Renal cell carcinoma accounts for about 85% of primary kidney tumors and its incidence worldwide is increasing rapidly. Although the diagnosis of RCC is routinely performed by means of multiple imaging techniques, benign solid renal masses sometimes cannot be confidently differentiated from malignant ones. Moreover, the TNM (Tumor-Node-Metastasis) classification system, the Fuhrman grading system and serum markers are still the main factors used to predict the outcome of patients. For these reasons, RCC still remains a significant clinical challenge not only in terms of early diagnosis but also clinical management. Moreover, since the main alterations in regulation processes caused by tumorigesis not only involve genes but also proteins, MS-based protein profiling is considered an effective approach both for the discovery of multiple biomarkers and for the detection of disease specific modifications. Therefore, this PhD project has been focused on the study and characterisation of the urinary peptidome and proteome of RCC patients, patients affected by other kidney neoplasms and control subjects in order to evaluate potential molecular signatures capable of characterising renal cancers. For this purpose, sistematic analysis at the peptidome level employing a protein profiling approach based on MALDI-TOF mass spectrometry analysis combined with pre-purification step of urine samples using functionalized magnetic beads, has been performed. This technique has allowed, on one hand, to build models of potential biomarkers able to discriminate not only ccRCC patients from controls, but also to significantly distinguish malignant renal masses from benign forms and, on the other hand, to highlight alterations of endogenous peptides according to clinical data (stage, grade, dimension). The identification of discriminant and/or tumor progression related signals has been obtained through a nLC-ESI MS/MS approach on urine pools of 80 healthy volunteers and 80 RCC patients. For the proteomic analysis, a tryptic digestion of urine samples using the FASP (Filter Aided Sample Preparation) protocol followed by shotgun analysis by nanoUHPLC-ESI MS/MS has been performed. The relative label-free quantification has facilitated the investigation of protein alterations in ccRCC subjects. The subsequent functional analysis has highlighted the bological processes and the molecular functions in which the varied proteins are involved. Moreover, in the study of a complex system such as the kidney, a systematic comparison between different –omic sciences (peptidomics/proteomics) could highlight functions, biological processes and molecular targets that are implicated in the deregulation caused by the presence of the tumor and for this reason an integration of the collected data has been performed in order to identify potential targets and biological effectors that could improve the understanding of the intricate and multifactorial mechanisms underlying kidney malignancies.

(2016). Ricerca di una firma molecolare tipizzante tumori renali mediante approccio proteomico di profiling in spettrometria di massa.. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2016).

Ricerca di una firma molecolare tipizzante tumori renali mediante approccio proteomico di profiling in spettrometria di massa.

CAZZANIGA, MARTA
2016

Abstract

Renal cell carcinoma accounts for about 85% of primary kidney tumors and its incidence worldwide is increasing rapidly. Although the diagnosis of RCC is routinely performed by means of multiple imaging techniques, benign solid renal masses sometimes cannot be confidently differentiated from malignant ones. Moreover, the TNM (Tumor-Node-Metastasis) classification system, the Fuhrman grading system and serum markers are still the main factors used to predict the outcome of patients. For these reasons, RCC still remains a significant clinical challenge not only in terms of early diagnosis but also clinical management. Moreover, since the main alterations in regulation processes caused by tumorigesis not only involve genes but also proteins, MS-based protein profiling is considered an effective approach both for the discovery of multiple biomarkers and for the detection of disease specific modifications. Therefore, this PhD project has been focused on the study and characterisation of the urinary peptidome and proteome of RCC patients, patients affected by other kidney neoplasms and control subjects in order to evaluate potential molecular signatures capable of characterising renal cancers. For this purpose, sistematic analysis at the peptidome level employing a protein profiling approach based on MALDI-TOF mass spectrometry analysis combined with pre-purification step of urine samples using functionalized magnetic beads, has been performed. This technique has allowed, on one hand, to build models of potential biomarkers able to discriminate not only ccRCC patients from controls, but also to significantly distinguish malignant renal masses from benign forms and, on the other hand, to highlight alterations of endogenous peptides according to clinical data (stage, grade, dimension). The identification of discriminant and/or tumor progression related signals has been obtained through a nLC-ESI MS/MS approach on urine pools of 80 healthy volunteers and 80 RCC patients. For the proteomic analysis, a tryptic digestion of urine samples using the FASP (Filter Aided Sample Preparation) protocol followed by shotgun analysis by nanoUHPLC-ESI MS/MS has been performed. The relative label-free quantification has facilitated the investigation of protein alterations in ccRCC subjects. The subsequent functional analysis has highlighted the bological processes and the molecular functions in which the varied proteins are involved. Moreover, in the study of a complex system such as the kidney, a systematic comparison between different –omic sciences (peptidomics/proteomics) could highlight functions, biological processes and molecular targets that are implicated in the deregulation caused by the presence of the tumor and for this reason an integration of the collected data has been performed in order to identify potential targets and biological effectors that could improve the understanding of the intricate and multifactorial mechanisms underlying kidney malignancies.
MAGNI, FULVIO
Proteomics, Urine, Renal Cell Carcinoma
BIO/10 - BIOCHIMICA
Italian
4-mar-2016
TECNOLOGIE BIOMEDICHE - 20R
28
2014/2015
open
(2016). Ricerca di una firma molecolare tipizzante tumori renali mediante approccio proteomico di profiling in spettrometria di massa.. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2016).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/104019
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