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Published in: Breast Cancer Research 1/2022

Open Access 01-12-2022 | Breast Cancer | Research article

Deep whole genome sequencing identifies recurrent genomic alterations in commonly used breast cancer cell lines and patient-derived xenograft models

Authors: Niantao Deng, Andre Minoche, Kate Harvey, Meng Li, Juliane Winkler, Andrei Goga, Alex Swarbrick

Published in: Breast Cancer Research | Issue 1/2022

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Abstract

Background

Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDXs) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions.

Results

Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60 × coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1, previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers.

Conclusions

Our WGS data provides a comprehensive genome sequencing resource of these models.
Appendix
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Metadata
Title
Deep whole genome sequencing identifies recurrent genomic alterations in commonly used breast cancer cell lines and patient-derived xenograft models
Authors
Niantao Deng
Andre Minoche
Kate Harvey
Meng Li
Juliane Winkler
Andrei Goga
Alex Swarbrick
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2022
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-022-01540-0

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