Evidence map›Paper›PMID 36153537›Full record

ArticleBreast cancer research : BCR2022

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

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

Open access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Omics-Based Investigations of Breast Cancer.Molecules (Basel, Switzerland) · 2023
    Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Niantao DengCancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, Australia.
Andre MinocheSchool of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia.
Kate HarveyCancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, Australia.
Meng LiDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA.
Juliane WinklerDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA.
Andrei GogaDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA.
Alex SwarbrickCancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, Australia. a.swarbrick@garvan.org.au.ORCID 0000-0002-3051-5676
Garvan Institute of Medical Research · AUUniversity of California, San Francisco · US

Funding

Uncovering Mechanisms of Regulation and Dependency on Fatty Acid Oxidation in MYC-Driven TumorsR01CA223817 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GOGA, ANDREI · 2018 to 2022
$1.8M
NCI NIH HHS R01 CA223817
6 · The paper itself

Abstract

backgroundBreast 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.

resultsHere 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.

conclusionsOur WGS data provides a comprehensive genome sequencing resource of these models.

Indexed as

Breast NeoplasmsAnimalsDisease Models, AnimalFemaleGenomicsHeterograftsHumansMCF-7 CellsNucleotidesWhole Genome SequencingNucleotidesBreast cancer cell linesNon-coding mutationsPatient-derived xenograftsStructural variantsWhole genome sequencing

Identifiers

PMID36153537
PMCPMC9509640
OpenAlexW4296954517

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.