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The development of multidrug resistance (MDR) to chemotherapy remains a major challenge in the treatment of cancer. Resistance exists against every effective anticancer drug and can develop by multiple mechanisms. These mechanisms can act individually or synergistically, leading to MDR, in which the cell becomes resistant to a variety of structurally and mechanistically unrelated drugs in addition to the drug initially administered. Although extensive work has been done to characterize MDR mechanisms in vitro, the translation of this knowledge to the clinic has not been successful. Therefore, identifying genes and mechanisms critical to the development of MDR in vivo and establishing a reliable method for analyzing highly homologous genes from small amounts of tissue is fundamental to achieving any significant enhancement in our understanding of MDR mechanisms and could lead to treatments designed to circumvent it. In this study, we use a previously established database that allows the identification of lead compounds in the early stages of drug discovery that are not ATP-binding cassette (ABC) transporter substrates. We believe this can serve as a model for appraising the accuracy and sensitivity of current methods used to analyze the expression profiles of ABC transporters. We found two platforms to be superior methods for the analysis of expression profiles of highly homologous gene superfamilies. This study also led to an improved database by revealing previously unidentified substrates for ABCB1, ABCC1, and ABCG2, transporters that contribute to MDR.

Evaluation of current methods used to analyze the expression profiles of ATP-binding cassette transporters yields an improved drug-discovery database