Combined Fourier transform infrared and Raman spectroscopic approach for identification of multidrug resistance phenotype in cancer cell lines

Vibrational Biospectroscopy: An Alternative Approach to Endometrial Cancer Diagnosis and Screening

Endometrial cancer (EC) is the sixth most common cancer and the fourth leading cause of death among women worldwide. Early detection and treatment are associated with a favourable prognosis and reduction in mortality. Unlike other common cancers, however, screening strategies lack the required sensitivity, specificity and accuracy to be successfully implemented in clinical practice and current diagnostic approaches are invasive, costly and time consuming. Such limitations highlight the unmet need to develop diagnostic and screening alternatives for EC, which should be accurate, rapid, minimally invasive and cost-effective. Vibrational spectroscopic techniques, Mid-Infrared Absorption Spectroscopy and Raman, exploit the atomic vibrational absorption induced by interaction of light and a biological sample, to generate a unique spectral response: a “biochemical fingerprint”. These are non-destructive techniques and, combined with multivariate statistical analysis, have been shown over the last decade to provide discrimination between cancerous and healthy samples, demonstrating a promising role in both cancer screening and diagnosis. The aim of this review is to collate available evidence, in order to provide insight into the present status of the application of vibrational biospectroscopy in endometrial cancer diagnosis and screening, and to assess future prospects.

Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging

BACKGROUND

Digital pathology, in its primary meaning, describes the utilization of computer screens to view scanned histology slides. Digitized tissue sections can be easily shared for a second opinion. In addition, it allows tissue image analysis using specialized software to identify and measure events previously observed by a human observer. These tissue-based readouts were highly reproducible and precise. Digital pathology has developed over the years through new technologies. Currently, the most discussed development is the application of artificial intelligence to automatically analyze tissue images. However, even new label-free imaging technologies are being developed to allow imaging of tissues by means of their molecular composition.

SUMMARY

This review provides a summary of the current state-of-the-art and future digital pathologies. Developments in the last few years have been presented and discussed. In particular, the review provides an outlook on interesting new technologies (e.g., infrared imaging), which would allow for deeper understanding and analysis of tissue thin sections beyond conventional histopathology.

KEY MESSAGES

In digital pathology, mathematical methods are used to analyze images and draw conclusions about diseases and their progression. New innovative methods and techniques (e.g., label-free infrared imaging) will bring significant changes in the field in the coming years.

Raman Spectroscopy: An Exploratory Study to Identify Post-Radiation Cell Survival

Resistance to radiotherapy has been an impediment in the treatment of cancer, and the inability to detect it at an early stage further exacerbates the prognosis. We have assessed the feasibility of Raman spectroscopy as a rapid assay for predicting radiosensitivity of cancer cells in comparison to the conventional biological assays. Cell lines derived from breast adenocarcinoma (MCF7), gingivobuccal squamous cell carcinoma (ITOC-03), and human embryonic kidney (HEK293) were subjected to varying doses of ionizing radiation. Cell viability of irradiated cells was assessed at different time points using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and Raman spectroscopy, and colony-forming capability was evaluated by clonogenic assay. Radiosensitivity observed using MTT assay was limited by the finding of similar cell viability in all the three cell lines 24 h post-irradiation. However, cell survival assessed using clonogenic assay and principal component linear discriminant analysis (PC-LDA) classification of Raman spectra showed correlating patterns. Irradiated cells showed loss of nucleic acid features and enhancement of 750 cm^-1 peak probably attributing to resonance Raman band of cytochromes in all three cell lines. PC-LDA analysis affirmed MCF7 to be a radioresistant cell line as compared to ITOC-03 and HEK293 to be the most radiosensitive cell line. Raman spectroscopy is shown to be a rapid and alternative assay for identification of radiosensitivity as compared to the gold standard clonogenic assay.

Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Analysis of Saliva for Breast Cancer Diagnosis

Saliva biomarkers using reagent-free biophotonic technology have not been investigated as a strategy for early detection of breast cancer (BC). The attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has been proposed as a promising tool for disease diagnosis. However, its utilization in cancer is still incipient, and currently saliva has not been used for BC screening. We have applied ATR-FTIR onto saliva from patients with breast cancer, benign breast disease, and healthy matched controls to investigate its potential use in BC diagnosis. Several salivary vibrational modes have been identified in original and second-derivative spectra. The absorbance levels at wavenumber 1041 cm⁻¹ were significantly higher (p < 0.05) in saliva of breast cancer patients compared with those of benign patients, and the ROC curve analysis of this peak showed a reasonable accuracy to discriminate breast cancer from benign and control patients. The 1433–1302.9 cm⁻¹ band area was significantly higher (p < 0.05) in saliva of breast cancer patients than in control and benign patients. This salivary ATR-FTIR spectral area was prevalidated as a potential diagnostic biomarker of BC. This spectral biomarker was able to discriminate human BC from controls with sensitivity and specificity of 90% and 80%, respectively. Besides, it was able to differentiate BC from benign disease with sensitivity and specificity of 90% and 70%, respectively. Briefly, for the first time, saliva analysis by ATR-FTIR spectroscopy has demonstrated the potential use of salivary spectral biomarkers (1041 cm⁻¹ and 1433–1302.9 cm⁻¹) as a novel alternative for noninvasive BC diagnosis, which could be used for screening purposes.

Evaluation of Multidrug Resistance of Leukemia Using Surface-Enhanced Raman Scattering Method for Clinical Applications

P-glycoprotein (P-gp) is an important multidrug resistance (MDR) regulator for leukemia to mediate its development and thus can be considered as a powerful reference for the diagnosis of MDR. The detection of P-gp is of vital significance and has attracted considerable concerns. In this study, we proposed a surface-enhanced Raman scattering (SERS) method for the evaluation of P-gp expression levels in leukemia cell lines. Basically, we utilized an aqueous phase sandwich-type immunoassay to analyze the expression of P-gp. First, anti-CD45-decorated magnetic beads (MBs) and P-gp antibody-decorated SERS probes were fabricated. CD45 is a common protein expressed in all leukemia cells. As a result, a sandwich immunocomplex can be formed by the MBs, P-gp-overexpressed leukemia cells, and SERS probes. The expression level of P-gp determines the amount of SERS probes that can be captured. Consequently, the SERS intensity of the immunocomplex can be used to evaluate the expression level of P-gp. In a typical procedure, we measured the P-gp expression of an MDR leukemia cell line (K562/ADM) as well as unprocessed whole-blood samples. The SERS intensity of K562/ADM cells was highly correlated with the extent of MDR or the incubation time of adriamycin (which is an MDR inducing drug). In addition, the SERS intensity of the refractory/relapsing group was about sixfolds of that of the control group ( P < 0.01). These results demonstrated that the proposed method holds excellent sensitivity, specificity, reliability, and application potential in assessing both cultured cells and clinical samples. With these outstanding features, we anticipated that such a SERS-based method could be very helpful for the clinical diagnosis of early-stage MDR in leukemia.

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 with 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 principal component analysis or linear discriminant analysis 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 2,900 cm-1 and the lactate contributions at 1,785 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.

Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.

Hyperspectral Raman imaging of human prostatic cells: An attempt to differentiate normal and malignant cell lines by univariate and multivariate data analysis

Hyperspectral Raman images of human prostatic cells have been collected and analysed with several approaches to reveal differences among normal and tumor cell lines. The objective of the study was to test the potential of different chemometric methods in providing diagnostic responses. We focused our analysis on the ν(CH) region (2800-3100cm^-1) owing to its optimal Signal-to-Noise ratio and because the main differences between the spectra of the two cell lines were observed in this frequency range. Multivariate analysis identified two principal components, which were positively recognized as due to the protein and the lipid fractions, respectively. The tumor cells exhibited a modified distribution of the cytoplasmatic lipid fraction (mainly localized alongside the cell boundary) which may result very useful for a preliminary screening. Principal Component analysis was found to provide high contrast and to be well suited for image-processing purposes. Self-Modelling Curve Resolution made available meaningful spectra and relative-concentration values; it revealed a 97% increase of the lipid fraction in the tumor cell with respect to the control. Finally, a univariate approach confirmed significant and reproducible differences between normal and tumor cells.

Effects of nilotinib on leukaemia cells using vibrational microspectroscopy and cell cloning

S-FTIR and Raman microspectroscopies identify spectral markers of sensitivity/resistance to nilotinib in leukaemia cell clones.

Renal Graft Fibrosis and Inflammation Quantification by an Automated Fourier-Transform Infrared Imaging Technique

Renal interstitial fibrosis and interstitial active inflammation are the main histologic features of renal allograft biopsy specimens. Fibrosis is currently assessed by semiquantitative subjective analysis, and color image analysis has been developed to improve the reliability and repeatability of this evaluation. However, these techniques fail to distinguish fibrosis from constitutive collagen or active inflammation. We developed an automatic, reproducible Fourier-transform infrared (FTIR) imaging-based technique for simultaneous quantification of fibrosis and inflammation in renal allograft biopsy specimens. We generated and validated a classification model using 49 renal biopsy specimens and subsequently tested the robustness of this classification algorithm on 166 renal grafts. Finally, we explored the clinical relevance of fibrosis quantification using FTIR imaging by comparing results with renal function at 3 months after transplantation (M3) and the variation of renal function between M3 and M12. We showed excellent robustness for fibrosis and inflammation classification, with >90% of renal biopsy specimens adequately classified by FTIR imaging. Finally, fibrosis quantification by FTIR imaging correlated with renal function at M3, and the variation in fibrosis between M3 and M12 correlated well with the variation in renal function over the same period. This study shows that FTIR-based analysis of renal graft biopsy specimens is a reproducible and reliable label-free technique for quantifying fibrosis and active inflammation. This technique seems to be more relevant than digital image analysis and promising for both research studies and routine clinical practice.

FTIR spectroscopy reveals lipid droplets in drug resistant laryngeal carcinoma cells through detection of increased ester vibrational bands intensity

The major obstacle to successful chemotherapy of cancer patients is drug resistance. Previously we explored the molecular mechanisms of curcumin cross-resistance in carboplatin resistant human laryngeal carcinoma 7T cells. Following curcumin treatment we found a reduction in curcumin accumulation, and reduced induction of reactive oxygen species (ROS) and their downstream effects, compared to parental HEp-2 cells. In order to shed more light on mechanisms involved in drug resistance of 7T cells, in the present study we applied Fourier transform infrared (FTIR) spectroscopy, a technique that provides information about the nature and quantities of all molecules present in the cell. By comparing the spectra from parental HEp-2 cells and their 7T subline, we found an increase in the intensity of ester vibrational bands in 7T cells. This implied an increase in the amount of cholesteryl esters in resistant cells, which we confirmed by an enzymatic assay. Since cholesteryl esters are localized in lipid droplets, we confirmed their higher quantity and serum dependency in 7T cells compared to HEp-2 cells. Moreover, treatment with oleic acid induced more lipid droplets in 7T when compared to HEp-2 cells, as shown by flow cytometry. We can conclude that along with previously determined molecular mechanisms of curcumin resistance in 7T cells, these cells exhibit an increased content of cholesteryl esters and lipid droplets, suggesting an alteration in cellular lipid metabolism as a possible additional mechanism of drug resistance. Furthermore, our results suggest the use of FTIR spectroscopy as a promising technique in drug resistance research.

Unsupervised explorative data analysis of normal human leukocytes and BCR/ABL positive leukemic cells mid-infrared spectra

We proved the ability of Fourier Transform Infrared microspectroscopy (microFTIR) complemented by Principal Component Analysis (PCA) to detect protein phosphorylation/de-phosphorylation in mammalian cells. We analyzed by microFTIR human polymorphonuclear neutrophil (PMNs) leukocytes, mouse-derived parental Ba/F3 cells (Ba/F3#PAR), Ba/F3 cells transfected with p210(BCR/ABL) (Ba/F3#WT) and expressing high levels of protein tyrosine kinase (PTK), and human-derived BCR/ABL positive K562 leukemic cell sub-clones engineered to differently express receptor-type tyrosine-protein phosphatase gamma (PTPRG). Synchrotron radiation (SR) and conventional (globar) IR sources were used to perform microFTIR respectively, on single cells and over several cells within the same sample. Ex vivo time-course experiments were run, inducing maximal protein phosphorylation in PMNs by 100 nM N-formylated tripeptide fMLP. Within the specific IR fingerprint 1800-850 cm(-1) frequency domain, PCA identified two regions with maximal signal variance. These were used to model and test the robustness of PCA in representing the dynamics of protein phosphorylation/de-phosphorylation processes. An IR signal ratio marker reflecting the homeostatic control by protein kinases and phosphatases was identified in normal leukocytes. The models identified by microFTIR and PCA in normal leukocytes also distinguished BCR/ABL positive Ba/F3#WT from BCR/ABL negative Ba/F3#PAR cells as well as K562 cells exposed to functionally active protein tyrosine phosphatase recombinant protein ICD-Tat transduced in cells by HIV-1 Tat technology or cells treated with the PTK inhibitor imatinib mesylate (IMA) from cells exposed to phosphatase inactive (D1028A)ICD-Tat recombinant protein and untreated control cells, respectively. The IR signal marker correctly reflected the degrees of protein phosphorylation associated with abnormal PTK activity in BCR/ABL positive leukemic cells and in general was inversely related to the expression/activity of PTPRG in leukemic sub-clones. In conclusion, we have described a new, reliable and simple spectroscopic method to study the ex vivo protein phosphorylation/de-phosphorylation balance in cell models: it is suitable for biomedical and pharmacological research labs but it also needs further optimization and its evaluation on large cohorts of patients to be proposed in the clinical setting of leukemia.

Emerging technology: applications of Raman spectroscopy for prostate cancer

There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.

Direct determination of phosphatase activity from physiological substrates in cells

A direct and continuous approach to determine simultaneously protein and phosphate concentrations in cells and kinetics of phosphate release from physiological substrates by cells without any labeling has been developed. Among the enzymes having a phosphatase activity, tissue non-specific alkaline phosphatase (TNAP) performs indispensable, multiple functions in humans. It is expressed in numerous tissues with high levels detected in bones, liver and neurons. It is absolutely required for bone mineralization and also necessary for neurotransmitter synthesis. We provided the proof of concept that infrared spectroscopy is a reliable assay to determine a phosphatase activity in the osteoblasts. For the first time, an overall specific phosphatase activity in cells was determined in a single step by measuring simultaneously protein and substrate concentrations. We found specific activities in osteoblast like cells amounting to 116 ± 13 nmol min^-1 mg^-1 for PPi, to 56 ± 11 nmol min^-1 mg^-1 for AMP, to 79 ± 23 nmol min^-1 mg^-1 for beta-glycerophosphate and to 73 ± 15 nmol min^-1 mg^-1 for 1-alpha-D glucose phosphate. The assay was also effective to monitor phosphatase activity in primary osteoblasts and in matrix vesicles. The use of levamisole – a TNAP inhibitor- served to demonstrate that a part of the phosphatase activity originated from this enzyme. An IC₅₀ value of 1.16 ± 0.03 mM was obtained for the inhibition of phosphatase activity of levamisole in osteoblast like cells. The infrared assay could be extended to determine any type of phosphatase activity in other cells. It may serve as a metabolomic tool to monitor an overall phosphatase activity including acid phosphatases or other related enzymes.

Raman spectroscopic study of radioresistant oral cancer sublines established by fractionated ionizing radiation

Radiotherapy is an important treatment modality for oral cancer. However, development of radioresistance is a major hurdle in the efficacy of radiotherapy in oral cancer patients. Identifying predictors of radioresistance is a challenging task and has met with little success. The aim of the present study was to explore the differential spectral profiles of the established radioresistant sublines and parental oral cancer cell lines by Raman spectroscopy. We have established radioresistant sublines namely, 50Gy-UPCI:SCC029B and 70Gy-UPCI:SCC029B from its parental UPCI:SCC029B cell line, by using clinically admissible 2Gy fractionated ionizing radiation (FIR). The developed radioresistant character was validated by clonogenic cell survival assay and known radioresistance-related protein markers like Mcl-1, Bcl-2, Cox-2 and Survivin. Altered cellular morphology with significant increase (p<0.001) in the number of filopodia in radioresistant cells with respect to parental cells was observed. The Raman spectra of parental UPCI:SCC029B, 50Gy-UPCI:SCC029B and 70Gy-UPCI:SCC029B cells were acquired and spectral features indicate possible differences in biomolecules like proteins, lipids and nucleic acids. Principal component analysis (PCA) provided three clusters corresponding to radioresistant 50Gy, 70Gy-UPCI:SCC029B sublines and parental UPCI:SCC029B cell line with minor overlap, which suggest altered molecular profile acquired by the radioresistant cells due to multiple doses of irradiation. The findings of this study support the potential of Raman spectroscopy in prediction of radioresistance and possibly contribute to better prognosis of oral cancer.

Biochemical and molecular aspects of spectral diagnosis in calcinosis cutis

Calcinosis cutis (CC) is a type of calcinosis wherein insoluble compounds or salts deposited on the skin. Clinical diagnosis of CC is usually achieved through time consuming histopathological or immunohistochemical procedures, but it can only be empirically identified by experienced practitioners. The use of advanced vibrational spectroscopy has been recently shown to have great potential as a diagnostic technique for various diseased tissues because it analyses the chemical composition of diseased tissue rather than its anatomy and predicts disease progression. This review article includes a summary of the application of Fourier transform infrared (FT-IR) and Raman spectroscopic or microspectroscopic analysis for the rapid diagnosis and identification of the chemical composition of skin calcified deposits in patients with various CC symptoms. Both advanced techniques not only can detect the types of insoluble salts such as calcium phosphate, calcium carbonate, and monosodium urate, and β-carotene in the calcified deposits of human skin tissue but also can directly differentiate the carbonate substitution in the apatite structure of the skin calcified deposits. In particular, the combination of both vibrational techniques may provide complementary information to simultaneously assess the intact components of the calcified deposits. In the future, both FT-IR and Raman vibrational microspectroscopic techniques will become available tools to support the standard test techniques currently used in some clinical diagnoses. Molecular spectroscopy technique is rapidly changing disease diagnosis and management.

Detection and identification of cancerous murine fibroblasts, transformed by murine sarcoma virus in culture, using Raman spectroscopy and advanced statistical methods

BACKGROUND

Cancer is one of the leading worldwide causes of death. It may be induced by a variety of factors, including carcinogens, radiation, genetic factors, or DNA and RNA viruses. The early detection of cancer is critical for its successful therapy, which can result in complete recovery from some types of cancer.

METHODS

Raman spectroscopy has been widely used in medicine and biology. It is a noninvasive, nondestructive, and water-insensitive technique that can detect changes in cells and tissues that are caused by different disorders, such as cancer. In this study, Raman spectroscopy was used for the identification and characterization of murine fibroblast cell lines (NIH/3T3) and malignant fibroblast cells transformed by murine sarcoma virus (NIH-MuSV) cells.

RESULTS

Using principal component analysis and LDA it was possible to differentiate between the NIH/3T3 and NIH-MuSV cells with an 80-85% success rate based on their Raman shift spectra.

CONCLUSIONS

The best results for differentiation were achieved from spectra that were obtained from the rich membrane sites.

GENERAL SIGNIFICANCE

Because of its homogeneity and complete control of most factors affecting its growth, cell culture is a preferred model for the detection and identification of specific biomarkers related to cancer transformation or other cellular modifications.

Immunohistochemistry, histopathology and infrared spectral histopathology of colon cancer tissue sections

During the past years, many studies have shown that infrared spectral histopathology (SHP) can distinguish different tissue types and disease types independently of morphological criteria. In this manuscript, we report a comparison of immunohistochemical (IHC), histopathological and spectral histopathological results for colon cancer tissue sections. A supervised algorithm, based on the "random forest" methodology, was trained using classical histopathology, and used to automatically identify colon tissue types, and areas of colon adenocarcinoma. The SHP images subsequently were compared to IHC-based images. This comparison revealed excellent agreement between the methods, and demonstrated that label-free SHP detects compositional changes in tissue that are the basis of the sensitivity of IHC.

Raman spectroscopy in biomedicine - non-invasive in vitro analysis of cells and extracellular matrix components in tissues

Raman spectroscopy is an established laser-based technology for the quality assurance of pharmaceutical products. Over the past few years, Raman spectroscopy has become a powerful diagnostic tool in the life sciences. Raman spectra allow assessment of the overall molecular constitution of biological samples, based on specific signals from proteins, nucleic acids, lipids, carbohydrates, and inorganic crystals. Measurements are non-invasive and do not require sample processing, making Raman spectroscopy a reliable and robust method with numerous applications in biomedicine. Moreover, Raman spectroscopy allows the highly sensitive discrimination of bacteria. Rama spectra retain information on continuous metabolic processes and kinetics such as lipid storage and recombinant protein production. Raman spectra are specific for each cell type and provide additional information on cell viability, differentiation status, and tumorigenicity. In tissues, Raman spectroscopy can detect major extracellular matrix components and their secondary structures. Furthermore, the non-invasive characterization of healthy and pathological tissues as well as quality control and process monitoring of in vitro-engineered matrix is possible. This review provides comprehensive insight to the current progress in expanding the applicability of Raman spectroscopy for the characterization of living cells and tissues, and serves as a good reference point for those starting in the field.

Raman imaging

The past decade has seen an enormous increase in the number and breadth of imaging techniques developed for analysis in many industries, including pharmaceuticals, food, and especially biomedicine. Rather than accept single-dimensional forms of information, users now demand multidimensional assessment of samples. High specificity and the need for little or no sample preparation make Raman imaging a highly attractive analytical technique and provide motivation for continuing advances in its supporting technology and utilization. This review discusses the current tools employed in Raman imaging, the recent advances, and the major applications in this ever-growing analytical field.

Raman imaging of single living cells: probing effects of non-cytotoxic doses of an anti-cancer drug

Identifying cell response to a chemotherapy drug treatment, in particular at the single cell level, is an important issue in patient management. This study aims at evaluating the effect of gemcitabine on single living cells using micro-Raman imaging. We used as a model the non-small lung cancer cell line, Calu-1, exposed to cytostatic doses (1 nM to 1 μM for 24 h and 48 h) of gemcitabine, an antitumor drug currently used in the treatment of lung cancer. Following drug treatment as a function of doses and incubation times, the Raman maps of single living cells were acquired. Cell biomolecules (DNA, RNA, and proteins) were chemically extracted and their spectral signatures used to evaluate their respective distribution in the cellular spectral information of control and treated cells. The quantification of these distributions reveals a significant effect of 100 nM gemcitabine at 48 h incubation (concomitant decrease of nucleic acids and increase of proteins). PCA analyses performed both on nuclear and extracted biomolecules spectra show a time-dependent effect of the drug. These promising results reveal that effects of subtoxic doses can be monitored at the single cell level highlighting the importance of such studies for clinical applications.

Combining metabolic fingerprinting and footprinting to understand the phenotypic response of HPV16 E6 expressing cervical carcinoma cells exposed to the HIV anti-viral drug lopinavir

Recently, it has been reported that the anti-viral drug, lopinavir, which is currently used as a human immunodeficiency virus (HIV) protease inhibitor, could also inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells. In this study, C33A parent control cells and HPV16 E6-transfected cells were exposed to lopinavir at concentrations ranging from 0 to 30 microM. The phenotypic response was assessed by Fourier transform infrared (FT-IR) spectroscopy directly on cells (the metabolic fingerprint) and on the cell growth medium (the metabolic footprint). Multivariate analysis of the data using both principal components analysis (PCA) and canonical variates analysis (PC-CVA) showed trends in scores plots that were related to the concentration of the drug. Inspection of the PC-CVA loadings vector revealed that the effect was not due to the drug alone and that several IR spectral regions including proteins, nucleotides and carbohydrates contributed to the separation in PC-CVA space. Finally, partial least squares regression (PLSR) could be used to predict the concentration of the drug accurately from the metabolic fingerprints and footprints, indicating a dose related phenotypic response. This study shows that the combination of metabolic fingerprinting and footprinting with appropriate chemometric analysis is a valuable approach for studying cellular responses to anti-viral drugs.

Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer

The main curative therapy for patients with nonsmall cell lung cancer is surgery. Despite this, the survival rate is only 50%, therefore it is important to more efficiently diagnose and predict prognosis for lung cancer patients. Raman spectroscopy is useful in the diagnosis of malignant and premalignant lesions. The aim of this study is to investigate the ability of Raman microscopy to diagnose lung cancer from surgically resected tissue sections, and predict the prognosis of these patients. Tumor tissue sections from curative resections are mapped by Raman microscopy and the spectra analzsed using multivariate techniques. Spectra from the tumor samples are also compared with their outcome data to define their prognostic significance. Using principal component analysis and random forest classification, Raman microscopy differentiates malignant from normal lung tissue. Principal component analysis of 34 tumor spectra predicts early postoperative cancer recurrence with a sensitivity of 73% and specificity of 74%. Spectral analysis reveals elevated porphyrin levels in the normal samples and more DNA in the tumor samples. Raman microscopy can be a useful technique for the diagnosis and prognosis of lung cancer patients receiving surgery, and for elucidating the biochemical properties of lung tumors.

Infrared spectroscopy characterization of normal and lung cancer cells originated from epithelium

The vibrational spectral differences of normal and lung cancer cells were studied for the development of effective cancer cell screening by means of attenuated total reflection infrared spectroscopy. The phosphate monoester symmetric stretching ν_s(PO₃^2-) band intensity at ~970 cm^-1 and the phosphodiester symmetric stretching ν_s(PO₂^-) band intensity at ~1,085 cm^-1 in nucleic acids and phospholipids appeared to be significantly strengthened in lung cancer cells with respect to the other vibrational bands compared to normal cells. This finding suggests that more extensive phosphorylation occur in cancer cells. These results demonstrate that lung cancer cells may be prescreened using infrared spectroscopy tools.

Protein profile study of breast-tissue homogenates by HPLC-LIF

Proteomics is a promising approach for molecular understanding of neoplastic processes including response to treatment. Widely used 2D-gel electrophoresis/Liquid chromatography coupled with mass spectrometry (LC-MS) are time consuming and not cost effective. We have developed a high-sensitivity (femto/subfemtomoles of protein/20 mul) High Performance Liquid Chromatography-Laser Induced Fluorescence HPLC-LIF instrument for studying protein profiles of biological samples. In this study, we have explored the feasibility of classifying breast tissues by multivariate analysis of chromatographic data. We have analyzed 13 normal, 17 malignant, 5 benign and 4 post-treatment breast-tissue homogenates. Data was analyzed by Principal Component Analysis PCA in both unsupervised and supervised modes on derivative and baseline-corrected chromatograms. Our findings suggest that PCA of derivative chromatograms gives better classification. Thus, the HPLC-LIF instrument is not only suitable for generation of chromatographic data using femto/subfemto moles of proteins but the data can also be used for objective diagnosis via multivariate analysis. Prospectively, identified fractions can be collected and analyzed by biochemical and/or MS methods.

Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy

In this study we obtained Fourier transform infrared (FTIR) spectra of fixed prostate cell lines of differing types as well as the primary epithelial cells from benign prostatic hyperplasia (BPH). Results showed that by using multivariate chemometric analysis it was possible to discriminate and classify these cell lines, which gave rise to sensitivity and specificity values of >94% and >98%, respectively. Following on from these results the possible influences of different factors on the discrimination and classification of the prostate cell lines were examined. Firstly, the effect of using different growth media during cell culturing was investigated, with results indicating that this did not influence chemometric discrimination. Secondly, differences in the nucleus-to-cytoplasm (N/C) ratio were examined, and it was concluded that this factor was not the main reason for the discrimination and classification of the prostate cancer (CaP) cell lines. In conclusion, given the fact that neither growth media nor N/C ratio could totally explain the classification it is likely that actual biochemical differences between the cell lines is the major contributing factor.

Spectral monitoring of surfactant clearance during alveolar epithelial type II cell differentiation

In this study, we report on the noninvasive identification of spectral markers of alveolar type II (ATII) cell differentiation in vitro using Raman microspectroscopy. ATII cells are progenitor cells for alveolar type I (ATI) cells in vivo, and spontaneously differentiate toward an ATI-like phenotype in culture. We analyzed undifferentiated and differentiated primary human ATII cells, and correlated Raman spectral changes to cellular changes in morphology and marker protein synthesis (surfactant protein C, alkaline phosphatase, caveolin-1). Undifferentiated ATII cells demonstrated spectra with strong phospholipid vibrations, arising from alveolar surfactant stored within cytoplasmic lamellar bodies (Lbs). Differentiated ATI-like cells yielded spectra with significantly less lipid content. Factor analysis revealed a phospholipid-dominated spectral component as the main discriminator between the ATII and ATI-like phenotypes. Spectral modeling of the data revealed a significant decrease in the spectral contribution of cellular lipids-specifically phosphatidyl choline, the main constituent of surfactant, as ATII cells differentiate. These observations were consistent with the clearance of surfactant from Lbs as ATII cells differentiate, and were further supported by cytochemical staining for Lbs. These results demonstrate the first spectral characterization of primary human ATII cells, and provide insight into the biochemical properties of alveolar surfactant in its unperturbed cellular environment.

Metabolic fingerprinting as a diagnostic tool

Within the framework of systems biology, functional analyses at all 'omic levels have seen an intense level of activity during the first decade of the twenty-first century. These include genomics, transcriptomics, proteomics, metabolomics and lipidomics. It could be said that metabolomics offers some unique advantages over the other 'omics disciplines and one of the core approaches of metabolomics for disease diagnostics is metabolic fingerprinting. This review provides an overview of the main metabolic fingerprinting approaches used for disease diagnostics and includes: infrared and Raman spectroscopy, Nuclear magnetic resonance (NMR) spectroscopy, followed by an introduction to a wide range of novel mass spectrometry-based methods, which are currently under intense investigation and developmental activity in laboratories worldwide. It is hoped that this review will act as a springboard for researchers and clinicians across a wide range of disciplines in this exciting era of multidisciplinary and novel approaches to disease diagnostics.

Analysis of structural changes in normal and aneurismal human aortic tissues using FTIR microscopy

Aortic aneurisms are frequently asymptomatic but can induce dramatic complications. The diagnosis is only based on the aortic diameter and not on a structural and compositional basis. In this preliminary study, we propose infrared microspectroscopy to nondestructively probe normal and aneurismal human aortas. Spectra from 19 human ascending aortic biopsies (10 normal and 9 aneurismal) were acquired using infrared microspectroscopy. A 1500 x 150 microm(2) area of each 7-microm thick cryosection was investigated using a 30-microm spatial resolution with a total of about 200 spectra per sample. Spectral differences between normal and aneurismal tissues were mainly located in spectral regions related to proteins, such as elastin and collagen, and proteoglycans (1750-1000 cm(-1)). Tissue heterogeneity and sample classification have been evaluated using hierarchical cluster analysis of individual or mean spectra and their second derivative. Using spectral range related to proteins, 100% of good classification was obtained whereas the proteoglycan spectral range was less discriminant. This in vitro study demonstrates the potential of such technique to differentiate between normal and aneurismal aortas using selected spectral ranges. Future investigations will be focused on these specific spectral regions to determine the role of elastin and collagen in the discrimination of normal and pathological aortas.

Raman characterization and chemical imaging of biocolloidal self-assemblies, drug delivery systems, and pulmonary inhalation aerosols: a review

This review presents an introduction to Raman scattering and describes the various Raman spectroscopy, Raman microscopy, and chemical imaging techniques that have demonstrated utility in biocolloidal self-assemblies, pharmaceutical drug delivery systems, and pulmonary research applications. Recent Raman applications to pharmaceutical aerosols in the context of pulmonary inhalation aerosol delivery are discussed. The "molecular fingerprint" insight that Raman applications provide includes molecular structure, drug-carrier/excipient interactions, intramolecular and intermolecular bonding, surface structure, surface and interfacial interactions, and the functional groups involved therein. The molecular, surface, and interfacial properties that Raman characterization can provide are particularly important in respirable pharmaceutical powders, as these particles possess a higher surface-area-to-volume ratio; hence, understanding the nature of these solid surfaces can enable their manipulation and tailoring for functionality at the nanometer level for targeted pulmonary delivery and deposition. Moreover, Raman mapping of aerosols at the micro- and nanometer level of resolution is achievable with new, sophisticated, commercially available Raman microspectroscopy techniques. This noninvasive, highly versatile analytical and imaging technique exhibits vast potential for in vitro and in vivo molecular investigations of pulmonary aerosol delivery, lung deposition, and pulmonary cellular drug uptake and disposition in unfixed living pulmonary cells.

Revealing covariance structures in fourier transform infrared and Raman microspectroscopy spectra: a study on pork muscle fiber tissue subjected to different processing parameters

The aim of this study was to investigate the correlation patterns between Fourier transform infrared (FT-IR) and Raman microspectroscopic data obtained from pork muscle tissue, which helped to improve the interpretation and band assignment of the observed spectral features. The pork muscle tissue was subjected to different processing factors, including aging, salting, and heat treatment, in order to induce the necessary degree of variation of the spectra. For comparing the information gained from the two spectroscopic techniques with respect to the experimental design, multiblock principal component analysis (MPCA) was utilized for data analysis. The results showed that both FT-IR and Raman spectra were mostly affected by heat treatment, followed by the variation in salt content. Furthermore, it could be observed that IR amide I, II, and III band components appear to be effected to a different degree by brine-salting and heating. FT-IR bands assigned to specific protein secondary structures could be related to different Raman C-C stretching bands. The Raman C-C skeletal stretching bands at 1,031, 1,061, and 1,081 cm(-1) are related to the IR bands indicative of aggregated beta-structures, while the Raman bands at 901 cm(-1) and 934 cm(-1) showed a strong correlation with IR bands assigned to a alpha-helical structures. At the same time, the IR band at 1,610 cm(-1), which formerly was assigned to tyrosine in spectra originating from pork muscle, did not show a correlation to the strong tyrosine doublet at 827 and 852 cm(-1) found in Raman spectra, leading to the conclusion that the IR band at 1,610 cm(-1) found in pork muscle tissue is not originating from tyrosine.

Raman microspectroscopy for non-invasive biochemical analysis of single cells

Recent developments in biomedical vibrational spectroscopy now permit the non-invasive imaging of cells and tissues within both the laboratory and clinical settings. The rapid nature and diagnostic potential of both Raman and FTIR (Fourier-transform IR) spectroscopy have resulted in their widespread application to a number of biological fields including fundamental cell biology, medical imaging, tissue engineering and pharmacology. In particular, Raman microspectroscopy shows tremendous promise for the analysis of biological processes within living cells, such as cell cycle dynamics, cell differentiation and cell death. Unlike conventional biological assays, laser-based Raman spectroscopy enables rapid and non-invasive biochemical analysis of cells in the absence of fixatives or labels. The low Raman signal of cell culture buffer/media permits the rapid monitoring of living cells growing under standard cell culture conditions. The Raman spectrum of a cell is a biochemical ‘fingerprint’, containing molecular-level information about all biopolymers contained within the cell. The high information content of Raman spectra can be used to characterize the distribution of multiple cellular components, and to study the dynamics of subcellular reactions, with excellent spatial resolution. This review highlights recent developments in Raman microspectroscopy, with a focus on non-invasive biochemical analysis of single living cells.

Early spectral changes of cellular malignant transformation using Fourier transform infrared microspectroscopy

Fourier transform infrared microspectroscopy (FTIR-MSP) is potentially a powerful analytical method for identifying the spectral properties of biological activity in cells. The goal of the present research is the implementation of FTIR-MSP to study early spectral changes accompanying malignant transformation of cells. As a model system, cells in culture are infected by the murine sarcoma virus (MuSV), which induces malignant transformation. The spectral measurements are taken at various postinfection time intervals. To follow up systematically the progress of the spectral changes at early stages of cell transformation, it is essential first to determine and validate consistent and significant spectral parameters (biomarkers), which can evidently discriminate between normal and cancerous cells. Early stages of cell transformation are classified by an array of spectral biomarkers utilizing cluster analysis and discriminant classification function techniques. The classifications indicate that the first spectral changes are detectable much earlier than the first morphological signs of cell transformation. Our results point out that the first spectral signs of malignant transformation are observed on the first and third day of postinfection (PI) (for NIH/3T3 and MEF cell cultures, respectively), while the first visible morphological alterations are observed only on the third and seventh day, respectively. These results strongly support the potential of developing FTIR microspectroscopy as a simple, reagent-free method for early detection of malignancy.