Prediction of radiotherapy response in cervix cancer by Raman spectroscopy: A pilot study

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network

Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy resistance. Identifying biochemical signatures associated with tumour radioresistance may assist with the development of targeted treatment strategies to improve clinical outcomes. Raman spectroscopy (RS) can monitor post-irradiation biomolecular changes and signatures of radiation response in tumour cells in a label-free manner. Convolutional Neural Networks (CNN) perform feature extraction directly from data in an end-to-end learning manner, with high classification performance. Furthermore, recently developed CNN explainability techniques help visualize the critical discriminative features captured by the model. In this work, a CNN is developed to characterize tumour response to radiotherapy based on its degree of radioresistance. The model was trained to classify Raman spectra of three human tumour cell lines as radiosensitive (LNCaP) or radioresistant (MCF7, H460) over a range of treatment doses and data collection time points. Additionally, a method based on Gradient-Weighted Class Activation Mapping (Grad-CAM) was used to determine response-specific salient Raman peaks influencing the CNN predictions. The CNN effectively classified the cell spectra, with accuracy, sensitivity, specificity, and F1 score exceeding 99.8%. Grad-CAM heatmaps of H460 and MCF7 cell spectra (radioresistant) exhibited high contributions from Raman bands tentatively assigned to glycogen, amino acids, and nucleic acids. Conversely, heatmaps of LNCaP cells (radiosensitive) revealed activations at lipid and phospholipid bands. Finally, Grad-CAM variable importance scores were derived for glycogen, asparagine, and phosphatidylcholine, and we show that their trends over cell line, dose, and acquisition time agreed with previously established models. Thus, the CNN can accurately detect biomolecular differences in the Raman spectra of tumour cells of varying radiosensitivity without requiring manual feature extraction. Finally, Grad-CAM may help identify metabolic signatures associated with the observed categories, offering the potential for automated clinical tumour radiation response characterization.

Effect of pre-analytical variables on Raman and FTIR spectral content of lymphocytes

The use of Fourier transform infrared (FTIR) and Raman spectroscopy (RS) for the analysis of lymphocytes in clinical applications is increasing in the field of biomedicine. The pre-analytical phase, which is the most vulnerable stage of the testing process, is where most errors and sample variance occur; however, it is unclear how pre-analytical variables affect the FTIR and Raman spectra of lymphocytes. In this study, we evaluated how pre-analytical procedures undertaken before spectroscopic analysis influence the spectral integrity of lymphocytes purified from the peripheral blood of male volunteers (n = 3). Pre-analytical variables investigated were associated with (i) sample preparation, (blood collection systems, anticoagulant, needle gauges), (ii) sample storage (fresh or frozen), and (iii) sample processing (inter-operator variability, time to lymphocyte isolation). Although many of these procedural pre-analytical variables did not alter the spectral signature of the lymphocytes, evidence of spectral effects due to the freeze-thaw cycle, in vitro culture inter-operator variability and the time to lymphocyte isolation was observed. Although FTIR and RS possess clinical potential, their translation into a clinical environment is impeded by a lack of standardisation and harmonisation of protocols related to the preparation, storage, and processing of samples, which hinders uniform, accurate, and reproducible analysis. Therefore, further development of protocols is required to successfully integrate these techniques into current clinical workflows.

Raman Spectroscopy for Early Detection of Cervical Cancer, a Global Women’s Health Issue—A Review

This review focuses on recent advances and future perspectives in the use of Raman spectroscopy for cervical cancer, a global women’s health issue. Cervical cancer is the fourth most common women’s cancer in the world, and unfortunately mainly affects younger women. However, when detected at the early precancer stage, it is highly treatable. High-quality cervical screening programmes and the introduction of the human papillomavirus (HPV) vaccine are reducing the incidence of cervical cancer in many countries, but screening is still essential for all women. Current gold standard methods include HPV testing and cytology for screening, followed by colposcopy and histopathology for diagnosis. However, these methods are limited in terms of sensitivity/specificity, cost, and time. New methods are required to aid clinicians in the early detection of cervical precancer. Over the past 20 years, the potential of Raman spectroscopy together with multivariate statistical analysis has been shown for the detection of cervical cancer. This review discusses the research to date on Raman spectroscopic approaches for cervical cancer using exfoliated cells, biofluid samples, and tissue ex vivo and in vivo.

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 spectroscopy and convolutional neural networks for monitoring biochemical radiation response in breast tumour xenografts

Tumour cells exhibit altered metabolic pathways that lead to radiation resistance and disease progression. Raman spectroscopy (RS) is a label-free optical modality that can monitor post-irradiation biomolecular signatures in tumour cells and tissues. Convolutional Neural Networks (CNN) perform automated feature extraction directly from data, with classification accuracy exceeding that of traditional machine learning, in cases where data is abundant and feature extraction is challenging. We are interested in developing a CNN-based predictive model to characterize clinical tumour response to radiation therapy based on their degree of radiosensitivity or radioresistance. In this work, a CNN architecture is built for identifying post-irradiation spectral changes in Raman spectra of tumour tissue. The model was trained to classify irradiated versus non-irradiated tissue using Raman spectra of breast tumour xenografts. The CNN effectively classified the tissue spectra, with accuracies exceeding 92.1% for data collected 3 days post-irradiation, and 85.0% at day 1 post-irradiation. Furthermore, the CNN was evaluated using a leave-one-out- (mouse, section or Raman map) validation approach to investigate its generalization to new test subjects. The CNN retained good predictive accuracy (average accuracies 83.7%, 91.4%, and 92.7%, respectively) when little to no information for a specific subject was given during training. Finally, the classification performance of the CNN was compared to that of a previously developed model based on group and basis restricted non-negative matrix factorization and random forest (GBR-NMF-RF) classification. We found that CNN yielded higher classification accuracy, sensitivity, and specificity in mice assessed 3 days post-irradiation, as compared with the GBR-NMF-RF approach. Overall, the CNN can detect biochemical spectral changes in tumour tissue at an early time point following irradiation, without the need for previous manual feature extraction. This study lays the foundation for developing a predictive framework for patient radiation response monitoring.

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.

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.

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.

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.

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.

Monitoring Breast Cancer Response to Treatment Using Stokes Shift Spectroscopy of Blood Plasma

With the emerging trend of personalized cancer treatment, there is a need to develop noninvasive/minimally invasive techniques for treatment monitoring. In this regard, in this work fluorescence analysis of blood plasma of breast cancer patients has been used for the evaluation of response to treatment. This approach delivers information not only about the change in biochemical constituents but also about the altered metabolic pathway. Spectral deconvolution method is employed to compute the fluorescence intensity, peak wavelength, and full-width half maxima for different endogenous fluorophores. The fluorescence measurements were made on blood plasma collected from 10 normal subjects, 10 pre-treated cancer patients, and 10 post-treated patients. Besides, variations in relative concentration of tryptophan, collagen, NADH, and FAD, peak shifts and broadening of peaks are observed for tryptophan, NADH, and FAD, in blood plasma of pre-treated cancer patients indicating both biochemical and microenvironmental changes at cellular level. Further, the spectral profile of blood plasma of post-treated patients found to be similar to blood plasma of normal subjects. Linear discriminant analysis showed that pre-treated and post-treated breast cancer is discriminated with a sensitivity and specificity of 100% and 100% respectively.

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.

Label-Free Raman Spectroscopy Reveals Signatures of Radiation Resistance in the Tumor Microenvironment

Delay in the assessment of tumor response to radiotherapy continues to pose a major challenge to quality of life for patients with nonresponsive tumors. Here, we exploited label-free Raman spectroscopic mapping to elucidate radiation-induced biomolecular changes in tumors and uncovered latent microenvironmental differences between treatment-resistant and -sensitive tumors. We used isogenic radiation-resistant and -sensitive A549 human lung cancer cells and human head and neck squamous cell carcinoma (HNSCC) cell lines (UM-SCC-47 and UM-SCC-22B, respectively) to grow tumor xenografts in athymic nude mice and demonstrated the molecular specificity and quantitative nature of Raman spectroscopic tissue assessments. Raman spectra obtained from untreated and treated tumors were subjected to chemometric analysis using multivariate curve resolution-alternating least squares (MCR-ALS) and support vector machine (SVM) to quantify biomolecular differences in the tumor microenvironment. The Raman measurements revealed significant and reliable differences in lipid and collagen content postradiation in the tumor microenvironment, with consistently greater changes observed in the radiation-sensitive tumors. In addition to accurately evaluating tumor response to therapy, the combination of Raman spectral markers potentially offers a route to predicting response in untreated tumors prior to commencing treatment. Combined with its noninvasive nature, our findings provide a rationale for in vivo studies using Raman spectroscopy, with the ultimate goal of clinical translation for patient stratification and guiding adaptation of radiotherapy during the course of treatment. SIGNIFICANCE: These findings highlight the sensitivity of label-free Raman spectroscopy to changes induced by radiotherapy and indicate the potential to predict radiation resistance prior to commencing 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.

Unique spectral markers discern recurrent Glioblastoma cells from heterogeneous parent population

An inability to discern resistant cells from bulk tumour cell population contributes to poor prognosis in Glioblastoma. Here, we compared parent and recurrent cells generated from patient derived primary cultures and cell lines to identify their unique molecular hallmarks. Although morphologically similar, parent and recurrent cells from different samples showed variable biological properties like proliferation and radiation resistance. However, total RNA-sequencing revealed transcriptional landscape unique to parent and recurrent populations. These data suggest that global molecular differences but not individual biological phenotype could differentiate parent and recurrent cells. We demonstrate that Raman Spectroscopy a label-free, non-invasive technique, yields global information about biochemical milieu of recurrent and parent cells thus, classifying them into distinct clusters based on Principal-Component-Analysis and Principal-Component-Linear-Discriminant-Analysis. Additionally, higher lipid related spectral peaks were observed in recurrent population. Importantly, Raman spectroscopic analysis could further classify an independent set of naïve primary glioblastoma tumour tissues into non-responder and responder groups. Interestingly, spectral features from the non-responder patient samples show a considerable overlap with the in-vitro generated recurrent cells suggesting their similar biological behaviour. This feasibility study necessitates analysis of a larger cohort of naïve primary glioblastoma samples to fully envisage clinical utility of Raman spectroscopy in predicting therapeutic response.

Clinical instrumentation and applications of Raman spectroscopy

Clinical diagnostic devices provide new sources of information that give insight about the state of health which can then be used to manage patient care. These tools can be as simple as an otoscope to better visualize the ear canal or as complex as a wireless capsule endoscope to monitor the gastrointestinal tract. It is with tools such as these that medical practitioners can determine when a patient is healthy and to make an appropriate diagnosis when he/she is not. The goal of diagnostic medicine then is to efficiently determine the presence and cause of disease in order to provide the most appropriate intervention. The earliest form of medical diagnostics relied on the eye - direct visual observation of the interaction of light with the sample. This technique was espoused by Hippocrates in his 5th century BCE work Epidemics, in which the pallor of a patient's skin and the coloring of the bodily fluids could be indicative of health. In the last hundred years, medical diagnosis has moved from relying on visual inspection to relying on numerous technological tools that are based on various types of interaction of the sample with different types of energy - light, ultrasound, radio waves, X-rays etc. Modern advances in science and technology have depended on enhancing technologies for the detection of these interactions for improved visualization of human health. Optical methods have been focused on providing this information in the micron to millimeter scale while ultrasound, X-ray, and radio waves have been key in aiding in the millimeter to centimeter scale. While a few optical technologies have achieved the status of medical instruments, many remain in the research and development phase despite persistent efforts by many researchers in the translation of these methods for clinical care. Of these, Raman spectroscopy has been described as a sensitive method that can provide biochemical information about tissue state while maintaining the capability of delivering this information in real-time, non-invasively, and in an automated manner. This review presents the various instrumentation considerations relevant to the clinical implementation of Raman spectroscopy and reviews a subset of interesting applications that have successfully demonstrated the efficacy of this technique for clinical diagnostics and monitoring in large (n ≥ 50) in vivo human studies.

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.

Current Advances in the Application of Raman Spectroscopy for Molecular Diagnosis of Cervical Cancer

Raman spectroscopy provides a unique biochemical fingerprint capable of identifying and characterizing the structure of molecules, cells, and tissues. In cervical cancer, it is acknowledged as a promising biochemical tool due to its ability to detect premalignancy and early malignancy stages. This review summarizes the key research in the area and the evidence compiled is very encouraging for ongoing and further research. In addition to the diagnostic potential, promising results for HPV detection and monitoring treatment response suggest more than just a diagnosis prospective. A greater body of evidence is however necessary before Raman spectroscopy is fully validated for clinical use and larger comprehensive studies are required to fully establish the role of Raman spectroscopy in the molecular diagnostics of cervical cancer.

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.

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.

Confocal Raman micro-spectroscopy for rapid and label-free detection of maleic acid-induced variations in human sperm

Confocal Raman microspectroscopy is a valuable analytical tool in biological and medical research, allowing the detection of sample variations without external labels or extensive preparation. To determine whether this method can assess the effect of maleic acid on sperm, we prepared human sperm samples incubated in different concentrations of maleic acid, after which Raman spectra from the various regions of sperm cells were recorded. Following the maleic acid treatment, Raman spectra indicated significant changes. Combined with other means, we found that the structures and chemical compositions of sperm membranes were damaged, and even the sperm DNA was damaged by the incorporation of maleic acid. Thus, this technique can be used for detection and identification of maleic acid-induced changes in human sperm at a molecular level. Although this particular application of Raman microspectroscopy still requires further validation, it has potentially promise as a diagnostic tool for reproductive medicine.

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.

Real-time Raman microspectroscopy scanning of the single live sperm bound to human zona pellucida

OBJECTIVE

To determine if Raman microspectroscopy (RMS) can distinguish sperm bound to the human zona pellucida (ZP) from those unbound sperm.

DESIGN

Paired experiments to compare Raman scanning features of ZP-bound and unbound sperm.

SETTING

Public hospital-based clinical assisted reproduction center.

PATIENT(S)

Sperm samples from ten fertile donors were used in this study.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Sperm-ZP binding, ZP-induced acrosome reaction, and scanning intensity of various regions of sperm.

RESULT(S)

The RMS found two slightly low-intensity regions (800-900 and 3,200-4,000 cm(-1)) shifted to high-intensity grade at the acrosome region of the ZP-bound sperm compared with unbound sperm. Moreover, principal component analysis and statistical analysis showed that the RMS can distinguish the ZP-bound sperm from the unbound sperm.

CONCLUSION(S)

RMS scanning of single live sperm could be used to distinguish ZP-bound sperm from unbound sperm. Thus, RMS may be a useful tool to detect normal functional sperm and to select sperm for intracytoplasmic sperm injection.

Cyclophilin B expression is associated with in vitro radioresistance and clinical outcome after radiotherapy

The tools for predicting clinical outcome after radiotherapy are not yet optimal. To improve on this, we applied the COXEN informatics approach to in vitro radiation sensitivity data of transcriptionally profiled human cells and gene expression data from untreated head and neck squamous cell carcinoma (HNSCC) and bladder tumors to generate a multigene predictive model that is independent of histologic findings and reports on tumor radiosensitivity. The predictive ability of this 41-gene model was evaluated in patients with HNSCC and was found to stratify clinical outcome after radiotherapy. In contrast, this model was not useful in stratifying similar patients not treated with radiation. This led us to hypothesize that expression of some of the 41 genes contributes to tumor radioresistance and clinical recurrence. Hence, we evaluated the expression the 41 genes as a function of in vitro radioresistance in the NCI-60 cancer cell line panel and found cyclophilin B (PPIB), a peptidylprolyl isomerase and target of cyclosporine A (CsA), had the strongest direct correlation. Functional inhibition of PPIB by small interfering RNA depletion or CsA treatment leads to radiosensitization in cancer cells and reduced cellular DNA repair. Immunohistochemical evaluation of PPIB expression in patients with HNSCC was found to be associated with outcome after radiotherapy. This work demonstrates that a novel 41-gene expression model of radiation sensitivity developed in bladder cancer cell lines and human skin fibroblasts predicts clinical outcome after radiotherapy in head and neck cancer patients and identifies PPIB as a potential target for clinical radiosensitization.

Sperm preparation: state-of-the-art--physiological aspects and application of advanced sperm preparation methods

For assisted reproduction technologies (ART), numerous techniques were developed to isolate spermatozoa capable of fertilizing oocytes. While early methodologies only focused on isolating viable, motile spermatozoa, with progress of ART, particularly intracytoplasmic sperm injection (ICSI), it became clear that these parameters are insufficient for the identification of the most suitable spermatozoon for fertilization. Conventional sperm preparation techniques, namely, swim-up, density gradient centrifugation and glass wool filtration, are not efficient enough to produce sperm populations free of DNA damage, because these techniques are not physiological and not modeled on the stringent sperm selection processes taking place in the female genital tract. These processes only allow one male germ cell out of tens of millions to fuse with the oocyte. Sites of sperm selection in the female genital tract are the cervix, uterus, uterotubal junction, oviduct, cumulus oophorus and the zona pellucida. Newer strategies of sperm preparation are founded on: (i) morphological assessment by means of 'motile sperm organelle morphological examination (MSOME)'; (ii) electrical charge; and (iii) molecular binding characteristics of the sperm cell. Whereas separation methods based on electrical charge take advantage of the sperm's adherence to a test tube surface or separate in an electrophoresis, molecular binding techniques use Annexin V or hyaluronic acid (HA) as substrates. Techniques in this category are magnet-activated cell sorting, Annexin V-activated glass wool filtration, flow cytometry and picked spermatozoa for ICSI (PICSI) from HA-coated dishes and HA-containing media. Future developments may include Raman microspectrometry, confocal light absorption and scattering spectroscopic microscopy and polarization microscopy.

Diagnostic applications of Raman spectroscopy

Raman spectroscopy has been widely used in various fields of science. It has been successfully utilized to qualitatively and quantitatively determine the molecular compositions of solid, liquid, and gaseous samples. This review focuses on the diagnostic applications of Raman spectroscopy in the past 5 years, with specific emphasis on transplant allograft rejection and cancer detections. First we introduce the principle of Raman spectroscopy and associated surface enhancement techniques. Various recent biomedical and clinical applications of Raman spectroscopy are then reviewed in detail. Finally, we present the experimental and analytical techniques required to implement Raman spectroscopy in a laboratory.

FROM THE CLINICAL EDITOR

This review focuses on evolving diagnostic applications of Raman spectroscopy with special emphasis on transplant allograft rejection and cancer detection.

Raman Spectroscopy for Clinical Oncology

Cancer is one of the leading causes of death throughout the world. Advancements in early and improved diagnosis could help prevent a significant number of these deaths. Raman spectroscopy is a vibrational spectroscopic technique which has received considerable attention recently with regards to applications in clinical oncology. Raman spectroscopy has the potential not only to improve diagnosis of cancer but also to advance the treatment of cancer. A number of studies have investigated Raman spectroscopy for its potential to improve diagnosis and treatment of a wide variety of cancers. In this paper the most recent advances in dispersive Raman spectroscopy, which have demonstrated promising leads to real world application for clinical oncology are reviewed. The application of Raman spectroscopy to breast, brain, skin, cervical, gastrointestinal, oral, and lung cancers is reviewed as well as a special focus on the data analysis techniques, which have been employed in the studies.

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

This work applies noninvasive single-cell Raman spectroscopy (RS) and principal component analysis (PCA) to analyze and correlate radiation-induced biochemical changes in a panel of human tumour cell lines that vary by tissue of origin, p53 status and intrinsic radiosensitivity. Six human tumour cell lines, derived from prostate (DU145, PC3 and LNCaP), breast (MDA-MB-231 and MCF7) and lung (H460), were irradiated in vitro with single fractions (15, 30 or 50 Gy) of 6 MV photons. Remaining live cells were harvested for RS analysis at 0, 24, 48 and 72 h post-irradiation, along with unirradiated controls. Single-cell Raman spectra were acquired from 20 cells per sample utilizing a 785 nm excitation laser. All spectra (200 per cell line) were individually post-processed using established methods and the total data set for each cell line was analyzed with PCA using standard algorithms. One radiation-induced PCA component was detected for each cell line by identification of statistically significant changes in the PCA score distributions for irradiated samples, as compared to unirradiated samples, in the first 24-72 h post-irradiation. These RS response signatures arise from radiation-induced changes in cellular concentrations of aromatic amino acids, conformational protein structures and certain nucleic acid and lipid functional groups. Correlation analysis between the radiation-induced PCA components separates the cell lines into three distinct RS response categories: R1 (H460 and MCF7), R2 (MDA-MB-231 and PC3) and R3 (DU145 and LNCaP). These RS categories partially segregate according to radiosensitivity, as the R1 and R2 cell lines are radioresistant (SF(2) > 0.6) and the R3 cell lines are radiosensitive (SF(2) < 0.5). The R1 and R2 cell lines further segregate according to p53 gene status, corroborated by cell cycle analysis post-irradiation. Potential radiation-induced biochemical response mechanisms underlying our RS observations are proposed, such as (1) the regulated synthesis and degradation of structured proteins and (2) the expression of anti-apoptosis factors or other survival signals. This study demonstrates the utility of RS for noninvasive radiobiological analysis of tumour cell radiation response, and indicates the potential for future RS studies designed to investigate, monitor or predict radiation response.

In situ visualization of damaged DNA in human sperm by Raman microspectroscopy

BACKGROUND

Beyond determining the percentage of damaged sperm, current methods of DNA assessment are of limited clinical utility as they render the sample unusable. We evaluated Raman microspectroscopy, a laser-based non-invasive technique that provides detailed chemical 'fingerprints' of cells and which potentially could be used for nuclear DNA-based sperm selection.

METHODS

Eight healthy donors provided ejaculates. After system optimization, a minimum of 200 air-dried sperm/sample/donor, prior to/and after UVB irradiation, were assessed by two observers. Spectra were analysed by Principal Component, Spectral Angle and Wavelet Analyses.

RESULTS

Spectra provided a chemical map delineating each sperm head region. Principal Component Analysis showed clear separation between spectra from UV-irradiated and untreated samples whilst averaged data identified two regions of interest (1040 and 1400 cm(-1)). Local spectral analysis around the DNA PO(4) backbone peak (1042 cm(-1)), showed that changes in this region were indicative of DNA damage. Wavelet decomposition confirmed both the 1042 cm(-1) shift and a second UVB susceptible region (1400-1600 cm(-1)) corresponding to protein-DNA interactions. No difference was found between observer measurements.

CONCLUSIONS

Raman microspectroscopy can provide accurate and reproducible assessment of sperm DNA structure and the sites and location of damage.

Near-infrared micro-Raman spectroscopy for in vitro detection of cervical cancer

Near-infrared Raman spectroscopy is a powerful analytical tool for detecting critical differences in biological samples with minimum interference in the Raman spectra from the native fluorescence of the samples. The technique is often suggested as a potential screening tool for cancer. In this article we report in vitro Raman spectra of squamous cells in normal and cancerous cervical human tissue from seven patients, which have good signal-to-noise ratio and which were found to be reproducible. These preliminary results show that several Raman features in these spectra could be used to distinguish cancerous cervical squamous cells from normal cervical squamous cells. In general, the Raman spectra of cervical cancer cells show intensity differences compared to those of normal squamous cell spectra. For example, several well-defined Raman peaks of collagen in the 775 to 975 cm(-1) region are observed in the case of normal squamous cells, but these are below the detection limit of normal Raman spectroscopy in the spectra of invasive cervical cancer cells. In the high frequency 2800 to 3100 cm(-1) region, it is found that the peak area under the CH stretching band is lower by a factor of approximately six in the spectra of cervical cancer cells as compared with that of the normal cells. The Raman chemical maps of regions of cancer and normal cells in the cervical epithelium made from the spectral features in the 775 to 975 cm(-1) and 2800 to 3100 cm(-1) regions are also found to show good correlation with each other.

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

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

Towards oncological application of Raman spectroscopy

As the possibilities in the treatment of cancer continue to evolve, its early detection and correct diagnosis are becoming increasingly important. From the early detection of cancer to the guidance of oncosurgical procedures new sensitive in vivo diagnostic tools are much needed. Many studies report the Raman spectroscopic detection of malignant and premalignant tissues in different sites of the body with high sensitivities. The great appeal of this technique lies in its potential for in vivo clinical implementation. We present an overview of the in vitro and in vivo work on the oncological application of Raman spectroscopy and discuss its potential as a new tool in the clinico-oncological practice. Opportunities for integration of Raman spectroscopy in oncological cure and care as a real-time guidance tool during diagnostic (i.e. biopsy) and therapeutic (surgical resection) modalities as well as technical shortcomings are discussed from a clinician's point of view.