Multilevel Omic Data Clustering Reveals Variable Contribution of Methylator Phenotype to Integrative Cancer Subtypes

Abstract

Aim: We aimed to assess to what extent CpG island methylator phenotype (CIMP) contributes to cancer subtypes obtained by multilevel omic data analysis. Materials & methods: 16 The Cancer Genome Atlas datasets encompassing three data layers in 4688 tumor samples were analyzed. We identified cancer integrative subtypes (ISs) by the use of similarity network fusion and consensus clustering. CIMP high (CIMP-H) associated ISs were profiled by gene sets and transcriptional regulators enrichment analysis. Results & conclusion: In nine out of 16 cancer datasets CIMP-H clusters significantly overlaped with unique ISs. The contribution of CIMP-H on integrative molecular profiling is variable; therefore, only in a subset of cancer types does CIMP-H contribute to homogenous integrative subtype. CIMP-H associated ISs are heterogenous groups with regard to deregulated pathways and transcriptional regulators.

Keywords::

• cancer
• CpG island methylator phenotype
• DNA methylation
• Illumina 450k
• integrative clustering

Acknowledgments

Authors are grateful to patients and TCGA.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.