Melanoma Diagnosis by Raman Spectroscopy and Neural Networks: Structure Alterations in Proteins and Lipids in Intact Cancer Tissue

Raman Spectroscopy: Incorporating the Chemical Dimension into Dermatological Diagnosis

Raman spectroscopy provides chemical analysis of tissue in vivo. By measuring the inelastic interactions of light with matter, Raman spectroscopy can determine the chemical composition of a sample. Diseases that are visually difficult to visually distinguish can be delineated based on differences in chemical composition of the affected tissue. Raman spectroscopy has successfully found spectroscopic signatures for skin cancers and differentiated those of benign skin growths. With current and on-going advances in optics and computing, inexpensive and effective Raman systems may soon be available for clinical use. Raman spectroscopy provides direct analyses of skin lesions, thereby improving both disease diagnosis and management.

Raman spectral dynamics of single cells in the early stages of growth factor stimulation

Cell fates change dynamically in response to various extracellular signals, including growth factors that stimulate differentiation and proliferation. The processes underlying cell-fate decisions are complex and often include large cell-to-cell variations, even within a clonal population in the same environment. To understand the origins of these cell-to-cell variations, we must detect the internal dynamics of single cells that reflect their changing chemical milieu. In this study, we used the Raman spectra of single cells to trace their internal dynamics during the early stages of growth factor stimulation. This method allows nondestructive and inclusive time-series analyses of chemical compositions of the same single cells. Applying a Gaussian mixture model to the major principal components of the single-cell Raman spectra, we detected the dynamics of the chemical states in MCF-7 cancer-derived cells in the absence and presence of differentiation and proliferation factors. The dynamics displayed characteristic variations according to the functions of the growth factors. In the differentiation pathway, the chemical composition changed directionally between multiple states, including both reversible and irreversible state transitions. In contrast, in the proliferation pathway, the chemical composition was homogenized into a single state. The differentiation factor also stimulated fluctuations in the chemical composition, whereas the proliferation factor did not.

Dispersion-based stimulated Raman scattering spectroscopy, holography, and optical coherence tomography

Stimulated Raman scattering (SRS) enables fast, high resolution imaging of chemical constituents important to biological structures and functional processes, both in a label-free manner and using exogenous biomarkers. While this technology has shown remarkable potential, it is currently limited to point scanning and can only probe a few Raman bands at a time (most often, only one). In this work we take a fundamentally different approach to detecting the small nonlinear signals based on dispersion effects that accompany the loss/gain processes in SRS. In this proof of concept, we demonstrate that the dispersive measurements are more robust to noise compared to amplitude-based measurements, which then permit spectral or spatial multiplexing (potentially both, simultaneously). Finally, we illustrate how this method may enable different strategies for biochemical imaging using phase microscopy and optical coherence tomography.

Single exosome study reveals subpopulations distributed among cell lines with variability related to membrane content

Current analysis of exosomes focuses primarily on bulk analysis, where exosome-to-exosome variability cannot be assessed. In this study, we used Raman spectroscopy to study the chemical composition of single exosomes. We measured spectra of individual exosomes from 8 cell lines. Cell-line-averaged spectra varied considerably, reflecting the variation in total exosomal protein, lipid, genetic, and cytosolic content. Unexpectedly, single exosomes isolated from the same cell type also exhibited high spectral variability. Subsequent spectral analysis revealed clustering of single exosomes into 4 distinct groups that were not cell-line specific. Each group contained exosomes from multiple cell lines, and most cell lines had exosomes in multiple groups. The differences between these groups are related to chemical differences primarily due to differing membrane composition. Through a principal components analysis, we identified that the major sources of spectral variation among the exosomes were in cholesterol content, relative expression of phospholipids to cholesterol, and surface protein expression. For example, exosomes derived from cancerous versus non-cancerous cell lines can be largely separated based on their relative expression of cholesterol and phospholipids. We are the first to indicate that exosome subpopulations are shared among cell types, suggesting distributed exosome functionality. The origins of these differences are likely related to the specific role of extracellular vesicle subpopulations in both normal cell function and carcinogenesis, and they may provide diagnostic potential at the single exosome level.

Raman Spectroscopy of Experimental Oral Carcinogenesis: Study on Sequential Cancer Progression in Hamster Buccal Pouch Model

Oral cancers suffer from poor 5-year survival rates, owing to late detection of the disease. Current diagnostic/screening tools need to be upgraded in view of disadvantages like invasiveness, tedious sample preparation, long output times, and interobserver variances. Raman spectroscopy has been shown to identify many disease conditions, including oral cancers, from healthy conditions. Further studies in exploring sequential changes in oral carcinogenesis are warranted. In this Raman spectroscopy study, sequential progression in experimental oral carcinogenesis in Hamster buccal pouch model was investigated using 3 approaches-ex vivo, in vivo sequential, and in vivo follow-up. In all these studies, spectral changes show lipid dominance in early stages while later stages and tumors showed increased protein to lipid ratio and nucleic acids. On similar lines, early weeks of 7,12-dimethylbenz(a)anthracene-treated and control groups showed higher overlap and low classification. The classification efficiency increased progressively, reached a plateau phase and subsequently increased up to 100% by 14 weeks. The misclassifications between treated and control spectra suggested some changes in controls as well, which was confirmed by a careful reexamination of histopathological slides. These findings suggests Raman spectroscopy may be able to identify microheterogeneity, which may often go unnoticed in conventional biochemistry wherein tissue extracts are employed, as well as in histopathology. In vivo findings, quite comparable to gold-standard supported ex vivo findings, give further proof of Raman spectroscopy being a promising label-free, noninvasive diagnostic adjunct for future clinical applications.

Spontaneous and coherent anti-Stokes Raman spectroscopy of human gastrocnemius muscle biopsies in CH-stretching region for discrimination of peripheral artery disease

Peripheral Artery Disease (PAD) is a common manifestation of atherosclerosis, characterized by lower leg ischemia and myopathy in association with leg dysfunction. In the present study, Spontaneous and coherent anti-Stokes Raman scattering (CARS) spectroscopic techniques in CH-stretching spectral region were evaluated for discriminating healthy and diseased tissues of human gastrocnemius biopsies of control and PAD patients. Since Raman signatures of the tissues in the fingerprint region are highly complex and CH containing moieties are dense, CH-stretching limited spectral range was used to classify the diseased tissues. A total of 181 Raman spectra from 9 patients and 122 CARS spectra from 12 patients were acquired. Due to the high dimensionality of the data in Raman and CARS measurements, principal component analysis (PCA) was first performed to reduce the dimensionality of the data (6 and 9 principal scores for Raman and CARS, respectively) in the CH-stretching region, followed by a discriminant function analysis (DFA) to classify the samples into different categories based on disease severity. The CH2 and CH3 vibrational signatures were observed in the Raman and CARS spectroscopy. Raman and CARS data in conjunction with PCA-DFA analysis were capable of differentiating healthy and PAD gastrocnemius with an accuracy of 85.6% and 78.7%, respectively.

Applications of Raman spectroscopy in skin research--From skin physiology and diagnosis up to risk assessment and dermal drug delivery

In the field of skin research, confocal Raman microscopy is an upcoming analytical technique. Substantial technical progress in design and performance of the individual setup components like detectors and lasers as well as the combination with confocal microscopy enables chemically selective and non-destructive sample analysis with high spatial resolution in three dimensions. Due to these advantages, the technique bears tremendous potential for diverse skin applications ranging from the analysis of physiological component distribution in skin tissue and the diagnosis of pathological states up to biopharmaceutical investigations such as drug penetration kinetics within the different tissue layers. This review provides a comprehensive introduction about the basic principles of Raman microscopy highlighting the advantages and considering the limitations of the technique for skin applications. Subsequently, an overview about skin research studies applying Raman spectroscopy is given comprising various in vitro as well as in vivo implementations. Furthermore, the future perspective and potential of Raman microscopy in the field of skin research are discussed.

In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy

Raman spectroscopy has proved its capability as an objective, non-invasive tool for the detection of various melanoma and non-melanoma skin cancers (NMSC) in a number of studies. Most publications are based on a Raman microspectroscopic ex vivo approach. In this in vivo clinical evaluation, we apply Raman spectroscopy using a fibre-coupled probe that allows access to a multitude of affected body sites. The probe design is optimized for epithelial sensitivity, whereby a large part of the detected signal originates from within the epidermal layer's depth down to the basal membrane where early stages of skin cancer develop. Data analysis was performed on measurements of 104 subjects scheduled for excision of lesions suspected of being malignant melanoma (MM) (n = 36), basal cell carcinoma (BCC) (n = 39) and squamous cell carcinoma (SCC) (n = 29). NMSC were discriminated from normal skin with a balanced accuracy of 73% (BCC) and 85% (SCC) using partial least squares discriminant analysis (PLS-DA). Discriminating MM and pigmented nevi (PN) resulted in a balanced accuracy of 91%. These results lie within the range of comparable in vivo studies and the accuracies achieved by trained dermatologists using dermoscopy. Discrimination proved to be unsuccessful between cancerous lesions and suspicious lesions that had been histopathologically verified as benign by dermoscopy.

Advances in the in Vivo Raman Spectroscopy of Malignant Skin Tumors Using Portable Instrumentation

Raman spectroscopy has emerged as a promising tool for real-time clinical diagnosis of malignant skin tumors offering a number of potential advantages: it is non-intrusive, it requires no sample preparation, and it features high chemical specificity with minimal water interference. However, in vivo tissue evaluation and accurate histopathological classification remain a challenging task for the successful transition from laboratory prototypes to clinical devices. In the literature, there are numerous reports on the applications of Raman spectroscopy to biomedical research and cancer diagnostics. Nevertheless, cases where real-time, portable instrumentations have been employed for the in vivo evaluation of skin lesions are scarce, despite their advantages in use as medical devices in the clinical setting. This paper reviews the advances in real-time Raman spectroscopy for the in vivo characterization of common skin lesions. The translational momentum of Raman spectroscopy towards the clinical practice is revealed by (i) assembling the technical specifications of portable systems and (ii) analyzing the spectral characteristics of in vivo measurements.

Current concepts and future of noninvasive procedures for diagnosing oral squamous cell carcinoma--a systematic review

Background

Oral squamous cell carcinoma (OSCC) has a remarkably high incidence worldwide, and a fairly serious prognosis, encouraging further research into advanced technologies for noninvasive methods of making early diagnoses, ideally in primary care settings.

Objectives

Our purpose was to examine the validity of using advanced noninvasive technologies in diagnosis of OSCC by identifying and evaluating relevant published reports.

Data source

MEDLINE, EMBASE, and CINAHL were searched to identify clinical trials and other information published between 1990 and 10 June 2014; the searches of MEDLINE and EMBASE were updated to November 2014. Study selection: Studies of noninvasive methods of diagnosing OSCC, including oral brush biopsy, optical biopsy, saliva-based oral cancer diagnosis, and others were included.

Data extraction

Data were abstracted and evaluated in duplicate for possible relevance on two occasions at an interval of 2 months before being included or excluded.

Data synthesis

This study identified 163 studies of noninvasive methods for diagnosing OSCC that met the inclusion criteria. These included six studies of oral brush biopsy, 42 of saliva-based oral diagnosis, and 115 of optical biopsy. Sixty nine of these studies were assessed by the modified version of the QUADAS instrument. Saliva-based oral cancer diagnosis and optical biopsy were found to be promising noninvasive methods for diagnosing OSCC.

Limitation

The strength of evidence was rated low for accuracy outcomes because the studies did not report important details required to assess the risk for bias.

Conclusions

It is clear that screening for and early detection of cancer and pre-cancerous lesions have the potential to reduce the morbidity and mortality of this disease. Advances in technologies for saliva-based oral diagnosis and optical biopsy are promising pathways for the future development of more effective noninvasive methods for diagnosing OSCC that are easy to perform clinically in primary care settings.

Biochemical changes of the endothelium in the murine model of NO-deficient hypertension

Alterations in the α-helix and β-sheet content and the lipid-to-protein ratio are the most striking features of hypertension development in the vascular endothelium.

Perturbation factors in the clinical handling of a fiber-coupled Raman probe for cutaneous in vivo diagnostic Raman spectroscopy

The application of fiber-coupled Raman probes for the discrimination of cancerous and normal skin has the advantage of a non-invasive in vivo application, easy clinical handling, and access to the majority of body sites, which would otherwise be limited by stationary Raman microscopes. Nevertheless, including optical fibers and miniaturizing optical components, as well as measuring in vivo, involves the sensibility to external perturbation factors that could introduce artifacts to the acquired Raman spectra and thereby potentially reduce classification performance. In this study, typical perturbation factors of Raman measurements with a Raman fiber probe, optimized for clinical in vivo discrimination of skin cancer, were investigated experimentally. Measurements were performed under standardized conditions in clinical settings in vivo on human skin, as well as ex vivo on porcine ears. Raman spectra were analyzed in the fingerprint region between 1150 and 1730 cm(-1) using principal component analysis. The largest artifacts in the Raman spectra were found in measurements performed under the influence of strong ambient light conditions as well as after miscellaneous pre-treatments to the skin, such as use of a permanent marker or a sunscreen. Minor influences were also found in measurements using H2O immersion and when varying the probe contact force. The effect of reasonable variation of the fiber-bending radius was found to be of negligible impact. The influence of measurements on hairy or sun-exposed body sites, as well as inter-subject variation, was also investigated. The presented results may serve as a guide to avoid negative effects during the process of data acquisition and so avoid misclassification in tumor discrimination.

Design and characterization of a novel multimodal fiber-optic probe and spectroscopy system for skin cancer applications

The design and characterization of an instrument combining Raman, fluorescence, and reflectance spectroscopic modalities is presented. Instrument development has targeted skin cancer applications as a novel fiber-optic probe has been specially designed to interrogate cutaneous lesions. The instrument is modular and both its software and hardware components are described in depth. Characterization of the fiber-optic probe is also presented, which details the probe's ability to measure diagnostically important parameters such as intrinsic fluorescence and absorption and reduced scattering coefficients along with critical performance metrics such as high Raman signal-to-noise ratios at clinically practical exposure times. Validation results using liquid phantoms show that the probe and system can extract absorption and scattering coefficients with less than 10% error. As the goal is to use the instrument for the clinical early detection of skin cancer, preliminary clinical data are also presented, which indicates our system's ability to measure physiological quantities such as relative collagen and nicotinamide adenine dinucleotide concentration, oxygen saturation, blood volume fraction, and mean vessel diameter.

Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening

Surface-enhanced Raman scattering (SERS) spectra of serum proteins purified from human serum samples were employed to detect colorectal cancer. Acetic acid as a new aggregating agent was introduced to increase the magnitude of the SERS enhancement. High-quality SERS spectra of serum proteins were acquired from 103 cancer patients and 103 healthy volunteers. Tentative assignments of SERS bands reflect that some specific biomolecular contents and protein secondary structures change with colorectal cancer progression. Principal component analysis combined with linear discriminant analysis was used to assess the capability of this approach for identifying colorectal cancer, yielding diagnostic accuracies of 100% (sensitivity: 100%; specificity: 100%) based on albumin SERS spectroscopy and 99.5% (sensitivity: 100%; specificity: 99%) based on globulin SERS spectroscopy, respectively. A partial least squares (PLS) approach was introduced to develop diagnostic models. An albumin PLS model successfully predicted the unidentified subjects with a diagnostic accuracy of 93.5% (sensitivity: 95.6%; specificity: 91.3%) and the globulin PLS model gave a diagnostic accuracy of 93.5% (sensitivity: 91.3%; specificity: 95.6%). These results suggest that serum protein SERS spectroscopy can be a sensitive and clinically powerful means for colorectal cancer detection.

High-Speed Coherent Raman Fingerprint Imaging of Biological Tissues

An imaging platform based on broadband coherent anti-Stokes Raman scattering (BCARS) has been developed which provides an advantageous combination of speed, sensitivity and spectral breadth. The system utilizes a configuration of laser sources that probes the entire biologically-relevant Raman window (500 cm^-1 to 3500 cm^-1) with high resolution (< 10 cm^-1). It strongly and efficiently stimulates Raman transitions within the typically weak "fingerprint" region using intrapulse 3-colour excitation, and utilizes the nonresonant background (NRB) to heterodyne amplify weak Raman signals. We demonstrate high-speed chemical imaging in two- and three-dimensional views of healthy murine liver and pancreas tissues and interfaces between xenograft brain tumours and the surrounding healthy brain matter.

Combined fluorescence-Raman spectroscopic setup for the diagnosis of melanocytic lesions

Two optical fibre-based probes for spectroscopic measurements on human tissues were designed and developed. The two probes combine fluorescence and Raman spectroscopy in a multimodal approach. The fluorescence excitation was provided by two laser diodes emitting in the UV (378 nm) and in the visible (445 nm) range, while a third source in the NIR (785 nm) was used for Raman. The device was tested on freshly excised human skin biopsies clinically diagnosed as malignant melanoma, melanocytic nevus, or healthy skin. Discrimination of lesions based on their fluorescence and Raman spectra showed good correlation with the subsequent histological examination.

Clinical study of noninvasive in vivo melanoma and nonmelanoma skin cancers using multimodal spectral diagnosis

The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.

Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study

Aim

To elucidate whether Raman spectroscopy aided by extensive spectral database and neural network analysis can be a fast and confident biomarking tool for the diagnosis of various types of cancer.

Methods

Study included 27 patients with 11 different malignant tumors. Using Raman microscopy (RM) a total of 540 Raman spectra were recorded from histology specimens of both tumors and surrounding healthy tissues. Spectra were analyzed using the principal component analysis (PCA) and results, along with histopathology data, were used to train the neural network (NN) learning algorithm. Independent sets of spectra were used to test the accuracy of PCA/NN tissue classification.

Results

The confident tumor identification for the purpose of medical diagnosis has to be performed by taking into account the whole spectral shape, and not only particular spectral bands. The use of PCA/NN analysis showed overall sensitivity of 96% with 4% false negative tumor classification. The specificity of distinguishing tumor types was 80%. These results are comparable to previously published data where tumors of only one tissue type were examined and can be regarded satisfactorily for a relatively small database of Raman spectra used here.

Conclusion

In vitro RM combined with PCA/NN is an almost fully automated method for histopathology at the level of macromolecules. Supported by an extensive tumor spectra database, it could become a customary histological analysis tool for fast and reliable diagnosis of different types of cancer in clinical settings.

Optical techniques for the noninvasive diagnosis of skin cancer

PURPOSE

The aim of this paper is to provide an overview of the most investigated optical diagnostic techniques: optical coherence tomography, fluorescence spectrometry, reflectance spectrometry, Raman spectroscopy, and confocal microscopy.

METHODS

A search of three databases was conducted using specific keywords and explicit inclusion and exclusion criteria for the analysis of the performances of these techniques in the pre- and postoperative diagnosis of skin cancers.

RESULTS

Optical coherence tomography has shown promising results in the assessment of deep margins of skin tumors and inflammatory skin diseases, but differentiating premalignant from malignant lesions proved to be less effective. Fluorescence spectroscopy proved to be effective in revealing the biochemical composition of tissue; early detection of malignant melanoma was reliable only with stepwise two-photon excitation of melanin, while tumoral margin assessment and differential diagnosis between malignant and non-malignant lesions showed some conflicting results. Characterization of the structural properties of tissue can be made using diffuse reflectance spectrometry, and the values of the specificity and sensitivity of this method are ranging between 72-92 % and 64-92 %, respectively. Raman spectroscopy proved to have better results both in carcinoma and melanoma diagnosis with sensitivities and specificities above 90 % and high above 50 %, respectively. Confocal microscopy is the closest technique to pathological examination and has gained the most clinical acceptance, despite the need for a standardization of the interpretation algorithm.

CONCLUSIONS

In conclusion, these optical techniques proved to be effective in the diagnosis of skin cancer, but further studies are needed in finding the appropriate method or combination of methods that can have wide clinical applications.

Detection and identification of cancerous murine fibroblasts, transformed by murine sarcoma virus in culture, using Raman spectroscopy and advanced statistical methods

BACKGROUND

Cancer is one of the leading worldwide causes of death. It may be induced by a variety of factors, including carcinogens, radiation, genetic factors, or DNA and RNA viruses. The early detection of cancer is critical for its successful therapy, which can result in complete recovery from some types of cancer.

METHODS

Raman spectroscopy has been widely used in medicine and biology. It is a noninvasive, nondestructive, and water-insensitive technique that can detect changes in cells and tissues that are caused by different disorders, such as cancer. In this study, Raman spectroscopy was used for the identification and characterization of murine fibroblast cell lines (NIH/3T3) and malignant fibroblast cells transformed by murine sarcoma virus (NIH-MuSV) cells.

RESULTS

Using principal component analysis and LDA it was possible to differentiate between the NIH/3T3 and NIH-MuSV cells with an 80-85% success rate based on their Raman shift spectra.

CONCLUSIONS

The best results for differentiation were achieved from spectra that were obtained from the rich membrane sites.

GENERAL SIGNIFICANCE

Because of its homogeneity and complete control of most factors affecting its growth, cell culture is a preferred model for the detection and identification of specific biomarkers related to cancer transformation or other cellular modifications.

New diagnostics for melanoma detection: from artificial intelligence to RNA microarrays

Early detection of melanoma remains crucial to ensuring a favorable prognosis. Dermoscopy and total body photography are well-established noninvasive aids that increase the diagnostic accuracy of dermatologists in their daily routine, beyond that of a naked-eye examination. New noninvasive diagnostic techniques, such as reflectance confocal microscopy, multispectral digital imaging and RNA microarrays, are currently being investigated to determine their utility for melanoma detection. This review presents emerging technologies for noninvasive melanoma diagnosis, and discusses their advantages and limitations.

Emerging technologies for the detection of melanoma: achieving better outcomes

Every year around 2.5–3 million skin lesions are biopsied in the US, and a fraction of these – between 50,000 and 100,000 – are diagnosed as melanoma. Diagnostic instruments that allow early detection of melanoma are the key to improving survival rates and reducing the number of unnecessary biopsies, the associated morbidity, and the costs of care. Advances in technology over the past 2 decades have enabled the development of new, sophisticated test methods, which are currently undergoing laboratory and small-scale clinical testing. This review highlights and compares some of the emerging technologies that hold the promise of melanoma diagnosis at an early stage of the disease. The needs for detection at different levels (patient, primary care, specialized care) are discussed, and three broad classes of instruments are identified that are capable of satisfying these needs. Technical and clinical requirements on the diagnostic instruments are introduced to aid the comparison and evaluation of new technologies. White- and polarized-light imaging, spatial and spectroscopic multispectral methods, quantitative thermographic imaging, confocal microscopy, Optical Coherence Tomography (OCT), and Terahertz (THZ) imaging methods are highlighted in light of the criteria identified in the review. Based on the properties, possibilities, and limitations of individual methods, those best suited for a particular setting are identified. Challenges faced in development and wide-scale application of novel technologies are addressed.

Artificial neural networks trained to detect viral and phage structural proteins

Phages play critical roles in the survival and pathogenicity of their hosts, via lysogenic conversion factors, and in nutrient redistribution, via cell lysis. Analyses of phage- and viral-encoded genes in environmental samples provide insights into the physiological impact of viruses on microbial communities and human health. However, phage ORFs are extremely diverse of which over 70% of them are dissimilar to any genes with annotated functions in GenBank. Better identification of viruses would also aid in better detection and diagnosis of disease, in vaccine development, and generally in better understanding the physiological potential of any environment. In contrast to enzymes, viral structural protein function can be much more challenging to detect from sequence data because of low sequence conservation, few known conserved catalytic sites or sequence domains, and relatively limited experimental data. We have designed a method of predicting phage structural protein sequences that uses Artificial Neural Networks (ANNs). First, we trained ANNs to classify viral structural proteins using amino acid frequency; these correctly classify a large fraction of test cases with a high degree of specificity and sensitivity. Subsequently, we added estimates of protein isoelectric points as a feature to ANNs that classify specialized families of proteins, namely major capsid and tail proteins. As expected, these more specialized ANNs are more accurate than the structural ANNs. To experimentally validate the ANN predictions, several ORFs with no significant similarities to known sequences that are ANN-predicted structural proteins were examined by transmission electron microscopy. Some of these self-assembled into structures strongly resembling virion structures. Thus, our ANNs are new tools for identifying phage and potential prophage structural proteins that are difficult or impossible to detect by other bioinformatic analysis. The networks will be valuable when sequence is available but in vitro propagation of the phage may not be practical or possible.

Bacteriophages are extremely abundant and diverse biological entities. All phage particles are comprised of nucleic acids and structural proteins, with few other packaged proteins. Despite their simplicity and abundance, more than 70% of phage sequences in the viral Reference Sequence database encode proteins with unknown function based on FASTA annotations. As a result, the use of sequence similarity is often insufficient for detecting virus structural proteins among unknown viral sequences. Viral structural protein function is challenging to detect from sequence data because structural proteins possess few known conserved catalytic motifs and sequence domains. To address these issues we investigated the use of Artificial Neural Networks as an alternative means of predicting function. Here, we trained thousands of networks using the amino acid frequency of structural protein sequences and identified the optimal architectures with the highest accuracies. Some hypothetical protein sequences detected by our networks were expressed and visualized by TEM, and produced images that strongly resemble virion structures. Our results support the utility of our neural networks in predicting the functions of unknown viral sequences.

Optical spectroscopy: current advances and future applications in cancer diagnostics and therapy

Optical spectroscopy (OS) is a tissue-sensing technique that could enhance cancer diagnosis and treatment in the near future. With OS, tissue is illuminated with a selected light spectrum. Different tissue types can be distinguished from each other based on specific changes in the reflected light spectrum that are a result of differences on a molecular level between compared tissues. Therefore, OS has the potential to become an important optical tool for cancer diagnosis and treatment monitoring. In recent years, significant progress has been made in the discriminating abilities of OS techniques between normal and cancer tissues of multiple human tissue types. This article provides an overview of the advances made with diffuse reflectance, fluorescence and Raman spectroscopy techniques in the field of clinical oncology, and focuses on the different clinical applications that OS could enhance.

Discriminating model for diagnosis of basal cell carcinoma and melanoma in vitro based on the Raman spectra of selected biochemicals

Raman spectroscopy has been employed to identify differences in the biochemical constitution of malignant [basal cell carcinoma (BCC) and melanoma (MEL)] cells compared to normal skin tissues, with the goal of skin cancer diagnosis. We collected Raman spectra from compounds such as proteins, lipids, and nucleic acids, which are expected to be represented in human skin spectra, and developed a linear least-squares fitting model to estimate the contributions of these compounds to the tissue spectra. We used a set of 145 spectra from biopsy fragments of normal (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues, collected using a near-infrared Raman spectrometer (830 nm, 50 to 200 mW, and 20 s exposure time) coupled to a Raman probe. We applied the best-fitting model to the spectra of biochemicals and tissues, hypothesizing that the relative spectral contribution of each compound to the tissue Raman spectrum changes according to the disease. We verified that actin, collagen, elastin, and triolein were the most important biochemicals representing the spectral features of skin tissues. A classification model applied to the relative contribution of collagen III, elastin, and melanin using Euclidean distance as a discriminator could differentiate normal from BCC and MEL.

Discrimination of basal cell carcinoma and melanoma from normal skin biopsies in vitro through Raman spectroscopy and principal component analysis

OBJECTIVE

Raman spectroscopy has been employed to discriminate between malignant (basal cell carcinoma [BCC] and melanoma [MEL]) and normal (N) skin tissues in vitro, aimed at developing a method for cancer diagnosis.

BACKGROUND DATA

Raman spectroscopy is an analytical tool that could be used to diagnose skin cancer rapidly and noninvasively.

METHODS

Skin biopsy fragments of ≈ 2 mm(2) from excisional surgeries were scanned through a Raman spectrometer (830 nm excitation wavelength, 50 to 200 mW of power, and 20 sec exposure time) coupled to a fiber optic Raman probe. Principal component analysis (PCA) and Euclidean distance were employed to develop a discrimination model to classify samples according to histopathology. In this model, we used a set of 145 spectra from N (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues.

RESULTS

We demonstrated that principal components (PCs) 1 to 4 accounted for 95.4% of all spectral variation. These PCs have been spectrally correlated to the biochemicals present in tissues, such as proteins, lipids, and melanin. The scores of PC2 and PC3 revealed statistically significant differences among N, BCC, and MEL (ANOVA, p<0.05) and were used in the discrimination model. A total of 28 out of 30 spectra were correctly diagnosed as N, 93 out of 96 as BCC, and 13 out of 19 as MEL, with an overall accuracy of 92.4%.

CONCLUSIONS

This discrimination model based on PCA and Euclidean distance could differentiate N from malignant (BCC and MEL) with high sensitivity and specificity.

In vivo diagnosis of melanoma and nonmelanoma skin cancer using oblique incidence diffuse reflectance spectrometry

Early detection and treatment of skin cancer can significantly improve patient outcome. However, present standards for diagnosis require biopsy and histopathologic examinations that are relatively invasive, expensive, and difficult for patients with many early-stage lesions. Here, we show an oblique incidence diffuse reflectance spectroscopic (OIDRS) system that can be used for rapid skin cancer detection in vivo. This system was tested under clinical conditions by obtaining spectra from pigmented and nonpigmented skin lesions, including melanomas, differently staged dysplastic nevi, and common nevi that were validated by standard pathohistologic criteria. For diagnosis of pigmented melanoma, the data obtained achieved 90% sensitivity and specificity for a blinded test set. In a second analysis, we showed that this spectroscopy system can also differentiate nonpigmented basal cell or squamous cell carcinomas from noncancerous skin abnormalities, such as actinic keratoses and seborrheic keratoses, achieving 92% sensitivity and specificity. Taken together, our findings establish how OIDRS can be used to more rapidly and easily diagnose skin cancer in an accurate and automated manner in the clinic.

Real-time Raman spectroscopy for in vivo skin cancer diagnosis

Raman spectroscopy is a noninvasive optical technique capable of measuring vibrational modes of biomolecules within viable tissues. In this study, we evaluated the application of an integrated real-time system of Raman spectroscopy for in vivo skin cancer diagnosis. Benign and malignant skin lesions (n = 518) from 453 patients were measured within 1 second each, including melanomas, basal cell carcinomas, squamous cell carcinomas, actinic keratoses, atypical nevi, melanocytic nevi, blue nevi, and seborrheic keratoses. Lesion classification was made using a principal component with general discriminant analysis and partial least-squares in three distinct discrimination tasks: skin cancers and precancers from benign skin lesions [receiver operating characteristic (ROC) = 0.879]; melanomas from nonmelanoma pigmented lesions (ROC = 0.823); and melanomas from seborrheic keratoses (ROC = 0.898). For sensitivities between 95% and 99%, the specificities ranged between 15% and 54%. Our findings establish that real-time Raman spectroscopy can be used to distinguish malignant from benign skin lesions with good diagnostic accuracy comparable with clinical examination and other optical-based methods.

Optical diagnosis of laryngeal cancer using high wavenumber Raman spectroscopy

We report the implementation of the transnasal image-guided high wavenumber (HW) Raman spectroscopy to differentiate tumor from normal laryngeal tissue at endoscopy. A rapid-acquisition Raman spectroscopy system coupled with a miniaturized fiber-optic Raman probe was utilized to realize real-time HW Raman (2800-3020 cm(-1)) measurements in the larynx. A total of 94 HW Raman spectra (22 normal sites, 72 tumor sites) were acquired from 39 patients who underwent laryngoscopic screening. Significant differences in Raman intensities of prominent Raman bands at 2845, 2880 and 2920 cm(-1) (CH(2) stretching of lipids), and 2940 cm(-1) (CH(3) stretching of proteins) were observed between normal and cancer laryngeal tissue. The diagnostic algorithms based on principal components analysis (PCA) and linear discriminant analysis (LDA) together with the leave-one subject-out, cross-validation method on HW Raman spectra yielded a diagnostic sensitivity of 90.3% (65/72) and specificity of 90.9% (20/22) for laryngeal cancer identification. This study demonstrates that HW Raman spectroscopy has the potential for the noninvasive, real-time diagnosis and detection of laryngeal cancer at the molecular level.

Elastic scattering spectroscopy in assessing skin lesions: an "in vivo" study

INTRODUCTION

Elastic scattering spectroscopy (ESS) has been shown to be accurate in the identification of abnormalities of soft tissue. These include ischemia and inflammation, pre-cancer and cancer. The aim of this study was to compare findings of ESS with gold standard histopathology in patients with various skin lesions.

MATERIALS AND METHODS

Seventy-three patients with clinically suspicious facial skin lesions were included. Those lesions with the surrounding innocuous skin were interrogated by ESS, biopsies were taken and examined histopathologically; the results were then compared.

RESULTS

The preliminary analysis showed obvious spectral differences between normal and pathological skin. Spectral differences were identified when comparing benign skin conditions to malignant ones. Spectral differences were identified between basal cell carcinomas and other skin lesions.

CONCLUSIONS

This preliminary study shows that ESS can distinguish between normal, benign and malignant skin conditions.

State of the art of diagnostic technology for early-stage melanoma

In the past few decades, rapid improvements in noninvasive optical technologies have revolutionized the diagnosis of early-stage melanoma. Current knowledge and limitations of these tools will be reviewed in this article. Dermoscopy has been recognized as the 'gold standard' in the screening phase. Digital dermoscopy monitoring and total-body photography are used to identify so-called 'featureless' melanoma only on the criteria of change over time. Automated instruments, as well as optical and nonmorphological methods, are still under development, and offer many opportunities to improve the speed and accuracy of the diagnosis of melanoma and/or to reduce the need for expertise. Despite a penetration depth limited to the upper dermis, the quasi-histological imaging achieved by in vivo reflectance confocal microscopy has been demonstrated to significantly aid diagnostic accuracy for selected melanocytic lesions. Future perspectives on diagnostic instrumentation will also be explored.

Differential diagnosis in primary and metastatic cutaneous melanoma by FT-Raman spectroscopy

PURPOSE

To qualify the FT-Raman spectral data of primary and metastatic cutaneous melanoma in order to obtain a differential diagnosis.

METHODS

Ten normal human skin samples without any clinical or histopathological alterations, ten cutaneous melanoma fragments, and nine lymph node metastasis samples were used; 105, 140 and 126 spectra were obtained respectively. Each sample was divided into 2 or 3 fragments of approximately 2 mm³ and positioned in the Raman spectrometer sample holder in order to obtain the spectra; a monochrome laser light Nd:YAG at 1064 nm was used to excite the inelastic effect.

RESULTS

To differentiate the three histopathological groups according to their characteristics extracted from the spectra, data discriminative analysis was undertaken. Phenylalanine, DNA, and Amide-I spectral variables stood out in the differentiation of the three groups. The percentages of correctly classified groups based on Phenylalanine, DNA, and Amide-I spectral features was 93.1%.

CONCLUSION

FT-Raman spectroscopy is capable of differentiating melanoma from its metastasis, as well as from normal skin.

FT-Raman spectroscopy for the differentiation between cutaneous melanoma and pigmented nevus

Cutaneous melanoma is the most aggressive type of skin cancer and Ft-Raman spectroscopy has been studied as a potential method that could be a real alternative for early diagnosis of neoplasms.

PURPOSE

To qualify the spectral FT-Raman data, in order to differentiate cutaneous melanoma and pigmented nevus.

METHODS

For this study, 10 samples of cutaneous melanoma, 9 samples of pigmented nevi, and 10 samples of normal skin were obtained by incisional biopsies performed during plastic surgeries ex vivo, immediately after removing the surgical sample.

RESULTS

The FT-Raman spectra of each group presented a high correlation between the elements of the same group, thus favoring the elaboration of spectral averages. When analyzing the spectral standard of each group, the normal skin standard did not show a significant variation between the spectra; the standard of the pigmented nevi group showed significant variation, and the cutaneous melanoma group also showed variation. Through univariate analysis, specific bands were detected for each vibrational mode identified. The discriminatory analysis of the data showed a 75.3% efficiency of the differentiation between the three groups studied.

CONCLUSION

The vibrational modes Polysaccharides, Tyrosine and Amide-I differentiated the melanoma from the pigmented nevus.