Biochemical differences in tumorigenic and nontumorigenic cells measured by Raman and infrared spectroscopy

Hyperspectral Mapping of Human Primary and Stem Cells at Cell-Matrix Interfaces

Extracellular matrices interface with cells to promote cell growth and tissue development. Given this critical role, matrix mimetics are introduced to enable biomedical materials ranging from tissue engineering scaffolds and tumor models to organoids for drug screening and implant surface coatings. Traditional microscopy methods are used to evaluate such materials in their ability to support exploitable cell responses, which are expressed in changes in cell proliferation rates and morphology. However, the physical imaging methods do not capture the chemistry of cells at cell-matrix interfaces. Herein, we report hyperspectral imaging to map the chemistry of human primary and embryonic stem cells grown on matrix materials, both native and artificial. We provide the statistical analysis of changes in lipid and protein content of the cells obtained from infrared spectral maps to conclude matrix morphologies as a major determinant of biochemical cell responses. The study demonstrates an effective methodology for evaluating bespoke matrix materials directly at cell-matrix interfaces.

Vibrational spectroscopies for biochemical investigation of X-ray exposure effects on SH-SY5Y human neuroblastoma cells

Neuroblastoma is the most recurring cancer in childhood and adolescence. The SH-SY5Y neuroblastoma cell line is generally adopted for elaborating new therapeutical approaches and/or elaborating strategies for the prevention of central nervous system disturbances. In fact, it represents a valid model system for investigating in vitro the effects on the brain of X-ray exposure using vibrational spectroscopies that can detect early radiation-induced molecular alterations of potential clinical usefulness. In recent years, we dedicated significant efforts in the use of Fourier-transform and Raman microspectroscopy techniques for characterizing such radiation-induced effects on SH-SY5Y cells by examining the contributions from different cell components (DNA, proteins, lipids, and carbohydrates) to the vibrational spectra. In this review, we aim at revising and comparing the main results of our studies to provide a wide outlook of the latest outcomes and a framework for future radiobiology research using vibrational spectroscopies. A short description of our experimental approaches and data analysis procedures is also reported.

Understanding radiation response and cell cycle variation in brain tumour cells using Raman spectroscopy

Radiation therapy is currently utilised in the treatment of approximately 50% of cancer patients. A move towards patient tailored radiation therapy would help to improve the treatment outcome for patients as the inter-patient and intra-patient heterogeneity of cancer leads to large differences in treatment responses. In radiation therapy, a typical treatment outcome is cell cycle arrest which leads to cell cycle synchronisation. As treatment is typically given over multiple fractions it is important to understand how variation in the cell cycle can affect treatment response. Raman spectroscopy has previously been assessed as a method for monitoring radiation response in cancer cells and has shown promise in detecting the subtle biochemical changes following radiation exposure. This study evaluated Raman spectroscopy as a potential tool for monitoring cellular response to radiation in synchronised versus unsynchronised UVW human glioma cells in vitro. Specifically, it was hypothesised that the UVW cells would demonstrate a greater radiation resistance if the cell cycle phase of the cells was synchronised to the G1/S boundary prior to radiation exposure. Here we evaluated whether Raman spectroscopy, combined with cell cycle analysis and DNA damage and repair analysis (γ-H2AX assay), could discriminate the subtle cellular changes associated with radiation response. Raman spectroscopy combined with principal component analysis (PCA) was able to show the changes in radiation response over 24 hours following radiation exposure. Spectral changes were assigned to variations in protein, specifically changes in protein signals from amides as well as changes in lipid expression. A different response was observed between cells synchronised in the cell cycle and unsynchronised cells. After 24 hours following irradiation, the unsynchronised cells showed greater spectral changes compared to the synchronised cells demonstrating that the cell cycle plays an important role in the radiation resistance or sensitivity of the UVW cells, and that radiation resistance could be induced by controlling the cell cycle. One of the main aims of cancer treatment is to stop the proliferation of cells by controlling or halting progression through the cell cycle, thereby highlighting the importance of controlling the cell cycle when studying the effects of cancer treatments such as radiation therapy. Raman spectroscopy has been shown to be a useful tool for evaluating the changes in radiation response when the cell cycle phase is controlled and therefore highlighting its potential for assessing radiation response and resistance.

Advances in measuring cancer cell metabolism with subcellular resolution

Characterizing metabolism in cancer is crucial for understanding tumor biology and for developing potential therapies. Although most metabolic investigations analyze averaged metabolite levels from all cell compartments, subcellular metabolomics can provide more detailed insight into the biochemical processes associated with the disease. Methodological limitations have historically prevented the wider application of subcellular metabolomics in cancer research. Recently, however, ways to distinguish and identify metabolic pathways within organelles have been developed, including state-of-the-art methods to monitor metabolism in situ (such as mass spectrometry-based imaging, Raman spectroscopy and fluorescence microscopy), to isolate key organelles via new approaches and to use tailored isotope-tracing strategies. Herein, we examine the advantages and limitations of these developments and look to the future of this field of research.

Diagnosing molecular subtypes of breast cancer by means of Raman spectroscopy

OBJECTIVES

Raman spectroscopy has been used to discriminate human breast cancer and its different tumor molecular subtypes (luminal A, luminal B, HER2, and triple-negative) from normal tissue in surgical specimens.

MATERIALS AND METHODS

Breast cancer and normal tissue samples from 31 patients were obtained by surgical resection and submitted for histopathology. Before anatomopathological processing, the samples had been submitted to Raman spectroscopy (830 nm, 25 mW excitation laser parameters). In total, 424 Raman spectra were obtained. Principal component analysis (PCA) was used in an exploratory analysis to unveil the compositional differences between the tumors and normal tissues. Discriminant models were developed to distinguish the different cancer subtypes by means of partial least squares (PLS) regression.

RESULTS

PCA vectors showed spectral features referred to the biochemical constitution of breast tissues, such as lipids, proteins, amino acids, and carotenoids, where lipids were decreased and proteins were increased in breast tumors. Despite the small spectral differences between the different subtypes of tumor and normal tissues, the discriminant model based on PLS was able to discriminate the spectra of the breast tumors from normal tissues with an accuracy of 97.3%, between luminal and nonluminal subtypes with an accuracy of 89.9%, between nontriple-negative and triple-negative with an accuracy of 94.7%, and each molecular subtype with an accuracy of 73.0%.

CONCLUSION

PCA could reveal the compositional difference between tumors and normal tissues, and PLS could discriminate the Raman spectra of breast tissues regarding the molecular subtypes of cancer, being a useful tool for cancer diagnosis.

A Single-Organelle Optical Omics Platform for Cell Science and Biomarker Discovery

Research in fundamental cell biology and pathology could be revolutionized by developing the capacity for quantitative molecular analysis of subcellular structures. To that end, we introduce the Ramanomics platform, based on confocal Raman microspectrometry coupled to a biomolecular component analysis algorithm, which together enable us to molecularly profile single organelles in a live-cell environment. This emerging omics approach categorizes the entire molecular makeup of a sample into about a dozen of general classes and subclasses of biomolecules and quantifies their amounts in submicrometer volumes. A major contribution of our study is an attempt to bridge Raman spectrometry with big-data analysis in order to identify complex patterns of biomolecules in a single cellular organelle and leverage discovery of disease biomarkers. Our data reveal significant variations in organellar composition between different cell lines. We also demonstrate the merits of Ramanomics for identifying diseased cells by using prostate cancer as an example. We report large-scale molecular transformations in the mitochondria, Golgi apparatus, and endoplasmic reticulum that accompany the development of prostate cancer. Based on these findings, we propose that Ramanomics datasets in distinct organelles constitute signatures of cellular metabolism in healthy and diseased states.

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer

This study addresses the core issue facing a surgical team during breast cancer surgery: quantitative prediction of tumor likelihood including estimates of prediction error. We have previously reported that a molecular probe, Laser Raman spectroscopy (LRS), can distinguish healthy and tumor tissue. We now report that combining LRS with two machine learning algorithms, unsupervised k-means and stochastic nonlinear neural networks (NN), provides rapid, quantitative, probabilistic tumor assessment with real-time error analysis. NNs were first trained on Raman spectra using human expert histopathology diagnostics as gold standard (74 spectra, 5 patients). K-means predictions using spectral data when compared to histopathology produced clustering models with 93.2-94.6% accuracy, 89.8-91.8% sensitivity, and 100% specificity. NNs trained on k-means predictions generated probabilities of correctness for the autonomous classification. Finally, the autonomous system characterized an extended dataset (203 spectra, 8 patients). Our results show that an increase in DNA|RNA signal intensity in the fingerprint region (600-1800 cm-1) and global loss of high wavenumber signal (2800-3200 cm-1) are particularly sensitive LRS warning signs of tumor. The stochastic nature of NNs made it possible to rapidly generate multiple models of target tissue classification and calculate the inherent error in the probabilistic estimates for each target.

In situ exploring Chidamide, a histone deacetylase inhibitor, induces molecular changes of leukemic T-lymphocyte apoptosis using Raman spectroscopy

Though it has been demonstrated that Chidamide (CS055/HBI-8000), a novel benzamide class of histone deacetylase (HDAC) subtype-selectively inhibitor, reveals better anticancer effect in acute leukemia, but it remains unknown about the precise mechanism of Chidamide-induced acute leukemia cell apoptosis due to the lack of in situ molecular changes information. Based on Raman spectral analysis, we find that the action of Chidamide on Jurkat cell will lead to an addition of an acetyl group to a specific lysine residue at the end of histone amino acid, and greatly enhance the acetylation of histones H1, H2A, H2B, H3, and H4, and then destroy the electrostatic force between the alkaline terminal of the positive charged arginine side chain and the negative charged DNA of phosphate group, finally cause the depolymerization of DNA and histone octamer in chromatin nucleosome depolymerization and the relaxation of chromatin. Accordingly, the accumulation of reactive oxygen species (ROS) and the decreasing of mitochondrial membrane potential (MMP) are observed. For comparison, we also present the corresponding results of suberoylanilide hydroxamic acid (SAHA) and MS-275 inhibitors. The achieved results show that proliferation of Chidamide-treated Jurkat cells is low relative to MS-275 or SAHA, and the action of Chidamide or MS-275 on Jurkat cells lead to obvious increasing in histones H1, H2A, H2B, H3, and H4, whereas the action effect of SAHA is mainly observed in histones H1, H2A, H2B, H3 but weak in histone H4. Moreover, it is found that Chidamide-induced histone H3 acetylation in Jurkat cells is stronger than MS-275 and SAHA. Collectively, by Raman spectral analysis, we achieve the dynamic behavior of biochemical components, molecular conformation and morphological changes of HDAC inhibitors-treated Jurkat cells. Importantly, our research is the first to demonstrate that the action site of HDAC inhibitors on Jurkat cell is located in the DNA minor groove. Most importantly, the application of Raman spectrum in exploring in-situ molecular changes information, histone acetylation modification in epigenetics, drug action sites and cell cycle affected by HDAC inhibitors will supply new idea and reference for the design and modification of HDAC inhibitors.

Depth-sensitive Raman spectroscopy for skin wound evaluation in rodents

Raman spectroscopy has demonstrated great potential for skin wound assessment. Given that biochemical changes in wound healing is depth dependent as the skin is a layered structure, depth sensitive Raman spectroscopy could enhance the power of Raman spectroscopy in this application. Considering the critical importance of rodent studies in the field of skin wound assessment, it is necessary to develop and validate a system that can perform depth sensitive measurements in rat skin with a proper target depth range. In this manuscript, we report the design, optimization and evaluation of a new snapshot depth-sensitive Raman instrument for rat skin measurements. The optical design and optimization process are presented first. The depth sensitive measurement performance is characterized on both ex vivo porcine skin with a gradient of layer thickness and ex vivo rat skin samples with wounds. The statistical analysis of the measured Raman spectra demonstrates the feasibility of differentiation between the wound edge and healthy skin. Moreover, the accuracy of classification improves monotonically as more data from new depths are used, which implies that each depth offers additional information useful for classification. This instrument demonstrates the ability to perform snapshot depth sensitive Raman measurements from rat skin, which paves the way towards in vivo preclinical studies of rat skin wounds.

Raman Spectroscopy for Rapid Evaluation of Surgical Margins during Breast Cancer Lumpectomy

Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery.

Inkjet-printed micro-calibration standards for ultraquantitative Raman spectral cytometry

Herein we report the development of a cytometric analysis platform for measuring the contents of individual cells in absolute (picogram) scales; this study represents the first report of Raman-based quantitation of the absolute mass - or the total amount - of multiple endogenous biomolecules within single-cells. To enable ultraquantitative calibration, we engineered single-cell-sized micro-calibration standards of known composition by inkjet-printer deposition of biomolecular components in microarrays across the surface of silicon chips. We demonstrate clinical feasibility by characterizing the compositional phenotype of human skin fibroblast and porcine alveolar macrophage cell populations in the respective contexts of Niemann-Pick disease and drug-induced phospholipidosis: two types of lipid storage disorders. We envision this microanalytical platform as the foundation for many future biomedical applications, ranging from diagnostic assays to pathological analysis to advanced pharmaco/toxicokinetic research studies.

Exploring the margins of SERS in practical domain: An emerging diagnostic modality for modern biomedical applications

Excellent multiplexing capability, molecular specificity, high sensitivity and the potential of resolving complex molecular level biological compositions augmented the diagnostic modality of surface-enhanced Raman scattering (SERS) in biology and medicine. While maintaining all the merits of classical Raman spectroscopy, SERS provides a more sensitive and selective detection and quantification platform. Non-invasive, chemically specific and spatially resolved analysis facilitates the exploration of SERS-based nano probes in diagnostic and theranostic applications with improved clinical outcomes compared to the currently available so called state-of-art technologies. Adequate knowledge on the mechanism and properties of SERS based nano probes are inevitable in utilizing the full potential of this modality for biomedical applications. The safety and efficiency of metal nanoparticles and Raman reporters have to be critically evaluated for the successful translation of SERS in to clinics. In this context, the present review attempts to give a comprehensive overview about the selected medical, biomedical and allied applications of SERS while highlighting recent and relevant outcomes ranging from simple detection platforms to complicated clinical applications.

Linear Regression Links Transcriptomic Data and Cellular Raman Spectra

Raman microscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra and transcriptomic profiles of Schizosaccharomyces pombe and Escherichia coli can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA sequencing can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Highly expressed non-coding RNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe. This demonstration of correspondence between cellular Raman spectra and transcriptomes is a promising step toward establishing spectroscopic live-cell omics studies.

Myc, Oncogenic Protein Translation, and the Role of Polyamines

Deregulated protein synthesis is a common feature of cancer cells, with many oncogenic signaling pathways directly augmenting protein translation to support the biomass needs of proliferating tissues. MYC’s ability to drive oncogenesis is a consequence of its essential role as a governor linking cell cycle entry with the requisite increase in protein synthetic capacity, among other biomass needs. To date, direct pharmacologic inhibition of MYC has proven difficult, but targeting oncogenic signaling modules downstream of MYC, such as the protein synthetic machinery, may provide a viable therapeutic strategy. Polyamines are essential cations found in nearly all living organisms that have both direct and indirect roles in the control of protein synthesis. Polyamine metabolism is coordinately regulated by MYC to increase polyamines in proliferative tissues, and this is further augmented in the many cancer cells harboring hyperactivated MYC. In this review, we discuss MYC-driven regulation of polyamines and protein synthetic capacity as a key function of its oncogenic output, and how this dependency may be perturbed through direct pharmacologic targeting of components of the protein synthetic machinery, such as the polyamines themselves, the eukaryotic translation initiation factor 4F (eIF4F) complex, and the eukaryotic translation initiation factor 5A (eIF5A).

Raman Spectroscopy Applied to Parathyroid Tissues: A New Diagnostic Tool to Discriminate Normal Tissue from Adenoma

Primary hyperparathyroidism is an endocrine disorder characterized by autonomous production of parathyroid hormone. Patients with the symptomatic disease should be referred for parathyroidectomy. However, the distinction between the pathological condition and the benign one is very challenging in the surgical setting; therefore, accurate recognition is important to ensure success during minimally invasive surgery. At present, all intraoperative techniques significantly increase surgical time and, consequently, cost. In this proof-of-concept study, Raman microscopy was used to differentiate between healthy parathyroid tissue and parathyroid adenoma from 18 patients. The data showed different spectroscopic features for the two main tissue types of healthy and adenoma. Moreover, the parathyroid adenoma subtypes (chief cells and oxyphil cells) were characterized by their own Raman spectra. The partial least-squares discriminant analysis (PLS-DA) model built to discriminate healthy from adenomatous parathyroid tissue was able to correctly classify all samples in the calibration and validation data sets, providing 100% prediction accuracy. The PLS-DA model built to discriminate chief cell adenoma from oxyphil cell adenoma allowed us to correctly classify >99% of the spectra during calibration and cross-validation and to correctly predict 100% of oxyphil and 99.8% of chief cells in the external validation data set. The results clearly demonstrate the great potential of Raman spectroscopy. The final goal would be development of a Raman portable fiber probe device for intraoperative optical biopsy, both to improve the surgical success rate and reduce surgical cost.

Ramanomics: New Omics Disciplines Using Micro Raman Spectrometry with Biomolecular Component Analysis for Molecular Profiling of Biological Structures

Modern instrumentation for Raman microspectroscopy and current techniques in analysis of spectral data provide new opportunities to study molecular interactions and dynamics at subcellular levels in biological systems. Implementation of biomolecular component analysis (BCA) to microRaman spectrometry provides basis for the emergence of Ramanomics, a new biosensing discipline with unprecedented capabilities to measure concentrations of distinct biomolecular groups in live cells and organelles. Here we review the combined use of microRaman-BCA techniques to probe absolute concentrations of proteins, DNA, RNA and lipids in single organelles of live cells. Assessing biomolecular concentration profiles of organelles at the single cell level provides a physiologically relevant set of biomarkers for cellular heterogeneity. In addition, changes to an organelle's biomolecular concentration profile during a cellular transformation, whether natural, drug induced or disease manifested, can provide molecular insight into the nature of the cellular process.

Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells

Cells must duplicate their mass in order to proliferate. Glucose and glutamine are the major nutrients consumed by proliferating mammalian cells, but the extent to which these and other nutrients contribute to cell mass is unknown. We quantified the fraction of cell mass derived from different nutrients and found that the majority of carbon mass in cells is derived from other amino acids, which are consumed at much lower rates than glucose and glutamine. While glucose carbon has diverse fates, glutamine contributes most to protein, suggesting that glutamine's ability to replenish tricarboxylic acid cycle intermediates (anaplerosis) is primarily used for amino acid biosynthesis. These findings demonstrate that rates of nutrient consumption are indirectly associated with mass accumulation and suggest that high rates of glucose and glutamine consumption support rapid cell proliferation beyond providing carbon for biosynthesis.

Detection of Vero Cells Infected with Herpes Simplex Types 1 and 2 and Varicella Zoster Viruses Using Raman Spectroscopy and Advanced Statistical Methods

Of the eight members of the herpes family of viruses, HSV1, HSV2, and varicella zoster are the most common and are mainly involved in cutaneous disorders. These viruses usually are not life-threatening, but in some cases they might cause serious infections to the eyes and the brain that can lead to blindness and possibly death. An effective drug (acyclovir and its derivatives) is available against these viruses. Therefore, early detection and identification of these viral infections is highly important for an effective treatment. Raman spectroscopy, which has been widely used in the past years in medicine and biology, was used as a powerful spectroscopic tool for the detection and identification of these viral infections in cell culture, due to its sensitivity, rapidity and reliability. Our results showed that it was possible to differentiate, with a 97% identification success rate, the uninfected Vero cells that served as a control, from the Vero cells that were infected with HSV-1, HSV-2, and VZV. For that, linear discriminant analysis (LDA) was performed on the Raman spectra after principal component analysis (PCA) with a leave one out (LOO) approach. Raman spectroscopy in tandem with PCA and LDA enable to differentiate among the different herpes viral infections of Vero cells in time span of few minutes with high accuracy rate. Understanding cell molecular changes due to herpes viral infections using Raman spectroscopy may help in early detection and effective treatment.

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

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

Rapid detection of oral cancer using Ag–TiO2 nanostructured surface-enhanced Raman spectroscopic substrates

Developed Ag–TiO₂ based large area SERS substrate that enables spectroscopic detection and classification of oral squamous cell carcinoma with a specificity and sensitivity of 95.83% and 100%, respectively.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

GENERAL SIGNIFICANCE

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

Comparison of principal component analysis and biochemical component analysis in Raman spectroscopy for the discrimination of apoptosis and necrosis in K562 leukemia cells

Raman spectroscopy has been explored as a promising label-free technique in discriminating apoptosis and necrosis induced cell death in leukemia cells. In addition to Principal component analysis (PCA) as commonly employed in Raman data analysis, another less commonly used but powerful method is Biochemical Component Analysis (BCA). In BCA, a Raman spectrum is decomposed into the contributions from several known basic biochemical components, such as proteins, lipid, nucleic acids and glycogen groups etc. The differences in terms of classification accuracy and interpretability of resulting data between these two methods in Raman spectroscopy have not been systematically investigated to our knowledge. In this study, we utilized both methods to analyze the Raman spectra measured from live cells, apoptotic and necrotic leukemia cells. The comparison indicates that two methods yield comparable accuracy in sample classification when the numbers of basic components are equal. The changes in the contributions of biochemical components in BCA can be interpreted by cell biology principles in apoptosis and necrosis. In contrast, the contributions of most principle components in PCA are difficult to interpret except the first one. The capability of BCA to unveil fine biochemical changes in cell spectra and excellent accuracy in classification can impel the broad application of Raman spectroscopy in biological research.

Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis

The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral "fingerprints" of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis.

Tissue refractive index as marker of disease

The gold standard in histopathology relies on manual investigation of stained tissue biopsies. A sensitive and quantitative method for in situ tissue specimen inspection is highly desirable, as it would allow early disease diagnosis and automatic screening. Here we demonstrate that quantitative phase imaging of entire unstained biopsies has the potential to fulfill this requirement. Our data indicates that the refractive index distribution of histopathology slides, which contains information about the molecular scale organization of tissue, reveals prostate tumors and breast calcifications. These optical maps report on subtle, nanoscale morphological properties of tissues and cells that cannot be recovered by common stains, including hematoxylin and eosin. We found that cancer progression significantly alters the tissue organization, as exhibited by consistently higher refractive index variance in prostate tumors versus normal regions. Furthermore, using the quantitative phase information, we obtained the spatially resolved scattering mean free path and anisotropy factor g for entire biopsies and demonstrated their direct correlation with tumor presence. In essence, our results show that the tissue refractive index reports on the nanoscale tissue architecture and, in principle, can be used as an intrinsic marker for cancer diagnosis.

Multivariate optical computing using a digital micromirror device for fluorescence and Raman spectroscopy

A multivariate optical computer has been constructed consisting of a spectrograph, digital micromirror device, and photomultiplier tube that is capable of determining absolute concentrations of individual components of a multivariate spectral model. We present experimental results on ternary mixtures, showing accurate quantification of chemical concentrations based on integrated intensities of fluorescence and Raman spectra measured with a single point detector. We additionally show in simulation that point measurements based on principal component spectra retain the ability to classify cancerous from noncancerous T cells.

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

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

Analysis of intracellular state based on controlled 3D nanostructures mediated surface enhanced Raman scattering

Near-infrared surface-enhanced Raman spectroscopy (SERS) is a powerful technique for analyzing the chemical composition within a single living cell at unprecedented resolution. However, current SERS methods employing uncontrollable colloidal metal particles or non-uniformly distributed metal particles on a substrate as SERS-active sites show relatively low reliability and reproducibility. Here, we report a highly-ordered SERS-active surface that is provided by a gold nano-dots array based on thermal evaporation of gold onto an ITO surface through a nanoporous alumina mask. This new combined technique showed a broader distribution of hot spots and a higher signal-to-noise ratio than current SERS techniques due to the highly reproducible and uniform geometrical structures over a large area. This SERS-active surface was applied as cell culture system to study living cells in situ within their culture environment without any external preparation processes. We applied this newly developed method to cell-based research to differentiate cell lines, cells at different cell cycle stages, and live/dead cells. The enhanced Raman signals achieved from each cell, which represent the changes in biochemical compositions, enabled differentiation of each state and the conditions of the cells. This SERS technique employing a tightly controlled nanostructure array can potentially be applied to single cell analysis, early cancer diagnosis and cell physiology research.

Surface-enhanced Raman scattering (SERS) cytometry

Significant advances have been made in the preparation and applications of surface-enhanced Raman scattering (SERS)-active materials for biomolecular analysis. Bright signals, photostability, and narrow spectral features of SERS-active materials offer attractive advantages for cytometric analyses. However, SERS cytometry is still in an early stage of development, and advances in both instrumentation and reagents will be necessary to realize its full potential. In this chapter, we discuss the challenges of expanding the numbers of fluorescent labels that can be measured in cytometry, and introduce SERS tags with extremely narrow spectral peaks as an approach to make more efficient use of the optical spectrum and increase the number of parameters in cytometry.

Variability in Raman spectra of single human tumor cells cultured in vitro: correlation with cell cycle and culture confluency

In this work we investigate the capability of Raman microscopy (RM) to detect inherent sources of biochemically based spectral variability between single cells of a human tumor cell line (DU145) cultured in vitro. Principal component analysis (PCA) is used to identify differences in single-cell Raman spectra. These spectral differences correlate with (1) cell cycle progression and (2) changing confluency of a cell culture during the first 3 to 4 days after sub-culturing. Cell cycle regulatory drugs are used to synchronize the cell cycle progression of cell cultures, and flow cytometry is used to determine the cell cycle distribution of cell cultures at the time of Raman analysis. Spectral variability arising from cell cycle progression is (1) expressed as varying intensities of protein and nucleic acid features relative to lipid features, (2) well correlated with known biochemical changes in cells as they progress through the cell cycle, and (3) shown to be the most significant source of inherent spectral variability between cells. Furthermore, the specific biomolecules responsible for the observed spectral variability due to both cell cycle progression and changes in cell culture confluency can be identified in the first and second components of principal component analysis (PCA). Our characterization of the inherent sources of variability in Raman spectra of single human cells will be useful for understanding subtle spectral differences in RM studies of single cells.

The use of synchrotron infrared microspectroscopy in the assessment of cutaneous T-cell lymphoma vs. pityriasis lichenoides chronica

BACKGROUND

The diagnosis of cutaneous lymphomas remains a challenge for both the clinician and dermatopathologist.

OBJECTIVES

To differentiate between frank malignant and premalignant lymphocytes within the skin.

METHODS

This study was performed on 20 patients with a mean age of 50 years. They were divided into two groups: mycosis fungoides (MF) (stage IA, IB and IIA) and pityriasis lichenoides chronica (PLC). Immunophenotyping using antibodies CD3, CD4, CD8, CD20 and CD30 was performed. Synchrotron Fourier transform infrared microspectroscopy (S-FTIRM) was performed on cell nuclei to assess chemical differences between MF and PLC cases as a potential complementary screening tool. Dermal spectra of both MF and PLC were compared using principal components analysis (PCA) of the S-FTIRM data.

RESULTS

All PLC spectra was clustered together. However, the MF spectra formed two clusters, one that grouped with the PLC and the other grouped separately. Moreover, protein and nucleic acids showed highly significant differences between MF (IIA and IB), MF (IA) and PLC.

CONCLUSIONS

The malignant transformation within lymphocytes was identifiable through the spectroscopic analysis of protein, RNA and DNA with S-FTIRM, making it a promising tool for classifying the progression of cutaneous T-cell lymphoma.

Assessment of cell line models of primary human cells by Raman spectral phenotyping

Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures.

Role of Synchrotron infra red microspectroscopy in studying epidermotropism of cutaneous T-cell lymphoma

BACKGROUND

The molecular mechanisms of epidermotropism in mycosis fungoides (MF) are not well understood to date.

OBJECTIVES

The aim of this study was to differentiate between epidermal and dermal lymphocytes within the skin of MF patients.

METHODS

This study was done on 10 MF patients with a mean age of 50 years diagnosed clinically in the Department of Dermatology, Cairo University, Egypt. A 6 mm biopsy was taken from each patient in order to confirm the diagnosis. Skin biopsies were cut, put on low e-slides and then stained with H&E. Further examination with Synchrotron infrared (IR) microspectroscopy was done in National Synchrotron Light Source--Brookhaven National Laboratory, New York, USA. Immunophenotyping using antibodies CD3, CD4, CD8, CD20 and CD30 was also done. Statistical analysis was done by Student's t-test and cluster analysis.

RESULTS

Both epidermal and dermal lymphocytes were clustered separately. Also, Amide I and RNA and DNA within the lymphocytes were significantly different between the epidermis and the dermis.

CONCLUSIONS

The biochemical analysis of protein, RNA and DNA with Synchrotron IR microspectroscopy is a promising tool for studying epidermotropism in cutaneous T-cell lymphoma.

Raman signature from brain hippocampus could aid Alzheimer's disease diagnosis

Micro-Raman spectroscopy (MRS) is used for the first time to our knowledge to investigate brain hippocampus tissue from Alzheimer's disease (AD) infected rats. In situ Raman analysis of tissue sections provides distinct spectra useful for distinguishing AD from normal state. The biochemical changes of brain hippocampus tissue including the deposit of beta-amyloid (Abeta) protein, the increase of cholesterol, and hyperphosphorylated tau are observed through MRS when AD occurs. A more convincing multi-Raman criterion based on single Raman peaks, and further in combination with statistical analysis of the entire Raman spectrum, is found capable of classifying brain hippocampus tissues with different pathological features. This study demonstrates the brain hippocampus is an important candidate for considering the early pathological state of AD, and Raman signatures from the brain hippocampus could aid AD diagnosis. In addition, Raman results undoubtedly confirm simultaneous changes of cholesterol and Abeta in the progression of AD.

The effect of cell fixation on the discrimination of normal and leukemia cells with laser tweezers Raman spectroscopy

Laser tweezers Raman spectroscopy (LTRS) was used to characterize the effect of different chemical fixation procedures on the Raman spectra of normal and leukemia cells. Individual unfixed, paraformaldehyde-fixed, and methanol-fixed normal and transformed lymphocytes from three different cell lines were analyzed with LTRS. When compared to the spectra of unfixed cells, the fixed cell spectra show clear, reproducible changes in the intensity of specific Raman markers commonly assigned to DNA, RNA, protein, and lipid vibrations (e.g. 785, 1230, 1305, 1660 cm(-1)) in mammalian cells, many of which are important markers that have been used to discriminate between normal and cancer lymphocytes. Statistical analyses of the Raman data and classification using principal component analysis and linear discriminant analysis indicate that methanol fixation induces a greater change in the Raman spectra than paraformaldehyde. In addition, we demonstrate that the spectral changes as a result of the fixation process have an adverse effect on the accurate Raman discrimination of the normal and cancer cells. The spectral artifacts created by the use of fixatives indicate that the method of cell preparation is an important parameter to consider when applying Raman spectroscopy to characterize, image, or differentiate between different fixed cell samples to avoid potential misinterpretation of the data.

Vibrational spectroscopy: a clinical tool for cancer diagnostics

Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.

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

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

Review: Optical Micrometer Resolution Scanning for Non-invasive Grading of Precancer in the Human Uterine Cervix

Management of cervical precancer is archetypal for other cancer prevention programmes but has to consider diagnostic and logistic challenges. Numerous optical tools are emerging for non-destructive near real-time early diagnosis of precancerous lesions of the cervix. Non-destructive, real-time imaging modalities have reached pre-commercial status, but high resolution mapping tools are not yet introduced in clinical settings. The NCBI PubMed web page was searched using the keywords ‘CIN diagnosis’ and the combinations of ‘cervix {confocal, optical coherence tomography, ftir, infrared, Raman, vibrational, spectroscopy}’. Suitable titles were identified and their relevant references followed. Challenges in precancer management are discussed. The following tools capable of non-destructive high resolution mapping in a clinical environment were selected: confocal microscopy, optical coherence tomography, IR spectroscopy, and Raman spectroscopy. Findings on the clinical performance of these techniques are put into context in order to assist the reader in judging the likely performance of these methods as diagnostic tools. Rationale for carrying out research under the prospect of the HPV vaccine is given.

Raman spectroscopic characterization of necrotic cell death

Raman spectroscopy has been used to estimate the biochemical changes due to necrosis in an in vitro model system comprised of a human malignant melanoma cell line (MEL-28). Combined oxygen and glucose deprivation was used to simulate necrotic cell death in tumors. Raman spectroscopy measurements of nonproliferating live cells and dead cells were made at 24, 48, and 72 hours. Quantitative estimates of the biochemical composition of live and dead cells were made by fitting cell spectra to the basis spectra of protein, lipid, RNA, DNA, and glycogen. A decrease in the relative amount of lipid and RNA, and an increase in the relative protein content, were observed in dead cells. A comparison of the spectra indicated the existence of conformational changes in protein and nucleic acids in dead cells. These results suggest that Raman spectroscopy could be used to detect necrotic cell death in tumors.

Comparison of Raman spectrograph throughput using two commercial systems: transmissive versus reflective

A common goal of most Raman spectroscopists is the acquisition of clear Raman spectra in short integration times. It is paramount, then, that the hardware used in a Raman system be optimized for throughput, signal-to-noise ratio, and resolution. To this end, we performed a systematic comparison of two Raman spectrographs: the widely used Kaiser HoloSpec and a relatively new commercial offering, the Raman Explorer by Headwall Photonics. Both strong and weak Raman scattering samples were measured using various launching conditions. When resolution-matched, the throughputs of both spectrographs were found to be roughly similar over the central range of the fingerprint region (approximately 800 to 1140 cm(-1), using 785 nm illumination), with the Raman Explorer demonstrating a slight throughput advantage outside this range. Other factors are also considered such that end users may better select the optimum spectrograph for their particular application.

Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric tissue within 5 s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200-1500 cm(-1) and 1600-1800 cm(-1), which contained signals related to amide III and amide I of proteins, CH(3)CH(2) twisting of proteins/nucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875 cm(-1) to the peak intensity at 1450 cm(-1) gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules.

In vivo Raman study of the living rat esophagus and stomach using a micro-Raman probe under an endoscope

A small endoscope system equipped with a micro Raman probe is developed for in vivo Raman measurements in living rats. The measurements are done under anesthesia and artificial respiration to minimize the impact on the rats. Raman spectra of living rat esophagus and stomach are successfully measured. Our results suggest that the Raman spectra reflect subsurface tissue structure that cannot be distinguished in the endoscope image. After the experiments, rats recover without any aftereffects. It is verified that the Raman measurement using the present system is safe and noninvasive for rats.