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.     

Transcutaneous in vivo Raman spectroscopy of breast tumors and pretumors

Breast cancer is the most common cancer amongst women worldwide. Early detection of this cancer results in better prognosis. Owing to the disadvantages of currently available screening tools for early detection of this cancer, rapid and sensitive alternatives such as optical spectroscopic techniques are being extensively explored. Detection of premalignant lesions using these techniques has been reported. However, premalignant lesions are risk indicators and may not be true predictors of tumor development. Therefore, the current study aims at correlation between spectral changes and tumor appearance. In this context, transcutaneous in vivo spectra were acquired from same carcinogen‐induced rats immediately before carcinogen treatment, 3, 8–10, and 12–14 weeks after carcinogen treatment and from frank tumors. These were analyzed using multivariate statistical tools principal component analysis and principal component linear discriminant analysis. Further, a complex test data set consisting of spectra from rats of varying ages, tumor appearance times, and tumor induction protocols was used to test the feasibility of correctly identifying controls and pretumors using Raman spectroscopy. Results suggest feasibility of distinguishing pretumor spectra from controls. Taking into consideration the heterogeneity of afflicted breast, rat‐wise analysis was performed wherein a rat was declared ‘will develop tumor’, even if one spectrum was found abnormal. Using this criterion, in vivo Raman spectroscopy could predict tumor appearance with 82% sensitivity and 95% specificity. Prospectively, combined with emerging technologies like deep Raman spectroscopy and fiber‐probe‐based whole sample imaging, Raman spectroscopy may prove as an invaluable adjunct to currently available breast cancer screening tools. Copyright © 2015 John Wiley & Sons, Ltd.     

Method development: Raman spectroscopy‐based histopathology of oral mucosa

An earlier and more accurate detection of (small) cancerous and precancerous lesions in the oral cavity is essential to improve the prognosis of oral squamous cell carcinomas. Raman spectroscopy is being pursued as a potential method to realize this improvement, since the technique provides objective information on a biochemical level and can be used for real‐time guidance of the diagnostic procedure. Since oral mucosal tissue is inhomogeneous and comprises different layers and histological structures, a good understanding of the signal contributions of the individual layers and structures is required for an accurate interpretation of in vivo tissue spectra measurement volumes. The aim of this study was to create a standardized method to collect and analyse the spectral contributions of individual histopathological structures in oral mucosa. The method is based on Raman microspectroscopic mapping of unstained frozen tissue sections and subsequent histopathological annotation of the features in the resulting Raman images. The obtained annotated reference spectra were used as input in an unsupervised hierarchical cluster analysis in order to determine the spectral characteristics and variance within one histo(patho)logical structure. The described method resulted in an annotated database of Raman spectral characteristics of individual histopathological structures encountered in oral tissue. This database can be used as input for the development of classification and quantification algorithms, in order to achieve a high specificity and sensitivity for clinical diagnostic instruments. Additionally, this database can be used to optimize the exact location and measurement volume of in vivo measurements. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

膀胱肿瘤离体组织的拉曼光谱学研究

使用激光共聚焦显微拉曼光谱仪测取膀胱肿瘤和正常膀胱组织的拉曼特征谱,应用主成分分析/支持向量机(principal component analysis,PCA/support vector machines,SVM)分类器对数据进行判别分析,最后使用弃一交叉验证法(leave-one-out cross validation,LOOCV)测试判别结果的准确度。结果发现膀胱肿瘤组织与正常膀胱组织的拉曼光谱存在明显差异,肿瘤组织在782和1 583cm-1等核酸特征谱带处峰高显著增强,而正常组织在1 061,1 295,2 849,2 881cm-1等蛋白质和脂质特征谱带处峰高显著增强。PCA/SVM可良好区分膀胱肿瘤组织和正常膀胱组织的拉曼光谱,LOOCV测试分类器显示肿瘤诊断的敏感度86.7%、特异度87.5%、阳性预测值92.9%、阴性预测值77.8%。由此得出结论:拉曼光谱可以良好诊断膀胱肿瘤的体外组织,展现了优越的临床应用前景。     

Do formalin fixation and freeze‐thaw affect near‐infrared Raman spectroscopy of cartilaginous tissue? A preliminary ex vivo analysis of native human articular cartilage

Near‐infrared (NIR) Raman microprobe spectroscopy has been applied to the non‐invasive characterization of the biochemical structure of extracellular matrix in articular cartilage, a step forward along the path of in vivo diagnostic application of chondropathy. In most studies handling ex vivo cartilage specimens, formalin fixation or freeze‐thaw treatments have been applied in order to stabilize tissue and cell constituents prior to spectroscopic measurements. However, these pre‐processing manipulations might significantly affect certain target bands of the cartilage spectra, thus introducing biases in the characterizations, and potentially leading to data misinterpretation. In this study, we evaluated how formalin fixing and freeze‐thaw processes affect Raman spectra from human femur cartilage. Healthy cartilage specimens were fixed/stored either in a 10% neutral buffered formalin solution or in a deep freezer set at −80 °C. The results of this study show that formalin fixation significantly affects the NIR Raman spectra of cartilage specimens due to concurrent formalin absorption and water dehydration within both collagen and glycosaminoglycan macromolecules. Water dehydration was also confirmed in the amide I structure in the frozen‐thawed specimen, but to a much lesser extent. Furthermore, soaking the tissues in phosphate‐buffered saline solution minimized the storage‐induced Raman artifacts, but its immersion had limited effectiveness in formalin‐fixed specimens, predominantly due to an overlap of signals from the formalin liquid (i.e. emitting at 1046 and 1492 cm⁻¹). Therefore, to provide a highly accurate biochemical evaluation of extracellular matrix using NIR Raman spectroscopy, freeze‐thaw processes are more suitable for ex vivo samples of human cartilage than formalin fixation. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterizing variability in in vivo Raman spectroscopic properties of different anatomical sites of normal tissue in the oral cavity

Raman spectroscopy is an inelastic light scattering technique that is capable of probing biochemical and biomolecular structures and conformations of tissue. This study aims to characterize the in vivo Raman spectroscopic properties of different normal oral tissues in the fingerprint region (800–1800 cm⁻¹) and to assess distinctive biochemical variations of different anatomical regions in the oral cavity. A specially designed fiber‐optic Raman probe with a ball lens was utilized for real‐time, in vivo Raman measurements of various oral tissue sites (i.e. inner lip, attached gingiva, floor, dorsal tongue, ventral tongue, hard palate, soft palate, and buccal). The semiquantitative non‐negativity‐constrained least squares minimization fitting of reference biochemicals representing oral tissue constituents (i.e. hydroxyapatite, keratin, collagen, DNA, and oleic acid) and partial least squares‐discriminant analysis (PLS‐DA) were employed to assess the significance of inter‐anatomical variability. A total of 402 high‐quality in vivo oral Raman spectra were acquired from 20 subjects. The histological characteristics of different oral tissues were found to have influence on the in vivo Raman spectra and could be grossly divided into three major clusterings: (1) buccal, inner lip, and soft palate; (2) dorsal, ventral tongue, and floor; (3) gingiva and hard palate. The PLS‐DA multiclass algorithms were able to identify different tissue sites with varying accuracies (inner lip 83.1%, attached gingiva 91.3%, floor 86.1%, dorsal tongue 88.8%, ventral tongue 83.1%, hard palate 87.6%, soft palate 83.3%, and buccal mucosa 85.3%), bringing out the similarities among different oral tissues at the biomolecular level. This study discloses that inter‐anatomical variability is significant and should be considered as an important parameter in the interpretation and rendering of Raman diagnostic algorithms for oral tissue diagnosis and characterization. Copyright © 2011 John Wiley & Sons, Ltd.     

Surface-enhanced Raman scattering spectroscopic analysis of Saposhnikovia divaricata decoction

ABSTRACT

Surface-enhanced Raman scattering spectroscopy was employed to analyze the biochemical composition of the Saposhnikovia divaricata decoction, which is a common traditional Chinese medicine. No reliable Raman peak was observed in traditional Raman spectra of Saposhnikovia divaricata decoction. However, 12 main Raman peaks (534, 616, 648, 685, 730, 781, 850, 958, 1242, 1319, 1460, and 1571 cm^?1) were observed in the surface-enhanced Raman scattering spectroscopy spectra from the mixture of silver colloids with Saposhnikovia divaricata decoction as a result of the silver colloid enhanced effects on the Raman scattering of Saposhnikovia divaricata decoction. The results demonstrated that the surface-enhanced Raman scattering spectroscopy may provide a new kind of non-destructive, accurate, direct, and fast detecting method for the Saposhnikovia divaricata decoction or other traditional Chinese medicine in the form of decoction.     

Raman spectroscopic analysis differentiates between breast cancer cell lines

Breast cancer incident rates are increasing in women worldwide with the highest incidence rates reported in developing countries. Major breast cancer screening approaches like mammography, ultrasound, clinical breast examination (CBE) and magnetic resonance imaging (MRI) are currently used but have their own limitations. Optical spectroscopy has attained great attention from biomedical researchers in recent years due to its non‐invasive and non‐destructive detection approach. Chemometrics is one of the powerful tools used in spectroscopic research to enhance its sensitivity. Raman spectroscopy, a vibrational spectroscopic approach, has been used to explore the chemical fingerprints of different biological tissues including normal and malignant types. This approach was used to characterize and differentiate two breast cancer and one normal breast cell lines (MDA‐MB‐436, MCF‐7 and MCF‐10A) using dispersive Raman spectroscopy. Raman spectra of the cell lines have revealed that basic differences in the concentration of biochemical compounds such as lipids, nucleic acids and protein Raman peaks were found to differ in intensity, and principal component analysis (PCA) was able to identify variations that lead to accurate and reliable separation of the three cell lines. Linear discriminant analysis (LDA) model of three cell lines was predicted with 100% sensitivity and 91% specificity. We have shown that a combination of Raman spectroscopy and chemometrics are capable of differentiation between breast cancer cell lines. These variations may be useful in identifying new spectral markers to differentiate different subtypes of breast cancer although this needs confirmation in a larger panel of cell lines as well as clinical material. Copyright © 2015 John Wiley & Sons, Ltd.     

Multiclass discrimination of cervical precancers using Raman spectroscopy

Raman spectroscopy has the potential to differentiate among the various stages leading to high‐grade cervical cancer such as normal, squamous metaplasia, and low‐grade cancer. For Raman spectroscopy to successfully differentiate among the stages, an applicable statistical method must be developed. Algorithms like linear discriminant analysis (LDA) are incapable of differentiating among three or more types of tissues. We developed a novel statistical method combining the method of maximum representation and discrimination feature (MRDF) to extract diagnostic information with sparse multinomial logistic regression (SMLR) to classify spectra based on nonlinear features for multiclass analysis of Raman spectra. We found that high‐grade spectra classified correctly 95% of the time; low‐grade data classified correctly 74% of the time, improving sensitivity from 92 to 98% and specificity from 81 to 96% suggesting that MRDF with SMLR is a more appropriate technique for categorizing Raman spectra. SMLR also outputs a posterior probability to evaluate the algorithm's accuracy. This combined method holds promise to diagnose subtle changes leading to cervical cancer. Copyright © 2008 John Wiley & Sons, Ltd.     

对痕量羊角材料降解产物的表面增强拉曼光谱研究

将一定浓度的硝酸银与柠檬酸三钠混合后,利用微波加热法制备纳米银溶胶,该方法加热速度快、温度分布均匀、反应条件易控制。采用准弹性激光散射技术检测其粒度大小及分布状态的信息,测得其平均粒度为(53.27±2.65)nm,粒度大小集中分布在56 nm左右。然后以之作为表面增强拉曼光谱(SERS)的活性基底,研究测定羊角痕量降解产物的SERS光谱。结果发现,羊角降解产物的表面增强拉曼效应显著,尤其在659,830,850,929,999,1 028,1 280,1 439,1 599 cm-1等多处出现了明显的拉曼振动峰,这些谱峰反映了羊角降解产物的生化成分信息。并且通过对所获得的羊角降解产物SERS信号进行的谱峰归属分析表明,羊角降解产物主要为氨基酸与多肽类物质。运用表面增强拉曼光谱检测角材料的降解产物,获得较高的灵敏度,可测定浓度低至ppm水平的痕量降解产物,本研究表明,SERS可能为羊角等角材料降解产物的检测提供一种快速、直观、准确的新方法。     

Raman spectroscopy measurement of levofloxacin lactate in blood using an optical fiber nano‐probe

Liquid chromatography and mass spectrometry were time‐consuming and expensive as the main methods for the drug analysis at present, and the samples must be pretreated. The Raman spectroscopy measurement methods were fast and simple, so the Raman spectroscopy methods for the drug analysis were explored in this paper. An optical fiber nano‐probe coated with gold nanoparticles was fabricated and used with surface‐enhanced Raman spectroscopy (SERS) to measure levofloxacin lactate. The resulting SERS spectra of levofloxacin lactate in mouse blood that was detected by the optical fiber nano‐probe clearly showed the characteristic wave numbers of levofloxacin lactate, indicating that optical fiber nano‐probes can be used with spectral techniques to analyze drugs in vitro or potentially even in vivo. Copyright © 2015 John Wiley & Sons, Ltd.     

In vivo study on the protection of indole‐3‐carbinol (I3C) against the mouse acute alcoholic liver injury by micro‐Raman spectroscopy

Micro‐Raman spectroscopy (MRS) was utilized for the first time to evaluate the effect of indole‐3‐carbinol (I3C) on acute alcoholic liver injury in vivo. In situ Raman analysis of tissue sections provided distinct spectra that can be used to distinguish alcoholic liver injury as well as ethanol‐induced liver fibrosis from the normal state. Sixteen mice with liver diseases including acute liver injury and chronic liver fibrosis, and eight mice with normal liver tissues, and eight remedial mice were studied employing the Raman spectroscopic technique in conjunction with biomedical assays. The biochemical changes in mouse liver tissue when liver injury/fibrosis occurs such as the loss of reduced glutathione (GSH), and the increase of collagen (α‐helix protein) were observed by MRS. The intensity ratio of two Raman peaks (I₁₄₅₀/I₆₆₆) and in combination with statistical analysis of the entire Raman spectrum was found capable of classifying liver tissues with different pathological features. Raman spectroscopy therefore is an important candidate for a nondestructive in vivo screening of the effect of drug treatment on liver disease, which potentially decreases the time‐consuming clinical trials. Copyright © 2008 John Wiley & Sons, Ltd.     

基于唾液的拉曼光谱检测进行肝癌诊断的研究

表面增强拉曼光谱技术是近年来快速发展的一种痕量特征标记性物质检测技术, 达到了分子识别水平, 具有很高的灵敏度, 能够精确地分析和了解物质结构和成分。人体唾液中含有大量体征相关的特异性蛋白质和分泌物质。唾液检测具有无创、获取方便、适合开展大规模普查等优点。表面增强拉曼光谱检测技术可以快速地对唾液进行检测, 二者的结合, 有可能成为一种癌症诊断的新方法。本文利用表面增强光谱技术对肝癌患者进行实验研究, 通过对肝癌患者唾液的采集、样品的处理、光谱的采集及光谱分析, 肝癌特异性标记物AFP(alpha fetoprotein)的检测及分析等过程得到肝癌相关特征信息, 表明肝癌患者与正常人的唾液样本分类良好, 灵敏度及特异性较好; 进一步验证了AFP抗原的分子组成, 且AFP抗原的拉曼强度基本随浓度的递增呈递减趋势; 对肝癌患者的唾液样本及AFP抗原的拉曼光谱进行比对分析, 提示利用表面增强拉曼光谱检测唾液有可能诊断早期癌症。     

Near‐infrared surface‐enhanced Raman spectroscopy (NIR‐SERS) studies on oxyheamoglobin (OxyHb) of liver cancer based on PVA‐Ag nanofilm

A near‐infrared surface‐enhanced Raman spectroscopy (NIR‐SERS) method was employed for oxyheamoglobin (OxyHb) detection to develop a simple blood test for liver cancer detection. Polyvinyl alcohol protected silver nanofilm (PVA‐Ag nanofilm) used as the NIR‐SERS active substrate to enhance the Raman scattering signals of OxyHb. High quality NIR‐SERS spectrum from OxyHb adsorbed on PVA‐Ag nanofilm can be obtained within 16 s using a portable Raman spectrometer. NIR‐SERS measurements were performed on OxyHb samples of healthy volunteers (control subjects, n = 30), patients (n = 40) with confirmed liver cancer (stage I, II and III) and the liver cancer patients after surgery (n = 30). Meanwhile, the tentative assignments of the Raman bands in the measured NIR‐SERS spectra were performed, and the results suggested cancer specific changes on molecule level, including a decrease in the relative concentrations and the percentage of aromatic amino acids of OxyHb, changes of the vibration modes of the C_aH_m group and pyrrole ring of OxyHb of liver cancer patients. In this paper, principal component analysis (PCA) combined with independent sample T test analysis of the measured NIR‐SERS spectra separated the spectral features of the two groups into two distinct clusters with the sensitivity of 95.0% and the specificity of 85.7%. Meanwhile, the recovery situations of the liver cancer patients after surgery were also assessed using the method of discriminant analysis‐predicting group membership based on PCA. The results show that 26.7% surgeried liver cancer patients were distinguished as the normal subjects and 63.3% were distinguished into the cancer. Our study demonstrated great potentials for developing NIR‐SERS OxyHb analysis into a novel clinical tool for non‐invasive detection of liver cancers. Copyright © 2013 John Wiley & Sons, Ltd.     

Trace level detection and identification of nitro‐based explosives by surface‐enhanced Raman spectroscopy

Methods for rapid identification of explosives and their associated compounds at trace level quantities are needed for security screening applications. In this paper, we apply the surface‐enhanced Raman spectroscopy (SERS) to detect and identify traces (as low as tens of pg) of pentaerythritol tetranitrate (PETN), ethylene glycol dinitrate (EGDN), cyclotrimethylene‐trinitramine (RDX) and trinitrotoluene (TNT) using commercially available substrates (Klarite®, Renishaw diagnostics). High quality spectra were achieved within 10 s with a compact Raman spectrometer. Principal component analysis (PCA) of the data was performed to understand what factors affected the spectral variation across the samples. It was found that 76% of the spectral variation was explained by the first three PCs. Score plots for these components showed that the energetic materials can be clearly classified on the basis of SERS spectra also at trace level quantity. Our measurements further demonstrate the potential for using SERS as fast, in situ analytical tool for safety devices, with a sensitivity which competes and, in some cases, overcomes other techniques. Copyright © 2013 John Wiley & Sons, Ltd.     

Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection

Combining membrane electrophoresis with surface‐enhanced Raman scattering (SERS) spectroscopy, the serum proteins were first purified and then mixed with silver nanoparticles to perform SERS spectral analysis. Therefore, the spectral signatures were enhanced to high‐fidelity SERS signatures because of the purification procedure of the first step. We used the method to analyze blood plasma samples from nasopharyngeal cancer patients (n = 43) and healthy volunteers (n = 33) for cancer detection. Principle component analysis of the SERS spectra revealed that the data points for the cancer group and the normal group form distinct, completely separated clusters with no overlap. Therefore, the nasopharyngeal cancer group can be unambiguously discriminated from the normal group, i.e., with both diagnostic sensitivity and specificity of 100%. These results are very promising for developing a label‐free, noninvasive, and reliable clinical tool for rapid cancer detection and screening. Copyright © 2011 John Wiley & Sons, Ltd.     

Effects of laser excitation wavelength and optical mode on Raman spectra of human fresh colon,pancreas, and prostate tissues

Early cancer detection is the central and most important factor for allowing successful treatment and resultant positive long‐term patient outcomes. Recently, optical techniques have been applied to this purpose, although each has inherent limitations. In particular, Raman spectroscopy applied in the pathological diagnosis of cancerous tissues has received increasing attention, with the merit of being highly sensitive to the biochemical alterations in tissue compositions and applicable in vivo. Nevertheless, its application has been impeded by the high background intensity, which masks the Raman signal of biological molecules. In this work, the influence of laser excitation wavelength (785 vs. 830 nm) and optical mode (single mode vs. multimode) on the background intensity of fresh human tissues was studied. Based on the results, laser with 830 nm excitation demonstrated better background reduction than that with 785 nm excitation for the same optical mode, but the Raman signal intensity was conversely reduced, and the signal‐to‐noise ratio (SNR) not improved. In contrast, by comparing single‐mode and multimode 785 nm excitations, it was shown that the single‐mode laser with its smaller beam waist and beam propagation factor had better background reduction ability and an improvement of the SNRs. It is speculated that this decrease in background intensity comes from the effect of the optical mode on the Mie scattering from the biological tissue. High‐quality spectra based on a careful selection of both laser excitation wavelength and optical mode will benefit Raman measurements in further research focusing on spectral interpretation and histopathological correlation ultimately aimed toward intraoperative applications. Copyright © 2014 John Wiley & Sons, Ltd.     

拉曼光纤技术快速无损鉴别甲硝唑片

采用光纤探头直接放在甲硝唑片上进行检测,采集谱图,对拉曼光谱峰进行指认,并改变测定条件(药品隔铝塑包装、刮除包膜)进行测定。建立了光纤传感技术结合拉曼光谱快速无损鉴别甲硝唑片的方法,所测药物图谱峰形良好、峰强明显、指纹性强、测定快速准确,可瞬间获得片剂的特征图谱。样品无需进行前处理,可无损鉴别。药片检测时,是否隔铝塑包装和刮除包膜不影响谱图识别。本法快速、准确、专属性强、灵敏度高,可用于对甲硝唑片进行有效的鉴别。     

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.