Breast cancer is the most common cancer in the female population. Among the different subtypes, the one called HER2 + which represents 15-20% of the total cases and is characterized by greater aggressiveness and an unfavorable prognosis compared to the other tumor subtypes. At the same time, it is also the only one for which there is currently a specific biological therapy (Trastuzumab). For these reasons, the accurate diagnosis of the HER2 + subtype is very important but at present it still has some limitations: i) subjective interpretation of the results provided by current diagnostic techniques; ii) long timescales necessary for obtaining the diagnosis by applying current techniques; iii) the inability to characterize the molecular characteristics of the lesions as a whole; iv) the lack of a test that allows to predict resistance or sensitivity to tumor-drug agents. Raman spectroscopy (RS) is a recently introduced technique in biomedical research whose potential could improve some aspects lacking in current diagnostic practice. The method integrates the principles of the optical microscope with those of vibrational spectroscopy in order to identify the presence of specific chemical bonds. This property is used to generate a spectrum that reflects the biochemical composition of the analyzed sample. The thesis project aims to develop an RS-based protocol for the analysis of surgical and biopsy tissue samples of breast cancer HER2 + and HER2- in order to evaluate the diagnostic potential of RS in this area. In addition, the secondary objective of the thesis project is to determine any biochemical differences between HER2 + and HER2-samples. For this purpose, 21 samples were studied (12 surgical tissues and 9 biopsies). For each sample, 3 consecutive histological sections were prepared; the first section was stained with hematoxylin-eosin, the second analyzed by immunohistochemistry to check for the presence of HER2 expression, the third section was placed on a steel slide, de-waxed and used for Raman measurements. For each sample, an average of 4 areas of the tissue were analyzed, indicated by the pathologist for the presence of the HER2 + or HER2- tumor, and for each area, an average of 25 spectra were obtained. The spectra have undergone a pre-processing in order to make them analyzable and comparable with each other. During the protocol optimization process, it emerged that the spectra obtained from the sample derive both from cell-rich tissue regions (called "cellular") and from fiber-rich portions of stromal tissue (called "fibrous"). In order to distinguish the spectra belonging to these categories, different criteria have been used such as: intensity of the characteristic peaks of the two categories; comparison with spectra derived from cultured cells; PCA, k-means clustering. Once the cellular and fibrous spectra were separated with the methods described, for each of the two categories the data were analyzed through multivariate analysis (PCA + linear discriminant analysis (LDA)) in order to automatically distinguish and classify the spectra in HER2 + and HER2- . In addition, a qualitative analysis of the spectra was carried out for each category in order to determine the spectral and biochemical differences between the two tumor subtypes. From the application of the protocol it emerged that the best method of classification of the HER2 + and HER2- samples is that which only considers the spectra of the cellular zones, classified according to the intensity of the characteristic peaks of the cells. By comparing the differences found in the analysis discrepancies emerged from biopsies and surgical tissues which do not allow the certain attribution of the biochemical differences detected to the HER2 + or HER2- phenotype.
Evaluating the potentialities of a label-free Raman spectroscopy approach for the assessment of HER2+ breast cancer. (Valutazione dell'efficacia di un protocollo basato sulla spettroscopia Raman label-free per la diagnosi del carcinoma mammario HER2+)
BALDASSARRA, DANIELE
2018/2019
Abstract
Breast cancer is the most common cancer in the female population. Among the different subtypes, the one called HER2 + which represents 15-20% of the total cases and is characterized by greater aggressiveness and an unfavorable prognosis compared to the other tumor subtypes. At the same time, it is also the only one for which there is currently a specific biological therapy (Trastuzumab). For these reasons, the accurate diagnosis of the HER2 + subtype is very important but at present it still has some limitations: i) subjective interpretation of the results provided by current diagnostic techniques; ii) long timescales necessary for obtaining the diagnosis by applying current techniques; iii) the inability to characterize the molecular characteristics of the lesions as a whole; iv) the lack of a test that allows to predict resistance or sensitivity to tumor-drug agents. Raman spectroscopy (RS) is a recently introduced technique in biomedical research whose potential could improve some aspects lacking in current diagnostic practice. The method integrates the principles of the optical microscope with those of vibrational spectroscopy in order to identify the presence of specific chemical bonds. This property is used to generate a spectrum that reflects the biochemical composition of the analyzed sample. The thesis project aims to develop an RS-based protocol for the analysis of surgical and biopsy tissue samples of breast cancer HER2 + and HER2- in order to evaluate the diagnostic potential of RS in this area. In addition, the secondary objective of the thesis project is to determine any biochemical differences between HER2 + and HER2-samples. For this purpose, 21 samples were studied (12 surgical tissues and 9 biopsies). For each sample, 3 consecutive histological sections were prepared; the first section was stained with hematoxylin-eosin, the second analyzed by immunohistochemistry to check for the presence of HER2 expression, the third section was placed on a steel slide, de-waxed and used for Raman measurements. For each sample, an average of 4 areas of the tissue were analyzed, indicated by the pathologist for the presence of the HER2 + or HER2- tumor, and for each area, an average of 25 spectra were obtained. The spectra have undergone a pre-processing in order to make them analyzable and comparable with each other. During the protocol optimization process, it emerged that the spectra obtained from the sample derive both from cell-rich tissue regions (called "cellular") and from fiber-rich portions of stromal tissue (called "fibrous"). In order to distinguish the spectra belonging to these categories, different criteria have been used such as: intensity of the characteristic peaks of the two categories; comparison with spectra derived from cultured cells; PCA, k-means clustering. Once the cellular and fibrous spectra were separated with the methods described, for each of the two categories the data were analyzed through multivariate analysis (PCA + linear discriminant analysis (LDA)) in order to automatically distinguish and classify the spectra in HER2 + and HER2- . In addition, a qualitative analysis of the spectra was carried out for each category in order to determine the spectral and biochemical differences between the two tumor subtypes. From the application of the protocol it emerged that the best method of classification of the HER2 + and HER2- samples is that which only considers the spectra of the cellular zones, classified according to the intensity of the characteristic peaks of the cells. By comparing the differences found in the analysis discrepancies emerged from biopsies and surgical tissues which do not allow the certain attribution of the biochemical differences detected to the HER2 + or HER2- phenotype.È consentito all'utente scaricare e condividere i documenti disponibili a testo pieno in UNITESI UNIPV nel rispetto della licenza Creative Commons del tipo CC BY NC ND.
Per maggiori informazioni e per verifiche sull'eventuale disponibilità del file scrivere a: unitesi@unipv.it.
https://hdl.handle.net/20.500.14239/24660