NDLI: Expression of c-erbB-2 in breast cancer cell lines as experimental receptor of magnetic nanoparticles

Content Provider	IEEE Xplore Digital Library
Author	Silva, J.G. Sanchez, V. Polo, S.M. Gonzalez, C.A.
Copyright Year	2013
Description	Author affiliation: EMGS-UDEFA, México City, Mexico (Silva, J.G.; Gonzalez, C.A.) \|\| EMGS-UDEFA, Mexico City, Mexico (Polo, S.M.) \|\| Centro de Estudios Cientificos y Tecnologicos, EMGS-UDEFA, Mexico City, Mexico (Sanchez, V.)
Abstract	High mortality in breast cancer is associated to a late diagnosis and therapy of the disease. Our research group is working on the development of an innovative technology to promote selective ablation of breast cancer in early stages by the use of high frequency magnetic fields assisted by magnetic nanoparticles. The concept behind the technical proposal is to increase the electrical conductivity of tumoral tissue by the use of bioconjugated “magnetic nanoparticle-monoclonal antibody”. Is expected that bioconjugated recognizes specific genes on the surface of cancer cells. The aim of this study was to evaluate the expression of the c-erbB-2 gene and c-erbB-2 antigen in breast cancer cells type BT-474, MCF-7 and MDA-MB-231, as previous step to propose the c-erbB-2 protein as receptor of magnetic nanoparticles. The results suggest that the elected breast cancer cell lines show well-differentiated relative expression of the elected gen and antigen, and sems suitable for experimental evaluation of selective targeting by magnetic nanoparticles.
Starting Page	4498
Ending Page	4501
File Size	675341
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610546
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Breast cancer Nanoparticles Magnetic fields Magnetic resonance imaging Medical treatment Conductivity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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