Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin [EPIC methylation data on cell lines and PDXs]

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive desmoplasia, which challenges the molecular analyses of bulk tumor samples. Here we FACS-purified epithelial cells from human PDAC and normal pancreas and derived their genome-wide transcriptome and DNA methylome landscapes. Clustering based on DNA methylation revealed two distinct PDAC groups displaying different methylation patterns at regions encoding repeat elements. Methylationlow tumors are characterized by higher expression of endogenous retroviral (ERV) transcripts and dsRNA sensors which leads to a cell intrinsic activation of an interferon signature (IFNsign). This results in a pro-tumorigenic microenvironment and poor patient outcome. Methylationlow/IFNsignhigh and Methylationhigh/IFNsignlow PDAC cells preserve lineage traits, respective of normal ductal or acinar pancreatic cells. Moreover, ductal-derived KrasG12D/Trp53-/- mouse PDACs show higher expression of IFNsign compared to acinar-derived counterparts. Collectively, our data point to two different origins and etiologies of human PDACs, with the aggressive Methylationlow/IFNsignhigh subtype potentially targetable by agents blocking intrinsic IFN-signaling. hPDAC primary cell lines (PACOs) were normalized together. PDAC-PDX tumor samples were normalized together with normal samples. These included HPDE cell line, normal bulk tissue, mixed exocrine DNA, acinar, de-differentiated acinar and ductal cells isolated by FACS from healthy donors, and 4 previously published acinar and ductal replicates (GSE122126, samples GSM3455826, GSM3455827, GSM3455828, GSM3455829). RnBeads was used to process the data. SNP-enriched and sex chromosome associated probes were removed from the analyses. BMIQ normalization was applied. **Submitter declares that the raw data for 34 Samples were deposited in the European Genome-phenome Archive (EGA) under accession number EGAS00001004660 due to patient privacy concerns.**