Raman spectroscopic analysis differentiates between breast cancer cell lines

Breast cancer incident rates are increasing in women worldwide with the highest incidence rates reported in developing countries. Major breast cancer screening approaches like mammography, ultrasound, clinical breast examination (CBE) and magnetic resonance imaging (MRI) are currently used but have their own limitations. Optical spectroscopy has attained great attention from biomedical researchers in recent years due to its non‐invasive and non‐destructive detection approach. Chemometrics is one of the powerful tools used in spectroscopic research to enhance its sensitivity. Raman spectroscopy, a vibrational spectroscopic approach, has been used to explore the chemical fingerprints of different biological tissues including normal and malignant types. This approach was used to characterize and differentiate two breast cancer and one normal breast cell lines (MDA‐MB‐436, MCF‐7 and MCF‐10A) using dispersive Raman spectroscopy. Raman spectra of the cell lines have revealed that basic differences in the concentration of biochemical compounds such as lipids, nucleic acids and protein Raman peaks were found to differ in intensity, and principal component analysis (PCA) was able to identify variations that lead to accurate and reliable separation of the three cell lines. Linear discriminant analysis (LDA) model of three cell lines was predicted with 100% sensitivity and 91% specificity. We have shown that a combination of Raman spectroscopy and chemometrics are capable of differentiation between breast cancer cell lines. These variations may be useful in identifying new spectral markers to differentiate different subtypes of breast cancer although this needs confirmation in a larger panel of cell lines as well as clinical material. Copyright © 2015 John Wiley & Sons, Ltd.     

Depth‐resolved in vivo micro‐Raman spectroscopy of a murine skin tumor model reveals cancer‐specific spectral biomarkers

We have developed a micro‐Raman spectrometer system for use to differentiate tumor lesions from normal skin using an in vivo animal model. A study of 494 Raman spectra from 24 mice revealed different spectral patterns at different depths and between normal and tumor‐bearing skin sites. A peak at 899 cm⁻¹ (possibly from proline or fatty acids) and one with higher intensity in the 1325–1330 cm⁻¹ range (assigned to nucleic acids) were correlated with the presence of tumors, which can potentially be used as biomarkers for skin cancer detection. Spectral diagnosis performed on the murine tumor model achieved a diagnostic sensitivity of 95.8% and specificity of 93.8%. These results encourage us to develop further the use of confocal Raman spectroscopy as a clinical tool for noninvasive human skin biochemical analysis, particularly in relation to skin cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

Raman spectroscopic analysis of breast cancer tissues: identifying differences between normal,invasive ductal carcinoma and ductal carcinoma in situ of the breast tissue

A relatively non‐destructive method employing Raman spectroscopy for the analysis of histopathological specimens is described. Raman spectroscopy has allowed qualitative analysis of the same specimen used for histopathological evaluation. Breast cancer tissues have been analysed to demonstrate the feasibility of the chemical changes taking place in the biological tissue, which can be identified precisely, and the results are reproducible. Raman analysis of tissue sections provides distinct spectra that can be used to distinguish between the nuclear grades of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of the breast. Sixty cases of breast carcinoma including DCIS and IDC and seven cases of normal breast tissues were studied employing the Raman spectroscopic technique. This study reports for the first time spectral differences between DCIS grades. It is concluded that Raman spectroscopy can objectively distinguish between DCIS and IDC grades and is non‐destructive and reproducible. It should become possible in future to use Raman spectroscopy as an informative and quantitative method suitable for classification of grades and diagnosis of breast carcinoma. Copyright © 2007 John Wiley & Sons, Ltd.     

Raman spectroscopy in experimental oral carcinogenesis: investigation of abnormal changes in control tissues

Oral cancer is a major cause of mortality in South Asian men owing to rampant tobacco abuse. Cancers are also reported in non‐tobacco habitués, especially women, attributed to chronic irritations from irregular/sharp teeth, improper fillings, and poorly fit dentures. Conventional screening approaches are shown to be effective for high‐risk groups (tobacco/alcohol habitués). Raman spectroscopy (RS) is being extensively explored as an alternate/adjunct tool for diagnosis and management of oral cancers. In a previous Raman study on sequential oral carcinogenesis using hamster buccal pouch model, misclassifications between spectra from control and carcinogen [7,12‐dimethylbenz(a)anthracene (DMBA)]‐treated tissues were observed. Histopathology of some control tissues suggested pathological changes, attributable to repeated forceps‐induced irritations/trauma during animal handling. To explore these changes, in the present study, we recorded spectra from three different types of controls – vehicle control (n = 45), vehicle contralateral (n = 45), and DMBA contralateral (n = 70) – exposed to varying degree of forceps handling, along with DMBA‐treated pouches (n = 70) using a 14‐week carcinogenesis protocol. Spectra certified on the basis of histopathology and abnormal cell proliferation (cyclin D1 expression) were used to build models that were evaluated by independent test spectra from an exclusive set of DMBA‐treated and control animals. Many DMBA‐contralateral, vehicle‐control, and vehicle‐contralateral spectra were identified as higher pathologies, which subsequently corroborated with histopathology/cyclin D1 expression. Repeated forceps‐mediated injuries/irritations, during painting and animal handling, may elicit inflammatory responses, leading to neoplasm. The findings of the study suggest that RS could identify micro‐changes. Further, RS‐based in vivo imaging can serve as a promising label‐free tool for screening even in the non‐habitué population where conventional screening is shown to be not effective. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessment of ex vivo perfused liver health by Raman spectroscopy

Raman spectroscopy was applied in this research to monitor the overall health and degradation of porcine livers perfused ex vivo using the VasoWaveW® perfusion system. A novel Raman‐based diagnostic analysis was developed that enables near real‐time and label‐free monitoring of organ health during ex vivo perfusion designed to extend the useful life of the organ for transplantation. Multivariate statistical analysis of Raman spectra of organ perfusate fluid, using a combination of principal component analysis and linear discriminant analysis, proved to be an effective technique to assess the degradation properties of the livers. Three livers (with replicates) were perfused ex vivo under different pressures and temperatures and were compared with a 24‐h time‐course. Results indicated that perfusion pressure was a more significant factor in organ degradation than was temperature. In addition, a non‐linear degradation profile was identified for all three perfused livers, and this profile was different for individual livers, demonstrating the time‐dependent transition from its initial ‘healthy’ state towards a more ‘unhealthy’ degenerative state at 24 h. The Raman spectroscopy‐based approach described here has potential applications in perfusion and diagnostic instrumentation that can be used in near real‐time during organ transit and in operating rooms to help identify appropriately healthy organs for transplantation. Copyright © 2015 John Wiley & Sons, Ltd.     

Raman spectral signatures of mouse mammary tissue and associated lymph nodes: normal,tumor and mastitis

Raman spectroscopy involves the interaction of light with the molecular vibrations and therefore can provide information about molecular structure, tissue composition and changes in its environment. We explored whether Raman spectroscopy can reliably distinguish mammary tumors from normal mammary tissues and other pathological states in mice. We analyzed a large number of Raman spectra from the tumor and normal mammary glands of mice injected with 4T1 tumor cells, which were collected using a high‐resolution (less than 4 cm⁻¹) Raman spectrometer at a fixed (785 nm) laser excitation wavelength and with 60 mW of laser power. The spectra of normal and tumor mammary glands showed consistent differences in the intensity of certain Raman bands and loss of some bands in the tumor spectra. Multivariate statistical methods—principal component analysis (PCA) and discriminant functional analysis (DFA)—were used to separate the data into different groups of mammary tumors, mastitis, lymph nodes contralateral and tumor‐cell‐injected sides, and normal contralateral and tumor‐cell‐injected sides. We demonstrate that this spectroscopic technique has the feasibility of discriminating tumor and mastitis from normal tissues and other pathological states in a short period of time and may detect tumor transformation earlier than the standard histological examination stage. Copyright © 2006 John Wiley & Sons, Ltd.     

Comparison of molecular images as defined by Raman spectra between normal mucosa and squamous cell carcinoma in the oral cavity

Raman spectroscopy has been effectively applied to clinically differentiate normal and cancerous mucosal tissues. Micro‐Raman spectroscopy provides a tool to better understand the molecular basis for the Raman clinical signal. The objective of the current study was to utilize micro‐Raman spectroscopy to define the molecular/spectral differences between normal and abnormal squamous cell carcinoma (SCC) in oral mucosa (in vitro). Understanding this may help in identifying unique spectra or may be useful for in vivo application of this technology. Micro‐Raman (confocal) spectroscopy was used to obtain molecular images of normal and SCC cells of human oral mucosa. Four fresh flashed‐frozen tumor and four matched normal tongue specimens were studied. The spectra covered a wavenumber range from 300 to 4000 cm⁻¹ with a spectral resolution of 8 cm⁻¹ and a spatial resolution of 1.0 µm. The cells were located within thin sections of tongue mucosa biopsies. The excitation wavelength of 515 nm was used. We were able to obtain Raman images with rich information about the spectroscopic and structural features within the cytoplasm, cell membrane, and cell nuclei. Significant spectral differences were observed between the Raman images of normal and malignant squamous cells. The heterogeneity of tumor cells within the abnormal tissue was also demonstrated. Spectral differences demonstrated between both tissue types have provided important information regarding the origins of specific signals within the cells of each tissue type. In our search for specific spectral biomarkers, we believe that a cell surface protein, greatly upregulated in SCC cells, was discovered at 1583 cm⁻¹. Copyright © 2010 John Wiley & Sons, Ltd.     

In vivo study on the protection of indole‐3‐carbinol (I3C) against the mouse acute alcoholic liver injury by micro‐Raman spectroscopy

Micro‐Raman spectroscopy (MRS) was utilized for the first time to evaluate the effect of indole‐3‐carbinol (I3C) on acute alcoholic liver injury in vivo. In situ Raman analysis of tissue sections provided distinct spectra that can be used to distinguish alcoholic liver injury as well as ethanol‐induced liver fibrosis from the normal state. Sixteen mice with liver diseases including acute liver injury and chronic liver fibrosis, and eight mice with normal liver tissues, and eight remedial mice were studied employing the Raman spectroscopic technique in conjunction with biomedical assays. The biochemical changes in mouse liver tissue when liver injury/fibrosis occurs such as the loss of reduced glutathione (GSH), and the increase of collagen (α‐helix protein) were observed by MRS. The intensity ratio of two Raman peaks (I₁₄₅₀/I₆₆₆) and in combination with statistical analysis of the entire Raman spectrum was found capable of classifying liver tissues with different pathological features. Raman spectroscopy therefore is an important candidate for a nondestructive in vivo screening of the effect of drug treatment on liver disease, which potentially decreases the time‐consuming clinical trials. Copyright © 2008 John Wiley & Sons, Ltd.     

Study of both fingerprint and high wavenumber Raman spectroscopy of pathological nasopharyngeal tissues

High wavenumber (HW) Raman spectroscopy has weaker fluorescence background compared with fingerprint (FP) region. This study aims to evaluate the discrimination feasibility of nasopharyngeal non‐cancerous and nasopharyngeal cancer (NPC) tissue with both FP and HW Raman spectroscopy. HW Raman spectra of nasopharyngeal tissue were obtained for the first time. Raman spectra were collected to differentiate nasopharyngeal non‐cancerous (n = 37) from NPC (n = 41) tissues in FP (800–1800cm⁻¹), HW (2700–3100cm⁻¹), and integrated FP/HW region. First, to assess the utility of this method, the averaged Raman spectral intensities and intensity ratios of corresponding Raman bands were analyzed in HW and FP regions, respectively. The results show that intensities as well as the ratios of specific Raman peaks might be helpful in distinguishing nasopharyngeal non‐cancerous from NPC tissue with the HW Raman spectroscopy, as with FP Raman reported before. The multivariate statistical method based on the combination of principal component analysis–liner discriminant analysis (PCA‐LDA), together with leave‐one‐patient‐out, cross‐validation diagnostic algorithm, was used for discriminating nasopharyngeal non‐cancerous from NPC tissue, generating sensitivities of 87.8%, 85.4%, and 95.1% and specificities of 86.5%, 91.9%, and 89.2%, respectively, with Raman spectroscopy in the FP, HW, and integrated FP/HW regions. The posterior probability of classification results and receiver operating characteristic curves were utilized to evaluate the discrimination of PCA‐LDA algorithm, verifying that HW Raman spectroscopy has a positive effect on the differentiation for the diagnosis of NPC tissue by integrated FP/HW Raman spectroscopy. What's more, the potential of Raman spectroscopy used for differentiating different pathology NPC tissues was also discussed. The results demonstrate that both FP and HW Raman spectroscopy have the potential for diagnosis and detection in early nasopharyngeal carcinoma, and HW Raman spectroscopy may improve the discrimination of NPC tissue compared with FP region alone, providing a promising diagnostic tool for the diagnosis of NPC tissue. Copyright © 2015 John Wiley & Sons, Ltd.     

Raman spectroscopy at different excitation wavelengths (1064, 785 and 532 nm) as a tool for diagnosis of colon cancer

Raman spectroscopy is structure sensitive non‐destructive method that allows observing the status of biological tissues with minimal impact. This method has a great potential in the diagnosis of various types of degenerative diseases including cancer damages. Near‐infrared Fourier transform (NIR‐FT)‐Raman (λ_ex ~1064 nm), NIR‐visible (Vis)‐Raman (λ_ex ~785 nm) and Vis‐Raman (λ_ex ~532 nm) spectra of normal and colorectal carcinoma colon tissue samples were recorded in macroscopic mode at 10–20 randomly chosen independent sites. In the cases of NIR‐Vis‐ and Vis‐Raman spectra, enhanced resonance effects were observed for tissue chromophores absorbing in the visible area. Evident spectral differences were noticed for Raman spectra of normal colon tissue samples in comparison with abnormal samples. The average Raman spectra of colon tissue samples were analysed by principal component analysis (PCA) to discriminate normal and abnormal tissues. PCA of combined dataset containing Raman intensities of chosen NIR‐FT, NIR‐Vis or Vis‐Raman bands led to discrimination of normal and abnormal colon tissue samples. Therefore, combination of these three Raman methods can be helpful for recognizing cancer lesions in colon for diagnostic purposes. Copyright © 2014 John Wiley & Sons, Ltd.     

Do formalin fixation and freeze‐thaw affect near‐infrared Raman spectroscopy of cartilaginous tissue? A preliminary ex vivo analysis of native human articular cartilage

Near‐infrared (NIR) Raman microprobe spectroscopy has been applied to the non‐invasive characterization of the biochemical structure of extracellular matrix in articular cartilage, a step forward along the path of in vivo diagnostic application of chondropathy. In most studies handling ex vivo cartilage specimens, formalin fixation or freeze‐thaw treatments have been applied in order to stabilize tissue and cell constituents prior to spectroscopic measurements. However, these pre‐processing manipulations might significantly affect certain target bands of the cartilage spectra, thus introducing biases in the characterizations, and potentially leading to data misinterpretation. In this study, we evaluated how formalin fixing and freeze‐thaw processes affect Raman spectra from human femur cartilage. Healthy cartilage specimens were fixed/stored either in a 10% neutral buffered formalin solution or in a deep freezer set at −80 °C. The results of this study show that formalin fixation significantly affects the NIR Raman spectra of cartilage specimens due to concurrent formalin absorption and water dehydration within both collagen and glycosaminoglycan macromolecules. Water dehydration was also confirmed in the amide I structure in the frozen‐thawed specimen, but to a much lesser extent. Furthermore, soaking the tissues in phosphate‐buffered saline solution minimized the storage‐induced Raman artifacts, but its immersion had limited effectiveness in formalin‐fixed specimens, predominantly due to an overlap of signals from the formalin liquid (i.e. emitting at 1046 and 1492 cm⁻¹). Therefore, to provide a highly accurate biochemical evaluation of extracellular matrix using NIR Raman spectroscopy, freeze‐thaw processes are more suitable for ex vivo samples of human cartilage than formalin fixation. Copyright © 2015 John Wiley & Sons, Ltd.     

Fourier‐transform Raman analysis of milk powder: a potential method for rapid quality screening

In this work, FT‐Raman spectroscopy was explored as a fast and reliable screening method for the assessment of milk powder quality and the identification of samples adulterated with whey (1–40% w/w). Raman measurements can easily differentiate milk powders without the need of sample preparation, whereas the traditional methods of quality control, including high‐performance liquid chromatography, are laborious and slow. The FT‐Raman spectra of whole, low‐fat, and skimmed milk powder samples were obtained and distinguished from commercial milk powder samples. In addition, the exploratory analysis employing data from Raman spectroscopy and principal component analysis (PCA)allowed the separation of milk powder samples according to type,identifying differences between samples in the same group. Multivariate analysis was also developed to classify the adulterated milk powder samples using PCA and partial least squares discriminate analysis (PLS‐DA). The resulting PLS‐DA model correctly classified 100% of the adulterated samples. These results clearly demonstrate the utility of FT‐Raman spectroscopy combined with chemometrics as a rapid method for screening milk powder. Copyright © 2011 John Wiley & Sons, Ltd.     

Raman spectroscopy measurement of levofloxacin lactate in blood using an optical fiber nano‐probe

Liquid chromatography and mass spectrometry were time‐consuming and expensive as the main methods for the drug analysis at present, and the samples must be pretreated. The Raman spectroscopy measurement methods were fast and simple, so the Raman spectroscopy methods for the drug analysis were explored in this paper. An optical fiber nano‐probe coated with gold nanoparticles was fabricated and used with surface‐enhanced Raman spectroscopy (SERS) to measure levofloxacin lactate. The resulting SERS spectra of levofloxacin lactate in mouse blood that was detected by the optical fiber nano‐probe clearly showed the characteristic wave numbers of levofloxacin lactate, indicating that optical fiber nano‐probes can be used with spectral techniques to analyze drugs in vitro or potentially even in vivo. Copyright © 2015 John Wiley & Sons, Ltd.     

Near‐infrared surface‐enhanced Raman spectroscopy (NIR‐SERS) studies on oxyheamoglobin (OxyHb) of liver cancer based on PVA‐Ag nanofilm

A near‐infrared surface‐enhanced Raman spectroscopy (NIR‐SERS) method was employed for oxyheamoglobin (OxyHb) detection to develop a simple blood test for liver cancer detection. Polyvinyl alcohol protected silver nanofilm (PVA‐Ag nanofilm) used as the NIR‐SERS active substrate to enhance the Raman scattering signals of OxyHb. High quality NIR‐SERS spectrum from OxyHb adsorbed on PVA‐Ag nanofilm can be obtained within 16 s using a portable Raman spectrometer. NIR‐SERS measurements were performed on OxyHb samples of healthy volunteers (control subjects, n = 30), patients (n = 40) with confirmed liver cancer (stage I, II and III) and the liver cancer patients after surgery (n = 30). Meanwhile, the tentative assignments of the Raman bands in the measured NIR‐SERS spectra were performed, and the results suggested cancer specific changes on molecule level, including a decrease in the relative concentrations and the percentage of aromatic amino acids of OxyHb, changes of the vibration modes of the C_aH_m group and pyrrole ring of OxyHb of liver cancer patients. In this paper, principal component analysis (PCA) combined with independent sample T test analysis of the measured NIR‐SERS spectra separated the spectral features of the two groups into two distinct clusters with the sensitivity of 95.0% and the specificity of 85.7%. Meanwhile, the recovery situations of the liver cancer patients after surgery were also assessed using the method of discriminant analysis‐predicting group membership based on PCA. The results show that 26.7% surgeried liver cancer patients were distinguished as the normal subjects and 63.3% were distinguished into the cancer. Our study demonstrated great potentials for developing NIR‐SERS OxyHb analysis into a novel clinical tool for non‐invasive detection of liver cancers. Copyright © 2013 John Wiley & Sons, Ltd.     

Polarized Raman and photoluminescence studies of a sub‐micron sized hexagonal AlGaN crystallite for structural and optical properties

The polarized Raman spectroscopy is capable of giving confirmation regarding the crystalline phase as well as the crystallographic orientation of the sample. In this context, apart from crystallographic X‐ray and electron diffraction tools, polarized Raman spectroscopy and corresponding spectral imaging can be a promising crystallographic tool for determining both crystalline phase and orientation. Sub‐micron sized hexagonal AlGaN crystallites are grown by a simple atmospheric pressure chemical vapor deposition technique using the self catalytic vapor–solid process under N‐rich condition. The crystallites are used for the polarized Raman spectra in different crystalline orientations along with spectral imaging studies. The results obtained from the polarized Raman spectral studies show single crystalline nature of sub‐micron sized hexagonal AlGaN crystallites. Optical properties of the crystallites for different crystalline orientations are also studied using polarized photoluminescence measurements. The influence of internal crystal field to the photoluminescence spectra is proposed to explain the distinctive observation of splitting of emission intensity reported, for the first time, in case of c‐plane oriented single crystalline AlGaN crystallite as compared with that of m‐plane oriented crystallite. Copyright © 2016 John Wiley & Sons, Ltd.     

Rapid biochemical profiling of endothelial dysfunction in diabetes,hypertension and cancer metastasis by hierarchical cluster analysis of Raman spectra

Raman spectroscopy is a label free, versatile, simple and fast method that is increasingly used to detect pathological changes in the cells and tissues that could be useful in medical diagnostics. In this work, we tested the hypothesis that Raman spectroscopy may serve to detect endothelial dysfunction in murine models of lifestyle diseases associated with endothelial dysfunction. For that purpose, we analysed spectra from ex vivo vessels taken from mice with diabetes, hypertension and cancer metastasis. We extracted 50–70 random, single spectra, recorded in 0.2 s, from endothelium of mice with diseases and respective control animals and subjected them to hierarchical cluster analysis. Independently on the sample preparation protocol, very good discrimination was obtained for three‐tested murine models, i.e. diabetes, hypertension and cancer metastasis. Obtained sensitivity and specificity parameters were between 93% and 96% (with the exception of sensitivity in the diabetes model equalled to 88%). Our results show that single, random spectra of endothelium, recorded in less than a second, contains enough information on biochemical content of the endothelium to detect endothelial dysfunction. Furthermore, we demonstrated that biochemical profile of the endothelial dysfunction in diabetes, hypertension or cancer metastasis differs with a very high specificity and sensitivity. This conclusion can be a good starting point for the development of in vivo fast diagnostic methodology of endothelium in the future. Copyright © 2016 John Wiley & Sons, Ltd.     

A comprehensive study of classification methods for medical diagnosis

In this model study, we developed a method to distinguish between breast cancer cells and normal epithelial cells, which is in principal suitable for online diagnosis by Raman spectroscopy. Two cell lines were chosen as model systems for cancer and normal tissue. Both cell lines consist of epithelial cells, but the cells of the MCF‐7 series are carcinogenic, where the MCF‐10A cells are normal growing. An algorithm is presented for distinguishing cells of the MCF‐7 and MCF‐10A cell lines, which has an accuracy rate of above 99%. For this purpose, two classification steps are utilized. The first step, the so‐called top‐level classifier searches for Raman spectra, which are measured in the nuclei region. In the second step, a wide range of discriminant models are possible and these models are compared. The classification rates are always estimated using a cross‐validation and a holdout‐validation procedure to ensure the ability of the routine diagnosis to work in clinical environments. Copyright © 2009 John Wiley & Sons, Ltd.     

Raman spectroscopy utilizing Fisher‐based feature selection combined with Support Vector Machines for the characterization of breast cell lines

Raman spectroscopy has the potential to significantly aid in the research and diagnosis of cancer. The information dense, complex spectra generate massive datasets in which subtle correlations may provide critical clues for biological analysis and pathological classification. Therefore, implementing advanced data mining techniques is imperative for complete, rapid and accurate spectral processing. Numerous recent studies have employed various data methods to Raman spectra for classification and biochemical analysis. Although, as Raman datasets from biological specimens are often characterized by high dimensionality and low sample numbers, many of these classification models are subject to overfitting. Furthermore, attempts to reduce dimensionality result in transformed feature spaces making the biological evaluation of significant and discriminative spectral features problematic. We have developed a novel data mining framework optimized for Raman datasets, called Fisher‐based Feature Selection Support Vector Machines (FFS‐SVM). This framework provides simultaneous supervised classification and user‐defined Fisher criterion‐based feature selection, reducing overfitting and directly yielding significant wavenumbers from the original feature space. Herein, we investigate five cancerous and non‐cancerous breast cell lines using Raman microspectroscopy and our unique FFS‐SVM framework. Our framework classification performance is then compared to several other frequently employed classification methods on four classification tasks. The four tasks were constructed by an unsupervised clustering method yielding the four different categories of cell line groupings (e.g. cancer vs non‐cancer) studied. FFS‐SVM achieves both high classification accuracies and the extraction of biologically significant features. The top ten most discriminative features are discussed in terms of cell‐type specific biological relevance. Our framework provides comprehensive cellular level characterization and could potentially lead to the discovery of cancer biomarker‐type information, which we have informally termed ‘Raman‐based spectral biomarkers’. The FFS‐SVM framework along with Raman spectroscopy will be used in future studies to investigate in‐situ dynamic biological phenomena. Copyright © 2013 John Wiley & Sons, Ltd.     

Decomposition of in vivo spatially offset Raman spectroscopy data using multivariate analysis techniques

The decomposition of spatially offset Raman spectra for complex multilayer systems, such as biological tissues, requires advanced techniques such as multivariate analyses. Often, in such situations, the decomposition methods can reach their limits of accuracy well before the limits imposed by signal‐to‐noise ratios. Consequently, more effective reconstruction methods could yield more accurate results with the same data set. In this study we process spatially offset Raman spectroscopy (SORS) data with three different multivariate techniques (band‐target entropy minimization (BTEM), multivariate curve resolution and parallel factor analysis (PARAFAC)) and compare their performance when analysing a spectrally challenging plastic model system and an even more challenging problem, the analysis of human bone transcutaneously in vivo. For the in vivo measurements, PARAFAC's requirement of multidimensional orthogonal data is addressed by recording SORS spectra both at different spatial offsets and at different anatomical points, the latter providing added dimensionality through the variation of skin/soft tissue thickness. The BTEM and PARAFAC methods performed the best on the plastic system with the BTEM more faithfully reconstructing the major Raman bands and PARAFAC the smaller more heavily overlapped features. All three methods succeeded in reconstructing the bone spectrum from the transcutaneous data and gave good figures for the phosphate‐to‐carbonate ratio (within 2% of excised human tibia bone); the PARAFAC gave the most accurate figure for the mineral‐to‐collagen ratio (20% less than excised human tibia bone). Previous studies of excised bones have shown that certain bone diseases (such as osteoarthritis, osteoporosis and osteogenesis imperfecta) are accompanied by compositional abnormalities that can be detected with Raman spectroscopy, the utility of a technique which could reconstruct bone spectra accurately is manifest. The results have relevance on the use of SORS in general. © 2014 Crown copyright. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.     

Method development: Raman spectroscopy‐based histopathology of oral mucosa

An earlier and more accurate detection of (small) cancerous and precancerous lesions in the oral cavity is essential to improve the prognosis of oral squamous cell carcinomas. Raman spectroscopy is being pursued as a potential method to realize this improvement, since the technique provides objective information on a biochemical level and can be used for real‐time guidance of the diagnostic procedure. Since oral mucosal tissue is inhomogeneous and comprises different layers and histological structures, a good understanding of the signal contributions of the individual layers and structures is required for an accurate interpretation of in vivo tissue spectra measurement volumes. The aim of this study was to create a standardized method to collect and analyse the spectral contributions of individual histopathological structures in oral mucosa. The method is based on Raman microspectroscopic mapping of unstained frozen tissue sections and subsequent histopathological annotation of the features in the resulting Raman images. The obtained annotated reference spectra were used as input in an unsupervised hierarchical cluster analysis in order to determine the spectral characteristics and variance within one histo(patho)logical structure. The described method resulted in an annotated database of Raman spectral characteristics of individual histopathological structures encountered in oral tissue. This database can be used as input for the development of classification and quantification algorithms, in order to achieve a high specificity and sensitivity for clinical diagnostic instruments. Additionally, this database can be used to optimize the exact location and measurement volume of in vivo measurements. Copyright © 2013 John Wiley & Sons, Ltd.