Genomic and transcriptomic data integration and its automated analysis in clear-cell renal cell carcinoma suggests population heterogeneity of causes and mechanism of the disease

Renal cell carcinoma (RCC) is one of the most widespread solid kidney tumors – it represents 90% of all malignant kidney tumors. Clear-cell RCC is the most widespread type of RCC. It is characterized by 3-rd chromosome rearrangements, VHL inactivation due to mutations or promoter hypermethylation, 5p amplification, and mutations in KDM6A/UTX, SETD2, KDM5C/JARID1C and MLL2 genes. Molecular profile of ccRCC was characterized in a number of research papers using high-throughput platforms (microarray SNP-profiling, RNA-seq, whole exome and whole genome sequencing). Nevertheless, differences of observed mutations and gene expression levels among different populations suggest that causes and mechanism of the disease can also vary. In order to obtain such information about Western Russian population we have performed DNA resequencing and microarray expression profiling, and then integrated this data in a single dataset. We then analyzed DNA mutations and gene expression level simultaneously using standard molecular data analysis pipelines (gene set enrichment analysis, casual gene network generation, principle component analysis). Gene expression was analyzed in tumor and normal kidney tissues of patients 50 to 75 years old using Affymetrix Human Gene 1.1 ST arrays.