Chromatin Structure–Based Prediction of Recurrent Noncoding Mutations in Cancer  

Oleh:

Kwoneel Kim ; Kiwon Jang ; Woojin Yang ; Eun-Young Choi ; Seong-Min Park

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Nature Genetics vol. 48 no. 11 (Nov. 2016), page 1321-1326.
Topik: Data Mining; Epigenomics; Genomics

Ketersediaan

Perpustakaan FK Nomor Panggil: N12.K Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Recurrence is a hallmark of cancer-driving mutations. Recurrent mutations can arise at the same site or affect the same gene at different sites. Here we identified a set of mutations arising in individual samples and altering different cis-regulatory elements that converge on a common gene via chromatin interactions. The mutations and genes identified in this fashion showed strong relevance to cancer, in contrast to noncoding mutations with site-specific recurrence only. We developed a prediction method that identifies potentially recurrent mutations on the basis of the features shared by mutations whose recurrence is observed in a given cohort. Our method was capable of accurately predicting recurrent mutations at the level of target genes but not mutations recurring at the same site. We experimentally validated predicted mutations in distal regulatory regions of the TERT gene. In conclusion, we propose a novel approach to discovering potential cancer-driving mutations in noncoding regions.

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