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Unscrambling cancer genomes via integrated analysis of structural variation and copy number
Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant call...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903802/ https://www.ncbi.nlm.nih.gov/pubmed/36776527 http://dx.doi.org/10.1016/j.xgen.2022.100112 |
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author | Shale, Charles Cameron, Daniel L. Baber, Jonathan Wong, Marie Cowley, Mark J. Papenfuss, Anthony T. Cuppen, Edwin Priestley, Peter |
author_facet | Shale, Charles Cameron, Daniel L. Baber, Jonathan Wong, Marie Cowley, Mark J. Papenfuss, Anthony T. Cuppen, Edwin Priestley, Peter |
author_sort | Shale, Charles |
collection | PubMed |
description | Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant calls into distinct events and predicts their effect on the local structure of the derivative chromosome and the functional impact on affected genes. Visualizations facilitate further investigation of complex rearrangements. LINX allows insights into a diverse range of structural variation events and can reliably detect pathogenic rearrangements, including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions, and duplications. Uniquely, LINX also predicts chained fusions that we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events that we term homozygous disruptions that may be a driver mutation in up to 9% of tumors and may frequently affect PTEN, TP53, and RB1. |
format | Online Article Text |
id | pubmed-9903802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99038022023-02-10 Unscrambling cancer genomes via integrated analysis of structural variation and copy number Shale, Charles Cameron, Daniel L. Baber, Jonathan Wong, Marie Cowley, Mark J. Papenfuss, Anthony T. Cuppen, Edwin Priestley, Peter Cell Genom Technology Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant calls into distinct events and predicts their effect on the local structure of the derivative chromosome and the functional impact on affected genes. Visualizations facilitate further investigation of complex rearrangements. LINX allows insights into a diverse range of structural variation events and can reliably detect pathogenic rearrangements, including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions, and duplications. Uniquely, LINX also predicts chained fusions that we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events that we term homozygous disruptions that may be a driver mutation in up to 9% of tumors and may frequently affect PTEN, TP53, and RB1. Elsevier 2022-03-22 /pmc/articles/PMC9903802/ /pubmed/36776527 http://dx.doi.org/10.1016/j.xgen.2022.100112 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technology Shale, Charles Cameron, Daniel L. Baber, Jonathan Wong, Marie Cowley, Mark J. Papenfuss, Anthony T. Cuppen, Edwin Priestley, Peter Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title | Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title_full | Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title_fullStr | Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title_full_unstemmed | Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title_short | Unscrambling cancer genomes via integrated analysis of structural variation and copy number |
title_sort | unscrambling cancer genomes via integrated analysis of structural variation and copy number |
topic | Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903802/ https://www.ncbi.nlm.nih.gov/pubmed/36776527 http://dx.doi.org/10.1016/j.xgen.2022.100112 |
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