Cytology by Infrared Micro-Spectroscopy: Automatic Distinction of Cell Types in Urinary Cytology

Analysis of urine using electronic tongue towards non-invasive cancer diagnosis

Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.

FTIR Spectroscopic Imaging Supports Urine Cytology for Classification of Low- and High-Grade Bladder Carcinoma

Simple Summary

Human urine cytological samples were investigated using Fourier transform infrared spectroscopic imaging in terms of recognition of bladder cancer. The clustering of IR spectra of whole cytological smears revealed very good spectral correlation with normal urothelial cell features. Next, the combination of spectral information derived from unsupervised hierarchical cluster analysis and partial least square discriminant analysis (PLS-DA) classified normal vs. low- and high-grade bladder urothelial carcinoma with sensitivity and specificity of 90–97%.

Abstract

Bladder urothelial carcinoma (BC) is a common, recurrent, life-threatening, and unpredictable disease which is difficult to diagnose. These features make it one of the costliest malignancies. Although many possible diagnostic methods are available, molecular heterogeneity and difficulties in cytological or histological examination induce an urgent need to improve diagnostic techniques. Herein, we applied Fourier transform infrared spectroscopy in imaging mode (FTIR) to investigate patients’ cytology samples assigned to normal (N), low-grade (LG) and high-grade (HG) BC. With unsupervised hierarchical cluster analysis (UHCA) and hematoxylin-eosin (HE) staining, we observed a correlation between N cell types and morphology. High-glycogen superficial (umbrella) and low-glycogen piriform urothelial cells, both with normal morphology, were observed. Based on the spectra derived from UHCA, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed, indicating a variation of protein content between the patient groups. Moreover, BC spectral cytology identified a low number of high-glycogen cells for which a shift of the carbohydrate/phosphate bands was also observed. Despite high cellular heterogeneity, PLS-DA was able to classify the spectra obtained. The voided urine FTIR cytology is one of the options that might be helpful in BC diagnosis, as high sensitivity and specificity up to 97% were determined.

Raman chemometric urinalysis (Rametrix) as a screen for bladder cancer

Bladder cancer (BCA) is relatively common and potentially recurrent/progressive disease. It is also costly to detect, treat, and control. Definitive diagnosis is made by examination of urine sediment, imaging, direct visualization (cystoscopy), and invasive biopsy of suspect bladder lesions. There are currently no widely-used BCA-specific biomarker urine screening tests for early BCA or for following patients during/after therapy. Urine metabolomic screening for biomarkers is costly and generally unavailable for clinical use. In response, we developed Raman spectroscopy-based chemometric urinalysis (Rametrix™) as a direct liquid urine screening method for detecting complex molecular signatures in urine associated with BCA and other genitourinary tract pathologies. In particular, the Rametrix^TM screen used principal components (PCs) of urine Raman spectra to build discriminant analysis models that indicate the presence/absence of disease. The number of PCs included was varied, and all models were cross-validated by leave-one-out analysis. In Study 1 reported here, we tested the Rametrix™ screen using urine specimens from 56 consented patients from a urology clinic. This proof-of-concept study contained 17 urine specimens with active BCA (BCA-positive), 32 urine specimens from patients with other genitourinary tract pathologies, seven specimens from healthy patients, and the urinalysis control Surine^TM. Using a model built with 22 PCs, BCA was detected with 80.4% accuracy, 82.4% sensitivity, 79.5% specificity, 63.6% positive predictive value (PPV), and 91.2% negative predictive value (NPV). Based on the number of PCs included, we found the Rametrix^TM screen could be fine-tuned for either high sensitivity or specificity. In other studies reported here, Rametrix^TM was also able to differentiate between urine specimens from patients with BCA and other genitourinary pathologies and those obtained from patients with end-stage kidney disease (ESKD). While larger studies are needed to improve Rametrix^TM models and demonstrate clinical relevance, this study demonstrates the ability of the Rametrix^TM screen to differentiate urine of BCA-positive patients. Molecular signature variances in the urine metabolome of BCA patients included changes in: phosphatidylinositol, nucleic acids, protein (particularly collagen), aromatic amino acids, and carotenoids.

Increased optical pathlength through aqueous media for the infrared microanalysis of live cells

The study of live cells using Fourier transform infrared spectroscopy (FTIR) and FTIR microspectroscopy (FT-IRMS) intrinsically yields more information about cell metabolism than comparable experiments using dried or chemically fixed samples. There are, however, a number of barriers to obtaining high-quality vibrational spectra of live cells, including correction for the significant contributions of water bands to the spectra, and the physical stresses placed upon cells by compression in short pathlength sample holders. In this study, we present a water correction method that is able to result in good-quality cell spectra from water layers of 10 and 12 μm and demonstrate that sufficient biological detail is retained to separate spectra of live cells based upon their exposure to different novel anti-cancer agents. The IR brilliance of a synchrotron radiation (SR) source overcomes the problem of the strong water absorption and provides cell spectra with good signal-to-noise ratio for further analysis. Supervised multivariate analysis (MVA) and investigation of average spectra have shown significant separation between control cells and cells treated with the DNA cross-linker PL63 on the basis of phosphate and DNA-related signatures. Meanwhile, the same control cells can be significantly distinguished from cells treated with the protein kinase inhibitor YA1 based on changes in the amide II region. Each of these separations can be linked directly to the known biochemical mode of action of each agent.

Automated cytological detection of Barrett's neoplasia with infrared spectroscopy

BACKGROUND

Development of a nonendoscopic test for Barrett's esophagus would revolutionize population screening and surveillance for patients with Barrett's esophagus. Swallowed cell collection devices have recently been developed to obtain cytology brushings from the esophagus: automated detection of neoplasia in such samples would enable large-scale screening and surveillance.

METHODS

Fourier transform infrared (FTIR) spectroscopy was used to develop an automated tool for detection of Barrett's esophagus and Barrett's neoplasia in esophageal cell samples. Cytology brushings were collected at endoscopy, cytospun onto slides and FTIR images were measured. An automated cell recognition program was developed to identify individual cells on the slide.

RESULTS

Cytology review and contemporaneous histology was used to inform a training dataset containing 141 cells from 17 patients. A classification model was constructed by principal component analysis fed linear discriminant analysis, then tested by leave-one-sample-out cross validation. With application of this training model to whole slide samples, a threshold voting system was used to classify samples according to their constituent cells. Across the entire dataset of 115 FTIR maps from 66 patients, whole samples were classified with sensitivity and specificity respectively as follows: normal squamous cells 79.0% and 81.1%, nondysplastic Barrett's esophagus cells 31.3% and 100%, and neoplastic Barrett's esophagus cells 83.3% and 62.7%.

CONCLUSIONS

Analysis of esophageal cell samples can be performed with FTIR spectroscopy with reasonable sensitivity for Barrett's neoplasia, but with poor specificity with the current technique.

Cancer screening via infrared spectral cytopathology (SCP): results for the upper respiratory and digestive tracts

Instrumental advances in infrared micro-spectroscopy have made possible the observation of individual human cells and even subcellular structures. The observed spectra represent a snapshot of the biochemical composition of a cell; this composition varies subtly but reproducibly with cellular effects such as progression through the cell cycle, cell maturation and differentiation, and disease. The aim of this summary is to provide a synopsis of the progress achieved in infrared spectral cytopathology (SCP) - the combination of infrared micro-spectroscopy and multivariate methods of analysis - for the detection of abnormalities in exfoliated human cells of the upper respiratory and digestive tract, namely the oral and nasopharyngeal cavities, and the esophagus.

Use of infrared microspectroscopy to elucidate a specific chemical signature associated with hypoxia levels found in glioblastoma

Detection of the chemical signature associated with hypoxia in single glioblastoma cells by synchrotron infrared microspectroscopy.

Infrared micro-spectroscopy for cyto-pathological classification of esophageal cells

We report results from a study utilizing infrared spectral cytopathology (SCP) to detect abnormalities in exfoliated esophageal cells. SCP has been developed over the past decade as an ancillary tool to classical cytopathology. In SCP, the biochemical composition of individual cells is probed by collecting infrared absorption spectra from each individual, unstained cell, and correlating the observed spectral patterns, and the variations therein, against classical diagnostic methods to obtain an objective, machine-based classification of cells. In the past, SCP has been applied to the analysis and classification of cells exfoliated from the cervix and the oral cavity. In these studies, it was established that SCP can distinguish normal and abnormal cell types. Furthermore, SCP can differentiate between truly normal cells, and cells with normal morphology from the vicinity of abnormalities. Thus, SCP may be a valuable tool for the screening of early stages of dysplasia and pre-cancer.

Comparison of transmission and transflectance mode FTIR imaging of biological tissue

FTIR microscopy is a powerful technique which has become popular due to its ability to provide complementary information during histopathological assessment of biomedical tissue samples. Recently however, questions have been raised on the suitability of the transflection mode of operation for clinical diagnosis due to the so called Electric Field Standing Wave (EFSW) effect. In this paper we compare chemical images measured in transmission and transflection from prostate tissue obtained from five different patients, and discuss the variability of the spectra acquired with each sampling modality. We find that spectra obtained in transflection undergo a non-linear distortion, i.e. non-linear variations in absorption band strength across the spectra, and that there are significant differences in spectra measured from the same area of tissue depending on the mode of operation. Principal Component Analysis (PCA) is used to highlight that poorer discrimination between benign and cancerous tissue is obtained in transflection mode. In addition we show that use of second derivatives, while qualitatively improves spectral discrimination, does not completely alleviate the underlying problem.

Vibrational spectroscopic methods for cytology and cellular research

The use of vibrational spectroscopy, FTIR and Raman, for cytology and cellular research has the potential to revolutionise the approach to cellular analysis. Vibrational spectroscopy is non-destructive, simple to operate and provides direct information. Importantly it does not require expensive exogenous labels that may affect the chemistry of the cell under analysis. In addition, the advent of spectroscopic microscopes provides the ability to image cells and acquire spectra with a subcellular resolution. This introductory review focuses on recent developments within this fast paced field and highlights potential for the future use of FTIR and Raman spectroscopy. We particularly focus on the development of live cell research and the new technologies and methodologies that have enabled this.

Using Fourier transform IR spectroscopy to analyze biological materials

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Quantification of DNA in simple eukaryotic cells using Fourier transform infrared spectroscopy

A technique capable of detecting and monitoring nucleic acid concentration offers potential in diagnosing cancer and further developing an understanding of the biochemistry of disease. The application of Fourier transform infrared (FTIR) spectroscopy has previously been hindered by the supposed non-Beer-Lambert absorption behavior of DNA in intact cells making elucidation of the DNA bands difficult. We use known composition DNA/hemoglobin standards to successfully estimate the DNA content in avian erythrocyte nuclei (44.2%) and intact erythrocytes (12.8%). Furthermore we demonstrate that the absorption of cellular DNA does follow the Beer-Lambert Law and highlights the role of conformation and hydration in FTIR spectroscopy of biological samples.

Technologic developments in the field of photonics for the detection of urinary bladder cancer

Bladder cancer is a common cause of morbidity and mortality worldwide in an aging population. Each year, thousands of people, mostly men, are diagnosed with this disease, but many of them present too late to receive optimal treatment. As with all cancers, early diagnosis of bladder cancer significantly improves the efficacy of therapy and increases survival and recurrence-free survival rates. Ongoing research has identified many limitations about the sensitivity of standard diagnostic procedures in detecting early-stage tumors and precancerous changes. The consequences of this are often tumor progression and increased tumor burden, leading to a decrease in patient quality of life and a vast increase in treatment costs. The necessity for improved early detection of bladder cancer has spurred on research into novel methods that use a wide range of biological and photonic phenomena. This review will broadly discuss standard detection methodologies and their major limitations before covering novel photonic techniques for early tumor detection and staging, assessing their diagnostic accuracy for flat and precancerous changes. We will do so in the context of both cystoscopic examination and the screening of voided urine and will also touch on the concept of using photonic technology as a surgical tool for tumor ablation.

Applications of Infrared and Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics: Present Status and Future Promises

This paper summarizes the progress achieved over the past fifteen years in applying vibrational (Raman and IR) spectroscopy to problems of medical diagnostics and cellular biology. During this time, a number of research groups have verified the enormous information content of vibrational spectra; in fact, genomic, proteomic, and metabolomic information can be deduced by decoding the observed vibrational spectra. This decoding process is aided enormously by the availability of high-power computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared microspectral data has rendered practical the collection of images based solely on spectral data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational biological and biomedical arenas.

Infrared spectroscopy and microscopy in cancer research and diagnosis

Since the middle of 20(th) century infrared (IR) spectroscopy coupled to microscopy (IR microspectroscopy) has been recognized as a non destructive, label free, highly sensitive and specific analytical method with many potential useful applications in different fields of biomedical research and in particular cancer research and diagnosis. Although many technological improvements have been made to facilitate biomedical applications of this powerful analytical technique, it has not yet properly come into the scientific background of many potential end users. Therefore, to achieve those fundamental objectives an interdisciplinary approach is needed with basic scientists, spectroscopists, biologists and clinicians who must effectively communicate and understand each other's requirements and challenges. In this review we aim at illustrating some principles of Fourier transform (FT) Infrared (IR) vibrational spectroscopy and microscopy (microFT-IR) as a useful method to interrogate molecules in specimen by mid-IR radiation. Penetrating into basics of molecular vibrations might help us to understand whether, when and how complementary information obtained by microFT-IR could become useful in our research and/or diagnostic activities. MicroFT-IR techniques allowing to acquire information about the molecular composition and structure of a sample within a micrometric scale in a matter of seconds will be illustrated as well as some limitations will be discussed. How biochemical, structural, and dynamical information about the systems can be obtained by bench top microFT-IR instrumentation will be also presented together with some methods to treat and interpret IR spectral data and applicative examples. The mid-IR absorbance spectrum is one of the most information-rich and concise way to represent the whole "… omics" of a cell and, as such, fits all the characteristics for the development of a clinically useful biomarker.

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.

Distinguishing cell types or populations based on the computational analysis of their infrared spectra

Infrared (IR) spectroscopy of intact cells results in a fingerprint of their biochemistry in the form of an IR spectrum; this has given rise to the new field of biospectroscopy. This protocol describes sample preparation (a tissue section or cytology specimen), the application of IR spectroscopy tools, and computational analysis. Experimental considerations include optimization of specimen preparation, objective acquisition of a sufficient number of spectra, linking of the derived spectra with tissue architecture or cell type, and computational analysis. The preparation of multiple specimens (up to 50) takes 8 h; the interrogation of a tissue section can take up to 6 h (∼100 spectra); and cytology analysis (n = 50, 10 spectra per specimen) takes 14 h. IR spectroscopy generates complex data sets and analyses are best when initially based on a multivariate approach (principal component analysis with or without linear discriminant analysis). This results in the identification of class clustering as well as class-specific chemical entities.

Cytopathology by optical methods: spectral cytopathology of the oral mucosa

Spectral cytopathology (SCP) is a novel approach for diagnostic differentiation of disease in individual exfoliated cells. SCP is carried out by collecting information on each cell's biochemical composition through an infrared micro-spectral measurement, followed by multivariate data analysis. Deviations from a cell's natural composition produce specific spectral patterns that are exclusive to the cause of the deviation or disease. These unique spectral patterns are reproducible and can be identified and used through multivariate statistical methods to detect cells compromised at the molecular level by dysplasia, neoplasia, or viral infection. In this proof of concept study, a benchmark for the sensitivity of SCP is established by classifying healthy oral squamous cells according to their anatomical origin in the oral cavity. Classification is achieved by spectrally detecting cells with unique protein expressions: for example, the squamous cells of the tongue are the only cell type in the oral cavity that have significant amounts of intracytoplasmic keratin, which allows them to be spectrally differentiated from other oral mucosa cells. Furthermore, thousands of cells from a number of clinical specimens were examined, among them were squamous cell carcinoma, malignancy-associated changes including reactive atypia, and infection by the herpes simplex virus. Owing to its sensitivity to molecular changes, SCP often can detect the onset of disease earlier than is currently possible by cytopathology visualization. As SCP is based on automated instrumentation and unsupervised software, it constitutes a diagnostic workup of medical samples devoid of bias and inconsistency. Therefore, SCP shows potential as a complementary tool in medical cytopathology.

Resonant Mie scattering (RMieS) correction of infrared spectra from highly scattering biological samples

Infrared spectra of single biological cells often exhibit the 'dispersion artefact' observed as a sharp decrease in intensity on the high wavenumber side of absorption bands, in particular the Amide I band at approximately 1655 cm(-1), causing a downward shift of the true peak position. The presence of this effect makes any biochemical interpretation of the spectra unreliable. Recent theory has shed light on the origins of the 'dispersion artefact' which has been attributed to resonant Mie scattering (RMieS). In this paper a preliminary algorithm for correcting RMieS is presented and evaluated using simulated data. Results show that the 'dispersion artefact' appears to be removed; however, the correction is not perfect. An iterative approach was subsequently implemented whereby the reference spectrum is improved after each iteration, resulting in a more accurate correction. Consequently the corrected spectra become increasingly more representative of the pure absorbance spectra. Using this correction method reliable peak positions can be obtained.

Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy

In this study we obtained Fourier transform infrared (FTIR) spectra of fixed prostate cell lines of differing types as well as the primary epithelial cells from benign prostatic hyperplasia (BPH). Results showed that by using multivariate chemometric analysis it was possible to discriminate and classify these cell lines, which gave rise to sensitivity and specificity values of >94% and >98%, respectively. Following on from these results the possible influences of different factors on the discrimination and classification of the prostate cell lines were examined. Firstly, the effect of using different growth media during cell culturing was investigated, with results indicating that this did not influence chemometric discrimination. Secondly, differences in the nucleus-to-cytoplasm (N/C) ratio were examined, and it was concluded that this factor was not the main reason for the discrimination and classification of the prostate cancer (CaP) cell lines. In conclusion, given the fact that neither growth media nor N/C ratio could totally explain the classification it is likely that actual biochemical differences between the cell lines is the major contributing factor.

Vibrational spectroscopy: a clinical tool for cancer diagnostics

Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.