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Updated: Aug 25, 2026
An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues
Published on: April 5, 2018
Integrated genomic and epigenomic analyses pinpoint biallelic gene inactivation in tumors
Giuseppe Zardo1, Maarit I Tiirikainen, Chibo Hong
1Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California 94115, USA.
Abstract:
Aberrant methylation of CpG islands and genomic deletion are two predominant mechanisms of gene inactivation in tumorigenesis, but the extent to which they interact is largely unknown. The lack of an integrated approach to study these mechanisms has limited the understanding of tumor genomes and cancer genes. Restriction landmark genomic scanning (RLGS; ref. 1) is useful for global analysis of aberrant methylation of CpG islands, but has not been amenable to alignment with deletion maps because the identity of most RLGS fragments is unknown. Here, we determined the nucleotide sequence and exact chromosomal position of RLGS fragments throughout the genome using the whole chromosome of origin of the fragments and in silico restriction digestion of the human genome sequence. To study the interaction of these gene-inactivation mechanisms in primary brain tumors, we integrated RLGS-based methylation analysis with high-resolution deletion maps from microarray-based comparative genomic hybridization (array CGH; ref. 3). Certain subsets of gene-associated CpG islands were preferentially affected by convergent methylation and deletion, including genes that exhibit tumor-suppressor activity, such as CISH1 (encoding SOCS1; ref. 4), as well as genes such as COE3 that have been missed by traditional non-integrated approaches. Our results show that most aberrant methylation events are focal and independent of deletions, and the rare convergence of these mechanisms can pinpoint biallelic gene inactivation without the use of positional cloning.
Insights
Aberrant DNA methylation and genomic deletions are key in cancer gene inactivation. This study integrates these methods to identify tumor suppressor genes, revealing focal methylation events and rare convergent inactivation.
Area of Science:
- Genomics
- Cancer Biology
- Epigenetics
Background:
- Aberrant CpG island methylation and genomic deletion are primary mechanisms of gene inactivation in tumorigenesis.
- The interaction between these mechanisms and their impact on tumor genomes is poorly understood.
- Existing methods like Restriction Landmark Genomic Scanning (RLGS) for methylation analysis lack integration with deletion mapping due to unknown fragment identities.
Purpose of the Study:
- To develop an integrated approach to study the interplay between aberrant methylation and genomic deletion in cancer.
- To identify novel cancer genes and understand tumor genome complexity.
- To pinpoint genes undergoing biallelic inactivation through combined epigenetic and genetic alterations.
Main Methods:
- Determined nucleotide sequences and chromosomal positions of RLGS fragments using whole chromosome data and in silico digestion.
- Integrated RLGS-based methylation analysis with high-resolution deletion maps from microarray-based comparative genomic hybridization (array CGH).
- Applied this integrated approach to primary brain tumors.
Main Results:
- Identified specific subsets of CpG islands preferentially affected by convergent methylation and deletion.
- Discovered tumor suppressor genes, including CISH1 (SOCS1), and other genes like COE3, missed by traditional methods.
- Demonstrated that most aberrant methylation events are focal and independent of deletions.
- Showed that rare convergence of methylation and deletion can identify biallelic gene inactivation.
Conclusions:
- The integration of methylation and deletion analysis provides a powerful tool for understanding tumor genomes.
- Convergent methylation and deletion events highlight critical genes for biallelic inactivation in cancer.
- This approach enhances the discovery of tumor suppressor genes and improves the characterization of cancer-associated genomic alterations.
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