Abstract
The Mediterranean diet (MD) has been reported to have beneficial effects on breast cancer and cardiovascular diseases. Recently, microRNAs (miRNAs) have been suggested as biomarkers for the diagnosis and disease prognosis in cancer and cardiovascular diseases. We evaluated the influence of the MD on the plasma-derived extracellular vesicle miRNA signature of overweight breast cancer survivors. Sixteen participants instructed to adhere to the MD for eight weeks were included in this study. To curate differentially expressed miRNAs after MD intervention, we employed two methods: significance analysis of microarrays and DESeq2. The selected miRNAs were analyzed using ingenuity pathway analysis. After an eight-week intervention, body mass index, waist circumference, fasting glucose, fasting insulin, and homeostatic model assessment for insulin resistance were significantly improved. Expression levels of 798 miRNAs were comprehensively analyzed, and 42 extracellular vesicle miRNAs were significantly differentially regulated after the eight-week MD (36 were up and 6 were down-regulated). We also identified enriched pathways in genes regulated by differentially expressed 42 miRNAs, which include signaling associated with breast cancer, energy metabolism, glucose metabolism, and insulin. Our study indicates that extracellular vesicle miRNAs differentially expressed as a result of the MD might be involved in the mechanisms that relate to cardiometabolic risk factors in overweight breast cancer survivors.
| Original language | English |
|---|---|
| Article number | 1355 |
| Journal | Cancers |
| Volume | 12 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2020 Jun |
Bibliographical note
Funding Information:This work was supported by the Bio and Medical Technology Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning (NRF- 2018R1D1A1B07049223), the Technology Innovation Program (20002781, A Platform for Prediction and Management of Health Risk Based on Personal Big Data and Lifelogging) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea) to JW Lee, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (NRF-2019R1A2C1010043) to H. Lee. Intramural funding from National Institute of Nursing Research in National Institutes of Health.
Funding Information:
Author Contributions: Y.J.K., Y.E.C., H.L., and J.W.L. contributed to designing the experiment, interpreting the data, and writing the manuscript. Y.E.C., H.P., and H.L. designed and conducted exosome experiments. Y.J.K., A.‐R.C., W.J.C., and J.W.L. designed and conducted clinical experiments. S.Y. analyzed bioinformatics. H.S.K., J.G., and A.K.C. interpreted data and contributed to discussion. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Bio and Medical Technology Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning (NRF‐ 2018R1D1A1B07049223), the Technology Innovation Program (20002781, A Platform for Prediction and Management of Health Risk Based on Personal Big Data and Lifelogging) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea) to JW Lee, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (NRF‐2019R1A2C1010043) to H. Lee. Intramural funding from National Institute of Nursing Research in National Institutes of Health.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
All Science Journal Classification (ASJC) codes
- Oncology
- Cancer Research
