Vibrational spectroscopy: a clinical tool for cancer diagnostics

Differentiation of neotropical fish species with statistical analysis of fourier transform infrared photoacoustic spectroscopy data

Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) was applied to nineteen fish species in Brazil's Upper Paraná River basin to identify differences in the structural composition of their scales. To differentiate the species, a canonical discriminant analysis was used to indicate the most important absorption peaks in the mid-infrared region. Significant differences were found in the chemical composition of scales among the studied fish species, with Wilk's lambda = 5.2 × 10(-6), F((13,18,394)) = 37.57, and P < 0.001, indicating that O-CH(2) wag at 1396 cm(-1) can be used as a biomarker of this species group. The species could be categorized into four groups according to phylogenetic similarity, suggesting that the O-CH(2) 1396 cm(-1) absorbance is related to the biological traits of each species. This procedure can also be used to complement evolutionary studies.

Vibrational spectroscopy: a tool being developed for the noninvasive monitoring of wound healing

Wound care and management accounted for over 1.8 million hospital discharges in 2009. The complex nature of wound physiology involves hundreds of overlapping processes that we have only begun to understand over the past three decades. The management of wounds remains a significant challenge for inexperienced clinicians. The ensuing inflammatory response ultimately dictates the pace of wound healing and tissue regeneration. Consequently, the eventual timing of wound closure or definitive coverage is often subjective. Some wounds fail to close, or dehisce, despite the use and application of novel wound-specific treatment modalities. An understanding of the molecular environment of acute and chronic wounds throughout the wound-healing process can provide valuable insight into the mechanisms associated with the patient's outcome. Pathologic alterations of wounds are accompanied by fundamental changes in the molecular environment that can be analyzed by vibrational spectroscopy. Vibrational spectroscopy, specifically Raman and Fourier transform infrared spectroscopy, offers the capability to accurately detect and identify the various molecules that compose the extracellular matrix during wound healing in their native state. The identified changes might provide the objective markers of wound healing, which can then be integrated with clinical characteristics to guide the management of wounds.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Raman 'optical biopsy' of human breast cancer

Raman imaging (RI) is a novel method of medical diagnostics of human breast cancer and has a potential to become a routine optical biopsy. Up to date the present study is the most statistically reliable Raman analysis based on data of normal, benign, and cancerous breast tissues for 146 patients. This paper present the first Raman 'optical biopsy' images of the normal and cancerous breast tissue of the same patient. The results presented here demonstrate the ability of Raman spectroscopy to accurately characterize cancer tissue and distinguish between normal (noncancerous), and cancerous types. The results provide evidence that carotenoids and lipids composition of cancerous breast tissues differs significantly from that of the surrounding noncancerous breast tissue and may be a key factor responsible for mechanisms of carcinogenesis. We have found that fatty acid composition of the cancerous breast tissue is markedly different from that of the surrounding noncancerous breast tissue. The cancerous breast tissue seems to be dominated by the metabolism products of the arachidonic acid - derived cyclic eicosanoids catalyzed by cyclooxygenase, while the noncancerous breast tissue is dominated by monounsaturated oleic acid and its derivatives.

Raman's "effect" on molecular imaging

Raman spectroscopy is an optical technique that offers unsurpassed sensitivity and multiplexing capabilities to the field of molecular imaging. In the past, Raman spectroscopy had predominantly been used as an analytic tool for routine chemical analysis, but more recently, researchers have been able to harness its unique properties for imaging and spectral analysis of molecular interactions in cell populations and preclinical animal models. Additionally, researchers have already begun to translate this optical technique into a novel clinical diagnostic tool using various endoscopic strategies.

Raman spectroscopic methods for classification of normal and malignant hypopharyngeal tissues: an exploratory study

Laryngeal cancer is more common in males. The present study is aimed at exploration of potential of conventional Raman spectroscopy in classifying normal from a malignant laryngopharyngeal tissue. We have recorded Raman spectra of twenty tissues (aryepiglottic fold) using an in-house built Raman setup. The spectral features of mean malignant spectrum suggests abundance proteins whereas spectral features of mean normal spectrum indicate redundancy of lipids. PCA was employed as discriminating algorithm. Both, unsupervised and supervised modes of analysis as well as match/mismatch "limit test" methodology yielded clear classification among tissue types. The findings of this study demonstrate the efficacy of conventional Raman spectroscopy in classification of normal and malignant laryngopharyngeal tissues. A rigorous evaluation of the models with development of suitable fibreoptic probe may enable real-time Raman spectroscopic diagnosis of laryngopharyngeal cancers in future.

Raman imaging of single living cells: probing effects of non-cytotoxic doses of an anti-cancer drug

Identifying cell response to a chemotherapy drug treatment, in particular at the single cell level, is an important issue in patient management. This study aims at evaluating the effect of gemcitabine on single living cells using micro-Raman imaging. We used as a model the non-small lung cancer cell line, Calu-1, exposed to cytostatic doses (1 nM to 1 μM for 24 h and 48 h) of gemcitabine, an antitumor drug currently used in the treatment of lung cancer. Following drug treatment as a function of doses and incubation times, the Raman maps of single living cells were acquired. Cell biomolecules (DNA, RNA, and proteins) were chemically extracted and their spectral signatures used to evaluate their respective distribution in the cellular spectral information of control and treated cells. The quantification of these distributions reveals a significant effect of 100 nM gemcitabine at 48 h incubation (concomitant decrease of nucleic acids and increase of proteins). PCA analyses performed both on nuclear and extracted biomolecules spectra show a time-dependent effect of the drug. These promising results reveal that effects of subtoxic doses can be monitored at the single cell level highlighting the importance of such studies for clinical applications.

Raman spectroscopic grading of astrocytoma tissues: using soft reference information

Gliomas are the most frequent primary brain tumours. During neurosurgical treatment, locating the exact tumour border is often difficult. This study assesses grading of astrocytomas based on Raman spectroscopy for a future application in intra-surgical guidance. Our predictive classification models distinguish the surgically relevant classes "normal tissue" and "low" and "high grade astrocytoma" in Raman maps of moist bulk samples (80 patients) acquired with a fibre-optic probe. We introduce partial class memberships as a strategy to utilize borderline cases for classification. Borderline cases supply the most valuable training and test data for our application. They are (a) examples of the sought boundary and (b) the cases for which new diagnostics are needed. Besides, the number of suitable training samples increases considerably: soft logistic regression (LR) utilizes 85% more spectra and 50% more patients than linear discriminant analysis (LDA). The predictive soft LR models achieve ca. 85, 67 and 84% (normal, low and high grade) sensitivity and specificity. We discuss the different heuristics of LR and LDA in the light of borderline samples. While we focus on prediction, the spectroscopic interpretation of the predictive models agrees with previous descriptive studies. Unsaturated lipids are used to differentiate between normal and tumour tissues, while the total lipid content prominently contributes to the determination of the tumour grade. The high-wavenumber region above 2,800 cm(-1) alone did not allow successful grading. We give a proof of concept for Raman spectroscopic grading of moist astrocytoma tissues and propose to include borderline samples into classifier training and testing.

Automation of an algorithm based on fuzzy clustering for analyzing tumoral heterogeneity in human skin carcinoma tissue sections

This study aims to develop a new FT-IR spectral imaging of tumoral tissue permitting a better characterization of tumor heterogeneity and tumor/surrounding tissue interface. Infrared (IR) data were acquired on 13 biopsies of paraffin-embedded human skin carcinomas. Our approach relies on an innovative fuzzy C-means (FCM)-based clustering algorithm, allowing the automatic and simultaneous estimation of the optimal FCM parameters (number of clusters K and fuzziness index m). FCM seems more suitable than classical 'hard' clusterings, as it permits the assignment of each IR spectrum to every cluster with a specific membership value. This characteristic allows differentiating the nuances in the assignment of pixels, particularly those corresponding to tumoral tissue and those located at the tumor/peritumoral tissue interface. FCM images permit to highlight a marked heterogeneity within the tumor and characterize the interconnection between tissular structures. For the infiltrative tumors, a progressive gradient in the membership values of the pixels of the invasive front was also revealed.

Coherent anti-Stokes Raman scattering hyperspectral tissue imaging with a wavelength-swept system

We present a wavelength-swept coherent anti-Stokes Raman scattering (WS-CARS) spectroscopy system for hyperspectral imaging in thick tissue. We use a strategy where the Raman lines are excited sequentially, circumventing the need for a spectrometer. This fibre laser system, consisting of a pump laser synchronized with a rapidly tunable programmable laser (PL), can access Raman lines over a significant fraction of the high wavenumber region (2700-2950 cm(-1)) at rates of up to 10,000 spectral points per second. To demonstrate its capabilities, we have acquired WS-CARS spectra of several samples as well as images and hyperspectral images (HSI) of thick tissue both in forward and epi-detection. This instrument should be especially useful in providing local biochemical information with surrounding context supplied by imaging.

Raman spectroscopy--a potential new method for the intra-operative assessment of axillary lymph nodes

Sentinel Lymph Node Biopsy has become the standard surgical procedure for the sampling of axillary lymph nodes in breast cancer. Intra-operative node assessment of these nodes would allow definitive axillary surgery to take place immediately with associated benefits for patient management. Our experimental study aims to demonstrate that a Raman spectroscopy probe system could overcome many of the disadvantages of current intra-operative methods. 59 axillary lymph nodes, 43 negative and 16 positive from 58 patients undergoing breast surgery at our district general hospital were mapped using Raman micro-spectroscopy. These maps were then used to model the effect of using a Raman spectroscopic probe by selecting 5 and 10 probe points across the mapped images and evaluating the impact on disease detection. Results demonstrated sensitivities of up to 81% and specificities of up to 97% when differentiating between positive and negative lymph nodes, dependent on the number of probe points included. The results would have concurred with histopathology assessment in 89% and 91% of cases in the 5 and 10 point models respectively. Using Raman spectroscopy in this way could allow lymph node assessment within a time-frame suitable for intra-operative use.

Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability

The process of carcinogenesis in the colon progresses through several overlapping stages, making the evaluation process challenging, as well as subjective. Owing to the complexity of colonic tissues and the search for a technique that is rapid and foolproof for precise grading and evaluation of biopsies, many spectroscopic techniques have been evaluated in the past few decades for their efficiency and clinical compatibility. Fourier-transform infrared spectroscopy, being quantitative and objective, has the capacity for automation and relevance to cancer diagnosis. This article highlights investigations on the application of Fourier-transform infrared spectroscopy (particularly microscopy) in colon cancer diagnosis and parallel developments in data analysis techniques for the characterization of spectral signatures of malignant tissues in the colon.

Comparative evaluation of spectroscopic models using different multivariate statistical tools in a multicancer scenario

Cancer is now recognized as one of the major causes of morbidity and mortality. Histopathological diagnosis, the gold standard, is shown to be subjective, time consuming, prone to interobserver disagreement, and often fails to predict prognosis. Optical spectroscopic methods are being contemplated as adjuncts or alternatives to conventional cancer diagnostics. The most important aspect of these approaches is their objectivity, and multivariate statistical tools play a major role in realizing it. However, rigorous evaluation of the robustness of spectral models is a prerequisite. The utility of Raman spectroscopy in the diagnosis of cancers has been well established. Until now, the specificity and applicability of spectral models have been evaluated for specific cancer types. In this study, we have evaluated the utility of spectroscopic models representing normal and malignant tissues of the breast, cervix, colon, larynx, and oral cavity in a broader perspective, using different multivariate tests. The limit test, which was used in our earlier study, gave high sensitivity but suffered from poor specificity. The performance of other methods such as factorial discriminant analysis and partial least square discriminant analysis are at par with more complex nonlinear methods such as decision trees, but they provide very little information about the classification model. This comparative study thus demonstrates not just the efficacy of Raman spectroscopic models but also the applicability and limitations of different multivariate tools for discrimination under complex conditions such as the multicancer scenario.

Surface-enhanced Raman scattering (SERS) cytometry

Significant advances have been made in the preparation and applications of surface-enhanced Raman scattering (SERS)-active materials for biomolecular analysis. Bright signals, photostability, and narrow spectral features of SERS-active materials offer attractive advantages for cytometric analyses. However, SERS cytometry is still in an early stage of development, and advances in both instrumentation and reagents will be necessary to realize its full potential. In this chapter, we discuss the challenges of expanding the numbers of fluorescent labels that can be measured in cytometry, and introduce SERS tags with extremely narrow spectral peaks as an approach to make more efficient use of the optical spectrum and increase the number of parameters in cytometry.

Detection of cervical metastatic lymph nodes in papillary thyroid carcinoma by Fourier transform infrared spectroscopy

Background

A previous study demonstrated that Fourier transform infrared (FTIR) spectroscopy can distinguish thyroid cancer from benign thyroid lesions. The aim of this study was to explore the use of FTIR for identifying metastatic lymph nodes of papillary thyroid cancer in vitro, and distinguishing between metastatic and non-metastatic tissue.

Methods

Some 184 freshly removed cervical lymph nodes were obtained from 22 patients with papillary thyroid cancer undergoing thyroid surgery with lymph node dissection. Samples were measured by FTIR spectroscopy before being processed for histopathological diagnosis. The FTIR spectrum of each sample identified 13 bands from 1000 to 4000 cm−1. The peak position, intensity and full width at half maximum of each absorbent band were measured, and the relative intensity ratios were calculated. The FTIR spectra of metastatic lymph nodes were compared with those of non-metastatic nodes, and a linear discriminant analysis was performed based on these data.

Results

Histopathological examination confirmed 61 metastatic and 123 non-metastatic lymph nodes. The FTIR parameters of metastatic and non-metastatic lymph nodes differed owing to the content or configuration alterations of nucleic acids, proteins, lipids and carbohydrates. The sensitivity for FTIR in diagnosing metastatic lymph nodes was 80·3 per cent, the specificity was 91·9 per cent and the accuracy was 88·0 per cent.

Conclusion

FTIR spectroscopy is a novel technique for detection of metastatic lymph nodes and may prove useful in surgery for papillary thyroid cancer.

Evaluation of linear discriminant analysis for automated Raman histological mapping of esophageal high-grade dysplasia

Rapid Raman mapping has the potential to be used for automated histopathology diagnosis, providing an adjunct technique to histology diagnosis. The aim of this work is to evaluate the feasibility of automated and objective pathology classification of Raman maps using linear discriminant analysis. Raman maps of esophageal tissue sections are acquired. Principal component (PC)-fed linear discriminant analysis (LDA) is carried out using subsets of the Raman map data (6483 spectra). An overall (validated) training classification model performance of 97.7% (sensitivity 95.0 to 100% and specificity 98.6 to 100%) is obtained. The remainder of the map spectra (131,672 spectra) are projected onto the classification model resulting in Raman images, demonstrating good correlation with contiguous hematoxylin and eosin (HE) sections. Initial results suggest that LDA has the potential to automate pathology diagnosis of esophageal Raman images, but since the classification of test spectra is forced into existing training groups, further work is required to optimize the training model. A small pixel size is advantageous for developing the training datasets using mapping data, despite lengthy mapping times, due to additional morphological information gained, and could facilitate differentiation of further tissue groups, such as the basal cells∕lamina propria, in the future, but larger pixels sizes (and faster mapping) may be more feasible for clinical application.

Cluster analysis of infrared spectra of rabbit cortical bone samples during maturation and growth

Bone consists of an organic and an inorganic matrix. During development, bone undergoes changes in its composition and structure. In this study we apply three different cluster analysis algorithms [K-means (KM), fuzzy C-means (FCM) and hierarchical clustering (HCA)], and discriminant analysis (DA) on infrared spectroscopic data from developing cortical bone with the aim of comparing their ability to correctly classify the samples into different age groups. Cortical bone samples from the mid-diaphysis of the humerus of New Zealand white rabbits from three different maturation stages (newborn (NB), immature (11 days-1 month old), mature (3-6 months old)) were used. Three clusters were obtained by KM, FCM and HCA methods on different spectral regions (amide I, phosphate and carbonate). The newborn samples were well separated (71-100% correct classifications) from the other age groups by all bone components. The mature samples (3-6 months old) were well separated (100%) from those of other age groups by the carbonate spectral region, while by the phosphate and amide I regions some samples were assigned to another group (43-71% correct classifications). The greatest variance in the results for all algorithms was observed in the amide I region. In general, FCM clustering performed better than the other methods, and the overall error was lower. The discriminate analysis results showed that by combining the clustering results from all three spectral regions, the ability to predict the correct age group for all samples increased (from 29-86% to 77-91%). This study is the first to compare several clustering methods on infrared spectra of bone. Fuzzy C-means clustering performed best, and its ability to study the degree of memberships of samples to each cluster might be beneficial in future studies of medical diagnostics.

Characterization of microRNA-125b expression in MCF7 breast cancer cells by ATR-FTIR spectroscopy

MicroRNAs (miRNAs), are ~22 nucleotides long, non-coding RNAs that control gene expression post-transcriptionally by binding to their target mRNA's 3'UTRs (untranslated regions). Due to their roles in various important regulatory processes and pathways, miRNAs have been implicated in disease mechanisms such as tumorigenesis when their expression is deregulated. To date, a significant number of miRNAs and their target messenger RNAs (mRNAs) have been identified and verified. It is generally accepted that miRNAs can potentially bind to many mRNAs, which brings the requirement of validation of these interactions. While understanding that such individual interactions is crucial to delineate the role of a specific miRNA, we took a holistic approach and analyzed global changes in the cell due to expression of a miRNA in a model cell line system. Our model consisted of MCF7 cells stably transfected with miR-125b (MCF7-125b) and empty vector (MCF7-EV). MiR-125b is one of the known down-regulated miRNAs in breast cancers. In this study we examined the global structural changes in MCF7 cells lacking and expressing miR-125b by Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy and investigated the dynamic changes by more sensitive spin-labelling Electron Spin Resonance (ESR) spectroscopy. Our results revealed less RNA, protein, lipid, and glycogen content in MCF7-125b compared to MCF7-EV cells. Membrane fluidity and proliferation rate were shown to be lower in MCF7-125b cells. Based on these changes, MCF7-125b and MCF7-EV cells were discriminated successfully by cluster analysis. Here, we provide a novel means to understand the global effects of miRNAs in cells. Potential applications of this approach are not only limited to research purposes. Such a strategy is also promising to pioneer the development of future diagnostic tools for deregulated miRNA expression in patient samples.

Evaluation of Raman probe for oesophageal cancer diagnostics

Early detection of (pre-)cancerous changes improves prognosis, therefore in the UK patients at high risk of developing gastrointestinal cancers are enrolled on endoscopic surveillance programmes or the Bowel Cancer Screening Programme. The current gold standard technique for the detection of pre-cancerous changes in the gastrointestinal tract is histopathological analysis of biopsy tissue collected at endoscopy. This relies upon subjective assessment of morphological changes within the excised tissue samples and poor targeting of pre-malignant lesions. Raman spectroscopy offers a number of potential advantages for in vivo assessment of tissue at endoscopy. The performance of a custom built Raman probe as a biopsy targeting tool has been evaluated using excised biopsy material. Multivariate classification models have been used to demonstrate the likely ability of a miniature, confocal, fibre optic Raman probe to be used as an optical biopsy tool at endoscopy to provide spectral information in clinically practicable timescales. This technique could facilitate improved targeting of excisional biopsy with associated clinical benefits.

Highly sensitive identification of cancer cells by combining the new tetrathiafulvalene derivative with a β-cyclodextrin/multi-walled carbon nanotubes modified GCE

In this contribution, we have prepared and explored a novel nano-interface based probe for the rapid identification and highly sensitive detection of cancer cells by means of an electrochemical study. The new probe tetrathiafulvalene (TTF) carboxylate salt (TTF-(COONBu(4))(2), ditetrabutylammonium salt for propylenedithio-4',5'-tetrathiafulvalene-4,5-dicarboxylate), which has specific spectral and electrochemical properties, has been synthesized and assembled with carbon nanotubes to form a new type of nanocomposite. A simple method of fabricating the β-CD/MWCNT modified electrodes based on functionalized multi-walled carbon nanotubes (MWCNTs) and β-cyclodextrin (β-CD) has been explored by using glassy carbon electrodes (GCEs), which could remarkably enhance the sensitivity of the biomolecular detection. Our results demonstrate that the combination of the new probe TTF-(COONBu(4))(2) with β-CD/MWCNT modified electrodes could be readily utilized to sensitively detect cancer cells such as liver cancer cells SMMC-7721 and HepG2, drug sensitive leukemia K562/B.W cells and drug resistant leukemia K562/ADM cells, with a detection limit of ~10(3) cells mL(-1). This may provide a novel strategy for the potential and promising application of the new TTF molecular probe in the development of multi-signal responsive biosensors for the early diagnosis of cancers.

Structural analysis of the antimalarial drug halofantrine by means of Raman spectroscopy and density functional theory calculations

The structure of the antimalarial drug halofantrine is analyzed by means of density functional theory (DFT) calculations, IR, and Raman spectroscopy. Strong, selective enhancements of the Raman bands of halofantrine at 1621 and 1590 cm(-1) are discovered by means of UV resonance Raman spectroscopy with excitation wavelength lambda(exc)=244 nm. These signal enhancements can be exploited for a localization of small concentrations of halofantrine in a biological environment. The Raman spectrum of halofantrine is calculated by means of DFT calculations [B3LYP/6-311+G(d,p)]. The calculation is very useful for a thorough mode assignment of the Raman bands of halofantrine. The strong bands at 1621 and 1590 cm(-1) in the UV Raman spectrum are assigned to combined C[Double Bond]C stretching vibrations in the phenanthrene ring of halofantrine. These bands are considered as putative marker bands for pipi interactions with the biological target molecules. The calculation of the electron density demonstrates a strong distribution across the phenanthrene ring of halofantrine, besides the electron withdrawing effect of the Cl and CF(3) substituents. This strong and even electron density distribution supports the hypothesis of pipi stacking as a possible mode of action of halofantrine. Complementary IR spectroscopy is performed for an investigation of vibrations of polar functional groups of the halofantrine molecule.

BRMS1 expression alters the ultrastructural, biomechanical and biochemical properties of MDA-MB-435 human breast carcinoma cells: an AFM and Raman microspectroscopy study

Restoring BReast cancer Metastasis Suppressor 1 (BRMS1) expression suppresses metastasis in MDA-MB-435 human breast carcinoma cells at ectopic sites without affecting tumor formation at orthotopic site in the body. BRMS1 expression induces many phenotypic alterations in 435 cells such as cell adhesion, cytoskeleton rearrangement, and the down regulation of epidermal growth factor receptor (EGFR) expression. In order to better understand the role of cellular biomechanics in breast cancer metastasis, the qualitative and quantitative detection of cellular biomechanics and biochemical composition is urgently needed. In the present work, using atomic force microscopy (AFM) and fluorescent microscopy we revealed that BRMS1 expression in 435 cells induced reorganization of F-actin and caused alteration in cytoarchitectures (cell topography and ultrastructure). Results from AFM observed increase in biomechanical properties which include cell adhesion, cellular spring constant, and Young's modulus in 435/BRMS1 cells. Raman microspectroscopy showed weaker vibrational spectroscopic bands in 435/BRMS1 cells, implying decrease in concentration of cellular biochemical components in these cells. This was despite the similar spectral patterns observed between 435 and 435/BRMS1 cells. This work demonstrated the feasibility of applying AFM and Raman techniques for in situ measurements of the cellular biomechanics and biochemical components of breast carcinoma cells. It provides vital clues in understanding of the role of cellular biomechanics in cancer metastasis, and further the development of new techniques for early diagnosis of breast cancer.