
Experimental identification of cancer driver alterations in the era of pan‐cancer genomics
Author(s) -
Korenjak Michael,
Zavadil Jiri
Publication year - 2019
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/cas.14210
Subject(s) - cancer , computational biology , genomics , cancer cell , somatic cell , synthetic lethality , functional genomics , biology , gene knockout , bioinformatics , computer science , gene , genetics , genome , dna repair
Rapidly accumulating data from large‐scale cancer genomics studies have been generating important information about genes and their somatic alterations underlying cell transformation, cancer onset and tumor progression. However, these events are usually defined by using computational techniques, whereas the understanding of their actual functional roles and impact typically warrants validation by experimental means. Critical information has been obtained from targeted genetic perturbation (gene knockout) studies conducted in animals, yet these investigations are cost‐prohibitive and time‐consuming. In addition, the 3R principles (replacement, reduction, refinement) have been set in place to reduce animal use burden and are increasingly observed in many areas of biomedical research. Consequently, the focus has shifted to new designs of innovative cell‐based experimental models of cell immortalization and transformation in which the critical cancer driver events can be introduced by mutagenic insult and studied functionally, at the level of critical phenotypic readouts. From these efforts, primary cell‐based selective barrier‐bypass models of cell immortalization have emerged as an attractive system that allows studies of the functional relevance of acquired mutations as well as their role as candidate cancer driver events. In this review, we provide an overview of various experimental systems linking carcinogen exposure‐driven cell transformation with the study of cancer driver events. We further describe the advantages and disadvantages of the currently available cell‐based models while outlining future directions for in vitro modeling and functional testing of cancer driver events.