Reference genes for quantitative reverse transcription-PCR (qRT-PCR) studies must be validated for the cell type studied and should be stable between the groups that represent the independent variable in an experimental design. We sought to identify the reference genes in cervical cell specimens showing the most stable expression between human papillomavirus (HPV)-infected and -uninfected women without high-grade cervical intraepithelial neoplasia. Using endocervical cells collected by cytology brush and Sybr green-based qRT-PCR, eight candidate genes were screened for amplification efficiency, specificity, and overall stability (by use of geNorm software). The five most stable genes were then further evaluated both for overall stability (geNorm) and intergroup stability (by use of NormFinder software) in specimens from HPV-negative and HPV-positive women. The combination of the glyceraldehyde-3-phosphate dehydrogenase gene (GAPDH) and RPLP0 was the most stable overall, with a geNorm stability measure of 0.603. The intergroup analysis showed GAPDH to be the most stable single gene and RPLP0 to be second most stable and also showed that these genes represent the most stable two-gene combination, with a NormFinder stability value of 0.130. The fact that these two distinct approaches identified the same pair of genes provides added confidence that, when the focus is on HPV infection, a normalization factor derived from these two genes is likely to be appropriate.An ideal universal reference gene for quantitative reverse transcription-PCR (qRT-PCR) studies would be stably expressed across tissue and cell types and independent of disease state, therapeutic intervention, physiologic covariates, or ex vivo manipulation; unfortunately, such a gene has never been identified and may not exist. Because of exponential amplification, validation of the expression stability of a candidate reference gene carries the same requirement for an independently stable reference against which to normalize input differences as does quantitation of a gene of interest (GOI). Recently, several algorithms have been developed to circumvent this problem (1,8,14,18). The approach of Vandesompele et al. starts with the proposition that the expression ratio of two suitable reference genes should be constant across samples to be studied and thus uses a pairwise evaluation strategy to identify the most stable genes from a pool of candidates (18). In contrast, that of Andersen et al. addresses directly the requirement for stable expression of the reference between the groups that represent the independent variable in an experimental design (e.g., pre-and posttreatment or infected versus uninfected) (1). Both algorithms can be automated using Microsoft Excel-based applications available from the respective authors.One area where studies of gene expression have been gaining momentum is in the investigation of diseases of the female genital tract. When the focus of such work is on the cervical mucosa, as in studies of cervical neoplasia or sexually tra...