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CpG methylation potentiates pixantrone and doxorubicin-induced DNA damage and is a marker of drug sensitivity.

ABSTRACT: DNA methylation is an epigenetic modification of the mammalian genome that occurs predominantly at cytosine residues of the CpG dinucleotide. Following formaldehyde activation, pixantrone alkylates DNA and particularly favours the CpG motif. Aberrations in CpG methylation patterns are a feature of most cancer types, a characteristic that may determine their susceptibility to specific drug treatments. Given their common target, DNA methylation may modulate the DNA damage induced by formaldehyde-activated pixantrone. In vitro transcription, mass spectrometry and oligonucleotide band shift assays were utilized to establish that pixantrone-DNA adduct formation was consistently enhanced 2-5-fold at discrete methylated CpG doublets. The methylation-mediated enhancement was exquisitely sensitive to the position of the methyl substituent since methylation at neighboring cytosine residues failed to confer an increase in pixantrone-DNA alkylation. Covalent modification of DNA by formaldehyde-activated doxorubicin, but not cisplatin, was augmented by neighbouring CpG methylation, indicating that modulation of binding by CpG methylation is not a general feature of all alkylators. HCT116 colon cancer cells vastly deficient in CpG methylation were 12- and 10-fold more resistant to pixantrone and doxorubicin relative to the wild-type line, suggesting that these drugs may selectively recognize the aberrant CpG methylation profiles characteristic of most tumour types.

SUBMITTER: Evison BJ

PROVIDER: S-EPMC2770666 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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CpG methylation potentiates pixantrone and doxorubicin-induced DNA damage and is a marker of drug sensitivity.

Evison Benny J BJ Bilardi Rebecca A RA Chiu Francis C K FC Pezzoni Gabriella G Phillips Don R DR Cutts Suzanne M SM

Nucleic acids research 20090831 19

DNA methylation is an epigenetic modification of the mammalian genome that occurs predominantly at cytosine residues of the CpG dinucleotide. Following formaldehyde activation, pixantrone alkylates DNA and particularly favours the CpG motif. Aberrations in CpG methylation patterns are a feature of most cancer types, a characteristic that may determine their susceptibility to specific drug treatments. Given their common target, DNA methylation may modulate the DNA damage induced by formaldehyde-a ...[more]

PMID: 19720735

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Project description:Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug responses for a given cell line based on molecular features may help to optimize drug-development pipelines and explain mechanisms behind treatment responses. In this study, we focus on DNA methylation profiles as one type of molecular feature that is known to drive tumorigenesis and modulate treatment responses. Using genome-wide, DNA methylation profiles from 987 cell lines in the Genomics of Drug Sensitivity in Cancer database, we used machine-learning algorithms to evaluate the potential to predict cytotoxic responses for eight anti-cancer drugs. We compared the performance of five classification algorithms and four regression algorithms representing diverse methodologies, including tree-, probability-, kernel-, ensemble-, and distance-based approaches. We artificially subsampled the data to varying degrees, aiming to understand whether training based on relatively extreme outcomes would yield improved performance. When using classification or regression algorithms to predict discrete or continuous responses, respectively, we consistently observed excellent predictive performance when the training and test sets consisted of cell-line data. Classification algorithms performed best when we trained the models using cell lines with relatively extreme drug-response values, attaining area-under-the-receiver-operating-characteristic-curve values as high as 0.97. The regression algorithms performed best when we trained the models using the full range of drug-response values, although this depended on the performance metrics we used. Finally, we used patient data from The Cancer Genome Atlas to evaluate the feasibility of classifying clinical responses for human tumors based on models derived from cell lines. Generally, the algorithms were unable to identify patterns that predicted patient responses reliably; however, predictions by the Random Forests algorithm were significantly correlated with Temozolomide responses for low-grade gliomas.

Dataset Information

CpG methylation potentiates pixantrone and doxorubicin-induced DNA damage and is a marker of drug sensitivity.

Publications

CpG methylation potentiates pixantrone and doxorubicin-induced DNA damage and is a marker of drug sensitivity.

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