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Identifica??o e rastreamento de c?ncer atrav?s da combina??o de an?lise multivariada e t?cnicas bioespectrosc?picas

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Previous issue date: 2017-08-09 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Esta tese relata a aplica??o das espectroscopias no infravermelho m?dio, de fluoresc?ncia molecular e espectrometria de massas, combinadas a t?cnicas de an?lise multivariada, para classifica??o de c?lulas cancerosas em cultivo e de les?es pr?-cancerosas atrav?s de plasma sangu?neo. Em um primeiro estudo, matrizes de excita??o/emiss?o de fluoresc?ncia molecular foram obtidas para diferentes linhagens de c?lulas normais (3T3, ARPE, HEK) e cancerosas (HepG2, HeLa, HT-29, 786-0) e modelos de classifica??o foram constru?dos utilizando uma combina??o dos algoritmos OPLS e UPLS-DA. Taxas de acerto de 100% e 75% foram obtidas para as classes Normal e Cancerosa, respectivamente. Ainda, foi avaliada a influ?ncia dos anticorpos anti-MMP-2 e anti-MMP-9 no desempenho dos modelos de classifica??o. Na presen?a dos anticorpos, as taxas de acerto nas classifica??es aumentaram consideravelmente atingindo 100% para ambas as classes, Normal e Cancerosa, atrav?s dos algoritmos OPLS/UPLS-DA. Em um segundo estudo, a espectroscopia ATR-FTIR foi utilizada para obten??o de espectros de plasmas sangu?neos de mulheres saud?veis (negativas para les?o intraepitelial ou malignidade, NILM) e portadoras de les?o intraepitelial cervical (SIL) de baixo (LSIL) ou alto grau (HSIL), causadas pelo v?rus HPV. Modelos multivariados de classifica??o foram constru?dos, visando uma metodologia de rastreamento para o c?ncer cervical. Os algoritmos PCA-LDA/QDA, SPA-LDA/QDA e GA-LDA/QDA foram aplicados como ferramentas de classifica??o e seus desempenhos comparados. De maneira geral, os resultados obtidos atrav?s do algoritmo GA-QDA foram os mais satisfat?rios, utilizando apenas vari?veis espectrais selecionadas que puderam ser relacionadas a grupos funcionais pertencentes a diferentes biomol?culas. Os modelos GA-QDA classificaram corretamente NILM vs. SIL com sensibilidade e especificidade em torno de 90% e 83%, respectivamente. NILM vs. LSIL apresentaram sensibilidade e especificidade variando entre 67-94% e 82-94%, respectivamente. Para NILM vs. HSIL, os valores de sensibilidade e especificidade estiveram entre 76-97% e 73-100%, respectivamente. Em um terceiro estudo, a espectrometria de massas foi aplicada para obter os espectros de lip?dios extra?dos do plasma sangu?neo de mulheres da Classe NILM (n=42) e SIL (n=34). Modelos de classifica??o multivariados foram constru?dos utilizando os classificadores LDA, QDA e SVM. Os modelos baseados em SVM permitiram a discrimina??o das classes com sensibilidade e especificidade de 83.3% e 80.0% para NILM e SIL, respectivamente. Alguns poss?veis lip?dios foram associados a cada classe, tais como prostaglandinas, esfingolip?dios e fosfolip?dios, Tetranor-PGFM e um lip?dio hidroxiperoxidado. Os resultados obtidos em todos os estudos evidenciam a potencialidade das t?cnicas espectrosc?picas e multivariadas como poss?veis metodologias de rastreamento e identifica??o de c?ncer, o que poderia contribuir fortemente para a redu??o da morbidade e mortalidade causadas pela doen?a. / This thesis reports the application of both infrared and molecular fluorescence spectroscopy, as well as mass spectrometry, combined with multivariate analysis techniques for classification of cancerous cells in culture medium and precancerous lesions in blood plasma. In a first study, excitation/emission matrices of molecular fluorescence were obtained for normal (3T3, ARPE, HEK) and cancerous (HepG2, HeLa, HT-29, 786-0) cell lines and classification models were built by using a combination of the algorithms OPLS and UPLS-DA. Correct classification indexes of 100% and 75% were obtained for both classes, Normal and Cancer, respectively. In addition, it was evaluated the influence of the antibodies anti-MMP-2 and anti-MMP-9 in the performance of the classification models. In the presence of the antibodies, the correct classification indexes were considerably improved reaching 100% for both classes, Normal and Cancer, using the algorithms OPLS/UPLS-DA. In a second study, the ATR-FTIR spectroscopy was applied to obtain the spectra of blood plasma of both healthy women (negative for intraepithelial lesion or malignancy, NILM) and women with cervical intraepithelial lesion (SIL) of low grade (LSIL) or high grade (HSIL), caused by HPV virus. Multivariate classification models were built, aiming a screening methodology for cervical cancer. The algorithms PCA-LDA/QDA, SPA-LDA/QDA and GA-LDA/QDA were applied as classification tools and their performance was evaluated. In general, the results obtained by GA-QDA were the most satisfactory, by using only chosen spectral variables that could be related to chemical groups of different biomolecules. The models GA-QDA correctly classified NILM vs. SIL with sensitivity and specificity around 67-94% e 82-94%, respectively. For NILM vs. LSIL, sensitivity and specificity values were about 67-94% e 82-94%, respectively. For NILM vs. HSIL, the sensitivity and specificity values were 76-97% e 73-100%, respectively. In the third study, mass spectrometry was applied to obtain the spectra of lipids extracted from blood plasma of women of NILM (n=42) and SIL (n=34) classes. Multivariate classification models were built by using the classifiers LDA, QDA and SVM. SVM-based models allowed to discriminate the classes with sensitivity and specificity values of 83.3% and 80.0% for NILM and SIL, respectively. Some possible lipids were associated to each class, such as prostaglandins, phospholipids, sphingolipids, Tetranor-PGFM and a hydroperoxide lipid. The results achieved in all studies highlight the potentiality of the spectroscopic and multivariate techniques as possible methodologies for cancer screening, what could effectively contribute to reduce morbidity and mortality caused by cancer.

Identiferoai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/24129
Date09 August 2017
CreatorsMenezes, Ana Carolina de Oliveira Neves
Contributors03144855464, Ara?jo, Aurigena Antunes de, 83806059420, Cavalcanti, Livia Nunes, 03977264494, Ara?jo, M?rio C?sar Ugulino de, 16075056491, Poppi, Ronei Jesus, 10260438839, Lima, Kassio Michell Gomes de
PublisherPROGRAMA DE P?S-GRADUA??O EM QU?MICA, UFRN, Brasil
Source SetsIBICT Brazilian ETDs
LanguagePortuguese
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/doctoralThesis
Sourcereponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN
Rightsinfo:eu-repo/semantics/openAccess

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