Comparison of Drug Transporter Levels in Normal Colon, Colon Cancer, and Caco-2 Cells: Impact on Drug Disposition and Discovery

Abstract

A critical step in early phase drug development is the determination of oral bioavailability. In part, the ability to predict whether a drug will be effectively transported across the gastrointestinal mucosa can be estimated from the physicochemical properties of the compound. Although advancements through rational drug design have more correctly predicted bioavailability, considerable variability remains to be explained. Transporter expression throughout the gastrointestinal tract may explain much of this variation. ATP-binding cassette (ABC) transporters were the first family of transporters identified to modify bioavailability. More recently, the solute carrier family has also been shown to alter the pharmacokinetic profile of drugs. Currently, the Caco-2 human colon carcinoma cell line is often used by the pharmaceutical industry to evaluate intestinal absorption of drugs; however, in vivo/in vitro permeabilities with carrier mediated drugs do not correlate well, suggesting that Caco-2 transporter expression varies from that of the small intestine. With this is mind, we integrated U133A GeneChip expression data from the NCBIs Gene Expression Omnibus (GEO) collection and then compared the expression pattern of Caco-2 cells to normal colon to determine if the Caco-2 cell line is a reliable model for colonic delivery. Furthermore, transporter expression of Caco-2 cells was compared to that of human colon tumors to assess whether this cell line could be useful to predict drug absorption for colon cancer. Our analysis shows that the expression pattern for Caco-2 cells closely resembles the gene expression profile of transporters within the normal colon, suggesting that this cell line may serve as an in vitro model of colonic drug adsorption. However, the molecular "fingerprint" of Caco-2 was distinctly different from tumor samples, indicating that the Caco-2 model would unlikely predict accurate drug absorption for colon cancer sites.