Quantitative methods of gene expression analysis in tumors require accurate data normalization, which allows comparison of different mRNA/cDNA samples with unknown concentration. For this purpose reference genes with stable expression level (such as GAPDH, ACTB, HPRT1, TBP) are used. The choice of appropriate reference genes is still actual because well-known reference genes are not suitable for certain cancer types frequently and their unreasonable use without additional tests lead to wrong conclusions. We have developed the bioinformatic approach and selected a new potential reference gene RPN1 for lung and kidney tumors. This gene is located at the long arm of chromosome 3. Our method includes mining of the dbEST and Oncomine databases and functional analysis of genes. The RPN1 was selected from 1500 candidate housekeeping genes. Using comparative genomic hybridization with NotI-microarrays we found no methylation, deletions and/or amplifications at the RPN1-containing locus in 56 non-small cell lung and 42 clear cell renal cancer samples. Using RT-qPCR we showed low variability of RPN1 mRNA level comparable to those of reference genes GAPDH and GUSB in lung and kidney cancer. The mRNA levels of two target genes coding hyalouronidases--HYAL1 and HYAL2--were estimated and normalized relative to pair RPN1--GAPDH genes for lung cancer and RPN1--GUSB for kidney cancer. These combinations were shown to be optimal for obtaining accurate and reproducible data. All obtained results allow us to suggest RPN1 as novel reference gene for quantitative data normalization in gene expression studies for lung and kidney cancers.