Systems Genetics of DNA Damage Tolerance – Cisplatin, RAD5 & CRISPR-mediated Nonsense

Systems Genetics of DNA Damage Tolerance – Cisplatin, RAD5 & CRISPR-mediated Nonsense

About
DNA sequence information is constantly threatened by damage. In the clinic, intentional DNA damage is often used to treat cancer. Cisplatin, a first-line chemotherapy used to treat millions of patients, functions specifically by generating physical links within DNA strands, blocking DNA replication, and killing dividing cells. To maintain genome integrity, organisms have evolved the capacity to repair, respond, or otherwise resist change to the DNA sequence through a network of genetically encoded DNA damage tolerance pathways. In chapter 1, I present advances in experimental design and current progress for a systems genetics approach, using Saccharomyces cerevisiae, to reveal relationships between cisplatin tolerance pathways. Additionally, recent efforts to sequence thousands of cancer genomes have revealed recurrent genetic changes that cause overexpression of specific cisplatin tolerance genes. In chapter 2, I present a submitted manuscript that models overexpression of an essential cisplatin tolerance gene. This study uses a systems genetics approach to reveal the genetic pathways that are essential for tolerating this perturbation, which ultimately led to mechanistic insights for this gene. Convenient genome engineering in Saccharomyces has made this organism an ideal model to develop systems genetics concepts and approaches. In chapter 3, I present a published manuscript that demonstrates a new approach to disrupting genes by making site-specific nonsense mutations. Importantly, this approach does not require cytotoxic double-strand DNA breaks and is applicable to many model organisms for disrupting almost any gene, which may advance systems genetics into new model organisms. Systems genetics provides a framework for determining how DNA damage tolerance pathways act together to maintain cellular fitness and genome integrity. Such insights may one day help clinicians predict which cancers will respond to treatment, potentially sparing patients from unnecessary chemotherapy.

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