Anti-spreading effects of olive oil phenolics (OVP) in colon cancer cells: evidence from MATLAB simulation and time-series approach
Globally, colon cancer is the third common cancer for both males and females. Recent studies showed that Mediterranean population has lower rate of colon cancer and this is believed to be due to high olive oil consumption. The special characteristic of olive oil, apart from its monounsaturated fatty...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/20454/ http://irep.iium.edu.my/20454/ http://irep.iium.edu.my/20454/1/Anti-spreading_effects_of_olive_oil_phenolics_%28OVP%29.pdf |
| Summary: | Globally, colon cancer is the third common cancer for both males and females. Recent studies showed that Mediterranean population has lower rate of colon cancer and this is believed to be due to high olive oil consumption. The special characteristic of olive oil, apart from its monounsaturated fatty acids (MUFA), is its phenolics content known as olive oil phenollics (OVP). Study on human adenocarcinoma cells (HT115) suggest that phenols from virgin olive oil are capable of inhibiting the invasion colon cancer cells with effects may be mediated at different levels of the invasion stage, particularly the cell spreading stage. Microarray data collected from Hashim (2006) has proven that OVP caused differential expression in genes associated with cell cycle, apoptosis, cytoskeleton, and motility (spreading/migration). However, the results from the cell culture work on migration was limited (OVP effect on cancer cell spreading was only studied at 24 h) leading to insufficiency of data to further investigate the possible regulation of cell spreading at gene level. Therefore, a simulation approach using MATLAB and time series method was used in this study to investigate a selection of genes ACTB, TUFM, PTMA, TGFBI, IGFBP5, ACP2, CLNS1A, HSPH1, RHOA, RHOC, CLTC and its potential pathways involved in the anti-spreading effects of OVP observed. It was found that the genes were involved in redundant regulatory network leading to the anti-spreading effects of OVP. This suggests that the combination of MATLAB simulation and time series method are valuable tools in pathway analysis particularly complementing the biological assay and gene expression data. The redundant regulatory network of genes observed in this study is important as they portray potential target genes for development of future therapeutic for colon cancer while also adding on the evidence that OVP may prevent and or inhibit cancer cell spreading through certain gene regulatory pathways. |
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