Raman microspectroscopy of noncancerous and cancerous human breast tissues. Identification and phase transitions of linoleic and oleic acids by Raman low-temperature studies

Biochemical changes in lipid and protein metabolism caused by mannose-Raman spectroscopy studies

Biochemical analysis of human normal bronchial cells (BEpiC) and human cancer lung cells (A549) has been performed by using Raman spectroscopy and Raman imaging. Our approach provides a biochemical compositional mapping of the main cell components: nucleus, mitochondria, lipid droplets, endoplasmic reticulum, cytoplasm and cell membrane. We proved that Raman spectroscopy and Raman imaging can distinguish successfully BEpiC and A549 cells. In this study, we have focused on the role of mannose in cancer development. It has been shown that changes in the concentration of mannose can regulate some metabolic processes in cells. Presented results suggest lipids and proteins can be considered as Raman biomarkers during lung cancer progression. Analysis obtained for bands 1444 cm-1, and 2854 cm-1 characteristic for lipids and derivatives proved that the addition of mannose reduced levels of these compounds. Results obtained for protein compounds based on bands 858 cm-1, 1004 cm-1 and 1584 cm-1 proved that the addition of mannose increases the values of protein in BEpiC cells and blocks protein glycolisation in A549 cells. Noticing Raman spectral changes in BEpiC and A549 cells supplemented with mannose can help to understand the mechanism of sugar metabolism during cancer development and could play in the future an important role in clinical treatment.

A new modality for cholesterol impact tracking in colon cancer development - Raman imaging, fluorescence and AFM studies combined with chemometric analysis

Colorectal cancer (CRC) is the third most common cancer worldwide. Obesity, alcohol consumption, smoking, high consumption of red or processed meat and a diet with low fibre, fruit, and vegetable intake increase CRC risk. Despite advances in surgery (the basic treatment for recovery), chemotherapy, and radiotherapy, CRC remains the second leading cause of cancer-related deaths in the world. Therefore the social importance of this problem stimulates research aimed at developing new tools for rapid CRC diagnosis and analysis of CRC risk factors. Considering the association between the cholesterol level and CRC, we hypothesize that cholesterol spectroscopic and AFM (atomic force microscopy) studies combined with chemometric analysis can be new, powerful tools used to visualize the cholesterol distribution, estimate cholesterol content and determine its influence on the biochemical and nanomechanical properties of colon cells. Our paper presents the analysis of human colon tissues: normal and cancer and human colon single cells normal CCD18-Co and cancer CaCo-2 in the physiological state and CaCo-2 upon mevastatin supplementation. Based on vibrational features we have shown that Raman spectroscopy and imaging allow cholesterol content in human colon tissues and human colon single cells of both types to be tracked and allow the effectiveness of mevastatin in the mevalonate pathway modulation and disruption of the cholesterol level to be proven. All observations have been confirmed by chemometric analysis including principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA). The positive impact of statins on cholesterol content has also been studied by using fluorescence microscopy and atomic force microscopy (AFM). A significant increase in Young modulus as a mechanomarker for CaCo-2 human cancer colon cells upon mevastatin supplementation compared to CCD18-Co human normal colon cells was observed. This paper is one of the first reports about the use of Raman spectroscopic techniques in cholesterol investigations and the first one about cholesterol investigation using Raman spectroscopy (RS) on human cells ex vivo in the context of colon cancer development.

Raman imaging and statistical methods for analysis various type of human brain tumors and breast cancers

Spectroscopic methods provide information on the spatial localization of biochemical components based on the analysis of vibrational spectra. Raman spectroscopy and Raman imaging can be used to analyze various types of human brain tumors and breast cancers. The objective of this study is to evaluate the Raman biomarkers to distinguish tumor types by Raman spectroscopy and Raman imaging. We have demonstrated that bands characteristic for carotenoids (1156 cm^-1, 1520 cm^-1), proteins (1004 cm^-1), fatty acids (1444 cm^-1, 1655 cm^-1) and cytochrome (1585 cm^-1) can be used as universal biomarkers to assess aggressiveness of human brain tumors. The sensitivity and specificity obtained from PLS-DA have been over 73%. Only for gliosarcoma WHO IV the specificity is lower and takes equal 50%. The presented results confirm clinical potential of Raman spectroscopy in oncological diagnostics.

A look into the use of Raman spectroscopy for brain and breast cancer diagnostics: linear and non-linear optics in cancer research as a gateway to tumor cell identity

Introduction: Currently, intensely developing of linear and non-linear optical methods for cancer detection provides a valuable tool to improve sensitivity and specificity. One of the main reasons for insufficient progress in cancer diagnostics is related to the fact that most cancer types are not only heterogeneous in their genetic composition but also reside in varying microenvironments and interact with different cell types. Until now, no technology has been fully proven for effective detecting of invasive cancer, which infiltrating the extracellular matrix.Areas covered: This review investigates the current status of Raman spectroscopy and Raman imaging for brain and breast cancer diagnostics. Moreover, the review provides a comprehensive overview of the applicability of atomic force microscopy (AFM), linear and non-linear optics in cancer research as a gateway to tumor cell identity.Expert commentary: A combination of linear and non-linear optics, particularly Raman-driven methods, has many additional advantages to identify alterations in cancer cells that are crucial for their proliferation and that distinguish them from normal cells.

Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer

Background: Artificial intelligence (AI) and machine learning (ML) approaches in combination with Raman spectroscopy (RS) to obtain accurate medical diagnosis and decision-making is a way forward for understanding not only the chemical pathway to the progression of disease, but also for tailor-made personalized medicine. These processes remove unwanted affects in the spectra such as noise, fluorescence and normalization, and help in the optimization of spectral data by employing chemometrics. Methods: In this study, breast cancer tissues have been analyzed by RS in conjunction with principal component (PCA) and linear discriminate (LDA) analyses. Tissue microarray (TMA) breast biopsies were investigated using RS and chemometric methods and classified breast biopsies into luminal A, luminal B, HER2, and triple negative subtypes. Results: Supervised and unsupervised algorithms were applied on biopsy data to explore intra and inter data set biochemical changes associated with lipids, collagen, and nucleic acid content. LDA predicted specificity accuracy of luminal A, luminal B, HER2, and triple negative subtypes were 70%, 100%, 90%, and 96.7%, respectively. Conclusion: It is envisaged that a combination of RS with AI and ML may create a precise and accurate real-time methodology for cancer diagnosis and monitoring.

Analysis of Human Colon by Raman Spectroscopy and Imaging-Elucidation of Biochemical Changes in Carcinogenesis

Noninvasive Raman imaging of non-fixed and unstained human colon tissues based on vibrational properties of noncancerous and cancerous samples can effectively enable the differentiation between noncancerous and tumor tissues. This work aimed to evaluate the biochemical characteristics of colon cancer and the clinical merits of multivariate Raman image and spectroscopy analysis. Tissue samples were collected during routine surgery. The non-fixed, fresh samples were used to prepare micrometer sections from the tumor mass and the tissue from the safety margins outside of the tumor mass. Adjacent sections were used for typical histological analysis. We have found that the chemical composition identified by Raman spectroscopy of the cancerous and the noncancerous colon samples is sufficiently different to distinguish pathologically changed tissue from noncancerous tissue. We present a detailed analysis of Raman spectra for the human noncancerous and cancerous colon tissue. The multivariate analysis of the intensities of lipids/proteins/carotenoids Raman peaks shows that these classes of compounds can statistically divide analyzed samples into noncancerous and pathological groups, reaffirming that Raman imaging is a powerful technique for the histochemical analysis of human tissues. Raman biomarkers based on ratios for lipids/proteins/carotenoids content were found to be the most useful biomarkers in spectroscopic diagnostics.

Discrimination of breast cancer from benign tumours using Raman spectroscopy

Breast cancer is the most common cancer among women worldwide, with an estimated 1.7 million cases and 522,000 deaths in 2012. Breast cancer is diagnosed by histopathological examination of breast biopsy material but this is subjective and relies on morphological changes in the tissue. Raman spectroscopy uses incident radiation to induce vibrations in the molecules of a sample and the scattered radiation can be used to characterise the sample. This technique is rapid and non-destructive and is sensitive to subtle biochemical changes occurring at the molecular level. This allows spectral variations corresponding to disease onset to be detected. The aim of this work was to use Raman spectroscopy to discriminate between benign lesions (fibrocystic, fibroadenoma, intraductal papilloma) and cancer (invasive ductal carcinoma and lobular carcinoma) using formalin fixed paraffin preserved (FFPP) tissue. Haematoxylin and Eosin stained sections from the patient biopsies were marked by a pathologist. Raman maps were recorded from parallel unstained tissue sections. Immunohistochemical staining for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) was performed on a further set of parallel sections. Both benign and cancer cases were positive for ER while only the cancer cases were positive for HER2. Significant spectral differences were observed between the benign and cancer cases and the benign cases could be differentiated from the cancer cases with good sensitivity and specificity. This study has shown the potential of Raman spectroscopy as an aid to histopathological diagnosis of breast cancer, in particular in the discrimination between benign and malignant tumours.

Rapid diagnostics of liver steatosis by Raman spectroscopyviafiber optic probe: a pilot study

Raman spectroscopyviafiber optic probes enables assessment of the liver condition and rapid quantification of liver steatosis, thus, this technique has the potential as a diagnostic tool.

Continuous gradient temperature Raman spectroscopy from -100 to 40°C yields new molecular models of arachidonic acid and 2-Arachidonoyl-1-stearoyl-sn-glycero-3-phosphocholine

Despite its biochemical importance, a complete Raman analysis of arachidonic acid (AA, 20:4n-6) has never been reported. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we utilize the GTRS technique for AA and 1-18:0, 2-20:4n-6 phosphatidyl choline (AAPC) from cryogenic to mammalian body temperatures. 20Mb three-dimensional data arrays with 0.2°C increments and first/second derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. The AA DSC shows a large exothermic peak at -60°C indicating crystallization or a similar major structural change. No exothermic peak of this magnitude was observed in six other unsaturated lipids (DHA, n-3DPA, n-6DPA, LA, ALA, OA). Melting in AA occurs over a large range: (-60 to -35°C): very large frequency offsets and intensity changes correlate with premelting initiating circa -60°C, followed by melting (-37°C). Novel, unique 3D structures for both molecules reveal that AA is not symmetric as a free fatty acid, and it changes significantly when in the sn-2 phospholipid position. Further, different CH and CH₂ sites are unequally elastic and nonequivalent.

Raman technologies in cancer diagnostics

Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.

Epigenetic changes in cancer by Raman imaging, fluorescence imaging, AFM and scanning near-field optical microscopy (SNOM). Acetylation in normal and human cancer breast cells MCF10A, MCF7 and MDA-MB-231

This paper examines epigenetic changes in breast cancer by Raman imaging, fluorescence imaging, AFM and SNOM and discusses how they contribute to different aspects of tumourigenesis in malignant human breast epithelial cell lines MCF7 and MDA-MB-231 compared with non-malignant MCF10A cell lines. The paper focuses on information that can be extracted from Raman microscopy and Raman imaging for the biological material of nucleoli contained within the cell nucleus and lipid droplets within the cell cytoplasm. The biochemical composition of the nuclei and lipid droplets in the non-malignant and malignant human breast epithelial cell lines has been monitored. The potential of Raman microspectroscopy to monitor acetylation processes and a prognostic value of Raman biomarkers in breast cancer have been discussed.

New look inside human breast ducts with Raman imaging. Raman candidates as diagnostic markers for breast cancer prognosis: Mammaglobin, palmitic acid and sphingomyelin

Looking inside the human body fascinated mankind for thousands of years. Current diagnostic and therapy methods are often limited by inadequate sensitivity, specificity and spatial resolution. Raman imaging may bring revolution in monitoring of disease and treatment. The main advantage of Raman imaging is that it gives spatial information about various chemical constituents in defined cellular organelles in contrast to conventional methods (liquid chromatography/mass spectrometry, NMR, HPLC) that rely on bulk or fractionated analyses of extracted components. We demonstrated how Raman imaging can drive the progress on breast cancer just unimaginable a few years ago. We looked inside human breast ducts answering fundamental questions about location and distribution of various biochemical components inside the lumen, epithelial cells of the duct and the stroma around the duct during cancer development. We have identified Raman candidates as diagnostic markers for breast cancer prognosis: carotenoids, mammaglobin, palmitic acid and sphingomyelin as key molecular targets in ductal breast cancer in situ, and propose the molecular mechanisms linking oncogenes with lipid programming.