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Disease Models & Mechanisms
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Disease Models & Mechanisms
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Disease Models & Mechanisms
Article . 2021
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Engineering chromosome rearrangements in cancer

Authors: Salvador Alonso; Lukas E. Dow;

Engineering chromosome rearrangements in cancer

Abstract

ABSTRACT The identification of large chromosomal rearrangements in cancers has multiplied exponentially over the last decade. These complex and often rare genomic events have traditionally been challenging to study, in part owing to lack of tools that efficiently engineer disease-associated inversions, deletions and translocations in model systems. The emergence and refinement of genome editing technologies, such as CRISPR, have significantly expanded our ability to generate and interrogate chromosomal aberrations to better understand the networks that govern cancer growth. Here we review how existing technologies are employed to faithfully model cancer-associated chromosome rearrangements in the laboratory, with the ultimate goal of developing more accurate pre-clinical models of and therapeutic strategies for cancers driven by these genomic events.

Keywords

Chromosome Aberrations, Gene Editing, Gene Rearrangement, Genome, R, Review, Chromosomes, fusion oncogenes, Neoplasms, Pathology, cancer, Medicine, RB1-214, Humans, crispr, chromosomal rearrangements

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
Green
gold