Biochemical signatures of in vitro radiation response in human lung, breast and prostate tumour cells observed with Raman spectroscopy

Comparison of biochemical changes induced in radioresistant prostate cancer cells by X-rays, radiosensitizing drugs, and a combined therapy using Raman microspectroscopy

Cancer radioresistance is a major problem in radiotherapy. Many strategies have been proposed to overcome this process including the use of radiosensitizing drugs such as C75 or silibinin. The overall result of all treatments (radiotherapy, chemotherapy, and combined treatment) is cancer cell death. On the other hand, each treatment affects cancer cells differently at the molecular level. However, little is known about biochemical changes induced in cancer cells by these treatments (especially in combined therapy) at the submicroscale. In this study, Raman microspectroscopy was applied to follow such changes induced in radioresistant prostate cancer cells by X-rays, radiosensitizing drugs (C75, silibinin), and a combined treatment. The analysis was supported by the Partial Least Squares Regression method to reveal spectral changes induced by an increasing dose of X-rays and concentrations of the drugs. The obtained regression coefficient (β) plots were compared to each other using a correlation coefficient (R). Our results show that PC-3 cells exhibit dose- and concentration-dependent responses to the treatment with different biochemical changes induced by X-rays in the presence of C75 and silibinin. Moreover, both drugs affect the cells differently at the submicroscale and independently from the X-ray's presence. Finally, C75 shows significant efficiency in the reduction of cell radioresistance.

Investigating ionizing radiation-induced changes in breast cancer cells using stimulated Raman scattering microscopy

Significance

Altered lipid metabolism of cancer cells has been implicated in increased radiation resistance. A better understanding of this phenomenon may lead to improved radiation treatment planning. Stimulated Raman scattering (SRS) microscopy enables label-free and quantitative imaging of cellular lipids but has never been applied in this domain.

Aim

We sought to investigate the radiobiological response in human breast cancer MCF7 cells using SRS microscopy, focusing on how radiation affects lipid droplet (LD) distribution and cellular morphology.

Approach

MCF7 breast cancer cells were exposed to either 0 or 30 Gy (X-ray) ionizing radiation and imaged using a spectrally focused SRS microscope every 24 hrs over a 72-hr time period. Images were analyzed to quantify changes in LD area per cell, lipid and protein content per cell, and cellular morphology. Cell viability and confluency were measured using a live cell imaging system while radiation-induced lipid peroxidation was assessed using BODIPY C11 staining and flow cytometry.

Results

The LD area per cell and total lipid and protein intensities per cell were found to increase significantly for irradiated cells compared to control cells from 48 to 72 hrs post irradiation. Increased cell size, vacuole formation, and multinucleation were observed as well. No significant cell death was observed due to irradiation, but lipid peroxidation was found to be greater in the irradiated cells than control cells at 72 hrs.

Conclusions

This pilot study demonstrates the potential of SRS imaging for investigating ionizing radiation-induced changes in cancer cells without the use of fluorescent labels.

Raman Spectroscopy Revealed Cell Passage-Dependent Distinct Biochemical Alterations in Radiation-Resistant Breast Cancer Cells

Recapitulating radioresistant cell features in pertinent cell line models is essential for deciphering fundamental cellular mechanisms. The limited understanding of passage and cell cycle phases on radioresistant cells revived post-cryopreservation led us to investigate the effect of sub-culturing in parental and radioresistant MCF-7 cells. In this study, the radioresistant cells showed high-intensity nucleic acid and cytochrome bands, which are potentially a radiation-induced spectral marker. Raman spectroscopy data showed dynamic biochemical alterations in revived radioresistant G₂/M synchronized cells at early cell passages 1 and 3 with stabilization at a latter cell passage, 5. The study highlights the importance of cell passaging and cell cycle phases in potentially changing the biochemical parameters during in vitro experiments after the revival of radioresistant cells post-cryopreservation.

Raman microspectroscopy based TNM staging and grading of breast cancer

The tumor-node-metastasis (TNM) system is the most common way that doctors determine the anatomical extent of cancer on the basis of clinical and pathological criteria. In this study, a spectral histopathological study has been carried out to bridge Raman micro spectroscopy with the breast cancer TNM system. A total of seventy breast tissue samples, including healthy tissue, early, middle, and advanced cancer, were investigated to provide detailed insights into compositional and structural variations that accompany breast malignant evolution. After evaluating the main spectral variations in all tissue types, the generalized discriminant analysis (GDA) pathological diagnostic model was established to discriminate the TNM staging and grading information. Moreover, micro-Raman images were reconstructed by K-means clustering analysis (KCA) for visualizing the lobular acinar in healthy tissue and ductal structures in all early, middle and advanced breast cancer tissue groups. While, univariate imaging techniques were adapted to describe the distribution differences of biochemical components such as tryptophan, β-carotene, proteins, and lipids in the scanned regions. The achieved spectral histopathological results not only established a spectra-structure correlations via tissue biochemical profiles but also provided important data and discriminative model references for in vivo Raman-based breast cancer diagnosis.

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity

OBJECTIVE

In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

METHODS

Analysis of Raman tissue data is achieved through a combination of techniques. We first distinguish between tissue measurements and air pockets in the lung by using group and basis restricted non-negative matrix factorization. We then analyze the tissue spectra using sparse multinomial logistic regression to discriminate between fibrotic gradings. Model validation is achieved by splitting the data into a training set containing 70% of the data and a test set with the remaining 30%; classification accuracy is used as the performance metric. We also explore several other potential classification tasks wherein the response considered is the grade of pneumonitis and fibrosis sickness.

RESULTS

A classification accuracy of 91.6% is achieved on the test set of fibrotic gradings, illustrating the ability of Raman measurements to detect differing levels of fibrotic disease among the murine lungs. It is also shown via further modeling that coarser consideration of fibrotic grading via binning (ie. 'Low', 'Medium', 'High') does not degrade performance. Finally, we consider preliminary models for pneumonitis discrimination using the same methodologies.

Raman spectroscopy and supervised learning as a potential tool to identify high-dose-rate-brachytherapy induced biochemical profiles of prostate cancer

High-dose-rate-brachytherapy (HDR-BT) is an increasingly attractive alternative to external beam radiation-therapy for patients with intermediate risk prostate cancer. Despite this, no bio-marker based method currently exists to monitor treatment response, and the changes which take place at the biochemical level in hypo-fractionated HDR-BT remain poorly understood. The aim of this pilot study is to assess the capability of Raman spectroscopy (RS) combined with principal component analysis (PCA) and random-forest classification (RF) to identify radiation response profiles after a single dose of 13.5 Gy in a cohort of nine patients. We here demonstrate, as a proof-of-concept, how RS-PCA-RF could be utilised as an effective tool in radiation response monitoring, specifically assessing the importance of low variance PCs in complex sample sets. As RS provides information on the biochemical composition of tissue samples, this technique could provide insight into the changes which take place on the biochemical level, as result of HDR-BT treatment.

Application of Advanced Non-Linear Spectral Decomposition and Regression Methods for Spectroscopic Analysis of Targeted and Non-Targeted Irradiation Effects in an In-Vitro Model

Irradiation of the tumour site during treatment for cancer with external-beam ionising radiation results in a complex and dynamic series of effects in both the tumour itself and the normal tissue which surrounds it. The development of a spectral model of the effect of each exposure and interaction mode between these tissues would enable label free assessment of the effect of radiotherapeutic treatment in practice. In this study Fourier transform Infrared microspectroscopic imaging was employed to analyse an in-vitro model of radiotherapeutic treatment for prostate cancer, in which a normal cell line (PNT1A) was exposed to low-dose X-ray radiation from the scattered treatment beam, and also to irradiated cell culture medium (ICCM) from a cancer cell line exposed to a treatment relevant dose (2 Gy). Various exposure modes were studied and reference was made to previously acquired data on cellular survival and DNA double strand break damage. Spectral analysis with manifold methods, linear spectral fitting, non-linear classification and non-linear regression approaches were found to accurately segregate spectra on irradiation type and provide a comprehensive set of spectral markers which differentiate on irradiation mode and cell fate. The study demonstrates that high dose irradiation, low-dose scatter irradiation and radiation-induced bystander exposure (RIBE) signalling each produce differential effects on the cell which are observable through spectroscopic analysis.

Monitoring Protein Denaturation of Egg White Using Passive Microwave Radiometry (MWR)

Passive microwave radiometry (MWR) is a measurement technique based on the detection of passive radiation in the microwave spectrum of different objects. When in equilibrium, this radiation is known to be proportional to the thermodynamic temperature of an emitting body. We hypothesize that living systems feature other mechanisms of emission that are based on protein unfolding and water rotational transitions. To understand the nature of these emissions, microwave radiometry was used in several in vitro experiments. In our study, we performed pilot measurements of microwave emissions from egg whites during denaturation induced by ethanol. Egg whites comprise 10% proteins, such as albumins, mucoproteins, and globulins. We observed a novel phenomenon: microwave emissions changed without a corresponding change in the water’s thermodynamic temperature. We also found striking differences between microwave emissions and thermodynamic temperature kinetics. Therefore, we hypothesize that these two processes are unrelated, contrary to what was thought before. It is known that some pathologies such as stroke or brain trauma feature increased microwave emissions. We hypothesize that this phenomenon originates from protein denaturation and is not related to the thermodynamic temperature. As such, our findings could explain the reason for the increase in microwave emissions after trauma and post mortem for the first time. These findings could be used for the development of novel diagnostics methods. The MWR method is inexpensive and does not require fluorescent or radioactive labels. It can be used in different areas of basic and applied pharmaceutical research, including in kinetics studies in biomedicine.

Group and Basis Restricted Non-Negative Matrix Factorization and Random Forest for Molecular Histotype Classification and Raman Biomarker Monitoring in Breast Cancer

Raman spectroscopy is a non-invasive optical technique that can be used to investigate biochemical information embedded in cells and tissues exposed to ionizing radiation used in cancer therapy. Raman spectroscopy could potentially be incorporated in personalized radiation treatment design as a tool to monitor radiation response in at the metabolic level. However, tracking biochemical dynamics remains challenging for Raman spectroscopy. Here we developed a novel analytical framework by combining group and basis restricted non-negative matrix factorization and random forest (GBR-NMF-RF). This framework can monitor radiation response profiles in different molecular histotypes and biochemical dynamics in irradiated breast cancer cells. Five subtypes of; human breast cancer (MCF-7, BT-474, MDA-MB-230, and SK-BR-3) and normal cells derived from human breast tissue (MCF10A) which had been exposed to ionizing radiation were tested in this framework. Reference Raman spectra of 20 biochemicals were collected and used as the constrained Raman biomarkers in the GBR-NMF-RF framework. We obtained scores for individual biochemicals corresponding to the contribution of each Raman reference spectrum to each spectrum obtained from the five cell types. A random forest classifier was then fitted to the chemical scores for performing molecular histotype classifications (HER2, PR, ER, Ki67, and cancer versus non-cancer) and assessing the importance of the Raman biochemical basis spectra for each classification test. Overall, the GBR-NMF-RF framework yields classification results with high accuracy (>97%), high sensitivity (>97%), and high specificity (>97%). Variable importance calculated in the random forest model indicated high contributions from glycogen and lipids (cholesterol, phosphatidylserine, and stearic acid) in molecular histotype classifications.

Exploring subcellular responses of prostate cancer cells to clinical doses of X-rays by Raman microspectroscopy

Modern techniques of radiotherapy such as fractioned radiotherapy require applications of low doses of ionizing radiation (up to 10 Gy) for effective patient treatment. It is, therefore, crucial to understand the response mechanisms in cancer cells irradiated with low (clinical) doses. The cell's response to irradiation depends on a dose and post-irradiation time. Both factors should be considered when studying the influence of ionizing radiation on cancer cells. Thus, in the present study, PC-3 prostate cancer cells were irradiated with clinical doses of X-rays to determine dose- and time-dependent response to the irradiation. Raman spectroscopy and biological methods (MTT and comet assays) were applied for the analysis of biochemical changes in the cells induced by low doses of X-ray irradiation at 0 h and 24 h post-irradiation timepoints. Due to a limited view of the biochemical changes at the subcellular level given by single spectrum Raman measurements, Raman mapping of the whole cell area was performed. The results were compared with those obtained for cell irradiation with high doses. The analysis was based on the Partial Least Squares Regression (PLSR) method for the cytoplasmic and nuclear regions separately. Additionally, for the first time, irradiation classification was performed to confirm Raman spectroscopy as a powerful tool for studies on cancer cells treated with clinical doses of ionizing radiation.

Detection of acquired radioresistance in breast cancer cell lines using Raman spectroscopy and machine learning

Radioresistance-a living cell's response to, and development of resistance to ionising radiation-can lead to radiotherapy failure and/or tumour recurrence. We used Raman spectroscopy and machine learning to characterise biochemical changes that occur in acquired radioresistance for breast cancer cells. We were able to distinguish between wild-type and acquired radioresistant cells by changes in chemical composition using Raman spectroscopy and machine learning with 100% accuracy. In studying both hormone receptor positive and negative cells, we found similar changes in chemical composition that occur with the development of acquired radioresistance; these radioresistant cells contained less lipids and proteins compared to their parental counterparts. As well as characterising acquired radioresistance in vitro, this approach has the potential to be translated into a clinical setting, to look for Raman signals of radioresistance in tumours or biopsies; that would lead to tailored clinical treatments.

Raman spectroscopy and group and basis-restricted non negative matrix factorisation identifies radiation induced metabolic changes in human cancer cells

This work combines single cell Raman spectroscopy (RS) with group and basis restricted non-negative matrix factorisation (GBR-NMF) to identify individual biochemical changes associated with radiation exposure in three human cancer cell lines. The cell lines analysed were derived from lung (H460), breast (MCF7) and prostate (LNCaP) tissue and are known to display varying degrees of radio sensitivity due to the inherent properties of each cell type. The GBR-NMF approach involves the deconstruction of Raman spectra into component biochemical bases using a library of Raman spectra of known biochemicals present in the cells. Subsequently, scores are obtained on each of these bases which can be directly correlated with the contribution of each chemical to the overall Raman spectrum. We validated GBR-NMF through the correlation of GBR-NMF-derived glycogen scores with scores that were previously observed using principal component analysis (PCA). Phosphatidylcholine, glucose, arginine and asparagine showed a distinct differential score pattern between radio-resistant and radio-sensitive cell types. In summary, the GBR-NMF approach allows for the monitoring of individual biochemical radiation-response dynamics previously unattainable with more traditional PCA-based approaches.

Physicochemical damage and early-stage biological response to X-ray radiation studied in prostate cancer cells by Raman spectroscopy

Exposure to ionizing radiation significantly affects biochemistry of cancer cells. The effect of irradiation can be divided into two stages, that is, the physicochemical stage and the biological response. Both effects induce different biochemical changes in the cells and should be analyzed as two separate phenomena. Thus, in the current study, Raman spectroscopy of prostate cancer cells fixed before (the physicochemical damage model) and just after (the biological response model) irradiation was undertaken to compare biochemical composition of irradiated cancer cells at both stages. Spectroscopic analysis of the cells was performed separately for cytoplasmic and nuclear regions. Biochemical changes of irradiated cells were analyzed using partial least squares regression (PLSR) method on the basis of the collected Raman spectra. Regression coefficients were therefore used to describe differences and similarities between biochemical composition of cancer cells undergoing the physicochemical stage and biological response. Additionally, PLSR models of both phenomena were compared for linear dose-dependence and a cross prediction.

Unveiling dose- and time-dependent osteosarcoma cell responses to the γ-secretase inhibitor, DAPT, by confocal Raman microscopy

Using confocal Raman micro-spectroscopy, this study aims to elucidate the cellular responses of the γ-secretase inhibitor, N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT), in osteosarcoma (OS) cells in a dose- and time-dependent manner. The K7M2 murine OS cell line was treated with different DAPT doses (0, 10, 20, and 40 μM) for 24 and 48 hours before investigations. Significant compositional changes (nucleic acids, protein and lipid) after DAPT treatment were addressed, which testified inhibitory effect of DAPT on the growth of OS cells. Moreover, both partial least squares-discriminant analysis (PLS-DA) and principal component analysis-linear discriminant analysis (PCA-LDA) analyses revealed governing composition variations among groups by distinguishing their spectral characteristics. Furthermore, by adopting leave-one-out cross validation method, it is shown that PLS-DA exhibited more classification capacity than PCA-LDA algorithm. Hence, by understanding the DAPT-based cellular variations, the achieved results provided an experimental foundation to establish new DAPT-based anticancer therapeutic strategies, and preclinical Raman analytical methodologies on drug-cell interactions.

Synergetic Influence of Bismuth Oxide Nanoparticles, Cisplatin and Baicalein-Rich Fraction on Reactive Oxygen Species Generation and Radiosensitization Effects for Clinical Radiotherapy Beams

Purpose

This study aimed to quantify synergetic effects induced by bismuth oxide nanoparticles (BiONPs), cisplatin (Cis) and baicalein-rich fraction (BRF) natural-based agent on the reactive oxygen species (ROS) generation and radiosensitization effects under irradiation of clinical radiotherapy beams of photon, electron and HDR-brachytherapy. The combined therapeutic responses of each compound and clinical radiotherapy beam were evaluated on breast cancer and normal fibroblast cell line.

Methods

In this study, individual BiONPs, Cis, and BRF, as well as combinations of BiONPs-Cis (BC), BiONPs-BRF (BB) and BiONPs-Cis-BRF (BCB) were treated to the cells before irradiation using HDR brachytherapy with 0.38 MeV iridium-192 source, 6 MV photon beam and 6 MeV electron beam. The individual or synergetic effects from the application of the treatment components during the radiotherapy were elucidated by quantifying the ROS generation and radiosensitization effects on MCF-7 and MDA-MB-231 breast cancer cell lines as well as NIH/3T3 normal cell line.

Results

The ROS generated in the presence of Cis stimulated the most substantial amount of ROS compared to the BiONPs and BRF. Meanwhile, the combination of the components had induced the higher ROS levels for photon beam than the brachytherapy and electron beam. The highest ROS enhancement relative to the control is attributable to the presence of BC combination in MDA-MB-231 cells, in comparison to the BB and BCB combinations. The radiosensitization effects which were quantified using the sensitization enhancement ratio (SER) indicate the highest value by BC in MCF-7 cells, followed by BCB and BB treatment. The radiosensitization effects are found to be more prominent for brachytherapy in comparison to photon and electron beam.

Conclusion

The BiONPs, Cis and BRF are the potential radiosensitizers that could improve the efficiency of radiotherapy to eradicate the cancer cells. The combination of these potent radiosensitizers might produce multiple effects when applied in radiotherapy. The BC combination is found to have the highest SER, followed by the BCB combination. This study is also the first to investigate the effect of BRF in combination with BiONPs (BB) and BC (BCB) treatments.

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

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

Raman spectroscopy combined with multivariate analysis to study the biochemical mechanism of lung cancer microwave ablation

Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.

Raman profile alterations of irradiated human nasopharyngeal cancer cells detected with laser tweezer Raman spectroscopy

Radiotherapy has been widely used for nasopharyngeal carcinoma (NPC) treatment, which causes DNA damage and alterations of macromolecules of cancer cells. However, the Raman profile alterations of irradiated NPC cells remain unclear. In the present study, we used laser tweezers Raman spectroscopy (LTRS) to monitor internal structural changes and chemical modifications in NPC cells after exposure at a clinical dose (2.3 Gy) to X-ray irradiation (IR) at a single-cell level. Two types of NPC cell lines, CNE2 (EBV-negative cell line) and C666-1 (EBV-positive cell line), were used. The Raman spectra of cells before and after radiation treatment were recorded by LTRS. The analysis of spectral differences indicated that the IR caused Raman profile alterations of intracellular proteins, DNA base and lipids. Moreover, by using the multivariate statistical analysis including principal component analysis (PCA) and linear discriminant analysis (LDA) algorithm, an accuracy of 90.0% for classification between CNE2 cells before and after IR could be achieved, which was 10% better than that of C666-1 cells. The results demonstrated that CNE2 cells were more sensitive to IR in comparison to C666-1 cells, providing useful information for creating a treatment strategy in clinical practice. This exploratory study suggested that LTRS combined with multivariate statistical analysis would be a novel and effective tool for evaluating the radiotherapeutic effect on tumor cells, and for detection of the corresponding alterations at the molecular level.

Laser tweezer Raman spectroscopy combined with multivariate statistical analysis was used for evaluating the radiotherapeutic effect on a single tumor cell.

Optical Imaging Approaches to Investigating Radiation Resistance

Radiation therapy is frequently the first line of treatment for over 50% of cancer patients. While great advances have been made in improving treatment response rates and reducing damage to normal tissue, radiation resistance remains a persistent clinical problem. While hypoxia or a lack of tumor oxygenation has long been considered a key factor in causing treatment failure, recent evidence points to metabolic reprogramming under well-oxygenated conditions as a potential route to promoting radiation resistance. In this review, we present recent studies from our lab and others that use high-resolution optical imaging as well as clinical translational optical spectroscopy to shine light on the biological basis of radiation resistance. Two-photon microscopy of endogenous cellular metabolism has identified key changes in both mitochondrial structure and function that are specific to radiation-resistant cells and help promote cell survival in response to radiation. Optical spectroscopic approaches, such as diffuse reflectance and Raman spectroscopy have demonstrated functional and molecular differences between radiation-resistant and sensitive tumors in response to radiation. These studies have uncovered key changes in metabolic pathways and present a viable route to clinical translation of optical technologies to determine radiation resistance at a very early stage in the clinic.

Effects of silver nanoparticles coated with anti-HER2 on irradiation efficiency of SKBR3 breast cancer cells

Breast cancer is the second cause of death in the world. Ionising radiation is a potent mutagen that can cause DNA damage, chromosomes breakage, and cell death. In the present study, radiotherapy and nanoparticle-antibodies (ABs) have been combined to enhance the efficacy of cancer cell treatment. Silver nanoparticles (SNP) were synthesised, coated with anti-HER2, and then characterised with different techniques such as X-ray diffraction, dynamic light scattering, transmission electron microscopy, Fourier transform infrared, and UV-Vis spectroscopy. SKBR3 cells were irradiated with cobalt-60 in the presence of nanoparticle-AB as the drug. Cell viability was measured using the diphenyltetrazolium bromide assay, and the cellular status was assessed by Raman spectroscopy. Irradiation considerably decreased cell viability proportionate to the dose increase and post-irradiation time. The surface-enhanced Raman spectroscopy increased the signal in the presence of SNP. Increasing the dose to 2 Gy increased the irradiation resistance, and higher dose increases (4 and 6 Gy) enhanced the irradiation sensitivity. Moreover, the cellular changes induced by irradiation in the presence of the drug were stable after 48 h. The authors results introduced the combination of the drug with radiation as an effective treatment for cancer and Raman spectroscopy as a suitable tool to diagnose effective irradiation doses.

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.

Raman spectroscopy detects metabolic signatures of radiation response and hypoxic fluctuations in non-small cell lung cancer

BACKGROUND

Radiation therapy is a standard form of treating non-small cell lung cancer, however, local recurrence is a major issue with this type of treatment. A better understanding of the metabolic response to radiation therapy may provide insight into improved approaches for local tumour control. Cyclic hypoxia is a well-established determinant that influences radiation response, though its impact on other metabolic pathways that control radiosensitivity remains unclear.

METHODS

We used an established Raman spectroscopic (RS) technique in combination with immunofluorescence staining to measure radiation-induced metabolic responses in human non-small cell lung cancer (NSCLC) tumour xenografts. Tumours were established in NOD.CB17-Prkdcscid/J mice, and were exposed to radiation doses of 15 Gy or left untreated. Tumours were harvested at 2 h, 1, 3 and 10 days post irradiation.

RESULTS

We report that xenografted NSCLC tumours demonstrate rapid and stable metabolic changes, following exposure to 15 Gy radiation doses, which can be measured by RS and are dictated by the extent of local tissue oxygenation. In particular, fluctuations in tissue glycogen content were observed as early as 2 h and as late as 10 days post irradiation. Metabolically, this signature was correlated to the extent of tumour regression. Immunofluorescence staining for γ-H2AX, pimonidazole and carbonic anhydrase IX (CAIX) correlated with RS-identified metabolic changes in hypoxia and reoxygenation following radiation exposure.

CONCLUSION

Our results indicate that RS can identify sequential changes in hypoxia and tumour reoxygenation in NSCLC, that play crucial roles in radiosensitivity.

Raman spectroscopy for the evaluation of the radiobiological sensitivity of normal human breast cells at different time points after irradiation by a clinical proton beam

Radiobiological effects occurring in normal human breast cells exposed to a low dose of a clinical proton beam are detectable by means of Raman spectra and the ratiometric analysis of Raman peak intensities.

Applications of Raman spectroscopy in cancer diagnosis

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

Assessment of Radiation Resistance and Therapeutic Targeting of Cancer Stem Cells: A Raman Spectroscopic Study of Glioblastoma

Radiation is the standard therapy used for treating Glioblastoma (GBM), a grade IV brain cancer. Glioma Stem-like Cells (GSCs), an integral part of GBM, enforces resistance to radiation therapy of GBM. Studying the differential biomolecular composition of GSCs with varying levels of radiation sensitivity can aid in identifying the molecules and their associated pathways which impose resistance to cells thereby unraveling new targets which would serve as potential adjuvant therapy. Raman spectroscopy being a noninvasive, label free technique can determine the biomolecular constituent of cells under live conditions. In this study, we have deduced Raman spectral signatures to predict the radiosensitivity of any GSC accurately using the inherent and radiation induced biomolecular composition. Our study identified the differential regulation of several biomolecules which can be potential targets for adjuvant therapy. We radiosensitized the resistant GSCs using small molecule inhibitors specific to the metabolic pathways of these biomolecules. Efficient antitumor therapy can be attained with lower dosage of radiation along with these inhibitors and thus improving the survival rate of GBM patients with reduced side-effects from radiation.

Upcoming imaging concepts and their impact on treatment planning and treatment response in radiation oncology

For 2018, the American Cancer Society estimated that there would be approximately 1.7 million new diagnoses of cancer and about 609,640 cancer-related deaths in the United States. By 2030 these numbers are anticipated to exceed a staggering 21 million annual diagnoses and 13 million cancer-related deaths. The three primary therapeutic modalities for cancer treatments are surgery, chemotherapy, and radiation therapy. Individually or in combination, these treatment modalities have provided and continue to provide curative and palliative care to the myriad victims of cancer.

Today, CT-based treatment planning is the primary means through which conventional photon radiation therapy is planned. Although CT remains the primary treatment planning modality, the field of radiation oncology is moving beyond the sole use of CT scans to define treatment targets and organs at risk. Complementary tissue scans, such as magnetic resonance imaging (MRI) and positron electron emission (PET) scans, have all improved a physician’s ability to more specifically identify target tissues, and in some cases, international guidelines have even been issued. Moreover, efforts to combine PET and MR to define solid tumors for radiotherapy planning and treatment evaluation are also gaining traction.

Keeping these advances in mind, we present brief overviews of other up-and-coming key imaging concepts that appear promising for initial treatment target definition or treatment response from radiation therapy.

The molecular cues for the biological effects of ionizing radiation dose and post-irradiation time on human breast cancer SKBR3 cell line: A Raman spectroscopy study

Radiotherapy is one of the main modalities of cancer treatment. The utility of Raman spectroscopy (RS) for detecting the distinct radiobiological responses in human cancer cells is currently under investigation. RS holds great promises to provide good opportunities for personalizing radiotherapy treatments. Here, we report the effects of the radiation dose and post-irradiation time on the molecular changes in the human breast cancer SKBR3 cells, using RS. The SKBR3 cells were irradiated by gamma radiation with different doses of 0, 1, 2, 4, and 6 Gy. The Raman signals were acquired 24 and 48 h after the gamma radiation. The collected Raman spectra were analyzed by different statistical methods such as principal component analysis, linear discriminant analysis, and genetic algorithm. A thorough analysis of the obtained Raman signals revealed that 2 Gy of gamma radiation induces remarkable molecular and structural changes in the SKBR3 cells. We found that the wavenumbers in the range of 1000-1400 cm^-1 in Raman spectra are selective for discriminating between the effects of the different doses of irradiation. The results also revealed that longer post-irradiation time leads to the relaxation of the cells to their initial state. The molecular changes that occurred in the 2Gy samples were mostly reversible. On the other hand, the exposure to doses higher than 4Gy induced serious irreversible changes, mainly seen in 2700-2800 cm^-1 in Raman spectra. The classification models developed in this study would help to predict the radiation-based molecular changes induced in the cancer cells by only using RS. Also, this designed framework may facilitate the process of biodosimetry.

Comparison of human lung cancer cell radiosensitivity after irradiations with therapeutic protons and carbon ions

The aim of this study was to investigate effects of irradiations with the therapeutic proton and carbon ion beams in two non-small cell lung cancers, CRL5876 adenocarcinoma and HTB177 large cell lung carcinoma. The DNA damage response dynamics, cell cycle regulation, and cell death pathway activation were followed. Viability of both cell lines was lower after carbon ions compared to the therapeutic proton irradiations. HTB177 cells showed higher recovery than CRL5876 cells seven days following the treatments, but the survival rates of both cell lines were lower after exposure to carbon ions with respect to therapeutic protons. When analyzing cell cycle distribution of both CRL5876 and HTB177 cells, it was noticed that therapeutic protons predominantly induced G1 arrest, while the cells after carbon ions were arrested in G2/M phase. The results illustrated that differences in the levels of phosphorylated H2AX, a double-strand break marker, exist after therapeutic proton and carbon ion irradiations. We also observed dose- and time-dependent increase in the p53 and p21 levels after applied irradiations. Carbon ions caused larger increase in the quantity of p53 and p21 compared to therapeutic protons. These results suggested that various repair mechanisms were induced in the treated cells. Considering the fact that we have not observed any distinct change in the Bax/Bcl-2 ratio following irradiations, it seemed that different types of cell death were involved in the response to the two types of irradiations that were applied.

Differences and Relationships Between Normal and Atypical Ductal Hyperplasia, Ductal Carcinoma In Situ, and Invasive Ductal Carcinoma Tissues in the Breast Based on Raman Spectroscopy

The aim of this study was to find the differences and relationships between normal, atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) lesions of the breast based on biochemical characteristics determined by Raman spectroscopy (RS). After collecting 39 frozen sections from patients who underwent surgical resection or mammotome biopsy, nine normal tissues, seven ADH, eight DCIS, and 15 IDC lesions were detected using confocal RS. We then used leave-one-out cross-validation (LOOCV) and radial basis function (RBF) to build a support vector machine (SVM) diagnosis model. Pronounced mean Raman spectra differences were observed between normal tissues, ADH, DCIS, and IDC tissues. Most noticeable was the increased protein and reduced lipid levels of ADH tissues compared to normal tissues. The major spectra differences in ADH, DCIS, and IDC spectrograms were evidenced by a red shift with a broad peak of CH2 (1301 cm^-1), the intensity of the stretching vibration peak of carotenoids (1526 cm^-1), a relatively strong band of amide-I (1656 cm^-1), and the nuclear (882 cm^-1) acid peak. Atypical ductal hyperplasia tissues had the largest constituent variations between subjects. During the disease progression, IDC tissues have smaller inter-subject constituent variations than DCIS and ADH tissues. The overall accuracy of SVM model is 74.39%. The sensitivities of normal tissue, ADH, DCIS, and IDC are 62.5%, 50%, 90%, and 66.7%, respectively. The specificities of normal tissue, ADH, DCIS, and IDC are 100%, 100%, 66.7%, and 89.06%, respectively. Atypical ductal hyperplasia shows significant differences and the relationship between normal tissue and malignant disease. Further study to explain the biochemical relationships between these differences will shed more light into a better understanding of the mechanism by which ADH converts to DCIS and to IDC.

Raman spectroscopy identifies radiation response in human non-small cell lung cancer xenografts

External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.

Vibrational spectroscopy in sensing radiobiological effects: analyses of targeted and non-targeted effects in human keratinocytes

Modern models of radiobiological effects include mechanisms of damage initiation, sensing and repair, for those cells that directly absorb ionizing radiation as well as those that experience molecular signals from directly irradiated cells. In the former case, the effects are termed targeted effects while, in the latter, non-targeted effects. It has emerged that phenomena occur at low doses below 1 Gy in directly irradiated cells that are associated with cell-cycle-dependent mechanisms of DNA damage sensing and repair. Likewise in non-targeted bystander-irradiated cells the effect saturates at 0.5 Gy. Both effects at these doses challenge the limits of detection of vibrational spectroscopy. In this paper, a study of the sensing of both targeted and non-targeted effects in HaCaT human keratinocytes irradiated with gamma ray photons is conducted with vibrational spectroscopy. In the case of directly irradiated cells, it is shown that the HaCaT cell line does exhibit both hyperradiosensitivity and increased radioresistance at low doses, a transition between the two effects occurring at a dose of 200 mGy, and that cell survival and other physiological effects as a function of dose follow the induced repair model. Both Raman and FTIR signatures are shown to follow a similar model, suggesting that the spectra include signatures of DNA damage sensing and repair. In bystander-irradiated cells, pro- and anti-apoptotic signalling and mechanisms of ROS damage were inhibited in the mitogen-activated protein kinase (MAPK) transduction pathway. It is shown that Raman spectral profiles of bystander-irradiated cells are correlated with markers of bystander signalling and molecular transduction. This work demonstrates for the first time that both targeted and non-targeted effects of ionizing radiation damage are detected by vibrational spectroscopy in vitro.

Radiation-Induced Glycogen Accumulation Detected by Single Cell Raman Spectroscopy Is Associated with Radioresistance that Can Be Reversed by Metformin

Altered cellular metabolism is a hallmark of tumor cells and contributes to a host of properties associated with resistance to radiotherapy. Detection of radiation-induced biochemical changes can reveal unique metabolic pathways affecting radiosensitivity that may serve as attractive therapeutic targets. Using clinically relevant doses of radiation, we performed label-free single cell Raman spectroscopy on a series of human cancer cell lines and detected radiation-induced accumulation of intracellular glycogen. The increase in glycogen post-irradiation was highest in lung (H460) and breast (MCF7) tumor cells compared to prostate (LNCaP) tumor cells. In response to radiation, the appearance of this glycogen signature correlated with radiation resistance. Moreover, the buildup of glycogen was linked to the phosphorylation of GSK-3β, a canonical modulator of cell survival following radiation exposure and a key regulator of glycogen metabolism. When MCF7 cells were irradiated in the presence of the anti-diabetic drug metformin, there was a significant decrease in the amount of radiation-induced glycogen. The suppression of glycogen by metformin following radiation was associated with increased radiosensitivity. In contrast to MCF7 cells, metformin had minimal effects on both the level of glycogen in H460 cells following radiation and radiosensitivity. Our data demonstrate a novel approach of spectral monitoring by Raman spectroscopy to assess changes in the levels of intracellular glycogen as a potential marker and resistance mechanism to radiation therapy.

Raman spectroscopic studies on screening of myopathies

Myopathies are among the major causes of mortality in the world. There is no complete cure for this heterogeneous group of diseases, but a sensitive, specific, and fast diagnostic tool may improve therapy effectiveness. In this study, Raman spectroscopy is applied to discriminate between muscle mutants in Drosophila on the basis of associated changes at the molecular level. Raman spectra were collected from indirect flight muscles of mutants, upheld(1) (up(1)), heldup(2) (hdp(2)), myosin heavy chain(7) (Mhc(7)), actin88F(KM88) (Act88F(KM88)), upheld(101) (up(101)), and Canton-S (CS) control group, for both 2 and 12 days old flies. Difference spectra (mutant minus control) of all the mutants showed an increase in nucleic acid and β-sheet and/or random coil protein content along with a decrease in α-helix protein. Interestingly, the 12th day samples of up(1) and Act88F(KM88) showed significantly higher levels of glycogen and carotenoids than CS. A principal components based linear discriminant analysis classification model was developed based on multidimensional Raman spectra, which classified the mutants according to their pathophysiology and yielded an overall accuracy of 97% and 93% for 2 and 12 days old flies, respectively. The up(1) and Act88F(KM88) (nemaline-myopathy) mutants form a group that is clearly separated in a linear discriminant plane from up(101) and hdp(2) (cardiomyopathy) mutants. Notably, Raman spectra from a human sample with nemaline-myopathy formed a cluster with the corresponding Drosophila mutant (up(1)). In conclusion, this is the first demonstration in which myopathies, despite their heterogeneity, were screened on the basis of biochemical differences using Raman spectroscopy.

A Raman spectroscopic study of cell response to clinical doses of ionizing radiation

The drive toward personalized radiation therapy (RT) has created significant interest in determining patient-specific tumor and normal tissue responses to radiation. Raman spectroscopy (RS) is a non-invasive and label-free technique that can detect radiation response through assessment of radiation-induced biochemical changes in tumor cells. In the current study, single-cell RS identified specific radiation-induced responses in four human epithelial tumor cell lines: lung (H460), breast (MCF-7, MDA-MB-231), and prostate (LNCaP), following exposure to clinical doses of radiation (2-10 Gy). At low radiation doses (2 Gy), H460 and MCF-7 cell lines showed an increase in glycogen-related spectral features, and the LNCaP cell line showed a membrane phospholipid-related radiation response. In these cell lines, only spectral information from populations receiving 10 Gy or less was required to identify radiation-related features using principal component analysis (PCA). In contrast, the MDA-MB-231 cell line showed a significant increase in protein relative to nucleic acid and lipid spectral features at doses of 6 Gy or higher, and high-dose information (30, 50 Gy) was required for PCA to identify this biological response. The biochemical nature of the radiation-related changes occurring in cells exposed to clinical doses was found to segregate by status of p53 and radiation sensitivity. Furthermore, the utility of RS to identify a biological response in human tumor cells exposed to therapeutic doses of radiation was found to be governed by the extent of the biochemical changes induced by a radiation response and is therefore cell line specific. The results of this study demonstrate the utility and effectiveness of single-cell RS to identify and measure biological responses in tumor cells exposed to standard radiotherapy doses.

Making colourful sense of Raman images of single cells

We demonstrate how changes in the application of colour shading can dramatically alter Raman images of single human keratinocytes cells.

Vision 20/20: the role of Raman spectroscopy in early stage cancer detection and feasibility for application in radiation therapy response assessment

Raman spectroscopy is an optical technique capable of identifying chemical constituents of a sample by their unique set of molecular vibrations. Research on the applicability of Raman spectroscopy in the differentiation of cancerous versus normal tissues has been ongoing for many years, and has yielded successful results in the context of prostate, breast, brain, skin, and head and neck cancers as well as pediatric tumors. Recently, much effort has been invested on developing noninvasive "Raman" probes to provide real-time diagnosis of potentially cancerous tumors. In this regard, it is feasible that the Raman technique might one day be used to provide rapid, minimally invasive real-time diagnosis of tumors in patients. Raman spectroscopy is relatively new to the field of radiation therapy. Recent work involving cell lines has shown that the Raman technique is able to identify proteins and other markers affected by radiation therapy. Although this work is preliminary, one could ask whether or not the Raman technique might be used to identify molecular markers that predict radiation response. This paper provides a brief review of Raman spectroscopic investigations in cancer detection, benefits and limitations of this method, advances in instrument development, and also preliminary studies related to the application of this technology in radiation therapy response assessment.

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

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

Raman microspectroscopy: shining a new light on reproductive medicine

BACKGROUND The last 20 years have seen an enormous upsurge in the number of publications reporting findings obtained by Raman spectroscopy, a non-invasive, non-destructive method which uses the inelastic scattering of light to provide a 'fingerprint' of the sample's chemical composition and constituents. Long neglected because of practical difficulties, the technique has been transformed by recent technological advances into a powerful analytical tool capable of opening avenues of investigation that were previously out of the reach of biomedical scientists. Beyond introducing the approach and describing its relative merits and weaknesses, the aim of this review is to provide a spur for discussion of what may become an invaluable tool for biomedical investigations. METHODS A comprehensive review of the literature was conducted searching PubMed and Ovid databases using numerous MeSH terms associated with reproductive medicine. Furthermore, the reference lists of all reported literature were explored. The searches were restricted to English language articles published in the last 50 years. RESULTS Beginning with simple characterizations of biologically and medically important substances, aided by increasing technological sophistication, the use of Raman spectroscopy in biomedicine has quickly expanded to the investigation of complex biochemical interactions, the assessment of organelles and now the evaluation of living cells and tissue. The first Raman investigations of reproductive organs were primarily oncological in nature; however, the past few years have seen an increase in the application of the technique for the assessment and evaluation of both male and female gametes. In particular, progress has been made in the characterization, identification and localization of sperm nuclear DNA damage. CONCLUSIONS The use of Raman spectroscopy has already provided many tantalizing glimpses into the potential that the technique has to answer many of the unresolved issues in investigative and therapeutic reproductive medicine. However, without stringent assessment and the clear representation of the methods' findings, their true meaning cannot be revealed nor should any conclusions be hastily derived. For the potential of Raman microspectroscopy to be truly realized, the dependability and reliability of the technique and its results can only be ascertained by multidisciplinary collaborations that undertake carefully conducted, controlled and analysed studies.