GSE115685
DNA methylation analysis of breast cancer Hs578T cells with TET1 knockout
Both gains and losses of DNA methylation are common in cancer but the factors controlling this methylation balance remain unclear. Triple negative breast cancer (TNBC), a subtype that does not overexpress hormone receptors or HER2/NEU is one of the most hypomethylated cancers observed. In search for an explanation for this, we discovered that the TET1 DNA demethylase is specifically overexpressed in about 40% of patients with TNBC, where it is associated with hypomethylation of up to 10% of queried CpG sites and a worse overall survival. Through bioinformatic analyses in both breast and ovarian cancer cell line panels, we uncovered an intricate network connecting TET1 to hypomethylation and activation of cancer specific oncogenic pathways including PI3K, EGFR and PDGF. TET1 expression correlated with sensitivity to drugs targeting the PI3K-mTOR pathway. CRISPR mediated deletion of TET1 in two independent TNBC cell lines resulted in reduced expression of PI3K pathway genes, upregulation of immune response genes and substantially reduced cellular proliferation, suggesting dependence of oncogenic pathways on TET1 overexpression. Our work establishes TET1 as a potential oncogene that contributes to aberrant hypomethylation in cancer and suggests that 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 Hs578T cells with TET1 knockout by CRISPR (single clones) and empty vector control 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.