Molecular Portrait of Clear Cell Renal Cell Carcinoma: An Integrative Analysis of Gene Expression and Genomic Copy Number Profiling

Renal cell carcinoma (RCC) incidence accounts for about 3 to 10 cases per 100,000 individuals with a predilection for adult males over 60 year old (1.6:1 male/female ratio) (Chow, 2010; Nese, 2009). In Europe, about 60,000 individuals are affected by RCC every year, with a mortality rate of about 18,000 subjects and an incidence rate for all stages steadily rising over the last three decades. Although inherited forms occur in a number of familial cancer syndromes, as the well-known von Hippel-Lindau (VHL) syndrome, RCC is commonly sporadic (Cohen & McGovern, 2005; Kaelin, 2007) and, as recently highlighted by the National Cancer Institute (NCI), influenced by the interplay between exposure to environmental risk factors and genetic susceptibility of exposed individuals (Chow et al., 2010). Being poorly symptomatic in early phases, many cases become clinically detectable only when already advanced and, as such, therapy-resistant (Motzer, 2011). Based on histology, RCC can be classified into several subtypes, i.e., clear cell (80% of cases), papillary (10%), chromophobe (5%) and oncocytoma (5%), each one characterized by specific histopathological features, malignant potential and clinical outcome (Cohen & McGovern, 2005). Patient stratification is normally achieved using prognostic algorithms and nomograms based on multiple clinico-pathological factors such as TNM stage, Fuhrman nuclear grade, tumor size, performance status, necrosis and other hematological indices (Flanigan et al., 2011), although the most efficient predictors of survival and recurrence are based on nuclear grade alone (Nese et al., 2009). As recently reviewed by Brannon et al. (Brannon & Rathmell, 2010), a finer RCC subtype classification could be obtained exploiting the vast amount of