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Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples

Genomic copy number alteration and allelic imbalance are distinct features of cancer cells, and recent advances in the genotyping technology have greatly boosted the research in the cancer genome. However, the complicated nature of tumor usually hampers the dissection of the SNP arrays. In this stud...

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Autores principales: Li, Ao, Liu, Yuanning, Zhao, Qihong, Feng, Huanqing, Harris, Lyndsay, Wang, Minghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907544/
https://www.ncbi.nlm.nih.gov/pubmed/24498045
http://dx.doi.org/10.1371/journal.pone.0087212
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author Li, Ao
Liu, Yuanning
Zhao, Qihong
Feng, Huanqing
Harris, Lyndsay
Wang, Minghui
author_facet Li, Ao
Liu, Yuanning
Zhao, Qihong
Feng, Huanqing
Harris, Lyndsay
Wang, Minghui
author_sort Li, Ao
collection PubMed
description Genomic copy number alteration and allelic imbalance are distinct features of cancer cells, and recent advances in the genotyping technology have greatly boosted the research in the cancer genome. However, the complicated nature of tumor usually hampers the dissection of the SNP arrays. In this study, we describe a bioinformatic tool, named GIANT, for genome-wide identification of somatic aberrations from paired normal-tumor samples measured with SNP arrays. By efficiently incorporating genotype information of matched normal sample, it accurately detects different types of aberrations in cancer genome, even for aneuploid tumor samples with severe normal cell contamination. Furthermore, it allows for discovery of recurrent aberrations with critical biological properties in tumorigenesis by using statistical significance test. We demonstrate the superior performance of the proposed method on various datasets including tumor replicate pairs, simulated SNP arrays and dilution series of normal-cancer cell lines. Results show that GIANT has the potential to detect the genomic aberration even when the cancer cell proportion is as low as 5∼10%. Application on a large number of paired tumor samples delivers a genome-wide profile of the statistical significance of the various aberrations, including amplification, deletion and LOH. We believe that GIANT represents a powerful bioinformatic tool for interpreting the complex genomic aberration, and thus assisting both academic study and the clinical treatment of cancer.
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spelling pubmed-39075442014-02-04 Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples Li, Ao Liu, Yuanning Zhao, Qihong Feng, Huanqing Harris, Lyndsay Wang, Minghui PLoS One Research Article Genomic copy number alteration and allelic imbalance are distinct features of cancer cells, and recent advances in the genotyping technology have greatly boosted the research in the cancer genome. However, the complicated nature of tumor usually hampers the dissection of the SNP arrays. In this study, we describe a bioinformatic tool, named GIANT, for genome-wide identification of somatic aberrations from paired normal-tumor samples measured with SNP arrays. By efficiently incorporating genotype information of matched normal sample, it accurately detects different types of aberrations in cancer genome, even for aneuploid tumor samples with severe normal cell contamination. Furthermore, it allows for discovery of recurrent aberrations with critical biological properties in tumorigenesis by using statistical significance test. We demonstrate the superior performance of the proposed method on various datasets including tumor replicate pairs, simulated SNP arrays and dilution series of normal-cancer cell lines. Results show that GIANT has the potential to detect the genomic aberration even when the cancer cell proportion is as low as 5∼10%. Application on a large number of paired tumor samples delivers a genome-wide profile of the statistical significance of the various aberrations, including amplification, deletion and LOH. We believe that GIANT represents a powerful bioinformatic tool for interpreting the complex genomic aberration, and thus assisting both academic study and the clinical treatment of cancer. Public Library of Science 2014-01-30 /pmc/articles/PMC3907544/ /pubmed/24498045 http://dx.doi.org/10.1371/journal.pone.0087212 Text en © 2014 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Li, Ao
Liu, Yuanning
Zhao, Qihong
Feng, Huanqing
Harris, Lyndsay
Wang, Minghui
Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title_full Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title_fullStr Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title_full_unstemmed Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title_short Genome-Wide Identification of Somatic Aberrations from Paired Normal-Tumor Samples
title_sort genome-wide identification of somatic aberrations from paired normal-tumor samples
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907544/
https://www.ncbi.nlm.nih.gov/pubmed/24498045
http://dx.doi.org/10.1371/journal.pone.0087212
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