Involvement of microRNA modifications in anticancer effects of major polyphenols from green tea, coffee, wine, and curry.
Tomokazu OhishiSumio HayakawaNoriyuki MiyoshiPublished in: Critical reviews in food science and nutrition (2022)
Epidemiological studies have shown that consumption of green tea, coffee, wine, and curry may contribute to a reduced risk of various cancers. However, there are some cancer site-specific differences in their effects; for example, the consumption of tea or wine may reduce bladder cancer risk, whereas coffee consumption may increase the risk. Animal and cell-based experiments have been used to elucidate the anticancer mechanisms of these compounds, with reactive oxygen species (ROS)-based mechanisms emerging as likely candidates. Chlorogenic acid (CGA), curcumin (CUR), epigallocatechin gallate (EGCG), and resveratrol (RSV) can act as antioxidants that activate AMP-activated protein kinase (AMPK) to downregulate ROS, and as prooxidants to generate ROS, leading to the downregulation of NF-κB. Polyphenols can modulate miRNA (miR) expression, with these dietary polyphenols shown to downregulate tumor-promoting miR-21. CUR, EGCG, and RSV can upregulate tumor-suppressing miR-16, 34a, 145, and 200c, but downregulate tumor-promoting miR-25a. CGA, EGCG, and RSV downregulate tumor-suppressing miR-20a, 93, and 106b. The effects of miRs may combine with ROS-mediated pathways, enhancing the anticancer effects of these polyphenols. More precise analysis is needed to determine how the different modulations of miRs by polyphenols relate to the cancer site-specific differences found in epidemiological studies related to the consumption of foods containing these polyphenols.
Keyphrases
- cell proliferation
- reactive oxygen species
- long non coding rna
- long noncoding rna
- protein kinase
- signaling pathway
- cell death
- dna damage
- poor prognosis
- papillary thyroid
- respiratory syncytial virus
- squamous cell carcinoma
- oxidative stress
- stem cells
- single cell
- squamous cell
- inflammatory response
- bone marrow
- data analysis