Purpose Surface-enhanced Raman scattering (SERS) spectroscopy on serum and other biofluids for cancer diagnosis represents an emerging field, which has shown promising preliminary results in several types of malignancies. The purpose of this study was to demonstrate that SERS spectroscopy on serum can be employed for the differential diagnosis between five of the leading malignancies, ie, breast, colorectal, lung, ovarian and oral cancer. Patients and methods Serum samples were acquired from healthy volunteers (n=39) and from patients diagnosed with breast (n=42), colorectal (n=109), lung (n=33), oral (n=17), and ovarian cancer (n=13), comprising n=253 samples in total. SERS spectra were acquired using a 532 nm laser line as excitation source, while the SERS substrates were represented by Ag nanoparticles synthesized by reduction with hydroxylamine. The classification accuracy yielded by SERS was assessed by principal component analysis–linear discriminant analysis (PCA-LDA). Results The sensitivity and specificity in discriminating between cancer patients and controls was 98% and 91%, respectively. Cancer samples were correctly assigned to their corresponding cancer types with an accuracy of 88% for oral cancer, 86% for colorectal cancer, 80% for ovarian cancer, 76% for breast cancer and 59% for lung cancer. Conclusion SERS on serum represents a promising strategy of diagnosing cancer which can discriminate between cancer patients and controls, as well as between cancer types such as breast, colorectal, lung ovarian and oral cancer.
Multimodal spectral histopathology (MSH), an optical technique combining tissue auto-fluorescence (AF) imaging and Raman micro-spectroscopy (RMS), was previously proposed for detection of residual basal cell carcinoma (BCC) at the surface of surgically-resected skin tissue. Here we report the development of a fully-automated prototype instrument based on MSH designed to be used in the clinic and operated by a non-specialist spectroscopy user. The algorithms for the AF image processing and Raman spectroscopy classification had been first optimised on a manually-operated laboratory instrument and then validated on the automated prototype using skin samples from independent patients. We present results on a range of skin samples excised during Mohs micrographic surgery, and demonstrate consistent diagnosis obtained in repeat test measurement, in agreement with the reference histopathology diagnosis. We also show that the prototype instrument can be operated by clinical users (a skin surgeon and a core medical trainee, after only 1-8 hours of training) to obtain consistent results in agreement with histopathology. The development of the new automated prototype and demonstration of inter-instrument transferability of the diagnosis models are important steps on the clinical translation path: it allows the testing of the MSH technology in a relevant clinical environment in order to evaluate its performance on a sufficiently large number of patients.
This study investigates the temporal and spatial interchange of the aromatic amino acid phenylalanine (Phe) between human retinal pigment epithelial cell line (ARPE-19) and tachyzoites of the apicomplexan protozoan parasite Toxoplasma gondii (T. gondii). Stable isotope labelling by amino acids in cell culture (SILAC) is combined with Raman micro-spectroscopy to selectively monitor the incorporation of deuterium-labelled Phe into proteins in individual live tachyzoites. Our results show a very rapid uptake of l-Phe(D8) by the intracellular growing parasite. T. gondii tachyzoites are capable of extracting l-Phe(D8) from host cells as soon as it invades the cell. l-Phe(D8) from the host cell completely replaces the l-Phe within T. gondii tachyzoites 7–9 hours after infection. A quantitative model based on Raman spectra allowed an estimation of the exchange rate of Phe as 0.5–1.6 × 104 molecules/s. On the other hand, extracellular tachyzoites were not able to consume l-Phe(D8) after 24 hours of infection. These findings further our understanding of the amino acid trafficking between host cells and this strictly intracellular parasite. In particular, this study highlights new aspects of the metabolism of amino acid Phe operative during the interaction between T. gondii and its host cell.
Raman micro-spectroscopy (RMS) is a non-invasive technique for imaging live cells in-vitro. However, obtaining quantitative molecular information from the Raman spectra is difficult because the intensity of a Raman band is proportional to the number of molecules in the sampled volume, which depends on the local molecular concentration and the thickness of the cell. In order to understand these effects, we combined RMS with atomic force microscopy (AFM), a technique that can measure accurately the thickness profile of the cells. Solution-based calibration models for RNA and albumin were developed to create quantitative maps of RNA and proteins in individual fixed cells. The maps were built by applying the solution-based calibration models, based on partial least square fitting (PLS), on raster-scan Raman maps, after accounting for the local cell height obtained from the AFM. We found that concentrations of RNA in the cytoplasm of mouse neuroprogenitor stem cells (NSCs) were as high as 25±6 mg/m, while proteins were distributed more uniformly and reaching concentrations as high as ~50±12 mg/ml. The combined AFM-Raman datasets from fixed cells were also used to investigate potential improvements for normalization of Raman spectral maps. For all Raman map of fixed cells (n=10), we found a linear relationship between the scores corresponding to the first component (PC1) and cell height profile obtained by AFM. We used PC1 scores to reconstruct the relative height profiles of independent cells (n=10), and obtained correlation coefficients with AFM maps higher than 0.99. Using this normalization method, qualitative maps of RNA and protein were obtained concentrations for live NSCs. While this study demonstrates the potential of using AFM and RMS for measuring concentration maps for individual NSCs in-vitro, further studies are required to establish the robustness of the normalization method based on principal component analysis when comparing Raman spectra of cells with large morphological differences.
We present the first clinical integration of a prototype device based on integrated auto-fluorescence imaging and Raman spectroscopy (Fast Raman device) for intra-operative assessment of surgical margins during Mohs micrographic surgery of basal cell carcinoma (BCC). Fresh skin specimens from 112 patients were used to optimise the tissue pre-processing and the Fast Raman algorithms to enable an analysis of complete Mohs layers within 30 minutes. The optimisation allowed >95% of the resection surface area to be investigated (including the deep and epidermal margins). The Fast Raman device was then used to analyse skin layers excised from the most relevant anatomical sites (nose, temple, eyelid, cheek, forehead, eyebrow and lip) and to detect the three main types of BCC (nodular, superficial and infiltrative). These results suggest that the Fast Raman technique is a promising tool to provide an objective diagnosis “tumour clear yes/no” during Mohs surgery of BCC. This clinical integration study is a key step towards a larger scale diagnosis test accuracy study to reliably determine the sensitivity and specificity in a clinical setting.
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