Expression of mdr-1 in refractory lymphoma: quantitation by polymerase chain reaction and validation of the assay [published erratum appears in Blood 1995 Dec 15;86(12):4710]

Abstract

Measurement of P-glycoprotein and the gene that encodes it, mdr-1, is an important tool for assessing the impact of multidrug resistance in clinical cancer. We evaluated mdr-1 expression by a quantitative polymerase chain reaction (PCR) assay in 78 biopsy samples from 48 patients with refractory lymphoma enrolled on a trial of infusional chemotherapy (EPOCH) in which R-verapamil was added as an antagonist of P-glycoprotein in a subset of patients whose tumors were unresponsive to treatment. Expression of mdr-1 was detectable in all biopsies at the time of enrollment on study, and a fourfold or greater increase in mdr- 1 expression was noted in 42% of patients at the time of treatment failure. Expression of mdr-1 was also detectable in biopsies from patients at the time of diagnosis of lymphoma. An endogenous control gene, beta 2-microglobulin, was quantitated for normalization of the mdr-1 values. The use of beta 2-microglobulin expression for normalization was validated in a subset of samples by comparing Northern blots detecting beta 2-microglobulin, beta actin, and GAPDH gene expression. Immunoblot analysis suggested that no major discrepancy was present between mRNA expression and protein level. Immunophenotyping of lymphomatous lymph nodes showed that infiltration of tumor cells ranged from 8% to 95% and of normal T cells from 1% to 83%. Expression of mdr-1 in normal T cells and monocytes was also shown to be low. The mdr-1 levels in patient samples were independent of T- cell contamination, suggesting that the presence of normal cells has at best a small impact on mdr-1 measurements. Expression of mdr-1 in lymphoma can be quantitated by PCR, and wide variations in expression can be observed. Increased expression in patients with refractory disease supports an important role for Pgp in drug resistance in lymphoma. These studies will aid in the design and interpretation of clinical trials in lymphoma.