4.5 Article

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

期刊

BREAST CANCER RESEARCH
卷 24, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13058-022-01540-0

关键词

Breast cancer cell lines; Patient-derived xenografts; Whole genome sequencing; Structural variants; Non-coding mutations

类别

资金

  1. National Breast Cancer Foundation of Australia
  2. NHMRC
  3. EMBO long-term post-doctoral fellowship
  4. NIH [R01CA223817]
  5. CDMRP [W81XWH-18-1-0713]
  6. Mark Foundation
  7. Petre Foundation
  8. Estate of the late RT Hall, Deborah and John Mcmurtrie
  9. Love Your Sister Foundation

向作者/读者索取更多资源

In this study, deep whole genome sequencing was conducted on commonly used breast cancer cell lines and patient-derived xenograft models, leading to the identification of novel genomic alterations and features. This provides a comprehensive genome sequencing resource for these models.
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 similar to 60 x 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.

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