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Issue 23, 2017
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An EGFRvIII targeted dual-modal gold nanoprobe for imaging-guided brain tumor surgery

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Abstract

Surgery is a mainstay to treat malignant brain tumors. However, due to the infiltrative nature of these tumors, it is a great challenge for surgeons to accurately identify and excise all the tumor foci. EGFRvIII, a variant of epidermal growth factor receptor (EGFR), is found in 20% of glioblastoma cases, which is the brain tumor with the highest malignancy. In this study, we developed an EGFRvIII-targeted nanoprobe to guide glioblastoma surgery by pre-operatively defining the tumor boundary via magnetic resonance imaging (MRI) and intra-operatively guiding resection by surface-enhanced resonance Raman scattering (SERRS) imaging. In vivo MRI studies show that this nanoprobe delineates an orthotopic EGFRvIII+ U87MG glioblastoma xenograft with a higher target to background ratio than the control nanoprobe without targeting specificity. With the assistance of a handheld Raman scanner, this nanoprobe successfully guided EGFRvIII+ glioblastoma resection by tracking its characteristic SERRS signal peaks. Ex vivo Raman microscopy and histological images verified that this nanoprobe precisely demarcated the glioblastoma boundary and no residual neoplastic foci were observed in the tumor bed. This dual-modal nanoprobe not only precisely guided glioblastoma resection, but also overcame the brain shift induced false-positive signal by real-timely co-registering pre-operative and intra-operative images. This nanoprobe is promising for the improvement in diagnostic accuracy and surgical outcome of EGFRvIII+ glioblastoma.

Graphical abstract: An EGFRvIII targeted dual-modal gold nanoprobe for imaging-guided brain tumor surgery

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Publication details

The article was received on 13 Feb 2017, accepted on 16 May 2017 and first published on 17 May 2017


Article type: Paper
DOI: 10.1039/C7NR01077J
Citation: Nanoscale, 2017,9, 7930-7940
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    An EGFRvIII targeted dual-modal gold nanoprobe for imaging-guided brain tumor surgery

    Q. Yue, X. Gao, Y. Yu, Y. Li, W. Hua, K. Fan, R. Zhang, J. Qian, L. Chen, C. Li and Y. Mao, Nanoscale, 2017, 9, 7930
    DOI: 10.1039/C7NR01077J

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