2020
DOI: 10.1101/2020.10.22.342436
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TET2 drives 5hmc marking of GATA6 and epigenetically defines pancreatic ductal adenocarcinoma transcriptional subtypes

Abstract: Background and Aims: Pancreatic ductal adenocarcinoma (PDAC) is characterised by advanced disease stage at presentation, aggressive disease biology and resistance to therapy resulting in extremely poor five-year survival <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression but exactly why is unclear and hindered by analysis of clinical samp… Show more

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Cited by 2 publications
(5 citation statements)
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“…Studies have classified PDAC into classical, quasimesenchymal, and exocrine-like subtypes. Classical PDAC showed that higher GATA6 mRNA expression is associated with a better prognosis ( 35 , 36 ). Additionally, low GATA6 expression is associated with shorter OS ( 37 ).…”
Section: Discussionmentioning
confidence: 99%
“…Studies have classified PDAC into classical, quasimesenchymal, and exocrine-like subtypes. Classical PDAC showed that higher GATA6 mRNA expression is associated with a better prognosis ( 35 , 36 ). Additionally, low GATA6 expression is associated with shorter OS ( 37 ).…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, we aimed to discover drugs that can induce drug sensitivity of pancreatic cancer sub-types that are resistant to existing anti-cancer therapies rather than screen compounds that can kill cancer cells directly. A recent study has shown that the combination of metformin and vitamin C can restore TET2 and GATA6 activities in aggressive squamous-like pancreatic ductal adenocarcinoma sub-type, which are the biomarkers of classical-pancreatic tumor, thereby improving therapeutic responses and survival of aggressive pancreatic sub-type 43 . The main step of this screening pipeline is to compare the chemical-induced gene expression profiles generated by CIGER with gene expression profile computed from pancreatic cancer cell lines treated by metformin and vitamin C. For drug gene expression profiles, we send queries to the DrugBank database to retrieve the list of all existing drugs (i.e., 11179 drugs) with their corresponding SMILES representations and then use CIGER trained on the LINCS L1000 dataset to generate profiles for these drugs from their SMILES representations.…”
Section: Gene Expression Classification For De Novo Chemicalsmentioning
confidence: 99%
“…The main step of this screening pipeline is to compare the chemical-induced gene expression profiles generated by CIGER with gene expression profile computed from pancreatic cancer cell lines treated by metformin and vitamin C. For drug gene expression profiles, we send queries to the DrugBank database to retrieve the list of all existing drugs (i.e., 11179 drugs) with their corresponding SMILES representations and then use CIGER trained on the LINCS L1000 dataset to generate profiles for these drugs from their SMILES representations. For gene expression profile of pancreatic cancer treated by metformin and vitamin C, we perform differential expression analysis with DESeq2 44 between metformin and vitamin C treated samples and mock-treated samples 43 . Then, we compute the similarity with respect to ranking information between the gene expression profiles of treatment and drugs across 10 cell lines by GSEA and Precision@200 scores to find potential treatment for this disease.…”
Section: Gene Expression Classification For De Novo Chemicalsmentioning
confidence: 99%
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