4.8 Article

Multiplexed specific label-free detection of NCI-H358 lung cancer cell line lysates with silicon based photonic crystal microcavity biosensors

期刊

BIOSENSORS & BIOELECTRONICS
卷 43, 期 -, 页码 50-55

出版社

ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2012.11.012

关键词

Photonic crystal microcavity; Chip integrated biosensor; Nanophotonic biosensor; Lung cancer detection; Sandwich assay; Multiplexed label-free assay

资金

  1. National Cancer Institute under the Small Business Innovation Research (SBIR) program [HHSN261201000085C]
  2. NCI [CA58187]
  3. AFOSR MURI [FA9550-08-1-0394]

向作者/读者索取更多资源

We experimentally demonstrate label-free photonic crystal (PC) microcavity biosensors in silicon-on-insulator (SOI) to detect the epithelial-mesenchymal transition (EMT) transcription factor, ZEB1, in minute volumes of sample. Multiplexed specific detection of ZEB1 in lysates from NCI-H358 lung cancer cells down to an estimated concentration of 2 cells per micro-liter is demonstrated. L13 photonic crystal microcavities, coupled to W1 photonic crystal waveguides, are employed in which resonances show high Q in the bio-ambient phosphate buffered saline (PBS). When the sensor surface is derivatized with a specific antibody, the binding of the corresponding antigen from a complex whole-cell lysate generates a change in refractive index in the vicinity of the photonic crystal microcavity, leading to a change in the resonance wavelength of the resonance modes of the photonic crystal microcavity. The shift in the resonance wavelength reveals the presence of the antigen. The sensor cavity has a surface area of similar to 11 mu m(2). Multiplexed sensors permit simultaneous detection of many binding interactions with specific immobilized antibodies from the same bio-sample at the same instant of time. Specificity was demonstrated using a sandwich assay which further amplifies the detection sensitivity at low concentrations. The device represents a proof-of-concept demonstration of label-free, high throughput, multiplexed detection of cancer cells with specificity and sensitivity on a silicon chip platform. (c) 2012 Elsevier B.V. All rights reserved.

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