K., Xu, Y., Gillies, R. J., Sloane, B. F., & Mattingly, R. R. (2021) · Cancers · doi:10.3390/cancers13236044 · Cited by 10
Xu, H., Cheng, C., & Le, W. (2022) · Electrophoresis · doi:10.1002/elps.202100360 · Cited by 10
Zhang, K., Du, Z., Yuan, T., Huang, J., Zhao, X., & Mi, S. (2022) · Biomicrofluidics · doi:10.1063/5.0090027 · Cited by 10
Kwak, D., Im, Y., Nam, H., Nam, U., Kim, S., Kim, W., Kim, H. J., Park, J., & Jeon, J. S. (2024) · Acta Biomaterialia · doi:10.1016/j.actbio.2024.01.021 · Cited by 10
Self-citationImage-guided, Laser-based Fabrication of Vascular-derived Microfluidic Networks
Heintz, K. A., Mayerich, D. M., & Slater, J. H. (2017) · Journal of Visualized Experiments · doi:10.3791/55101 · Cited by 13
Application of microfluidic technology in cancer research and therapy
Azadi, S., Es, H. A., Kulasinghe, A., Bordhan, P., & Warkiani, M. E. (2020) · Advances in clinical chemistry · doi:10.1016/bs.acc.2020.02.012 · Cited by 10
Yu, J., Piazza, A. N., Sparks, S., Hind, L. E., Niles, D. J., Ingram, P., Huang, W. C., Ricke, W. A., Jarrard, D. F., Anna Huttenlocher, A., et al. (2021) · Integrative Biology · doi:10.1093/intbio/zyab004 · Cited by 10
Ugrinic, M., Decanini, D., Bidan, N., Lazzari, G., Harouri, A., Hwang, G., Haghiri‐Gosnet, A., & Mura, S. (2022) · Microelectronic Engineering · doi:10.1016/j.mee.2022.111898 · Cited by 13
The Application of Microfluidic Techniques on Tissue Engineering in Orthopaedics
Wang, L., Jiang, D., Wang, Q., Wang, Q., Hu, H., & Jia, W. (2019) · Current Pharmaceutical Design · doi:10.2174/1381612825666190301142833 · Cited by 10
Unlocking the future: converging multi-organ-on-a-chip on the current biomedical sciences
Basak, S. (2020) · Emergent Materials · doi:10.1007/s42247-020-00124-y · Cited by 10
The use of microphysiological systems to model metastatic cancer
Jackson, C. E., Green, N. H., English, W., & Claeyssens, F. (2024) · Biofabrication · doi:10.1088/1758-5090/ad3b70 · Cited by 10
Jackett, K. N., DaPonte, D. L., Soman, P., & Horton, J. A. (2025) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-025-00774-y · Cited by 13
A Four-Dimensional Organoid System to Visualize Cancer Cell Vascular Invasion
Yanagisawa, K., Konno, M., Liu, H., Irie, S., Mizushima, T., Mori, M., Doki, Y., Eguchi, H., Matsusaki, M., & Ishii, H. (2020) · Biology · doi:10.3390/biology9110361 · Cited by 10
Learning Collective Cell Migratory Dynamics from a Static Snapshot with Graph Neural Networks
Yang, H., Meyer, F., Huang, S., Liu, Y., Lungu, C., Olayioye, M. A., Buehler, M. J., & Guo, M. (2024) · PRX Life · doi:10.1103/prxlife.2.043010 · Cited by 10
How to build a tumor: An industry perspective
Schüler, J. B., Borenstein, J. T., Buti, L., Dong, M., Masmoudi, F., Hribar, K. C., Anderson, E., & Sommergruber, W. (2022) · Drug Discovery Today · doi:10.1016/j.drudis.2022.07.014 · Cited by 9
Multi-organ microphysiological system: A new paradigm for COVID-19 research
Wang, P., Wang, Y., & Qin, J. (2023) · Organs-on-a-Chip · doi:10.1016/j.ooc.2023.100029 · Cited by 11
Parihar, P., Sunildutt, N., Rahim, C. S. A., Samantasinghar, A., Lim, J., & Choi, K. H. (2024) · Advanced Therapeutics · doi:10.1002/adtp.202300410 · Cited by 10
Engineered Biomaterials and Model Systems to Study YAP/TAZ in Cancer
Villares, E., & Gerecht, S. (2024) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.4c01170 · Cited by 9
Invasion/chemotaxis- and extravasation-chip models for breast cancer bone metastasis
Yildirir, B. F., Bati‐Ayaz, G., Nonappa, N., Pesen‐Okvur, D., & Yalcin-Ozuysal, Ö. (2024) · PLoS ONE · doi:10.1371/journal.pone.0309285 · Cited by 8
Mazzaglia, C., Huang, Y. Y. S., & Shields, J. D. (2024) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2024.115485 · Cited by 10
Biomaterials meet organ-on-chips – a perspective on tumor modeling
Monteiro, C. F., Deus, I. A., Custódio, C. A., & Mano, J. F. (2024) · International Materials Reviews · doi:10.1177/09506608241303436 · Cited by 9
Gestational Breast Cancer – a Review of Outcomes, Pathophysiology, and Model Systems
Callaway, M. K., & dos Santos, C. O. (2023) · Journal of Mammary Gland Biology and Neoplasia · doi:10.1007/s10911-023-09546-w · Cited by 8
Scemama, A., Lunetto, S., Tailor, A., Ciò, S. D., Dibble, M., Gautrot, J. E., & Biddle, A. (2024) · F1000Research · doi:10.12688/f1000research.131810.2 · Cited by 7
A high-throughput microfabricated platform for rapid quantification of metastatic potential
Bhattacharya, S., Ettela, A., Haydak, J. C., Hobson, C. M., Stern, A. D., Yoo, M., Chew, T., Gusella, G. L., Gallagher, E. J., Hone, J., et al. (2024) · Science Advances · doi:10.1126/sciadv.adk0015 · Cited by 8
A perforated microhole-based microfluidic device for improving sprouting angiogenesis in vitro
Chen, S., Zhang, L., Zhao, Y., Ke, M., Li, B., Chen, L., & Cai, S. (2017) · Biomicrofluidics · doi:10.1063/1.4994599 · Cited by 8
Principles of Personalized Oncology
Jain, K. K. (2020) · Springer eBooks · doi:10.1007/978-3-030-62080-6_19 · Cited by 7
Noorani, B., Cucullo, L., Ahn, Y., Kadry, H., Bhalerao, A., Raut, S., Nozohouri, E., & Chowdhury, E. A. (2022) · Current Neuropharmacology · doi:10.2174/1570159x20666220706112711 · Cited by 9
Huang, C., & Lei, K. F. (2022) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2022.132458 · Cited by 8
Highlight: microfluidic devices for cancer metastasis studies
Scemama, A., Lunetto, S., & Biddle, A. (2022) · In vitro models · doi:10.1007/s44164-022-00023-y · Cited by 7
Sigdel, I., Ofori‐Kwafo, A., Heizelman, R., Nestor‐Kalinoski, A. L., Prabhakarpandian, B., Tiwari, A. K., & Tang, Y. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1227119 · Cited by 8
Microdevices for Non-Invasive Detection of Bladder Cancer
Tzouanas, C. N., Lim, J., Wen, Y., Thiery, J. P., & Khoo, B. (2017) · Chemosensors · doi:10.3390/chemosensors5040030 · Cited by 8
Flat Cell Culturing Surface May Cause Misinterpretation of Cellular Uptake of Nanoparticles
Behzadi, S., Vatan, N. M., Lema, K., Nwaobasi, D., Zenkov, I., Abadi, P. P. S. S., Khan, D. A., Corbo, C., Aghaverdi, H., Farokhzad, O. C., et al. (2018) · Advanced Biosystems · doi:10.1002/adbi.201800046 · Cited by 8
Cassie–Baxter Surfaces for Reversible, Barrier-Free Integration of Microfluidics and 3D Cell Culture
Torabi, S., Li, L., Grabau, J. D., Sands, M., Berron, B. J., Xu, R., & Trinkle, C. A. (2019) · Langmuir · doi:10.1021/acs.langmuir.9b01163 · Cited by 8
A Multi-Niche Microvascularized Human Bone-Marrow-on-a-ChipPreprint
Nelson, M. R., Ghoshal, D., Mejías, J. C., Rubio, D. A. F., Keith, E., & Roy, K. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.15.876813 · Cited by 8
Human breast tissue engineering in health and disease
Buchholz, M., Scheerman, D. I., Levato, R., Wehrens, E. J., & Rios, A. C. (2024) · EMBO Molecular Medicine · doi:10.1038/s44321-024-00112-3 · Cited by 8
Watanabe, T., Hatayama, N., Guo, M. Z., Yuhara, S., & Shinoka, T. (2024) · Bioengineering · doi:10.3390/bioengineering11100954 · Cited by 8
Bone-on-a-Chip Systems for Hematological Cancers
Kozalak, G., & Koşar, A. (2025) · Biosensors · doi:10.3390/bios15030176 · Cited by 7
Patient-Derived Tumour Organoids (PDOs) may help oncologists in clinical practice
Brandi, R., Palcau, A. C., Migliano, E., Strano, S., & Blandino, G. (2025) · Personalized Medicine · doi:10.1080/17410541.2025.2581557 · Cited by 7
Zarin, B., Rafiee, L., Abdollahi, S., Vatani, M., Hassani, M., Sanati‐Nezhad, A., & Javanmard, S. H. (2025) · Translational Oncology · doi:10.1016/j.tranon.2025.102303 · Cited by 7
Contextual Control of Adipose-Derived Stem Cell Function: Implications for Engineered Tumor Models
Wittmann, K., & Fischbach, C. (2016) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.6b00328 · Cited by 7
Guo, J., Keller, K. A., Govyadinov, P. A., Ruchhoeft, P., Slater, J. H., & Mayerich, D. M. (2018) · Analytical Methods · doi:10.1039/c8ay01798k · Cited by 8
Li, B. ‘., Scott, E., Olafsen, N. E., Matthews, J. B., & Wheeler, A. R. (2021) · Lab on a Chip · doi:10.1039/d1lc00854d · Cited by 7
Chen, D., Yin, J., Yang, Z., Qin, W., Huo, J., Huang, J. H., Sun, J., & Piao, W. (2022) · Nutrients · doi:10.3390/nu14132768 · Cited by 7
Biomaterials for Mimicking and Modelling Tumor Microenvironment
Das, R., & Fernandez, J. G. (2022) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-04039-9_6 · Cited by 8
Vessel-on-a-Chip: A Powerful Tool for Investigating Endothelial COVID-19 Fingerprints
Shevchuk, O. O., Palii, S. M., Pak, A., Chantada, N., Seoane, N., Korda, M. M., Campos‐Toimil, M., & Álvarez, E. (2023) · Cells · doi:10.3390/cells12091297 · Cited by 7
Scaffold-integrated microchips for end-to-end in vitro tumor cell attachment and xenograft formation
Lee, J., Kohl, N., Shanbhang, S., & Parekkadan, B. (2015) · TECHNOLOGY · doi:10.1142/s2339547815500065 · Cited by 7
Gilardi, M., Bersini, S., Boussommier-Calleja, A., Kamm, R. D., Vanoni, M., & Moretti, M. (2016) · Thrombosis Research · doi:10.1016/s0049-3848(16)30145-1 · Cited by 7
Self-citationLee, Y., Lee, G., Cho, M., & Park, J. (2019) · Journal of Micromechanics and Microengineering · doi:10.1088/1361-6439/ab0796 · Cited by 7
Perforated and Endothelialized Elastomeric Tubes for Vascular Modeling
Duchamp, M., Bakht, S. M., Ju, J., Yazdi, I. K., Zhang, W., & Zhang, Y. S. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201800741 · Cited by 7
Yoon, N., Dadson, K., Dang, T. Q., Chu, T., Noskovičová, N., Hinz, B., Raignault, A., Thorin, É., Kim, S., Jeon, J. S., et al. (2019) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00564.2018 · Cited by 7
Self-citationEngineered tumor models for cancer biology and treatment
Moon, H., & Han, B. (2020) · Elsevier eBooks · doi:10.1016/b978-0-08-102983-1.00015-6 · Cited by 7
Monzo, P., Crestani, M., & Gauthier, N. C. (2020) · Neuromethods · doi:10.1007/978-1-0716-0856-2_8 · Cited by 7
Jeong, C. G., Negro, G. D., Getsios, S., & Ekert, J. E. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-813671-3.00005-0 · Cited by 8
A 3D, Compartmental Tumor-Stromal Microenvironment Model of Patient-Derived Bone Metastasis
Garakani, M. M., Cooke, M. E., Wertheimer, M. R., Wertheimer, M. R., Ajji, A., & Rosenzweig, D. H. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms24010160 · Cited by 6
Biomechanical and mechanobiological design for bioprinting functional microvasculature
Zhang, D., Liu, J., Liu, X., & Fan, Y. (2025) · Applied Physics Reviews · doi:10.1063/5.0227692 · Cited by 7
Advances in microfluidic biofabrication technology for bone metastasis modeling
Khanmohammadi, M., Ahmadkhani, N., Volpi, M., Khederlou, K., Uppal, A., Hosseini, M., Zhang, Y. S., & Święszkowski, W. (2025) · Biofabrication · doi:10.1088/1758-5090/add95f · Cited by 8
Gensheimer, T., Fuchs, S., de Heus, L. E., Vermeul, K., Mayr, T., & van der Meer, A. D. (2025) · Advanced Materials Technologies · doi:10.1002/admt.202500194 · Cited by 6
Organoid-on-a-chip (OrgOC): Advancing cystic fibrosis research
Zheng, M., Erice, E., Wang, H., Zhang, L., & Lawrie, C. H. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.102148 · Cited by 8
Lu, J., Huang, Y., Hu, S., Xuzhan, L., Huang, Y., Wu, B., Zhao, C., Huang, J., Tan, B., Zhao, B., et al. (2026) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2026.118791 · Cited by 7
Yuan, X., Duan, X., Zhao, L., Yao, B., Enhejirigala, Song, W., Kong, Y., Wang, Y., Zhang, F., Liang, L., et al. (2022) · Burns & Trauma · doi:10.1093/burnst/tkac035 · Cited by 6
Applications and Prospects of Microfluidic Chips in Orthopaedic Diseases
Yang, X., Tang, Q., Chen, L., Wu, K., & Shi, X. (2021) · Frontiers in Materials · doi:10.3389/fmats.2020.610558 · Cited by 7
The prospects of microphysiological systems in modeling platelet pathophysiology in cancer
Ghosh, L. D., & Jain, A. (2023) · Platelets · doi:10.1080/09537104.2023.2247489 · Cited by 6
Recent advances on cancer-on-chip models: Development of 3D tumors and tumor microenvironment
Moghimi, N., Hosseini, S. A., Poudineh, M., & Kohandel, M. (2022) · Bioprinting · doi:10.1016/j.bprint.2022.e00238 · Cited by 6
3D Organotypic Culture Model to Study Components of ERK Signaling
Chioni, A., Bajwa, R. T., & Grose, R. P. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-6424-6_19 · Cited by 6
Current Trends in Microfluidics and Biosensors for Cancer Research Applications
Caballero, D., Reis, R. L., & Kundu, S. C. (2022) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-04039-9_4 · Cited by 6
Dibble, M., Ciò, S. D., Luo, P., Balkwill, F. R., & Gautrot, J. E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.03.490457 · Cited by 6
Fu, B. M., & 李云飞 (2025) · Cells · doi:10.3390/cells14060456 · Cited by 5
Harnessing Advances in Bone Tissue Engineering for Design of Bone‐on‐Chip Systems
Sanaei, F., Hajee, Y., Koons, G. L., Wu, D. T. S., Leeuwenburgh, S. C. G., van den Beucken, J. J. J. P., & Diba, M. (2025) · Advanced Healthcare Materials · doi:10.1002/adhm.202503525 · Cited by 8
Multilayered microfluidic platform for three-dimensional vascularized organ-on-a-chip applications
Zhou, C., Li, Z., Xu, J., Yu, D., Xuan, L., & Wang, X. (2025) · Bio-Design and Manufacturing · doi:10.1631/bdm.2500091 · Cited by 6
Engineered bone matrix models for understanding breast cancer skeletal metastasis
Persson, K. M., Whitman, M. A., & Fischbach, C. (2026) · Cancer and Metastasis Reviews · doi:10.1007/s10555-025-10310-1 · Cited by 6
Scemama, A., Tailor, A., Ciò, S. D., Dibble, M., Gautrot, J. E., & Biddle, A. (2023) · F1000Research · doi:10.12688/f1000research.131810.1 · Cited by 5
Progress in patient-derived liver cancer cell models: a step forward for precision medicine
Zhang, Z., & Hui, L. (2023) · Acta Biochimica et Biophysica Sinica · doi:10.3724/abbs.2023224 · Cited by 5
Assessing the metastatic potential of circulating tumor cells using an organ-on-chip model
Rechberger, K. F., Zeinali, S., Moser, S. K., Dubey, C., Schneider, S., Deng, H., Haefliger, S., Marti, T. M., & Guenat, O. T. (2024) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2024.1457884 · Cited by 5
Modelomics to Investigate Cancer Bone Metastasis
Shafiee, A., & Hutmacher, D. W. (2018) · Current Molecular Biology Reports · doi:10.1007/s40610-018-0094-x · Cited by 5
Using organoid models to predict chemotherapy efficacy: the future of precision oncology?
Forsythe, S. D., Pu, T., & Skardal, A. (2019) · Expert Review of Precision Medicine and Drug Development · doi:10.1080/23808993.2019.1685868 · Cited by 5
Trends in biomaterials for three-dimensional cancer modeling
Caballero, D., Reis, R. L., & Kundu, S. C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818128-7.00001-0 · Cited by 5
Hwang, S.-H., Park, D., Lee, J.-W., Lee, S., & Kim, H. F. (2024) · Nature Communications · doi:10.1038/s41467-024-53342-x · Cited by 5
Coşkun, U. C., Kus, F., Rehman, A. U., Morova, B., Gülle, M., Baser, H., Kul, D., Kıraz, A., Baysal, K., & Erten, A. C. (2022) · ACS Omega · doi:10.1021/acsomega.1c05118 · Cited by 5
3-D Tissue Modelling and Virtual Pathology as New Approaches to Study Ductal Carcinoma In Situ
Booth, M. E., Nash, C. E., Roberts, N. P., Magee, D. R., Treanor, D. E., Hanby, A. M., & Speirs, V. (2015) · Alternatives to Laboratory Animals · doi:10.1177/026119291504300605 · Cited by 5
Integration of systems biology with organs-on-chips to humanize therapeutic development
Edington, C., Cirit, M., Chen, W. L. K., Clark, A. M., Wells, A. H., Trumper, D. L., & Griffith, L. G. (2017) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2256078 · Cited by 5
Martino, M. T. D., Zazzeroni, F., Donadelli, M., Chiodoni, C., Caraglia, M., Scotlandi, K., Meschini, S., & Leonetti, C. (2018) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-018-0710-x · Cited by 5
3D Bioprinting of Collagen-based Microfluidics for Engineering Fully-biologic Tissue SystemsPreprint
Shiwarski, D. J., Hudson, A. R., Tashman, J. W., Bakırcı, E., Moss, S., Coffin, B. D., & Feinberg, A. W. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.26.577422 · Cited by 5
An embedded microfluidic valve for dynamic control of cellular communication
DeAngelis, M. A., Ruder, W. C., & LeDuc, P. R. (2023) · Applied Physics Letters · doi:10.1063/5.0172538 · Cited by 4
Microfluidic manipulation of the multicellular spheroids and organoids for modeling human diseases
Zhao, L., Xiong, S., Wang, D., & Wang, X. (2025) · Microchemical Journal · doi:10.1016/j.microc.2025.113718 · Cited by 4
Hanin, L. G. (2023) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2023.111582 · Cited by 4
Cells in the 3D biomatrix on-chip: better mimicking the real micro-physiological system
D’Orazio, M., Filippi, J., Antonelli, G., Curci, G., Casti, P., Mencattini, A., Cidonio, G., & Martinelli, E. (2024) · Next Materials · doi:10.1016/j.nxmate.2024.100229 · Cited by 4
Santillán-Cortez, D., Castell-Rodríguez, A. E., González‐Arenas, A., Suárez‐Cuenca, J. A., Hautefeuille, M., Pérez‐Koldenkova, V., Añorve-Bailón, D., Garcı́a, S., Toledo-Lozano, C. G., Escamilla-Tilch, M., et al. (2024) · Bioengineering · doi:10.3390/bioengineering11101008 · Cited by 4
Microtechnology Applied to Stem Cells Research and Development
Acevedo, J. P., Angelopoulos, I., van Noort, D., & Khoury, M. (2018) · Regenerative Medicine · doi:10.2217/rme-2017-0123 · Cited by 4
Tumor-on-a-chip devices for cancer immunotherapy
Mu, X., & Zhang, Y. S. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90949-5.00006-1 · Cited by 4
Recent Development of Cell Analysis on Microfludics
He, Z., & Lin, J. (2017) · Integrated analytical systems · doi:10.1007/978-981-10-5394-8_2 · Cited by 4
Three Dimensional In Vitro Tumor Platforms for Cancer Discovery
Gadde, M., Marrinan, D., Michna, R. J., & Rylander, M. N. (2017) · Cancer drug discovery and develogment/Cancer drug discovery and development · doi:10.1007/978-3-319-60511-1_5 · Cited by 4
Bachmann, B., Spitz, S., Jordan, C., Schuller, P., Wanzenböck, H. D., Haddadi, B., Harasek, M., Redl, H. R., Holnthoner, W., & Ertl, P. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.08.438936 · Cited by 4
Metadata
- Authors
- Jeon, J. S., Bersini, S., Gilardi, M., Dubini, G., Charest, J. L., Moretti, M., & Kamm, R. D.
- Affiliations
- Massachusetts Institute of Technology (US)
- IRCCS Ospedale Galeazzi - Sant'Ambrogio (IT)
- Politecnico di Milano (IT)
- Draper Laboratory (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-12-18
- Volume
- 112
- Issue
- 1
- Pages
- 214-219
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4291627
- OpenAlex
- W2081560083
- Semantic Scholar
- f475569e9cefbccc34378d56e185a60e479f18b8
- Cited by
- 723
- References
- 44
- Citations by year
- 2026: 28 · 2025: 44 · 2024: 53 · 2023: 71 · 2022: 79 · 2021: 85 · 2020: 83 · 2019: 71 · 2018: 77 · 2017: 59 · 2016: 52 · 2015: 21
- FWCI
- 22.85
- Type
- journal article
- Language
- en
- Update notices
- correction (2015-02-02)
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
- BOA (University of Milano-Bicocca) (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- HHS | NIH | National Cancer Institute (R33 CA174550-01, R21 CA140096)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular Mechanics and Interactions
- Keywords
- breast cancer, tumor cell extravasation, organ-specific metastasis, microvascular permeability, A3 adenosine receptor, drug screening, personalized medicine
- MeSH terms
- Adenosine, Animals, Breast Neoplasms, Capillary Permeability, Extravasation of Diagnostic and Therapeutic Materials, Female, Humans, Stress, Mechanical, Shear Strength, Microfluidics, Cell Line, Tumor, Mice, Microvessels, Cellular Microenvironment, Human Umbilical Vein Endothelial Cells
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review