Journal article
MUTYH as an Emerging Predictive Biomarker in Ovarian Cancer
Diagnostics (Basel), Vol.11(1), 84
01/06/2021
DOI: 10.3390/diagnostics11010084
PMCID: PMC7825630
PMID: 33419231
Abstract
Approximately 18% of ovarian cancers have an underlying genetic predisposition and many of the genetic alterations have become intervention and therapy targets. Although mutations in MutY homolog (MUTYH) are best known for MUTYH associated polyposis and colorectal cancer, it plays a role in the development of ovarian cancer. In this review, we discuss the function of the MUTYH gene, mutation epidemiology, and its mechanism for carcinogenesis. We additionally examine its emerging role in the development of ovarian cancer and how it may be used as a predictive and targetable biomarker. MUTYH mutations may confer the risk of ovarian cancer by the failure of its well-known base excision repair mechanism or by failure to induce cell death. Biallelic germline MUTYH mutations confer a 14% risk of ovarian cancer by age 70. A monoallelic germline mutation in conjunction with a somatic MUTYH mutation may also contribute to the development of ovarian cancer. Resistance to platinum-based chemotherapeutic agents may be seen in tumors with monoallelic mutations, but platinum sensitivity in the biallelic setting. As MUTYH is intimately associated with targetable molecular partners, therapeutic options for MUTYH driven ovarian cancers include programed-death 1/programed-death ligand-1 inhibitors and poly-adenosine diphosphate ribose polymerase inhibitors. Understanding the function of MUTYH and its associated partners is critical for determining screening, risk reduction, and therapeutic approaches for MUTYH-driven ovarian cancers.
Details
- Title: Subtitle
- MUTYH as an Emerging Predictive Biomarker in Ovarian Cancer
- Creators
- Megan L. Hutchcraft - Markey Cancer CenterHolly H. Gallion - Markey Cancer CenterJill M. Kolesar - University of Kentucky
- Resource Type
- Journal article
- Publication Details
- Diagnostics (Basel), Vol.11(1), 84
- Publisher
- Mdpi
- DOI
- 10.3390/diagnostics11010084
- PMID
- 33419231
- PMCID
- PMC7825630
- ISSN
- 2075-4418
- eISSN
- 2075-4418
- Number of pages
- 13
- Language
- English
- Date published
- 01/06/2021
- Academic Unit
- Pharmacy; Pharmaceutical Sciences and Experimental Therapeutics
- Record Identifier
- 9984695784702771
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