Label-Free Raman Spectroscopic Imaging Monitors the Integral Physiologically Relevant Drug Responses in Cancer Cells

Assessing endothelial cytotoxicity induced by tyrosine kinase inhibitors: insights from Raman and fluorescence imaging

Since their approval, tyrosine kinase inhibitors (TKIs) have been widely used in antitumor therapy for chronic myeloblastic leukemia. Despite being approved by the FDA in 2001 to treat a rare cancer called chronic myeloid leukemia (CML), imatinib and other TKIs remain subjects of research for several reasons, such as their long-term effects, resistance, or molecular mechanisms. This study uses Raman and fluorescence imaging to investigate the in vitro cytotoxic effects of two TKIs, imatinib and dasatinib, on human aortic endothelial cells (HAECs). A comprehensive range of concentrations for these TKIs was applied to assess their cytotoxic impact based on viability, inflammation, and biochemical profile. Detailed data analysis revealed alterations in the biochemical profiles of cellular components, even though the viability of HAECs was around 80-90%. These changes indicate that, despite the cells retaining viability, they are experiencing considerable sub-lethal stress. Specifically, cells exposed to clinically relevant TKI concentrations showed increased signals from proteins and saturated lipids alongside decreased signals from nucleic acids, cytochromes, and unsaturated lipids. The subcellular analysis highlighted prominent changes in the perinuclear area, dominated by the endoplasmic reticulum and the cytoplasm. These findings suggest that TKIs are cytotoxic to vascular endothelium at concentrations close to those that are clinically observed. The predominant mechanism appears to involve oxidative stress-mediated inflammation, as evidenced by increased lipid content in treated cells and ICAM-1 staining. This cytotoxicity may contribute to the cardiotoxic effects observed during TKI therapy.

Raman imaging for monitoring deuterated squalene-gemcitabine nanomedicines in single living breast cancer cells

We have investigated the impact of gemcitabine (Gem) and deuterated gemcitabine-squalene (GemSQ-d6) nanoparticles (NPs) on MCF7 and MDA-MB-231 breast cancer cell lines by Raman spectroscopy. Quantification of LDL expression levels in both cell lines revealed a four-fold increase in MDA-MB-231 cells compared to MCF7 cells. In in vitro antitumor assessments, Gem displayed 13.5 times more effectiveness than GemSQ NPs against MCF7 cells, whereas GemSQ NPs induced a 14-fold increase in cytotoxicity compared to Gem for MDA-MB-231 cells. Oil Red O staining revealed that the treatment with GemSQ-d6 NPs induced a higher accumulation of lipid droplets at the periphery of the nucleus in MDA-MB-231 cells compared to MCF7 cells. Raman spectroscopy was employed to assess the impact of these drugs (50 µM, 24 hrs) on these breast cancer cell lines. By using the silent region (2000-2400 cm-1), we demonstrated that the accumulation of the GemSQ-d6 bioconjugate was higher in the cytoplasm of MDA-MB-231 cells than in MCF7 cells. This difference in drug accumulation is likely correlated with their expression levels of low-density lipoprotein receptors (LDLR). However, no information was obtained on Gem in this spectral region. We identified Raman features of squalene (SQ) in 700-1800 cm-1 fingerprint region that allowed us to observe almost the same distribution of GemSQ as that observed in the silent region for both cell lines treated with GemSQ-d6 or SQ-d6. Subsequently, the effects of Gem and GemSQ-d6 on cellular components such as proteins, nucleic acids, and cytochrome C were monitored within the fingerprint spectral region. Our results revealed distinct features in the subcellular accumulation of these biomolecules in response to Gem and GemSQ treatments.

Machine-learning-guided quantitative delineation of cell morphological features and responses to nanomaterials

Delineation of cell morphological features is essential to decipher cell responses to external stimuli like theranostic nanomaterials. Conventional methods rely on labeled approaches, such as fluorescence imaging and flow cytometry, to assess cell responses. Besides potentially perturbing cell structure and morphology, these approaches are relatively complex, time-consuming, expensive, and may not be compatible with downstream analysis involving live cells. Herein, leveraging label-free phase-contrast or brightfield microscopy imaging and machine learning, the delineation of different cell types, phenotypes, and states for monitoring live cell responses is reported. Notably, pixel classification based on a supervised random forest classifier is used to distinguish between cells and backgrounds from the microscopy images, followed by cell segmentation and morphological feature extraction. Quantitative analysis shows that most of the compared cell groups have distinguishable size and shape features. Principal component analysis and unsupervised k-means clustering of morphological features reveal the possible existence of heterogenous cell subpopulations and treatment responses among the seemingly homogenous cell groups. This shows the merit of the reported approach in complementing conventional techniques for cell analysis. It is anticipated that the demonstrated method will further aid the implementation of machine learning to streamline the analysis of cell morphology and responses for early disease diagnosis and treatment response monitoring.

Lipid metabolism reprogramming in renal cell carcinomas

This study investigates the intricate mechanisms underlying the correlation between elevated consumption of harmful fats and the onset of kidney malignancies. The rise in global obesity rates has been accompanied by an increased prevalence of renal cancers, prompting an exploration into the molecular pathways and biological processes linking these phenomena. Through an extensive review of current literature and clinical studies, we identify potential key factors contributing to the carcinogenic influence of harmful fats on renal tissues. Our analysis highlights the role of adipose tissue-derived factors, inflammatory mediators, and lipid metabolism dysregulation in fostering a microenvironment conducive to renal tumorigenesis. Furthermore, we delve into the impact of harmful fats on signaling pathways associated with cell proliferation, apoptosis evasion, and angiogenesis within the renal parenchyma. This review underscores the importance of elucidating the molecular intricacies linking lipid metabolism and kidney malignancies, offering a foundation for future research and the development of targeted preventive and therapeutic interventions. The findings discussed herein contribute to our understanding of the complex relationship between lipid mediators and renal cancer, providing a basis for public health strategies aimed at mitigating the impact of harmful fats on kidney health.

Activation of epidermal growth factor receptors in triple-negative breast cancer cells by morphine; analysis through Raman spectroscopy and machine learning

Triple negative breast cancer (TNBC) is a very aggressive form of breast cancer, and the analgesic drug morphine has been shown to promote the proliferation of TNBC cells. This article investigates whether morphine causes activation of epidermal growth factor receptors (EGFR), the roles of μ-opioid and EGFR receptors on TNBC cell proliferation and migration. While examining the changes with molecular techniques, we also aimed to investigate the analysis ability of Raman spectroscopy and machine learning-based approach. Effects of morphine on the proliferation and migration of MDA.MB.231 cells were evaluated by MTT and scratch wound-healing tests, respectively. Morphine-induced phosphorylation of the EGFR was analyzed by western blotting in the presence and absence of μ-receptor antagonist naltrexone and the EGFR-tyrosine kinase inhibitor gefitinib. Morphine-induced EGFR phosphorylation and cell migration were significantly inhibited by pretreatments with both naltrexone and gefitinib; however, morphine-increased cell proliferation was inhibited only by naltrexone. While morphine-induced changes were observed in the Raman scatterings of the cells, the inhibitory effect of naltrexone was analyzed with similarity to the control group. Principal component analysis (PCA) of the Raman confirmed the epidermal growth factor (EGF)-like effect of morphine and was inhibited by naltrexone and partly by gefitinib pretreatments. Our in vitro results suggest that combining morphine with an EGFR inhibitor or a peripherally acting opioidergic receptor antagonist may be a good strategy for pain relief without triggering cancer proliferation and migration in TNBC patients. In addition, our results demonstrated the feasibility of the Raman spectroscopy and machine learning-based approach as an effective method to investigate the effects of agents in cancer cells without the need for complex and time-consuming sample preparation. The support vector machine (SVM) with linear kernel automatically classified the effects of drugs on cancer cells with ∼95% accuracy.

Dysregulation of cellular membrane homeostasis as a crucial modulator of cancer risk

Cellular membranes serve as an epicentre combining extracellular and cytosolic components with membranous effectors, which together support numerous fundamental cellular signalling pathways that mediate biological responses. To execute their functions, membrane proteins, lipids and carbohydrates arrange, in a highly coordinated manner, into well-defined assemblies displaying diverse biological and biophysical characteristics that modulate several signalling events. The loss of membrane homeostasis can trigger oncogenic signalling. More recently, it has been documented that select membrane active dietaries (MADs) can reshape biological membranes and subsequently decrease cancer risk. In this review, we emphasize the significance of membrane domain structure, organization and their signalling functionalities as well as how loss of membrane homeostasis can steer aberrant signalling. Moreover, we describe in detail the complexities associated with the examination of these membrane domains and their association with cancer. Finally, we summarize the current literature on MADs and their effects on cellular membranes, including various mechanisms of dietary chemoprevention/interception and the functional links between nutritional bioactives, membrane homeostasis and cancer biology.

Efficacy of tyrosine kinase inhibitors examined by a combination of Raman micro-spectroscopy and a deep wavelet scattering-based multivariate analysis framework

HER2 is a crucial therapeutic target in breast cancer, and the survival rate of breast cancer patients has increased because of this receptor's inhibition. However, tumors have shown resistance to this therapeutic strategy due to oncogenic mutations that decrease the binding of several HER2-targeted drugs, including lapatinib, and confer resistance to this drug. Neratinib can overcome this drug resistance and effectively inhibit HER2 signaling and tumor growth. In the present study, we examined the efficacy of lapatinib and neratinib using breast cancer cells by Raman microscopy combined with a deep wavelet scattering-based multivariate analysis framework. This approach discriminated between control cells and drug-treated cells with high accuracy, compared to classical principal component analysis. Both lapatinib and neratinib induced changes in the cellular biochemical composition. Furthermore, the Raman results were compared with the results of several in vitro assays. For instance, drug-treated cells exhibited (i) inhibition of ERK and AKT phosphorylation, (ii) inhibition of cellular proliferation, (iii) cell-cycle arrest, and (iv) apoptosis as indicated by western blotting, real-time cell analysis (RTCA), cell-cycle analysis, and apoptosis assays. Thus, the observed Raman spectral changes are attributed to cell-cycle arrest and apoptosis. The results also indicated that neratinib is more potent than lapatinib. Moreover, the uptake and distribution of lapatinib in cells were visualized through its label-free marker bands in the fingerprint region using Raman spectral imaging. These results show the prospects of Raman microscopy in drug evaluation and presumably in drug discovery.

Monitoring Metabolic Changes in Response to Chemotherapies in Cancer with Raman Spectroscopy and Metabolomics

Resistance to clinical therapies remains a major barrier in cancer management. There is a critical need for rapid and highly sensitive diagnostic tools that enable early prediction of treatment response to allow accurate clinical decisions. Here, Raman spectroscopy was employed to monitor changes in key metabolites as early predictors of response in KRAS-mutant colorectal cancer (CRC) cells, HCT116, treated with chemotherapies. We show at the single cell level that HCT116 is resistant to cetuximab (CTX), the first-line treatment in CRC, but this resistance can be overcome with pre-sensitization of cells with oxaliplatin (OX). In combination treatment of CTX + OX, sequential delivery of OX followed by CTX rather than simultaneous administration of drugs was observed to be critical for effective therapy. Our results demonstrated that metabolic changes are well aligned to cellular mechanical changes where Young's modulus decreased after effective treatment, indicating that both changes in mechanical properties and metabolism in cells are likely responsible for cancer proliferation. Raman findings were verified with mass spectrometry (MS) metabolomics, and both platforms showed changes in lipids, nucleic acids, and amino acids as predictors of resistance/response. Finally, key metabolic pathways enriched were identified when cells are resistant to CTX but downregulated with effective treatment. This study highlights that drug-induced metabolic changes both at the single cell level (Raman) and ensemble level (MS) have the potential to identify mechanisms of response to clinical cancer therapies.

Sub-Cellular Dynamic Analysis of BGC823 Cells after Treatment with the Multi-Component Drug CKI Using Raman Spectroscopy

Multi-component drugs (MCDs) can induce various cellular changes covering multiple levels, from molecular and subcellular structure to cell morphology. A "non-invasive" method for comprehensively detecting the dynamic changes of cellular fine structure and chemical components on the subcellular level is highly desirable for MCD studies. In this study, the subcellular dynamic processes of gastric cancer BGC823 cells after treatment with a multi-component drug, Compound Kushen Injection (CKI), were investigated using a homemade, high-resolution, confocal Raman spectroscopy (RS) device combined with bright-field imaging. The Raman spectra of the nucleus, cytoplasm and intracellular vesicles (0.4-1 μm) were collected simultaneously for each cell treated with CKI at different times and doses. The RS measurements showed that CKI decreased the DNA signatures, which the drug is known to inhibit. Meanwhile, the CKI-induced subcellular dynamic changes in the appearance of numerous intracellular vesicles and the deconstruction of cytoplasm components were observed and discussed. The results demonstrated that high-resolution subcellular micro-Raman spectroscopy has potential for detecting fine cellular dynamic variation induced by drugs and the screening of MCDs in cancer therapy.

Label-Free Vibrational and Quantitative Phase Microscopy Reveals Remarkable Pathogen-Induced Morphomolecular Divergence in Tumor-Derived Cells

Delineating the molecular and morphological changes that cancer cells undergo in response to extracellular stimuli is crucial for identifying factors that promote tumor progression. Label-free optical imaging offers a potentially promising route for retrieving such single-cell information by generating detailed visualization of the morphology and determining alterations in biomolecular composition. The potential of such nonperturbative morphomolecular microscopy for analyzing microbiota-cancer cell interactions has been surprisingly underappreciated, despite the growing evidence of the critical role of dysbiosis in malignant transformations. Here, using a model system of breast cancer cells, we show that label-free Raman microspectroscopy and quantitative phase microscopy can detect biomolecular and morphological changes in single cells exposed to Bacteroides fragilis toxin (BFT), a toxin secreted by enterotoxigenicB. fragilis. Remarkably, using machine learning to elucidate subtle, but consistent, cellular differences, we found that the morphomolecular differences between BFT-exposed and control breast cancer cells became more accentuated after in vivo passage, corroborating our findings that a short-term BFT exposure imparts a long-term effect on cancer cells and promotes a more invasive phenotype. Complementing more classical labeling techniques, our label-free platform offers a global detection approach with measurements representative of the overall cellular phenotype, paving the way for further investigations into the multifaceted interactions between the cancer cell and the microbiota.

Microenvironmental Factors Modulating Tumor Lipid Metabolism: Paving the Way to Better Antitumoral Therapy

Metabolic reprogramming is one of the emerging hallmarks of cancer and is driven by both the oncogenic mutations and challenging microenvironment. To satisfy the demands of energy and biomass for rapid proliferation, the metabolism of various nutrients in tumor cells undergoes important changes, among which the aberrant lipid metabolism has gained increasing attention in facilitating tumor development and metastasis in the past few years. Obstacles emerged in the aspect of application of targeting lipid metabolism for tumor therapy, due to lacking of comprehensive understanding on its regulating mechanism. Tumor cells closely interact with stromal niche, which highly contributes to metabolic rewiring of critical nutrients in cancer cells. This fact makes the impact of microenvironment on tumor lipid metabolism a topic of renewed interest. Abundant evidence has shown that many factors existing in the tumor microenvironment can rewire multiple signaling pathways and proteins involved in lipid metabolic pathways of cancer cells. Hence in this review, we summarized the recent progress on the understanding of microenvironmental factors regulating tumor lipid metabolism, and discuss the potential of modulating lipid metabolism as an anticancer approach.

Raman and quantitative phase imaging allow morpho-molecular recognition of malignancy and stages of B-cell acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is one of the most common malignancies that account for nearly one-third of all pediatric cancers. The current diagnostic assays are time-consuming, labor-intensive, and require expensive reagents. Here, we report a label-free approach featuring diffraction phase imaging and Raman microscopy that can retrieve both morphological and molecular attributes for label-free optical phenotyping of individual B cells. By investigating leukemia cell lines of early and late stages along with the healthy B cells, we show that phase images can capture subtle morphological differences among the healthy, early, and late stages of leukemic cells. By exploiting its biomolecular specificity, we demonstrate that Raman microscopy is capable of accurately identifying not only different stages of leukemia cells but also individual cell lines at each stage. Overall, our study provides a rationale for employing this hybrid modality to screen leukemia cells using the widefield QPI and using Raman microscopy for accurate differentiation of early and late-stage phenotypes. This contrast-free and rapid diagnostic tool exhibits great promise for clinical diagnosis and staging of leukemia in the near future.

Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing

Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.

Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential

Identification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging its molecular specificity, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also perform multivariate curve resolution alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

Coherent Raman Scattering Microscopy in Oncology Pharmacokinetic Research

The high attrition rates of anti-cancer drugs during clinical development remains a bottleneck problem in pharmaceutical industry. This is partially due to the lack of quantitative, selective, and rapid readouts of anti-cancer drug activity in situ with high resolution. Although fluorescence microscopy has been commonly used in oncology pharmacological research, fluorescent labels are often too large in size for small drug molecules, and thus may disturb the function or metabolism of these molecules. Such challenge can be overcome by coherent Raman scattering microscopy, which is capable of chemically selective, highly sensitive, high spatial resolution, and high-speed imaging, without the need of any labeling. Coherent Raman scattering microscopy has tremendously improved the understanding of pharmaceutical materials in the solid state, pharmacokinetics of anti-cancer drugs and nanocarriers in vitro and in vivo. This review focuses on the latest applications of coherent Raman scattering microscopy as a new emerging platform to facilitate oncology pharmacokinetic research.

Multivariate probing of antitumor metal-based complexes damage on living cells through Raman imaging

Intracellular modifications caused by two metal-based antitumor compounds were assessed by confocal Raman imaging assisted by multivariate curve resolution method, a very powerful deconvolution tool that can be used to extract the characteristic spectral profile of the individual or "purest" components from an image dataset. The use of this Raman methodology has the advantage of being non-invasive and totally label-free. Four main different intracellular processes were observed under the Raman imaging and multivariate approach combination, and even, significant differences could be identified between the treatments with both metallodrugs. Leakage of the nucleus and nucleolus content into the cytoplasm, along with releasing of cytochrome c were observed for the treatment with the Cu-based complex. At the same time, changes of hydrogen-bonding network were also evidenced, indicating an apoptotic cellular death process, consistent with complementary Total Reflection X-Ray fluorescence (TXRF) and fluorescence experiments attesting mitochondria and DNA as main targets after uptake of the complex by cells. For treatment with the Zn-based complex, changes associated with cytochrome c were not detected, neither a rapid leakage of nucleus content upon 24 h treatment. The hydrogen-bonding network also followed a quite different pattern, suggesting that with this metallodrug, the cellular death follows a different mechanism.

Confocal Raman microspectroscopic analysis on the time-dependent impact of DAPT, a γ-secretase inhibitor, to osteosarcoma cells

Confocal Raman microspectroscopy (CRM) analysis provides subcellular compositional and morphology related information. In this study, we used CRM in conjunction with multivariate statistical analysis to elucidate the time-dependent impact of the γ-secretase inhibitor, DAPT (N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester) of osteosarcoma (OS) cells. The interactions of DAPT (20 μM) with a murine OS cell line K7M2 at 24 and 48 h were monitored. The spectral characteristics of drug action were identified to illustrate the cellular compositional alterations, showing that DAPT induced apoptosis by reducing the protein, lipid and nucleic acid content and structural changes. Multivariate algorithms, principal component analysis (PCA) and linear discriminant analysis (LDA) revealed a clear separation among cells in the untreated control (UT), 24H (DAPT-treated for 24 h), and 48H (DAPT-treated for 48 h) groups, achieving sensitivities of 100%, 96%, 100% and specificities of 98%, 100%, 100%, respectively. After point-scanned spectral imaging, K-means clustering analysis (KCA) was further used to visualize sub-cellular morphological changes and the underlying spectral characteristics in a temporal sequence. Compared with the UT group, Raman imaging results exhibited gradually increased nuclear division of OS cells with DAPT treatment duration extension, along with changes in the physiology of other organelles within the cell. By providing a unique perspective for understanding the temporary cellular responses to DAPT at molecular level, the achieved results form the foundation of strategies for the application of CRM and other Raman-based techniques for studying the therapeutic responses of other anticancer agents in cancer model systems.

Detection and time-tracking activation of a photosensitiser on live single colorectal cancer cells using Raman spectroscopy

Raman spectroscopy has been used to observe uptake, metabolism and response of single-cells to drugs. Photodynamic therapy is based on the use of light, a photosensitiser and oxygen to destroy tumour tissue. Here, we used single-cell Raman spectroscopy to study the uptake and intracellular degradation of a novel photosensitiser with a diphenylacetylene structure, DC473, in live single-cells from colorectal adenocarcinoma cell lines SW480, HT29 and SW620. DC473 was seen to predominantly accumulate in lipid droplets, showing higher accumulation in HT29 and SW620 cells than in SW480 cells, with a broader DC473 peak shifted to higher wavenumbers. DC473 activation and effects were tracked on live single-cells for 5 minutes. Upon exposure to UV light, the DC473 signal intensity dropped, with remaining DC473 shifting towards higher wavenumbers and widening, with a lifetime of approximately 50 seconds. Morphologically, SW480 and SW620 cells showed changes upon photodynamic therapy, whereas HT29 cells showed no changes. Morphological changes correlated with higher remaining DC473 signal after UV exposure. Our research suggests that DC473 forms aggregates within the cells that disaggregate following activation, showing the potential of Raman spectroscopy for the study of time-dependent single-cell pharmacodynamics.

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

To explore the effect in nasopharyngeal carcinoma (NPC) cells after treatment with chemodrugs, Raman profiles were characterized by laser tweezer Raman spectroscopy. Two NPC cell lines (CNE2 and C666-1) were treated with gemcitabine, cisplatin, and paclitaxel, respectively. The high-quality Raman spectra of cells without or with treatments were recorded at the single-cell level with label-free laser tweezers Raman spectroscopy (LTRS) and analyzed for the differences of alterations of Raman profiles. Tentative assignments of Raman peaks indicated that the cellular specific biomolecular changes associated with drug treatment include changes in protein structure (e.g. 1655 cm^-1), changes in DNA/RNA content and structure (e.g. 830 cm^-1), destruction of DNA/RNA base pairs (e.g. 785 cm^-1), and reduction in lipids (e.g. 970 cm^-1). Besides, both principal components analysis (PCA) combined with linear discriminant analysis (LDA) and the classification and regression trees (CRT) algorithms were employed to further analyze and classify the spectral data between control group and treated group, with the best discriminant accuracy of 96.7% and 90.0% for CNE2 and C666-1 group treated with paclitaxel, respectively. This exploratory work demonstrated that LTRS technology combined with multivariate statistical analysis has promising potential to be a novel analytical strategy at the single-cell level for the evaluation of NPC-related chemotherapeutic drugs.

Raman Scattering: From Structural Biology to Medical Applications

This is a review of relevant Raman spectroscopy (RS) techniques and their use in structural biology, biophysics, cells, and tissues imaging towards development of various medical diagnostic tools, drug design, and other medical applications. Classical and contemporary structural studies of different water-soluble and membrane proteins, DNA, RNA, and their interactions and behavior in different systems were analyzed in terms of applicability of RS techniques and their complementarity to other corresponding methods. We show that RS is a powerful method that links the fundamental structural biology and its medical applications in cancer, cardiovascular, neurodegenerative, atherosclerotic, and other diseases. In particular, the key roles of RS in modern technologies of structure-based drug design are the detection and imaging of membrane protein microcrystals with the help of coherent anti-Stokes Raman scattering (CARS), which would help to further the development of protein structural crystallography and would result in a number of novel high-resolution structures of membrane proteins—drug targets; and, structural studies of photoactive membrane proteins (rhodopsins, photoreceptors, etc.) for the development of new optogenetic tools. Physical background and biomedical applications of spontaneous, stimulated, resonant, and surface- and tip-enhanced RS are also discussed. All of these techniques have been extensively developed during recent several decades. A number of interesting applications of CARS, resonant, and surface-enhanced Raman spectroscopy methods are also discussed.

Micro-Raman spectroscopy in medicine

A potential role of optical technologies in medicine including micro-Raman spectroscopy is diagnosis of bacteria, cells and tissues which is covered in this chapter. The main advantage of Raman-based methods to complement and augment diagnostic tools is that unsurpassed molecular specificity is achieved without labels and in a nondestructive way. Principles and applications of micro-Raman spectroscopy in the context of medicine will be described. First, Raman spectra of biomolecules representing proteins, nucleic acids, lipids and carbohydrates are introduced. Second, microbial applications are summarized with the focus on typing on species and strain level, detection of infections, antibiotic resistance and biofilms. Third, cytological applications are presented to classify single cells and study cell metabolism and drug–cell interaction. Fourth, applications to tissue characterization start with discussion of lateral resolution for Raman imaging followed by Raman-based detection of pathologies and combination with other modalities. Finally, an outlook is given to translate micro-Raman spectroscopy as a clinical tool to solve unmet needs in point-of-care applications and personalized treatment of diseases.

New perspectives for viability studies with high-content analysis Raman spectroscopy (HCA-RS)

Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.

Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping

Understanding the response of cancer cells to ionising radiation is a crucial step in modern radiotherapy. Raman microspectroscopy, together with Partial Least Squares Regression (PLSR) analysis has been shown to be a powerful tool for monitoring biochemical changes of irradiated cells on the subcellular level. However, to date, the majority of Raman studies have been performed using a single spectrum per cell, giving a limited view of the total biochemical response of the cell. In the current study, Raman mapping of the whole cell area was undertaken to ensure a more comprehensive understanding of the changes induced by X-ray radiation. On the basis of the collected Raman spectral maps, PLSR models were constructed to elucidate the time-dependent evolution of chemical changes induced in cells by irradiation, and the performance of PLSR models based on whole cell averages as compared to those based on average Raman spectra of cytoplasm and nuclear region. On the other hand, prediction of X-ray doses for individual cellular components showed that cytoplasmic and nuclear regions should be analysed separately. Finally, the advantage of the mapping technique over single point measurements was verified by a comparison of the corresponding PLSR models.

Omega 3-DHA and Delta-Tocotrienol Modulate Lipid Droplet Biogenesis and Lipophagy in Breast Cancer Cells: the Impact in Cancer Aggressiveness

Omega 3-docosahexaenoic acid (DHA) and vitamin E Delta-tocotrienol (Delta-T3) are extensively studied as protective nutrients against cancer development. Little is known about the biological mechanisms targeted by these bioactive molecules on lipid droplet (LD) biogenesis, an important breast cancer aggressiveness marker, and the occurrence of lipophagy in breast cancer cells. The aim of this study was to investigate the effect of DHA, Delta-T3 and DHA plus Delta-T3 co-treatment in LD biogenesis and lipophagy process in triple negative breast cancer cell line MDA-MB-231. Cells were treated with 50 μM DHA and/or 5 μM Delta-T3. Our results demonstrated that DHA can trigger an increase in LD biogenesis and co-treatment with Delta-T3 was able to reduce this LD biogenesis. In addition, we showed that a higher cytoplasmic LD content is associated with a higher breast cancer cells malignance and proliferation. Reduction of cytoplasmic LD content by silencing ADRP (adipose differentiation-related protein), a structural LD protein, also decreased cell proliferation in MDA-MB-231 cells. Treatment with DHA and Delta-T3 alone or co-treatment did not reduce cell viability. Moreover, we showed here that DHA can trigger lipophagy in MDA-MB-231 cells and DHA plus Delta-T3 co-treatment was able to enhance this lipophagy process. Our findings demonstrated that co-treatment with DHA plus Delta-T3 in MDA-MB-231 cells could reduce LD biogenesis and potentiate lipophagy in these cells, possibly having a positive impact to inhibit breast cancer malignancy. Therefore, suitable doses of DHA and Delta-T3 vitamin E isoform supplementation can be a prominent tool in therapeutic treatments against breast cancer.

Functional link between plasma membrane spatiotemporal dynamics, cancer biology, and dietary membrane-altering agents

The cell plasma membrane serves as a nexus integrating extra- and intracellular components, which together enable many of the fundamental cellular signaling processes that sustain life. In order to perform this key function, plasma membrane components assemble into well-defined domains exhibiting distinct biochemical and biophysical properties that modulate various signaling events. Dysregulation of these highly dynamic membrane domains can promote oncogenic signaling. Recently, it has been demonstrated that select membrane-targeted dietary bioactives (MTDBs) have the ability to remodel plasma membrane domains and subsequently reduce cancer risk. In this review, we focus on the importance of plasma membrane domain structural and signaling functionalities as well as how loss of membrane homeostasis can drive aberrant signaling. Additionally, we discuss the intricacies associated with the investigation of these membrane domain features and their associations with cancer biology. Lastly, we describe the current literature focusing on MTDBs, including mechanisms of chemoprevention and therapeutics in order to establish a functional link between these membrane-altering biomolecules, tuning of plasma membrane hierarchal organization, and their implications in cancer prevention.

High-content screening Raman spectroscopy (HCS-RS) of panitumumab-exposed colorectal cancer cells

Label-free screening for cancer cells exposed to monoclonal antibody-based drugs using HCS-RS.

HTS-FTIR spectroscopy allows the classification of polyphenols according to their differential effects on the MDA-MB-231 breast cancer cell line

Breast cancer is a major public health issue among women in the world. Meanwhile new anticancer treatments struggle more and more to be accepted in the pharmaceutical market and research costs still increase. There is therefore a need to find new treatments and new screening methods to test them more quickly and efficiently. Among natural compounds, an increasing interest has been given to polyphenols as they can take action at the different stages of carcinogenesis, from tumour initiation to metastasis formation, by disturbing multiple cellular signalling pathways. They constitute one of the largest groups of plant metabolites and more than 8000 compounds have already been identified based on their chemical structure. Traditionally in pharmacology, new anticancer drugs are first evaluated for their potential to inhibit the proliferation of cancer cell lines. Numerous potential drugs are discarded at this stage even though they could show interesting modes of action. In turn, there is an increasing demand for more systemic approaches in order to obtain a global and accurate insight into the biochemical processes mediated by drugs. Recently, FTIR spectroscopy was demonstrated to be an innovative tool to obtain a unique fingerprint of the effects of anticancer drugs on cells in culture. While this spectral technique appears to have a definite potential to sort drugs according to their spectral fingerprints, characteristic of the metabolic modifications induced, the present challenge remains to evaluate the drug-induced spectral changes in cancer cells on a larger scale. This article presents the results obtained for a 24 h-exposure of the breast cancer cell line MDA-MB-231 to 15 compounds belonging to different classes of polyphenols using FTIR spectroscopy connected to a high throughput screening extension. Through unsupervised and supervised statistical analyses (PCA, MANOVA, Student's t-tests and HCA), a distinction between polyphenol treatments and controls could be well established.

Raman micro-spectroscopy monitors acquired resistance to targeted cancer therapy at the cellular level

Monitoring the drug efficacy or resistance in vitro is usually carried out by measuring the response of single few proteins. However, observation of single proteins instead of an integral cell response may lead to results that are not consistent with patient’s response to a drug. We present a Raman spectroscopic method that detects the integral cell response to drugs such as tyrosine kinase inhibitors (TKIs). Non-small cell lung cancer (NSCLC) patients with EGFR mutations develop acquired resistance to first (erlotinib)- and third (osimertinib)-generation TKIs. Large erlotinib-induced differences were detected by Raman micro-spectroscopy in NSCLC cells without T790M EGFR mutation but not in cells with this mutation. Additionally, Raman difference spectra detected the response of NSCLC cells with T790M EGFR mutation to second- (neratinib) and third-generation (osimertinib) TKIs, and the resistance of cells with T790M/C797S EGFR mutation to osimertinib. Thus, the in vitro Raman results indicated that NSCLC cells with T790M and T790M/C797S EGFR mutations are resistant to erlotinib- and osimertinib, respectively, consistent with the observed responses of patients. This study shows the potential of Raman micro-spectroscopy to monitor drug resistance and opens a new door to in vitro companion diagnostics for screening personalized therapies.

Hierarchical deep convolutional neural networks combine spectral and spatial information for highly accurate Raman-microscopy-based cytopathology

Hierarchical variants of so-called deep convolutional neural networks (DCNNs) have facilitated breakthrough results for numerous pattern recognition tasks in recent years. We assess the potential of these novel whole-image classifiers for Raman-microscopy-based cytopathology. Conceptually, DCNNs facilitate a flexible combination of spectral and spatial information for classifying cellular images as healthy or cancer-affected cells. As we demonstrate, this conceptual advantage translates into practice, where DCNNs exceed the accuracy of both conventional classifiers based on pixel spectra as well as classifiers based on morphological features extracted from Raman microscopic images. Remarkably, accuracies exceeding those of all previously proposed classifiers are obtained while using only a small fraction of the spectral information provided by the dataset. Overall, our results indicate a high potential for DCNNs in medical applications of not just Raman, but also infrared microscopy.

Raman Microspectroscopic Evidence for the Metabolism of a Tyrosine Kinase Inhibitor, Neratinib, in Cancer Cells

Tyrosine kinase receptors are one of the main targets in cancer therapy. They play an essential role in the modulation of growth factor signaling and thereby inducing cell proliferation and growth. Tyrosine kinase inhibitors such as neratinib bind to EGFR and HER2 receptors and exhibit antitumor activity. However, little is known about their detailed cellular uptake and metabolism. Here, we report for the first time the intracellular spatial distribution and metabolism of neratinib in different cancer cells using label-free Raman imaging. Two new neratinib metabolites were detected and fluorescence imaging of the same cells indicate that neratinib accumulates in lysosomes. The results also suggest that both EGFR and HER2 follow the classical endosome lysosomal pathway for degradation. A combination of Raman microscopy, DFT calculations, and LC-MS was used to identify the chemical structure of neratinib metabolites. These results show the potential of Raman microscopy to study drug pharmacokinetics.

Towards quantitative molecular mapping of cells by Raman microscopy: using AFM for decoupling molecular concentration and cell topography

Raman micro-spectroscopy (RMS) is a non-invasive technique for imaging live cells in vitro. However, obtaining quantitative molecular information from Raman spectra is difficult because the intensity of a Raman band is proportional to the number of molecules in the sampled volume, which depends on the local molecular concentration and the thickness of the cell. In order to understand these effects, we combined RMS with atomic force microscopy (AFM), a technique that can measure accurately the thickness profile of the cells. Solution-based calibration models for RNA and albumin were developed to create quantitative maps of RNA and proteins in individual fixed cells. The maps were built by applying the solution-based calibration models, based on partial least squares fitting (PLS), on raster-scan Raman maps, after accounting for the local cell height obtained from the AFM. We found that concentrations of RNA in the cytoplasm of mouse neuroprogenitor stem cells (NSCs) were as high as 25 ± 6 mg ml(-1), while proteins were distributed more uniformly and reached concentrations as high as ∼50 ± 12 mg ml(-1). The combined AFM-Raman datasets from fixed cells were also used to investigate potential improvements for normalization of Raman spectral maps. For all Raman maps of fixed cells (n = 10), we found a linear relationship between the scores corresponding to the first component (PC1) and the cell height profile obtained by AFM. We used PC1 scores to reconstruct the relative height profiles of independent cells (n = 10), and obtained correlation coefficients with AFM maps higher than 0.99. Using this normalization method, qualitative maps of RNA and protein were used to obtain concentrations for live NSCs. While this study demonstrates the potential of using AFM and RMS for measuring concentration maps for individual NSCs in vitro, further studies are required to establish the robustness of the normalization method based on principal component analysis when comparing Raman spectra of cells with large morphological differences.

In vitro label-free screening of chemotherapeutic drugs using Raman microspectroscopy: Towards a new paradigm of spectralomics

This overview groups some of the recent studies highlighting the potential application of Raman microspectroscopy as an analytical technique in preclinical development to predict drug mechanism of action and in clinical application as a companion diagnostic and in personalised therapy due to its capacity to predict cellular resistance and therefore to optimise chemotherapeutic treatment efficacy. Notably, the anthracyclines, doxorubicin and actinomycin D, elicit similar spectroscopic signatures of subcellular interaction characteristic of the mode of action of intercalation. Although cisplatin and vincristine show markedly different signatures, at low exposure doses, their signatures at higher doses show marked similarities to those elicited by the intercalating anthracyclines, confirming that anticancer agents can have different modes of action with different spectroscopic signatures, depending on the dose. The study demonstrates that Raman microspectroscopy can elucidate subcellular transport and accumulation pathways of chemotherapeutic agents, characterise and fingerprint their mode of action, and potentially identify cell-resistant strains. The consistency of the spectroscopic signatures for drugs of similar modes of action, in different cell lines, suggests that this fingerprint can be considered a "spectralome" of the drug-cell interaction suggesting a new paradigm of representing spectroscopic responses.

An in vitro study of the interaction of the chemotherapeutic drug Actinomycin D with lung cancer cell lines using Raman micro-spectroscopy

The applications of Raman microspectroscopy have been extended in recent years into the field of clinical medicine, and specifically in cancer research, as a non-invasive diagnostic method in vivo and ex vivo, and the field of pharmaceutical development as a label-free predictive technique for new drug mechanisms of action in vitro. To further illustrate its potential for such applications, it is important to establish its capability to fingerprint drug mechanisms of action and different cellular reactions. In this study, cytotoxicity assays were employed to establish the toxicity profiles for 48 and 72 hours exposure of lung cancer cell lines, A549 and Calu-1, after exposure to Actinomycin D (ACT) and Raman micro-spectroscopy was used to track its mechanism of action at subcellular level and subsequent cellular responses. Multivariate data analysis was used to elucidate the spectroscopic signatures associated with ACT chemical binding and cellular resistances. Results show that the ACT uptake and mechanism of action are similar in the 2 cell lines, while A549 cells exhibits spectral signatures of resistance to apoptosis related to its higher chemoresistance to the anticancer drug ACT. The observations are discussed in comparison to previous studies of the similar anthracyclic chemotherapeutic agent Doxorubicin. A, Preprocessed Raman spectrum of ACT stock solution dissolved in sterile water and mean spectrum with SD of (B) nucleolus, (C) nucleus and (D) cytoplasm of A549 cell lines after 48 hours exposure to the corresponding IC₅₀ .

Exploring the efficacy and cellular uptake of sorafenib in colon cancer cells by Raman micro-spectroscopy

This study demonstrates the efficacy and distribution of sorafenib in colon cancer cells by label-free Raman microscopy.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Label-Free Raman Hyperspectral Imaging of Single Cells Cultured on Polymer Substrates

While Raman hyperspectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and in vitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: (1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; and (2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples, we show that Raman hyperspectral data sets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins, and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering.

Noninvasive Diagnosis of High-Grade Urothelial Carcinoma in Urine by Raman Spectral Imaging

The current gold standard for the diagnosis of bladder cancer is cystoscopy, which is invasive and painful for patients. Therefore, noninvasive urine cytology is usually used in the clinic as an adjunct to cystoscopy; however, it suffers from low sensitivity. Here, a novel noninvasive, label-free approach with high sensitivity for use with urine is presented. Coherent anti-Stokes Raman scattering imaging of urine sediments was used in the first step for fast preselection of urothelial cells, where high-grade urothelial cancer cells are characterized by a large nucleus-to-cytoplasm ratio. In the second step, Raman spectral imaging of urothelial cells was performed. A supervised classifier was implemented to automatically differentiate normal and cancerous urothelial cells with 100% accuracy. In addition, the Raman spectra not only indicated the morphological changes that are identified by cytology with hematoxylin and eosin staining but also provided molecular resolution through the use of specific marker bands. The respective Raman marker bands directly show a decrease in the level of glycogen and an increase in the levels of fatty acids in cancer cells as compared to controls. These results pave the way for "spectral" cytology of urine using Raman microspectroscopy.

Label-Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches

Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label-free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface-enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman-active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber-based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Raman and infrared spectroscopy differentiate senescent from proliferating cells in a human dermal fibroblast 3D skin model

Senescence-associated alterations were detected in biomolecules of 3D cultured cells and these cells were distinguished from 2D cultured cells.

Raman-based detection of hydroxyethyl starch in kidney allograft biopsies as a potential marker of allograft quality in kidney transplant recipients

In brain-dead donor resuscitation, hydroxyethyl starch (HES) use has been associated with presence of osmotic-nephrosis-like lesions in kidney transplant recipients. Our aim was to determine whether the presence of HES in protocol renal graft biopsies at three months (M3) after transplantation is associated with renal graft quality. According to the HES administered to the donor during the procurement procedure, two groups of patients were defined according graft exposition to HES: HES group, (N = 20) and control group (N = 6). Detection and relative quantification of HES was performed by Raman spectroscopy microimaging on M3 protocol renal graft biopsies. Statistical analyses were used to investigate the association between Raman data and graft characteristics. HES spectral signal was revealed negative in the control group, whereas it was positive in 40% of biopsies from the HES group. In the HES group, a stronger HES signal was associated with a lower risk of graft failure measured by the Kidney Donor Risk Index (KDRI) and was correlated with the allograft kidney function. Thus, HES accumulation in donor kidney, as probed by Raman biophotonic technique, is correlated with the quality of donor kidney and consequently the graft renal function and graft survival.

Lipid metabolic reprogramming in cancer cells

Many human diseases, including metabolic, immune and central nervous system disorders, as well as cancer, are the consequence of an alteration in lipid metabolic enzymes and their pathways. This illustrates the fundamental role played by lipids in maintaining membrane homeostasis and normal function in healthy cells. We reviewed the major lipid dysfunctions occurring during tumor development, as determined using systems biology approaches. In it, we provide detailed insight into the essential roles exerted by specific lipids in mediating intracellular oncogenic signaling, endoplasmic reticulum stress and bidirectional crosstalk between cells of the tumor microenvironment and cancer cells. Finally, we summarize the advances in ongoing research aimed at exploiting the dependency of cancer cells on lipids to abolish tumor progression.