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Copy number-aware deconvolution of tumor-normal DNA methylation profiles

Larose Cadieux, E.; Tanic, M.; Wilson, G. A.; Baker, T.; Dietzen, M.; Dhami, P.; Vaikkinen, H.; Watkins, T. B. K.; Kanu, N.; Veeriah, S.; Jamal-Hanjani, M.; McGranahan, N.; Feber, A.; Swanton, C.; TRACERx Consortium, ; Beck, S.; Demeulemeester, J.; Van Loo, P.

2020-11-04 genomics
10.1101/2020.11.03.366252 bioRxiv
Show abstract

Aberrant methylation is a hallmark of cancer, but bulk tumor data is confounded by admixed normal cells and copy number changes. Here, we introduce Copy number-Aware Methylation Deconvolution Analysis of Cancers (CAMDAC; https://github.com/VanLoo-lab/CAMDAC), which outputs tumor purity, allele-specific copy number and deconvolved methylation estimates. We apply CAMDAC to 122 multi-region samples from 38 TRACERx non-small cell lung cancers profiled by reduced representation bisulfite sequencing. CAMDAC copy number profiles parallel those derived from genome sequencing and highlight widespread chromosomal instability. Deconvolved polymorphism-independent methylation rates enable unbiased tumor-normal and tumor-tumor differential methylation calling. Read-phasing validates CAMDAC methylation rates and directly links genotype and epitype. We show increased epigenetic instability in adenocarcinoma vs. squamous cell carcinoma, frequent hypermethylation at sites carrying somatic mutations, and parallel copy number losses and methylation changes at imprinted loci. Unlike bulk methylomes, CAMDAC profiles recapitulate tumor phylogenies and evidence distinct patterns of epigenetic heterogeneity in lung cancer.

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