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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Simultaneous and highly sensitive detection of multiple breast cancer biomarkers in real samples using a SERS
Zhihua Zheng1, Lei Wu1, Lang Li1
1Advanced Photonics Center, Southeast University, Nanjing 210096, China.
Abstract:
Accurate and quantitative analysis of breast cancer biomarkers is a particularly requisite in the early diagnosis of breast cancers, especially in real samples. Here, we develop a surface enhanced Raman scattering (SERS) immunoassay biosensor based on a microfluidic chip for the simultaneous detection of multiple breast cancer biomarkers in real samples. In such an immunoassay, immuno-Ag aggregates are labeled with different Raman reporters to detect multiple breast cancer biomarkers in real samples. Moreover, to better enhance the Raman signals, self-assembled silver nanoparticles are introduced on the bottom of the microfluidic channels to obtain the SERS active immune-substrate. In order to avoid the crosstalk of SERS signals, we designed a spatially separated detection biosensor by using multi-channels in a microfluidic chip. In the experiments, CA153, CA125 and CEA are selected as the models of breast cancer biomarkers, which can be simultaneously detected of in human serum with an excellently specificity and a high sensitivity. Furthermore, the proposed SERS microfluidic biosensor can be applied to detect the biomarkers in real samples using a linear regression method for the statistical analysis. Our detection results are in agreement with those obtained using commercial ELISA kits, which proves the reliability of our SERS-based microfluidic immunoassay.
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