Circular binary segmentation for the analysis of array-based DNA copy number data

Olshen, Adam B.; Venkatraman, E. S.; Lucito, Robert; Wigler, Michael

doi:10.1093/biostatistics/kxh008

Cited by 2,012 publications

(2,024 citation statements)

References 22 publications

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“…Generation of copy-number profiles. Copy-number calls reported by ACEseq were converted to the 'SEG' segmentation format, similar to the output of the circular binary segmentation algorithm based on chromosomal segment borders as pseudo marker positions 96 . All possible marker positions were determined from the whole cohort before assessing sample-wise copy-number profiles per marker in order to achieve identical resolution for all samples.…”

Section: Discussionmentioning

confidence: 99%

The landscape of genomic alterations across childhood cancers

Gröbner¹,

Worst²,

Weischenfeldt³

et al. 2018

Nature

1,167

1,156

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The landscape of genomic alterations across childhood cancers a list of authors and affiliations appears at the end of the paper. OPENPan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.Cure rates for childhood cancers have increased to about 80% in recent decades, but cancer is still the leading cause of death by disease in the developed world among children over one year of age 1,2 . Furthermore, many children who survive cancer suffer from long-term sequelae of surgery, cytotoxic chemotherapy, and radiotherapy, including mental disabilities, organ toxicities, and secondary cancers 3 . A crucial step in developing more specific and less damaging therapies is the unravelling of the complete genetic repertoire of paediatric malignancies, which differ from adult malignancies in terms of their histopathological entities and molecular subtypes 4 . Over the past few years, many entityspecific sequencing efforts have been launched, but the few paediatric pan-cancer studies thus far have focused only on mutation frequencies, germline predisposition, and alterations in epigenetic regulators [4][5][6] .We have carried out a broad exploration of cancers in children, adolescents, and young adults, by incorporating small mutations and copy-number or structural variants on somatic and germline levels, and by identifying putative cancer genes and comparing them to those previously reported in adult cancers by The Cancer Genome Atlas (TCGA) 7 . We have also examined mutational signatures and potential drug targets. The compendium of genetic alterations presented here is available to the scientific community at http://www.pedpancan.com.This integrative analysis includes 24 types of cancer and covers all major childhood cancer entities, many of which occur exclusively in children 8 (Fig. 1, Supplementary Table 1). Ninety-five per cent of the patients in this study were diagnosed during childhood or adolescence (aged 18 years or younger) and 5% as young adults (up to 25 years) (Extended Data ...

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Section: Discussionmentioning

confidence: 99%

The landscape of genomic alterations across childhood cancers

Gröbner¹,

Worst²,

Weischenfeldt³

et al. 2018

Nature

1,167

1,156

View full text Add to dashboard Cite

show abstract

“…Normalized signal intensity files were imported into and analyzed using Nexus Copy Number software (version 5.1) (BioDiscovery). This program analyzes log 2 ratio output files using a rank segmentation algorithm similar to circular binary segmentation (37). Settings were optimized using a selfself hybridization.…”

Section: Methodsmentioning

confidence: 99%

Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number variant analysis

Brown

Dobrinski

Lee

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

102

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Copy number variants (CNVs) represent a substantial source of genomic variation in vertebrates and have been associated with numerous human diseases. Despite this, the extent of CNVs in the zebrafish, an important model for human disease, remains unknown. Using 80 zebrafish genomes, representing three commonly used laboratory strains and one native population, we constructed a genome-wide, high-resolution CNV map for the zebrafish comprising 6,080 CNV elements and encompassing 14.6% of the zebrafish reference genome. This amount of copy number variation is four times that previously observed in other vertebrates, including humans. Moreover, 69% of the CNV elements exhibited strain specificity, with the highest number observed for Tubingen. This variation likely arose, in part, from Tubingen's large founding size and composite population origin. Additional population genetic studies also provided important insight into the origins and substructure of these commonly used laboratory strains. This extensive variation among and within zebrafish strains may have functional effects that impact phenotype and, if not properly addressed, such extensive levels of germ-line variation and population substructure in this commonly used model organism can potentially confound studies intended for translation to human diseases.

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“…Finally, copy number inferences were made by circular binary segmentation to reduce noise (e.g., from unmasked complex sequences in the target) and provide a consensus score for all regions of the genome based on at least two underlying SNPs (26). For all subsequent analysis, the genome was divided into 100 kb units in which each was assigned the circular binary segmentation -extracted value for every cancer cell line.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

Greshock

Cheng

Rusnak

et al. 2008

Molecular Cancer Therapeutics

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A common aim of pharmacogenomic studies that use genome-wide assays on panels of cancers is the unbiased discovery of genomic alterations that are associated with clinical outcome and drug response. Previous studies of lapatinib, a selective dual-kinase inhibitor of epidermal growth factor receptor (EGFR) and HER2 tyrosine kinases, have shown predictable relationships between the activity of these target genes and response. Under the hypothesis that additional genes may play a role in drug sensitivity, a predictive model for lapatinib response was constructed from genome-wide DNA copy number data from 24 cancer cell lines. An optimal predictive model which consists of aberrations at nine distinct genetic loci, includes gains of HER2, EGFR, and loss of CDKN2A. This model achieved an area under the receiver operating characteristic curve of f0.85 (80% confidence interval, 0.70 -0.98; P < 0.01), and correctly classified the sensitivity status of 8 of 10 head and neck cancer cell lines. This study shows that biomarkers predictive for lapatinib sensitivity, including the previously described copy number gains of EGFR and HER2, can be discovered using novel genomic assays in an unbiased manner. Furthermore, these results show the utility of DNA copy number profiles in pharmacogenomic studies. [Mol Cancer Ther 2008;7(4):935 -43]

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Circular binary segmentation for the analysis of array-based DNA copy number data

Cited by 2,012 publications

References 22 publications

The landscape of genomic alterations across childhood cancers

The landscape of genomic alterations across childhood cancers

Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number variant analysis

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

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