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Updated: Mar 10, 2026

Reusable Single Cell for Iterative Epigenomic Analyses
Published on: February 11, 2022
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.
Abstract:
A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (∼21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and miRNA transcripts, DNA copy number, and protein levels. Here, we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17% to 84%. A six-gene model, including PARP1, EP300, KDM5C, SMARCB1, and UHRF1 matched this pattern. In addition, promoter methylation of two translationally relevant genes, Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT), served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacologic data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer types. Cancer Res; 77(3); 601-12. ©2016 AACR.
Insights
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.

