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dc.contributor.authorClark, Amanda M.
dc.contributor.authorWheeler, Sarah E.
dc.contributor.authorTaylor, Donald P.
dc.contributor.authorPillai, Venkateswaran C.
dc.contributor.authorYoung, Carissa L.
dc.contributor.authorPrantil-Baun, Rachelle
dc.contributor.authorNguyen, Transon
dc.contributor.authorStolz, Donna B.
dc.contributor.authorBorenstein, Jeffrey T.
dc.contributor.authorLauffenburger, Douglas A.
dc.contributor.authorVenkataramanan, Raman
dc.contributor.authorGriffith, Linda G.
dc.contributor.authorWells, Alan
dc.date.accessioned2015-10-22T13:16:57Z
dc.date.available2015-10-22T13:16:57Z
dc.date.issued2014-05
dc.identifier.issn1535-3702
dc.identifier.issn1535-3699
dc.identifier.urihttp://hdl.handle.net/1721.1/99407
dc.description.abstractMetastasis accounts for almost 90% of cancer-associated mortality. The effectiveness of cancer therapeutics is limited by the protective microenvironment of the metastatic niche and consequently these disseminated tumors remain incurable. Metastatic disease progression continues to be poorly understood due to the lack of appropriate model systems. To address this gap in understanding, we propose an all-human microphysiological system that facilitates the investigation of cancer behavior in the liver metastatic niche. This existing LiverChip is a 3D-system modeling the hepatic niche; it incorporates a full complement of human parenchymal and non-parenchymal cells and effectively recapitulates micrometastases. Moreover, this system allows real-time monitoring of micrometastasis and assessment of human-specific signaling. It is being utilized to further our understanding of the efficacy of chemotherapeutics by examining the activity of established and novel agents on micrometastases under conditions replicating diurnal variations in hormones, nutrients and mild inflammatory states using programmable microdispensers. These inputs affect the cues that govern tumor cell responses. Three critical signaling groups are targeted: the glucose/insulin responses, the stress hormone cortisol and the gut microbiome in relation to inflammatory cues. Currently, the system sustains functioning hepatocytes for a minimum of 15 days; confirmed by monitoring hepatic function (urea, α-1-antitrypsin, fibrinogen, and cytochrome P450) and injury (AST and ALT). Breast cancer cell lines effectively integrate into the hepatic niche without detectable disruption to tissue, and preliminary evidence suggests growth attenuation amongst a subpopulation of breast cancer cells. xMAP technology combined with systems biology modeling are also employed to evaluate cellular crosstalk and illustrate communication networks in the early microenvironment of micrometastases. This model is anticipated to identify new therapeutic strategies for metastasis by elucidating the paracrine effects between the hepatic and metastatic cells, while concurrently evaluating agent efficacy for metastasis, metabolism and tolerability.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant 1UH2TR000496-01)en_US
dc.description.sponsorshipUnited States. Defense Advanced Research Projects Agency. Microphysiological Systems Program (W911NF-12-2-0039)en_US
dc.language.isoen_US
dc.publisherRoyal Society of Medicineen_US
dc.relation.isversionofhttp://dx.doi.org/10.1177/1535370214532596en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleA microphysiological system model of therapy for liver micrometastasesen_US
dc.typeArticleen_US
dc.identifier.citationClark, A. M., S. E. Wheeler, D. P. Taylor, V. C. Pillai, C. L. Young, R. Prantil-Baun, T. Nguyen, et al. “A Microphysiological System Model of Therapy for Liver Micrometastases.” Experimental Biology and Medicine 239, no. 9 (May 12, 2014): 1170–1179.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.mitauthorYoung, Carissa L.en_US
dc.contributor.mitauthorLauffenburger, Douglas A.en_US
dc.contributor.mitauthorGriffith, Linda G.en_US
dc.relation.journalExperimental Biology and Medicineen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsClark, A. M.; Wheeler, S. E.; Taylor, D. P.; Pillai, V. C.; Young, C. L.; Prantil-Baun, R.; Nguyen, T.; Stolz, D. B.; Borenstein, J. T.; Lauffenburger, D. A.; Venkataramanan, R.; Griffith, L. G.; Wells, A.en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8581-1261
dc.identifier.orcidhttps://orcid.org/0000-0002-1801-5548
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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