4.8 Article

Highly accurate and label-free discrimination of single cancer cell using a plasmonic oxide-based nanoprobe

期刊

BIOSENSORS & BIOELECTRONICS
卷 198, 期 -, 页码 -

出版社

ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2021.113814

关键词

Surface enhanced Raman spectroscopy; Single cell detection; Colorimetric cell detection; Plasmon oxide

资金

  1. Australian Research Council [DE160100715, DE170100239, DP200101248]
  2. ARC Future Low Energy Electronics Technologies (FLEET) centre of excellence [CE170100039]
  3. Australian Research Council [DE170100239, DP200101248] Funding Source: Australian Research Council

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A dual-functional nanoprobe based on dopant-driven plasmonic oxides is reported, which can accurately distinguish cancer cells at the single-cell level. This nanoprobe can differentiate different cells based on their SERS patterns and also enable colorimetric cell detection through bio-redox response.
The detection of cancer cells at the single-cell level enables many novel functionalities such as next-generation cancer prognosis and accurate cellular analysis. While surface-enhanced Raman spectroscopy (SERS) has been widely considered as an effective tool in a low-cost and label-free manner, however, it is challenging to discriminate single cancer cells with an accuracy above 90% mainly due to the poor biocompatibility of the noble-metal-based SERS agents. Here, we report a dual-functional nanoprobe based on dopant-driven plasmonic oxides, demonstrating a maximum accuracy above 90% in distinguishing single THP-1 cell from peripheral blood mononuclear cell (PBMC) and human embryonic kidney (HEK) 293 from human macrophage cell line U937 based on their SERS patterns. Furthermore, this nanoprobe can be triggered by the bio-redox response from individual cells towards stimuli, empowering another complementary colorimetric cell detection, approximately achieving the unity discrimination accuracy at a single-cell level. Our strategy could potentially enable the future accurate and low-cost detection of cancer cells from mixed cell samples.

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