Initiation, progression, and metastasis of cancer are due to genetic alterations. The major challenges of cancer research include the identification of genes involved in metastasis and the evaluation of emerging candidate genes for a potential clinical significance. Renal cancer with its unpredictable metastatic behavior is particularly challenging. The combination of several new molecular technologies, including comparative genomic hybridization, fluorescence in situ hybridization, and cDNA and tissue microarrays have advanced our understanding of renal cancer. However, one usually obtains a limited view of the dynamic process of renal tumor development in a particular cancer patient because renal cell carcinoma is characterized by an accumulation of complex molecular alterations during tumor progression. Some early chromosomal alterations in the carcinogenesis of renal tumors are known, but the nature of subsequent events, their interrelationships, and sequence is poorly understood. To analyze and model cancer development processes, including the presence of multiple pathways, a mathematical method for comparative genomic hybridization data was developed to search for tree models of the oncogenesis process. Tree modeling of comparative genomic hybridization data has provided new information on the interrelationships of genetic changes in renal cancer, their possible order, and a clustering of these events. This review concentrates on the application of comparative genomic hybridization in the area of renal cancer research