O-GlcNAcylation Links Nutrition to the Epigenetic Downregulation of UNC5A during Colon Carcinogenesis.
Amélie DecourcelleNinon VeryMadjid DjouinaIngrid LoisonJulien ThévenetMathilde Body-MalapelEric LelièvreOlivier CoqueretDominique LeprinceIkram El Yazidi-BelkouraVanessa DehennautPublished in: Cancers (2020)
While it is now accepted that nutrition can influence the epigenetic modifications occurring in colorectal cancer (CRC), the underlying mechanisms are not fully understood. Among the tumor suppressor genes frequently epigenetically downregulated in CRC, the four related genes of the UNC5 family: UNC5A, UNC5B, UNC5C and UNC5D encode dependence receptors that regulate the apoptosis/survival balance. Herein, in a mouse model of CRC, we found that the expression of UNC5A, UNC5B and UNC5C was diminished in tumors but only in mice subjected to a High Carbohydrate Diet (HCD) thus linking nutrition to their repression in CRC. O-GlcNAcylation is a nutritional sensor which has enhanced levels in CRC and regulates many cellular processes amongst epigenetics. We then investigated the putative involvement of O-GlcNAcylation in the epigenetic downregulation of the UNC5 family members. By a combination of pharmacological inhibition and RNA interference approaches coupled to RT-qPCR (Reverse Transcription-quantitative Polymerase Chain Reaction) analyses, promoter luciferase assay and CUT&RUN (Cleavage Under Target & Release Using Nuclease) experiments, we demonstrated that the O-GlcNAcylated form of the histone methyl transferase EZH2 (Enhancer of Zeste Homolog 2) represses the transcription of UNC5A in human colon cancer cells. Collectively, our data support the hypothesis that O-GlcNAcylation could represent one link between nutrition and epigenetic downregulation of key tumor suppressor genes governing colon carcinogenesis including UNC5A.
Keyphrases
- dna methylation
- gene expression
- physical activity
- mouse model
- cell proliferation
- transcription factor
- endothelial cells
- poor prognosis
- genome wide
- signaling pathway
- machine learning
- long non coding rna
- type diabetes
- skeletal muscle
- deep learning
- endoplasmic reticulum stress
- insulin resistance
- binding protein
- artificial intelligence
- high fat diet induced
- atomic force microscopy