Vibrational spectroscopy for molecular characterisation and diagnosis of benign, premalignant and malignant skin tumours

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Vibrational spectroscopy for molecular characterisation and diagnosis of benign, premalignant and malignant skin tumours Natalja Skrebova Eikje1,4,5,*, Katsuo Aizawa2, and Yukihiro Ozaki3 1

Department of Dermatology, Tokushima University School of Medicine, Tokushima 770-8503, Japan 2 Department of Physiology, Tokyo Medical University, Tokyo 160-8402, Japan 3 Department of Chemistry, School of Science and Technology, Kwansei-Gakuin University, Sanda 669-1337, Japan 4 Clinic of Dermatology, Tartu University, Tartu 57305, Estonia 5 River Diagnostics B.V., Erasmus MC Ee1979, Dr. Molewaterplein 50, 3015 GE Rotterdam, NL Abstract. Understanding the molecular, cellular and tissue changes that occur during skin carcinogenesis is central to cancer research in dermatology. The translational aspects of this field – the development of clinical applications in dermatology from the laboratory findings – aim at improving clinical diagnosis, monitoring and treatment of skin cancer. Vibrational spectroscopy, both infrared (IR) and Raman spectroscopy, would be helpful in achieving those goals, since it has been shown to have potential in characterising and discriminating tumour and dysplastic tissue from normal tissue. Clinically differential diagnosis of skin tumours is often difficult and a histopathologic analysis of skin biopsies remains the standard for diagnostic confirmation. We review and update the literature on the subject, demonstrating that the IR and Raman spectra of skin tissues provide valid and useful diagnostic information about a number of skin tumours. We also include a survey of introduced sampling methods for IR and Raman spectroscopy in dermatology, and additionally describe the differences between microscopic, macroscopic and fibreoptic diagnosis of skin cancer. Although in its early stages, we remain optimistic that vibrational spectroscopy has the potential to be fully accepted as a rapid screening tool with sufficient sensitivity and specificity for non-destructive in vitro, ex vivo and in vivo analyses by the dermatological community. Further progress toward molecular characterisation of skin cancer by vibrational spectroscopy would have important research and clinical benefits in dermatology. Keywords: infrared (IR) spectroscopy, near-infrared (NIR) spectroscopy, Raman spectroscopy, microspectroscopy, fibreoptic, skin cancer and carcinogenesis, non-destructive diagnosis.

Introduction Skin cancers are the most common neoplasms in humans. A dramatic increase in the incidence of skin tumours during the last half a century has led dermatologists to have a great need for fast and reliable techniques that can detect cancer in skin tissue early, predict the risk of precancerous lesion progression, detect margins in the operating room in real time, select molecular therapy rationally and monitor response to therapy in real time at a molecular level [1–4]. *Corresponding author: Tel: þ37 24 83416. Fax: þ47 52 777777. E-mail: [email protected] BIOTECHNOLOGY ANNUAL REVIEW VOLUME 11 ISSN: 1387-2656 DOI: 10.1016/S1387-2656(05)11006-0

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192 Approximately half of the patients seen by dermatologists have clearly benign lesions upon visual examination. The other half require action on the part of the dermatologist, and a biopsy is usually taken for a diagnosis by histopathology. Therefore, challenges relating to diagnosis of skin cancer include differentiation of precancer from cancer, differentiation of precancer from benign tumours, differentiation of cancer from benign tumours and identification of specific cancers [5]. Histopathologic analysis of skin tumours has been the linchpin of tissue diagnosis and classification. The information provided by histopathologists regarding tumour types and subtypes, tumour grade and stage forms the core body of information required for clinical management [6]. Although many pathologists are exceptionally good at diagnosis, this analysis is somewhat subjective. In some cases, a pathologic examination may not produce a firm diagnosis, either because certain tumours are histologically similar or because cells are poorly differentiated. Therefore, the question must be asked: is it sufficient to confirm malignancy on a biopsy, even with close to 100% accuracy? [7]. Vibrational spectroscopy has received much attention from the medical community as a promising tool for non-destructive characterisation of the molecular features of cancer due to the fact that vibrational spectra are sensitive to structures of biological molecules and their changes with the diseased state [7–11,14,34–36,38–40,42–43,56,60–72]. Over the last decade, studies using vibrational spectroscopy, either infrared (IR) or Raman spectroscopy, have been conducted extensively on various human cancers, including skin cancer [7–11, 14,34–36,38–40,42,43,60,62–72]. In general, based on the results of all these studies, normal and malignant tissues can be differentiated on the order of 70 to 100% accuracy using statistical analysis [5,7–11,69,72]. If this finding is true, one must ask why vibrational spectroscopy is not used in clinical trials for the diagnosis of cancer. Vibrational spectroscopy may also be used to establish early onset of disease or stages of cancer [7]. This chapter discusses several benign, premalignant and malignant skin tumours, and their state-of-the-art IR or Raman spectral diagnostics for in vitro, ex vivo and in vivo analyses. Here, we also provide a survey of recently introduced sampling methods for IR and Raman spectroscopy in dermatology and describe, additionally, the differences among microscopic, macroscopic and fibreoptic detection for skin cancer diagnostics.

Skin tumours and carcinogenesis: Clinical and histopathologic aspects Cancer is a complex family of diseases, and carcinogenesis is a complex multistep process [7]. The concept of lineage has been central to cancer [4]. Figure 1 shows a simplified diagram of cancer progression from normal cells to cancerous cells [7].

193 (e) Invasive cancer (c) Dysplasia (a) Genetically altered cell

(d) In-situ cancer (b) Hyperplasia

Fig. 1. Simplified diagram of cancer progression. (a) Normal cells with a single genetically altered cell, (b) hyperplasia, (c) dysplasia, (d) in situ cancer, (e) invasive cancer (reproduced with permission from reference 7).

Histopathologic examination of the excised suspicious skin cancerous lesions is the gold standard for the confirmation of diagnosis [7,11]. In general, histopathologically benign tumours of the skin are characterised by a symmetrical architecture and a circumscribed profile; a tendency to differentiate along organised tissue lines; uniformity in the appearance of the tumour cell nuclei; architectural order in the arrangement of the tumour cell nuclei; restraint in the rate of growth; and absence of metastases. Malignant tumours, in contrast, are characterised by a less symmetrical architecture and a poorly circumscribed profile; a variable but often poorly differentiated phenotype; atypical appearance of the tumour cell nuclei, which show pleomorphism, i.e., great variability in size and shape, and anaplasia, that is, hyperplasia and hyperchromasia; architectural disorder in the arrangement of the tumour cell nuclei with loss of polarity; rapid growth with the presence of mitoses, including atypical mitoses; and a potentiality to give rise to metastases. Of the criteria of malignancy just cited, only the potential to give rise to metastases is decisive evidence for the malignancy of a tumour. For metastases to form, the tumour cells must possess a degree of autonomy that non-malignant cells do not have. This autonomy enables malignant tumour cells to induce foreign tissue to furnish the necessary stroma in which they can multiply. In addition to malignant tumours, one finds in the surface epidermis the so-called premalignant tumours, better regarded as tumours located largely in situ. Although cytologically malignant, they are biologically benign [12]. Benign, premalignant and malignant skin lesions may be located epidermally, dermally, or both [12]. The most common cancer of the skin, derived from the basal cell layer in the epidermis, is basal cell carcinoma (BCC), and its incidence is increasing [10,13]. It is considered to be provoked mainly by ultraviolet (UV) radiation, since it often appears in the head and neck region. Although BCCs are slow growing and rarely metastasize, some variants manifest aggressive local growth and tissue destruction. The latter is of particular importance when situated near to the eye, nose or ear. Clinical diagnostic accuracy for BCC is rather poor, being only

194 65% for practising dermatologists [14]. Clinically, differential diagnosis of BCCs from other benign and premalignant skin lesions such as melanocytic nevi, warts, seborrhoeic keratoses (SK), actinic keratoses (AK), fibrous papules and sebaceous hyperplasia is difficult. BCCs are histologically classified into indolent and aggressive subtypes. The former include superficial and circumscribed carcinomas, whereas the aggressive types, which manifest wide local invasion and a high recurrence rate, include infiltrative, morpheaform and metatypical subtypes [11]. For most types of BCC, surgery is recommended as first-line treatment. In cases of multiple suspicious skin lesions, excessive biopsying is impractical and often unacceptable for patients [14]. Another problem is that the tumour borders cannot be detected visually with 100% accuracy during surgery, allowing for a 5-year recurrence rate for primary BCC of 10% after simple surgical excision. Mohs micrographic surgery is a technique that can detect tumour margins with approximately 100% certainty: the 5-year recurrence rates are only 1% for this surgical approach. Mohs micrographic surgery, however, is a time-consuming method, both for the pathologist and the surgeon, which prevents its widespread adoption [10]. Cutaneous squamous cell carcinoma (SCC), derived from the squamous cells in the middle part of the epidermis, is a potentially dangerous tumour that may occasionally infiltrate surrounding structures and metastasize to lymph nodes and subsequently be fatal [13]. Most commonly, cutaneous SCC arises in sundamaged skin, either as such or from an AK, and has a very low propensity to metastasize (i.e., approximately 0.5%). This rate is in contrast to a metastatic rate of 2 to 3% for SCC, with death resulting in about 75% of the patients with metastases [12]. Those SCCs arising within AK are much less aggressive than those arising de novo or from other causes such as mucosal Bowen’s disease, irradiation, burns or chronic skin disorders. Lesions on the genitalia or lips tend to become invasive and metastasize early. The diagnosis of SCC, although easily made in typical cases, may sometimes be difficult. The differences between SCC and AK lie in the degree rather than the type of changes. For differential diagnosis, only in SCC is there an invasion of the reticular dermis. No sharp line of demarcation exists between the two conditions even histologically [12]. Actinic (solar) keratoses are premalignant lesions that are characterised by variable degrees of dysplasia, ranging from mild changes through to carcinomata in situ. Bowen’s disease has the histologic features of carcinoma in situ. A typical lesion is characterised by parakeratosis, acanthosis and full-thickness dysplasia. Management of intraepidermal carcinoma of the skin depends on the size of the lesion and on the age of the patient. Excisional biopsy is the treatment of choice, but if the lesion is too large, radiotherapy, curettage and cautery, or cryotherapy may be satisfactory alternatives. Malignant melanoma (MM) is the most aggressive skin cancer, and if untreated is invariably fatal. It affects the melanocytes (pigment-producing cells)

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in the basal layer of epidermis. The specificity and sensitivity of clinical diagnosis varies from approximately 40 to 80% and the diagnostic accuracy depends largely on the length of training of the clinician: 80% for trained dermatologists, 62% for senior registrars, 56% for registrars and approximately 40% for nondermatologists. About 70% of patients survive 5 years after diagnosis. Early diagnosis is essential because removal of MM at early stages is almost always curative. The more superficial the lesion at the time of excision, the better the prognosis. Skin tumours that can be clinically confused with melanoma are pigmented nevi, superficial BCC and SK. Prophylactic removal of every pigmented lesion is unacceptable for the patient, particularly in the case of multiple skin lesions or lesions localised in cosmetically important parts of the body, such as the face, because of the risk of scarring. Eighty percent of biopsies taken by non-dermatologists of suspected malignant skin lesions have been reported to be benign and thus inappropriate surgery is frequent [9]. Melanocytic proliferations, benign or malignant, are composed of one or more of three types of cells: melanocytes, nevus cells and melanoma cells, each of which may be located in the epidermis or in the dermis. Melanocytes are solitary dendritic cells that generally are separated from one another by other cells (keratinocytes or fibroblasts). Nevus cells and melanoma cells differ from melanocytes in that they have undergone proliferation to lie in contiguity with their neighbours. Melanoma cells, in turn, acquire nuclear abnormalities constituting uniform cytologic atypia. Benign pigmented lesions composed of epidermal melanocytes include freckles, solar lentigines, the melanotic macules of Albright’s syndrome and Becker’s melanosis. Benign pigmented lesions derived from dermal melanocytes include the Mongolian spot, the nevi of Ota and of Ito and the blue nevus. Benign tumours of nevus cells are called melanocytic nevi and can be divided into junctional nevi, compound nevi and intradermal nevi [15]. MM may be located in situ or may be invasive. Invasive melanoma may be tumourigenic (vertical growth phase) or non-tumourigenic (radial growth phase). Clinically melanoma in situ and non-tumourigenic invasive melanoma can be divided into lentigo maligna, superficial spreading, acral lentiginous and mucosal lentiginous types. Generally, a complete report on MM includes the histogenetic subtype, the level of invasion, the tumour thickness, the presence or absence of lymphocytic infiltrate and an assessment of the mitotic activity of the tumour. Patients with MM should be monitored for the rest of their lives and examined for local recurrence, metastasis and fresh malignant disease. In conclusion, carcinogenesis of many skin tumours still remains unclear. Their etiology and pathology awaits further scientific explanation. Moreover, a search for rapid non-invasive techniques that can be applied for real-time primary and follow-up screening, selection of lesions for further biopsying and for real-time intraoperative in vivo tumour border demarcation is critical in clinical dermatology today [9–10,13].

196 Infrared and Raman spectroscopy: A comparison Both techniques are based on molecular vibrations, and are often complementary, each having their own advantages and disadvantages [3,7,11,15]. Raman effect and infrared absorption process The physics of Raman effect and that of the infrared absorption process are different to some extent from each other, and these dissimilarities have important implications for the applications of vibrational spectroscopy to biological samples. In IR spectroscopy, an irradiated molecule absorbs the incident light quanta and a transition from a lower to a higher vibrational level occurs. For the IR light to be absorbed by the molecule, a change in the dipole moment during the molecular vibration must take place. The Raman effect is an inelastic process of low probability. The incident light quanta collide with the molecule, and an exchange of energy between the molecule and the photons occurs. Consequently, the scattered light quanta have a higher or lower energy. The energy gained or lost by the molecule results in changing the molecule from its initial vibrational state to a different vibrational state. For the molecule to exhibit the Raman effect, a change in the molecular polarisability during the vibration must occur [3,7,17,26,30,32,33]. IR and Raman sampling techniques One of the great advantages of vibrational spectroscopy is that it is not limited to a particular state of the sample. In principle, Raman has an intrinsic advantage over IR for aqueous biologic samples, mostly due to the weak scattering of water. To that effect, a significant proportion of IR applications to date have concentrated on in vitro studies of tissues and cells, whereas in Raman, the big movement is toward in vivo diagnostics [7]. In Raman spectroscopy, excitation light can be UV (<400 nm), visible (400

780 nm) or near-infrared (>780 nm) light. However, when visible excitation is used, skin tissue exhibits strong, broadband fluorescence due to the presence of cellular components, which can obscure the tissue Raman spectrum. The onset of fluorescence from skin diminishes when a radiation source moves toward the red ( 600 nm) or particularly the near-infrared (NIR) region (above 780 nm). In the NIR region the energy of the photons usually is too low to cause the transitions between electronic states that give rise to fluorescence. Due to the lower energy of the NIR photons a higher laser power may be used without damaging the sample [3]. The selection of a radiation source is also influenced by sample colour, stability and molecular properties that may result in fluorescence [3,17,18]. NIR light penetrates tissue deeply, on the order of millimetres. That is the limited opportunity for IR light [7,16]. Therefore, when probing larger skin tissue

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depths by NIR Raman spectroscopy the tissue signal is not swamped by the water spectrum, since it shows only weak bands and backgrounds [19]. Over the last decade, dramatic technological advances have occurred for many components of IR and Raman instrumentarium, thus allowing the translation of these methods from that of a laboratory to a clinic [3,20–22]. Technical developments include new lasers that provide a wide range of excitation wavelength, sophisticated computer software for data collection and processing, novel photonic devices (charge-coupled device (CCD) detectors, holographic filters, fibreoptic probes) and new instrumental refinements and concepts (confocal Raman microscope, Fourier transform (FT) Raman spectroscopy and Raman imaging). (In-depth discussions of these new developments have been published elsewhere [17,23–28]). Therefore, micro- and macro-sampling conditions became possible for measuring tissue samples, including skin, as well as in vivo real-time measurements in almost any body region, thus providing potential in the field of clinical diagnostics. IR and Raman spectroscopic investigations can be roughly divided into two major areas; either IR or Raman pathology, which attempt to provide an alternative pathologic assessment of a tissue biopsy; and in vivo analyses, where the analysis of the molecular features of cancer is done without the need for an invasive procedure in real time [1,29]. At present, neither technique has regulatory approval nor is commercially available for routine medical diagnostics, but significant leaps have been made toward this goal [7]. Microscopic sampling introduced in dermatology Microspectroscopy Microscopy is an integral part of diagnostics, with visible microscopy of stained tissues considered the gold standard [7]. The microscope has become one of the most significant accessories for an FT-IR and Raman spectrometer, able to measure vibrational spectra of individual morphological components of tissues [7,20,30,31]. The essential features of confocal microscopy are illumination of only a small region of a sample and passing of the scattered light through an aperture placed at the entrance of the spectrometer [3,30,31]. Integration of Raman spectroscopy into confocal microscopes enables the depth information to be obtained, as well as signals from subcellular structures [32,33,45,46,72,73]. Vibrational microspectroscopy can create spectral maps of tissues, which if given some colour notation, would correspond directly to tissue histology. In addition to providing colours to which most pathologists are accustomed, these maps also provide fairly detailed biochemical information not available from other techniques. It is important to emphasise that these maps are produced from spectra without prior knowledge of tissue architecture on samples that are not stained. Spectral mapping allows the combined understanding of

198 morphology and biochemistry that give rise to observed spectra [7,60]. It is important to understand the spectral features of each morphological structure. By comparing spectra of each individual structure in the normal tissue and diseased state we can begin to understand how these components change during the process of carcinogenesis. A major advantage of the application of FT-IR or Raman microspectroscopy for histopathological assessment of skin cancers is the minimal sample preparation required for presentations of the specimen to the spectrometer [18,20]. Besides that, the microscopy technique provides non-destructive compound identification both at single cell and tissue levels, thus showing potential as a promising analytical technique for pathological examination of components and tissue changes during the process of carcinogenesis. However, one of the most important and difficult steps is to define accurately the sample area, or measured area, particularly if the sample of interest is very small such as a single cell or a cluster of cells embedded in tissue [7].

Sample preparation Skin tissue samples prepared for histology are readily available from any dermatology unit at a hospital or a histology laboratory, so it would seem natural to want to use these samples for in vitro spectroscopic studies. But, can we use those fixed, sectioned, mounted on a glass slide and stained samples that dermatopathologists assess for cancer diagnosis? Many questions immediately arise – glass absorbs mid-infrared radiation; what effects do paraffin and dyes have on the spectra? Very inexpensive and easy to use glass slides that are used for visible microscopy absorb strongly in the mid-infrared region, and thus are probably not optimal for tissue measurements [7]. Calcium fluoride (CaF2) windows are IR-transparent, and have been commonly used in studies by FT-IR and Raman microspectroscopy [10,34,35]. Hematoxylin, the dye of choice, has an affinity for negatively charged molecules and therefore reveals the distribution of DNA and RNA in a cell. Hematoxylin and eosin (H&E), is the most commonly used combination of dyes, staining the nucleus, cytoplasm and collagen. Any fixation and embedding procedure has a danger that the treatment may distort the structure of the cell. An alternative method of preparation is rapid freezing, which precludes either fixation or embedding. Although frozen tissues have an advantage that represent a more natural form of the tissue, they are more difficult to prepare and stabilise. Unstained tissues are very homogeneous to the eye, appearing alike throughout the section. Identification of regions of interest is extremely difficult, even with a polariser in the microscope. The use of unstained tissues is mainly due to the general belief that absorption bands due to the stains interfere with the absorption spectrum of the sample. Most investigators choose to make unstained samples for skin tissue studies, while using histological sample as a reference to orient collection of spectra [36]. Skin tissue samples can be prepared from frozen sections of tissue

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that are air dried before spectral data acquisition. Alternatively, in studies described by FT-IR microspectroscopy, sections can be prepared in strictly sequential order by first staining with H&E – both for the establishment of a histopathological diagnosis and for orientation spectra collection from the unstained samples – and then air-drying on CaF2 slide glasses for further spectral data acquisition from defined areas of interest [34,35]. Skin tissue sections of about 5–7 mm thickness give good signals by the IR microscope, but longer pathlengths can lead to intensity distortions in the strong protein absorption bands [11,34–36]. For NIR Raman microspectrometry cryosections of 25 mm thickness have been used for data acquisition [10]. Acquisition of spectra Utilised FT-IR microspectrometers were used to obtain spectra with a resolution of 4 cm1 over a spectral region of 800–4000 cm1, using a knife edge aperture reduced to 252  25 mm or 20  20 mm [11,34,35]. Raman data acquisition by a microscope was based on scanning the pixel area of 10  10 mm2 in two dimensions using a step size of 10 mm [10].

Macroscopic sampling introduced in dermatology IR spectroscopy In spite of being an easy and fast technique, IR spectroscopy has limited opportunities to greater skin tissue depths, than 20 mm, due to the physics involved [7,16,37]. Raman spectroscopy Introduction of NIR FT-Raman spectrometers, using 1064 nm excitation (neodymium-doped yttrium aluminium garnet (Nd:YAG) lasers) and cooled gallium arsenide (GaAs) or germanium (Ge) detectors has allowed collection of fluorescence-free spectra from a variety of tissues [7,17,18,38–41,59]. However, GaAs or Ge detectors exhibit substantial noise, so that the collection time needed to obtain Raman spectra of tissues with a good signal-to-noise ratio (S/N) is lengthy (30–60 min) [7]. Hamaguchi et al. recently have been involved in developing a dispersive NIR Raman spectrometer using a multichannel detector, with a new InP/InGaAsP photocathode which is well suited to 1064 nm excitation [75]. With laser power of less than 110 mW and a spectral resolution 10 cm1 it enables acquisition of a spectrum in the wavenumber range 800–1800 cm1 in 5 min. Next, by applying an image intensifier (NIR-II) and CCD linear sensor of Hamamatsu Photonics Co. (Shizuoka, Japan) they showed preliminary results obtaining spectra from lung tissue within 400 s and from human skin within 64 s using a fibreoptic dispersive NIR Raman spectrometer [62].

200 The development of diode lasers and low-noise cooled silicon charge-coupled device (CCD) cameras sensitive in the NIR region, combined with the use of dispersive systems instead of FT-based spectrometers, has enabled the measurement of fluorescence-free tissue Raman spectra on a much faster timescale, in minutes, or even seconds. A combination of a diode laser and a dispersive system has provided better sensitivity and the possibility of f-number matching of spectrographs with optical fibres for better throughput. The spot size is dependent on the optics used and because most research groups build their own systems or modify existing commercial systems, this number varies but is on the average around 1 mm. These three general components, NIR laser excitation, dispersive spectrograph and CCD cameras, are now used for most tissue studies, in vivo or in vitro and as with IR spectrometers can be easily modified for microscopic studies by an addition of a microscope [7]. Sample preparation Pathology by NIR FT-Raman spectroscopy has been reported for macro mode three-millimeter punch biopsies and curetted specimens of benign, dysplastic and malignant skin lesions [9,14,42]. Before sampling those lesions, the skin was cleaned with 70% ethanol and anaesthetised with a 2% lidocaine solution without adrenalin. The samples were kept at 4 C in a moist environment during the short period before analysis. Raman spectra measurements were performed within less than 30 min after collecting the biopsies. Those that were deeply frozen were transferred to closed vessels and allowed to thaw at +4 C for 3–5 min. No sample pre-treatment was performed. The lesions were histologically verified. Acquisition of spectra The laser beam (1064 nm line at 300 mW from a continuous wave Nd:YAG laser) was focused to a spot of approximately 100 mm diameter on the epidermal site of the biopsy or curetted specimens, which during the procedure were placed in a stainless-steel cup [9,14,42]. The measured spectra in macro mode reflect an average of all cellular and extracellular components present in the path of the beam [7]. Individual components have distinct vibrational features and the resulting spectra are dependent on the contribution of each component and its concentration. Because different components are always present in different concentrations throughout microtome tissues, even within the same tissue slice, Raman spectra obtained in this mode will definitely show differences. These differences could be significantly larger within the same group of tissues, e.g., normal, than for a different type of tissue, e.g., malignant. On the other hand, the presence or absence of a particular component in significant amounts might indicate ‘‘malignancy’’ or a change towards malignancy, and that can be easily detected by a macroscopic method [7].

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Direct measurement on the skin tissue Skin pre-treatment Removal of superficial dirt and excessive sebum with ethanol is recommended. No pre-treatment of the skin is normally needed, unless dependent on experiment design.

Fibreoptic probe A fibreoptic probe coupled to an IR [43] or Raman [28] spectrometer provides an intriguing and very promising possibility of in vivo, real-time spectroscopic diagnostics [54,55,60]. Fibreoptic cables provide a flexible solution for an adequate optical interface between the spectroscopic device and the sample to be interrogated in situ [28]. For IR spectroscopy, fibreoptic probes can be operated in transmission or an attenuated total reflectance (ATR) mode, with the latter being most common [7]. The principle is fairly simple – the beam is directed through an optical fibre to the ATR crystal and back to the spectrometer through another optical fibre. Advantages of such measurements are practically no sample preparation, noninvasiveness of the procedure, very fast turnaround time for diagnosis and less expense. The area measured is that of contact between a crystal and a sample and is usually a few square centimetres [7,16]. The suitability of two several types of IR transmitting fibres for distinguishing cancers from normal tissue by FT-IR microspectroscopy was investigated. Chalcogenide fibres showed higher optical stability than silver halide fibres. However, these fibres have a very low transmittance in the important fingerprint region. Moreover, chalcogenide fibres break easily [60]. The design of a fibreoptic probe for Raman spectroscopy is driven by maximal light collection. The usual construction of a fibreoptic probe is to have one laser fibre surrounded by a number of collection fibres, normally six or seven. Additionally, background signal originating from the laser source, the fibres and all optical components can fill the dynamic range of the detector and overwhelm the Raman signal [38–40]. These signals must be reduced with filters to enable sensitive in vivo measurements. The dynamic range of the detector can be enlarged with multiple readings that reduce the noise by the square root of the number of readings. Another advantage of Raman fibreoptic probes is that they can significantly reduce power density at the sample [7,28,44]. Remote microscopy has been achieved through the development of fibreoptic CCD-based confocal microscopes as a non-invasive in vivo optical method to measure molecular concentration profiles in the skin. This type of combination can provide high resolution, three-dimensional Raman imaging capabilities of analysing skin molecular composition as a function of distance to the skin surface in a portable package, with a depth resolution of 5 mm [45,46].

202 Vibrational reference spectra of normal skin and its main components The skin is a very complex and heterogeneous tissue, comprising several components and different cell types. As the biochemical composition varies in the distinct skin layers vibrational spectra measured on the individual layers are expected to show differences in band position and band intensity. As a consequence of the complexity of human tissues, the band assignment in the spectra is difficult, especially in diseased states. It is therefore important to facilitate the band assignment of spectra of major constituents of skin and its compounds [3,7]. Individual components have intrinsically different sizes and the same components may vary in size depending on cancer progression. So, unless components are measured with the beam size or spot size corresponding to the dimensions of that component, even with the microscope, the resulting spectrum will correspond to a composite spectrum of several such components, weighted with respect to their relative concentrations [7]. Main components of cells and tissues Proteins Both IR and Raman spectra of proteins provide information about the secondary structure of proteins, ligand interactions and folding [7]. In the vibrational spectra, the amide bonds of proteins form so-called chromophores that give rise to nine strong characteristic bands that are named amide A, amide B and amides I–VII. Among these bands, amide I, which is mostly due to the C O stretching vibration of the peptide backbone, is by far the best characterised. It gives rise to an IR band in the 1600 to 1700 cm1 region, and has been used mostly for secondary structural studies due to its high sensitivity to small changes in molecular conformation and hydrogen bonding of peptide groups. The amide II band, due largely to a coupling of C–N stretching and in-plane bending of the N–H group, is extremely weak in a Raman spectrum. Although it is fairly strong in IR, giving rise to a band in the 1500–1575 cm1 region, the amide II band is not often used for secondary structural studies per se because it is less sensitive and is subject to interference from absorption bands of amino acid side-chain vibrations. The amide III band, arising from coupling of C–N stretching and N–H bending, and giving rise to bands in the 1230 to 1300 cm1 region, is fairly weak in the IR but quite strong in Raman [7,18,21]. Nucleic acids Although all biomolecules are important, the nucleic acids of ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) are especially important because they carry within their structure the hereditary information that determines the

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identity and structure of proteins. Each protein, unique in its structure and hence in its function, then participates in the process that characterises the individuality of the cell. The bands with the strongest intensity correspond to regions and assignments of the following vibrations. The 1620 to 1750 cm1 region corresponds to in-plane double-bond vibrations of the bases. The spectra in this region are very sensitive to base-pairing interactions and base-stacking effects, i.e., effects of hydrogen bond formation. The 1230 cm1 and 1090 cm1 bands are assigned to antisymmetric and symmetric phosphate stretching vibrations, respectively. In solids, the most significant difference between the two nucleic acids is the ratio of intensity of the bands in the multiplet around 1055 cm1. The IR spectrum of a typical lipid shows the major absorptional bands at 1738, 1465, 1255, 1168, 1095, 1057 and 968 cm1 [7,21]. Lipids In Raman spectra of lipids, the 700–1800 cm1 region is dominated by bands due to –C–C– chain stretching modes, the CH2 bending modes and carbonyl stretching modes and the 2800–3100 cm1 region is characterised by bands due to –C–H– stretching modes [7,26,52]. The bands at 2850 cm1 and 2880 cm1 are assigned to acyl chain methylene (CH2) symmetric and asymmetric stretching vibrations. Additionally, intrachain trans-gauche isomerisation can be determined from the I2935/I2880 peak height intensity ratio [21]. The ordered nature of a lipid matrix can be indicated by the relative intensities of the 1083 cm1 and 1129 cm1 bands arising from gauche and trans –C–C– stretching modes, respectively. The unsaturated chain of lipids is probed by an intense 1662 cm1 band [7,21]. Water IR and Raman bands of water are observed as a broad feature centered at approximately 3250 cm1, which are known as symmetric and asymmetric stretching modes of the covalent O–H bonds [47], near the 1645 cm1 bending mode and at approximately 180 cm1 [37,48,49]. Stratum corneum The molecular basis of the human stratum corneum has been probed in vitro, ex vivo and in vivo by ATR FT-IR spectroscopy, FT-IR spectroscopy, FT Raman spectroscopy and confocal Raman spectroscopy [3,39–40,46,48,50–52]. In vitro spectra Wavenumber frequencies (cm1) and approximate description of the main vibrational modes identified in vitro in FT-IR and FT Raman spectra of normal stratum corneum of the skin in the range 400–4000 cm1 are presented in Table 1 [50–52].

204 Table 1. FT Raman, FT-IR and NIR-FT Raman frequencies (cm1) and approximate descriptions of vibrational modes for human stratum corneum (reproduced with permission from references 50, 52). FT Raman

FT-IR

Assignment

424 w, br 526 mw, br 600 w, br 623 w 644 746 w, br 827 w 850 w 883 mw 931 w, br 956 w 1002 m 1031 mw 1062 mw 1082 mw 1126 mw 1155 w 1172 w 1207 mw 1244 w, sh 1274 mw 1296 ms 1336 m — 1385 vw — 1421 w, sh 1438 s — — — 1552 w 1585 w 1652 s

— — — — — — — — — — — — — 1076 — — — — — 1247 — 1298 — 1366 1389 1401 — 1440 1451 1460 1515 1548 — 1650

d(CCC) skeletal backbone n(SS) r(CH) wagging n(CS) n(CS); amide IV r(CH)2 in-phase d(CCH) aliphatic d(CCH) aromatic r(CH2) r(CH3) terminal; n(CC) a-helix r(CH3); d(CCH) olefinic n(CC) aromatic ring n(CC) skeletal conformation n(CC) skeletal, trans conformation n(CC) skeletal, random conformation n(CC) skeletal, trans conformation n(CC); d(COH) n(CC)

1743 1768 2723 2852 — 2883 — 2931 2958 3000 3060 — —

1656 1743 — — 2851 2873 — 2919 — 2957 — — 3070 3287

vw vw w m ms s m, sh vw, sh w

w

w w vw vw w vw vw vw w, sh vs vs vs w

s w vs w

w vs, br

d(CH2) wagging; n(CN) amide III disordered n(CN) and d(NH) amide III a-helix d(CH2) — d[C(CH3)2] symmetric d(CH3) symmetric d[C(CH3)2] symmetric d(CH3) d(CH2) scissoring d(CH3) asymmetric d(CH2) — d(NH) and n(CN) amide II n(C C) olefinic n(C C) amide I a-helix n(C O) amide I disordered n(C O) lipid n(COO) n(CH) aliphatic n(CH)2 symmetric n(CH)3 symmetric n(CH)2 asymmetric n(CH)2 asymmetric n(CH)3 symmetric n(CH)3 symmetric — n(CH) olefinic 1st overtone, amide II at 1548 cm1 n(OH) of H2O

v ¼ Very, s ¼ Strong, m ¼ Medium, w ¼ Weak, sh ¼ Shoulder, br ¼ Broad, d ¼ Deformation, n ¼ Stretch, r ¼ Rock.

205

In vivo spectra Representative ATR-FTIR spectra of human stratum corneum in vivo have been recorded from different anatomical locations by Brancaleon et al. [37]. They described differences in hydration, lipid composition and conformation of the aliphatic chains strictly dependent on the anatomical site. In vivo spectra of normal stratum corneum of the thenar, obtained by confocal Raman microspectrometer in the 400–1850 cm1 spectral interval at the depth range of 0–80 mm (increment 10 mm) below the skin surface, were recorded by a group at Erasmus University [46].

Normal skin One possible solution is to record a vibrational spectrum of each individual skin layer of interest and, compare these so-called standard spectra with spectra that are recorded from a whole skin sample. The standard spectra can be made by chemically separating the distinct layers of the skin – the stratum corneum, the epidermis (the stratum corneum included) and the dermis – although this procedure, however, is not ideal; or recorded from a cross section of a whole skin sample by focusing the laser light parallel to the surface. A whole skin measurement can be done by focusing the laser beam on the epidermal site of the skin biopsy or directly from the skin [3,5, 8,9,14,42,52]. To aid in the interpretation of the spectra form the whole skin, various reference spectra must be recorded in vitro, ex vivo and in vivo. It has been found that there is a great similarity between the spectrum of the whole skin and the spectrum of dermis. Sample handling does not influence Raman spectra because it has been shown that the spectra from the biopsies and those collected directly from the skin via optic fibres are virtually identical in the region 600–3500 cm1 [3,40,52,53].

In vitro spectra Representative spectra of the epidermis and/or the dermis without contamination from other skin components were measured by means of FT-IR microspectroscopy, NIR-FT Raman spectroscopy, fibreoptic NIR-FT Raman spectroscopy, NIR Raman microscopy and confocal Raman microspectrometer by different research groups [3,10–11,34–35,39–40,45]. In vitro spectra of the whole skin have been intensively collected by NIR-FT Raman spectrometer and largely described by the group at the University of Copenhagen [9,41,42,49,52,53]. Major vibrational modes identified in biopsy samples of normal human skin are provided in Table 2.

206 Table 2. Major vibrational mode changes identified in NIR-FT Raman spectra of the samples of normal human skin. Peak position, mean with 95% confidence intervals (cm1) (reproduced with permission from reference 52). n(C O) amide I

d(NH) and n(C–N) amide III

das(CH3) in proteins

d(CH2) scissoring in lipids and d(CH2), d(CH3) in proteins

Acyl backbone chain conformation in lipids

n(S–S) in proteins

1661 cm1 1271 cm1 2942 cm1 1451 cm1 1100 cm1 540 cm1 1 1 1 1 1 (1660–1663 cm ) (1270–1273 cm ) (2941–2943 cm ) (1449–1452 cm ) (1093–107 cm ) (534–546 cm1)

n, stretching mode; ns, symmetric stretch; nas, asymmetric stretch.

In vivo spectra Literature shows only a few reference spectra measured in vivo of normal skin. They were mostly measured by commercially available fibreoptic NIR-FT Raman spectrometers [19,39,40,54,55]. The in vivo Raman spectrum of normal human skin obtained by fibreoptic NIR-FT Raman spectroscopy contains information about protein structure in the 1200–1700 cm1 region and about lipid conformations in the 1000–1200 cm1 region. The n(S–S) and n(C–S) regions, 500–550 cm1 and 620–700 cm1, respectively, contain information about transand gauche-conformations of the cystine residues of the keratins [41]. A group at Erasmus University measured in vivo spectra of normal skin in the depth range of 0–80 mm below the skin surface using a confocal Raman microspectrometer [46]. IR and Raman spectral features between healthy and diseased tissue All diseased states, without exception, are caused by fundamental alterations in cellular and/or tissue biochemistry, which inevitably lead to specific changes in concentrations and/or structure of proteins, lipids, nucleic acids and carbohydrates. These changes in the quantity and conformation manifest themselves in vibrational spectra as changed intensities and frequencies of observed bands. A critical issue is the requirement that variations in spectra from measurement to measurement, sample to sample and patient to patient must be small compared to a change caused by an abnormality, as well as variations between normal and abnormal tissues [3]. Vibrational spectroscopy allows the identification of chemical compositions, the elucidation of molecular structures and the probing of dynamic processes and intermolecular interactions [3,7,17–19,21,23,25,26,36,46,52,54,56]. In addition to the qualitative characterisation of medical samples of interest, vibrational spectroscopy can make quantitative or semi-quantitative determinations.

207

By measuring IR- or Raman marker bands of proteins, lipids, water or nucleotides, the relative ratios and the absolute concentrations of each component can be determined and related to pathogenic changes [5,7,8–11,14,19–21,34–36, 38–40,42,46,49,50,52–56,58–72]. Additionally, sensitivity of IR spectral features toward differentiation, maturation, cell cycle dependence and state of health of human cells is very advantageous for the correct interpretation of IR spectra of healthy and abnormal cells and tissues [56]. Two classes of changes in the IR and Raman spectral patterns have been observed between healthy and diseased tissues: gross spectral changes and disease-induced changes. The first class of changes includes those non-specific for disease. Similarly, changes in the structural protein content of tissue, or the changes accompanying cell maturation and differentiation, can be observed with IR spectroscopy, but these changes are not necessarily correlated with the occurrence of disease. However, these changes are ideally suited to create maps of tissues or distributions of cells that can augment the information obtainable from photomicrographs of stained tissues used in pathology. In fact, the advantage of IR mapping is that such a map contains more information per pixel element, than stained tissue, and can be constructed and interpreted totally objectively by computer methods [36,56]. Among the disease induced spectral changes, it has been found that certain spectral regions due to nuclear DNA appear to be enhanced in samples with diagnosed cancer. Since the DNA spectral features are superimposed on those due to nuclear and cytoplasmic RNA, these changes are generally very subtle [56]. Spectral features in the characterisation of skin cancers by vibrational spectroscopy Increasing number of reports suggests that the IR and Raman spectra of malignant skin tissues contain enough information to give valid, useful diagnostic information about that tissue for a number of skin tumours [29]. FT-IR microspectroscopy Examined FT-IR spectra of epidermal and dermal benign (dermal (benign) nevi), premalignant (Bowen’s disease, solar keratosis) and malignant (SCC, BCC, MM) skin lesions showed the most visible differences in the 800–1800 cm1 region, when compared to spectra from equivalent normal epidermal and dermal skin components (Figs. 2a–d) [34,35]. Those differences were related to variations in descriptive and non-descriptive proteins, DNA/protein (chromatin) and DNA peaks: absorption between 1000 and 1150 cm1 seems to correlate with a variation of the amide I1600–1700 cm1/amide II1480–1575 cm1 areas intensity ratio; the spectral features due to DNA and amide III (965 cm1, 1071 cm1, 1084 cm1, 1095 cm1, 1245 cm1) are modified and enhanced with progression to malignancy [34,35].

ABSORBANCE

ABSORBANCE

208

Fig. 2. (a–d) Representative FT-IR spectra in the 800–1750 cm1 region of epidermal premalignant (Bowen’s disease, solar keratosis), malignant (SCC, BCC, MM) tumours and dermal benign (nevi) lesions, in comparison to normal epidermal and dermal skin components (reproduced with permission from reference 35).

IR microspectroscopy Qualitatively, the following differences were noted in measured IR spectra of melanocytic lesions (lentiginous/junctional nevi, compound dysplastic nevi), SCC (SCC in situ and invasive SCC) and BCC (aggressive-growth tumours of infiltrative pattern; indolent growth neoplasms, comprising nodular and

209

Fig. 2. (Continued.)

superficial patterns): (i) absorption bands at 980 cm1 (ribose group of nucleic acids), 1080 and 1240 cm1 (phosphate groups of nucleic acids) were increased in all three tumour types when compared with normal epidermis, but most intense in the spectra of BCC; (ii) BCC tumour cells appeared to contain more lipid-like material than melanocytic lesions and SCC, as judged from the increased lipid ester C O (1740 cm1) and acyl chain CH2 bands; (iii) a shoulder was present on the DNA absorption band at 1080cm1 in melanocytic lesions and SCC [11]. Quantitatively, significantly increased intensities from nucleic acid absorption bands at 980,1080 and 1240 cm1 were found in the BCC spectra and significant increases in the lipid bands between 2800 and 3000 cm1 [11].

210 NIR-FT Raman spectroscopy Primarily, Raman spectra from BCC and normal skin were obtained in the region from 1000 to 3500 cm1. Analysis of the band intensities in the regions of 1220–1360, 900–990 and 830–900 cm1 allowed for a complete separation between BCC and normal skin spectra, since those spectral regions showed the most significant spectral changes (Table 3) [14]. An overall loss in total intensity seems to occur in both the amide I and amide III regions in the BCC spectra. Changes in the Raman spectra of BCC samples were observed in bands characteristic of lipids, CH2 scissoring vibration (1420–1450 cm1) and –(CH2)n– in-phase twist vibration around 1300 cm1 [14]. Subsequently, data obtained on NIR-FT Raman spectrometer showed prominent differences between normal samples and samples of benign, premalignant and malignant skin lesions (Table 4). Alterations of protein structure did not indicate malignancy, because amide I and amide III changes were present in non-malignant skin tumours. Most of the examined skin lesions presented alterations in the spectral regions 1065 to 1094 cm1 and 1243 to 1258 cm1 that can represent the phosphate backbones, phospholipid contributions and reflect protein conformations [42]. NIR-FT Raman spectra were obtained from samples of melanoma and other skin tumours that can be clinically confused with melanoma: pigmented nevi (PN), BCC, seborrheic keratoses (SK) and normal skin. Figure 3 demonstrates spectral alterations of the following major spectral bands: a major decrease in intensity of the amide I band of proteins in MM, a slight decrease of the right wing of the band in PN; the amide III band region around 1270 cm1 and an increase in the lipid-specific region 1300–1340 cm1 in MM, BCC and SK; a decrease of the n(C–C) band around 940 cm1 in proteins and lipids in MM, BCC and SK [9]. Neural network analysis of Raman spectra achieved a diagnostic sensitivity of 85% and specificity of 99% for MM and was 97% and 98% for BCC, respectively. SK was diagnosed with 96% sensitivity. PN were diagnosed with 78% sensitivity [9]. NIR Raman microscopy Raman spectra in a two-dimensional grid from unstained frozen sections of BCC specimens were compared to spectra obtained from the surrounding tumour-free Table 3. Comparison of Raman intensities from normal skin and BCC (means with 95% confidence intervals in parentheses) (reproduced with permission from reference 14). Region (cm1)

Normal skin

Basal cell carcinoma

(1290–1360)/(1230–1290) 900–990 830–900

0.29 (0.22–0.36) 0.20 (0.17–0.22) 1.16 (0.14–0.18)

1.37 (1.21–1.54) 0.10 (0.08–0.12) 0.07 (0.04–0.10)

Table 4. Summary of Raman spectral changes in benign and malignant skin lesions. The changes in spectra of skin lesions were compared with the spectra of normal, control skin. Only changes seen for all spectra collected from a particular lesion are included (reproduced with permission from reference 42). Lesion and number of acquired spectra

Amide I of proteins 1661 cm1

Amide III of proteins 1271 cm1

CH2 twisting and wagging of lipids 1309 cm1

nas(CH2) of proteins and lipids 2942 cm1

ns(CH2) of proteins and lipids 2852 cm1

d(CH2) d(CH3) of proteins and lipids 1451 cm1

Aromatic ring (breathing mode) 1004 cm1

n(C–C) proline valine 939 cm1

Tentative PO2 in nucleic acids and phospholipids 1247 cm1

Tentative PO2 in nucleic acids and phospholipids 1080 cm1

Skin tag Dermatofibroma SK Keratoacanthoma AK SCC BCC Compound nevus Dermal nevus Dysplastic nevus Lentigo maligna

— — ! ! ! ! ! # # # #

— — # # # # # — — # #

— "! "! "! — — — — — — —

— — ! ! ! ! ! — — — —

— — " " — — — — — — —

— — ! ! ! ! ! — ! — !

— — " " " " " — — — —

— — — — # # # — — — #

— — # # # — # — — — —

— — " " " " — — — — —

211

212

Fig. 3. NIR-FT Raman spectra of normal skin (NOR), pigmented nevi (PN), MM, BCC and SK. Spectral alterations of the following major spectral bands are shown: (a) a major decrease in intensity of the amide I band of proteins in MM, a slight decrease of the right wing of the band in PN; (b) the amide III band region around 1270 cm1 and an increase in the lipidspecific region 1300–1340 cm1 in MM, BCC and SK; (c) a decrease of the n(C–C) band around 940 cm1in proteins in MM, BCC and SK; (d) a widening of the d(CH2)(CH3) in proteins and lipids in MM, BCC and SK (reproduced with permission from reference 9).

epidermis and dermis, showing a marked difference between them. Table 5 shows the specific band assignments of the Raman peaks in the spectral difference calculated by subtracting the spectrum of dermis from that of BCC [10]. The dermis in the vicinity of the tumour contains less collagen than dermis at a greater distance from the tumour. While the distinction between the Raman spectra obtained from BCC and that form dermis was apparent, differences in the Raman spectra from BCC and epidermis were more subtle. Those small spectral differences were due to a relatively higher DNA content of BCC (Fig. 4). The principal component scores, obtained for each spectrum, were used as input for K-mean clustering analysis (KCA). The cluster means from Raman images were used to create a tissue classification model, to discriminate BCC from surrounding nontumourous tissue. This resulted in a sensitivity and specificity for BCC of 100% and 93%, respectively [10]. Data processing considerations Accurate IR- and Raman clinical diagnosis, objective analyses and interpretation of spectral data require special attention [7–11,14,21,29,35,57,58].

213 Table 5. Observed wave numbers of Raman peaks of difference spectrum BCC dermis and their assignments, characteristic for BCC (reproduced with permission from reference 10). Wave number (cm1)

Assignment

727 746 786 830 900 957 1003 1085 1127 1207 1304 1336 1445 1651

Adenine Thymine DNA, RNA (PO2 symmetric stretching) DNA (PO2 asymmetric stretching) Unassigned Lipids, proteins (CH3 deformations) Phenylalanine (ring breathing) Lipids, nucleic acid backbone (PO2 symmetric stretching) Lipids, (C–C stretching, trans) Tyrosine, phenylalanine Lipids; proteins (amide III band), adenine, cytosine Adenine, phenylalanine, CH deformations Lipids, proteins (CH2 deformation) Lipids C C stretching

Fig. 4. Comparison of pure DNA to a difference spectrum of BCC and epidermis. (a) Raman spectrum of BCC. (b) Raman spectrum of epidermis. (c) To enhance the differences between the two spectra (a,b), difference spectra (a,b) were calculated. For clarity of presentation the difference spectrum was magnified by a factor of 2.0. (d) DNA-Raman spectrum. Prominent and characteristic DNA-Raman bands are present in the difference spectrum BCC-DNA (c) (reproduced with permission from reference 10).

214

Fig. 5. (a) Intra-sample variability. PCA scores plot that discriminates between the FT-IR spectra of benign nevus (nevus regions (1–3), adjacent skin (4)) within 1661 points after being recalculated without outliers. (b) Inter-sample variability. PCA scores plot that discriminates between the FT-IR spectra of two variants of benign (intradermal) nevi (1–2) within 1661 points after identification of atypical spectra (reproduced with permission from reference 35).

The qualitative interpretation of spectra relies upon a visual assessment of oftensubtle changes in such variables as peak position, peak height, bandwidth and relative changes in these parameters. This is a method, which is highly subjective and depends upon the skill of the spectroscopist. More objective, statistically based methods for spectral interpretation are desirable. Because of the complexity of IR and Raman spectra of complicated samples such as skin tissue, many of the recent successes of IR and Raman spectroscopy in the medical fields have relied on the application of multivariate analysis methodologies to be able to differentiate disease states from normal against a huge background of inter- and intrasubject spectral variability (Figs. 5a–b) [8–11,14,34–35]. Given the size of some of these data sets, which are often larger than 100 MB, it is not surprising that much work is being focused on developing processing methodologies to extract relevant information and reduce the size and complexity of the data to a more manageable and information-rich set [29,57]. Multivariate pattern recognition techniques, such as LDA (a linear discriminant analysis), can be trained to determine intrinsic patterns, or fingerprints, in a large number of variables that characterise particular groups of spectra. Spectra

215

of unknown origin can then be analysed to assess the pattern present in the unknown spectrum and a classification of tissue types made based upon this analysis. This method of analysis results in very high classification accuracy of the different spectra. Partitioning together those spectra that share common features into a small number of groups or classes is one means by which large amounts of data can be reduced to a more meaningful and interpretable set. Two such classification methodologies are supervised classification (such as LDA), where the data are partitioned according to their similarity to predefined training sets, and unsupervised classification (such as cluster analysis), where the data are partitioned based solely on some measure of its variance without any a priori information being used (Figs. 6a–b). Recently, multivariate data evaluation approaches to pattern recognition like principal component analysis (PCA), factor analysis (FA), soft independent modelling of class analogies (SIMCA), or artificial neural networks (ANN) analysis have been applied to detect typical spectral signatures and to increase reliability of diagnosis (Figs. 6a–b, 7a–b, 8a–b) [9,14,35,60,61]. Future application of in vivo IR and Raman spectroscopy for clinical diagnosis demands dedicated software that can perform the necessary multivariate signal processing and subsequent multivariate data analysis, enabling clinically relevant parameters from the measured spectra to be extracted and made available in real time [29,58]. Bakker Schut et al. [57] have developed a customised software package for on-line data analysis in their in vivo Raman setup. The model structure contains an option to differentiate and scale the model data, after calibration and sensitivity correction and before multivariate statistical analysis. At present, two different multivariate statistical models can be implemented: classification models, using principal component analysis (PCA) followed by LDA, to assign a newly measured spectrum to one of the groups defined in the model; and least-squares fitting models to obtain quantitative information about the chemical constituents that contribute to a newly measured spectrum (Fig. 9). This work shows the feasibility of developing in vivo Raman spectroscopic methods for real-time clinical applications, including signal collection, data analysis and presentation of clinically relevant parameters within seconds. This also permits applications in which larger areas need to be investigated, as many locations can be examined within a limited amount of time [57]. Conclusions The majority of examined spectra of benign, premalignant and malignant skin lesions present alterations in the spectral regions related to the phosphate backbone and phospholipids, lipids and proteins. In particular, good correlation between histology and the pseudo-colour maps of Raman spectra demonstrated the ability of Raman microspectroscopy to distinguish BCC from its

216

Fig. 6. (a) A 2D scatter plot of the diagnostically significant principal component weights derived from larynx spectra acquired at 830 nm. (b) A 2D scatter plot of linear discriminant function weights calculated to maximise the separation between pathology groups. The functions were calculated from the first 20 principal components (describing 98% of the total variance in the spectra from the mean) (reproduced with permission from reference 69).

217

Fig. 7. Plot of the two largest principal components of the 1661-point (a) and 500-point (b) spectra of MMs and SCCs. Each spectrum is represented as a point in the principal component map: (a) not clearly identifying; (b) identifying two variants of SCC and one of MM (reproduced with permission from reference 35).

surrounding tissue in individual tissue sections by showing accumulation of lipids and nucleic acids in tumour cells, and a lower collagen content when compared to surrounding epidermis or dermis [9]. Although alterations of protein structures are not indications of malignancy, by NIR FT Raman spectroscopy, the alterations of a-helix structure by an overall loss in total intensity for amide I, amide II and amide III regions in the BCC samples were described [42]. Similarly, spectra of MM were distinguished from pigmented nevi, BCC, SK and normal skin due to the decrease in the intensity of the amide I protein band around 1660 cm1 [9]. By IR microspectroscopy a direct correlation between spectra and histology could be made, showing more lipid-like material, distinct differences in the shape and position of the nucleic acid absorptions in benign, premalignant and malignant skin lesions [11,34,35,61]. NIR-FT Raman spectroscopy also showed significant differences in the region from 800 to 1000 cm1 due to single bond stretching vibrations, as reported for the amino acids proline and valine, showing again a marked loss of intensity.

218 (a)

(b)

Fig. 8. (a) Structure of the feedforward neural network used for classification, with only five inputs shown (xj) The inputs and a bias 1 are multiplied by the input weights (vij) and summed at the hidden units (hi). A transfer function mimicking the firing threshold of a biological neuron is applied and the results (and a bias) are multiplied by the output weights (wj) and summed at the output yi. A negative output is interpreted as 1 (control skin) and a positive as +1 (BCC) (reproduced with permission from reference 14); (b) The sensitivity map of neural network weghting of spectral frequencies, used for MM classification. The dotted line indicates the 99% confidence interval. Spectral bands marked (A), (B), (D) correspond to the description from Fig. 3 showing differences detected on visual classification of the spectra. (E) CH3 stretching vibrations in proteins and lipids (around 2940 cm1); (F) vibration caused by skin fluorescence (2000–2350 cm1); (G) ring vibrations in amino acids (around 1000 cm1) (reproduced with permission from reference 9).

219

Fig. 9. Design of a Grams/Matlab software environment for real-time data analysis application. Single outlined boxes, software functions; double outlined boxes, data structures; solid single arrow lines, internal data stream; dotted single arrow lines, DDE (dynamic data exchange) data transfer; solid double arrow lines, file transfer; solid arrow heads, spectral data transfer; open arrow heads, non-spectral data transfer (reproduced with permission from reference 57).

220 Changes of lipid structure in the 1420–1450 cm1 region and around 1300 cm1 were observed in BCC by NIR-FT Raman spectroscopy [14]. Similar spectral patterns, reflecting protein and lipid alterations, have been seen in FT-Raman spectra from MM samples [9]. Some molecular alterations could be easily explained by known biochemical changes in the tumours. For example, an increased intensity of the band around 1000 cm1 from the phenyl ring in seborrheic keratosis, keratoacanthoma, actinic keratosis, SCC or BCC are probably due to hyperkeratosis, hence phenyl ring structure is abundant in the keratin molecule. In seborrheic keratoses that contain particularly high amounts of lipids, an increase in the ns(CH2) peak and prominent twisting and wagging vibrations of CH2 were also an expected finding. A similar pattern of lipid changes was detected in keratoacanthoma, which indicated that the concentration of unsaturated lipids was increased also in this lesion. However, the alterations in NIR-FT Raman spectra are likely to reflect subtle variations in the behaviour of protein and lipid molecules, rather than gross changes in biochemical tissue composition [42]. Gniadecka et al. noticed clear spectral similarities between histogenetically related lesions such as actinic keratosis and SCC [42]. There were obvious similarities in the pattern of protein-specific vibrations: the amide I was shifted and the amide III peak had decreased intensity; the nas(CH2) and s(CH2)(CH3) peaks were widened; the intensities of n(C–C) vibrations were decreased [42]. In conclusion, since IR and Raman spectra obtained from benign, premalignant and malignant skin lesions showed similar alterations in the regions responsible for proteins, lipids and nucleic acids, it is therefore most probable that malignant transformation triggers similar molecular changes independently of the tissue involved [9]. At the same time, it was possible not only to identify the presence of a skin neoplasm, but also to differentiate different types of skin tumours [11,35].

Future aspects ‘‘Vibrational Spectroscopy for the Molecular Characterisation and Diagnosis of Skin Cancers’’, as a technique to be used and accepted by the dermatological community is still in its early stages. Although we reviewed and updated the literature on the subject, much more needs to be done to further develop vibrational spectroscopy in such a way as to give the dermatologist a fast and trustworthy technique. Development of Raman spectroscopy in vivo should ease tracking skin malignancy in clinical practice and further detection of alterations in protein and lipid structure may add to the understanding of carcinogenic processes [9]. Vibrational spectroscopy methods are non-destructive and non-invasive, and can be automated. The measurements are fast, and the instruments are fairly inexpensive. It seems to be ideally suited for screening procedures.

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At present, the approach to record spectra in vivo is still in its first stage, and awaits further development. Moreover, in spite of a possibility to differentiate spectra between cancerous and normal tissues, the assignment of features in the cancerous spectra remains tentative. In general, much more research is needed. We urge patience and a quest for understanding not only of the morphology and biology of the sample, but also their spectra that are waiting to be interpreted and understood at the cellular level. Acknowledgement NSE would like to express her gratitude to Dr. M.A. Foote of Amgen Inc. at Thousand Oaks in USA for her encouragement in the preparation of the chapter. She also indebted to Prof. J.P. Barron of the International Medical Communication Center of Tokyo Medical University, Japan, for his support and review of the manuscript. She also wants to thank all those who helped during the studies that contributed to the composition of this chapter: technical help by Mrs. Takeshi and Mr. Fujimoto, all dermatologists in training for their support with skin tissue samples at the Department of Dermatology; Dr. Umehara, at the Department of Orthopaedic Surgery; Prof. Yoshizaki and Dr. Ikehara at the Department of Physiology, Tokushima University School of Medicine, Japan; Dr. Huehne and all staff at the Kwansei-Gakuin University School of Science and Technology; all members at the Department of Physiology, Tokyo Medical University, Japan. Furthermore, she offers her thanks to her family members for their support while composing the chapter. References 1. Sokolov K, Aaron J, Hsu B, Nida D, Gillenwater A, Follen M, MacAulay C, Adler-Storthz K, Korgel B, Descour M, Pasqualini R, Arap W, Lam W and Richards-Kortum R. Optical systems for in vivo molecular imaging of cancer. Technol in Cancer Res & Treat 2003;2(6):491–504. 2. Marks R. An overview of skin cancers: Incidence and causation. Cancer 1995;75:607–612. 3. Jacobsen ADT. Raman spectroscopy of human skin. Dissertation, University of Odense, 1977. 4. Bronchud MH, Foote MA, Giaccone G, Olopade O, and Workman P. Principles of Molecular Oncology, 2nd edn. New Jersey, Humana Press Inc., 2004. 5. McIntosh LM, Jackson M, Mantsch HH, Mansfield JR, Crowson AN and Toole JWP. Nearinfrared spectroscopy for dermatological applications. Vibratl Spectrosc 2002;28:53–58. 6. Jones C, Du MQ and Lakhani S. Molecular and pathological characterization of human tumors. In: Principles of Molecular Oncology, 2nd edn, Ch. 6. Foote MA, Giaccone G, Olopade O, Workman P, Totowa NJ and Bronchud MH (eds), Humana Press Inc, 2004, pp. 215–232. 7. Dukor RK. Vibrational spectroscopy in the detection of cancer. In: Handbook of Vibrational Spectroscopy. Chalmers J and Griffiths PR (eds), John Wiley and Sons Ltd. Vol. 5, Application in Life, Pharmaceutical and Nature Sciences, 2002, pp. 3335–3361. 8. McIntosh LM, Summers R, Jackson M, Mantsch H, Mansfield JR, Howlett M, Crowson AN and Toole JWP. Towards non-invasive screening of skin lesions by near-infrared spectroscopy. J Invest Dermatol 2001;116:175–181.

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