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Berries and red fruits are important dietary sources of polyphenols [1]. In vitro and animal studies have demonstrated the bioavailability and the anti-proliferative and anticarcinogenic properties of these fruits or of their phenolic components [2,3]. Consumption of berries may contribute to the reduction of colon cancer by mechanisms not yet understood. Gene expression analysis using microarrays allows for a more comprehensive study of the possible molecular mechanisms by which food or food components may prevent certain cancers of the gastrointestinal tract [4]. The aim of this research is to investigate the anti-proliferative effects of a polyphenol-rich berry juice on a human model of colon cancer cells and its association to transcriptional changes in relation to colon cancer. MethodologyWe investigated the effects of a commercial chokeberry (Aronia melanocarpa) juice on the human model of colon cancer Caco-2 cells. In vitro digested (pepsin + pancreatin)[5] chokeberry juice was added to the cells in the culture medium at a nontoxic dose (final pH 7.5 and osmolarity 325 miliosmoles L-1 in the culture medium) 2 h a day for a 4-day period. The concentration of phenolics in the medium at time 0 of the incubation period was *80 lM. Control cells were treated with an equivalent mix of enzymes and salts. Cells were counted using a hemacytometer and viability measured using Trypan blue dye exclusion. Results of proliferation and viability for both control and chokeberry treated Caco-2 cells are expressed as percentage of those values obtained for untreated cells. Gene expression changes were measured using microarrays (HG_U133A_2.0 human chips, Affymetrix). Transcripts that were 1.6-fold induced or repressed were selected. The changes in mRNA levels of several selected genes were further confirmed by RT-PCR. Results and conclusionsExposure of Caco-2 cells to pre-digested chokeberry juice resulted in inhibition of both cell proliferation (30-40%) and viability (*20%) in comparison to untreated cells. A very low proportion of genes (0.44% of total transcripts represented in the chip) were found to change in response to the treatment and most changes were in the range 1.6-2.0-fold. Resulting altered genes were categorized into several functional groups based on gene ontology search (Fatigo, GEPAS 1.

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