FOXO3a in cancer drug resistance.

Profiling the heterogeneous landscape of cell types and biomolecules is rapidly being adopted to address current imperative research questions. Precision medicine seeks advancements in molecular spatial profiling techniques with highly multiplexed imaging capabilities and subcellular resolution, which remains an extremely complex task. Surface-enhanced Raman spectroscopy (SERS) imaging offers promise through the utilization of nanoparticle-based contrast agents that exhibit narrow spectral features and molecular specificity. The current renaissance of gold nanoparticle technology makes Raman scattering intensities competitive with traditional fluorescence methods while offering the added benefit of unsurpassed multiplexing capabilities. Here, we present an expanded library of individually distinct SERS nanoparticles to arm researchers and clinicians. Our nanoparticles consist of a ∼60 nm gold core, a Raman reporter molecule, and a final inert silica coating. Using density functional theory, we have selected Raman reporters that meet the key criterion of high spectral uniqueness to facilitate unmixing of up to 26 components in a single imaging pixel in vitro and in vivo. We also demonstrated the utility of our SERS nanoparticles for targeting cultured cells and profiling cancerous human tissue sections for highly multiplexed optical imaging. This study showcases the far-reaching capabilities of SERS-based Raman imaging in molecular profiling to improve personalized medicine and overcome the major challenges of functional and structural diversity in proteomic imaging.

Expanding the Multiplexing Capabilities of Raman Imaging to Reveal Highly Specific Molecular Expression and Enable Spatial Profiling.

Surface-Enhanced Raman Spectroscopy (SERS) is a powerful analytical technique for the detection of small analytes with great potential for medical diagnostic applications. Its high sensitivity and excellent molecular specificity, which stems from the unique fingerprint of molecular species, have been applied toward the detection of different types of cancer. The noninvasive and rapid detection offered by SERS highlights its applicability for point-of-care (PoC) deployment for cancer diagnosis, screening, and staging, as well as for predicting tumor recurrence and treatment monitoring. This review provides an overview of the progress in label-free (direct) SERS-based chemical detection for cancer diagnosis with the main focus on the advances in the design and preparation of SERS substrates on the basis of metal nanoparticle structures formed via bottom-up strategies. It begins by introducing a synopsis of the working principles of SERS, including key chemometric approaches for spectroscopic data analysis. Then it introduces the advances of label-free sensing with SERS in cancer diagnosis using biofluids (blood, urine, saliva, sweat) and breath as the detection media. In the end, an outlook of the advances and challenges in cancer diagnosis via SERS is provided.

Label-Free Sensing with Metal Nanostructure-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis.

We report on the influence of resistivity in picosecond (ps) laser ablation of silicon (Si) leading to the formation of diverse surface micro- and nanostructures. Subsequently, we investigated their potential in sensing applications based on the surface enhanced Raman scattering (SERS) technique. The varying resistivity (ρ 1: 1–10 Ω cm, ρ 2: 0.01–0.02 Ω cm, ρ 3: 0.001–0.005 Ω cm) Si wafers were subjected to cross patterned ps laser ablation in ambient air. Ladder-like microstructures embedded with numerous nano growths were formed on low resistivity Si (ρ 3) while similar micro- and nanostructures were observed on higher resistivity Si (ρ 2 < ρ 1). The structures were non-plasmonic and anti-reflecting in nature with an optical reflectance of <6% over a broad range of wavelengths (350–1200 nm). Non-plasmonic Si microstructures were subsequently transformed to plasmonic by means of deposition of a thin layer of gold (Au). Additionally, the effect of annealing on the evolution of nanostructures was also investigated. We employed these hybrid substrates for the trace detection of an explosive molecule, ammonium nitrate, and dye, malachite green. Our detailed SERS studies have demonstrated a superior enhancement in the trace detection of analytes for low resistivity Si substrate. However, the annealed hybrid substrates have demonstrated further improvement in the SERS signal (by at least one order of magnitude). These detailed SERS investigations provide us a proof of the sensitivity of different resistivity Si nano/microstructures.

Resistivity dependence on nanostructure formation in picosecond ablation of silicon and SERS-based sensing applications

The detection and identification of molecular traces in the environment as well as in the human breath are very significant for the development of a healthy society. This is extremely...

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Nanomaterial-based surface-enhanced Raman scattering spectroscopy for sensing and diagnostics gas molecules in environment and healthcare

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.

https://zenodo.org/record/6651711/files/2022%20Plou%20acsphotonics.pdf

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

During the response to different stress conditions, damaged cells react in multiple ways, including the release of a diverse cocktail of metabolites. Moreover, secretomes from dying cells can contribute to the effectiveness of anticancer therapies and can be exploited as predictive biomarkers. The nature of the stress and the resulting intracellular responses are key determinants of the secretome composition, but monitoring such processes remains technically arduous. Hence, there is growing interest in developing tools for noninvasive secretome screening. In this regard, it has been previously shown that the relative concentrations of relevant metabolites can be traced by surface-enhanced Raman scattering (SERS), thereby allowing label-free biofluid interrogation. However, conventional SERS approaches are insufficient to tackle the requirements imposed by high-throughput modalities, namely fast data acquisition and automatized analysis. Therefore, machine learning methods were implemented to identify cell secretome variations while extracting standard features for cell death classification. To this end, ad hoc microfluidic chips were devised, to readily conduct SERS measurements through a prototype relying on capillary pumps made of filter paper, which eventually would function as the SERS substrates. The developed strategy may pave the way toward a faster implementation of SERS into cell secretome classification, which can be extended even to laboratories lacking highly specialized facilities.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/smll.202207658

Pablo S. Valera

Papers

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

Machine Learning-Assisted High-Throughput SERS Classification of Cell Secretomes.