New look inside human breast ducts with Raman imaging. Raman candidates as diagnostic markers for breast cancer prognosis: Mammaglobin, palmitic acid and sphingomyelin

Analysis of spatiotemporal changes mechanism of cell wall biopolymers and monosaccharide components in kiwifruit during Botryosphaeria dothidea infection

To further reveal the interaction mechanism between plants and pathogens, this study used confocal Raman microscopy spectroscopy (CRM) combined with chemometrics to visualize the biopolymers distribution of kiwifruit cell walls at different infection stages at the cellular micro level. Simultaneously, the changes in the content of various monosaccharides in fruit were studied at the molecular level using high-performance liquid chromatography (HPLC). There were significant differences in the composition of various nutrient components in the cell wall structure of kiwifruit at different infection times after infection by Botryosphaeria dothidea. PCA could cluster samples with infection time of 0-9 d into different infection stages, and SVM was used to predict the PCA classification results, the accuracy >96 %. Multivariate curve resolution-alternating least squares (MCR-ALS) helped to identify single substance spectra and concentration signals from mixed spectral signals. The pure substance chemical imaging maps of low methylated pectin (LMP), high methylated pectin (HMP), cellulose, hemicellulose, and lignin were obtained by analyzing the resolved concentration data. The imaging results showed that the lignin content in the kiwifruit cell wall increased significantly to resist pathogens infection after the infection of B. dothidea. With the development of infection, B. dothidea decomposed various substances in the host cell walls, allowing them to penetrate the interior of fruit cells. This caused significant changes in the form, structure, and distribution of various chemicals on the fruit cell walls in time and space. HPLC showed that glucose was the main carbon source and energy substance obtained by pathogens from kiwifruit during infection. The contents of galactose and arabinose, which maintained the structure and function of the fruit cell walls, decreased significantly and the cell wall structure was destroyed in the late stage of pathogens infection. This study provided a new perspective on the cellular structure changes caused by pathogenic infection of fruit and the defense response process of fruit and provided effective references for further research on the mechanisms of host-pathogen interactions in fruit infected by pathogens.

Could Raman spectroscopy investigate the changes of cell oxidative stress status in thyroid diseases? A pilot study on cytological samples

The incidence of thyroid nodules is rapidly increasing worldwide. Raman spectroscopy (RS) is a powerful label-free and non-invasive technique, successfully used for early stage diagnosis. Here, RS is proposed as a tool to investigate the thyroid disease, including neoplasms, through the study of cell oxidative stress (OS), which represents one of the main cancer risk factors. In this study, we enrolled 28 patients, submitted to a first and second thyroid fine needle aspiration (FNA) during follow up. The cytological samples were studied by RS and morphological examination. Typical Raman spectra of thyroid cytological samples are reported and the contribution of oxidized and reduced cytochrome b and c and carotenoids are discussed. On the basis of the evolution of the Raman features over the time lapse between the two FNAs, the 28 patients have been classified into 4 different categories and the most representative case for each category is reported and discussed in detail. For each category, the different Raman intensity ratio between oxidized and reduced cytochromes b and c is reported and associated to different cell OS status, along with the presence of carotenoids. Overall, our results support a correlation among changes in oxidative stress, carotenoids uptake and thyroid diseases, which could inspire new fundamental research on biomarkers and signaling pathways involved in thyroid OS.

Biochemical changes in lipid and protein metabolism caused by mannose-Raman spectroscopy studies

Biochemical analysis of human normal bronchial cells (BEpiC) and human cancer lung cells (A549) has been performed by using Raman spectroscopy and Raman imaging. Our approach provides a biochemical compositional mapping of the main cell components: nucleus, mitochondria, lipid droplets, endoplasmic reticulum, cytoplasm and cell membrane. We proved that Raman spectroscopy and Raman imaging can distinguish successfully BEpiC and A549 cells. In this study, we have focused on the role of mannose in cancer development. It has been shown that changes in the concentration of mannose can regulate some metabolic processes in cells. Presented results suggest lipids and proteins can be considered as Raman biomarkers during lung cancer progression. Analysis obtained for bands 1444 cm-1, and 2854 cm-1 characteristic for lipids and derivatives proved that the addition of mannose reduced levels of these compounds. Results obtained for protein compounds based on bands 858 cm-1, 1004 cm-1 and 1584 cm-1 proved that the addition of mannose increases the values of protein in BEpiC cells and blocks protein glycolisation in A549 cells. Noticing Raman spectral changes in BEpiC and A549 cells supplemented with mannose can help to understand the mechanism of sugar metabolism during cancer development and could play in the future an important role in clinical treatment.

Nutritional Metabolomics in Diet-Breast Cancer Relations: Current Research, Challenges, and Future Directions-A Review

Breast cancer is one of the most common types of cancer in women worldwide, and its incidence is increasing. Diet has been identified as a modifiable risk factor for breast cancer, but the complex interplay between diet, metabolism, and cancer development is not fully understood. Nutritional metabolomics is a rapidly evolving field that can provide insights into the metabolic changes associated with dietary factors and their impact on breast cancer risk. The review's objective is to provide a comprehensive overview of the current research on the application of nutritional metabolomics in understanding the relationship between diet and breast cancer. The search strategy involved querying several electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar. The search terms included combinations of relevant keywords such as "nutritional metabolomics", "diet", "breast cancer", "metabolites", and "biomarkers". In this review, both in vivo and in vitro studies were included, and we summarize the current state of knowledge on the role of nutritional metabolomics in understanding the diet-breast cancer relationship, including identifying specific metabolites and metabolic pathways associated with breast cancer risk. We also discuss the challenges associated with nutritional metabolomics research, including standardization of analytical methods, interpretation of complex data, and integration of multiple-omics approaches. Finally, we highlight future directions for nutritional metabolomics research in studying diet-breast cancer relations, including investigating the role of gut microbiota and integrating multiple-omics approaches. The application of nutritional metabolomics in the study of diet-breast cancer relations, including 2-amino-4-cyano butanoic acid, piperine, caprate, rosten-3β,17β-diol-monosulfate, and γ-carboxyethyl hydrochroman, among others, holds great promise for advancing our understanding of the role of diet in breast cancer development and identifying personalized dietary recommendations for breast cancer prevention, control, and treatment.

A Handheld Visible Resonance Raman Analyzer Used in Intraoperative Detection of Human Glioma

There is still a lack of reliable intraoperative tools for glioma diagnosis and to guide the maximal safe resection of glioma. We report continuing work on the optical biopsy method to detect glioma grades and assess glioma boundaries intraoperatively using the VRR-LRRTM Raman analyzer, which is based on the visible resonance Raman spectroscopy (VRR) technique. A total of 2220 VRR spectra were collected during surgeries from 63 unprocessed fresh glioma tissues using the VRR-LRRTM Raman analyzer. After the VRR spectral analysis, we found differences in the native molecules in the fingerprint region and in the high-wavenumber region, and differences between normal (control) and different grades of glioma tissues. A principal component analysis–support vector machine (PCA-SVM) machine learning method was used to distinguish glioma tissues from normal tissues and different glioma grades. The accuracy in identifying glioma from normal tissue was over 80%, compared with the gold standard of histopathology reports of glioma. The VRR-LRRTM Raman analyzer may be a new label-free, real-time optical molecular pathology tool aiding in the intraoperative detection of glioma and identification of tumor boundaries, thus helping to guide maximal safe glioma removal and adjacent healthy tissue preservation.

Combined Morphological and Spectroscopic Diagnostic of HER2 Expression in Breast Cancer Tissues Based on Label-Free Surface-Enhanced Raman Scattering

Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a combined morphological and spectroscopic diagnostic method based on label-free surface-enhanced Raman scattering (SERS) for HER2 expression in breast cancer is proposed. It can not only quantitively detect HER2 expression in breast cancer tissues by spectroscopic measurements but also give morphological images reflecting the distribution of HER2 in tissues. The results show that the consistency between this method and IHC is 95% and achieves the annotation of tumor regions on tissue sections. This method is time-consuming, quantifiable, intuitive, scalable, and easy to understand. Combined with deep learning approaches, it is expected to promote the development of clinical detection and diagnosis technology for breast cancer and other cancers.

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.

Clinical Use of Raman Spectroscopy Improves Diagnostic Accuracy for Indeterminate Thyroid Nodules

BACKGROUND AND OBJECTIVE

Molecular analysis of thyroid fine-needle aspiration (FNA) specimens is believed to improve the management of indeterminate nodules. Raman spectroscopy (RS) can differentiate benign and malignant thyroid lesions in surgically removed tissues, generating distinctive structural profiles. Herein, the diagnostic performance of RS was tested on FNA biopsies of thyroid gland.

DESIGN

Prospective, blinded, and single-center study.

METHODS

We enrolled 123 patients with indeterminate or more ominous cytologic diagnoses (TIR3A-low-risk indeterminate lesion, TIR3B-high-risk indeterminate lesion, TIR4-suspicious of malignancy, TIR5-malignant). All subjects were surgical candidates (defined by international guidelines) and submitted to FNA procedures for RS analysis. We compared RS data, cytologic findings, and final histologic assessments (as reference standard) using various statistical techniques.

RESULTS

The distribution of our study population was as follows: TIR3A:37, TIR3B:32, TIR4:16, and TIR5:38. In 30.9% of patients, histologic diagnoses were benign. For predicting thyroid malignancy in FNA samples, the overall specificity of RS was 86.8%, with 86.5% specificity in indeterminate cytologic categories. In patients with high-risk ultrasound categories, the specificity of RS increased to 87.5% for TIR3A, reaching 100% for TIR3B. Benign histologic diagnoses accounted for 72.9% of patients classified as TIR3A and 31.3% of those classified as TIR3B. Based on positive RS testing, unnecessary surgery was reduced to 7.4% overall (TIR3A-33.3%, TIR3B-6.7%).

CONCLUSIONS

This premier use of RS for thyroid cytology confirms its role as a valuable diagnostic tool and a valid alternative to molecular studies, capable of improving the management of indeterminate nodules and reducing unnecessary surgery.

Label-free discrimination of tumorigenesis stages using in vitro prostate cancer bone metastasis model by Raman imaging

Metastatic prostate cancer colonizes the bone to pave the way for bone metastasis, leading to skeletal complications associated with poor prognosis and morbidity. This study demonstrates the feasibility of Raman imaging to differentiate between cancer cells at different stages of tumorigenesis using a nanoclay-based three-dimensional (3D) bone mimetic in vitro model that mimics prostate cancer bone metastasis. A comprehensive study comparing the classification of as received prostate cancer cells in a two-dimensional (2D) model and cancer cells in a 3D bone mimetic environment was performed over various time intervals using principal component analysis (PCA). Our results showed distinctive spectral differences in Raman imaging between prostate cancer cells and the cells cultured in 3D bone mimetic scaffolds, particularly at 1002, 1261, 1444, and 1654 cm-1, which primarily contain proteins and lipids signals. Raman maps capture sub-cellular responses with the progression of tumor cells into metastasis. Raman feature extraction via cluster analysis allows for the identification of specific cellular constituents in the images. For the first time, this work demonstrates a promising potential of Raman imaging, PCA, and cluster analysis to discriminate between cancer cells at different stages of metastatic tumorigenesis.

The role of pro- and antiangiogenic factors in angiogenesis process by Raman spectroscopy

Raman spectroscopy and Raman imaging are powerful techniques to monitor biochemical composition around blood vessel. The aim of this study was to understand the role of pro- and antiangiogenic factors in angiogenesis process. Raman imaging and Raman single spectrum measurements allow the diagnosis of cancer biochemical changes in blood vessel based on several biomarkers simultaneously. We have demonstrated that Raman imaging combined with statistical methods are useful to monitoring pro- and antiangiogenic factors responsible for angiogenesis process. In this work Raman markers of proangiogenic and antiangiogenic factors were identified based on their vibrational signatures. Obtained results can help understand how growing tumor create its vascular system.

Raman imaging and statistical methods for analysis various type of human brain tumors and breast cancers

Spectroscopic methods provide information on the spatial localization of biochemical components based on the analysis of vibrational spectra. Raman spectroscopy and Raman imaging can be used to analyze various types of human brain tumors and breast cancers. The objective of this study is to evaluate the Raman biomarkers to distinguish tumor types by Raman spectroscopy and Raman imaging. We have demonstrated that bands characteristic for carotenoids (1156 cm^-1, 1520 cm^-1), proteins (1004 cm^-1), fatty acids (1444 cm^-1, 1655 cm^-1) and cytochrome (1585 cm^-1) can be used as universal biomarkers to assess aggressiveness of human brain tumors. The sensitivity and specificity obtained from PLS-DA have been over 73%. Only for gliosarcoma WHO IV the specificity is lower and takes equal 50%. The presented results confirm clinical potential of Raman spectroscopy in oncological diagnostics.

Revision of Commonly Accepted Warburg Mechanism of Cancer Development: Redox-Sensitive Mitochondrial Cytochromes in Breast and Brain Cancers by Raman Imaging

We used Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues, surgically resected specimens of human tissues and in vitro human brain cells of normal astrocytes (NHA), astrocytoma (CRL-1718), glioblastoma (U87-MG) and medulloblastoma (Daoy), and human breast cells of normal cells (MCF 10A), slightly malignant cells (MCF7) and highly aggressive cells (MDA-MB-231) by means of Raman microspectroscopy at 532 nm. We visualized localization of cytochromes by Raman imaging in the major organelles in cancer cells. We demonstrated that the "redox state Raman marker" of the ferric low-spin heme in cytochrome c at 1584 cm^-1 can serve as a sensitive indicator of cancer aggressiveness. We compared concentration of reduced cytochrome c and the grade of cancer aggressiveness in cancer tissues and single cells and specific organelles in cells: nucleous, mitochondrium, lipid droplets, cytoplasm and membrane. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers in human tissues. Our results reveal the universality of Raman vibrational characteristics of mitochondrial cytochromes in metabolic regulation in cancers that arise from epithelial breast cells and brain glial cells.

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

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

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

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

Redox Imbalance and Biochemical Changes in Cancer by Probing Redox-Sensitive Mitochondrial Cytochromes in Label-Free Visible Resonance Raman Imaging

Simple Summary

Gliomas comprise around 30% of human brain tumors, while invasive ductal carcinoma (IDC) comprises around 80% of human breast cancers. The aim of our study was to show that cancerogenesis affects the redox status of mitochondrial cytochromes, which can be tracked by using Raman spectroscopy and imaging. Our results confirmed that human breast cancer and brain tumor demonstrate a redox imbalance compared to normal tissues. We have shown the correlation between the intensity of cytochromes Raman bands at 750, 1126, 1337 and 1584 cm⁻¹ and malignancy grade for brain and breast cancers.

Abstract

To monitor redox state changes and biological mechanisms occurring in mitochondrial cytochromes in cancers improving methods are required. We used Raman spectroscopy and Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues at 532 nm, 633 nm, 785 nm. We identified the oncogenic processes that characterize human infiltrating ductal carcinoma (IDC) and human brain tumors: gliomas; astrocytoma and medulloblastoma based on the quantification of cytochrome redox status by exploiting the resonance-enhancement effect of Raman scattering. We visualized localization of cytochromes by Raman imaging in the breast and brain tissues and analyzed cytochrome c vibrations at 750, 1126, 1337 and 1584 cm⁻¹ as a function of malignancy grade. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers and correlates with the grade of cancer. We showed that Raman imaging provides additional insight into the biology of astrocytomas and breast ductal invasive cancer, which can be used for noninvasive grading, differential diagnosis.

Astaxanthin as a new Raman probe for biosensing of specific subcellular lipidic structures: can we detect lipids in cells under resonance conditions?

Here we report a new Raman probe for cellular studies on lipids detection and distribution. It is (3S, 3'S)-astaxanthin (AXT), a natural xanthophyll of hydrophobic properties and high solubility in lipids. It contains a chromophore group, a long polyene chain of eleven conjugated C=C bonds including two in the terminal rings, absorbing light in the visible range that coincides with the excitation of lasers commonly used in Raman spectroscopy for studying of biological samples. Depending on the laser, resonance (excitation in the visible range) or pre-resonance (the near infrared range) Raman spectrum of astaxanthin is dominated by bands at ca. 1008, 1158, and 1520 cm⁻¹ that now can be also a marker of lipids distribution in the cells. We showed that AXT accumulates in lipidic structures of endothelial cells in time-dependent manner that provides possibility to visualize e.g. endoplasmic reticulum, as well as nuclear envelope. As a non-toxic reporter, it has a potential in the future studies on e.g. nucleus membranes damage in live cells in a very short measuring time.

SERS studies on normal epithelial and cancer cells derived from clinical breast cancer specimens

Surface-enhanced Raman scattering (SERS) spectroscopy of single-cell suspensions obtained from fresh specimens of breast cancer tissue and normal breast tissue by mechanical enzymatic digestion was obtained and analysed, which is different from most Raman studies using breast cancer cell lines. Random forest classification was implemented to develop effective diagnostic algorithms for the classification of SERS of different typed cells. We first examined the SERS spectra of the primary breast cancer single cell and normal epithelial single cell obtained by flow sorting cytometry due to their biomarkers of CD326+/CD45-. Comparison analyses on their SERS spectra disclose that the nucleic acid and protein levels of the primary breast cancer single cell are higher than those of the normal epithelial single cell, while the lipids are at a relatively lower level. An important finding is that the cholesterol, palmitic acid, and sphingomyelin in the cancer cell profiles exhibit stronger than those of normal cells, while the glycans are at a relatively lower level. Furthermore, the standard deviation (SD) of the normal epithelial single cell is larger than that of the breast cancer cell, and the SD of the primary breast cancer single cell is more obvious than that of the normal epithelial cells. In addition, the prospective application of an algorithm to the dataset results in an accuracy of 78.2%, a precision of 75.5%, and a recall of 66.7%. The breast cancer diagnostic model laid a solid foundation for judgment of breast-conserving surgical margins and early diagnosis of breast cancer.

Vibrational spectroscopy of liquid biopsies for prostate cancer diagnosis

Background:

Screening for prostate cancer with prostate specific antigen and digital rectal examination allows early diagnosis of prostate malignancy but has been associated with poor sensitivity and specificity. There is also a considerable risk of over-diagnosis and over-treatment, which highlights the need for better tools for diagnosis of prostate cancer. This study investigates the potential of high throughput Raman and Fourier Transform Infrared (FTIR) spectroscopy of liquid biopsies for rapid and accurate diagnosis of prostate cancer.

Methods:

Blood samples (plasma and lymphocytes) were obtained from healthy control subjects and prostate cancer patients. FTIR and Raman spectra were recorded from plasma samples, while Raman spectra were recorded from the lymphocytes. The acquired spectral data was analysed with various multivariate statistical methods, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and classical least squares (CLS) fitting analysis.

Results:

Discrimination was observed between the infrared and Raman spectra of plasma and lymphocytes from healthy donors and prostate cancer patients using PCA. In addition, plasma and lymphocytes displayed differentiating signatures in patients exhibiting different Gleason scores. A PLS-DA model was able to discriminate these groups with sensitivity and specificity rates ranging from 90% to 99%. CLS fitting analysis identified key analytes that are involved in the development and progression of prostate cancer.

Conclusions:

This technology may have potential as an alternative first stage diagnostic triage for prostate cancer. This technology can be easily adaptable to many other bodily fluids and could be useful for translation of liquid biopsy-based diagnostics into the clinic.

Resveratrol Modifies Lipid Composition of Two Cancer Cell Lines

Resveratrol (Resv) offers health benefits in cancer and has been reported to modulate important enzymes of lipid metabolism. Studies of its effects on lipid composition in different subtypes of breast-cancer cells are scarce. Thus, we investigated the alterations in phospholipids (PL), fatty acids (FA), and lipid metabolism enzymes in two breast-cancer cell lines after Resv treatment. MCF-7 and MDA-MB-231 cells were treated with 80 and 200 μM of Resv, respectively, for 24 hours. We analyzed PL with radiolabeled inorganic phosphate (³²Pi) by thin-layer chromatography, FA by gas chromatography-mass spectrometry, and lipid metabolism enzymes (DGAT2, FAS, ρACCβ, pAMPKα, and AMPK) by Western blot. Resv treated MDA-MB-231 phospholipids showed a reduction in phosphatidylcholine (63%) and phosphatidylethanolamine (35%). We observed an increase in eicosapentaenoic acid (EPA) (73%) and docosahexaenoic acid (DHA) (65%) in MCF-7 cells after Resv treatment. Interestingly, the same treatment caused 50% and 90% increases in EPA and DHA, respectively, in MDA-MB-231 cells. In MCF-7 cells, Resv increased the expression of ρACCβ (3.3-fold) and AMPKα/ρAMPKα (1.5-fold) and in MDA-MB-231 cells it inhibited the expression of ρACCβ (111.8-fold) and AMPKα/ρAMPKα (1.2 fold). Our results show that Resv modified PL and saturated and unsaturated FA especially in MDA-MB-231 cells, and open new perspectives to the understanding of the reported anticancer effect of Resv on these cells.

A look into the use of Raman spectroscopy for brain and breast cancer diagnostics: linear and non-linear optics in cancer research as a gateway to tumor cell identity

Introduction: Currently, intensely developing of linear and non-linear optical methods for cancer detection provides a valuable tool to improve sensitivity and specificity. One of the main reasons for insufficient progress in cancer diagnostics is related to the fact that most cancer types are not only heterogeneous in their genetic composition but also reside in varying microenvironments and interact with different cell types. Until now, no technology has been fully proven for effective detecting of invasive cancer, which infiltrating the extracellular matrix.Areas covered: This review investigates the current status of Raman spectroscopy and Raman imaging for brain and breast cancer diagnostics. Moreover, the review provides a comprehensive overview of the applicability of atomic force microscopy (AFM), linear and non-linear optics in cancer research as a gateway to tumor cell identity.Expert commentary: A combination of linear and non-linear optics, particularly Raman-driven methods, has many additional advantages to identify alterations in cancer cells that are crucial for their proliferation and that distinguish them from normal cells.

Aberrant Protein Phosphorylation in Cancer by Using Raman Biomarkers

(1) Background: Novel methods are required for analysing post-translational modifications of protein phosphorylation by visualizing biochemical landscapes of proteins in human normal and cancerous tissues and cells. (2) Methods: A label-free Raman method is presented for detecting spectral changes that arise in proteins due to phosphorylation in the tissue of human breasts, small intestines, and brain tumours, as well as in the normal human astrocytes and primary glioblastoma U-87 MG cell lines. Raman spectroscopy and Raman imaging are effective tools for monitoring and analysing the vibrations of functional groups involved in aberrant phosphorylation in cancer without any phosphorecognition of tag molecules. (3) Results: Our results based on 35 fresh human cancer and normal tissues prove that the aberrant tyrosine phosphorylation monitored by the unique spectral signatures of Raman vibrations is a universal characteristic in the metabolic regulation in different types of cancers. Overexpressed tyrosine phosphorylation in the human breast, small intestine and brain tissues and in the human primary glioblastoma U-87 MG cell line was monitored by using Raman biomarkers. (4) We showed that the bands at 1586 cm-1 and 829 cm-1, corresponding to phosphorylated tyrosine, play a pivotal role as a Raman biomarker of the phosphorylation status in aggressive cancers. We found that the best Raman biomarker of phosphorylation is the 1586/829 ratio showing the statistical significance at p Values of ≤ 0.05. (5) Conclusions: Raman spectroscopy and imaging have the potential to be used as screening functional assays to detect phosphorylated target proteins and will help researchers to understand the role of phosphorylation in cellular processes and cancer progression. The abnormal and excessive high level of tyrosine phosphorylation in cancer samples compared with normal samples was found in the cancerous human tissue of breasts, small intestines and brain tumours, as well as in the mitochondria and lipid droplets of the glioblastoma U-87 MG cell line. Detailed insights are presented into the intracellular oncogenic metabolic pathways mediated by phosphorylated tyrosine.

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

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

Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.

Advances in Raman imaging combined with AFM and fluorescence microscopy are beneficial for oncology and cancer research

Aim: The aim of this paper is to provide images of the universal cancer Raman biomarkers based on lipidomic, proteomic, glycomic profiles and nanomechanical properties. Materials & methods: Biochemical mapping and nanomechanical properties (topography, stiffness and adhesion) of human breast and brain for normal and cancer tissues and cell culture line U87 MG of glioblastoma were obtained using Raman imaging combined with atomic force microscopy (AFM) and fluorescence microscopy. Results & conclusion: Detailed analysis of breast ductal carcinoma in situ, and astrocytoma brain tissues as well as cells of glioblastoma U87 MG showed that Raman scattering generates images as accurately as histology hematoxylin and eosin stain used in clinical practice with additional advantage of biochemical information. Combination of AFM maps and Raman images allows to correlate mechanical properties with biochemical composition of cells.

Analysis of Human Colon by Raman Spectroscopy and Imaging-Elucidation of Biochemical Changes in Carcinogenesis

Noninvasive Raman imaging of non-fixed and unstained human colon tissues based on vibrational properties of noncancerous and cancerous samples can effectively enable the differentiation between noncancerous and tumor tissues. This work aimed to evaluate the biochemical characteristics of colon cancer and the clinical merits of multivariate Raman image and spectroscopy analysis. Tissue samples were collected during routine surgery. The non-fixed, fresh samples were used to prepare micrometer sections from the tumor mass and the tissue from the safety margins outside of the tumor mass. Adjacent sections were used for typical histological analysis. We have found that the chemical composition identified by Raman spectroscopy of the cancerous and the noncancerous colon samples is sufficiently different to distinguish pathologically changed tissue from noncancerous tissue. We present a detailed analysis of Raman spectra for the human noncancerous and cancerous colon tissue. The multivariate analysis of the intensities of lipids/proteins/carotenoids Raman peaks shows that these classes of compounds can statistically divide analyzed samples into noncancerous and pathological groups, reaffirming that Raman imaging is a powerful technique for the histochemical analysis of human tissues. Raman biomarkers based on ratios for lipids/proteins/carotenoids content were found to be the most useful biomarkers in spectroscopic diagnostics.

Discrimination of breast cancer from benign tumours using Raman spectroscopy

Breast cancer is the most common cancer among women worldwide, with an estimated 1.7 million cases and 522,000 deaths in 2012. Breast cancer is diagnosed by histopathological examination of breast biopsy material but this is subjective and relies on morphological changes in the tissue. Raman spectroscopy uses incident radiation to induce vibrations in the molecules of a sample and the scattered radiation can be used to characterise the sample. This technique is rapid and non-destructive and is sensitive to subtle biochemical changes occurring at the molecular level. This allows spectral variations corresponding to disease onset to be detected. The aim of this work was to use Raman spectroscopy to discriminate between benign lesions (fibrocystic, fibroadenoma, intraductal papilloma) and cancer (invasive ductal carcinoma and lobular carcinoma) using formalin fixed paraffin preserved (FFPP) tissue. Haematoxylin and Eosin stained sections from the patient biopsies were marked by a pathologist. Raman maps were recorded from parallel unstained tissue sections. Immunohistochemical staining for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) was performed on a further set of parallel sections. Both benign and cancer cases were positive for ER while only the cancer cases were positive for HER2. Significant spectral differences were observed between the benign and cancer cases and the benign cases could be differentiated from the cancer cases with good sensitivity and specificity. This study has shown the potential of Raman spectroscopy as an aid to histopathological diagnosis of breast cancer, in particular in the discrimination between benign and malignant tumours.

Monitoring glycosylation metabolism in brain and breast cancer by Raman imaging

We have shown that Raman microspectroscopy is a powerful method for visualization of glycocalyx offering cellular interrogation without staining, unprecedented spatial and spectral resolution, and biochemical information. We showed for the first time that Raman imaging can be used to distinguish successfully between glycosylated and nonglycosylated proteins in normal and cancer tissue. Thousands of protein, lipid and glycan species exist in cells and tissues and their metabolism is monitored via numerous pathways, networks and methods. The metabolism can change in response to cellular environment alterations, such as development of a disease. Measuring such alterations and understanding the pathways involved are crucial to fully understand cellular metabolism in cancer development. In this paper Raman markers of glycogen, glycosaminoglycan, chondroitin sulfate, heparan sulfate proteoglycan were identified based on their vibrational signatures. High spatial resolution of Raman imaging combined with chemometrics allows separation of individual species from many chemical components present in each cell. We have found that metabolism of proteins, lipids and glycans is markedly deregulated in breast (adenocarcinoma) and brain (medulloblastoma) tumors. We have identified two glycoforms in the normal breast tissue and the malignant brain tissue in contrast to the breast cancer tissue where only one glycoform has been identified.

Raman spectroscopy for medulloblastoma

PURPOSE

The aim of the study is to use Raman spectroscopy to analyze the biochemical composition of medulloblastoma and normal tissues from the safety margin of the CNS and to find specific Raman biomarkers capable of differentiating between tumorous and normal tissues.

METHODS

The tissue samples consisted of medulloblastoma (grade IV) (n = 11). The tissues from the negative margins were used as normal controls. Raman images were generated by a confocal Raman microscope-WITec alpha 300 RSA.

RESULTS

Raman vibrational signatures can predict which tissue has tumorous biochemistry and can identify medulloblastoma. The Raman technique makes use of the fact that tumors contain large amounts of protein and far less lipids (fatty compounds), while healthy tissue is rich in both.

CONCLUSION

The ability of Raman spectroscopy and imaging to detect medulloblastoma tumors fills the niche in diagnostics. These powerful analytical techniques are capable of monitoring tissue morphology and biochemistry. Our results demonstrate that RS can be used to discriminate between normal and medulloblastoma tissues.

Effect of Diets, Familial History, and Alternative Therapies on Genomic Instability of Breast Cancer Patients

This study evaluates a correlation between family history, micronutrients intake, and alternative therapies with genetic instability, before and during breast cancer treatment. For this study, a total of 150 women were selected. Among those, 50 women were breast cancer patients on chemotherapy, while 50 breast cancer patients were on radiotherapy, and 50 were healthy females. All the participants signed the informed consent form and answered the public health questionnaire. Samples of buccal epithelial and peripheral blood cells were collected and analyzed through micronucleus and comet assays. The cells were evaluated for apoptosis and DNA damage. Results showed the association of patients' family history with an increase in toxicogenetic damage before and during cancer therapy. On the other hand, patients with late-onset cancer also presented genetic instability before and during therapy, along with those who did not take sufficient vegetables and alternative therapies. A positive correlation was observed between the genetic instability and alternative therapies, while inverse correlation was recorded with the vegetable consumption. Results clearly explain that the nutritional aspects and alternative therapies influence the genetic instability before and during cancer therapies especially in radiotherapy treated patients. Our data could be used for the monitoring therapies and management of breast cancer patients.

Development of a high throughput (HT) Raman spectroscopy method for rapid screening of liquid blood plasma from prostate cancer patients

Extensive research has been undertaken on the examination of tissue biopsies using vibrational spectroscopic techniques. However, fewer studies have focused on less invasive and commonly acquired blood samples. Recent studies have shown the ability of Raman and Fourier transform infrared (FTIR) spectroscopy to discriminate between non-cancer controls and cancer cases using blood serum or plasma. Even though many studies have proposed Raman spectroscopy as a potential diagnostic tool in various cancers, the Raman spectroscopic technique has not been introduced as a routine clinical technology. This is due to multiple drawbacks with the application of the technique, including sample preparation, the requirement for expensive substrates and long acquisition times. The current study aims to overcome these limitations and focuses on the translation of Raman spectroscopy into a high throughput clinical diagnostic tool for prostate cancer. In this study, the effect of different instrumental and sample preparation parameters were investigated, with the aim of identifying a combination that would reduce the overall acquisition time for spectra from peripheral blood plasma, reduce the complexity of sample preparation and retain the classification accuracy from Raman spectroscopic diagnostics. A high throughput (HT) system was developed and Raman spectroscopic measurements were performed on plasma samples from 10 prostate cancer patients and 10 healthy volunteers. The spectra were pre-processed and classified by principal component analysis - linear discriminant analysis (PCA-LDA) in the R environment. Statistically significant differences were observed between Raman spectra of prostate cancer patients and non-cancer controls. The (HT) classification resulted in a sensitivity and specificity of 96.5% and 95% respectively. Overall, this study has overcome some of the limitations associated with clinical translation of Raman spectroscopy. The HT-Raman spectroscopy method developed in this study can be used for rapid and accurate diagnosis of prostate cancer using liquid plasma samples.

Persistent Increased Frequency of Genomic Instability in Women Diagnosed with Breast Cancer: Before, during, and after Treatments

This study aimed to evaluate DNA damage in patients with breast cancer before treatment (background) and after chemotherapy (QT) and radiotherapy (RT) treatment using the Comet assay in peripheral blood and the micronucleus test in buccal cells. We also evaluated repair of DNA damage after the end of RT, as well as the response of patient's cells before treatment with an oxidizing agent (H2O2; challenge assay). Fifty women with a mammographic diagnosis negative for cancer (control group) and 100 women with a diagnosis of breast cancer (followed up during the treatment) were involved in this study. The significant DNA damage was observed by increasing in the index and frequency of damage along with the increasing of the frequency of micronuclei in peripheral blood and cells of the buccal mucosa, respectively. Despite the variability of the responses of breast cancer patients, the individuals presented lesions on the DNA, detected by the Comet assay and micronucleus Test, from the diagnosis until the end of the oncological treatment and were more susceptible to oxidative stress. We can conclude that the damages were due to clastogenic and/or aneugenic effects related to the neoplasia itself and that they increased, especially after RT.

Angiogenesis - a crucial step in breast cancer growth, progression and dissemination by Raman imaging

Combined micro-Raman imaging and AFM imaging are efficient methods for analyzing human tissue due to their high spatial and spectral resolution as well as sensitivity to subtle chemical, structural and topographical changes. The aim of this study was to determine biochemical composition and mechanical topography around blood vessels in the tumor mass of human breast tissue. Significant alterations of the chemical composition and structural architecture around the blood vessel were found compared to the normal breast tissue. A pronounced increase of collagen-fibroblast-glycocalyx network, as well as enhanced lactic acid, and glycogen activity in patients affected by breast cancer were reported.

Correlations between Risk Factors for Breast Cancer and Genetic Instability in Cancer Patients-A Clinical Perspective Study

Molecular epidemiological studies have identified several risk factors linking to the genes and external factors in the pathogenesis of breast cancer. In this sense, genetic instability caused by DNA damage and DNA repair inefficiencies are important molecular events for the diagnosis and prognosis of therapies. Therefore, the objective of this study was to analyze correlation between sociocultural, occupational, and lifestyle risk factors with levels of genetic instability in non-neoplastic cells of breast cancer patients. Total 150 individuals were included in the study that included 50 breast cancer patients submitted to chemotherapy (QT), 50 breast cancer patients submitted to radiotherapy (RT), and 50 healthy women without any cancer. Cytogenetic biomarkers for apoptosis and DNA damage were evaluated in samples of buccal epithelial and peripheral blood cells through micronuclei and comet assay tests. Elder age patients (61-80 years) had higher levels of apoptosis (catriolysis by karyolysis) and DNA damage at the diagnosis (baseline damage) with increased cell damage during QT and especially during RT. We also reported the increased frequencies of cytogenetic biomarkers in patients who were exposed to ionizing radiation as well as for alcoholism and smoking. QT and RT induced high levels of fragmentation (karyorrhexis) and nuclear dissolution (karyolysis) and DNA damage. Correlations were observed between age and karyorrhexis at diagnosis; smoking and karyolysis during RT; and radiation and karyolysis during QT. These correlations indicate that risk factors may also influence the genetic instability in non-neoplastic cells caused to the patients during cancer therapies.

Feature driven classification of Raman spectra for real-time spectral brain tumour diagnosis using sound

Spectroscopic diagnostics have been shown to be an effective tool for the analysis and discrimination of disease states from human tissue. Furthermore, Raman spectroscopic probes are of particular interest as they allow for in vivo spectroscopic diagnostics, for tasks such as the identification of tumour margins during surgery. In this study, we investigate a feature-driven approach to the classification of metastatic brain cancer, glioblastoma (GB) and non-cancer from tissue samples, and we provide a real-time feedback method for endoscopic diagnostics using sound. To do this, we first evaluate the sensitivity and specificity of three classifiers (SVM, KNN and LDA), when trained with both sub-band spectral features and principal components taken directly from Raman spectra. We demonstrate that the feature extraction approach provides an increase in classification accuracy of 26.25% for SVM and 25% for KNN. We then discuss the molecular assignment of the most salient sub-bands in the dataset. The most salient sub-band features are mapped to parameters of a frequency modulation (FM) synthesizer in order to generate audio clips from each tissue sample. Based on the properties of the sub-band features, the synthesizer was able to maintain similar sound timbres within the disease classes and provide different timbres between disease classes. This was reinforced via listening tests, in which participants were able to discriminate between classes with mean classification accuracy of 71.1%. Providing intuitive feedback via sound frees the surgeons' visual attention to remain on the patient, allowing for greater control over diagnostic and surgical tools during surgery, and thus promoting clinical translation of spectroscopic diagnostics.

The biochemical, nanomechanical and chemometric signatures of brain cancer

Raman spectroscopy and imaging combined with AFM topography and mechanical indentation by AFM have been shown to be an effective tool for analysis and discrimination of human brain tumors from normal structures. Raman methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n=5) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma (IV grade), and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational spectra and Raman images we provide a real-time feedback that is label-free method to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, and proteins. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have shown that the ratio of Raman intensities I2930/I2845 at 2930 and 2845cm^-1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the lipid and protein contents of tumorous brain tissue compared to the non-tumor tissue. Almost all brain tumors have the Raman intensity ratios significantly higher (1.99±0.026) than that found in non-tumor brain tissue, which is 1.456±0.02, and indicates that the relative amount of lipids compared to proteins is significantly higher in the normal brain tissue. Mechanical indentation using AFM on sliced human brain tissues (medulloblastoma, grade IV) revealed that the mechanical properties of this tissue are strongly heterogeneous, between 1.8 and 75.7kPa, and the mean of 27.16kPa. The sensitivity and specificity obtained directly from PLSDA and cross validation gives a sensitivity and specificity of 98.5% and 96% and 96.3% and 92% for cross-validation, respectively. The high sensitivity and specificity demonstrates usefulness for a proper decision for a Raman diagnostic test on biochemical alterations monitored by Raman spectroscopy related to brain cancer development.

Novel strategies of Raman imaging for brain tumor research

Raman diagnostics and imaging have been shown to be an effective tool for the analysis and discrimination of human brain tumors from normal structures. Raman spectroscopic methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n= 5), low-grade astrocytoma (grades I-II WHO) (n =4), ependymoma (n=3) and metastatic brain tumors (n= 1) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma, low grade astrocytoma and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational features and Raman images we provide a real–time feedback method that is label-free to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, proteins, DNA and RNA. Our results indicate marked metabolic differences between low and high grade brain tumors. We discuss molecular mechanisms causing these metabolic changes, particularly lipid alterations in malignant medulloblastoma and low grade gliomas that may shed light on the mechanisms driving tumor recurrence thereby revealing new approaches for the treatment of malignant glioma. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have found that almost all tumors studied in the paper have increased Raman signals of nucleic acids. This increase can be interpreted as increased DNA/RNA turnover in brain tumors. We have shown that the ratio of Raman intensities I₂₉₃₀/I₂₈₄₅ at 2930 and 2845 cm^-1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the different lipid and protein contents of cancerous brain tissue compared to the non-tumor tissue. We found that levels of the saturated fatty acids were significantly reduced in the high grade medulloblastoma samples compared with non-tumor brain samples and low grade astrocytoma. Differences were also noted in the n-6/n-3 polyunsaturated fatty acids (PUFA) content between medulloblastoma and non-tumor brain samples. The content of the oleic acid (OA) was significantly smaller in almost all brain high grade brain tumors than that observed in the control samples. It indicates that the fatty acid composition of human brain tumors differs from that found in non-tumor brain tissue. The iodine number N_I for the normal brain tissue is 60. For comparison OA has 87, docosahexaenoic acid (DHA) 464, α-linolenic acid (ALA) 274. The high grade tumors have the iodine numbers between that for palmitic acid, stearic acid, arachidic acid (N_I=0) and oleic acid (N_I=87). Most low grade tumors have N_I similar to that of OA. The iodine number for arachidonic acid (AA) (N_I=334) is much higher than those observed for all studied samples.

Sphingolipid abnormalities in cancer multidrug resistance: Chicken or egg?

The cancer multidrug resistance (MDR) phenotype encompasses a myriad of molecular, genetic and cellular alterations resulting from progressive oncogenic transformation and selection. Drug efflux transporters, in particular the MDR P-glycoprotein ABCB1, play an important role in MDR but cannot confer the complete phenotype alone indicating parallel alterations are prerequisite. Sphingolipids are essential constituents of lipid raft domains and directly participate in functionalization of transmembrane proteins, including providing an optimal lipid microenvironment for multidrug transporters, and are also perturbed in cancer. Here we postulate that increased sphingomyelin content, developing early in some cancers, recruits and functionalizes plasma membrane ABCB1 conferring a state of partial MDR, which is completed by glycosphingolipid disturbance and the appearance of intracellular vesicular ABCB1. In this review, the independent and interdependent roles of sphingolipid alterations and ABCB1 upregulation during the transformation process and resultant conferment of partial and complete MDR phenotypes are discussed.

β-Thalassemia Patients Revealed a Significant Change of Untargeted Metabolites in Comparison to Healthy Individuals

β-Thalassemia is one of the most prevalent forms of congenital blood disorders characterized by reduced hemoglobin levels with severe complications, affecting all dimensions of life. The mechanisms underlying the phenotypic heterogeneity of β-thalassemia are still poorly understood. We aimed to work over metabolite biomarkers to improve mechanistic understanding of phenotypic heterogeneity and hence better management of disorder at different levels. Untargeted serum metabolites were analyzed after protein precipitation and SPE (solid phase extraction) from 100 β-thalassemia patients and 61 healthy controls using GC-MS. 40 metabolites were identified having a significance difference between these two groups at probability of 0.05 and fold change >1.5. Out of these 40 metabolites, 17 were up-regulated while 23 were down-regulated. PCA and PLS-DA model was also created that revealed a fine separation with a sensitivity of 70% and specificity of 100% on external validation of samples. Metabolic pathway analysis revealed alteration in multiple pathways including glycolysis, pyruvate, propanoate, glycerophospholipid, galactose, fatty acid, starch and sucrose metabolism along with fatty acid elongation in mitochondria, glycerolipid, glyoxylate and dicarboxylate metabolism pointing towards the shift of metabolism in β-thalassemia patients in comparison to healthy individuals.

Label-Free Raman Imaging to Monitor Breast Tumor Signatures

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.