Label-Free Plasmon-Enhanced Spectroscopic HER2 Detection for Dynamic Therapeutic Surveillance of Breast Cancer

Abstract

The expression of human epidermal growth factor receptor-2 (HER2) has important implications for pathogenesis, progression, and therapeutic efficacy of breast cancer. The detection of its variation during the treatment is crucial for therapeutic decision-making but remains a grand challenge, especially at the cellular level. Here, we develop a machine learning-driven surface-enhanced Raman spectroscopy (SERS)-integrated strategy for label-free detection of cellular HER2. Specifically, our method allows the extraction of cell-rich spectral signatures utilized for identification and classification of cancer cells with distinct HER2 expression with a high accuracy of 99.6%. By combining label-free SERS detection and machine learning-driven chemometric analysis, we are able to perform longitudinal monitoring of therapeutic efficacy at the cellular level during the treatment of HER2+ breast cancer, which aids in the subsequent decision-making and management. This work provides a promising technique capable of performing dynamic label-free spectroscopic detection for therapeutic surveillance of diseases.

Absolute Quantification of Serum Exosomes in Patients with an SERS-Lateral Flow Strip Biosensor for Noninvasive Clinical Cancer Diagnosis

“…Following the removal of unbound HER2 and MUC1 probes, the SERS data set of 50 spectra from SKBR exos and 50 spectra from MCF exos was collected and then spectrally unmixed by the multivariate curve resolution-alternating least-squares (MCR-ALS) algorithm. MCR-ALS allows decomposition of the complex experimental spectra into its pure component spectra (endmembers) with the weights (α for SKBR exos and β for MCF exos) for quantitative estimation of component abundances. , As seen in Figure a­(iii), the MCR-ALS spectral unmixing of the SERS data set yields two component spectra ( C HER2 and C MUC1 ) that exhibit 92 and 88% similarity with the SERS spectra of HER2 and MUC1 probes, respectively. We also attempted to decompose the SERS spectra into more ( n = 3, 4, or 5) component spectra, but it yielded component redundancy (Figure S8).…”

Encapsulation and assessment of therapeutic cargo in engineered exosomes: a systematic review

“…They found that intramyocardial delivery of exosomes followed by intravenous MSC infusion significantly improved cardiac function, reduced infarct size, and increased neovascularization compared to exosome alone or MSC monotherapy [ 80 ]. Xie et al presented a novel technique for label-free detection of cellular HER2 using machine learning-driven SERS, and they applied their method to dynamically monitor the therapeutic efficacy of drug-loaded exosomes targeting HER2+ breast cancer cells [ 81 ]. They showed that their method could capture the variations in HER2 expression and cell viability during the treatment, which could facilitate the therapeutic decision-making and management of breast cancer.…”

Rational Design of Near‐infrared II Plasmonic Optofunctional Materials for Diagnostic and Therapeutic Applications

“…[63,64] Overall, SERS presents many prominent features for biosensing and bioimaging: i) SERS is able to perform label-free or label-based quantitative analysis with ultrahigh sensitivity even down to single molecule level; ii) SERS spectra enrich abundant molecular fingerprint information characteristic of biological systems or events; iii) SERS is resistant to photobleaching and photodegradation so that the SERS detection is suitable for longitudinal long-term monitoring, much superior to fluorescence; iv) The spectral bandwidth of the SERS bands is usually 10-100 times narrower than that of fluorescence emission from organic dyes, inorganic nanocrystals or quantum dots so that the SERS techniques allow for convenient multiplex detection with a single wavelength excitation; v) SERS-active nanostructures can be easily designed by tailoring the particle size, shape, and surface chemistry for different purposes. These unique features have enabled SERS for a wide range of biomedical applications, including in vitro and in vivo biosensing, [65][66][67][68][69][70] multimodal image-guided therapy, [71][72][73] SERS-guided surgical navigation with precise delineation of tumor margins and intraoperative removal of microscopic tumor foci. [73][74][75][76]…”