Clear cell renal cell carcinoma (ccRCC), the most common subtype of RCC, is characterized by high metastasis potential and strong resistance to traditional therapies, resulting in a poor five-year survival rate of patients. Several therapies targeted to VEGF pathway for advanced RCC have been developed, however, it still needs to discover new therapeutic targets for treating RCC. Genome-wide gene expression analyses have been broadly used to identify unknown molecular mechanisms of cancer progression. Recently, we applied the oligo-capping method to construct the full-length cDNA libraries of ccRCC and adjacent normal kidney, and analyzed the gene expression profiles by high-throughput sequencing. This paper presents a review for recent findings on therapeutic potential of MYC pathway and nicotinamide N-methyltransferase for the treatment of RCC. 1. Introduction Renal cell carcinoma (RCC) represents 3% of all human malignancies worldwide with an increasing incidence and accounts for 85% of renal cancers, resulting in close to 78,000 deaths annually [1–5]. The most common subtype, clear cell RCC (ccRCC), which originates from the proximal tubule epithelium, is mostly sporadic, unilateral, and unifocal [6]. RCC cells have a poor response to traditional therapies, such as the chemotherapy, hormonal therapy, and radiation therapy [7–10]. These properties result in a poor prognosis and low five-year survival rate of RCC patients. Surgery remains to be the main therapeutics for treatment of RCC [11]. It has been demonstrated that the activation of hypoxia-inducible factor-α (HIF-α) turns on the genes, such as VEGF and PDGF, which are responsible for the progression of ccRCC, providing potential targets for advanced ccRCC [12]. Gene expression analysis appears to be an important tool for studying cancer pathogenesis and progression. Markers related to tumor proliferation, growth, angiogenesis, and loss of cell adhesion have been evaluated for their potential as prognostic factors. Numerous reports have investigated the differential gene expression profile between normal and tumor tissues using the high-throughput technologies, including cDNA microarray, cDNA subtraction, and serial analysis of gene expression [13–15]. Many studies have applied these methods to analyze the genome-wide changes in ccRCC, providing specific gene expression signature, the potential biomarkers, and prognostic factors [16–21], whereas Lenburg et al. pointed out a diverse gene expression results by microarray method published previously [22]. Recently, two international projects, The
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