Longitudinal Study of Cirrhosis Development in STAM and carbon tetrachloride Mouse Models Using Fourier Transform Infrared Spectral Imaging.

Animal models of cirrhosis are of great interest to investigate the pathological process leading to the final stage of cirrhosis. The aim of this study was to analyze the different steps involved in the progressive development of cirrhosis using Fourier transform infrared spectral histology in 2 mouse models of cirrhosis, the STAM model of metabolic cirrhosis, and the carbon tetrachloride-induced cirrhosis model. Formalin-fixed, paraffin-embedded liver samples were obtained from 3 mice at 5 time points in each model to analyze the course of hepatic lesions up to the formation of cirrhosis. For each time point, adjacent 3-µm-thick liver sections were obtained for histologic stains and spectral histology. Fourier transform infrared acquisitions of liver sections were performed at projected pixel sizes of 25 µm × 25 µm and 6.25 µm × 6.25 µm. Spectral images were then preprocessed with an extended multiplicative signal correction and analyzed with common k-means clustering, including all stages in each model. In both models, the 2- and 4-class common k-means clustering in the 1000 to 1350 cm-1 range showed that spectral classes characterized by higher absorbance peaks of glycogen were predominant at baseline, then decreased markedly in early stages of hepatic damage, and almost disappeared in cirrhotic tissues. Concomitantly, spectral classes characterized by higher absorbance peaks of nucleic acids became progressively predominant during the course of hepatic lesions. These results were confirmed using k-means clustering on the peaks of interest identified for glycogen and nucleic acid content. Our study showed that the glycogen depletion previously described at the stage of cirrhosis is an early event in the pathological process, independently of the cause of cirrhosis. In addition, there was a progressive increase in the nucleic acid content, which may be linked to increased proliferation and polyploidy in response to cellular lesions.

HS2ST1-dependent signaling pathways determine breast cancer cell viability, matrix interactions, and invasive behavior.

Heparan sulfate proteoglycans (HSPGs) act as signaling co-receptors by interaction of their sulfated glycosaminoglycan chains with numerous signaling molecules. In breast cancer, the function of heparan sulfate 2-O-sulfotransferase (HS2ST1), the enzyme mediating 2-O-sulfation of HS, is largely unknown. Hence, a comparative study on the functional consequences of HS2ST1 overexpression and siRNA knockdown was performed in the breast cancer cell lines MCF-7 and MDA-MB-231. HS2ST1 overexpression inhibited Matrigel invasion, while its knockdown reversed the phenotype. Likewise, cell motility and adhesion to fibronectin and laminin were affected by altered HS2ST1 expression. Phosphokinase array screening revealed a general decrease in signaling via multiple pathways. Fluorescent ligand binding studies revealed altered binding of fibroblast growth factor 2 (FGF-2) to HS2ST1-expressing cells compared with control cells. HS2ST1-overexpressing cells showed reduced MAPK signaling responses to FGF-2, and altered expression of epidermal growth factor receptor (EGFR), E-cadherin, Wnt-7a, and Tcf4. The increased viability of HS2ST1-depleted cells was reduced to control levels by pharmacological MAPK pathway inhibition. Moreover, MAPK inhibitors generated a phenocopy of the HS2ST1-dependent delay in scratch wound repair. In conclusion, HS2ST1 modulation of breast cancer cell invasiveness is a compound effect of altered E-cadherin and EGFR expression, leading to altered signaling via MAPK and additional pathways.

Infrared spectral histopathology for cancer diagnosis: a novel approach for automated pattern recognition of colon adenocarcinoma.

Histopathology remains the gold standard method for colon cancer diagnosis. Novel complementary approaches for molecular level diagnosis of the disease are need of the hour. Infrared (IR) imaging could be a promising candidate method as it probes the intrinsic chemical bonds present in a tissue, and provides a "spectral fingerprint" of the biochemical composition. To this end, IR spectral histopathology, which combines IR imaging and data processing techniques, was employed on seventy seven paraffinized colon tissue samples (48 tumoral and 29 non-tumoral) in the form of tissue arrays. To avoid chemical deparaffinization, a digital neutralization of the spectral interference of paraffin was implemented. Clustering analysis was used to partition the spectra and construct pseudo-colored images, for assigning spectral clusters to various tissue structures (normal epithelium, malignant epithelium, connective tissue etc.). Based on the clustering results, linear discriminant analysis was then used to construct a stringent prediction model which was applied on samples without a priori histopathological information. The predicted spectral images not only revealed common features representative of the colonic tissue biochemical make-up, but also highlighted additional features like tumor budding and tumor-stroma association in a label-free manner. This novel approach of IR spectral imaging on paraffinized tissues showed 100% sensitivity and allowed detection and differentiation of normal and malignant colonic features based purely on their intrinsic biochemical features. This non-destructive methodology combined with multivariate statistical image analysis appears as a promising tool for colon cancer diagnosis and opens up the way to the concept of numerical spectral histopathology.

Vibrational spectroscopy differentiates between multipotent and pluripotent stem cells.

Over the last few years, there has been an increased interest in the study of stem cells in biomedicine for therapeutic use and as a source for healing diseased or injured organs/tissues. More recently, vibrational spectroscopy has been applied to study stem cell differentiation. In this study, we have used both synchrotron based FTIR and Raman microspectroscopies to assess possible differences between human pluripotent (embryonic) and multipotent (adult mesenchymal) stem cells, and how O(2) concentration in cell culture could affect the spectral signatures of these cells. Our work shows that infrared spectroscopy of embryonic (pluripotent) and adult mesenchymal (multipotent) stem cells have different spectral signatures based on the amount of lipids in their cytoplasm (confirmed with cytological staining). Furthermore, O(2) concentration in cell culture causes changes in both the FTIR and Raman spectra of embryonic stem cells. These results show that embryonic stem cells might be more sensitive to O(2) concentration when compared to mesenchymal stem cells. While vibrational spectroscopy could therefore be of potential use in identifying different populations of stem cells further work is required to better understand these differences.

Spectroscopic signatures of single, isolated cancer cell nuclei using synchrotron infrared microscopy.

Single-cell studies have important implications in biomedicine. An accurate investigation of biochemical behaviour and status requires a biomolecular probe such as vibrational microscopy. Amongst other approaches, synchrotron infrared microspectroscopy is an appropriate analytical tool for single-cell investigation. However, it is important to understand the precise origin of spectral differences as they are directly related to the cell biochemistry. Beside biomolecular changes, physical properties can interfere in the resulting information, and the two effects need separating. Both cells and nuclei induce Mie scattering effects due to their equivalent size with the probe wavelength. This results in a large modification of the spectra, and its precise contribution has to be determined in order to extract the true spectral information. On this basis, we carried out this study in order to evaluate the exact contribution of cell nuclei to Mie scattering. To this purpose, we isolated whole cancer cell nuclei and obtained, for the first time, their FTIR spectra with good signal to noise ratio. The synchrotron-based FTIR (S-FTIR) spectra of nuclei showed changes in lipids, proteins, and DNA absorptions when compared to spectra of whole lung cancer cells. Importantly, we estimated the Mie scattering properties of single cells and single nuclei spectra and were consequently able to separate optical and chemical properties of single cells and nuclei. This is the first study which sheds new light on the identification of the precise spectral biomarkers of a whole cell and those of the cell nucleus.

Bile analysis using high-throughput FTIR spectroscopy for the diagnosis of malignant biliary strictures: a pilot study in 57 patients.

This study aimed at determining whether FTIR spectroscopy is able to distinguish bile samples from patients with and without malignant biliary strictures. Bile samples were collected in 19 patients with malignant biliary strictures and 38 with benign biliary diseases during endoscopic procedures. FTIR spectra were acquired on dried drops of whole bile, aqueous and organic phases obtained after lipid extraction. Data were analyzed by principal component analysis and by the support vector machine classification using a leave-n-out cross validation procedure. This was applied to the whole set of spectra and the mean and median spectra of each patient. By leaving one patient out, the classifier allowed discriminating patients with and without malignant biliary strictures with a sensitivity between 82% and 95% and a specificity between 85% and 100%. Using a randomized leave-n -out cross-validation with n = 2, 5 and 10 patients, the sensitivity decreased slightly by about 5 to 10% while the specificity remained stable, suggesting the robustness of the classifier. FTIR spectroscopy combined with chemometrics therefore shows potential to differentiate bile from patients with and without malignant biliary strictures. Although promising, the results of this pilot study cannot be generalized and needs to be confirmed in a larger population.

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis.

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.