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The NCI-60 Methylome and Its Integration into CellMiner
William C Reinhold1, Sudhir Varma2,3,4, Margot Sunshine2,3
1Developmental Therapeutics Branch, Center for Cancer Research, NCI, NIH, Bethesda, Maryland. wcr@mail.nih.gov pommier@nih.gov.
Cancer Research
|December 8, 2016
Summary
The NCI-60 cancer cell line panel now includes a comprehensive DNA methylation database, revealing gene methylation patterns and their links to cancer drug responses. This resource aids in identifying new cancer drugs and therapeutic strategies.
Area of Science:
- Genomics
- Systems Pharmacology
- Cancer Biology
Background:
- The NCI-60 cancer cell line panel is a vital resource for drug discovery, offering extensive compound and genomic data.
- Existing data lacked comprehensive genome-wide DNA methylation profiles for the NCI-60 panel.
Purpose of the Study:
- To establish the first readily usable genome-wide DNA methylation database for the NCI-60 cancer cell line panel.
- To integrate DNA methylation data with existing genomic and pharmacologic data for novel insights.
Main Methods:
- Utilized the Infinium HumanMethylation450k BeadChip array to generate DNA methylation data for 485,577 probes across the NCI-60 panel.
- Integrated DNA methylation signatures for 17,559 genes into the open-access CellMiner version 2.0 platform.
- Performed correlations between transcript levels and DNA methylation, and integrated DNA methylation with copy number data.
Main Results:
- Identified epithelial/mesenchymal transition gene category as significantly influenced by DNA methylation.
- Assessed the relative influence of DNA methylation and copy number on transcript levels for 15,798 genes.
- Found promoter methylation of SLFN11 and MGMT as indicators of therapeutic resistance and susceptibility, respectively.
- Developed a six-gene model (PARP1, EP300, KDM5C, SMARCB1, UHRF1) correlating with global methylome patterns.
Conclusions:
- The new DNA methylation database provides a valuable resource for systems pharmacology and genomic studies.
- The findings reinforce known therapeutic strategies and highlight potential novel drug targets and therapies for various cancer types.
- This integrated molecular data resource facilitates a deeper understanding of cancer biology and drug response mechanisms.

