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Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X

We developed cis-X, a computational method for discovery of 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 el...

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Autores principales: Liu, Yu, Li, Chunliang, Shen, Shuhong, Chen, Xiaolong, Szlachta, Karol, Edmonson, Michael N., Shao, Ying, Ma, Xiaotu, Hyle, Judith, Wright, Shaela, Ju, Bensheng, Rusch, Michael C., Liu, Yanling, Li, Benshang, Macias, Michael, Tian, Liqing, Easton, John, Qian, Maoxiang, Yang, Jun J., Hu, Shaoyan, Look, A. Thomas, Zhang, Jinghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679232/
https://www.ncbi.nlm.nih.gov/pubmed/32632335
http://dx.doi.org/10.1038/s41588-020-0659-5
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author Liu, Yu
Li, Chunliang
Shen, Shuhong
Chen, Xiaolong
Szlachta, Karol
Edmonson, Michael N.
Shao, Ying
Ma, Xiaotu
Hyle, Judith
Wright, Shaela
Ju, Bensheng
Rusch, Michael C.
Liu, Yanling
Li, Benshang
Macias, Michael
Tian, Liqing
Easton, John
Qian, Maoxiang
Yang, Jun J.
Hu, Shaoyan
Look, A. Thomas
Zhang, Jinghui
author_facet Liu, Yu
Li, Chunliang
Shen, Shuhong
Chen, Xiaolong
Szlachta, Karol
Edmonson, Michael N.
Shao, Ying
Ma, Xiaotu
Hyle, Judith
Wright, Shaela
Ju, Bensheng
Rusch, Michael C.
Liu, Yanling
Li, Benshang
Macias, Michael
Tian, Liqing
Easton, John
Qian, Maoxiang
Yang, Jun J.
Hu, Shaoyan
Look, A. Thomas
Zhang, Jinghui
author_sort Liu, Yu
collection PubMed
description We developed cis-X, a computational method for discovery of 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 (T-ALL) identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by ChIP-seq of a patient-derived xenograft (PDX). Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion which 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 discovery of regulatory noncoding variants in individual cancer genomes.
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spelling pubmed-76792322021-01-06 Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X Liu, Yu Li, Chunliang Shen, Shuhong Chen, Xiaolong Szlachta, Karol Edmonson, Michael N. Shao, Ying Ma, Xiaotu Hyle, Judith Wright, Shaela Ju, Bensheng Rusch, Michael C. Liu, Yanling Li, Benshang Macias, Michael Tian, Liqing Easton, John Qian, Maoxiang Yang, Jun J. Hu, Shaoyan Look, A. Thomas Zhang, Jinghui Nat Genet Article We developed cis-X, a computational method for discovery of 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 (T-ALL) identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by ChIP-seq of a patient-derived xenograft (PDX). Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion which 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 discovery of regulatory noncoding variants in individual cancer genomes. 2020-07-06 2020-08 /pmc/articles/PMC7679232/ /pubmed/32632335 http://dx.doi.org/10.1038/s41588-020-0659-5 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Liu, Yu
Li, Chunliang
Shen, Shuhong
Chen, Xiaolong
Szlachta, Karol
Edmonson, Michael N.
Shao, Ying
Ma, Xiaotu
Hyle, Judith
Wright, Shaela
Ju, Bensheng
Rusch, Michael C.
Liu, Yanling
Li, Benshang
Macias, Michael
Tian, Liqing
Easton, John
Qian, Maoxiang
Yang, Jun J.
Hu, Shaoyan
Look, A. Thomas
Zhang, Jinghui
Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title_full Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title_fullStr Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title_full_unstemmed Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title_short Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X
title_sort discovery of regulatory noncoding variants in individual cancer genomes by using cis-x
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679232/
https://www.ncbi.nlm.nih.gov/pubmed/32632335
http://dx.doi.org/10.1038/s41588-020-0659-5
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