| Literature DB >> 31146464 |
Luca Guerrini1, Ramon A Alvarez-Puebla2,3.
Abstract
As medicine continues to advance our understanding of and knowledge about the complex and multifactorial nature of cancer, new major technological challenges have emerged in the design of analytical methods capable of characterizing and assessing the dynamic heterogeneity of cancer for diagnosis, prognosis and monitoring, as required by precision medicine. With this aim, novel nanotechnological approaches have been pursued and developed for overcoming intrinsic and current limitations of conventional methods in terms of rapidity, sensitivity, multiplicity, non-invasive procedures and cost. Eminently, a special focus has been put on their implementation in liquid biopsy analysis. Among optical nanosensors, those based on surface-enhanced Raman scattering (SERS) have been attracting tremendous attention due to the combination of the intrinsic prerogatives of the technique (e.g., sensitivity and structural specificity) and the high degree of refinement in nano-manufacturing, which translate into reliable and robust real-life applications. In this review, we categorize the diverse strategic approaches of SERS biosensors for targeting different classes of tumor biomarkers (cells, nucleic acids and proteins) by illustrating key recent research works. We will also discuss the current limitations and future research challenges to be addressed to improve the competitiveness of SERS over other methodologies in cancer medicine.Entities:
Keywords: SERS; cancer; circulating tumor cells; circulating tumor nucleic acids; diagnosis; nanoparticles; oncoproteins; optical sensors; prognosis
Year: 2019 PMID: 31146464 PMCID: PMC6627759 DOI: 10.3390/cancers11060748
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1(A) Schematic depiction of the traditional surface-enhanced Raman scattering (SERS)-encoded nanoparticle (SEP) construction. (B–D) Application of SERS imaging to resected tumor tissue for intraoperative surgical guidance: (B) Unique SERS spectra of five different codes on gold particles coated with a silica shell. (C) Upon excision, the resected sample is placed in an automated staining device combining multiple quick dipping of the specimen into a SEPs solution with high-frequency vibration for fast and extensive topically applications of encoded particles onto the surface of the fresh tissue. (D) Ratiometric images biomarker targeting SEPs vs. negative control (isotype) obtained from raster-scanned SERS imaging (<3 min) of the illustrated human breast tumor and normal tissue. Adapted with permission from [18]. Copyright 2016, Wiley-VHC. (E) Schematic of the proposed application of intravesical SERS imaging for intraoperative endoscopic surgery. Adapted with permission from [19]. Copyright 2018, American Chemical Society. (F–H) SERS-microfluidic device for single live cell analysis: (F) Schematic depiction of the droplet-based optofluidic device; (G) Low-resolution map of the chamber array, (H) High-resolution map of individual cells encapsulated in droplets. Adapted with permission from [20] Copyright 2018, American Chemical Society.
Figure 2(A) Size-based capturing of circulating-tumor cells (CTCs) from blood, and multiplexed SERS phenotyping and chemometric classification of single cancer cells. (i) CTCs are isolated by flowing the whole blood through a nanogap array: see SEM image, arrow indicates the flow direction, and fluorescence image of fluorescently labelled individual cells (green, breast cancer cells MCF7; red, white blood cells) trapped at the edge of the pillar structure (dash lines show the edge of the pillar structure). (ii) Incubation with aptamer-SEPs enables the acquisition of SERS spectra that, upon deconvolution, yield single-cell SERS phenotypic signatures. Adapted with permission from ref. [54]. Copyright 2018, Wiley-VHC. (B,C) Real-time evolution of the phenotypic distribution of different cancer cell subpopulations: (B) Schematic outline of the experimental workflow. The ensemble of CTCs labelled with antibody-SEPs is interrogated via average analysis. Demultiplexing of the acquired SERS spectra is performed to yield SERS intensities from each code plotted as a frequency distribution curve. (C) Phenotypic signatures of CTCs in response to treatment. Patient with stage IV melanoma (day 1) was treated with dabrafenib and trametinib. After 1 month, treatment was discontinued due to toxicity. Cluster analysis of the SERS data is also reported. Adapted from Tsao et al., Nature Communications, 2019, 1482; DOI: 10.1038/s41467-018-03725-8 [55], licensed under CC BY 4.0. (D) PCR-SERS integration for identification of tumor DNAs using SEPs. Biotin-labelled amplicons of tumor DNA are recognized by SEPs and, subsequently, separated from the media with streptavidin-coated magnetic beads prior to multiplex SERS analysis. Adapted from Wee et al., Theranostics, 2016, 6, 1506; DOI: 10.7150/thno.15871 [56], licensed under CC BY-NC [56]. (E) Conformational classification of K-Ras point mutations (MT1-5) in long single-stranded DNAs via direct SERS analysis. Adapted with permission from [57]. Copyright 2017, WILEY-VCH. (F) Detection of the oncoprotein c-MYC in biological fluids using peptidic receptor derivatized with a SERS transducer which undergoes structural rearrangement upon target binding. The resulting spectral alterations, expressed as ratiometric intensities of two spectral marker bands at 756 and 1075 cm−1, are directly correlated with the c-MYC concent. Adapted with permission from [58]. Copyright 2016, American Chemical Society.