Cited by 952

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Nanotechnology Applications in Cancer

Nie, Shuming, Xing, Yun, Kim, Gloria J., Simons, Jonathan W.·2007·Annual Review of Biomedical Engineering

Abstract

Cancer nanotechnology is an interdisciplinary area of research in science, engineering, and medicine with broad applications for molecular imaging, molecular diagnosis, and targeted therapy. The basic rationale is that nanometer-sized particles, such as semiconductor quantum dots and iron oxide nanocrystals, have optical, magnetic, or structural properties that are not available from molecules or bulk solids. When linked with tumor targeting ligands such as monoclonal antibodies, peptides, or small molecules, these nanoparticles can be used to target tumor antigens (biomarkers) as well as tumor vasculatures with high affinity and specificity. In the mesoscopic size range of 5–100 nm diameter, nanoparticles also have large surface areas and functional groups for conjugating to multiple diagnostic (e.g., optical, radioisotopic, or magnetic) and therapeutic (e.g., anticancer) agents. Recent advances have led to bioaffinity nanoparticle probes for molecular and cellular imaging, targeted nanoparticle drugs for cancer therapy, and integrated nanodevices for early cancer detection and screening. These developments raise exciting opportunities for personalized oncology in which genetic and protein biomarkers are used to diagnose and treat cancer based on the molecular profiles of individual patients.

Overview

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Crossref · 10.1146/annurev.bioeng.9.060906.152025

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Citations

Cites

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Metadata

Authors
Nie, S., Xing, Y., Kim, G. J., & Simons, J. W.
Affiliations
Department of Biomedical Engineering and the Winship Cancer Institute, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30322;
Venue
Annual Review of Biomedical Engineering
Published
2007-08-15
Volume
9
Issue
1
Pages
257-288
ISSN
  • 1523-9829
  • 1545-4274
Cited by
952
References
5
Language
en

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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.

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