| Literature DB >> 32632335 |
Yu Liu1,2, Chunliang Li3, Shuhong Shen4,5, Xiaolong Chen6, Karol Szlachta6, Michael N Edmonson6, Ying Shao6, Xiaotu Ma6, Judith Hyle3, Shaela Wright3, Bensheng Ju6, Michael C Rusch6, Yanling Liu6, Benshang Li4,5, Michael Macias6, Liqing Tian6, John Easton6, Maoxiang Qian7, Jun J Yang7,8,9, Shaoyan Hu10, A Thomas Look11,12, Jinghui Zhang13.
Abstract
We developed cis-X, a computational method for discovering regulatory noncoding variants in cancer by integrating whole-genome and transcriptome sequencing data from a single cancer sample. cis-X first finds aberrantly cis-activated genes that exhibit allele-specific expression accompanied by an elevated outlier expression. It then searches for causal noncoding variants that may introduce aberrant transcription factor binding motifs or enhancer hijacking by structural variations. Analysis of 13 T-lineage acute lymphoblastic leukemias identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by chromatin immunoprecipitation sequencing of a patient-derived xenograft. Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion that removes a CTCF-insulated neighborhood boundary. cis-X may be applied to pediatric and adult solid tumors that are aneuploid and heterogeneous. In contrast to existing approaches, which require large sample cohorts, cis-X enables the discovery of regulatory noncoding variants in individual cancer genomes.Entities:
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Year: 2020 PMID: 32632335 PMCID: PMC7679232 DOI: 10.1038/s41588-020-0659-5
Source DB: PubMed Journal: Nat Genet ISSN: 1061-4036 Impact factor: 38.330