Abstract

Real-time quantitative reverse transcription polymerase chain reaction (RT-PCR) is a powerful method for measurement of gene expression for diagnostic and prognostic studies of non-Hodgkin's lymphomas (NHL). In order for this technique to gain wide applicability, it is critically important to establish a uniform method for normalization of RNA input. In this study, we have determined the best method to quantify the RNA/cDNA input per reaction and searched for the most useful endogenous control genes for normalization of the measurements, based on their abundance and lowest variability between different types of lymphoid cells. To accomplish these aims, we have analyzed the RNA expression of 11 potential endogenous control genes (glyceraldehyde-3-phosphate dehydrogenase, beta-actin, peptidylprolyl isomerase A, beta 2 microglobulin, protein kinase cGMP-dependent, type I, hypoxanthine phosphoribosyltransferase 1, TATA box binding protein, transferrin receptor, large ribosomal protein, beta-glucoronidase and 18S ribosomal RNA). In all, 12 different B- and T-cell lymphoma/leukemia cell lines, 80 B- and T-cell NHL specimens, and resting and activated normal B and T lymphocytes were screened. Normalization of the nucleic acid input by spectrophotometric OD(260) measurement of RNA proved more reliable than spectrophotometric or fluorometric measurements of cDNA or than electrophoretic estimation of the ribosomal and mRNA fractions. The protein kinase cGMP-dependent, type I (PRKG1) and the TBP genes were expressed at common abundance and exhibited the lowest variability among the cell specimens. We suggest that for further lymphoma studies based on the real-time RT-PCR quantification of gene expression, that RNA input in each reaction be equalized between the specimens by spectrophotometric OD(260) measurements. The expression of the gene of interest in different samples should be normalized by concomitant measurement of the PRKG1 and/or the TBP gene products.

View details for DOI 10.1038/sj.leu.2402880

View details for Web of Science ID 000182362200014

View details for PubMedID 12682639