Comparison of molecular images as defined by Raman spectra between normal mucosa and squamous cell carcinoma in the oral cavity

Raman spectroscopy has been effectively applied to clinically differentiate normal and cancerous mucosal tissues. Micro‐Raman spectroscopy provides a tool to better understand the molecular basis for the Raman clinical signal. The objective of the current study was to utilize micro‐Raman spectroscopy to define the molecular/spectral differences between normal and abnormal squamous cell carcinoma (SCC) in oral mucosa (in vitro). Understanding this may help in identifying unique spectra or may be useful for in vivo application of this technology. Micro‐Raman (confocal) spectroscopy was used to obtain molecular images of normal and SCC cells of human oral mucosa. Four fresh flashed‐frozen tumor and four matched normal tongue specimens were studied. The spectra covered a wavenumber range from 300 to 4000 cm⁻¹ with a spectral resolution of 8 cm⁻¹ and a spatial resolution of 1.0 µm. The cells were located within thin sections of tongue mucosa biopsies. The excitation wavelength of 515 nm was used. We were able to obtain Raman images with rich information about the spectroscopic and structural features within the cytoplasm, cell membrane, and cell nuclei. Significant spectral differences were observed between the Raman images of normal and malignant squamous cells. The heterogeneity of tumor cells within the abnormal tissue was also demonstrated. Spectral differences demonstrated between both tissue types have provided important information regarding the origins of specific signals within the cells of each tissue type. In our search for specific spectral biomarkers, we believe that a cell surface protein, greatly upregulated in SCC cells, was discovered at 1583 cm⁻¹. Copyright © 2010 John Wiley & Sons, Ltd.     

Confocal Raman microspectroscopy discriminates live human metastatic melanoma and skin fibroblast cells

Confocal Raman microspectroscopy (CRM) continues to develop as a promising technique with possible clinical applications for the diagnosis and treatment of skin cancers. CRM studies of single cells can provide information on the biochemical content of cancer cells in situ, potentially providing new biochemical signatures or markers of cancer cells. Here, we report a CRM study of single, living human metastatic melanoma cells (SK‐Mel‐2) and normal skin fibroblast cells (BJ) cultured and examined under identical experimental conditions. A total of almost 1200 Raman spectra were measured from more than 120 BJ and SK‐Mel‐2 cells using an inverted microscope with 647 nm laser excitation. Raman spectra were measured from within three distinct intracellular regions of the cells – cytoplasm, nucleoplasm, and nucleolus. When Raman spectra from each cell type were compared using principal components analysis (PCA) and linear discriminant analysis with leave‐one‐dish‐out cross‐validation (LDA‐CV), the two cell types were discriminated with 93% (cytoplasm), 98% (nucleolus), and 96% (nucleoplasm) accuracy. The main biochemical differences identified between the two cell types were higher RNA levels in the nucleoli of BJ cells and high amounts of lipid and collagen in the cytoplasm of SK‐Mel‐2 cells. For both cell types, higher levels of RNA were detected in the nucleoli versus the nucleoplasm. PCA with LDA‐CV was 98% (cytoplasm), 93% (nucleoplasm), and 73% (nucleolus) accurate in identifying the intracellular region based on the Raman spectra from both cell types. No significant trend was observed when the data were analyzed with respect to cell passage number. Thus, CRM with PCA and LDA‐CV successfully discriminated two skin cancer‐relevant cell lines while detecting different amounts of nucleic acids, lipids, and proteins in distinct intracellular regions, further underscoring its potential as a clinical diagnostic tool. Copyright © 2013 John Wiley & Sons, Ltd.     

Raman spectral signatures of mouse mammary tissue and associated lymph nodes: normal,tumor and mastitis

Raman spectroscopy involves the interaction of light with the molecular vibrations and therefore can provide information about molecular structure, tissue composition and changes in its environment. We explored whether Raman spectroscopy can reliably distinguish mammary tumors from normal mammary tissues and other pathological states in mice. We analyzed a large number of Raman spectra from the tumor and normal mammary glands of mice injected with 4T1 tumor cells, which were collected using a high‐resolution (less than 4 cm⁻¹) Raman spectrometer at a fixed (785 nm) laser excitation wavelength and with 60 mW of laser power. The spectra of normal and tumor mammary glands showed consistent differences in the intensity of certain Raman bands and loss of some bands in the tumor spectra. Multivariate statistical methods—principal component analysis (PCA) and discriminant functional analysis (DFA)—were used to separate the data into different groups of mammary tumors, mastitis, lymph nodes contralateral and tumor‐cell‐injected sides, and normal contralateral and tumor‐cell‐injected sides. We demonstrate that this spectroscopic technique has the feasibility of discriminating tumor and mastitis from normal tissues and other pathological states in a short period of time and may detect tumor transformation earlier than the standard histological examination stage. Copyright © 2006 John Wiley & Sons, Ltd.     

Depth‐resolved in vivo micro‐Raman spectroscopy of a murine skin tumor model reveals cancer‐specific spectral biomarkers

We have developed a micro‐Raman spectrometer system for use to differentiate tumor lesions from normal skin using an in vivo animal model. A study of 494 Raman spectra from 24 mice revealed different spectral patterns at different depths and between normal and tumor‐bearing skin sites. A peak at 899 cm⁻¹ (possibly from proline or fatty acids) and one with higher intensity in the 1325–1330 cm⁻¹ range (assigned to nucleic acids) were correlated with the presence of tumors, which can potentially be used as biomarkers for skin cancer detection. Spectral diagnosis performed on the murine tumor model achieved a diagnostic sensitivity of 95.8% and specificity of 93.8%. These results encourage us to develop further the use of confocal Raman spectroscopy as a clinical tool for noninvasive human skin biochemical analysis, particularly in relation to skin cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

拉曼光谱检测生物大分子损伤的研究进展

拉曼光谱是基于拉曼散射效应而发展起来的一种光谱分析技术,体现的是分子的振动或转动信息。由于拉曼光谱技术与常规化学分析技术相比,具有对样品无损、样品制备简单和所需样品量少等特点,广泛用于生物大分子结构变化的研究。拉曼光谱不仅可以用于蛋白质、核酸和脂类等生物大分子损伤的快速检测,而且可以用于癌症的诊断与手术治疗。通过对比正常组织与癌变组织的拉曼光谱,可以找到两种组织特征吸收峰的差异,从而为癌症的最终确诊和确定肿瘤切除范围提供重要信息。文章综述了拉曼光谱检测生物大分子损伤的研究进展,介绍了利用表面增强拉曼光谱、傅里叶变换拉曼光谱和紫外共振拉曼光谱等技术在检测蛋白质二级结构、膜脂及DNA损伤中的应用,并展望了未来拉曼光谱技术的发展前景。     

Research on the Raman spectral character and diagnostic value of squamous cell carcinoma of oral mucosa

Early diagnosis of oral carcinomas is essential for successful treatment. The purpose of the present study is to apply near‐infrared Raman spectroscopy to detect oral squamous cell carcinoma (SCC) and leukoplakia (OLK), in order to establish the diagnostic model of the Raman spectra of oral diseases. We collected Raman spectra of normal, OLK and SCC by near‐infrared Fourier transform Raman spectroscopy. The biochemical variations between different lesions were analyzed by the characteristic bands in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to classify spectra and establish the diagnostic models. Major differences were observed in the range between 800 and 1800 cm⁻¹. Compared with normal mucosa, high contents of protein, DNA and lipid in SCC and OLK were observed, but the difference between OLK and normal tissue was not as much as that between normal and SCC. SVM displayed a powerful ability in the classifying of normal and SCC, and the specificity, sensitivity and accuracy were 100, 97.56 and 98.75%, respectively. In discriminating between the OLK and normal groups, the three parameters were 85, 68 and 72.5%. The algorithm showed good ability in grouping and modeling of OLK and SCC, and the three parameters were 95, 97.43 and 96.25%. Combined with SVM, near‐infrared Raman spectroscopy can detect biochemical variations in oral normal mucosa, OLK and SCC, and establish diagnostic models accurately. Copyright © 2009 John Wiley & Sons, Ltd.     

Paramagnetic centers in tumor cells

Free radical properties of different types of tumor cells were compared. Electron paramagnetic resonance (EPR) studies were performed for human (BM, IGR and SK) and mouse (B16 and S91) melanoma cells. In contrast to melanotic melanoma IGR, BM and B16 cells, amelanotic S91 cells contained only a trace amount of melanin. No EPR signals were detected for Caco2 cells and only a very weak EPR line was measured for fibroblast cells. Melanin does not exist in these cells. The aim of this work was the application of EPR spectroscopy to the determination of the kind of melanin (eu- or pheomelanin) in melanotic tumor cells. Microwave saturation of EPR spectra of tumor cells with high and low melanin content was compared. Eumelanin was identified in human BM, IGR, SK, and B16 melanoma cells. Single asymmetrical EPR lines were detected for these samples. The EPR spectra of human BM melanoma cells had the highest intensity. Paramagnetic centers in amelanotic S91 melanoma cells were also found. Trace amounts of eumelanin free radicals and the other free radicals in cells were responsible for their very weak EPR lines. The obtained results indicate that EPR spectroscopy is a very useful technique for the identification of melanin in tumor cells. Strong differences of microwave saturation of EPR lines for cells with high and low melanin content were observed. EPR lines of tumor cells with a low melanin content did not saturate at the used range of microwave power. Saturation was observed for melanotic BM melanoma cells.     

拉曼光谱技术在病理诊断中的研究进展

拉曼光谱技术能够提供与物质特定分子结构相关的光谱信息,可用于识别生物组织微小的生化变异,具有快速、实时、无损、无需样本预处理等优点,在临床病理诊断领域极具应用前景。与常规组织病理学分析相比,拉曼光谱技术能够直接检测活体组织,简化了分析程序,缩短了诊断时间。人体病变组织的细胞分子组成和结构可能发生变化,这为拉曼光谱技术在组织病理诊断中的应用提供了检测依据。基于组织分子组成与结构的差异,结合机器学习和化学计量学方法,拉曼光谱技术可以提供客观的诊断信息,实现快速、低侵入的病理诊断。回顾了近十年来拉曼光谱技术在组织病理诊断中的研究进展,对取得的关键成果进行了总结,阐述了当前离体和活体应用拉曼光谱技术的一些关键问题。针对离体拉曼光谱检测,重点评估福尔马林固定石蜡包埋样本、冷冻样本和新鲜组织样本等离体样本的适用情况;阐述拉曼光谱数据收集的关键技术,包括适用光源、光谱范围,以及病理样本光谱采集的方式等。对于活体拉曼光谱检测,重点介绍了活体检测研究中拉曼光谱技术应用的两种形式:结合医用内窥镜进行体内检测,以及开放手术中的直接检测;综述了临床适用的拉曼系统,重点介绍了当前活体拉曼研究中应用的光纤探头。同...     

Inhibitory effect of Saccharomyces cerevisiae extract obtained through ultrasound-assisted extraction on melanoma cells

Although the immune enhancing effect of yeast has been widely reported, studies specifically investigating its effects on skin cancer are lacking. Therefore, this study aimed to develop a yeast extract capable of inhibiting melanoma cells using ultrasound technology, which can lyse the cell walls allowing subsequent rapid yeast extraction. To compare the extraction efficiency across different extraction methods, the total yield, as well as total glucan, α-glucan, and β-glucan yields were measured. Ultrasound-assisted extract of yeast (UAEY) was found to effectively inhibit melanoma cell growth and proliferation as well as the expression of cyclin D1 and c-myc, in vitro. Additionally, the extract reduced melanoma tumor volume and cyclin D1 levels in BALB/c nu/nu mice. The optimal extraction conditions were 0.2 M NaOH, 3 h, 70 °C, 20 kHz, and 800 W, resulting in an increased total extraction and β-glucan yields of 73.6% and 7.1%, respectively, compared with that achieved using a conventional chemical (0.5 M NaOH) extraction method. Taken together, the results of this study suggest that UAEY may represent an effective anti-skin cancer agent.     

Photoacoustic detection of metastatic melanoma cells in the human circulatory system

Detection of disseminating tumor cells among patients suffering from various types and stages of cancer can function as an early warning system, alerting the physician of the metastatic spread or recurrence of the disease. Early detection of such cells can result in preventative treatment of the disease, while late stage detection can serve as an indicator of the effectiveness of chemotherapeutics. The prognostic value of exposing disseminating tumor cells poses an urgent need for an efficient, accurate screening method for metastatic cells. We propose a system for the detection of metastatic circulating tumor cells based on the thermoelastic properties of melanoma. The method employs photoacoustic excitation coupled with a detection system capable of determining the presence of disseminating cells within the circulatory system in vitro. Detection trials consisting of tissue phantoms and a human melanoma cell line resulted in a detection threshold of the order of ten individual cells, thus validating the effectiveness of the proposed mechanism. Results imply the potential to assay simple blood draws, from healthy and metastatic patients, for the presence of cancerous melanoma providing an unprecedented method for routine cancer screening.     

基于拉曼光谱技术的甲状腺疾病检测的研究

基于光学成像与光谱技术的无损检测是生物医学光学交叉领域研究的重要发展方向。其中拉曼光谱技术可获得检测对象的生化成分的“指纹信息”,被广泛应用于面向生物分子,细胞以及生物组织的检测诊断研究。甲状腺疾病尤其肿瘤的临床检测往往涉及多方法和技术手段的结合,且存在一定的诊断难度,因此发展新的检测技术方法具有重要的意义。首先综述了拉曼光谱技术在甲状腺细胞系的单细胞拉曼光谱检测与分析,然后介绍甲状腺病理组织和甲状腺正常组织的拉曼光谱鉴别诊断(特别介绍了本研究小组开展以银纳米粒子为增强基底的甲状腺离体组织SERS光谱研究情况),以及拉曼光谱技术在甲状腺激素等方面的研究概况。最后简要探讨了拉曼光谱技术在该领域的研究应用前景和发展方向。     

Ⅱ型糖尿病人与大鼠红细胞拉曼光谱学比较

使用激光共聚焦拉曼光谱仪测量正常大鼠红细胞、正常人红细胞、糖尿病STZ造模大鼠红细胞、糖尿病四氧嘧啶造模大鼠红细胞和人Ⅱ型糖尿病红细胞的拉曼光谱,应用主成分分析(principal component analysis,PCA)结合支持向量机(support vector machines,SVM)分类器对数据进行判别分析,然后采用类间距离判断两种造模方法与人Ⅱ型糖尿病的接近程度。结果发现糖尿病红细胞与正常红细胞的拉曼光谱存在明显差异,糖尿病在酰胺 ⅥCO变形振动谱带处峰高显著,并在酰胺ⅤN—H变形振动谱带处谱线出现偏移,属于磷脂的脂酰基C—C骨架1 130 cm-1谱线增强,1 088 cm-1谱线强度减弱,说明糖尿病红细胞膜的通透性增强。PCA结合SVM可以很好地区分以上5类红细胞的拉曼光谱,分类器测试结果表明分类准确度达100%。通过分别计算两种造模方法与人Ⅱ型糖尿病的类间距离,发现STZ造模法更接近人Ⅱ型糖尿病。由此得出结论：拉曼光谱法可以用于糖尿病诊断,大鼠糖尿病STZ造模法更接近人类Ⅱ型糖尿病。     

Raman spectroscopy can discriminate distinct glioma subtypes as defined by RNA expression profiling

Raman spectroscopy is a molecular spectroscopic technique that can measure the molecular composition of tissue samples within seconds without any extraction processes or dyes. In microbiology, Raman spectroscopy is used to identify bacteriae. In glioblastoma tissue, it was reported that necrosis, normal brain and tumor can be discriminated using Raman spectroscopy. Therefore, we hypothesized that Raman spectroscopy could discriminate glioblastoma tissue from different glioma subtypes defined by RNA expression profiling. We analyzed 20 glioma samples from two distinct molecular subtypes. Both subtypes consisted of glioblastoma samples showing a variety in glioma grading and typing. The Raman spectroscopic results could be grouped in two distinct clusters in an unsupervised cluster analysis. Further analysis of these clusters showed that they were fully congruent with the two clusters as defined by RNA expression profiling. Conclusion: our results demonstrate that Raman spectroscopy can discriminate between different molecular subtypes of glioma and, therefore, may prove to be a valuable tool in in vitro cancer research. Copyright © 2013 John Wiley & Sons, Ltd.     

A comprehensive study of classification methods for medical diagnosis

In this model study, we developed a method to distinguish between breast cancer cells and normal epithelial cells, which is in principal suitable for online diagnosis by Raman spectroscopy. Two cell lines were chosen as model systems for cancer and normal tissue. Both cell lines consist of epithelial cells, but the cells of the MCF‐7 series are carcinogenic, where the MCF‐10A cells are normal growing. An algorithm is presented for distinguishing cells of the MCF‐7 and MCF‐10A cell lines, which has an accuracy rate of above 99%. For this purpose, two classification steps are utilized. The first step, the so‐called top‐level classifier searches for Raman spectra, which are measured in the nuclei region. In the second step, a wide range of discriminant models are possible and these models are compared. The classification rates are always estimated using a cross‐validation and a holdout‐validation procedure to ensure the ability of the routine diagnosis to work in clinical environments. Copyright © 2009 John Wiley & Sons, Ltd.     

Fourier Transform Infrared Spectroscopy of Skin Cancer Cells and Tissues

Abstract

The aim of this review is to combine all the information related to the characterization of skin tissues and cells, focusing on the identification of the specific biochemical characteristics of skin cancer. We have characterized two types of melanoma by FTIR spectroscopy: a murine melanoma (B16F10 cell line) and a human melanoma (C8161 cell line). The cells were deposited on IR transparent CaF₂ windows, the spectral range used lay between 900-4000 cm^{? 1}, transmission mode with 2 cm^{? 1} resolution, and 32 scans. A biochemical association is presented for all the absorption bands identified in this study. Besides the characterization of both cell lines above, a collection of works done in the area of skin cancer was also carried out, in this review; some interesting results obtained by different authors with respect to the characterization of different samples (melanomas, follicle sheath, basal cell carcinoma, epidermis tissues, dermis tissue, and human stratum corneum) are presented and compared to the chemical and biological associations performed in each case. The identification of biochemical injuries provides important information that, associated with clinical examination, can assist the diagnosis of diseases. Several FTIR techniques can be used in the diagnosis of biochemical changes in biological tissues, by identifying molecular markers associated with malignant and benign changes or variations in the composition of amino acids in tissues and cells. In the near future, a further study to compare histopatological analysis and biochemical characterization by FTIR spectroscopy would be interesting, in order to verify the accuracy and validate the applicability of this technique in the diagnosis of skin lesions from a statistical viewpoint.     

Measurement of the extracellular volume of human melanoma xenografts by contrast enhanced magnetic resonance imaging

The magnitude of the extracellular volume fraction (ECV) of tumors is of importance for the transport of macromolecular therapeutic agents from the vessel wall to the tumor cells. The aim of this study was to develop a method for measurement of tumor ECV by contrast enhanced MRI. Tumors of two human amelanotic melanoma xenograft lines (A-07 and R-18) grown intradermally in Balb/c nu/nu mice were used as model system, and muscle tissue was used as control. The renal arteries of the mice were ligated prior to i.v. administration of Gd-DTPA, and an MRI protocol for calculating Gd-DTPA concentration in tissue was followed. ECV was calculated from the Gd-DTPA concentrations in the tissue and in a plasma sample. In muscle tissue, the concentration reached a constant level after 1 min and the ECV was calculated to be 0.12 (+/- 0.01), consistent with values reported in the literature. Individual tumors showed large differences in the uptake of Gd-DTPA. The Gd-DTPA concentration in the tissue at 40 min after the Gd-DTPA administration was used to calculate tumor ECV. The ECV was found to differ significantly among regions of individual tumors and among individual tumors. The ECV ranged from 0.075 to 0.33 for A-07 tumors and from 0.016 to 0.097 for R-18 tumors. The intra- and intertumor heterogeneity in ECV was confirmed by histologic findings, showing that contrast enhanced MRI is suitable for non-invasive studies of the ECV in experimental tumors without necrosis.     

乳腺肿瘤周边组织的拉曼光谱研究

使用REMSHAW显微共焦拉曼光谱仪测量了40例手术切除乳腺肿瘤周边(肿块边约5 mm)组织的拉曼光谱.通过对浸润性导管癌、乳腺增生、纤维腺瘤等乳腺肿瘤周边组织的拉曼光谱分析,发现不同乳腺肿瘤周边组织的拉曼光谱有显著差异.这些差异在肿瘤诊断中,可作为乳腺癌和其他乳腺肿瘤拉曼光谱的特征,为乳腺疾病诊断提供依据.乳腺肿瘤周边组织的拉曼光谱对乳腺肿瘤诊断具有重要的价值.     

Analyzing normal proliferating,hypoxic and necrotic regions of T-47D human breast cancer spheroids using Raman spectroscopy

Raman spectroscopy is an advanced chemical analytical technique that has gained significant interest in cancer research, in particular early detection and monitoring of cancer, with added advantages of non-invasive and real-time diagnosis. Recently, studies have shown its sensitivity to monitor chemical changes during cancer progression. This information will lead to identification of chemical markers (molecular fingerprints of chemical composition) that can be used as biological markers. In this study, we used a tumor spheroid model that mimics the characteristics of a non-vascular in vitro tumor model, we used a combination of Raman and multivariate approach to identify chemical changes associated with normal proliferating, hypoxic and necrotic regions of T-47D human breast cancer spheroid model. The results provide evidence that lipids, amide I, III and nucleic acid contents differ significantly in normal, hypoxic and necrotic regions. Principal component analysis loading plots has suggested that normal proliferating region separated with low amide I and high-tryptophan content compared to hypoxic and necrotic regions. These differences observed in three regions might be useful in identification of new spectral markers associated stress faced by each region progressing toward necrosis.     

内吞金纳米粒子的鼻咽癌细胞SERS光谱

采用内吞方法将金纳米粒子引入细胞内,测试分析单个活性CNE-1鼻咽癌细胞的常规拉曼光谱和SERS光谱,并对其进行初步谱峰归属。CNE-1细胞的常规拉曼光谱有6个主要的拉曼峰:718,1001,1123,1336,1446和1660cm-1;沉积于细胞内的金纳米粒子强烈地增强了细胞内生化物质拉曼信号,在内吞金纳米粒子的CNE-1细胞的拉曼光谱中出现了20多个SERS拉曼信号,主要拉曼峰的强度明显高于常规拉曼信号。DNA骨架振动(1026,1097,1336和1585cm-1)证明金纳米粒子通过内吞作用而进入细胞核内。结果表明,基于胶体金SERS技术可能为活性鼻咽癌细胞内生化物质的探测提供一种高灵敏的方法。     

Near‐infrared Raman spectroscopy for gastric precancer diagnosis

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with neoplastic transformation. The purpose of this study was to apply near‐infrared (NIR) Raman spectroscopy for differentiating dysplasia from normal gastric mucosa tissue. A total of 65 gastric mucosa tissues (44 normal and 21 dysplasia) were obtained from 35 patients who underwent endoscopy investigation or gastrectomy operation for this study. A rapid NIR Raman system was utilized for tissue Raman spectroscopic measurements at 785‐nm laser excitation. High‐quality Raman spectra in the range of 800–1800 cm⁻¹ can be acquired from gastric mucosa tissue within 5 s. Raman spectra showed significant differences between normal and dysplastic tissue, particularly in the spectral ranges of 850–1150, 1200–1500 and 1600–1750 cm⁻¹, which contained signals related to proteins, nucleic acids and lipids. The diagnostic decision algorithm based on the combination of Raman peak intensity ratios of I₈₇₅/I₁₄₅₀ and I₁₂₀₈/I₁₆₅₅ and the logistic regression analysis yielded a diagnostic sensitivity of 90.5% and specificity of 90.9% for identification of gastric dysplasia tissue. This work demonstrates that NIR Raman spectroscopy in conjunction with intensity ratio algorithms has the potential for the noninvasive diagnosis and detection of precancer in the stomach at the molecular level. Copyright © 2009 John Wiley & Sons, Ltd.