Refinement of computational identification of somatic copy number alterations using DNA methylation microarrays illustrated in cancers of unknown primary. Issue 5 (6th May 2022)

• Record Type: Journal Article
• Authors: Blecua, Pedro; Davalos, Veronica; de Villasante, Izar; Merkel, Angelika; Musulen, Eva; Coll-SanMartin, Laia; Esteller, Manel
• Is Part Of: Briefings in bioinformatics. Volume 23:Issue 5(2022)
• Publication Date: 2022-05-06
• Subjects: somatic copy number alterations -- DNA methylation -- gene amplification -- actionable target identification -- cancers of unknown primary; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbac161
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: High-throughput genomic technologies are increasingly used in personalized cancer medicine. However, computational tools to maximize the use of scarce tissues combining distinct molecular layers are needed. Here we present a refined strategy, based on the R-package 'conumee', to better predict somatic copy number alterations (SCNA) from deoxyribonucleic acid (DNA) methylation arrays. Our approach, termed hereafter as 'conumee- KCN ', improves SCNA prediction by incorporating tumor purity and dynamic thresholding. We trained our algorithm using paired DNA methylation and SNP Array 6.0 data from The Cancer Genome Atlas samples and confirmed its performance in cancer cell lines. Most importantly, the application of our approach in cancers of unknown primary identified amplified potentially actionable targets that were experimentally validated by Fluorescence in situ hybridization and immunostaining, reaching 100% specificity and 93.3% sensitivity.