Yu Liu, Chunliang Li, Shuhong Shen, Xiaolong Chen, Karol Szlachta, Michael N. Edmonson, Ying Shao, Xiaotu Ma, Judith Hyle, Shaela Wright, Bensheng Ju, Michael C. Rusch, Yanling Liu, Benshang Li, Michael Macias, Liqing Tian, John Easton, Maoxiang Qian, Jun J. Yang, Shaoyan Hu, A. Thomas Look & Jinghui Zhang

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.

 doi: https://doi.org/10.1038/s41588-020-0659-5