The work comprised in this PhD thesis described the development of a novel mathematical and statistical framework to analyse and combine, at genome-wide level, gene expression profile and DNA copy number data obtained by high-throughput oligonucleotide microarray platform. This dual strategy is now considered the most effective to understand the genetic causes underlying neoplastic diseases and identify interesting regions and genes with potential clinical application as novel tumor markers. In this thesis, we applied this combined approach to study the clear cell renal carcinoma (ccRCC) pathology, using firstly a human metastatic cell line as in vitro model and then a collection of clinical tumor tissue samples. Considering the physical position of genes along the genome, high-throughput gene expression data were used to assemble a regional transcriptional activity profile. In the meantime, a genome-wide DNA copy number map was assembled by high-throughput SNP mapping technology, thus identifying recurrent aberrations that might be novel candidate regions characterizing all or subsets of ccRCC samples. To filter the large amount of array-based data and narrow down the hundreds of candidate regions to those whose altered expression level was attributable to underlying chromosomal alterations, regional gene expression data were combined with DNA copy number alteration map at genome-wide level. After confirming a strong association between aneuploidy and regional transcriptional activity profiles, we identified a set of regions showing concomitant DNA alteration and modulated expression level and, within, particularly interesting genes as novel candidate RCC-related markers. Overall, this study demonstrates the efficacy of the combination of DNA and RNA profiles to improve the specificity of analysis and increase the possibility of identifying the genetic causes underlying ccRCC pathology, so highlighting candidate genes that are actively involved in the causation or mainteinance of the malignant phenotype.
|Titolo:||Association of genome-wide DNA copy number data and transcriptional profile in renal carcinoma|
|Supervisori e coordinatori interni:||VILLA, MARIA LUISA|
|Data di pubblicazione:||2006|
|Settore Scientifico Disciplinare:||Settore BIO/10 - Biochimica|
Settore MED/04 - Patologia Generale
|Citazione:||Association of genome-wide DNA copy number data and transcriptional profile in renal carcinoma ; Cristina Battaglia, Maria Luisa Villa. - Milano : Università degli studi di Milano. DIPARTIMENTO DI SCIENZE E TECNOLOGIE BIOMEDICHE, 2006. ((19. ciclo, Anno Accademico 2005/2006.|
|Appare nelle tipologie:||13 - Tesi di dottorato discussa entro ottobre 2010|