Biosensor Platforms for Molecular Analyses of Circulating Cancer Biomarkers
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CitationShao, Huilin. 2013. Biosensor Platforms for Molecular Analyses of Circulating Cancer Biomarkers. Doctoral dissertation, Harvard University.
AbstractSolid cancers often shed (sub)cellular materials into the circulation, such as circulating tumor cells and extracellular microvesicles. Mounting evidence supports that these circulating materials could serve as surrogate cancer markers for classifying primary tumors, stratifying patients for targeted therapies, assessing treatment efficacy, and achieving clinical benefits. A sensor platform capable of sensitive and portable detection of circulating cancer markers would thus be an invaluable tool, that will advance our understanding of tumor biology as well as clinical outcomes. This dissertation describes various systems that we have developed for quantitative analyses of circulating cancer biomarkers. Firstly, we have developed a novel magnetic resonance sensing platform for microvesicle analyses. By using a chip-based platform that combines microfiltration and bioorthogonal nanoparticle targeting, we demonstrate for the first time that magnetic biosensing can be applied for clinical evaluation of circulating microvesicles in blood samples to monitor cancer therapy. Secondly, we have advanced a new plasmonic sensor to achieve label-free detection of microvesicles. Based on periodic nanohole arrays, this platform has been applied for high-throughput protein profiling of microvesicles in native ascites. Finally, we have implemented microfluidic devices to effectively enrich circulating tumor cells from peripheral whole blood, and to enable comprehensive molecular analyses of isolated tumor cells at a single cell resolution. By enabling rapid, sensitive and cost-effective detection of circulating cancer markers, these developed platforms could significantly expand the reach of preclinical and clinical cancer research, in informing therapy selection, rationally directing trials, and improving sequential monitoring to achieve better clinical outcomes.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:11169784
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