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J Integr Bioinform. 2017 Sep 23;14(3). pii: /j/jib.2017.14.issue-3/jib-2017-0027/jib-2017-0027.xml. doi: 10.1515/jib-2017-0027.

Computational Approaches to Identify Genetic Interactions for Cancer Therapeutics.

Abstract

The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Here we describe how genetic interactions are being therapeutically exploited to identify novel targeted treatments for cancer. We discuss the current methodologies that use 'omics data to identify genetic interactions, in particular focusing on synthetic sickness lethality (SSL) and synthetic dosage lethality (SDL). We describe the experimental and computational approaches undertaken both in humans and model organisms to identify these interactions. Finally we discuss some of the identified targets with licensed drugs, inhibitors in clinical trials or with compounds under development.

KEYWORDS:

genetic interactions; oncogene; synthetic dosage lethality; synthetic sickness lethality; tumour suppressor

PMID:
28941356
PMCID:
PMC6042820
DOI:
10.1515/jib-2017-0027
[Indexed for MEDLINE]
Free PMC Article

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