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Candidate Markers of Olaparib Response from Genomic Data Analyses of Human Cancer Cell Lines
SIMPLE SUMMARY: Olaparib is an oral medication typically used to treat certain advanced ovarian and breast cancers with mutations in BRCA1 or BRCA2 genes. Mutations in these genes can increase the risk of developing breast, ovarian, and other types of cancer. Olaparib is the first clinically approve...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998846/ https://www.ncbi.nlm.nih.gov/pubmed/33803939 http://dx.doi.org/10.3390/cancers13061296 |
Sumario: | SIMPLE SUMMARY: Olaparib is an oral medication typically used to treat certain advanced ovarian and breast cancers with mutations in BRCA1 or BRCA2 genes. Mutations in these genes can increase the risk of developing breast, ovarian, and other types of cancer. Olaparib is the first clinically approved drug that specifically targets a vulnerability of cancers with these mutations. Genetic alterations in cancer tumors can affect response to treatment in cancer patients. Cancer models such as cell lines, which are cancer cells derived from patients and have been grown in the laboratory over time, can be used to identify these alterations which may contribute to sensitivity or resistance to treatment. We analyzed data from two independent groups of cancer cell lines and identified alterations in additional genes (PUM3, EEF1A1 and ELP4) that potentially increase sensitivity to olaparib. Further experimental and clinical investigations are required to validate our findings. ABSTRACT: The benefit of PARP inhibitor olaparib in relapsed and advanced high-grade serous ovarian carcinoma (HGSOC) is well established especially in BRCA1/2 mutation carriers. Identification of additional biomarkers can help expand the population of patients most likely to benefit from olaparib treatment. To identify candidate markers of olaparib response we analyzed genomic and in vitro olaparib response data from two independent groups of cancer cell lines. Using pan-cancer cell lines (n = 896) from the Genomics of Drug Sensitivity in Cancer database, we applied linear regression methods to identify statistically significant gene predictors of olaparib response based on mRNA expression. We then analyzed whole exome sequencing and mRNA gene expression data from our collection of 18 HGSOC cell lines previously classified as sensitive, intermediate, or resistant based on in vitro olaparib response for mutations, copy number variation and differential expression of candidate olaparib response genes. We identify genes previously associated with olaparib response (SLFN11, ABCB1), and discover novel candidate olaparib sensitivity genes with known functions including interaction with PARP1 (PUM3, EEF1A1) and involvement in homologous recombination DNA repair (ELP4). Further investigations at experimental and clinical levels are required to validate novel candidates, and ultimately determine their efficacy as potential biomarkers of olaparib sensitivity. |
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