Journal article
Molecular Characterization of Non-responders to Chemotherapy in Serous Ovarian Cancer
International Journal of Molecular Sciences, Vol.20(5), p.1175
2019
DOI: 10.3390/ijms20051175
PMID: 30866519
Abstract
Nearly one-third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial treatment with platinum-based therapy. Genomic and clinical characterization of these patients may lead to potential alternative therapies. Here, the objective is to classify non-responders into subsets using clinical and molecular features. Using patients from The Cancer Genome Atlas (TCGA) dataset with platinum-resistant or platinum-refractory HGSC, we performed a genome-wide unsupervised cluster analysis that integrated clinical data, gene copy number variations, gene somatic mutations, and DNA promoter methylation. Pathway enrichment analysis was performed for each cluster to identify the targetable processes. Following the unsupervised cluster analysis, three distinct clusters of non-responders emerged. Cluster 1 had overrepresentation of the stage IV disease and suboptimal debulking, under-expression of miRNAs and mRNAs, hypomethylated DNA, “loss of function” TP53 mutations, and the overexpression of genes in the PDGFR pathway. Cluster 2 had low miRNA expression, generalized hypermethylation, MUC17 mutations, and significant activation of the HIF-1 signaling pathway. Cluster 3 had more optimally cytoreduced stage III patients, overexpression of miRNAs, mixed methylation patterns, and “gain of function” TP53 mutations. However, the survival for all clusters was similar. Integration of genomic and clinical data from patients that do not respond to chemotherapy has identified different subgroups or clusters. Pathway analysis further identified the potential alternative therapeutic targets for each cluster.
Details
- Title: Subtitle
- Molecular Characterization of Non-responders to Chemotherapy in Serous Ovarian Cancer
- Creators
- Megan E McDonald - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAErin A Salinas - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAEric J Devor - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAAndreea M Newtson - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAKristina W Thiel - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAMichael J Goodheart - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USADavid P Bender - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USABrian J Smith - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAKimberly K Leslie - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USAJesus Gonzalez-Bosquet - Department of biostatistics, University of Iowa College of Public Health, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- International Journal of Molecular Sciences, Vol.20(5), p.1175
- DOI
- 10.3390/ijms20051175
- PMID
- 30866519
- NLM abbreviation
- Int J Mol Sci
- ISSN
- 1661-6596
- eISSN
- 1422-0067
- Publisher
- MDPI
- Grant note
- DOI: 10.13039/100000009, name: National Institutes of Health, award: R01CA99908
- Language
- English
- Date published
- 2019
- Academic Unit
- Biostatistics; Obstetrics and Gynecology; Holden Comprehensive Cancer Center
- Record Identifier
- 9983930280502771
Metrics
20 Record Views