Nanoresonator chip-based RNA sensor strategy for detection of circulating tumor cells: response using PCA3 as a prostate cancer marker
Abstract There is widespread interest in circulating tumor cells (CTCs) in blood. Direct detection of CTCs (often < 1/mL) is complicated by a number of factors, but the presence of ∼103 to 104 copies of target RNA per CTC, coupled with simple enrichments, can greatly increase detection capability...
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Published in | Nanomedicine Vol. 8; no. 6; pp. 1017 - 1025 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.08.2012
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Subjects | |
Online Access | Get full text |
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Summary: | Abstract There is widespread interest in circulating tumor cells (CTCs) in blood. Direct detection of CTCs (often < 1/mL) is complicated by a number of factors, but the presence of ∼103 to 104 copies of target RNA per CTC, coupled with simple enrichments, can greatly increase detection capability. In this study we used resonance frequency shifts induced by mass-amplifying gold nanoparticles to detect a hybridization sandwich bound to functionalized nanowires. We selected PCA3 RNA as a marker for prostate cancer, optimized antisense binding sites, and defined conditions allowing single nucleotide mismatch discrimination, and used a hybrid resonator integration scheme, which combines elements of top-down fabrication with strengths of bottom-up fabrication, with a view to enable multiplexed sensing. Bound mass calculated from frequency shifts matched mass estimated by counting gold nanoparticles. This represents the first demonstration of use of such nanoresonators, which show promise of both excellent specificity and quantitative sensitivity. From the Clinical Editor Cancer cell detection from blood is an emerging method for more sensitive screening for malignancies. In this work, RNA detection with nanoresonators is demonstrated to have high specificity and sensitivity, suggesting that such technology may be feasible for laboratory medicine-based cancer detection. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Current address: Department of Mechanical Engineering, University of Victoria, Victoria BC, Canada Current address: Agilent Technologies, Santa Rosa, CA |
ISSN: | 1549-9634 1549-9642 |
DOI: | 10.1016/j.nano.2011.11.009 |