Monitoring alterations of all-trans-retinal in human brain cancer cells by label-free confocal Raman imaging: regulation of the redox status of cytochrome c

This article has shown the impact of all-trans-retinal on human brain cancer, which is apparent in the shifts in the redox status of cytochrome c in a single cell. The connection between cytochrome c expression and its role in cancer development remains relatively unexplored. To assess this, we employed Raman spectroscopy and imaging to determine the redox state of the iron ion in cytochrome c across different cellular locations, including mitochondria, cytoplasm, lipid droplets, and the endoplasmic reticulum within human brain cancer cells. We have analyzed normal human astrocytes (NHA) and two brain cancer cell lines (astrocytoma - CRL-1718 and glioblastoma - U-87 MG) without and supplemented with all-trans-retinal. Our results confirmed that human brain cancer cells demonstrate varying redox status compared to normal cells based on the established correlation between the intensity of the cytochrome c Raman band at 1583 cm-1 and the malignancy grade of brain cancer cells. Our research unveiled that all-trans-retinal induces remarkable changes in the mitochondrial functional activity (redox status) of cancer cells, which were measured by confocal Raman spectroscopy and imaging.

Exploring the cellular antioxidant mechanism against cytotoxic silver nanoparticles: a Raman spectroscopic analysis

Silver nanoparticles (AgNPs) hold great promise for several different applications, from colorimetric sensors to antimicrobial agents. Despite their widespread incorporation in consumer products, limited understanding of the detrimental effects and cellular antioxidant responses associated with AgNPs at sublethal concentrations persists, raising concerns for human and ecological well-being. To address this gap, we synthesized AgNPs of varying sizes and evaluated their cytotoxicity against human dermal fibroblasts (HDF). Our study revealed that toxicity of AgNPs is a time- and size-dependent process, even at low exposure levels. AgNPs exhibited low short-term cytotoxicity but high long-term impact, particularly for the smallest NPs tested. Raman microspectroscopy was employed for in-time investigations of intracellular molecular variations during the first 24 h of exposure to AgNPs of 35 nm. Subtle protein and lipid degradations were detected, but no discernible damage to the DNA was observed. Signals associated with antioxidant proteins, such as superoxide dismutase (SOD), catalase (CAT) and metallothioneins (MTs), increased over time, reflecting the heightened production of these defense agents. Fluorescence microscopy further confirmed the efficacy of overexpressed antioxidant proteins in mitigating ROS formation during short-term exposure to AgNPs. This work provides valuable insights into the molecular changes and remedial strategies within the cellular environment, utilizing Raman microspectroscopy as an advanced analytical technique. These findings offer a novel perspective on the cytotoxicity mechanism of AgNPs, contributing to the development of safer materials and advice on regulatory guidelines for their biomedical applications.

Phenotype Identification of HeLa Cells Knockout CDK6 Gene Based on Label-Free Raman Imaging

Identifying cell phenotypes is essential for understanding the function of biological macromolecules and molecular biology. We developed a noninvasive, label-free, single-cell Raman imaging analysis platform to distinguish between the cell phenotypes of the HeLa cell wild type (WT) and cyclin-dependent kinase 6 (CDK6) gene knockout (KO) type. Via large-scale Raman spectral and imaging analysis, two phenotypes of the HeLa cells were distinguished by their intrinsic biochemical profiles. A significant difference was found between the two cell lines: large lipid droplets formed in the knockout HeLa cells but were not observed in the WT cells, which was confirmed by Oil Red O staining. The band ratio of the Raman spectrum of saturated/unsaturated fatty acids was identified as the Raman spectral marker for HeLa cell WT or gene knockout type differentiation. The interaction between organelles involved in lipid metabolism was revealed by Raman imaging and Lorentz fitting, where the distribution intensity of the mitochondria and the endoplasmic reticulum membrane decreased. At the same time, lysosomes increased after the CDK6 gene knockout. The parameters obtained from Raman spectroscopy are based on hierarchical cluster analysis and one-way ANOVA, enabling highly accurate cell classification.

Evaluation of Label-Free Confocal Raman Microspectroscopy for Monitoring Oxidative Stress In Vitro in Live Human Cancer Cells

Understanding the impact of free radicals and antioxidants in cell biology is vital; however, noninvasive nonperturbative imaging of oxidative stress remains a challenge. Here, we evaluated the ability of label-free Raman spectroscopy to monitor redox biochemical changes in antioxidant (N-acetyl-l-cysteine, NAC) and pro-oxidant (tert-butyl hydroperoxide, TBHP) environments. Cellular changes were compared to fluorescence microscopy using CellROX Orange as a marker of oxidative stress. We also investigated the influence of cell media with and without serum. Incubation of cells with NAC increased the Raman signal at 498 cm-1 from S-S disulphide stretching mode, one of the most important redox-related sensors. Exposure of cells to TBHP resulted in decreased Raman spectral signals from DNA/proteins and lipids (at 784, 1094, 1003, 1606, 1658 and 718, 1264, 1301, 1440, 1746 cm-1). Using partial least squares-discriminant analysis, we showed that Raman spectroscopy can achieve sensitivity up to 96.7%, 94.8% and 91.6% for control, NAC and TBHP conditions, respectively, with specificity of up to 93.5, 90.1% and 87.9%. Our results indicate that Raman spectroscopy can directly measure the effect of NAC antioxidants and accurately characterize the intracellular conditions associated with TBHP-induced oxidative stress, including lipid peroxidation and DNA damage.

Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra

Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.

Molecular imaging of extracellular vesicles in vitro via Raman metabolic labelling

Extracellular vesicles (EVs) are biologically-derived nanovectors important for intercellular communication and trafficking. As such, EVs show great promise as disease biomarkers and therapeutic drug delivery vehicles. However, despite the rapidly growing interest in EVs, understanding of the biological mechanisms that govern their biogenesis, secretion, and uptake remains poor. Advances in this field have been hampered by both the complex biological origins of EVs, which make them difficult to isolate and identify, and a lack of suitable imaging techniques to properly study their diverse biological roles. Here, we present a new strategy for simultaneous quantitative in vitro imaging and molecular characterisation of EVs in 2D and 3D based on Raman spectroscopy and metabolic labelling. Deuterium, in the form of deuterium oxide (D2O), deuterated choline chloride (d-Chol), or deuterated d-glucose (d-Gluc), is metabolically incorporated into EVs through the growth of parent cells on medium containing one of these compounds. Isolated EVs are thus labelled with deuterium, which acts as a bio-orthogonal Raman-active tag for direct Raman identification of EVs when introduced to unlabelled cell cultures. Metabolic deuterium incorporation demonstrates no apparent adverse effects on EV secretion, marker expression, morphology, or global composition, indicating its capacity for minimally obstructive EV labelling. As such, our metabolic labelling strategy could provide integral insights into EV biocomposition and trafficking. This approach has the potential to enable a deeper understanding of many of the biological mechanisms underpinning EVs, with profound implications for the design of EVs as therapeutic delivery vectors and applications as disease biomarkers.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives

This comprehensive review article discusses current and future perspectives of Raman spectroscopy-based analyses of cell therapy processes and products.

Developing Fully Automated Quality Control Methods for Preprocessing Raman Spectra of Biomedical and Biological Samples

Spectral preprocessing is frequently required to render Raman spectra useful for further processing and analyses. The various preprocessing steps, individually and sequentially, are increasingly being automated to cope with large volumes of data from, for example, hyperspectral imaging studies. Full automation of preprocessing is especially desirable when it produces consistent results and requires minimal user input. It is therefore essential to evaluate the "quality" of such preprocessed spectra. However, relatively few methods exist to evaluate preprocessing quality, and fully automated methods for doing so are virtually non-existent. Here we provide a brief overview of fully automated spectral preprocessing and fully automated quality assessment of preprocessed spectra. We follow this with the introduction of fully automated methods to establish figures-of-merit that encapsulate preprocessing quality. By way of illustration, these quantitative methods are applied to simulated and real Raman spectra. Quality factor and quality parameter figures-of-merit resulting from individual preprocessing step quality tests, as well as overall figures-of-merit, were found to be consistent with the quality of preprocessed spectra.

Controlled drug release with surface-capped mesoporous silica nanoparticles and its label-free in situ Raman monitoring

Mesoporous silica nanoparticles (MSNs) have drawn attention as efficient nanocarriers for drug delivery systems owing to their unique physiochemical properties. However, systemically controlling the kinetics of drug release from the nanocarriers and in situ monitoring of the drug release are still challenging. Here, we report surface-capped MSNs used for controlled drug release and demonstrate label-free in situ Raman monitoring of released drugs based on the molecule-specific spectral fingerprints. By capping the surface of MSNs with amine moieties, gold nanoparticles, and albumin, we achieved high loading efficiencies (up to 97%) of doxorubicin and precisely controlled drug release stimulated by changing pH value. Moreover, we monitored in real-time drug release profile and visualized cellular distribution of the delivered drug at nanoscale based on its intrinsic Raman peak. Finally, we evaluated drug responses in cancer cells and normal cells to investigate whether capped-dMSNs exhibit selective drug release. Our findings would be beneficial for designing smart drug carriers and directly monitoring the release behavior of drugs in actual cellular environments.

Histological coherent Raman imaging: a prognostic review

Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free imaging modality with sub-cellular spatial resolution and molecule-specific contrast possesses characteristics which could support the qualitative-to-quantitative transition of histopathology. In this work we briefly survey major themes related to modernization of histopathology, review applications of CRI to histopathology and, finally, discuss potential roles for CRI in the transformation of histopathology that is already underway.

Label-free Detection for a DNA Methylation Assay Using Raman Spectroscopy

Background:

DNA methylation has been suggested as a biomarker for early cancer detection and treatment. Varieties of technologies for detecting DNA methylation have been developed, but they are not sufficiently sensitive for use in diagnostic devices. The aim of this study was to determine the suitability of Raman spectroscopy for label-free detection of methylated DNA.

Methods:

The methylated promoter regions of cancer-related genes cadherin 1 (CDH1) and retinoic acid receptor beta (RARB) served as target DNA sequences. Based on bisulfite conversion, oligonucleotides of methylated or nonmethylated probes and targets were synthesized for the DNA methylation assay. Principal component analysis with linear discriminant analysis (PCA-DA) was used to discriminate the hybridization between probes and targets (methylated probe and methylated target or nonmethylated probe and nonmethylated target) of CDH1 and RARB from nonhybridization between the probe and targets (methylated probe and nonmethylated target or nonmethylated probe and methylated target).

Results:

This study revealed that the CDH1 and RARB oligo sets and their hybridization data could be classified using PCA-DA. The classification results for CDH1 methylated probe + CDH1 methylated target versus CDH1 methylated probe + CDH1 unmethylated target showed sensitivity, specificity, and error rates of 92%, 100%, and 8%, respectively. The classification results for the RARB methylated probe + RARB methylated target versus RARB methylated probe + RARB unmethylated target showed sensitivity, specificity, and error rates of 92%, 93%, and 11%, respectively.

Conclusions:

Label-free detection of DNA methylation could be achieved using Raman spectroscopy with discriminant analysis.

Empirical Factors Affecting the Quality of Non-Negative Matrix Factorization of Mammalian Cell Raman Spectra

Mammalian cells contain various macromolecules that can be investigated non-invasively with Raman spectroscopy. The particular mixture of major macromolecules present in a cell being probed are reflected in the measured Raman spectra. Determining macromolecular identities and estimating their concentrations from these mixture Raman spectra can distinguish cell types and otherwise enable biological research. However, the application of canonical multivariate methods, such as principal component analysis (PCA), to perform spectral unmixing yields mathematical solutions that can be difficult to interpret. Non-negative matrix factorization (NNMF) improves the interpretability of unmixed macromolecular components, but can be difficult to apply because ambiguities produced by overlapping Raman bands permit multiple solutions. Furthermore, theoretically sound methods can be difficult to implement in practice. Here we examined the effects of a number of empirical approaches on the quality of NNMF results. These approaches were evaluated on simulated mammalian cell Raman hyperspectra and the results were used to develop an enhanced procedure for implementing NNMF. We demonstrated the utility of this procedure using a Raman hyperspectral data set measured from human islet cells to recover the spectra of insulin and glucagon. This was compared to the relatively inferior PCA of these data.

Label-free live cell imaging by Confocal Raman Microscopy identifies CHO host and producer cell lines

As a possible viable and non-invasive method to identify high producing cells, Confocal Raman Microscopy was shown to be able to differentiate CHO host cell lines and derivative production clones. Cluster analysis of spectra and their derivatives was able to differentiate between different producer cell lines and a host, and also distinguished between an intracellular region of high lipid and protein content that in structure resembles the Endoplasmic Reticulum. This ability to identify the ER may be a major contributor to the identification of high producers. PCA enabled the discrimination even of host cell lines and their subclones with inherently higher production capacity. The method is thus a promising option that may contribute to early, non-invasive identification of high potential candidates during cell line development and possibly could also be used for proof of identity of established production clones.

Molecular imaging with CARS micro-spectroscopy

After more than a decade of instrument and method development, broadband coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy is beginning to live up to its potential as a label-free imaging modality that can rapidly generate high resolution images with full vibrational spectra at each image pixel. Presently these instruments are able to obtain quantitative, spatially resolved information on lipids from the CH stretch region of the Raman spectrum, and some instrument designs facilitate acquisition of high quality fingerprint spectra, containing information on a host of molecular species including structural proteins, nucleotides, and metabolites. While most of the existing instruments are research projects themselves, it appears that the relevant technologies are maturing so that commercially available instruments may not be too far in the future, making this remarkable imaging modality widely available.

Resonance Raman Probes for Organelle-Specific Labeling in Live Cells

Raman microspectroscopy provides for high-resolution non-invasive molecular analysis of biological samples and has a breakthrough potential for dissection of cellular molecular composition at a single organelle level. However, the potential of Raman microspectroscopy can be fully realized only when novel types of molecular probes distinguishable in the Raman spectroscopy modality are developed for labeling of specific cellular domains to guide spectrochemical spatial imaging. Here we report on the design of a next generation Raman probe, based on BlackBerry Quencher 650 compound, which provides unprecedentedly high signal intensity through the Resonance Raman (RR) enhancement mechanism. Remarkably, RR enhancement occurs with low-toxic red light, which is close to maximum transparency in the biological optical window. The utility of proposed RR probes was validated for targeting lysosomes in live cultured cells, which enabled identification and subsequent monitoring of dynamic changes in this organelle by Raman imaging.

Raman microscopy for cellular investigations--From single cell imaging to drug carrier uptake visualization

Progress in advanced therapeutic concepts requires the development of appropriate carrier systems for intracellular drug delivery. Consequently, analysis of interaction between carriers, drugs and cells as well as their uptake and intracellular fate is a current focus of research interest. In this context, Raman spectroscopy recently became an emerging analytical technique, due to its non-destructive, chemically selective and label-free working principle. In this review, we briefly present the state-of-the-art technologies for cell visualization and drug internalization. Against this background, Raman microscopy is introduced as a versatile analytical technique. An overview of various Raman spectroscopy investigations in this field is given including interactions of cells with drug molecules, carrier systems and other nanomaterials. Further, Raman instrumentations and sample preparation methods are discussed. Finally, as the analytical limit is not reached yet, a future perspective for Raman microscopy in pharmaceutical and biomedical research on the single cell level is given.

Identifying the lineages of individual cells in cocultures by multivariate analysis of Raman spectra

The cellular and matrix cues that induce stem cell differentiation into distinct cell lineages must be identified to permit the ex vivo expansion of desired cell populations for clinical applications. Combinatorial biomaterials enable screening multiple different microenvironments while using small numbers of rare stem cells. New methods to identify the phenotypes of individual cells in cocultures with location specificity would increase the efficiency and throughput of these screening platforms. Here, we demonstrate that partial least-squares discriminant analysis (PLS-DA) models of calibration Raman spectra from cells in pure cultures can be used to identify the lineages of individual cells in more complex culture environments. The calibration Raman spectra were collected from individual cells of four different lineages, and a PLS-DA model that captured the Raman spectral profiles characteristic of each cell line was created. The application of these models to Raman spectra from test sets of cells indicated individual, fixed and living cells in separate monocultures, as well as those in more complex culture environments, such as cocultures, could be identified with low error. Cells from populations with very similar biochemistries could also be identified with high accuracy. We show that these identifications are based on reproducible cell-related spectral features, and not spectral contributions from the culture environment. This work demonstrates that PLS-DA of Raman spectra acquired from pure monocultures provides an objective, noninvasive, and label-free approach for accurately identifying the lineages of individual, living cells in more complex coculture environments.

Development and integration of block operations for data invariant automation of digital preprocessing and analysis of biological and biomedical Raman spectra

High-throughput information extraction from large numbers of Raman spectra is becoming an increasingly taxing problem due to the proliferation of new applications enabled using advances in instrumentation. Fortunately, in many of these applications, the entire process can be automated, yielding reproducibly good results with significant time and cost savings. Information extraction consists of two stages, preprocessing and analysis. We focus here on the preprocessing stage, which typically involves several steps, such as calibration, background subtraction, baseline flattening, artifact removal, smoothing, and so on, before the resulting spectra can be further analyzed. Because the results of some of these steps can affect the performance of subsequent ones, attention must be given to the sequencing of steps, the compatibility of these sequences, and the propensity of each step to generate spectral distortions. We outline here important considerations to effect full automation of Raman spectral preprocessing: what is considered full automation; putative general principles to effect full automation; the proper sequencing of processing and analysis steps; conflicts and circularities arising from sequencing; and the need for, and approaches to, preprocessing quality control. These considerations are discussed and illustrated with biological and biomedical examples reflecting both successful and faulty preprocessing.

Advantages and limitations of Raman spectroscopy for molecular diagnostics: an update

Over the last decade, Raman spectroscopy has gained more and more interest in research as well as in clinical laboratories. As a vibrational spectroscopy technique, it is complementary to the also well-established infrared spectroscopy. Through specific spectral patterns, substances can be identified and molecular changes can be observed with high specificity. Because of a high spatial resolution due to an excitation wavelength in the visible and near-infrared range, Raman spectroscopy combined with microscopy is very powerful for imaging biological samples. Individual cells can be imaged on the subcellular level. In vivo tissue examinations are becoming increasingly important for clinical applications. In this review, we present currently ongoing research in different fields of medical diagnostics involving linear Raman spectroscopy and imaging. We give a wide overview over applications for the detection of atherosclerosis, cancer, inflammatory diseases and pharmacology, with a focus on developments over the past 5 years. Conclusions drawn from Raman spectroscopy are often validated by standard methods, for example, histopathology or PCR. The future potential of Raman spectroscopy and its limitations are discussed in consideration of other non-linear Raman techniques.

Rare earths exposure and male infertility: the injury mechanism study of rare earths on male mice and human sperm

The weight; testis/body coefficient; levels of LDH, SDH, SODH, G-6PD, and testosterone; cell cycle; and cell apoptosis of the male mice were influenced after being treated with 200 mg/[kg/day] of rare earths suspension for 3 weeks. The "Raman fingerprints" of the human sperm DNA exposed to 0.040 mg/ml CeCl3 were very different from those of the untreated; the Raman bands at 789 cm(-1) (backbone phosphodiester), PO4 backbone at 1,094 cm(-1), methylene deformation mode at 1,221 cm(-1), methylene deformation mode at 1,485 cm(-1), and amide II at 1,612 cm(-1), of which intensities and shifts were changed, might be the diagnostic biomarkers or potential therapeutic targets. The injury mechanism might be that the rare earths influence the oxidative stress and blood testosterone barrier, tangle the big biomolecule concurrently, which might cause the testicular cells and vascular system disorder and/or dysfunction, and at the same time change the physical and chemical properties of the sperm directly.

Cellular discrimination using in vitro Raman micro spectroscopy: the role of the nucleolus

Raman micro spectroscopy is employed to discriminate between cell lines. Results show the importance of the nuclear sub-cellular organelle, the nucleoli, to differentiate between cancer cell lines with high specificity and sensitivity.

Antioxidative protective effect of icariin on the FeSO4/H 2O 2-damaged human sperm based on confocal raman micro-spectroscopy

Oxidative stress is implicated in male infertility and significantly higher reactive oxygen species are detected in 25% of infertile males. Although different agents of various alternative medicines, including traditional Chinese medicine, have been tried with varying success, evidence remains limited on whether and how much herbs or supplements might help increase the anti-oxidant ability of the sperm. This study examined the anti-oxidative effects of icariin, a flavonoid isolated from Herba Epimedii, on the human sperm. We prepared the FeSO4/H2O2-damaged human sperms, which were co-cultured with icariin in vitro, and then observed the changes of the sperm by employing Raman micro-spectroscopy. The results showed that Raman mapping with a 514 nm excitation laser allowed clear differentiation of the nucleus, neck, and, in particular, the mitochondria-rich middle piece of a human sperm cell. The effect of icariin on different organelles of the sperm was quantified by localized spectral Raman signatures obtained within milli-seconds, and icariin could keep the "Raman fingerprint" of the human sperm the same as the control groups, suggesting that icariin could protect the human sperm from being damaged by FeSO4/H2O2. Icariin may serve as a tonifying and replenishing agent of herbal origin for enhancing reproductive functions.

Confocal mirco-Raman spectroscopic analysis of the antioxidant protection mechanism of the oligosaccharides extracted from Morinda officinalis on human sperm DNA

ETHNOPHARMACOLOGICAL RELEVENCE

Male infertility is a stressful and frustrating problem for the society, but a number of male infertility treatments are available as traditional Chinese medicine strategies which have been tried with variable success, while evidence is still limited on whether-or how much-herbs or supplements might help increase fertility, so the aim of this study was to investigate if the oligosaccharides extracted from Morinda officialis, a Chinese herb, is the active constituents to the fertility.

MATERIALS AND METHODS

In this study, we prepared the H2O2-demaged human sperm, cocultured with the oligosaccharides in vitro, then observed the changes of the DNA using confocal micro-Raman spectroscopy, and comparative analysis the differences of the spectra of different treated groups.

RESULTS

The results showed that the oligosaccharides extracted from Morinda officialis can keep the "Raman fingerprints" of the human sperm DNA almost the same as those of the control groups, but very different from the H2O2-induced groups, especially the intensity of bands at 787, 993, 1094, 1254, 1340, 1376, 1421, 1443, 1487, 1577 and 1662cm(-1) which could be as potential targets for the drugs finding, and further principal component analysis was successfully used to classify the Raman spectra of normal control and model groups.

CONCLUSION

This results suggested that the oligosaccharides can protect the DNA of human sperm from being damaged by H2O2, and which was one of the active constituents of Morinda officialis on treating infertility. It was also demonstrated that Morinda officialis as a tonifying and replenishing natural herb medicine can be used to enhance reproductive functions, and the Raman spectroscopy could be an applicable technology for screening active components in vitro from herbs.

Monitoring UVR induced damage in single cells and isolated nuclei using SR-FTIR microspectroscopy and 3D confocal Raman imaging

Melanocytes exposed to artificial sunlight and analysed with FTIR and Raman spectroscopy show changes in DNA bands and evidence of lipid accumulation.

Differentiation of cancer cells in two-dimensional and three-dimensional breast cancer models by Raman spectroscopy

We demonstrate the first application of Raman spectroscopy in diagnosing nonmalignant, premalignant, malignant, and metastatic stages of breast cancer in a three-dimensional (3-D) cell culture model that closely mimics an in vivo environment. Comprehensive study comparing classification in two-dimensional (2-D) and 3-D cell models was performed using statistical methods composed of principal component analysis for exploratory analysis and outlier removal, partial least squares discriminant analysis, and elastic net regularized regression for classification. Our results show that Raman spectroscopy with an appropriate classification tool has excellent resolution to discriminate the four stages of breast cancer progression, with a near 100% accuracy for both 2-D and 3-D cell models. The diversity in chemical groups related to nucleic acids, proteins, and lipids, among other chemicals, were identified by appropriate peaks in the Raman spectra that correspond to the correct classification of the different stages of tumorigenesis model comprising of MCF10A, MCF10AneoT, MCF10CA1h, and MCF10CA1a cell lines. An explicit relationship between wavenumber and the stages of cancer progression was identified by the elastic net variable selection.