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Global analysis of somatic structural genomic alterations and their impact on gene expression in diverse human cancers.

Journal article
Authors Babak Alaei-Mahabadi
Joydeep Bhadury
Joakim Karlsson
Jonas Nilsson
Erik Larsson
Published in Proceedings of the National Academy of Sciences of the United States of America
Volume 113
Issue 48
Pages 13768-13773
ISSN 1091-6490
Publication year 2016
Published at Institute of Clinical Sciences, Department of Surgery
Institute of Biomedicine, Department of Medical Biochemistry and Cell Biology
Pages 13768-13773
Language en
Links dx.doi.org/10.1073/pnas.1606220113
www.ncbi.nlm.nih.gov/entrez/query.f...
Subject categories Bioinformatics and Systems Biology, Medical Genetics, Other Basic Medicine

Abstract

Tumor genomes are mosaics of somatic structural variants (SVs) that may contribute to the activation of oncogenes or inactivation of tumor suppressors, for example, by altering gene copy number amplitude. However, there are multiple other ways in which SVs can modulate transcription, but the general impact of such events on tumor transcriptional output has not been systematically determined. Here we use whole-genome sequencing data to map SVs across 600 tumors and 18 cancers, and investigate the relationship between SVs, copy number alterations (CNAs), and mRNA expression. We find that 34% of CNA breakpoints can be clarified structurally and that most amplifications are due to tandem duplications. We observe frequent swapping of strong and weak promoters in the context of gene fusions, and find that this has a measurable global impact on mRNA levels. Interestingly, several long noncoding RNAs were strongly activated by this mechanism. Additionally, SVs were confirmed in telomere reverse transcriptase (TERT) upstream regions in several cancers, associated with elevated TERT mRNA levels. We also highlight high-confidence gene fusions supported by both genomic and transcriptomic evidence, including a previously undescribed paired box 8 (PAX8)-nuclear factor, erythroid 2 like 2 (NFE2L2) fusion in thyroid carcinoma. In summary, we combine SV, CNA, and expression data to provide insights into the structural basis of CNAs as well as the impact of SVs on gene expression in tumors.

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