Transcriptome and DNA Methylome Analysis in a Mouse Model of Diet-Induced Obesity Predicts Increased Risk of Colorectal Cancer.
| Citation | Li, Ruifang, et al. “Transcriptome and DNA Methylome Analysis in a Mouse Model of Diet-Induced Obesity Predicts Increased Risk of Colorectal Cancer”. 2018. Cell Reports, vol. 22, no. 3, 2018, pp. 624–637. |
| Center | University of Washington |
| Author | Ruifang Li, Sara A Grimm, Deepak Mav, Haiwei Gu, Danijel Djukovic, Ruchir Shah, Alex Merrick, Daniel Raftery, Paul A Wade |
| Keywords | DNA methylation, Cellular metabolism, colorectal cancer, gene expression, obesity, signal transduction, weight loss |
| Abstract |
Colorectal cancer (CRC) tends to occur at older age; however, CRC incidence rates have been rising sharply among young age groups. The increasing prevalence of obesity is recognized as a major risk, yet the mechanistic underpinnings remain poorly understood. Using a diet-induced obesity mouse model, we identified obesity-associated molecular changes in the colonic epithelium of young and aged mice, and we further investigated whether the changes were reversed after weight loss. Transcriptome analysis indicated that obesity-related colonic cellular metabolic switch favoring long-chain fatty acid oxidation happened in young mice, while obesity-associated downregulation of negative feedback regulators of pro-proliferative signaling pathways occurred in older mice. Strikingly, colonic DNA methylome was pre-programmed by obesity at young age, priming for a tumor-prone gene signature after aging. Furthermore, obesity-related changes were substantially preserved after short-term weight loss, but they were largely reversed after long-term weight loss. We provided mechanistic insights into increased CRC risk in obesity. |
| Year of Publication |
2018
|
| Journal |
Cell reports
|
| Volume |
22
|
| Issue |
3
|
| Number of Pages |
624-637
|
| Date Published |
12/2018
|
| ISSN Number |
2211-1247
|
| DOI |
10.1016/j.celrep.2017.12.071
|
| Alternate Journal |
Cell Rep
|
| PMCID |
PMC5793878
|
| PMID |
29346762
|
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