DREAM of MDA-MB-231 cells with TET1 knockout

DNA hypermethylation is known to contribute to the formation of cancer. However, DNA hypomethylation has received far less attention and the factors controlling the balance between hypo and hypermethylation and its impact on tumorigenesis remains unclear. Triple negative breast cancer (TNBC), a subtype of breast cancer that does not overexpress the hormone receptors or HER2/NEU, is one of the most hypomethylated cancers observed. Importantly, TNBCs are often a therapeutic challenge because of advanced presentation and lack of targeted therapies. TET1 is a DNA demethylase that regulates DNA methylation, hydroxymethylation and gene expression. We found that TET1 is specifically overexpressed in TNBC, where it is associated with hypomethylation and a worse overall survival. Further, we uncover an intricate network connecting TET1 expression to maintaining activation of cancer specific pathways, including PI3K, EGFR and PDGF. In TET1 KO cells, we observed reduced phospho-4EBP1 and decreased expression of genes in the PI3K pathway, suggesting loss of PI3K-mTOR activity is concomitant with loss of TET1. Additionally, TET1 KO cells have reduced cellular proliferation and migration. Our work establishes TET1 as an oncogene that contributes to the aberrant hypomethylation observed in cancer and suggests TET1 could serve as a novel druggable target for therapeutic intervention. Overall design: Digital restriction enzyme analysis of methylation (DREAM) was performed to determine the methylation profile of MDA_MB_231 cells with TET1 knockout (single clones), including empty vector control pooled cells and empty vector single clones. Briefly, genomic DNA was sequentially digested by SmaI and XmaI, which both recognize the sequence CCCGGG. SmaI is methylation sensitive, where XmaI is methylation insensitive. Distinct signatures, 5'-GGG at unmethylated sites or 5'-CCGGG at methylated sites were created by enzyme digestion and ultimately high througput sequencing was used to map these sites to the genome. Methylation ratios for each individual CCCGGG site were calculated as a proportion of methylated counts to the sum of unmethylated and methylated counts, and subsequently adjusted for differences in restriction enzyme efficiency using values obtained from spiked in standards.