SERS analysis of serum for detection of early and locally advanced breast cancer.

ABSTRACT

In this contribution, we investigated whether surface-enhanced Raman scattering (SERS) of serum can be a candidate method for detecting "luminal A" breast cancer (BC) at different stages. We selected three groups of participants aged over 50 years 20 healthy women, 20 women with early localized small BC, and 20 women affected by BC with lymph node involvement. SERS revealed clear spectral differences between these three groups. A predictive model using principal component analysis (PCA) and linear discriminant analysis (LDA) was developed based on spectral data, and its performance was estimated with cross-validation. PCA-LDA of SERS spectra could distinguish healthy from BC subjects (sensitivity, 92 %; specificity, 85 %), as well as subjects with BC at different stages, with a promising diagnostic performance (sensitivity and specificity, ≥80 %; overall accuracy, 84 %). Our data suggest that SERS spectroscopy of serum, combined with multivariate data analysis, represents a minimally invasive, easy to use, and fast approach to discriminate healthy from BC subjects and even to distinguish BC at different clinical stages.