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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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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. |
format | Online Article Text |
id | pubmed-7679232 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
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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