Biochemical fingerprint of colorectal cancer cell lines using label-free live single-cell Raman spectroscopy

Label-free live single-cell Raman spectroscopy was used to obtain a chemical fingerprint of colorectal cancer cells including the classification of the SW480 and SW620 cell line model system, derived from primary and secondary tumour cells from the same patient. High-quality Raman spectra were acquired from hundreds of live cells, showing high reproducibility between experiments. Principal component analysis with linear discriminant analysis yielded the best cell classification, with an accuracy of 98.7±0.3% (standard error) when compared to discrimination trees or support vector machines. SW480 showed higher content of the disordered secondary protein structure amide III band, whereas SW620 showed larger α-helix and β-sheet band content. The SW620 cell line also displayed higher nucleic acid, phosphates, saccharide, and CH2 content. HL60, HT29, HCT116, SW620 and SW480 live single-cell spectra were classified using PCA/LDA with an accuracy of 92.4±0.4% (standard error), showing differences mainly in the β-sheet content, the cytochrome C bands, the CH-stretching regions, the lactate contributions and the DNA content. The lipids contributions above 2900 cm-1 and the lactate contributions at 1785 cm-1 appeared to be dependent on the colorectal adenocarcinoma stage, the advanced stage cell lines showing lower lipid and higher lactate content. The results demonstrate that these cell lines can be distinguished with high confidence, suggesting that Raman spectroscopy on live cells can distinguish between different disease stages, and could play an important role clinically as a diagnostic tool for cell phenotyping

Discriminant Analysis of Raman Spectra for Body Fluid Identification for Forensic Purposes

Detection and identification of blood, semen and saliva stains, the most common body fluids encountered at a crime scene, are very important aspects of forensic science today. This study targets the development of a nondestructive, confirmatory method for body fluid identification based on Raman spectroscopy coupled with advanced statistical analysis. Dry traces of blood, semen and saliva obtained from multiple donors were probed using a confocal Raman microscope with a 785-nm excitation wavelength under controlled laboratory conditions. Results demonstrated the capability of Raman spectroscopy to identify an unknown substance to be semen, blood or saliva with high confidence

Diagnosis Of The Chronic Lymphocytic Leukemia (CLL) Using A Raman-Based Scanner Optimized For Blood Smear Analysis (M3s Project)

Introduction/ Background In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. Aims The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. Methods Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labeling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a microscope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted to immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). Results Currently, a total of 60 patients (CLL and healthy) were included in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (Random Forest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.

Guiding Brain Tumor Resection Using Surface-Enhanced Raman Scattering Nanoparticles and a Hand-Held Raman Scanner

The current difficulty in visualizing the true extent of malignant brain tumors during surgical resection represents one of the major reasons for the poor prognosis of brain tumor patients. Here, we evaluated the ability of a hand-held Raman scanner, guided by surface-enhanced Raman scattering (SERS) nanoparticles, to identify the microscopic tumor extent in a genetically engineered RCAS/tv-a glioblastoma mouse model. In a simulated intraoperative scenario, we tested both a static Raman imaging device and a mobile, hand-held Raman scanner. We show that SERS image-guided resection is more accurate than resection using white light visualization alone. Both methods complemented each other, and correlation with histology showed that SERS nanoparticles accurately outlined the extent of the tumors. Importantly, the hand-held Raman probe not only allowed near real-time scanning, but also detected additional microscopic foci of cancer in the resection bed that were not seen on static SERS images and would otherwise have been missed. This technology has a strong potential for clinical translation because it uses inert gold-silica SERS nanoparticles and a hand-held Raman scanner that can guide brain tumor resection in the operating room

An unmet medical need:advances in endoscopic imaging of colorectal neoplasia

Gastrointestinal cancer is a major public health problem worldwide. Detection of early neoplastic lesions in gastrointestinal tract is essential for cure, because prognosis and survival are related to the size and stage of malignant lesions. Endoscopic screening and treatment of polyps could prevent approximately 80% of colorectal cancer (CRC). However, white-light endoscopy is an imperfect technology since miss rates of up to 25% have been reported and polyps without malignant potential were treated without benefit but with additional costs and risks to the patient. There are several known "human" predictors of an inadequate colonoscopy. These include patient characteristics such as poor bowel preparation, female gender, or inpatient status. Skills of the endoscopists are also an important issue. Therefore, a variety of advanced technologies has been attempted to overcome these issues. These new endoscopic imaging techniques allow a more precise classification of mucosal alterations with selection of patients for invasive therapy or surveillance. Further, molecular and functional imaging techniques could identify novel targets for therapies and new prospects to access response to therapies. However, at the "end of the day" a better endoscopic approach for CRC screening and surveillance depends on a good bowel preparation, a trained endoscopist spending sufficient time on a detailed examination together with an advanced endoscope

Discrimination between two different grades of human glioma based on blood vessel infrared spectral imaging

Gliomas are brain tumours classified into four grades with increasing malignancy from I to IV. The development and the progression of malignant glioma largely depend on the tumour vascularization. Due to their tissue heterogeneity, glioma cases can be difficult to classify into a specific grade using the gold standard of histological observation, hence the need to base classification on a quantitative and reliable analytical method for accurately grading the disease. Previous works focused specifically on vascularization study by Fourier transform infrared (FTIR) spectroscopy, proving this method to be a way forward to detect biochemical changes in the tumour tissue not detectable by visual techniques. In this project, we employed FTIR imaging using a focal plane array (FPA) detector and globar source to analyse large areas of glioma tumour tissue sections via molecular fingerprinting in view of helping to define markers of the tumour grade. Unsupervised multivariate analysis (hierarchical cluster analysis and principal component analysis) of blood vessel spectral data, retrieved from the FPA images, revealed the fine structure of the borderline between two areas identified by a pathologist as grades III and IV. Spectroscopic indicators are found capable of discriminating different areas in the tumour tissue and are proposed as biomolecular markers for potential future use of grading gliomas. Graphical Abstract Infrared imaging of glioma blood vessels provides a means to revise the pathologists' line of demarcation separating grade III (GIII) from grade IV (GIV) parts