An important limitation of prior biomarkers studies

An important limitation of prior biomarkers studies is that they included all stages of RCC (Takahashi et al., 2001; Sultmann et al., 2005; Kosari et al., 2005; Jones et al., 2005; Zhao et al., 2006; Cancer Genome Atlas Research N, 2013; Brannon et al., 2010), limiting their applicability to patients with metastatic disease. However, many of these studies used an unbiased, genome-wide approach to discovery of prognostic markers, and provided a wealth of candidate gene expression markers for us to evaluate. An increased understanding of pathways and mechanisms driving clear cell RCC provided additional candidate markers. In univariate analysis, we found that 21 of the candidate biomarkers were significant predictors of OS using q<0.05 (Table 2 and Supplemental Table 2). These results are validation of prior discovery studies of prognostic markers. Our multivariable analysis identified an 8-gene model of OS. Following VHL inactivation, PBRM1 is the second major gene in ccRCC, with truncating mutations in 41% of cases (Varela et al., 2011). Genes in pathways deregulated following PBRM1 knockdown in RCC cell lines were included as candidate genes in this study. In our final prognostic model, 4 genes (CRYL1, HSD17B10, CEP55 and HGF) were PBRM1 related genes; 3 (CRYL1, HSD17B10 and CEP55) were also differentially expressed when comparing ccRCC to normal kidney (Tun et al., 2010). HGF, which binds the proto-oncogene c-MET, has been linked to invasiveness and VHL inactivation in ccRCC (Horie et al., 1999; Koochekpour et al., 1999; Harshman and Choueiri, 2013). Both TRAF2 (Vasselli et al., 2003) and USP6NL (Zhao et al., 2006) were previously identified as prognostic genes is microarray-based studies of RCC. PCNA was included as a candidate gene because it is a classic marker of proliferation and has been previously associated with RCC prognosis (Nogueira and Kim, 2008). CDK1, a dpp-iv inhibitors regulator, was included as a candidate gene because it was previously reported to predict response to antiangiogenic and epidermal growth factor targeted therapy in RCC (Tsavachidou-Fenner et al., 2010). When generating our prognostic signature, genes were favored that provided independent and non-redundant prognostic information. Therefore, it is not surprising that our 8 genes have been associated with a wide range of functions important to cancer progression such as proliferation (CEP55, PCNA, CDK1), apoptosis (TRAF2), metabolism (CRYL1, HSD17B10) and invasion (HGF) (http://www.ncbi.nlm.nih.gov.eleen.top/gene, 2015). The genetic heterogeneity of RCC is well documented (Gerlinger et al., 2012, 2014). However, the clonal evolutionary tree has a common “trunk” that links all genomic mutations. In addition, there are common histologic features that pathologists use to classify renal tissue as RCC. Therefore, it is reasonable to expect that there are markers, particularly expression markers that directly reflect the phenotype of RCC. To generate a signature that was less sensitive to sampling artifacts produced by tumor heterogeneity, we performed a separate analysis using untreated primary tumors from metastatic clear cell RCC patients that were sampled in two different areas. Genes with heterogeneous expression within individual patients were excluded from consideration in our multimarker models.
Conclusion
Introduction Uveal melanoma (UM) is the most common primary cancer of the eye in adults, with a reported incidence of 5.1 per million (Singh et al., 2011). The majority of UM cases (97.8%) occur in the Caucasian population (Singh et al., 2011). Despite the common embryologic origin of cutaneous and uveal melanocytes, the clinical, epidemiologic, and molecular characteristics of UM differ from those of cutaneous melanoma (Collaborative Ocular Melanoma Study G, 2001; Singh et al., 2001; Ewens et al., 2014). Local treatment of primary UM has improved; conservative non-surgical treatments such as brachytherapy with radioisotopes result in eye preservation and control the growth of primary UM. However, this improvement in local treatment did not significantly increase the overall survival for UM patients (Singh et al., 2011). Systemic metastases develop in up to 50% of the cases of UM patients. UM disseminates hematogeneously, as there is no major lymphatic drainage from the eye. Metastatic disease leads to death in the majority of patients because of the lack of effective systemic treatments (Kujala et al., 2003). The metastatic UM cells have significant tropism to the liver, and the liver is the first organ of metastasis in approximately 80% to 95% of patients who develop systemic recurrence. Several histologic, genetic, and demographic factors have been associated with metastases in UM, including large tumor size in primary cancer of the eye, monosomy 3, and BAP1 mutation (Collaborative Ocular Melanoma Study G, 2001; Ewens et al., 2014). It has been reported that 80% of metastatic uveal melanoma have mutation in BAP1 (Harbour et al., 2010). Published clinical observations suggested that UM cell metastases in the liver grow faster than metastases in other organs (All-Ericsson et al., 2002; Yoshida et al., 2014; Chattopadhyay et al., 2014). The lung is the second most common site of metastasis. A small percentage of patients first develop osseous and brain metastasis (Lorigan et al., 1991; Rietschel et al., 2005). It has been reported that distant micrometastasis resulting from the dissemination of tumor cells through the blood stream developed even before primary UM was clinically diagnosed and treated (Eskelin et al., 2000). It is also reported that the recurrence for patients undergoing enucleation displays a bimodal pattern, peaking three years with a second surge peaking at about nine years (Demicheli et al., 2014).