Epistasis and evolutionary dependencies in human cancers.

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State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_87AEECFCDB0B
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
Epistasis and evolutionary dependencies in human cancers.
Journal
Current opinion in genetics & development
Author(s)
Mina M., Iyer A., Ciriello G.
ISSN
1879-0380 (Electronic)
ISSN-L
0959-437X
Publication state
Published
Issued date
12/2022
Peer-reviewed
Oui
Volume
77
Pages
101989
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Abstract
Cancer evolution is driven by the concerted action of multiple molecular alterations, which emerge and are selected during tumor progression. An alteration is selected when it provides an advantage to the tumor cell. However, the advantage provided by a specific alteration depends on the tumor lineage, cell epigenetic state, and presence of additional alterations. In this case, we say that an evolutionary dependency exists between an alteration and what influences its selection. Epistatic interactions between altered genes lead to evolutionary dependencies (EDs), by favoring or vetoing specific combinations of events. Large-scale cancer genomics studies have discovered examples of such dependencies, and showed that they influence tumor progression, disease phenotypes, and therapeutic response. In the past decade, several algorithmic approaches have been proposed to infer EDs from large-scale genomics datasets. These methods adopt diverse strategies to address common challenges and shed new light on cancer evolutionary trajectories. Here, we review these efforts starting from a simple conceptualization of the problem, presenting the tackled and still unmet needs in the field, and discussing the implications of EDs in cancer biology and precision oncology.
Keywords
Humans, Epistasis, Genetic, Neoplasms/genetics, Precision Medicine, Genomics/methods, Phenotype
Pubmed
Web of science
Open Access
Yes
Create date
11/10/2022 12:31
Last modification date
19/07/2023 6:13
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