High Uniformity and Enhancement Au@AgNS 3D Substrates for the Diagnosis of Breast Cancer

Zhengxia Yang; Hai-Sheng Su; En-Ming You; Siying Liu; Zihang Li; Yun Zhang

doi:10.1021/acsomega.2c01453

High Uniformity and Enhancement Au@AgNS 3D Substrates for the Diagnosis of Breast Cancer

ACS Omega. 2022 Apr 24;7(17):15223-15230. doi: 10.1021/acsomega.2c01453. eCollection 2022 May 3.

Authors

Zhengxia Yang^{1

2}, Hai-Sheng Su^{1

2}, En-Ming You³, Siying Liu^{1

2

4}, Zihang Li⁵, Yun Zhang^{1

2

4

6}

Affiliations

¹ CAS Key Laboratory of Design and Assembly of Functional Nanostructures, and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, P. R. China.
² Xiamen Institute of Rare Earth Materials, Haixi Institute, Xiamen Key Laboratory of Rare Earth Photoelectric Functional Materials, Chinese Academy of Sciences, Xiamen 361021, P. R. China.
³ State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.
⁴ University of Chinese Academy of Sciences, Beijing 100049, P. R. China.
⁵ Wenzhou-Kean University, 88 Daxue Road, Ouhai, Wenzhou, Zhejiang Province 325060, China.
⁶ Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi 341000, P. R. China.

Abstract

Breast cancer appears to be one of the leading causes of cancer-related morbidity and mortality for women worldwide. The accurate and rapid diagnosis of breast cancer is hence critical for the treatment and prognosis of patients. With the vibrational fingerprint information and high detection sensitivity, surface-enhanced Raman spectroscopy (SERS) has been extensively applied in biomedicine. Here, an optimized bimetallic nanosphere (Au@Ag NS) 3D substrate was fabricated for the aim of the diagnosis of breast cancer based on the SERS analysis of the extracellular metabolites. The unique stacking mode of 3D Au@Ag NSs provided multiple plasmonic hot spots according to the theoretical calculations of the electromagnetic field distribution. The low relative standard deviation (RSD = 2.7%) and high enhancement factor (EF = 1.42 × 10⁵) proved the uniformity and high sensitivity. More importantly, the normal breast cells and breast cancer cells could be readily distinguished from the corresponding SERS spectra based on the extracellular metabolites. Furthermore, the clear clusters of SERS spectra from MCF-7 and MDA-MB-231 extracellular metabolites in the orthogonal partial least-squares discriminant analysis plot indicate the distinct metabolic fingerprint between breast cancer cells, which imply their potential clinical application in the diagnosis of breast cancer.