Fourier Transform Infrared spectroscopy for the assessment of skin cancer:a potential tool in cancer diagnostics

Abstract Skin cancer is the most common cancer, and its incidence is increasing each year. Its diagnosis is based on a histopathological inspection by pathologists. Other imaging techniques are currently being actively researched to assist pathologists in improving diagnostic accuracy. Fourier Transform Infrared (FTIR) spectroscopy is gaining in popularity among researchers due to its ability to provide spatially resolved biochemical and biological information while also being compatible with histopathological samples. Furthermore, facilitating FTIR spectroscopic data with various machine learning methodologies for automating classification has become a popular practice. These methodologies have achieved high accuracy in discriminating cancerous samples from healthy ones, but limited work has been done to determine the metastatic potential of cells and optimize the FTIR spectroscopy protocol for achieving the best classification result. This thesis reviewed all skin cancer studies that used FTIR spectroscopy as a potential diagnostic tool to assess its effectiveness in various aspects of skin cancer research and to analyse the performance of different methods used for differentiating diseased samples from healthy ones. In addition, a model was developed to examine whether different malignant melanoma cell lines (primary and metastatic) can be discriminated using the spectral data acquired from the samples. Furthermore, the effects of different modes (transmission and transflection) and sample processing methods (deparaffinized and paraffinized) on the acquired spectra were investigated, and the combination providing the best classification result was determined. According to the results of this thesis, FTIR spectroscopy can differentiate different types of skin cancers from healthy samples as well as between different skin cancers (melanoma and non-melanoma) and the most common non-melanoma cancers. Melanoma has received the most attention in skin cancer research due to its ability to metastasize nearby lymph nodes and other vital organs in a short period of time. FTIR spectroscopy has the potential to discriminate between different malignant melanoma cells and possibly characterize their metastatic potential by utilizing spectral features associated with them. Although good classification accuracy for discriminating different malignant melanoma cells can be achieved in both modes and sample types, spectral data acquired using the transflection mode from a paraffinized sample provides the best classification result.Tiivistelmä Ihosyövät ovat maailmanlaajuisesti yleisimpiä syöpiä, ja niiden ilmaantuvuus kasvaa joka vuosi. Ihosyöpien diagnoosi perustuu patologin tekemään histopatologiseen tutkimukseen. Kuvantamistekniikoita tutkitaan aktiivisesti, jotta ihosyöpien diagnostiikkaa voitaisiin parantaa. Infrapuna (IR)-spektroskopia on kasvattanut suosiota tutkijoiden keskuudessa, koska sillä voidaan tutkia kudosleikkeistä alueellisia eroja kudoksen koostumuksessa. Kudosten IR-spektrien luokittamisessa käytetään usein koneoppimiseen perustuvia automaattisia menetelmiä. Näillä menetelmillä on kyetty erottamaan tarkasti syöpäsolut terveistä soluista. Toisaalta syöpäsolujen metastasoimispotentiaalin määrittämiseksi IR-spektreistä on tehty vain vähän tutkimuksia, ja mittausprotokollia ei ole vielä optimoitu parhaimman luokitustuloksen saavuttamiseksi. Tässä väitöskirjatyössä tehtiin kirjallisuuskatsaus kaikista IR-spektroskopiaa hyödyntävistä ihosyöpätutkimuksista. Katsauksessa arvioitiin IR-spektroskopian soveltuvuutta ihosyöpätutkimuksen eri osa-alueilla ja analysoitiin eri mittaus- ja data-analyysimenetelmien kykyä erottaa sairaat ja terveet ihonäytteet toisistaan. Lisäksi tässä työssä kehitettiin malli, jolla pyrittiin luokittelemaan pahanlaatuisia melanoomasolulinjoja niiden IR-spektrien perusteella. Työssä tutkittiin myös eri mittausmoodien (transmissio ja transflektio) ja näytteenkäsittelymenetelmien (ei-parafinoitu ja parafinoitu) vaikutuksia mitattuihin IR-spektreihin ja määritettiin näiden yhdistelmä, jolla saadaan paras tulos melanoomasolujen luokittelemisessa. Väitöskirjan tulosten perusteella voidaan sanoa, että IR-spektroskopialla pystytään erottamaan eri ihosyövät terveestä ihokudoksesta ja tunnistamaan ihosyövän tyyppi. Melanooma on saanut eniten huomiota ihosyöpätutkimuksessa, koska se pystyy muodostamaan etäpesäkkeitä lähellä oleviin imusolmukkeisiin ja muihin elintärkeisiin elimiin lyhyessä ajassa. IR-spektroskopialla voidaan erottaa eri pahanlaatuiset melanoomasolulinjat toisistaan ja mahdollisesti arvioida melanoomasolujen metastasoimispotentiaalia IR-spektrien piirteiden perusteella. Melanoomasolujen luokittelutarkkuus oli hyvä molemmissa tutkituissa mittausmoodeissa ja näytetyypeissä, mutta paras luokitustulos saavutettiin, kun käytettiin parafinoituja näytteitä ja mittaukset tehtiin transflektiomoodissa

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy

Abstract Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma

Optimization of measurement mode and sample processing for FTIR microspectroscopy in skin cancer research

Abstract The use of Fourier Transform Infrared (FTIR) microspectroscopy to study cancerous cells and tissues has gained popularity due to its ability to provide spatially resolved information at the molecular level. Transmission and transflection are the commonly used measurement modes for FTIR microspectroscopy, and the tissue samples measured in these modes are often paraffinized or deparaffinized. Previous studies have shown that variability in the spectra acquired using different measurement modes and sample processing methods affect the result of the analysis. However, there is no protocol that standardizes the mode of measurement and sample processing method to achieve the best classification result. This study compares the spectra of primary (IPC-298) and metastatic (SK-MEL-30) melanoma cell lines acquired in both transmission and transflection modes using paraffinized and deparaffinized samples to determine the optimal combination for accurate classification. Significant differences were observed in the spectra of the same cell line measured in different modes and with or without deparaffinization. The PLS-DA model built for the classification of two cell lines showed high accuracy in each case, suggesting that both modes and sample processing alternatives are suitable for differentiating cultured cell samples using supervised multivariate analysis. The biochemical information contained in the cells capable of discriminating two melanoma cell lines is present regardless of mode or sample type used. However, the paraffinized samples measured in transflection mode provided the best classification

The use of Fourier Transform Infrared (FTIR) spectroscopy in skin cancer research:a systematic review

Abstract Skin cancers are one of the most frequently occurring diseases in humans that pose severe health issues. Fourier Transform Infrared (FTIR) spectroscopy in cancer research has gained considerable attention because of its ability to provide biochemical information in addition to being compatible with traditional histopathology. With this review, we aim to identify all skin cancer studies which have been conducted using FTIR spectroscopy and depict different methodologies that have been used to analyze FTIR spectroscopic data of skin cancers. We conducted the systematic review following PRISMA guidelines for which three databases, Scopus, PubMed and Web of Science, were searched from commencement to 16 January 2019. All the studies which used FTIR spectroscopy for skin cancer research were included in the review. A total of 35 studies were found eligible to be included in the review. Of these, 21 studies were based on melanoma, 6 studies on BCC, 2 studies on SCC, and 2 on lymphocytes. The remaining 4 studies aimed to differentiate between various skin cancer types. The potential of FTIR spectroscopy for many relevant aspects of skin cancer research has already been demonstrated, but more work is needed to establish FTIR spectroscopy as a routine method in the field