Breast cancer has become the most diagnosed cancer globally, replacing lung cancer in 2020, with 2.3 million new cases and an estimated death of 685000 women. It is predicted that by the year of 2040 there would be an increase to around 3 million new cases and 1 million deaths worldwide. This calls for techniques for better and faster diagnosis, and in understanding the different biomarkers and the resulting metabolic alterations aiding the development and progression of the tumour. Obesity is associated with metabolic alterations that have shown to increase the risk of cancer and worsen its prognosis. It is associated with dysfunction of adipose tissue that alter the lipid metabolism resulting in excessive accumulation of adipose tissue at sites other than where they are classically found. Tumour cells depend on their microenvironment for nutrients, oxygen and for proliferation. The tumor microenvironment in breast cancer constitutes adipocytes, fibroblasts, endothelial cells, immune cells, and components of the extracellular matrix. The effects of adipocytes on the tumor prognosis are predominant as the breast is composed of abundant fatty tissue. Hence it is important to investigate this effects on molecular levels for understanding the communication between the adipocytes and the tumoral cells which is supporting the proliferation of the cancer. The current diagnostic technique of cancer includes a three step procedure including imaging (such as MRI, Ultrasound imaging), clinical examination and histopathological assessment of biopsy sample if a lesion is suspected to be malignant. However, histopathological assessment observes the morphologic abnormalities in the sample sections and is limited to provide information on the biochemical alterations likely to occur within the tissue even before the morphology is modified. Vibrational spectroscopy has demonstrated its potential to provide diagnostic information. Additionally, vibrational spectroscopy can facilitate the prediction of the biochemical progression for different diseases in a rapid non-destructive manner. Raman spectroscopy is an inelastic scattering process which has incredible potential in biological sample analysis. This technique is capable of rendering information on the vibrational modes of molecules, thus giving access to the biochemical information needed about the sample of interest. Raman spectroscopy is also less time consuming compared to conventional methods of tissue analysis, because the hassle of sample preparation is minimum or not required. The goal of this project is to study the alterations of lipid metabolic pathways in the tumour microenvironment and the impact of obesity in development and progression of breast cancer using vibrational spectroscopy.
Confocal Raman microspectroscopy is a relevant and useful tool to perform in vivo diagnosis of cutaneous tissues noninvasively and without labeling. This optical technique provides in-depth molecular and conformational characterization of skin. Unfortunately, spectral distortions occur due to elastic scattering. Our objective is to correct the attenuation of in-depth Raman peaks intensity by considering elastic scattering in biological tissues. In this purpose, a correction model was constructed using skin scattering properties as parameters thus enabling quantitative analysis. The work presented here is a technique of in vivo Diffuse Reflectance Micro-Spectroscopy called Micro-DRS. It achieves optical properties characterization in the skin layers probed by Raman microspectroscopy. The Micro-DRS setup can easily be coupled to a confocal Raman micro-probe to perform simultaneous measurements. Thanks to Monte Carlo simulations and experimental results obtained on homemade solid phantoms mimicking skin optical properties, we show that it is possible to measure the absorption coefficient μa, the reduced scattering coefficient μs', the scattering coefficient μs and the anisotropy of scattering g with this new apparatus. The measured scattering properties can be used subsequently as parameters in our correction model. Coupled to a Raman micro-spectrometer, Micro-DRS enables a quantitative analysis when tracking drug penetration through skin and it can be used independently to provide additional diagnosing criterions.
Light/tissue interactions, like diffuse reflectance, endogenous fluorescence and Raman scattering, are a powerful means for providing skin diagnosis. Instrument calibration is an important step. We thus developed multilayered phantoms for calibration of optical systems. These phantoms mimic the optical properties of biological tissues such as skin. Our final objective is to better understand light/tissue interactions especially in the case of confocal Raman spectroscopy.
The phantom preparation procedure is described, including the employed method to obtain a stratified object. PDMS was chosen as the bulk material. TiO2 was used as light scattering agent. Dye and ink were adopted to mimic, respectively, oxy-hemoglobin and melanin absorption spectra. By varying the amount of the incorporated components, we created a material with tunable optical properties.
Monolayer and multilayered phantoms were designed to allow several characterization methods. Among them, we can name: X-ray tomography for structural information; Diffuse Reflectance Spectroscopy (DRS) with a homemade fibered bundle system for optical characterization; and Raman depth profiling with a commercial confocal Raman microscope for structural information and for our final objective.
For each technique, the obtained results are presented and correlated when possible.
A few words are said on our final objective. Raman depth profiles of the multilayered phantoms are distorted by elastic scattering. The signal attenuation through each single layer is directly dependent on its own scattering property. Therefore, determining the optical properties, obtained here with DRS, is crucial to properly correct Raman depth profiles. Thus, it would be permitted to consider quantitative studies on skin for drug permeation follow-up or hydration assessment, for instance.
Confocal Raman microspectroscopy allows in-depth molecular and conformational characterization of biological tissues non-invasively. Unfortunately, spectral distortions occur due to elastic scattering. Our objective is to correct the attenuation of in-depth Raman peaks intensity by considering this phenomenon, enabling thus quantitative diagnosis. In this purpose, we developed PDMS phantoms mimicking skin optical properties used as tools for instrument calibration and data processing method validation. An optical system based on a fibers bundle has been previously developed for in vivo skin characterization with Diffuse Reflectance Spectroscopy (DRS). Used on our phantoms, this technique allows checking their optical properties: the targeted ones were retrieved. Raman microspectroscopy was performed using a commercial confocal microscope. Depth profiles were constructed from integrated intensity of some specific PDMS Raman vibrations. Acquired on monolayer phantoms, they display a decline which is increasing with the scattering coefficient. Furthermore, when acquiring Raman spectra on multilayered phantoms, the signal attenuation through each single layer is directly dependent on its own scattering property. Therefore, determining the optical properties of any biological sample, obtained with DRS for example, is crucial to correct properly Raman depth profiles. A model, inspired from S.L. Jacques's expression for Confocal Reflectance Microscopy and modified at some points, is proposed and tested to fit the depth profiles obtained on the phantoms as function of the reduced scattering coefficient. Consequently, once the optical properties of a biological sample are known, the intensity of deep Raman spectra distorted by elastic scattering can be corrected with our reliable model, permitting thus to consider quantitative studies for purposes of characterization or diagnosis.
Dermatologists need to combine different clinically relevant characteristics for a better understanding of skin health. These characteristics are usually measured by different techniques, and some of them are highly time consuming. Therefore, a predicting model based on Raman spectroscopy and partial least square (PLS) regression was developed as a rapid multiparametric method. The Raman spectra collected from the five uppermost micrometers of 11 healthy volunteers were fitted to different skin characteristics measured by independent appropriate methods (transepidermal water loss, hydration, pH, relative amount of ceramides, fatty acids, and cholesterol). For each parameter, the obtained PLS model presented correlation coefficients higher than R2=0.9. This model enables us to obtain all the aforementioned parameters directly from the unique Raman signature. In addition to that, in-depth Raman analyses down to 20 μm showed different balances between partially bound water and unbound water with depth. In parallel, the increase of depth was followed by an unfolding process of the proteins. The combinations of all these information led to a multiparametric investigation, which better characterizes the skin status. Raman signal can thus be used as a quick response code (QR code). This could help dermatologic diagnosis of physiological variations and presents a possible extension to pathological characterization.
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.
In the last few years, Raman spectroscopy has been increasingly used for the characterization of normal and pathological tissues. A new Raman system, constituted of optic fibers bundle coupled to an axial Raman spectrometer (Horiba Jobin Yvon SAS), was developed for in vivo investigations. Here, we present in vivo analysis on two tissues: human skin and esophagus mucosa on a rat model. The skin is a directly accessible organ, representing a high diversity of lesions and cancers. Including malignant melanoma, basal cell carcinoma and the squamous cell carcinoma, skin cancer is the cancer with the highest incidence worldwide. Several Raman investigations were performed to discriminate and classify different types of skin lesions, on thin sections of biopsies. Here, we try to characterize in vivo the different types of skin cancers in order to be able to detect them in their early stages of development and to define precisely the exeresis limits. Barrett's mucosa was also studied by in vivo examination of rat's esophagus. Barrett's mucosa, induced by gastro-esophageal reflux, is a pretumoral state that has to be carefully monitored due to its high risk of evolution in adenocarcinoma. A better knowledge of the histological transformation of esophagus epithelium in a Barrett's type will lead to a more efficient detection of the pathology for its early diagnosis. To study these changes, an animal model (rats developing Barrett's mucosa after duodenum - esophagus anastomosis) was used. Potential of vibrational spectroscopy for Barrett's mucosa identification is assessed on this model.
The baking quality and storage stability of white flour are affected by its non-starch lipids content, and by the proportions of non-polar and polar lipids classes. At present, information on the lipids composition in the various parts of the wheat grain is scarce and their redistribution in the flour millstreams after milling is not well understood. Here we have implemented a novel method based on microspectrofluorometry to investigate lipids distribution in the wheat kernel. This technique has already been a proven tool to study primary fluorescence in wheat grain. For this study Nile Red was introduced as a fluorescent stain to map lipids in different compartments of a wheat transverse section. Microspectrofluorometry allows in situ characterization of lipids material in transverse cut of wheat grain. Florescence spectra were recorded and decomposed into the principal spectral components which can in turn be approximated to the real lipid materials of the wheat. Using these models, spectral fluorescence imaging was performed allowing the spatial organization of lipids in the wheat sections to be obtained.
Raman microspectroscopy is a very well appropriate technique for the characterization of the molecules responsible of the wheat grain cohesion, since it is non-destructive and can be readily applied in-situ. The cohesion of the kernel or starchy endosperm depends on a protein content located at the interstices of starch granules. The separation between the kernel and the envelope depends on the composition of the aleurone cells layer, in phenolic acids and pentosans. Confocal Raman microscopy has been performed on kernel sections of various Triticum aestivum samples. Raman spectra recorded at different parts of such sections are very specific, such as spectra of the starchy endosperm protein. The technique has been also used to study the effect of chemical treatment on the binding of the constituents of the aleurone cells walls. In addition, certain marker bands of starch and proteins have been used to construct spectral images.
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