Although SERS spectroscopy, which is sensitive to molecular vibration states, offers label-free visualization of molecules, identification of molecules and their reliable large-area imaging remains to be developed. Limitation comes from difficulties in fabricating a SERS-active substrate with homogeneity over a large area. Here, we overcome this hurdle by utilizing a self-assembled nanostructure of boehmite that is easily achieved by a hydrothermal preparation of aluminum as a template for subsequent gold (Au) deposition. This approach brought about random arrays of Au-nanostructures with a diameter of ∼125 nm and a spacing of <10 nm, ideal for the hot-spots formation. The substrate, which we named "gold nanocoral" (GNC) after its coral reef-like shape, exhibited a small variability of signal intensities (coefficient value <11.2%) in detecting rhodamine 6G molecule when 121 spots were measured over an area of 10 × 10 mm(2), confirming high uniformity. The transparent nature of boehmite enabled us to conduct the measurement from the back-side of the substrate as efficiently as that from the front-side. We then conducted tissue imaging using the mouse ischemic brain adhered on the GNC substrate. Through nontargeted construction of two-dimensional-Raman-intensity map using differential bands from two metabolically distinct regions, that is, ischemic core and contralateral-control areas, we found that mapping using the adenine ring vibration band at 736 cm(-1) clearly demarcated ischemic core where high-energy adenine phosphonucleotides were degraded as judged by imaging mass spectrometry. Such a detection capability makes the GNC-based SERS technology especially promising for revealing acute energy derangement of tissues.
Gold deposition with diagonal angle towards boehmite-based nanostructure creates random arrays of horse-bean-shaped nanostructures named gold-nanofève (GNF). GNF generates many electromagnetic hotspots as surface-enhanced Raman spectroscopy (SERS) excitation sources, and enables large-area visualization of molecular vibration fingerprints of metabolites in human cancer xenografts in livers of immunodeficient mice with sufficient sensitivity and uniformity. Differential screening of GNF-SERS signals in tumours and those in parenchyma demarcated tumour boundaries in liver tissues. Furthermore, GNF-SERS combined with quantum chemical calculation identified cysteine-derived glutathione and hypotaurine (HT) as tumour-dominant and parenchyma-dominant metabolites, respectively. CD44 knockdown in cancer diminished glutathione, but not HT in tumours. Mechanisms whereby tumours sustained HT under CD44-knockdown conditions include upregulation of PHGDH, PSAT1 and PSPH that drove glycolysis-dependent activation of serine/glycine-cleavage systems to provide one-methyl group for HT synthesis. HT was rapidly converted into taurine in cancer cells, suggesting that HT is a robust anti-oxidant for their survival under glutathione-suppressed conditions.
Pathological examination of formalin-fixed paraffin-embedded (FFPE) needle-biopsied samples by certified pathologists represents the gold standard for differential diagnosis between ductal carcinoma in situ (DCIS) and invasive breast cancers (IBC), while information of marker metabolites in the samples is lost in the samples. Infrared laser-scanning large-area surface-enhanced Raman spectroscopy (SERS) equipped with gold-nanoparticle-based SERS substrate enables us to visualize metabolites in fresh-frozen needle-biopsied samples with spatial matching between SERS and HE staining images with pathological annotations. DCIS (n = 14) and IBC (n = 32) samples generated many different SERS peaks in finger-print regions of SERS spectra among pathologically annotated lesions including cancer cell nests and the surrounding stroma. The results showed that SERS peaks in IBC stroma exhibit significantly increased polysulfide that coincides with decreased hypotaurine as compared with DCIS, suggesting that alterations of these redox metabolites account for fingerprints of desmoplastic reactions to distinguish IBC from DCIS. Furthermore, the application of supervised machine learning to the stroma-specific multiple SERS signals enables us to support automated differential diagnosis with high accuracy. The results suggest that SERS-derived biochemical fingerprints derived from redox metabolites account for a hallmark of desmoplastic reaction of IBC that is absent in DCIS, and thus, they serve as a useful method for precision diagnosis in breast cancer.
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